1. bookVolume 1 (2010): Issue 1 (January 2010)
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Impedance cardiography: Pulsatile blood flow and the biophysical and electrodynamic basis for the stroke volume equations

Published Online: 03 Dec 2009
Volume & Issue: Volume 1 (2010) - Issue 1 (January 2010)
Page range: 2 - 17
Received: 25 Nov 2009
Journal Details
License
Format
Journal
eISSN
1891-5469
First Published
01 Jan 2010
Publication timeframe
1 time per year
Languages
English
Abstract

Impedance cardiography (ICG) is a branch of bioimpedance primarily concerned with the determination of left ventricular stroke volume (SV). As implemented, using the transthoracic approach, the technique involves applying a current field longitudinally across a segment of thorax by means of a constant magnitude, high frequency, low amplitude alternating current (AC). By Ohm’s Law, the voltage difference measured within the current field is proportional to the electrical impedance Z (Ω). Without ventilatory or cardiac activity, Z is known as the transthoracic, static base impedance Z0. Upon ventricular ejection, a characteristic time dependent cardiac-synchronous pulsatile impedance change is obtained, ΔZ(t), which, when placed electrically in parallel with Z0, constitutes the time-variable total transthoracic impedance Z(t). ΔZ(t) represents a dual-element composite waveform, which comprises both the radially-oriented volumetric expansion of and axially-directed forward blood flow within both great thoracic arteries. In its majority, however, ΔZ(t) is known to primarily emanate from the ascending aorta. Conceptually, commonly implemented methods assume a volumetric origin for the peak systolic upslope of ΔZ(t), (i.e. dZ/dtmax), with the presumed units of Ω·s–1. A recently introduced method assumes the rapid ejection of forward flowing blood in earliest systole causes significant changes in the velocity-induced blood resistivity variation (Δρb(t), Ωcm·s–1), and it is the peak rate of change of the blood resistivity variation dρb(t)/dtmax (Ωcm·s–2) that is the origin of dZ/dtmax. As a consequence of dZ/dtmax peaking in the time domain of peak aortic blood acceleration, dv/dtmax (cm·s–2), it is suggested that dZ/dtmax is an ohmic mean acceleration analog (Ω·s–2) and not a mean flow or velocity surrogate as generally assumed. As conceptualized, the normalized value, dZ/dtmax/Z0, is a dimensionless ohmic mean acceleration equivalent (s–2), and more precisely, the electrodynamic equivalent of peak aortic reduced average blood acceleration (PARABA, d<v>/dtmax/R, s–2). As necessary for stroke volume calculation, dZ/dtmax/Z0 must undergo square root transformation to yield an ohmic mean flow velocity equivalent. To compute SV, the square root of the dimensionless ohmic mean acceleration equivalent ([dZ/dtmax/Z0]0.5, s–1) is multiplied by a volume of electrically participating thoracic tissue (VEPT, mL) and left ventricular ejection time (TLVE, s). To find the bulk volume of the thoracic contents (i.e. VEPT), established methods implement exponential functions of measured thoracic length (L(cm)n) or height-based thoracic length equivalents (0.01×%H(cm)n). The new method conceptualizes VEPT as the intrathoracic blood volume (ITBV, mL), which is approximated through allometric equivalents of body mass (aMb). In contrast to the classical two-element parallel conduction model, the new method comprises a three-compartment model, which incorporates excess extra-vascular lung water (EVLW) as a component of both Z0 and VEPT. To fully appreciate the evolution and analytical justification for impedance-derived SV equations, a review of the basics of pulsatile blood flow is in order.

Keywords

Pulsatile Blood Flow

Stroke volume (SV) is defined as that quantity of blood ejected from the cardiac ventricles for each heart beat. More specifically, it relates to the volume of blood ejected from opening to closure of the semilunar valves, and in the case of the left ventricle, the aortic valve. The time interval over which left ventricular ejection occurs is known as left ventricular ejection time (TLVE, s). For purposes of simplicity, and considering this is not an in-depth analytical treatise on pulsatile blood flow, per se, the following simplistic model is proposed as an operational tool for understanding the opposing hypotheses concerning SV determination by means of the transthoracic electrical bioimpedance technique (TEB).

In geometric terms, consider stroke volume V (mL) a cylinder of length S (cm) and cross-sectional area πr2 (CSA, cm2). In this model it is assumed that SV is surrounded by a thin-walled viscoelastic aorta, equal in length S to the SV contained within at end-systole. Hemodynamically, as a function of ventricular ejection, let S (cm) also represent the time velocity integral, also known as stroke distance (cm).

V=πr2SmL$$V=\pi {{r}^{2}}S\,\,\,\,\,\left( \text{mL} \right)$$

If the dependent variable, V, and independent variables r and S are continuously differentiable functions of time t, the rate of change of aortic volume dV/dt or flow Q(t) (mL·s–1) is given as,

dVtdt=Q˙=2πrdrtdtS+πr2dStdtmLs1$$\frac{dV\left( t \right)}{dt}=\dot{Q}=2\pi r\frac{dr\left( t \right)}{dt}S+\pi {{r}^{2}}\frac{dS\left( t \right)}{dt}\left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

If 2πrS (circumference × length) is the internal surface area AISA (cm2) of an ascending aortic segment and dr(t)/dt aortic wall velocity (cm·s–1), then (i.e. Q(t)) in derivative 1 equals

NB: Q(t) in lieu of Q˙$\dot{Q}$will be used within the body of the text. Whereas Q is the physiologic symbol for volume, Q(t) connotes volume changing with time, which is flow.

,

Q˙=AISA×vWallmLs1$$\dot{Q}={{A}_{ISA}}\times {{v}_{Wall}}\left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

For derivative 2, if πr2 is the CSA of the aorta at a discreet point of measurement and dS(t)/dt the axial blood velocity (v, cm·s–1) measured at that point, then axial Q can be given as,

Q˙=ACSA×vBloodmLs1$$\dot{Q}={{A}_{CSA}}\times {{v}_{Blood}}\left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

Inasmuch as ACSA changes continuously over the cardiac cycle as a function of aortic valve radius dr, the following is an animated representation of derivative 2 of equation 2 and equation 4 [1].

Q˙=0R2πrdAdrv=0R2πrdrvmLs1$$\dot{Q}=\int_{0}^{R}{2\pi r\frac{dA}{dr}v=}\int_{0}^{R}{2\pi rdrv\,}\ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

At an operational level, derivative 2 of equation 2 and equations 4 and 5 represent the basis for SV determination by means of both the Doppler/echo method and electromagnetic flowmetry. To find SV simply requires integration of the velocity profile over the ejection period at a discreet point in the aortic root and multiplying this by the aortic root CSA at the point of velocity measurement. Common sites for measurement include the left ventricular outflow tract and aortic valve leaflets. Thus,

SV=πr2t0t1vtdt=πr2×v×tLVE=πr2SmL$$SV=\pi {{r}^{2}}\int_{{{t}_{0}}}^{{{t}_{1}}}{v\left( t \right)dt=\pi {{r}^{2}}\times {v}\times {{t}_{LVE}}=\pi {{r}^{2}}S}\ \ \left( \text{mL} \right)$$

where Vv is the mean velocity during ejection and the interval t0 to t1, TLVE. Extrapolating derivative 1 of equation 2 and equation 3 for determination of SV is something very much more complex, for it represents the geometric foundation of the windkessel model for SV determination [1]. For this model of pulsatile blood flow, it is assumed that the proximal aorta acts as a compliance chamber C and the distal vasculature a static resistance, Rs. Upon the force of ventricular ejection in early systole, and because of distal vascular hindrance, the proximal aorta expands, storing a part of the inflow (Q(t)in) as potential energy (Q(t)stored). Simultaneously, due to open outflow, blood is expelled axially (Q(t)out) to the periphery, where Q(t)out is commonly referred to as “runoff”. When aortic pressure exceeds left ventricular pressure from mid-systole to aortic valve closure, the recoiling aorta converts potential energy to kinetic energy, expelling the stored blood to the periphery. From aortic valve closure (end-systole) to end-diastole, non-pulsatile flow dissipates along a quasi-mono-exponential pressure decay. Pulsatile blood flow is therefore buffered and converted from periodic oscillating flow to near-continuous flow for each cardiac cycle [2]. It is this aforementioned physical phenomenon that is the basis for conceptualization of the plethysmographic-based ICG-derived SV equations, and the mechanics underlying the windkessel model for pulsatile blood flow. Referring to derivative 1 of equation 2, if 2πrdr / dt equals dA / dt (time-rate of change of aortic area, cm2·s–1), then Q(t) for derivative 1 can be given as,

Q˙=dAdtS=dVtdtmLs1$$\dot{Q}=\frac{dA}{dt}S=\frac{dV\left( t \right)}{dt}\ \ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

In terms of mechanics, since dA(t) and dA(t)/dt are non-linear functions of vessel material composition, pressure P(t) (mmHg) and rate of change of aortic pressure dP(t)/dt (mmHg·s–1), respectively, the following pertains [3]:

dVtdt=CdPtdtmLs1$$\frac{dV\left( t \right)}{dt}=C\frac{dP\left( t \right)}{dt}\ \ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

where the right hand side (rhs) of equation 8 defines the magnitude and shape of the flow wave, and C is the aortic compliance.

If aortic dP(t) is a function of force F and area A, both changing with time over the ejection interval, dP(t) (mmHg) and dP(t)/dt (mmHg ⋅ s–1) are given as,

dPtaorta=dFtdAtdPtaortadt=1AdFtdtFA2dAtdt$$dP{{\left( t \right)}_{aorta}}=\frac{dF\left( t \right)}{dA\left( t \right)}\Rightarrow \frac{dP{{\left( t \right)}_{aorta}}}{dt}=\frac{1}{A}\frac{dF\left( t \right)}{dt}-\frac{F}{{{A}^{2}}}\frac{dA\left( t \right)}{dt}\,$$

respectively, and compliance C is given as,

C=dAdPS=dVdPmLmmHg1$$C=\frac{dA}{dP}S=\frac{dV}{dP}\ \ \ \ \ \ \left( \text{mL}\cdot \text{mmH}{{\text{g}}^{-1}} \right)$$

where dA/dP is a non-linear function of Pulse pressure (ΔP) and mean distending pressure Pm. Thus,

dVtdt=dAPdPSdPtdt=dAPdPS1AdFtdtFA2dAtdt=CAdFtdtCFA2dAtdtmLs1$$\begin{align}& \frac{dV\left( t \right)}{dt}=\frac{dA\left( P \right)}{dP}S\frac{dP\left( t \right)}{dt}=\frac{dA\left( P \right)}{dP}S\left( \frac{1}{A}\frac{dF\left( t \right)}{dt}-\frac{F}{{{A}^{2}}}\frac{dA\left( t \right)}{dt} \right)= \\ & \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \ \frac{C}{A}\frac{dF\left( t \right)}{dt}-\frac{CF}{{{A}^{2}}}\frac{dA\left( t \right)}{dt}\ \ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right) \\ \end{align}$$

where the mechanical expression for dV/dt of equation 11 is equivalent to the geometrical definition for dV/dt of derivative 1 in equation 2. As an analytical expansion of equation 8, the rhs of equation 11 more precisely defines the temporal landmarks, shape and magnitude of the radially oriented flow wave.

Figure 1 shows the pressure curve P(t), the rate of change of aortic pressure, dP/dt, aortic blood flow (Q(t)) and the rate of change of flow, which is acceleration of flow, dQ(t)/dt. It is clear from equation 11 that dF/dtmax, the major derivative, will occur early in systole, when dA/dt is trivial. Likewise, dA/dtmax will occur when dF/dt = 0. When dP/dt is modulated by C, dA/dtmax will occur at the peak magnitude of the flow wave dV/dtmax (i.e. Qmax) and dF/dtmax will occur on the steepest portion of the flow wave, immediately following aortic valve opening in early systole.

Fig. 1

ECG, aortic pressure, aortic blood flow Q, aortic rate of change of pressure dP/dt, and rate of change of flow, which is acceleration dQ/dt. From a canine model In: Li J-K. The arterial circulation: physical principles and clinical applications. Totowa, NJ: Humana Press; 2000, p. 78.

When flow is differentiated with respect to time dQ/dtmax will occur when dA/dt and dV/dt are minimal. Also apparent is that when flow acceleration = 0, dV/dt is at maximum. Therefore, dQ(t)/dtmax and dV/dtmax are monotonically restricted to their respective time-domains, with acceleration of blood flow, dQ/dtmax peaking, on the mean, approximately 50ms before peak flow, dV/dtmax.

If S is a segment of aorta with closed outflow, then flow into the segment would be the total input flow from left ventricular ejection. If, however, segment S is an open outflow conduit, equation 8 would represent a net flow. For a simple 2-element windkessel model, net flow into the segment (Q(t)in) is given as [4],

Q˙innet=CdPtdtPtRsmLs1$${{\dot{Q}}_{in-net}}=C\frac{dP\left( t \right)}{dt}-\frac{P\left( t \right)}{{{R}_{s}}}\ \ \ \ \ \ \ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

where derivatives 1 and 2 on the rhs of (12) represent Q(t)stored and Q(t)out, respectively.

To obtain total flow Q(t)total through the segment over a single systolic interval (TLVE, s), Q(t)out must be measured. With regard to a two-element windkessel model, Q(t)out is obtained by dividing the pressure change over the ejection interval P(t) by the distal, or systemic vascular resistance, Rs. Rs is defined as the quotient of mean pressure to mean flow Pm/Qm. Q(t)total is thus given as [4],

Q˙intotal=CdPtdt+PtRsmLs1$${{\dot{Q}}_{in-total}}=C\frac{dP\left( t \right)}{dt}+\frac{P\left( t \right)}{{{R}_{s}}}\ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

Integration of Q(t)strored yields stored volume inflow, SVstored:

SVstored=Ct0t1dPtdtdt=CΔPmL$$S{{V}_{stored}}=C\int_{{{t}_{0}}}^{{{t}_{1}}}{\frac{dP\left( t \right)}{dt}}dt=C\Delta P\,\,\,\,\left( \text{mL} \right)$$

where ΔP is the pulse pressure, which is aortic peak systolic pressure Ps minus aortic diastolic pressure Pd (Ps–Pd) [5].

Since SV = CΔP, where C is a non-constant time variable function of pressure P, the following expression also represents total flow into a segment of aorta of length S and internal surface area wall velocity dA/dt [6].

Q˙in=CdPtdt+PdCptdtmLs1$${{\dot{Q}}_{in}}=C\frac{dP\left( t \right)}{dt}+P\frac{d{{C}_{p}}\left( t \right)}{dt}\,\,\,\,\left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

where derivatives 1 and 2 represent Q(t)stored and Q(t)out, respectively. Differentiating dCp(t)/dt results in,

dCptdt=dΔVΔPdt=1PdVdtVP2dPdt$$\frac{d{{C}_{p}}\left( t \right)}{dt}=\frac{d\left( \frac{\Delta V}{\Delta P} \right)}{dt}=\frac{1}{P}\frac{dV}{dt}-\frac{V}{{{P}^{2}}}\frac{dP}{dt}$$

In terms of total flow into segment S, equations 12 and 15 are equivalent. Integration of equation 13 over an ejection interval yields SV and is thus given as [2],

SV=t0t1Q˙tdt=Ct0t1dPtdtdt+1Rst0t1Ptdt$$SV=\int_{{{t}_{0}}}^{{{t}_{1}}}{\dot{Q}\left( t \right)dt=C\int_{{{t}_{0}}}^{{{t}_{1}}}{\frac{dP\left( t \right)}{dt}dt+\frac{1}{{{R}_{s}}}\int_{{{t}_{0}}}^{{{t}_{1}}}{P\left( t \right)dt}}}$$

where equation 17 represents a two-element windkessel model. Derivatives 1 and 2 on the rhs equation 17 represent Vstored and Vout, respectively.

Although a theoretically correct model for SV, equation 17 is not easily solved. Clearly, P(t), dP(t)/dt, and Pm can be computed by direct measurement and signal processing, but C and Rs must be obtained independently by alternative means [2]. This is clear from equation 10 for the determination of C and the relationship of Rs to Q(t)mean in equation 17. From equations 15 and 16, it is also clear that C is not a constant as equation 17 implies. Pressure dependent C and the rate of change of C with respect to time, dC/dt, are not accounted for in equation 17. To more accurately predict SV from the windkessel model, it is necessary to incorporate the transverse frequency-dependent pulsatile resistance, also known as mechanical or characteristic aortic input impedance, Zc. Zc is approximated by aortic pulse pressure divided by peak aortic blood flow (ΔP/Qmax). Incorporating characteristic aortic impedance into the windkessel model, which constitutes the three-element model, is now considered the “gold-standard” [4]. Thus, as an approximate unifying statement for SV from equations 5, 6 and 17:

SV=0R2πrdrt0t1vtdt=πr2SCt0t`dPtdtdt+1Rs(mL)t0t1Ptdt$$\begin{align}& SV=\int_{0}^{R}{2\pi }rdr\int_{{{t}_{0}}}^{{{t}_{1}}}{v\left( t \right)dt=\pi {{r}^{2}}S\cong C\int_{{{t}_{0}}}^{t\grave{\ }}{\frac{dP\left( t \right)}{dt}dt+\mathop{\frac{1}{{{R}_{s}}}}_{( \text{mL})}\int_{{{t}_{0}}}^{{{t}_{1}}}{P\left( t \right)dt}}} \end{align}$$
Impedance Cardiography
Modeling the transthoracic impedance Z(t)

Impedance cardiography (ICG) is a branch of bioimpedance primarily concerned with the determination of left ventricular stroke volume (SV) [710]. It was the first and still the only truly noninvasive, continuous, operator-independent, hands-off, beat-to-beat method used in clinical practice. Despite these desirable attributes, general acceptance of the method as a replacement for invasive reference standards in critically-ill humans has not been realized. As summarized by Raaijmakers et al. and Moshkovitz et al., both correlation and agreement against standard reference methods have been far too variable to reliably apply the method clinically for modulation of patient therapy [7,12]. As emphasized by Kauppinen et al. [11], the major problem in cardiovascular impedance measurements is the inability to accurately correlate the magnitude of the impedance waveforms to the hemodynamic variables they pretend to mimic. The lack of consistently high correlation and agreement between ICG measurements and reference standards would suggest that, the equation models describing SV in ICG are not sufficiently robust and the physical acquisition of the impedance signals not sensitive and specific enough for clinical application in the critically ill [11].

While measurements can be obtained by the whole body technique, the method is usually implemented by means of the transthoracic approach (i.e. transthoracic electrical bioimpedance cardiography, TEB, ICG) [7]. The latter technique, and subject of this review, involves applying a current field longitudinally across a segment L (cm) of thorax by means of a constant magnitude, high frequency (50–100 kHz), low amplitude AC (I(t)) (1–4 mA). By Ohm’s Law, the voltage difference U(t) (volt, U) measured within the current field is proportional to the transthoracic electrical impedance Z.

UtIt=ZΩ$$\frac{U\left( t \right)}{I\left( t \right)}=Z\ \ \ \left( \Omega \right)$$

where Z is the frequency-dependent AC analog of the static DC resistance R. The magnitude of the impedance, or modulus, │Z│, comprises a resistive component, also known as the real part, R, and an imaginary part X. X is further comprised of an inductive part (XL) and capacitive part (XC), both collectively known as the reactance. With regard to the magnitude of X, XL is proportional and XC inversely proportional (1/f) to the frequency of the applied AC. │Z│ is determined by the geometric addition of the resistive and reactive components.

Z=R2+XLXC2$$\left| Z \right|=\sqrt{{{R}^{2}}+{{\left( {{X}_{L}}-{{X}_{C}} \right)}^{2}}}$$

where the reactance X is,

X=XLXC$$X=\left( {{X}_{L}}-{{X}_{C}} \right)$$

Thus,

Z=R2+X2$$\left| Z \right|=\sqrt{{{R}^{2}}+{{X}^{2}}}$$

where the magnitudes of R and X on Cartesian coordinates are determined by the phase angle φ, and thus, R tan φ = X.

For the remainder of the discussion, let |Z| = Z.

For cylindrical electrical conductors, and as a companion equation to equation 19 [13],

Z=ρLAρL2VΩ$$Z=\frac{\rho L}{A}\equiv \frac{\rho {{L}^{2}}}{V}\ \ \ \left( \Omega \right)$$

where ρ = the resistivity (Ω ⋅ cm), L = the length of the conductor, and A and V are the CSA (cm2) and volume (mL) of the conductor, respectively. Thus, substituting ρL2/V in equation 23 for Z in equation (19) and rearranging,

For the remainder of the discussion, the character “U” is used in lieu of “v” for volt, so as not to confuse v with velocity “v” or volume “V”.

ItρL2V=UtU$$I\left( t \right)\cdot \frac{\rho {{L}^{2}}}{V}=U\left( t \right)\ \ \ \left( U \right)$$

If the thorax is considered a cylindrical bulk electrical conductor of length L between the voltage sensing electrodes, with ρT the transthoracic specific resistance and VT the volume of thorax, then, without ventilatory or cardiac activity, Z in equations 19 and 23 represents the adynamic or static transthoracic base impedance Z0. When cardiac and ventilatory activity are superimposed on Z0, a time-variable transthoracic impedance is registered, Z(t). By eliminating the oscillating cardiac-asynchronous ventilatory component ΔZvent, Z(t) comprises, in parallel, a static DC component Z0 (22Ω–45Ω) and a dynamic AC component ΔZ(t) (0.1Ω–0.2Ω) [14,15] (Fig.2). It should be noted that the magnitude of Z0 not only varies between individuals and the frequency of the applied AC, but also with the electrode configuration used for signal acquisition. For four common electrode configurations a computer model predicts a Z0 range of 26.3Ω–34.3Ω [11].

Fig. 2

Schematic of a multi-compartmental parallel conduction model of the thorax. The transthoracic electrical impedance Z(t) to an applied AC field represents the parallel connection of a quasi-static base impedance Z0 and a time-dependent component of the blood impedance, ΔZb(t). Z0 represents the parallel connection of all static tissue impedances, Zt, and the static component of the blood resistance, Zb. Ze represents the quasi-static EVLW compartment. A voltmeter (U) and AC generator (~) are shown. From reference 37.

When electrical resistances or impedances are added in parallel, they are summed as their reciprocals.

Zt=Z0ΔZt=1Zt=1Z0+1ΔZt$$Z\left( t \right)=\left. {{Z}_{0}} \right\|\Delta Z\left( t \right)=\frac{1}{Z\left( t \right)}=\frac{1}{{{Z}_{0}}}+\frac{1}{\Delta Z\left( t \right)}$$

As a composite impedance with tissues of widely varying specific resistances, Z0 comprises, in parallel, a static, relatively non-conductive multi-compartmental tissue impedance Zt (400Ω·cm–1020Ω·cm) [11,16], a highly conductive blood impedance Zb (or resistance Rb 100Ω·cm–180Ω·cm) varying with hematocrit [17], and a very highly conductive interstitial extra-vascular lung water (EVLW) impedance Ze (60Ω·cm–70Ω·cm).

Z0 is thus an intensity weighted mean of the reciprocal sum of all thoracic tissue impedances, the sum of the reciprocals being less than the lowest tissue impedance of the thorax.

Z0=ZtZbZe=1Z0=1Zt+1Zb+1Ze$${{Z}_{0}}=\left. {{Z}_{t}} \right\|\left. {{Z}_{b}} \right\|{{Z}_{e}}=\frac{1}{{{Z}_{0}}}=\frac{1}{{{Z}_{t}}}+\frac{1}{{{Z}_{b}}}+\frac{1}{{{Z}_{e}}}$$

In this model, the blood resistance Rb is considered a cylindrical tube of constant length L, surrounded by the highly conductive extravascular lung water impedance Ze and both surrounded by a non-conductive thoracic encompassing cylinder Zt. It should be noted that, at the frequencies used in ICG, blood is almost purely resistive with a trivial reactive component. Therefore, the term blood resistance, Rb, is justifiably used in lieu of blood impedance Zb.

ΔZb(t): The Transthoracic Cardiogenic Impedance Pulse Variation
The velocity and volume components

The systolic portion of the cardiogenically-induced impedance pulse variation ΔZ(t), hereafter known as ΔZb(t), comprises two components, arguably of equal magnitude [14,1821]. The first is a velocity-induced change in the specific resistance of axially directed flowing blood (Δρb(t), Ω·cm·s–1), where, in end-diastole, the state of highest blood resistivity, red blood cells are randomly oriented. By contrast, during peak aortic blood acceleration and the rapid ejection phase of early systole, red blood cells become deformed and assume a well defined state of parallel orientation along their long axis of symmetry [19,22,23] (fig. 3).

Fig. 3

Behavior of AC as applied to pulsatile blood flow. → = AC flow. v = red cell velocity; Δρb(t) = changing specific resistance of flowing blood.; Qin = flow into aortic segment; Qout = simultaneous flow out of aortic segment; dA(t) = time-dependent change in aortic CSA. From reference 13.

Parallel alignment opens clear current pathways through the highly conductive plasma, causing a decrease in blood resistivity and transthoracic resistivity [19,22] (i.e.↑Conductivity). The rapidity of and degree to which attainment of complete parallel orientation is achieved determines the magnitude of the resistivity change Δρb(t)max (Ω·cm·s–1) [23]. The maximum resistivity change occurs when the long axis of the red cell is oriented within 200 to the direction of blood flow [23]. Figure 4 shows that, in early ejection, maximum acceleration of red cell reduced average velocity (i.e. mean spatial velocity) parallels the change in blood resistivity (i.e. conductivity) (r = 0.99). By comparison, upon negative acceleration, the resistivity change does not parallel the reduced average velocity, with subsequent delay in reaching baseline [19,23]. This disparity is, no doubt, a consequence of the red cells’ inability to achieve complete randomization at end-systole.

Fig. 4

Absolute spatial average velocity (i.e. reduced average velocity <v>/R, s–1) vs. conductivity change in an in vitro pulsatile ejection model over one cardiac cycle. Note that, upon red cell acceleration in early ejection, the peak rate of change of the reduced average velocity parallels the peak rate of change of conductivity (r = 0.99). From reference 23.

The second component generating a change in transthoracic specific resistance is the transversely or laterally-oriented volume displacement of non-conductive alveolar gas (ρ =1020 Ω·cm) by stroke volume-induced expansion of the ascending aorta, principally [24,25], with highly conductive blood (ρb=100–180 Ω·cm) ΔVb(t) (ΔΩ·cm(t)). As discussed under pulsatile blood flow, in addition to distal vascular hindrance Rs, the volumetric expansion of the aorta is due to pressure-induced, compliance modulated changes in cross sectional area, πr2 (cm2), and, over segment L, a change in internal surface area, 2π·(dA/dr)L, (cm2) [1,26]. For example, assume that equation 23 represents the impedance Z of a segment of very thin walled aorta embedded within the thorax. Assume that the aortic segment is of length L with open outflow, the content of which is blood of static specific resistance ρb and volume Vb. Thus, an increase in aortic volume ΔVb(t) would result in a corresponding decrease in vessel and transthoracic impedance ΔZb(t)volume.

ΔZbtvolume=ρbL2ΔVbtΔΩtΔVbt=ρbL2ΔZbtΔvolumet$$\begin{align}& \downarrow \Delta {{Z}_{b}}{{\left( t \right)}_{volume}}=\frac{{{\rho }_{b}}{{L}^{2}}}{\uparrow \Delta {{V}_{b}}\left( t \right)}\left( \Delta \Omega \left( t \right) \right) \\ & \Rightarrow \uparrow \Delta {{V}_{b}}\left( t \right)=\frac{{{\rho }_{b}}{{L}^{2}}}{\downarrow \Delta {{Z}_{b}}\left( t \right)}\ \ \ \ \left( \Delta \text{volume}\left( \text{t} \right) \right) \\ \end{align}$$

where the rhs of equation 27 is the ohmic equivalent of equation 14, wherein ΔZb(t) and ΔVb(t) represent net changes. The combined velocity and volume effects cause a steep drop in transthoracic impedance.

For the velocity-induced change in blood resistivity, the decrease in vessel and transthoracic impedance is given as,

ΔZbtvelocity=ΔρbL2VbΩs1$$\Delta {{Z}_{b}}{{\left( t \right)}_{velocity}}=\frac{\Delta {{\rho }_{b}}{{L}^{2}}}{{{V}_{b}}}\,\ \ \ \ \ \left( \Omega \cdot {{\text{s}}^{-1}} \right)$$

where Δρb(t) is of diminishing value upon ejection. Combining equations 27 and 28,

ΔZbt=ΔρbtL2Vb+ρbL2ΔVbt=ΔZbtvelocity+ΔZbtvolume$$\Delta {{Z}_{b}}\left( t \right)=\frac{\Delta {{\rho }_{b}}\left( t \right){{L}^{2}}}{{{V}_{b}}}+\frac{{{\rho }_{b}}{{L}^{2}}}{\Delta {{V}_{b}}\left( t \right)}=\Delta {{Z}_{b}}{{\left( t \right)}_{velocity}}+\Delta {{Z}_{b}}{{\left( t \right)}_{volume}}$$

Combining equations 24, 26, and 29, the following impedance model describes the static and dynamic impedances in parallel, when an AC field is applied longitudinally across the thorax (fig 2).

ItZtZbZeΔZbtvelocity+ΔZbtvolume=U0ΔUbt$$I\left( t \right)\left[ \left. \left( \left\| {{Z}_{t}} \right.\left\| {{Z}_{b}} \right.\left\| {{Z}_{e}} \right. \right) \right\|\left( \Delta {{Z}_{b}}{{\left( t \right)}_{velocity}}+\Delta {{Z}_{b}}{{\left( t \right)}_{volume}} \right) \right]=\left. {{U}_{0}} \right\|\Delta {{U}_{b}}\left( t \right)$$
Stroke Volume Equations
Nyboer equations: Foundation and Rationale for the Plethysmographic Hypothesis and Parallel Conduction Model in Impedance Cardiography

The original Nyboer equation [27] was specifically proposed for determination of segmental blood volume changes in the upper and lower extremities. It is based upon the assumption that the arteries of the extremities are rigidly encased in muscle and connective tissue, and that both the arteries and surrounding tissue can be approximated as cylindrical conductors placed in parallel alignment. Nyboer found that, by placing spaced-apart circumferential current injecting electrodes on a limb segment and voltage sensing electrodes within the current field proximate the current injectors, impedance changes proportional to strain gauge determined blood volume changes could be measured. He also determined that, in order to compensate for simultaneous volume outflow from the limb segment during arterial inflow, venous outflow occlusion was necessary. Thus, the ΔZb(t) waveform represents the sum of two signals: one caused by inflow and the other caused by outflow (runoff) between the voltage sensing electrodes [28]. Using venous outflow obstruction, absolute volume changes during each pressure pulse were accurately approximated. Nyboer referred to this method, and quite accurately as, electrical impedance plethysmography. The foundation of Nyboer’s equation, and for that matter the earliest SV equations, originate from equation 27, where, when solving for ΔVb(t)net,

ΔVbtnet=ρbL2ΔZbtnetmL$$\Delta V_b{\left(t\right)}_{net}=\frac{\rho_bL^2}{\Delta Z_b{\left(t\right)}_{net}}\;\;\;\;\left(\text{mL}\right)$$

However, since a large extremity artery (i.e. brachial or femoral) is encased in muscle and connective tissue, ΔZb(t) had to be further refined, reflecting a parallel connection of the static tissue and dynamic blood impedances. Since the magnitude of Z(t) of an extremity is larger than extremity Z0 by a trivial factor of extremity ΔZb(t), the approximation that extremity Z(t) and Z0 are virtually identical is a plausible assumption. Without assumption, it also follows that Z(t)–Z0 = ΔZb(t). Thus, if equation 25 is solved for ΔZb(t), using the reciprocal rule for impedances added in parallel:

ΔZbt=Z0ZtZ0ZtZ02ΔZbtΩt$$\Delta {{Z}_{b}}\left( t \right)=\frac{{{Z}_{0}}\cdot Z\left( t \right)}{{{Z}_{0}}-Z\left( t \right)}\cong \frac{Z_{0}^{2}}{-\Delta {{Z}_{b}}\left( t \right)}\ \ \ \ \ \left( \Omega \left( t \right) \right)$$

Substituting the right hand side of equation 32 for ΔZb(t) into equation 31 results in the operational model for measurement of blood volume changes in an extremity. For the maximum volume change ΔVb(max) with venous outflow occlusion [28],

ΔVbmax=ρbL2Z02ΔZmaxmL$$\Delta {{V}_{b\left( \max \right)}}=-\frac{{{\rho }_{b}}{{L}^{2}}}{Z_{0}^{2}}\Delta {{Z}_{\max }}\ \ \ \ \left( \text{mL} \right)$$

where ΔZmax is the peak magnitude of the waveform and ρbL2/Z02 is a constant. For an arterial conduit with closed outflow, equation 33 is the bioelectric equivalent of the hemodynamic expression given for SV in equation 14 with outflow obstruction. For an extremity vessel with open outflow, equation 33 is analogous to the integrated value for equation 12. Clearly, as applied to SV calculations, equation 33 is inadequate, because complete aortic outflow obstruction for calculation of total SV is impossible.

Stroke Volume Calculation
Nyboer’s method: Maximum Systolic Down-slope Backward Extrapolation of ΔZb(t)

As applied to thoracic measurements of SV, Nyboer professed to have solved the outflow problem by manually determining the maximum systolic down-slope of ΔZb(t) and extrapolating it backward to the beginning of ejection [28]. Thus, the maximum impedance change resulting from the backward extrapolation method was believed to be equivalent to the maximum impedance change attained as if no arterial runoff occurred during ejection.

Thus, SV, or the maximum volume change ΔVb measured between the voltage sensing electrodes is given as,

SVNyboer=ρbL2Z02ΔZmaxDown-slope extrapolation$$S{{V}_{Nyboer}}=-\frac{{{\rho }_{b}}{{L}^{2}}}{Z_{^{0}}^{2}}\Delta {{Z}_{\max }}\ \ \left( \text{Down-slope extrapolation} \right)$$

where Z0 is the static transthoracic base impedance and ΔZmax is the maximum backward extrapolated value of the thoracic cardiogenic impedance pulse variation, which includes runoff. While credible SV values could be obtained with equation 34, it was not widely accepted, this being due to difficulty in manually determining the true maximum downslope.

Kubicek’s Method: Maximum Systolic Upslope Forward Extrapolation of ΔZb(t)

As a consequence of the deficiencies of the backward extrapolation procedure, Kubicek et al. proposed a maximum systolic forward extrapolation of ΔZb(t), which is the basis for all subsequent plethysmographic conceptually-based SV equations using the transthoracic approach [29,30]. Kubicek et al. made the assumption that, if the maximum systolic upslope (i.e. ΔZ′ = ΔZ·s–1, Ω·s–1) is held constant throughout ejection, then compensation for outflow, before and after attainment of Qmax is achieved. Theory underlying Kubicek’s method assumes that little arterial runoff occurs during the inertial phase of rapid systolic ejection. Unlike Nyboer’s direct measurement of ΔZmax, Kubicek’s method requires multiplying ΔZ′ (forward extrapolation) by left ventricular ejection time TLVE (i.e. ΔZ′ × TLVE = ΔZmax). In the original description of the technique, TLVE was determined by means of phono-cardiography. As opposed to manual extrapolation of ΔZ′, electronic differentiation of ΔZb(t) was implemented. The first time-derivative clearly defines dZ/dtmax, with the presumed units of Ω·s–1, as a distinct point C and left ventricular ejection time (s) as the interval between points B (aortic valve opening) and X (aortic valve closure) (fig. 5). Thus, ΔZmax = dZ/dtmax × TLVE = Ω. Kubicek’s equation is thus obtained by substituting dZ/dtmax × TLVE for ΔZmax in equation 34. The Kubicek equation is given below and purportedly equivalent to equation 17. Thus [29,30],

Fig. 5

ECG, ΔZ(t) and dZ/dt waveforms from a human subject. For ΔZ(t) note Nyboer’s maximum down-slope backward extrapolation to find ΔZmax. Also note Kubicek’s maximal systolic up-slope forward extrapolation of ΔZ(t). For dZ/dt, point B = aortic valve opening; point X = aortic valve closure; Y = pulmonic valve closure; O = rapid ventricular filling wave; Q–B interval = pre-ejection period (s); B–C interval = time-to-peak (TTP, s) of dZ/dtmax; B–X interval; left ventricular ejection time (TLVE, s). dZ/dt waveform to right shows the square wave integration (shaded area), dZ/dtmax remaining constant over the ejection interval, which represents outflow compensation. Modified from reference 13.

SVKubicek=ρbL2Z02dZtdtmaxTLVEmL$$S{{V}_{Kubicek}}=\frac{{{\rho }_{b}}{{L}^{2}}}{Z_{0}^{2}}\frac{dZ\left( t \right)}{d{{t}_{\max }}}{{T}_{LVE}}\ \ \left( \text{mL} \right)$$

where ρb is the static specific resistance of blood, which was initially fixed at 150 Ω·cm [29]. As concerns the appropriate value for ρ, Quail et al [31] rearranged the Kubicek equation (assuming it correct), solved for ρ as the dependent variable, and measured SV by EMF. By means of normovolemic hemodilution exchange transfusion, they showed that, over a wide range of hematocrit from 26%–66%, the value of ρ remained virtually constant about a mean of 135Ω·cm at hematocrit 40%. L (cm) is the longitudinal distance between the voltage sensing electrodes on the base of the neck and those on the lower thorax at the level of the xiphoid process. Z0 is the quasi-static base impedance measured between the voltage sensing electrodes. In an in vitro expansible tube model, when equation 35 is compared to equation 33 without outflow occlusion, equation 33 systematically underestimates SV obtained from 35 [26]. By elimination of a Z0 term, the volume conductor VC in equation 35 is given as,

VC=ρbL2Z0mL$${{\text{V}}_{\text{C}}}=\frac{{{\rho }_{b}}{{L}^{2}}}{{{Z}_{0}}}\ \ \ \ \left( \text{mL} \right)$$

where, when Z0 varies with alterations in extravascular lung water, the VC is non-constant. Equation 35 is, in theory, modeled as the ohmic equivalent of windkesselequation 17, where outflow correction is explicitly defined. Thus, by analogy and inspection of equation 17, Kubicek’s equation is conceptually and explicitly dependent on aortic pressure, the rate of change of aortic pressure and mean arterial pressure. However, by comparison with equation 17, and without theoretical or mathematical explanation, Kubicek’s equation implicitly integrates the unknowns of compliance C, characteristic (mechanical) aortic input impedance (Zc) and systemic vascular resistance Rs into the overall theoretical gestalt.

Assumptions of the Nyboer/Kubicek method [14,15]

The transthoracic impedance Z(t) is considered the parallel connection of an aggregate of static cylindrical tissue impedances, Zt, considered as one, and, encased within, a dynamic blood resistance, Rb, otherwise known as the blood impedance, Zb.

The blood resistance is considered a homogeneously conducting blood-filled cylinder of constant length L, or a parallel connection of an aggregate of cylinders considered as one.

The current distribution in the blood resistance is uniform.

All current flows through the blood resistance.

The volume conductor VC is homogeneously perfused with blood of specific resistance ρb.

The magnitude of stroke volume is directly proportional to power functions of measured distance L between the voltage sensing electrodes [2930], or to height-based thoracic length equivalents [32].

All pulsatile impedance changes ΔZb(t) are due to vessel volume changes ΔVb(t), and, in the context of assumption 2, ΔZb(t) is due exclusively to changes in vessel radius dr(t) and CSA dA(t).

In the context of assumption 7, dZ/dtmax is the bioelectric equivalent of dV/dtmax, Q˙max${{\dot{Q}}_{\max }}$(i.e.dAtdtmax×L=dVtdtmax).$(\text{i}\text{.e}\text{.}\frac{dA\left( t \right)}{d{{t}_{\max }}}\times L=\frac{dV\left( t \right)}{d{{t}_{\max }}}).$See equation 7.

Outflow, or runoff during ventricular ejection, can be compensated for by extrapolating the peak rate of change of ΔZb(t) over the ejection interval (i.e. dZ/dtmax × TLVE) to obtain ΔZmax [2930].

The specific resistance (resistivity) of blood ρb is constant during ejection [29]

The transthoracic specific resistance, ρT, is constant [31].

Sramek-Bernstein Method: A Constant-Magnitude Volume of Electrically Participating Thoracic Tissue VEPT

The assumptions of the Sramek-Bernstein equation are virtually identical to those of the Kubicek method, except for the physical definition and magnitude of the VC [32]. In Sramek’s interpretation of Kubicek’s VC, ρ and a Z0 variable are eliminated by mathematical substitution. This simplification assumes, as per the work of Quail et al. [29] that, the ρT equivalent, Z0A/L can replace ρT. By this substitution, VC is rendered a personal constant for each individual. Sramek [32] named the modification of Kubicek’s VC as the volume of electrically participating thoracic tissue, VEPT. Conceptually, as opposed to Kubicek’s cylindrical VC, Sramek’s VEPT is geometrically a frustum, or truncated cone. Full mathematical derivation and justification for Sramek’s model is provided elsewhere [32]. The original Sramek equation is given as,

SVSramek=VEPTdZ/dtmaxZ0TLVE=L34.25dZ/dtmaxZ0mLTLVE$$\begin{align}& S{{V}_{Sramek}}={{V}_{EPT}}\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}{{T}_{LVE}}=\frac{{{L}^{3}}}{4.25}\mathop{\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}}_\left( \text{mL} \right){{T}_{LVE}} \end{align}$$

where L is the measured distance (cm) between the voltage sensing electrodes and 4.25 an experimentally-derived constant. The Bernstein modification of VEPT assumes that SV is not only a function of thoracic length, but also body weight and blood volume. Correcting for the magnitude of the blood resistance (i.e. intrathoracic blood volume, ITBV, mL) and using the work of Feldschuh and Enson [33], a factor δ (delta) was appended to the Sramek equation. The Sramek-Bernstein equation is given as [32],

SVSB=δL34.25dZ/dtmaxZ0TLVEmL$$S{{V}_{S-B}}=\delta \frac{{{L}^{3}}}{4.25}\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}{{T}_{LVE}}\ \ \ \left( \text{mL} \right)$$

where L is a thoracic length equivalent, equal to 17% of body height (i.e. 0.17⋅H) (cm), and delta δ is the weight correction for blood volume. δ is a dimensionless parameter, which corrects for deviation from ideal body weight (kg) at any given height and further modified for the indexed blood volume (mL·kg–1) at that weight deviation [32,33].

Validity of the Plethysmographic Hypothesis and its Assumptions

In order for equations 35, 37 and 38 to yield equivalent results to equation 17, it must be demonstrated that dZ/dtmax is explicitly dependent on aortic systolic pressure P(t), the rate of change of aortic pressure dP/dt, mean arterial pressure Pmean, systemic vascular resistance Rs and aortic compliance C. In an early, well designed experimental study, Yamakoshi et al. [1] demonstrated that, in an in vitro distensible tube model, the magnitude of impedance-derived SV is not related to any one of the above windkessel parameters. Despite their results, which clearly invalidate the plethysmographic hypothesis, the literature has ignored these findings. Data provided by Djordjevich et al. [34], though purporting to show a close relationship between dZ/dtmax and blood pressure levels, actually demonstrated that the correlations are weak, at best. Clinically, Brown et al. [35] demonstrated that, despite advancing age (20–80 years) and progressive stiffening of the aorta, ICG CO is nonetheless highly correlated with thermodilution CO (TDCO). It is also interesting to note that, as an alleged analog of dV/dtmax, dZ/dtmax supposedly provides an ohmic mean velocity analog necessary for SV calculation (vide infra). As concerns the volume conductor (VEPT) of the Kubicek equation (equation 36), it seems quite improbable that the transthoracic specific resistance, ρT, remains constant in the face of changing values of Z0. By inspection of equation 23, L and V remaining constant, it is apparent that this is impossibility, because, ρT must vary directionally with its dependent variable Z0. Other unanswered questions concerning the validity of the plethysmographic hypotheses include the following:

The proper value, physiologic definition, and theoretical basis for ρ: i.e. does ρ vary with hematocrit (ρb), or is it a constant based on thoracic resistivity (ρT)?

The physiological relevance of measured L or thoracic length equivalents in the Kubicek and Sramek-Bernstein equations regarding SV.

The validity of the outflow extrapolation procedure [36].

A coherent physiologic basis and correlate for the empirically-derived volume conductors and their relevance to SV.

Lack of consideration for the changing transthoracic base impedance (ΔZ0) in critical illness, typified by increased thoracic liquids (pulmonary edema) causing aberrant electrical conduction [37].

Lack of regard for the effect of the blood velocity-induced change in the transthoracic specific resistance Δρb(t) [37].

Origin of dZ/dtmax in the hemodynamic time domain [37].

Despite the objections to the plethysmographic hypothesis, correlation with reference standards is considered good (r2 = 0.67, range = 0.52–0.81 and, r = 0.82, range = 0.70–0.90 [7,12]. However, high correlation and reasonable agreement with invasive reference standards does not verify the plethysmographic hypothesis as correct. It may simply mean that the product of dZ/dtmax, TLVE, and a best-fit volume conductor VC, yield results that mimic reference method SV [14,15].

Origin of dZ/dtmax
Resolution of Origin by Differential Time-Domain Analysis

If equation 23 is differentiated by parts with respect to time, the following results:

dZtdt=dZlengthtdt+dZveltdtdZvoltdt$$\frac{dZ\left( t \right)}{dt}=\frac{d{{Z}_{length}}\left( t \right)}{dt}+\frac{d{{Z}_{vel}}\left( t \right)}{dt}-\frac{d{{Z}_{vol}}\left( t \right)}{dt}$$

Furthermore, if all variables in equation 23 are continuously differentiable functions of time and are expressed within the respective dZ/dt derivatives of equation 39 [37],

dZtdt=ρbVb2L1dLtdt+L2VbdρbtdtρbL2Vb2dVbtdt$$\frac{dZ\left( t \right)}{dt}=\frac{{{\rho }_{b}}}{{{V}_{b}}}\frac{2L}{1}\frac{dL\left( t \right)}{dt}+\frac{{{L}^{2}}}{{{V}_{b}}}\frac{d{{\rho }_{b}}\left( t \right)}{dt}-\frac{{{\rho }_{b}}{{L}^{2}}}{V_{b}^{2}}\frac{d{{V}_{b}}\left( t \right)}{dt}$$

Since dL and dL/dt are of trivial magnitude, dZ/dt comprises derivatives 2 and 3, the units of which are Ω·s–2 and Ω·s–1, respectively.

Using older plethysmographic techniques, which are conceptually analogous to the simple two-element windkessel model, simultaneous outflow during inflow over aortic segment L is compensated for by using the maximal systolic upslope extrapolation of ΔZb(t). The peak slope is conceptually believed to be the peak slope of ΔZvol(t), and, according to theoretical assumptions, represents the ohmic equivalent of the peak rate of change of aortic volume (peak flow, dV/dtmax, mL·s–1), at and before which little outflow is thought to occur [36]. When extrapolated over the ejection interval, this convention is believed to be proportional to total SV [29,30]. To better define the peak slope, ΔZb(t) is electronically differentiated to dZ/dt (i.e. d[ΔZb(t)]/dt), the peak magnitude of which is dZ/dtmax and conceptually analogous to the peak value of derivative 3 of equation 40 (i.e. d[ΔZvol(t)]/dtmax). That is,

dZvoltdtmax=ρbL2Vb2dVbtdtmaxΩs1$$\frac{d{{Z}_{vol}}\left( t \right)}{d{{t}_{\max }}}=\frac{{{\rho }_{b}}{{L}^{2}}}{V_{b}^{2}}\frac{d{{V}_{b}}\left( t \right)}{d{{t}_{\max }}}\ \ \ \ \left( \Omega \cdot {{\text{s}}^{-1}} \right)$$

A recently introduced ICG method conceptualizes the peak value of derivative 2 of equation 40 to represent dZ/dtmax, which is the peak rate of change of the red cell velocity-induced blood resistivity variation dρb(t)/dtmax (Ω⋅cm·s–2) (i.e d[ΔZvel(t)]/dtmax, Ω·s–2) [37]. Thus,

dZveltdtmax=L2VbdρbtdtmaxΩs2$$\frac{d{{Z}_{vel}}\left( t \right)}{d{{t}_{\max }}}=\frac{{{L}^{2}}}{{{V}_{b}}}\frac{d{{\rho }_{b}}\left( t \right)}{d{{t}_{\max }}}\ \ \ \ \left( \Omega \cdot {{\text{s}}^{-2}} \right)$$

While differential time domain analysis provides the two possible origins of dZ/dtmax, the definitive origin requires temporal correspondence of dZ/dtmax with either peak ascending aortic blood flow (Q(t)max, dV/dtmax) or peak aortic blood acceleration (dv/dtmax, dQ/dtmax).

Resolution of Origin by Comparative Time-Domain Analysis: Evidence for a New Paradigm

Comparative time domain analysis confirms that peak flow velocity occurs at 100±20ms after opening of the aortic valve [38], whereas dZ/dt, (as extrapolated from the data of Matsuda et al. [39] and Lozano et al. [40]) and acceleration dv/dt peak at a mean value of 50 (Lozano)→60 (Matsuda)±20ms. As testaments to the validity of these rise times, which is the temporal interval between aortic valve opening, designated as point B on the dZ/dt tracing to dZ/dtmax, data provided by Matsuda et al. [39] show that, when the time interval from the Q wave of the ECG to LVdP/dtmax is subtracted from the time interval between the Q wave and dZ/dtmax, TTP of dZ/dtmax = 60±15ms (i.e. [Q→dZ/dtmax(ms)] – [Q→LVdP/dtmax (ms)] = 60±15 ms). This analysis is valid, because, in the absence of aortic valve disease, LVdP/dtmax almost invariably occurs within 2–5 ms just prior to aortic valve opening. Corroborative evidence from Lozano et al., obtained by subtracting the R(ECG)→B(dZ/dt) interval (mean 68 ms, range 47–84 ms) from the R→dZ/dtmax interval (mean 120ms, range 80–160ms), shows that the mean rise time (TTP) from point B to dZ/dtmax = 52±20 ms (i.e. [R→dZ/dtmax ms] – [R→B ms] = 52±20 ms). These calculated rise times are corroborated by actual measurements obtained by Debski et al. [41]. It can also be shown that TTP of both dv/dt and dZ/dt occur in the first 10–20% of systole, whereas peak flow velocity occurs at the end of the first third of systole [13]. Matsuda et al. have shown that, while peaking out of phase, the maximum upslope and TTP of LVdP/dtmax and dZ/dtmax are identical. Regression equations by Adler et al. [42] and graphic evidence interpolated from Lyssegen et al. [43] show that, at normocardia (70–90 bpm) TTP of LVdP/dtmax is 50–60 ms, which is equivalent to the rise time of dZ/dtmax. These data suggest that the inotropic forces governing the potential energy generated during isovolumic contraction time (IVCT) are transferred, unabated, converting potential energy to equivalent kinetic energy (as expressed as dv/dtmax or equivalently dZ/dtmax) during the earliest phase of ejection. Welham et al. [44] have definitively shown that, during halothane-induced myocardial depression LVdP/dtmax, dv/dtmax, and dZ/dtmax decrease and recover proportionately with the depth of anesthesia. With profound myocardial depression, it is easily demonstrated that dZ/dtmax peaks synchronously with dv/dtmax and appreciably before Q (t)max.

Figure 6 shows that dZ/dtmax intersects the flow curve during peak acceleration and appreciably before Q(t)max. Simultaneously obtained waveforms comparing TTP of peak flow velocity and dZ/dtmax, showing the latter temporally preceding the former, can be found elsewhere [30,45,46,47].

Fig. 6

Relationship between esophageal ECG (A), aortic pressure (B), aortic expansion (C), aortic blood flow (D), pulmonic expansion (E), ΔZ(t) (F), and dZ/dt (G). Note that dZ/dtmax precedes peak aortic blood flow (Qmax) during the period of peak flow acceleration in early systole. Modified from reference 13.

Figure 7 shows that dZ/dtmax peak synchronously with aortic dP/dtmax, where, as extrapolated from equation 9 and its following discussion (vide supra) dP/dtmax corresponds in time with dF/dtmax (major derivative) when dA/dtmax (minor derivative) is trivial. This indicates that the peak rate of change of force of ventricular ejection is manifest as dZ/dtmax in impedance cardiography. As equations 9 and 11 predict and figure 1 indicates, Q(t)max will occur synchronously with dA/dtmax, when aortic dP/dt, dF/dt and dQ/dt=0.

Fig. 7

Ascending aortic dP/dt, ascending aortic pressure P, and dZ/dt from a human. Note that dZ/dtmax peaks precisely with ascending aortic dP/dtmax. Note computer artifact. Courtesy of Kirk L. Peterson, M.D.; From the cardiac catheterization laboratory at the University of California School of Medicine, San Diego.

Figure 6 indicates that, at Q(t)max, dZ/dt = 0. These observations infer, if not prove that dZ/dtmax occurs in earliest systole, contemporaneously with aortic dP/dtmax and peak blood flow acceleration (dv/dtmax, dQ/dtmax). Further proof that dZ/dtmax peaks with and is the electrical analog of dv/dtmax is verified experimentally by their corresponding relationship with the “I” wave of the ultra-low frequency acceleration ballistocardiogram (aBCG). Winter et al. [48] showed that the “I” wave of the aBCG corresponds precisely in time with peak aortic blood acceleration dv/dtmax, while both Kubicek [49] and Mohapatra and Hill [50] demonstrated that the “I” wave corresponds precisely in time with dZ/dtmax (fig 8). Seitz and McIlroy [51] demonstrated that peak blood acceleration and the “I” wave of the HJ interval occur 40–50 ms after opening of the aortic valve, which is consistent with the TTP of dZ/dtmax. Consistent with figure 7, showing that dZ/dtmax peaks with aortic dP/dtmax, Reeves et al. [52] demonstrated that the “I” wave of the aBCG peaks with the second derivative of the carotid contour volume displacement curve (i.e. carotid dP/dtmax, pressure acceleration).

Fig. 8

ECG, ultra-low frequency ballistocardiogram (BCg), dZ/dt, and ΔZ(t) from a human. Note that the “I” wave of the HJ interval peaks precisely with dZ/dtmax. The unlabeled noisy signal above ECG is a phonocardiogram. From reference 49.

Gaw et al. [23] showed that the relative blood conductivity change (Δσ/σ (%), i.e. [Δρb(t)/ρb]–1(%)) parallels the peak acceleration of the red cell reduced average velocity (mean spatial velocity, <v>/R (s–1)) with r = 0.99 (fig 4). This implies that the normalized peak rate of change of the blood resistivity variation dρb(t)/dtmaxb(stat) is hemodynamically equivalent to the peak rate of change of the red cell reduced average blood acceleration, which is concordant with equation 42. Thus, dZ/dtmax appears during the inertial phase of earliest ventricular ejection when little volume change occurs and represents the electrical analog of the most explosive phase of the initial ventricular impulse. Thus, dZ/dtmax is bioelectrically equivalent to equation 42 and possesses the units of Ω⋅s–2.

Square Root Acceleration Step-down Transformation: Ohmic Mean Velocity from Ohmic Mean Acceleration

As discussed by Gaw [23] and Visser [19], the relative change of blood resistivity (or equivalently blood conductivity) due to aortic blood flow is related, hemodynamically, to an exponential power (n) of the reduced average blood velocity (i.e. mean spatial velocity) [(<v>/R)n, (s–1)n]. It thus follows that dZ/dtmax/Z0 (s–2) is the ohmic analog of peak aortic reduced average blood acceleration (PARABA), this being the mean acceleration divided by the aortic valve radius.

PARABA=dv/dtmaxRs2$$\text{PARABA=}\frac{d\left\langle v \right\rangle /d{{t}_{\text{max}}}}{R}\ \ \ \ \left( {{\text{s}}^{-2}} \right)$$

Through the relationship for mean flow velocity given by Visser [19], PARABA can be reduced to mean blood flow velocity by square root transformation,

Q˙¯=πr3dv/dtmaxRmmLs1$$\overline{{\dot{Q}}}=\pi {{r}^{3}}\sqrt{{{\left( \frac{d\left\langle v \right\rangle /d{{t}_{\text{max}}}}{R} \right)}^{m}}}\ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

Preliminary evidence suggests that the exponent m is in the range of 1.15–1.25.

To obtain ohmic mean velocity (s–1) from the mean acceleration analog, dZ/dtmax/Z0 must also undergo square root transformation.

L2Vbdρbtdtmax1Z=dZ/dtmaxZ0s1$$\sqrt{\frac{{{L}^{2}}}{{{V}_{b}}}\frac{d{{\rho }_{b}}\left( t \right)}{d{{t}_{\max }}}\frac{1}{Z}}=\sqrt{\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}}\ \ \ \ \,\left( {{\text{s}}^{-1}} \right)$$

It naturally follows that,

dv/dtmaxRmdZ/dtmaxZ0s1$$\sqrt{{{\left( \frac{d\left\langle v \right\rangle /d{{t}_{\max }}}{R} \right)}^{m}}}\equiv \sqrt{\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}}\ \ \ \ \,\left( {{\text{s}}^{-1}} \right)$$

Inasmuch as dZ/dtmax is the electrodynamic equivalent of mean aortic blood acceleration, and SV is obtained from a mean velocity calculation, it is suggested that equations 35, 37, and 38 produce a mean acceleration surrogate of SV, which is impossible according to equation 6. Thus,

SV=πr2t0t1vtdtVEPTdZ/dtmaxZ0TLVESV=Ct0t1dPtdt+1RSt0t1PtdtVEPTdZt/dtmaxZ0TLVE$$\begin{array}{*{35}{l}}SV=\pi {{r}^{2}}\int_{{{t}_{0}}}^{{{t}_{1}}}{v\left( t \right)dt\ne {{V}_{EPT}}}\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}{{T}_{LVE}}\Rightarrow \\SV=C\int_{{{t}_{0}}}^{{{t}_{1}}}{\frac{dP\left( t \right)}{dt}+\frac{1}{R_{S}}}\int_{{{t}_{0}}}^{{{t}_{1}}}{P\left( t \right)dt\ne {{V}_{EPT}}}\frac{dZ\left( t \right)/d{{t}_{\max }}}{{{Z}_{0}}}{{T}_{LVE}} \\\end{array}$$

Based on the above discussion, this leads to the inevitable conclusion that,

SV=πr2t0t1vtdt=πr2v¯TLVE=VEPTdZ/dtmaxZ0TLVE$$SV=\pi {{r}^{2}}\int_{{{t}_{0}}}^{{{t}_{1}}}{v\left( t \right)dt=\pi {{r}^{2}}\cdot \overline{v}\cdot {{T}_{LVE}}={{V}_{EPT}}}\sqrt{\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}}{{T}_{LVE}}$$

In view of this discussion, the outflow correction factor, dZ/dtmax x TLVE, is rendered moot, because dZ/dtmax represents axial blood acceleration and not radially-oriented rate of change of volume according to windkessel theory [36]. Close correspondence between the Kubicek or Sramek-Bernstein equations with reference method CO is simply due to the fact that peak velocity and mean acceleration are highly correlated (r=0.75) and both peak and mean aortic blood acceleration are highly correlated with SV (r = 0.75) as well as with the systolic velocity integral (stroke distance) (r = 0.75) [5355]. Thus over a selected range of ohmic acceleration (i.e. dZ/dtmax), dZ/dtmax × TLVE provides acceleration facsimiles of ohmic mean velocity.

As per equation 46, the relationship between ohmic mean velocity and ohmic mean acceleration is parabolic (ohmic mean acceleration = (ohmic mean velocity)2 or y = x2. This relationship predicts that, over wide ranges of dZ/dtmax, ohmic mean velocity will be overestimated and underestimated at its upper and lower extremes, respectively.

Indeed, Yamakoshi et al. [1] showed that ICG-derived SV overestimates reference method SV in healthy canines by as much as 70%, and correspondingly underestimates reference SV by as much as 25% when myocardial failure is induced. Similarly, Ehlert and Schmidt [56] could not find a linear relationship between ICG and EMF-derived SV over a wide range of hemodynamic perturbations.

Effect of Hematocrit on dZ/dtmax and ICG-Derived SV and CO

As inferred, the static specific resistance of blood, ρb, nor the static specific resistance of the thorax, ρT, are included in the ohmic acceleration-based SV method. Despite Visser’s [19] and Hoetink’s [22] in vitro experimental findings, showing that the relative blood resistivity change is proportional to hematocrit, Visser et al. [14] also showed that, although the peak magnitude of ΔZb(t) (i.e ΔZb(t)max) is hemocrit-dependent, its maximum upslope, dZ/dtmax, is not (figure 3 in Visser et al.). In a canine model, Quail et al. [31] showed that normovolemic hemodilution over a hematocrit range of 66%–26%, produced an appropriate increase in SV, which was not different from electromagnetic flow-meter-derived (EMF) SV. Corroboratively, an in vivo ICG study by Wallace et al. [57] showed that, over a wide range of hematocrit (20%–35%) and blood conductivity (ρ=80–160Ω·cm) induced by normovolemic hemodilution, ICG CO was in agreement with transit time flow probe CO.

The Volume Conductor (VEPT, VC)

In contrast to the earlier methods, where the swept volume of the thorax (or portion thereof) is considered the appropriate VC, the VEPT corresponding to the new method is conceptualized physiologically and by magnitude as the intrathoracic blood volume (ITBV, VITBV). As opposed to linear-based volume conductors, using thoracic length or a height-based equivalent, ITBV is biophysically assumption-free, inherently unambiguous in physiologic meaning and intuitively understood as the physical embodiment of the blood resistance, Rb. Physiologically, ITBV has been shown to be highly correlated with left ventricular preload, as expressed by left ventricular end-diastolic volume (LVEDV), and thus with absolute values for SV and directional changes thereof [5861]. Computationally, VITBV is found through linear allometric equivalents of body mass (kg). Supporting this relationship, studies show that body mass correlates linearly, and much more closely with total blood volume (TBV), SV and CO than patient height [6266]. By magnitude, the ITBV represents approximately 25% of TBV, or about 17.5 mL⋅ kg–1, which results in VITBV = 17.5 x Wkg, or equivalently 16Wkg1.02 [37,67] By comparison, existing volume conductors associated with the plethysmographic hypothesis are modeled as simple geometric abstractions, which are firmly rooted in basic electrical theory. By virtue of their “best-fit” mathematical construction, they bare little relevance to, and have virtually no biophysical relationship with other commonly accepted physiologic, anatomic, or hemodynamic parameters.

Determinants of the Magnitude of dZ/dtmax

Evidence suggesting that dZ/dtmax varies inversely with aortic valve CSA, or radius r, as a function of PARABA, is inferentially demonstrated through the work of Sageman [68]. He clearly showed that an inversely proportional and highly negatively correlated (r = –0.75) relationship exists between dZ/dtmax/Z0 and body mass in healthy humans. Aortic valve CSA has been shown to correlate highly with body mass (kg) and body surface area (BSA, m2). But by contrast with dZ/dtmax/Z0, Doppler and EMF peak velocities and systolic velocity integrals are totally independent of body mass [69]. Thus, Newtonian-based peak velocities of equal magnitude, measured between age-matched individuals of different body mass and aortic valve CSAs, will produce correspondingly disparate values of dZ/dtmax/Z0. It follows that, while there is no direct proportionality between hemodynamically-based and impedance-derived systolic velocity integrals within or between individuals, a linear equivalence exists through their respective mean flow values. Specifically, as a convoluted abstraction of the equation of continuity,

Area×v¯=Volume×dZ/dtmaxZ0mLs1$$Area\times \overline{v}=Volume\times \sqrt{\frac{dZ/d{{t}_{\max }}}{{{Z}_{0}}}}\ \ \ \ \ \left( \text{mL}\cdot {{\text{s}}^{-1}} \right)$$

Because of the absolute dependency of dZ/dtmax/Z0 upon PARABA, this means that, for any given value of mean acceleration, the magnitude of dZ/dtmax is related to and explicitly dependent on aortic root CSA by its dependency on R. Since aortic root CSA is a function of body mass, age, and gender, dZ/dtmax will vary accordingly. Thus, the magnitude of dZ/dtmax is multi-factorial and not wholly dependent on the respective levels of myocardial contractility and Z0. As a first order approximation,

dZtdtmax=Z0πr3VCdv/dtmaxRm2Ωs2$$\frac{dZ\left( t \right)}{d{{t}_{\max }}}={{Z}_{0}}{{\left[ \frac{\pi {{r}^{3}}}{{{V}_{C}}}\left( \sqrt{{{\left( \frac{d\left\langle v \right\rangle /d{{t}_{\max }}}{R} \right)}^{m}}} \right) \right]}^{2}}\ \ \ \ \ \ \left( \Omega \cdot {{\text{s}}^{-2}} \right)$$
Index of Transthoracic Aberrant Conduction: Genesis of the Three-Compartment Parallel Conduction Model

One of the major drawbacks of the impedance technique has been its inability to correctly predict SV in the presence of excess EVLW [7072]. Critchley et al. [73] tested the hypothesis that the poor agreement between invasive reference standards and ICG is due to excess EVLW. Typified by Sepsis, they were able to show that ICG CO underestimated its thermodilution counterpart and that the degree of underestimation was related to the degree of EVLW excess. They also noted that, in general, excess EVLW was associated with values of Z0<20–22Ω. In a subsequent experimental model in canines, where pulmonary edema was induced by oleic acid infusion, they found a systematic progressive bias between flow probe and ICG CO [74]. As pulmonary edema progressively worsened, ICG CO progressively underestimated the flow probe estimate. In concert with the progressive divergence of the two methods, Z0 progressively decreased (fig. 10).

Fig. 9

Square root acceleration step-down transformation. On the y-axis, the ohmic equivalent of peak aortic reduced average blood acceleration (PARABA), which is dZ/dtmax/Z0., and the linear extrapolation of the square root transformation, ohmic mean velocity on the x-axis (x = √y and y = x2). From reference 13.

Fig. 10

Box plots showing that, as oleic acid-induced pulmonary edema worsened, as reflected by decreasing Z0, the systematic underestimation of flow-probe CO by ICG-derived CO increased. From reference 74.

Expanding equation 30, the following is a useful analytical tool for studying the effect of excess EVLW on the various compartments of the transthoracic impedance with the AC field.

ItρtL2Vt1ρbL2Vb2ρeL2Ve3ΔρbtL2Vb+ρbL2ΔVbt4=U0ΔUbt$$I\left( t \right)\left[ \left. \left( \left. \frac{{{\rho }_{t}}{{L}^{2}}}{{{V}_{t\left( 1 \right)}}} \right\|\left. \frac{{{\rho }_{b}}{{L}^{2}}}{{{V}_{b\left( 2 \right)}}} \right\|\frac{{{\rho }_{e}}{{L}^{2}}}{{{V}_{e\left( 3 \right)}}} \right) \right\|{{\left( \frac{\Delta {{\rho }_{b}}\left( t \right){{L}^{2}}}{{{V}_{b}}}+\frac{{{\rho }_{b}}{{L}^{2}}}{\Delta {{V}_{b}}\left( t \right)} \right)}_{\left( 4 \right)}} \right]=\left. {{U}_{0}} \right\|\Delta {{U}_{b}}\left( t \right)$$

In this model it is assumed that AC (I(t)) flows exclusively through the blood resistance Zb (100Ω·cm–180Ω·cm) (element 2), despite the fact that Ze (element 3) is of lower specific resistance (60Ω·cm–70Ω·cm). This assumption is probably not accurate, because the blood resistance Rb is considered a cylindrical conductor surrounded by a more highly conductive EVLW impedance Ze. By the reciprocal rule for parallel impedances, the resultant impedance (i.e. Zb||Ze) would be lower than either impedance alone. If Ze is of variable magnitude and Zb is held constant, then Z0 should vary with Ze. This is precisely what is observed clinically. When Ze reaches a critical volume (Ve(CRIT)), Ze becomes the lowest impedance as relates to the components of Z0. This causes electrical shunting, and in the extreme case (Z0 =10Ω–12Ω), a complete short circuiting of current away from the blood resistance. This results in preferential flow through Ze at the expense of Zb, with the result being a decrease in the magnitude of Z0 and the amplitude of ΔZb(t) [1]. At this critical level of Z0 (i.e. Z0(CRIT), ZC), which in humans is 20Ω±3Ω, excess EVLW causes spuriously reduced values of dZ/dtmax. Thus, dZ/dtmax no longer parallels its hemodynamic equivalent, PARABA, resulting in systematic underestimation of ICG SV/CO. In order to compensate for pathologic conduction through excess EVLW, an index of transthoracic aberrant conduction has been derived (ζ, zeta), which, as its magnitude decreases, creates a larger VEPT.

In patients without excess EVLW, VEPT is equivalent to VITBV. For all values of Z0<20 Ω, 0<ζ<1 and for Z0≥20 Ω, ζ=1. For all values of Z0<20 Ω, the following pertains:

VEPT=VITBVζ2VITBV+VEVLWmL$${{V}_{EPT}}=\frac{{{V}_{ITBV}}}{{{\zeta }^{2}}}\equiv {{V}_{ITBV}}+{{V}_{EVLW}}\ \ \ \ \left( \text{mL} \right)$$

where ζ is given as [37],

ζ=ZC2Z0ZC+K2ZC2+Z023ZCZ0+KDimensionless$$\zeta =\frac{{{Z}_{C}}^{2}-{{Z}_{0}}{{Z}_{C}}+K}{2{{Z}_{C}}^{2}+{{Z}_{0}}^{2}-3{{Z}_{C}}{{Z}_{0}}+K}\ \ \ \ \ \left( \text{Dimensionless} \right)$$

where ZC = critical level of base impedance Z0(CRIT) = 20Ω, corresponding to Ve(critical). Z0 = measured transthoracic impedance ≤ ZC, and K = a trivial constant →0.

Stroke Volume Equation for Impedance Cardiography
SVICG=VITBVζ2dZt/dtmaxZ0TLVEmL$$S{{V}_{ICG}}=\frac{{{V}_{ITBV}}}{{{\zeta }^{2}}}\sqrt{\frac{dZ\left( t \right)/d{{t}_{\max }}}{{{Z}_{0}}}}{{T}_{LVE}}\ \ \ \ \ \ \ \ \ \ \ \left( \text{mL} \right)$$

where VITBV = 16W(kg)1.02. Equation 55 [37] has been prospectively tested in critical and non-critically-ill patients and been shown to provide SV and CO values comparable to standard reference methods [37,7578]. As reviewed and compiled by Moshkovitz et al. [7] there are other whole body and transthoracic equations, but they have not been effectively prospectively tested.

Conclusions

From the results of this review, it is strongly suggested that the conceptually-based plethysmographic hypothesis for ICG-derived CO is flawed. The incontrovertible evidence provided herein shows quite conclusively that dZ/dtmax is a mean acceleration analog and not that of the peak rate of change of aortic volume. Therefore, to obtain ohmic mean velocity from dZ/dtmax/Z0, square root transformation is obligatory. Because dZ/dtmax represents axial blood acceleration, the “outflow compensation” for runoff is entirely irrelevant as a theoretical problem to be proved or disproved, as per the work of Faes et al. (36). The fact that dZ/dtmax is a mean acceleration analog permits the square wave integration, dZ/dtmax x TLVE, as a valid convention similar to equations 6 and 49 for the Doppler/EMF method of SV determination. As for the volume conductors implemented by both the Nyboer/Kubicek and Sramek/Bernstein models, there seems little physiologic justification for either approach. The volume of electrically participating thoracic tissue involved in dynamic conduction is clearly the blood resistance. By magnitude, the blood resistance translates directly into the intrathoracic blood volume. While basing the volume conductor on a fixed volume appears to be concordant with the Sramek/Bernstein model, this can only be true when dynamic conduction through the blood resistance is in parallel with peak aortic reduced average blood acceleration. This can only occur, when, by volume, the blood resistance is the compartment with the lowest impedance. Thus, when excess extravascular lung water exceeds some critical volume, current is diverted to the compartment of lowest impedance, which is now that of the extravascular lung water. With progressive diversion of AC away from the blood resistance, the magnitude of ΔZb(t) and dZ/dtmax diminish and therefore are not reflective of or proportional to the hemodynamic state. Clearly, a more robust mathematical solution for excess extravascular lung water is desirable; that is, if is at all possible.

Fig. 1

ECG, aortic pressure, aortic blood flow Q, aortic rate of change of pressure dP/dt, and rate of change of flow, which is acceleration dQ/dt. From a canine model In: Li J-K. The arterial circulation: physical principles and clinical applications. Totowa, NJ: Humana Press; 2000, p. 78.
ECG, aortic pressure, aortic blood flow Q, aortic rate of change of pressure dP/dt, and rate of change of flow, which is acceleration dQ/dt. From a canine model In: Li J-K. The arterial circulation: physical principles and clinical applications. Totowa, NJ: Humana Press; 2000, p. 78.

Fig. 2

Schematic of a multi-compartmental parallel conduction model of the thorax. The transthoracic electrical impedance Z(t) to an applied AC field represents the parallel connection of a quasi-static base impedance Z0 and a time-dependent component of the blood impedance, ΔZb(t). Z0 represents the parallel connection of all static tissue impedances, Zt, and the static component of the blood resistance, Zb. Ze represents the quasi-static EVLW compartment. A voltmeter (U) and AC generator (~) are shown. From reference 37.
Schematic of a multi-compartmental parallel conduction model of the thorax. The transthoracic electrical impedance Z(t) to an applied AC field represents the parallel connection of a quasi-static base impedance Z0 and a time-dependent component of the blood impedance, ΔZb(t). Z0 represents the parallel connection of all static tissue impedances, Zt, and the static component of the blood resistance, Zb. Ze represents the quasi-static EVLW compartment. A voltmeter (U) and AC generator (~) are shown. From reference 37.

Fig. 3

Behavior of AC as applied to pulsatile blood flow. → = AC flow. v = red cell velocity; Δρb(t) = changing specific resistance of flowing blood.; Qin = flow into aortic segment; Qout = simultaneous flow out of aortic segment; dA(t) = time-dependent change in aortic CSA. From reference 13.
Behavior of AC as applied to pulsatile blood flow. → = AC flow. v = red cell velocity; Δρb(t) = changing specific resistance of flowing blood.; Qin = flow into aortic segment; Qout = simultaneous flow out of aortic segment; dA(t) = time-dependent change in aortic CSA. From reference 13.

Fig. 4

Absolute spatial average velocity (i.e. reduced average velocity <v>/R, s–1) vs. conductivity change in an in vitro pulsatile ejection model over one cardiac cycle. Note that, upon red cell acceleration in early ejection, the peak rate of change of the reduced average velocity parallels the peak rate of change of conductivity (r = 0.99). From reference 23.
Absolute spatial average velocity (i.e. reduced average velocity <v>/R, s–1) vs. conductivity change in an in vitro pulsatile ejection model over one cardiac cycle. Note that, upon red cell acceleration in early ejection, the peak rate of change of the reduced average velocity parallels the peak rate of change of conductivity (r = 0.99). From reference 23.

Fig. 5

ECG, ΔZ(t) and dZ/dt waveforms from a human subject. For ΔZ(t) note Nyboer’s maximum down-slope backward extrapolation to find ΔZmax. Also note Kubicek’s maximal systolic up-slope forward extrapolation of ΔZ(t). For dZ/dt, point B = aortic valve opening; point X = aortic valve closure; Y = pulmonic valve closure; O = rapid ventricular filling wave; Q–B interval = pre-ejection period (s); B–C interval = time-to-peak (TTP, s) of dZ/dtmax; B–X interval; left ventricular ejection time (TLVE, s). dZ/dt waveform to right shows the square wave integration (shaded area), dZ/dtmax remaining constant over the ejection interval, which represents outflow compensation. Modified from reference 13.
ECG, ΔZ(t) and dZ/dt waveforms from a human subject. For ΔZ(t) note Nyboer’s maximum down-slope backward extrapolation to find ΔZmax. Also note Kubicek’s maximal systolic up-slope forward extrapolation of ΔZ(t). For dZ/dt, point B = aortic valve opening; point X = aortic valve closure; Y = pulmonic valve closure; O = rapid ventricular filling wave; Q–B interval = pre-ejection period (s); B–C interval = time-to-peak (TTP, s) of dZ/dtmax; B–X interval; left ventricular ejection time (TLVE, s). dZ/dt waveform to right shows the square wave integration (shaded area), dZ/dtmax remaining constant over the ejection interval, which represents outflow compensation. Modified from reference 13.

Fig. 6

Relationship between esophageal ECG (A), aortic pressure (B), aortic expansion (C), aortic blood flow (D), pulmonic expansion (E), ΔZ(t) (F), and dZ/dt (G). Note that dZ/dtmax precedes peak aortic blood flow (Qmax) during the period of peak flow acceleration in early systole. Modified from reference 13.
Relationship between esophageal ECG (A), aortic pressure (B), aortic expansion (C), aortic blood flow (D), pulmonic expansion (E), ΔZ(t) (F), and dZ/dt (G). Note that dZ/dtmax precedes peak aortic blood flow (Qmax) during the period of peak flow acceleration in early systole. Modified from reference 13.

Fig. 7

Ascending aortic dP/dt, ascending aortic pressure P, and dZ/dt from a human. Note that dZ/dtmax peaks precisely with ascending aortic dP/dtmax. Note computer artifact. Courtesy of Kirk L. Peterson, M.D.; From the cardiac catheterization laboratory at the University of California School of Medicine, San Diego.
Ascending aortic dP/dt, ascending aortic pressure P, and dZ/dt from a human. Note that dZ/dtmax peaks precisely with ascending aortic dP/dtmax. Note computer artifact. Courtesy of Kirk L. Peterson, M.D.; From the cardiac catheterization laboratory at the University of California School of Medicine, San Diego.

Fig. 8

ECG, ultra-low frequency ballistocardiogram (BCg), dZ/dt, and ΔZ(t) from a human. Note that the “I” wave of the HJ interval peaks precisely with dZ/dtmax. The unlabeled noisy signal above ECG is a phonocardiogram. From reference 49.
ECG, ultra-low frequency ballistocardiogram (BCg), dZ/dt, and ΔZ(t) from a human. Note that the “I” wave of the HJ interval peaks precisely with dZ/dtmax. The unlabeled noisy signal above ECG is a phonocardiogram. From reference 49.

Fig. 9

Square root acceleration step-down transformation. On the y-axis, the ohmic equivalent of peak aortic reduced average blood acceleration (PARABA), which is dZ/dtmax/Z0., and the linear extrapolation of the square root transformation, ohmic mean velocity on the x-axis (x = √y and y = x2). From reference 13.
Square root acceleration step-down transformation. On the y-axis, the ohmic equivalent of peak aortic reduced average blood acceleration (PARABA), which is dZ/dtmax/Z0., and the linear extrapolation of the square root transformation, ohmic mean velocity on the x-axis (x = √y and y = x2). From reference 13.

Fig. 10

Box plots showing that, as oleic acid-induced pulmonary edema worsened, as reflected by decreasing Z0, the systematic underestimation of flow-probe CO by ICG-derived CO increased. From reference 74.
Box plots showing that, as oleic acid-induced pulmonary edema worsened, as reflected by decreasing Z0, the systematic underestimation of flow-probe CO by ICG-derived CO increased. From reference 74.

Yamakoshi K, Togawa T, Ito H. Evaluation of the theory of cardiac-output computation from transthoracic impedance plethysmogram. Med Biol Eng Comput 1977;15:479–88.10.1007/BF02442275199803YamakoshiKTogawaTItoHEvaluation of the theory of cardiac-output computation from transthoracic impedance plethysmogramMed Biol Eng Comput19771547988199803Open DOISearch in Google Scholar

Bernstein DP. Pressure pulse contour-derived stroke volume and cardiac output in the morbidly obese patient. Obes Surg 2008;18:1015–21.1844389210.1007/s11695-007-9378-6BernsteinDPPressure pulse contour-derived stroke volume and cardiac output in the morbidly obese patientObes Surg20081810152118443892Search in Google Scholar

Quick CM, Berger DS, Noordergraaf A. Apparent arterial compliance. Am J. Physiol (Heart Circ Physiol 43) 1998;274:H1393–1403.10.1152/ajpheart.1998.274.4.H1393QuickCMBergerDSNoordergraafAApparent arterial complianceAm J. Physiol (Heart Circ Physiol 43)1998274H139314039575945Open DOISearch in Google Scholar

Fogliardo R, Di Donfrancesco M, Burattini R. Comparison of linear and nonlinear formulations of the three-element winkdessel model. Am J Physiol (Heart Circ Physiol 40) 1996;271:H2661–68.10.1152/ajpheart.1996.271.6.H2661FogliardoRDi DonfrancescoMBurattiniRComparison of linear and nonlinear formulations of the three-element winkdessel modelAm J Physiol (Heart Circ Physiol 40)1996271H2661688997329Open DOISearch in Google Scholar

Chemla D, Hebert J-L, Coirault C, et al. Total arterial compliance estimated by stroke volume-to-aortic pulse pressure ratio in humans. Am J Physiol (Heart Circ Physiol 43)1998;274:H500–05.10.1152/ajpheart.1998.274.2.H500ChemlaDHebertJ-LCoiraultCTotal arterial compliance estimated by stroke volume-to-aortic pulse pressure ratio in humansAm J Physiol (Heart Circ Physiol 43)1998274H500059486253Open DOISearch in Google Scholar

Olufsen MS, Ottesen JT, Tran HT, et al. Blood pressure and blood flow variation during postural change from sitting to standing: model development and validation. J Appl Physiol 2005;99:1523–37.1586068710.1152/japplphysiol.00177.2005OlufsenMSOttesenJTTranHTBlood pressure and blood flow variation during postural change from sitting to standing: model development and validationJ Appl Physiol200599152337209403915860687Search in Google Scholar

Moshkovitz Y, Kaluski E, Milo O, et al. Recent developments in cardiac output determination by bioimpedance: comparison with invasive cardiac output and potential cardiovascular applications. Curr Opin Cardiol 2004;19:229–37.10.1097/00001573-200405000-0000815096956MoshkovitzYKaluskiEMiloORecent developments in cardiac output determination by bioimpedance: comparison with invasive cardiac output and potential cardiovascular applicationsCurr Opin Cardiol2004192293715096956Open DOISearch in Google Scholar

Summers RL, Shoemaker WC, Peacock DF, et al. Bench to bedside: electrophysiologic and clinical principles of noninvasive hemodynamic monitoring using impedance cardiography. Acad Emerg Med 2003;10:669–80.10.1111/j.1553-2712.2003.tb00054.x12782531SummersRLShoemakerWCPeacockDFBench to bedside: electrophysiologic and clinical principles of noninvasive hemodynamic monitoring using impedance cardiographyAcad Emerg Med2003106698012782531Open DOISearch in Google Scholar

Newman DG, Callister R. The non-invasive assessment of stroke volume and cardiac output by impedance cardiography: a review. Aviat Space Environ Med. 1999;70:780–9.10447052NewmanDGCallisterRThe non-invasive assessment of stroke volume and cardiac output by impedance cardiography: a reviewAviat Space Environ Med1999707809Search in Google Scholar

Woltjer HH, Bogaard HJ, deVries PM. The technique of impedance cardiography. Eur Heart J 1997;18:1396–403.945844410.1093/oxfordjournals.eurheartj.a015464WoltjerHHBogaardHJdeVriesPMThe technique of impedance cardiographyEur Heart J19971813964039458444Search in Google Scholar

Kauppinen PK, Hyttinen JA, Malmivuo JA. Senstitivity distributions of impedance cardiography using band and spot electrodes analyzed by a three-dimensional computer model. Ann Biomed Eng 1998;26:694–702.10.1114/1.44KauppinenPKHyttinenJAMalmivuoJASenstitivity distributions of impedance cardiography using band and spot electrodes analyzed by a three-dimensional computer modelAnn Biomed Eng1998266947029662161Open DOISearch in Google Scholar

Raaijmakers E, Faes TJ, Scholten RJ, et al. A meta-analysis of three decades of validating thoracic impedance cardiography. Crit Care Med 1999;27:1203–13.1039723010.1097/00003246-199906000-00053RaaijmakersEFaesTJScholtenRJA meta-analysis of three decades of validating thoracic impedance cardiographyCrit Care Med19992712031310397230Search in Google Scholar

Bernstein DP. Impedance cardiography: development of the stroke volume equations and their electrodynamic and biophysical foundations. In: Leondes CT, editor. Biomechanical systems technology: cardiovascular systems. Singapore: World Scientific; 2007. p. 49–87.BernsteinDPImpedance cardiography: development of the stroke volume equations and their electrodynamic and biophysical foundationsLeondesCTeditorBiomechanical systems technology: cardiovascular systemsSingaporeWorld Scientific200749–8710.1142/9789812771377_0003Search in Google Scholar

Visser KR, Lamberts R, Zijlstra WG. Investigation of the origin of the impedance cardiogram by means of exchange transfusion with stroma free haemoglobin solution in the dog. Cardiovasc Res 1990;24:24–32.10.1093/cvr/24.1.242328511VisserKRLambertsRZijlstraWGInvestigation of the origin of the impedance cardiogram by means of exchange transfusion with stroma free haemoglobin solution in the dogCardiovasc Res19902424322328511Open DOISearch in Google Scholar

Visser KR, Lamberts R, Zijlstra WG. Investigation of the parallel conductor model of impedance cardiography by means of exchange transfusion with stroma free haemoglobin solution. Cardiovasc Res 1987;21:637–45.10.1093/cvr/21.9.6373446367VisserKRLambertsRZijlstraWGInvestigation of the parallel conductor model of impedance cardiography by means of exchange transfusion with stroma free haemoglobin solutionCardiovasc Res198721637453446367Open DOISearch in Google Scholar

Wang L, Patterson R. Multiple sources of the impedance cardiogram based on 3-D finite difference human thorax models. IEEE Trans Biomed Eng 1995;42:141–8.10.1109/10.3418267868141WangLPattersonRMultiple sources of the impedance cardiogram based on 3-D finite difference human thorax modelsIEEE Trans Biomed Eng19954214187868141Open DOISearch in Google Scholar

Geddes LA, Sadler C. The specific resistance of blood at body temperature. Med Biol Eng Comput 1973;11:1973.GeddesLASadlerCThe specific resistance of blood at body temperatureMed Biol Eng Comput197311197310.1007/BF024755434746389Search in Google Scholar

Sakamoto K, Kanai H. Electrical characteristics of flowing blood. IEEE Trans Biomed Eng 1979;26:686–95.544441SakamotoKKanaiHElectrical characteristics of flowing bloodIEEE Trans Biomed Eng1979266869510.1109/TBME.1979.326459544441Search in Google Scholar

Visser KR. Electrical properties of flowing blood and impedance cardiography. Ann Biomed Eng. 1989;17:463–73.10.1007/BF02368066VisserKRElectrical properties of flowing blood and impedance cardiographyAnn Biomed Eng198917463732610418Open DOISearch in Google Scholar

Kosicki J, Chen LH, Hobbie R, et al. Contributions to the impedance cardiogram waveform. Ann Biomed Eng 1986;14:67–80.10.1007/BF023646493706856KosickiJChenLHHobbieRContributions to the impedance cardiogram waveformAnn Biomed Eng19861467803706856Open DOISearch in Google Scholar

Ravi Shankar TM, Webster JG, Shao SY. The contribution of vessel volume change and blood resistivity change to the electrical impedance pulse. IEEE Trans Biomed Eng 1985;32:192–98.3997176Ravi ShankarTMWebsterJGShaoSYThe contribution of vessel volume change and blood resistivity change to the electrical impedance pulseIEEE Trans Biomed Eng1985321929810.1109/TBME.1985.3255283997176Search in Google Scholar

Hoetink AE, Faes TJ, Visser KR et al. On the flow dependency of the electrical conductivity of blood. IEEE Trans Biomed Eng 2004;51:1251–61.10.1109/TBME.2004.82726315248541HoetinkAEFaesTJVisserKROn the flow dependency of the electrical conductivity of bloodIEEE Trans Biomed Eng20045112516115248541Open DOISearch in Google Scholar

Gaw RL, Cornish BH, Thomas BJ. The electrical impedance of pulsatile blood flowing through rigid tubes: a theoretical investigation. IEEE Trans Biomed Eng 2008;55:721–27.1827000910.1109/TBME.2007.903531GawRLCornishBHThomasBJThe electrical impedance of pulsatile blood flowing through rigid tubes: a theoretical investigationIEEE Trans Biomed Eng2008557212718270009Search in Google Scholar

Saito Y, Goto T, Terasaki H, et al. The effects of pulmonary circulation pulsatility on the impedance cardiogram. Arch Int Physiol Biochim 1983;91:339–44.6202263SaitoYGotoTTerasakiHThe effects of pulmonary circulation pulsatility on the impedance cardiogramArch Int Physiol Biochim1983913394410.3109/138134583090679796202263Search in Google Scholar

Ito H, Yamakoshi KI, Yamada A. Physiological and fluid-dynamic investigations of the transthoracic impedance plethysmography method for measuring cardiac output. Part II-Analysis of the transthoracic impedance wave by perfusing dogs. Med Biol Eng Comput 1976;14:373–8.10.1007/BF02476113ItoHYamakoshiKIYamadaAPhysiological and fluid-dynamic investigations of the transthoracic impedance plethysmography method for measuring cardiac output. Part II-Analysis of the transthoracic impedance wave by perfusing dogsMed Biol Eng Comput1976143738967172Open DOISearch in Google Scholar

Yamakoshi KI, Ito H, Yamada A, et al. Physiological and fluid-dynamic investigations of the transthoracic impedance plethysmography method for measuring cardiac output: Part 1-A fluid-dynamic approach using an expansible tube model. Med Biol Eng Comput 1976;14:365–72.10.1007/BF02476112YamakoshiKIItoHYamadaAPhysiological and fluid-dynamic investigations of the transthoracic impedance plethysmography method for measuring cardiac output: Part 1-A fluid-dynamic approach using an expansible tube modelMed Biol Eng Comput19761436572967171Open DOISearch in Google Scholar

Nyboer J. Electrical impedance plethysmogrphy; a physical and physiologic approach to peripheral vascular study. Circulation 1950;2:811–21.10.1161/01.CIR.2.6.81114783833NyboerJElectrical impedance plethysmogrphy; a physical and physiologic approach to peripheral vascular studyCirculation1950281121Open DOISearch in Google Scholar

Lamberts R, Visser KR, Zijlstra WG. Impedance Cardiography. Assen, The Netherlands, Van Gorcum; 1984.LambertsRVisserKRZijlstraWGImpedance CardiographyAssen, The Netherlands, Van Gorcum1984Search in Google Scholar

Kubicek WG, Karnegis JN, Patterson RP et al. Development and evaluation of an impedance cardiac output system. Aerosp Med 1966;37:1208–12.5339656KubicekWGKarnegisJNPattersonRPDevelopment and evaluation of an impedance cardiac output systemAerosp Med196637120812Search in Google Scholar

Kubicek WG, Kottke J, Ramos MU, et al. The Minnesota impedance cardiograph-theory and applications. Biomed Eng 1974;9:410–16.4416602KubicekWGKottkeJRamosMUThe Minnesota impedance cardiograph-theory and applicationsBiomed Eng1974941016Search in Google Scholar

Quail AW, Traugott FM, Porges WL, et al. Thoracic resistivity for stroke volume determination in impedance cardiography. J Appl Physiol 1981;50:191–95.10.1152/jappl.1981.50.1.191QuailAWTraugottFMPorgesWLThoracic resistivity for stroke volume determination in impedance cardiographyJ Appl Physiol198150191957204186Open DOISearch in Google Scholar

Bernstein DP. A new stroke volume equation for thoracic electrical bioimpedance: theory and rationale. Crit Care Med 1986;14:904–09.10.1097/00003246-198610000-000173757533BernsteinDPA new stroke volume equation for thoracic electrical bioimpedance: theory and rationaleCrit Care Med198614904093757533Open DOISearch in Google Scholar

Feldschuh J, Enson Y. Prediction of the normal blood volume. Relation of blood volume to body habitus. Circulation 1977;56:605–12.FeldschuhJEnsonYPrediction of the normal blood volumeRelation of blood volume to body habitus. Circulation1977566051210.1161/01.CIR.56.4.605Search in Google Scholar

Djordjevich L, Sadove MS, Mayoral J, et al. Correlation between arterial blood pressure levels and (dZ/dt)min in impedance plethysmography. IEEE Trans Biomed Eng 1985;32:69–73.DjordjevichLSadoveMSMayoralJCorrelation between arterial blood pressure levels and (dZ/dt)min in impedance plethysmographyIEEE Trans Biomed Eng198532697310.1109/TBME.1985.3256323980034Search in Google Scholar

Brown CV, Shoemaker WC, Wo CC, et al. Is noninvasive hemodynamic monitoring appropriate for the elderly critically injured patient? J Trauma 2005;58:102–71567415810.1097/01.TA.0000105990.05074.4ABrownCVShoemakerWCWoCCIs noninvasive hemodynamic monitoring appropriate for the elderly critically injured patient?J Trauma2005581027Search in Google Scholar

Faes TJ, Raaijmakers E, Meijer JH, et al. Towards a theoretical understanding of stroke volume estimation with impedance cardiography. Ann NY Acad Sci 1999;873:128–34.10.1111/j.1749-6632.1999.tb09459.xFaesTJRaaijmakersEMeijerJHTowards a theoretical understanding of stroke volume estimation with impedance cardiographyAnn NY Acad Sci199987312834Open DOISearch in Google Scholar

Bernstein DP, Lemmens HJ. Stroke volume equation for impedance cardiography. Med Biol Eng Comput 2005;43:443–50.1625542510.1007/BF02344724BernsteinDPLemmensHJStroke volume equation for impedance cardiographyMed Biol Eng Comput20054344350Search in Google Scholar

Gardin JM, Burn CS, Childs WJ, et al. Evaluation of blood flow velocity in the ascending aorta and main pulmonary artery of normal subjects by Doppler echocardiography. Am Heart J 1984;107:310–19.10.1016/0002-8703(84)90380-66695664GardinJMBurnCSChildsWJEvaluation of blood flow velocity in the ascending aorta and main pulmonary artery of normal subjects by Doppler echocardiographyAm Heart J198410731019Open DOISearch in Google Scholar

Matsuda Y, Yamada S, Kuragane H, et al. Assessment of left ventricular performance in man with impedance cardiography. Jpn Circ J 1978;42:945–54.10.1253/jcj.42.945731836MatsudaYYamadaSKuraganeHAssessment of left ventricular performance in man with impedance cardiographyJpn Circ J19784294554Open DOISearch in Google Scholar

Lozano DL, Norman G, Knox D, et al. Where to B in dZ/dt. Psychophysiology 2007;44:113–19.LozanoDLNormanGKnoxDWhere to B in dZ/dtPsychophysiology2007441131910.1111/j.1469-8986.2006.00468.xSearch in Google Scholar

Debski TT, Zhang Y, Jennings JR, et al. Stability of cardiac impedance measures: aortic valve opening (B point) detection and scoring. Biol Psychol 1993;36:63–74.10.1016/0301-0511(93)90081-I8218625DebskiTTZhangYJenningsJRStability of cardiac impedance measures: aortic valve opening (B point) detection and scoringBiol Psychol1993366374Open DOISearch in Google Scholar

Adler D, Nikolic SD, Pajaro O, et al. Time to dP/dtmax reflects both inotropic and chronotropic properties of cardiac contraction. Physiol Meas 1996;17:287–9510.1088/0967-3334/17/4/0068953627AdlerDNikolicSDPajaroOTime to dP/dtmax reflects both inotropic and chronotropic properties of cardiac contractionPhysiol Meas199617287958953627Open DOISearch in Google Scholar

Lyseggen E, Rabben SI, Skulstad H, et al. Myocardial acceleration during isovolumic contraction: relationship to contractility. Circulation 2005;111:1362–9.1575321710.1161/01.CIR.0000158432.86860.A6LyseggenERabbenSISkulstadHMyocardial acceleration during isovolumic contraction: relationship to contractilityCirculation20051111362915753217Search in Google Scholar

Welham KC, Mohapatra SN, Hill DW, et al. The first derivative of the transthoracic electrical impedance as an index of changes in myocardial contractility in the intact anaesthetized dog. Intensive Care Med 1978;4:43–50.10.1007/BF01683136WelhamKCMohapatraSNHillDWThe first derivative of the transthoracic electrical impedance as an index of changes in myocardial contractility in the intact anaesthetized dogIntensive Care Med197844350621315Open DOISearch in Google Scholar

Kim DW. Detection of physiologic events by impedance. Yonsei Med J 1989;30:1–11.10.3349/ymj.1989.30.1.1KimDWDetection of physiologic events by impedanceYonsei Med J1989301112662632Open DOISearch in Google Scholar

Rubal BJ, Baker LE, Poder TC. Correlation between maximum dZ/dt and parameters of left ventricular performance. Med Biol Eng Comput 1980;18:541–8.10.1007/BF024431247464275RubalBJBakerLEPoderTCCorrelation between maximum dZ/dt and parameters of left ventricular performanceMed Biol Eng Comput19801854187464275Open DOISearch in Google Scholar

Barbacki M, Gluck A, Sandhage K. Estimation of the correlation between the transcutaneous aortic flow velocity curve and impedance cardiogram in normal children. Cor Vasa 1981;23:291–8.7297075BarbackiMGluckASandhageKEstimation of the correlation between the transcutaneous aortic flow velocity curve and impedance cardiogram in normal childrenCor Vasa1981232918Search in Google Scholar

Winter PJ, Deuchar DC, Noble MI, et al. Relationship between the ballistocardiogram and the movement of blood from the left ventricle in the dog. Cardiovasc Res 1967;1:194–200.605885710.1093/cvr/1.2.194WinterPJDeucharDCNobleMIRelationship between the ballistocardiogram and the movement of blood from the left ventricle in the dogCardiovasc Res196711942006058857Search in Google Scholar

Kubicek WG. On the source of peak first time derivative (dZ/dt) during impedance cardiography. Ann Biomed Eng 1989;17:459–62.261041710.1007/BF02368065KubicekWGOn the source of peak first time derivative (dZ/dt) during impedance cardiographyAnn Biomed Eng198917459622610417Search in Google Scholar

Mohapatra SN, Hill DW. Origin of the impedance cardiogram. In: Mohapatra SN. Non-invasive cardiovascular monitoring by electrical impedance technique. London: Pitman Medical Limited.;1981. P. 41.MohapatraSNHillDWOrigin of the impedance cardiogramMohapatraSNNon-invasive cardiovascular monitoring by electrical impedance techniqueLondonPitman Medical Limited198141Search in Google Scholar

Seitz WS, McIlroy MB. Interpretation of the HJ interval of the normal ballistocardiogram based on the principle of conservation of momentum and aortic ultrasonic Doppler velocity measurements during left ventricular ejection. Cardiovasc Res 1988;22:571–74.10.1093/cvr/22.8.5713073865SeitzWSMcIlroyMBInterpretation of the HJ interval of the normal ballistocardiogram based on the principle of conservation of momentum and aortic ultrasonic Doppler velocity measurements during left ventricular ejectionCardiovasc Res198822571743073865Open DOISearch in Google Scholar

Reeves TJ, Hefner LL, Jones WB, et al. Wide frequency range force ballistocardiogram: its correlation with cardiovascular dynamics. Circulation 1957;16:43–53.1344714910.1161/01.CIR.16.1.43ReevesTJHefnerLLJonesWBWide frequency range force ballistocardiogram: its correlation with cardiovascular dynamicsCirculation195716435313447149Search in Google Scholar

Kolettis M, Jenkins BS, Webb-Peploe MM. Assessment of left ventricular function by indices derived from aortic flow velocity. Br Heart J 1976;38:18–31.125229210.1136/hrt.38.1.18KolettisMJenkinsBSWebb-PeploeMMAssessment of left ventricular function by indices derived from aortic flow velocityBr Heart J19763818314829651252292Search in Google Scholar

Sohn S, Kim HS. Doppler aortic flow velocity measurements in healthy children. J Korean Med Sci 2001;16:140–4.10.3346/jkms.2001.16.2.140SohnSKimHSDoppler aortic flow velocity measurements in healthy childrenJ Korean Med Sci2001161404305471611306737Open DOISearch in Google Scholar

Wallmeyer K, Wann LS, Sagar KB, et al. The influence of preload and heart rate on Doppler echocardiographic indexes of left ventricular performance: comparison with invasive indexes in an experimental preparation. Circulation 1986;74:181–6.10.1161/01.CIR.74.1.181WallmeyerKWannLSSagarKBThe influence of preload and heart rate on Doppler echocardiographic indexes of left ventricular performance: comparison with invasive indexes in an experimental preparationCirculation19867418163085976Open DOISearch in Google Scholar

Ehlert RE, Schmidt HD. An experimental evaluation of impedance cardiographic and electromagnetic measurements of stroke volumes. J Med Eng Technol 1982;6:193–200.10.3109/030919082090410197143415EhlertRESchmidtHDAn experimental evaluation of impedance cardiographic and electromagnetic measurements of stroke volumesJ Med Eng Technol198261932007143415Open DOISearch in Google Scholar

Wallace AW, Salahieh A, Lawrence A, et al. Endotracheal cardiac output monitor. Anesthesiology 2000;92:178–89.10.1097/00000542-200001000-0003010638915WallaceAWSalahiehALawrenceAEndotracheal cardiac output monitorAnesthesiology20009217889Open DOISearch in Google Scholar

Rex S, Brose S, Metzelder S, et al. Prediction of fluid responsiveness in patients during cardiac surgery. Br J Anaesth 2004;93:782–8.10.1093/bja/aeh28015465840RexSBroseSMetzelderSPrediction of fluid responsiveness in patients during cardiac surgeryBr J Anaesth2004937828Open DOISearch in Google Scholar

Della Rocca G, Costa GM, Coccia C, et al. Preload index: pulmonary artery occlusion pressure versus intrathoracic blood volume monitoring during lung transplantation. Anesth Analg 2002;95:835–43.12351254DellaRocca GCostaGMCocciaCPreload index: pulmonary artery occlusion pressure versus intrathoracic blood volume monitoring during lung transplantationAnesth Analg2002958354310.1213/00000539-200210000-00009Search in Google Scholar

Godje O, Peyerl M, Seebauer T, et al. Central venous pressure, pulmonary capillary wedge pressure and intrathoracic blood volumes a preload indicators in cardiac surgery patients. Eur J Cardiothorac Surg 1998;13:533–9.10.1016/S1010-7940(98)00063-39663534GodjeOPeyerlMSeebauerTCentral venous pressure, pulmonary capillary wedge pressure and intrathoracic blood volumes a preload indicators in cardiac surgery patientsEur J Cardiothorac Surg1998135339Open DOISearch in Google Scholar

Kumar A, Anel R, Bunnell E, et al. Pulmonary artery occlusion pressure and central venous pressure fail to predict ventricular filling volume, cardiac performance, or the response to volume infusion in normal subjects. Crit Care Med 2004;32:691–99.1509094910.1097/01.CCM.0000114996.68110.C9KumarAAnelRBunnellEPulmonary artery occlusion pressure and central venous pressure fail to predict ventricular filling volume, cardiac performance, or the response to volume infusion in normal subjectsCrit Care Med20043269199Search in Google Scholar

Lindstedt L, Schaeffer PJ. Use of allometry in predicting anatomical and physiologic parameters of mammals. Lab Anim 2002;36:1–19.10.1258/0023677021911731LindstedtLSchaefferPJUse of allometry in predicting anatomical and physiologic parameters of mammalsLab Anim20023611911833526Open DOISearch in Google Scholar

Feldschuh J, Enson Y. Prediction of normal blood volume: relation of blood volume to body habitus. Circulation 1977;56:605–12.10.1161/01.CIR.56.4.605902387FeldschuhJEnsonYPrediction of normal blood volume: relation of blood volume to body habitusCirculation19775660512902387Open DOISearch in Google Scholar

Collis T, Devereux RB, Roman MJ, et al. Relations of stroke volume and cardiac output to body composition: the strong heart study.Circulation 2001;103:820–5.1117178910.1161/01.CIR.103.6.820CollisTDevereuxRBRomanMJRelations of stroke volume and cardiac output to body composition: the strong heart studyCirculation2001103820511171789Search in Google Scholar

West GB, Brown JH, Enquist BJ. A general model for the origin of allometric scaling laws in biology. Science 1997;276:122–6.908298310.1126/science.276.5309.122WestGBBrownJHEnquistBJA general model for the origin of allometric scaling laws in biologyScience199727612269082983Search in Google Scholar

Holt JP, Rhode A, Kines H. Ventricular volumes and body weight in mammals. Am J Physiol 1968;215:704–15.567101010.1152/ajplegacy.1968.215.3.704HoltJPRhodeAKinesHVentricular volumes and body weight in mammalsAm J Physiol1968215704155671010Search in Google Scholar

Hofer CK, Zalunardo P, Klaghofer R, et al. Changes in intrathoracic blood volume associated with pneumoperitoneum and positioning. Acta Anaesthesiol Scand. 2002;46:303–8.10.1034/j.1399-6576.2002.t01-1-460313.x11939922HoferCKZalunardoPKlaghoferRChanges in intrathoracic blood volume associated with pneumoperitoneum and positioningActa Anaesthesiol Scand2002463038Open DOISearch in Google Scholar

Sageman WS. Reliability and precision of a new thoracic electrical bioimpedance monitor in a lower body negative pressure model. Crit Care Med 1999;27:1986–90.10.1097/00003246-199909000-00044SagemanWSReliability and precision of a new thoracic electrical bioimpedance monitor in a lower body negative pressure modelCrit Care Med199927198690Open DOISearch in Google Scholar

Goldman JH, Schiller NB, Lim DC, et al. usefulness of stroke distance by echocardiography as a surrogate marker of cardiac output that is independent of gender and size in a normal population. Am J Cardiol 2001;87:499–502.10.1016/S0002-9149(00)01417-XGoldmanJHSchillerNBLimDCusefulness of stroke distance by echocardiography as a surrogate marker of cardiac output that is independent of gender and size in a normal populationAm J Cardiol200187499502Open DOISearch in Google Scholar

Young JD, McQuillan P. Comparison of thoracic electrical bioimpedance and thermodilution for the measurement of cardiac index in patients with severe sepsis. Br J Anaesth 1993:70:58–62.YoungJDMcQuillanPComparison of thoracic electrical bioimpedance and thermodilution for the measurement of cardiac index in patients with severe sepsisBr J Anaesth70586210.1093/bja/70.1.588431335Search in Google Scholar

Raaijmakers E, Faes TJ, Kunst PW, et al. The influence of extravascular lung water on cardiac output measurements using thoracic impedance cardiograph. Physiol Meas 1998;19:491–9.10.1088/0967-3334/19/4/004RaaijmakersEFaesTJKunstPWThe influence of extravascular lung water on cardiac output measurements using thoracic impedance cardiographPhysiol Meas19981949199863675Open DOISearch in Google Scholar

Genoni M, Pelosi P, Romand JA, et al. Determination of cardiac output during mechanical ventilation by electrical bioimpedance or thermodilution in patients with acute lung injury: effects of positive end-expiratory pressure. Crit Care Med 1998;26:1441–5.971010710.1097/00003246-199808000-00035GenoniMPelosiPRomandJADetermination of cardiac output during mechanical ventilation by electrical bioimpedance or thermodilution in patients with acute lung injury: effects of positive end-expiratory pressureCrit Care Med199826144159710107Search in Google Scholar

Critchley LA, Calcroft RM, Tan PY, et al. The effect of lung injury and excessive lung fluid, on impedance cardiac output measurements, in the critically ill. Intensive Care Med. 2000;26:679–85.1094538310.1007/s001340051232CritchleyLACalcroftRMTanPYThe effect of lung injury and excessive lung fluid, on impedance cardiac output measurements, in the critically illIntensive Care Med2000266798510945383Search in Google Scholar

Peng ZY, Critchley LA, Fok BS. An investigation to show the effect of lung fluid on impedance cardiac output in the anaesthetized dog. Br J Anaesth 2005;95:458–64.1605165110.1093/bja/aei206PengZYCritchleyLAFokBSAn investigation to show the effect of lung fluid on impedance cardiac output in the anaesthetized dogBr J Anaesth2005954586416051651Search in Google Scholar

Schmidt C, Theilmeier G, Van Aken H, et al. Comparison of electrical velocimetry and transoesophageal Doppler echocardiography for measuring stroke volume and cardiac output. Br J Anaesth 2005;95:603–1010.1093/bja/aei22416155037SchmidtCTheilmeierGVanAken HComparison of electrical velocimetry and transoesophageal Doppler echocardiography for measuring stroke volume and cardiac outputBr J Anaesth2005956031016155037Open DOISearch in Google Scholar

Suttner S, Schollhorn T, Boldt J, et al. Noninvasive assessment of cardiac output using thoracic electrical bioimpedance in hemodynamically stable and unstable patients after cardiac surgery: a comparison with pulmonary artery thermodilution. Intensive Care Med 2006;32:1253–8.SuttnerSSchollhornTBoldtJNoninvasive assessment of cardiac output using thoracic electrical bioimpedance in hemodynamically stable and unstable patients after cardiac surgery: a comparison with pulmonary artery thermodilutionIntensive Care Med2006321253810.1007/s00134-006-0409-x17039348Search in Google Scholar

Norozi K, Thrane L, Manner J, et al. Electrical velocimetry for measuring cardiac output in children with congenital heart disease. Br J Anaesth 2008;100:88–94.1802495410.1093/bja/aem320NoroziKThraneLMannerJElectrical velocimetry for measuring cardiac output in children with congenital heart diseaseBr J Anaesth2008100889418024954Search in Google Scholar

Zoremba N, Bickenbach J, Krauss B, et al. Comparison of electrical velocimetry and thermodilution techniques for the measurement of cardiac output. Acta Anaesthesiol Scand 2007;51:1314–9.1794463310.1111/j.1399-6576.2007.01445.xZorembaNBickenbachJKraussBComparison of electrical velocimetry and thermodilution techniques for the measurement of cardiac outputActa Anaesthesiol Scand2007511314917944633Search in Google Scholar

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