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Imaging perfusion changes in oncological clinical applications by hyperspectral imaging: a literature review

Rok Hren

Rok Hren

  • Faculty of Mathematics and Physics, University of LjubljanaLjubljana, Slovenia
  • Institute of Mathematics, Physics, and MechanicsLjubljana, Slovenia
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Hren, Rok
, 
Gregor Sersa

Gregor Sersa

Institute of Oncology LjubljanaLjubljana, Slovenia
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Sersa, Gregor
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Urban Simoncic

Urban Simoncic

  • Faculty of Mathematics and Physics, University of LjubljanaLjubljana, Slovenia
  • Jozef Stefan InstituteLjubljana, Slovenia
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Simoncic, Urban
 et 
Matija Milanic

Matija Milanic

  • Faculty of Mathematics and Physics, University of LjubljanaLjubljana, Slovenia
  • Jozef Stefan InstituteLjubljana, Slovenia
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Milanic, Matija
  
13 déc. 2022
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Catégorie d'article: review
Publié en ligne: 13 déc. 2022
Pages: 420 - 429
Reçu: 27 oct. 2022
Accepté: 02 nov. 2022
DOI: https://doi.org/10.2478/raon-2022-0051
Mots clés
© 2022 Rok Hren, Gregor Sersa, Urban Simoncic, Matija Milanic, published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.

Figure 1

Structure and composition of hyperspectral images and physiological parameters derived from the images, which are typically displayed in false color. NIR PI = near-infrared perfusion index; OHI = organ hemoglobin index; StO2 = oxygen saturation of tissue; TWI = tissue water index
Structure and composition of hyperspectral images and physiological parameters derived from the images, which are typically displayed in false color. NIR PI = near-infrared perfusion index; OHI = organ hemoglobin index; StO2 = oxygen saturation of tissue; TWI = tissue water index

Figure 2

Flow diagram of the selection strategy. Taken from Pfahl et al.15 and reprinted with permission from the publisher.
Flow diagram of the selection strategy. Taken from Pfahl et al.15 and reprinted with permission from the publisher.

Figure 3

Images of the kidney depicting the percentage of HbO2 as a function of color. A dark red represents high values while the yellows and greens indicate lower values. Taken from Best et al.34 and reprinted with permission from the publisher.
Images of the kidney depicting the percentage of HbO2 as a function of color. A dark red represents high values while the yellows and greens indicate lower values. Taken from Best et al.34 and reprinted with permission from the publisher.

Figure 4

(A) Red-Green-Blue (RGB) representation of the imaged brain, including normal and tumor tissue. (B) Extraction of blood vessels from hyperspectral images using the spectral angle mapper algorithm (SAM). (C) Tissue classification map generated from hyperspectral images: tumor tissue is red, normal tissue is green, blood vessels are blue, and background is black. Taken from Fabelo et al.38 and reprinted with permission from the publisher.
(A) Red-Green-Blue (RGB) representation of the imaged brain, including normal and tumor tissue. (B) Extraction of blood vessels from hyperspectral images using the spectral angle mapper algorithm (SAM). (C) Tissue classification map generated from hyperspectral images: tumor tissue is red, normal tissue is green, blood vessels are blue, and background is black. Taken from Fabelo et al.38 and reprinted with permission from the publisher.

Figure 5

Comparison of Red-Green-Blue (RGB) images and near-infrared perfusion index (NIR PI) images recorded in a patient with (A, B) and without postoperative anastomotic insufficiency (C, D). Taken from Köhler et al.9 and reprinted with permission from the publisher.
Comparison of Red-Green-Blue (RGB) images and near-infrared perfusion index (NIR PI) images recorded in a patient with (A, B) and without postoperative anastomotic insufficiency (C, D). Taken from Köhler et al.9 and reprinted with permission from the publisher.

Figure 6

Hyperspectral imaging (HSI) acquisition system in the operating room. Hyperspectral images were acquired within a few seconds with physiologic HSI parameters displayed in false colors. Taken from Moulla et al.45 and reprinted with permission from the publisher.
Hyperspectral imaging (HSI) acquisition system in the operating room. Hyperspectral images were acquired within a few seconds with physiologic HSI parameters displayed in false colors. Taken from Moulla et al.45 and reprinted with permission from the publisher.

Figure 7

Usefulness of hyperspectral imaging (HSI) in establishing transection line during colorectal surgery. The Red-Green-Blue (RGB) image (A) and StO2 map (B) show a patient in whom the clinical transection line (continuous line in black) and HSI transection line (dotted line in blue) were aligned; (C) and (D) show the RGB image and StO2 map, respectively, of a patient in whom the clinical transection line deviated from the HSI transection line. Taken from Barberio et al.51 and reprinted with permission from the publisher.
Usefulness of hyperspectral imaging (HSI) in establishing transection line during colorectal surgery. The Red-Green-Blue (RGB) image (A) and StO2 map (B) show a patient in whom the clinical transection line (continuous line in black) and HSI transection line (dotted line in blue) were aligned; (C) and (D) show the RGB image and StO2 map, respectively, of a patient in whom the clinical transection line deviated from the HSI transection line. Taken from Barberio et al.51 and reprinted with permission from the publisher.

Included articles reporting the use of hyperspectral imaging (HSI) to quantify perfusion changes in clinical applications in oncology

Reference Year of publication Number of patients Oncologic intervention System Algorithm
Kidneys
Best34 Eye 2013 26 Partial nephrectomy DLP HSI, 520–645 nm Supervised multivariate least squares regression
Rose35 Breasts 2018 8 Radiation retinopathy Tunable laser, 520–620 nm with 5 nm steps PHYSPEC software (Photon etc., Montreal, QC, Canada)
Chin36 2017 43 Skin response to radiation OxyVu-2TM (Hypermed, Inc., Waltham, MA), 500–600 nm The OxyVu-2TM software (Hypermed, Inc., Waltham, MA)
Pruimboom8 2022 10 Mastectomy skin flap necrosis TIVITA™ (Diaspective Vision GmbH, Am Salzhaff, Germany), 500– 1000 nm with 5 nm step TIVITA™ (Diaspective Vision GmbH, Am Salzhaff, Germany)
Brain
Fabelo37 2018 22 Craniotomy for resection of intraaxial brain tumor Hyperspec VNIR A-Series (HeadWall Photonics, Massachusetts, USA), 400–1000 nm Spectral angle mapper
Fabelo38 2018 5 Craniotomy for resection of intraaxial brain tumor; all 5 patients with grade IV glioblastoma As in Fabelo37 As in Fabelo37
Fabelo39 2019 6 Craniotomy for resection of intra-axial brain tumor; all 6 patients with grade IV glioblastoma As in Fabelo37 As in Fabelo37
Fabelo40 2019 22 Craniotomy for resection of intraaxial brain tumor As in Fabelo37 As in Fabelo37
Entire GI tract
Jansen-Winkeln41 [Article in German] 2018 47 Gastrointestinal surgery with esophageal, gastric, pancreatic, small bowel or colorectal anastomoses As in Pruimboom8 As in Pruimboom8
Upper GI tract
Kohler9 2019 22 Hybrid or open esophagectomy followed by reconstruction of gastric conduit As in Pruimboom8 As in Pruimboom8
Moulla42 [Article in German] 2020 Video presentation of hybrid esophagectomy As in Pruimboom8 As in Pruimboom8
Schwandner43 2020 4 Hybrid esophagectomy followed by reconstructing gastric conduit As in Pruimboom8 As in Pruimboom8
Hennig44 2021 13 Hybrid esophagectomy followed by reconstructing gastric conduit As in Pruimboom8 As in Pruimboom8
Moulla45 2021 20 Pancreatoduodenectomy As in Pruimboom8 As in Pruimboom8
Lower GI tract
Jansen-Winkeln46 2019 24 Colorectal resection As in Pruimboom8 As in Pruimboom8
Jansen-Winkeln47 2020 32 Colorectal resection As in Pruimboom8 As in Pruimboom8
Pfahl48 2022 128 Colorectal resection As in Pruimboom8 As in Pruimboom8
Jansen-Winkeln49 2021 54 Colorectal resection As in Pruimboom8 As in Pruimboom8
Jansen-Winkeln50 2022 115 Colorectal resection As in Pruimboom8 As in Pruimboom8
Barberio51 2022 52 Colorectal resection As in Pruimboom8 As in Pruimboom8
Langue:
Anglais
Périodicité:
4 fois par an
Sujets de la revue:
Médecine, Médecine clinique, Médecine interne, Hématologie, oncologie, Radiologie
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