Volume 18 (2022): Issue 1 (December 2022)

Objectives: Intervertebral disc segmentation is one of the methods to diagnose spinal disease through the degeneration in asymptomatic and symptomatic patients. Even though numerous intervertebral disc segmentation techniques are available, classifying the grades in the inter-vertebral disc is a hectic challenge in the existing disc segmentation methods. Thus, an effective Whale Spine-Generative Adversarial Network (WSpine-GAN) method is proposed to segment the intervertebral disc for effective grade classification.

Methods: The proposed WSpine-GAN method effectively performs the disc segmentation, wherein the weights of Spine-GAN are optimally tuned using Whale Optimization Algorithm (WOA). Then, the refined disc features, such as pixel-based features and the connectivity features are extracted. Finally, the K-Nearest Neighbor (KNN) classifier based on the pfirrmann’s grading system performs the grade classification.

Results: The implementation of the grade classification strategy based on the proposed WSpine-GAN and KNN is performed using the real-time database, and the performance based on the metrics yielded the accuracy, true positive rate (TPR), and false positive rate (FPR) values of 97.778, 97.83, and 0.586% for the training percentage and 92.382, 90.580, and 1.972% for the K-fold value.

Conclusions: The proposed WSpine-GAN method effectively performs the disc segmentation by integrating the Spine-GANmethod and WOA. Here, the spinal cord images are segmented using the proposed WSpine-GAN method by tuning the weights optimally to enhance the performance of the disc segmentation.

Objectives: To make a clear literature review on state-ofthe-art heart disease prediction models.

Methods: It reviews 61 research papers and states the significant analysis. Initially, the analysis addresses the contributions of each literature works and observes the simulation environment. Here, different types of machine learning algorithms deployed in each contribution. In addition, the utilized dataset for existing heart disease prediction models was observed.

Results: The performance measures computed in entire papers like prediction accuracy, prediction error, specificity, sensitivity, f-measure, etc., are learned. Further, the best performance is also checked to confirm the effectiveness of entire contributions.

Conclusions: The comprehensive research challenges and the gap are portrayed based on the development of intelligent methods concerning the unresolved challenges in heart disease prediction using data mining techniques.

Objectives: This paper proposed the neural network-based segmentation model using Pre-trained Mask Convolutional Neural Network (CNN) with VGG-19 architecture. Since ovarian is very tiny tissue, it needs to be segmented with higher accuracy from the annotated image of ovary images collected in dataset. This model is proposed to predict and suppress the illness early and to correctly diagnose it, helping the doctor save the patient’s life.

Methods: The paper uses the neural network based segmentation using Pre-trained Mask CNN integrated with VGG-19 NN architecture for CNN to enhance the ovarian cancer prediction and diagnosis.

Results: Proposed segmentation using hybrid neural network of CNN will provide higher accuracy when compared with logistic regression, Gaussian naïve Bayes, and random Forest and Support Vector Machine (SVM) classifiers.

Quantitative imaging (i.e., providing not just an image but also the related data) guidance in proton radiation therapy to achieve and monitor the precision of planned radiation energy deposition field in-vivo (a.k.a. proton range verification) is one of the most under-invested aspects of radiation cancer treatment despite that it may dramatically enhance the treatment accuracy and lower the exposure related toxicity improving the entire outcome of cancer therapy. In this article, we briefly describe the effort of the TPPT Consortium (a collaborative effort of groups from the University of Texas and Portugal) on building a time-of-flight positron-emission-tomography (PET) scanner to be used in pre-clinical studies for proton therapy at MD Anderson Proton Center in Houston. We also discuss some related ideas towards improving and expanding the use of PET detectors, including the total body imaging.

In this article, we present the geometrical design and preliminary results of a high sensitivity organ-specific Positron Emission Tomography (PET) system dedicated to the study of the human brain. The system, called 4D-PET, will allow accurate imaging of brain studies due to its expected high sensitivity, high 3D spatial resolution and, by including precise photon time of flight (TOF) information, a boosted signal-to-noise ratio (SNR).

The 4D-PET system incorporates an innovative detector design based on crystal slabs (semi-monolithic) that enables accurate 3D photon impact positioning (including photon Depth of Interaction (DOI) measurement), while providing a precise determination of the photon arrival time to the detector. The detector includes a novel readout system that reduces the number of detector signals in a ratio of 4:1 thus, alleviating complexity and cost. The analog output signals are fed to the TOFPET2 ASIC (PETsys) for scalability purposes.

The present manuscript reports the evaluation of the 4D-PET detector, achieving best values 3D resolution values of <1.6 mm (pixelated axis), 2.7±0.5 mm (monolithic axis) and 3.4±1.1 (DOI axis) mm; 359 ± 7 ps coincidence time resolution (CTR); 10.2±1.5 % energy resolution; and sensitivity of 16.2% at the center of the scanner (simulated). Moreover, a comprehensive description of the 4D-PET architecture (that includes 320 detectors), some pictures of its mechanical assembly, and simulations on the expected image quality are provided.

Cascade nuclides emit two or more gamma rays successively through an intermediate state. The coincidence detection of cascade gamma rays provides several advantages in gamma-ray imaging. In this review article, three applications of the double photon coincidence method are reviewed. Double-photon emission imaging with mechanical collimators and Compton double-photon emission imaging can identify radioactive source positions with their angular-resolving detectors, and reduce the crosstalk between nuclides. In addition, a novel method of coincidence Compton imaging is proposed by taking coincidence detection between a Compton event and a photopeak events. Although this type of coincidence Compton imaging cannot specify the location, it can be useful in multi-nuclide Compton imaging.

Multi-molecule imaging and inter-molecular imaging are not fully implemented yet, however, can become an alternative in nuclear medicine. In this review article, we present arguments demonstrating that the advent of the Compton positron emission tomography (Compton-PET) system and the invention of the quantum chemical sensing method with double photon emission imaging (DPEI) provide realistic perspectives for visualizing inter-molecular and multi-molecule in nuclear medicine with MeV photon. In particular, the pH change of InCl3 solutions can be detected and visualized in a three-dimensional image by combining the hyperfine electric quadrupole interaction sensing and DPEI. Moreover, chemical states, such as chelating, can be detected through angular correlation sensing. We argue that multi-molecule and chemical sensing could be a realistic stream of research in future nuclear medicine.

We develop a positronium imaging method for the Jagiellonian PET (J-PET) scanners based on the time-of-flight maximum likelihood expectation maximisation (TOF MLEM). The system matrix elements are calculated on-the-fly for the coincidences comprising two annihilation and one de-excitation photons that originate from the ortho-positronium (o-Ps) decay. Using the Geant4 library, a Monte Carlo simulation was conducted for four cylindrical ²²Na sources of β⁺ decay with diverse o-Ps mean lifetimes, placed symmetrically inside the two JPET prototypes. The estimated time differences between the annihilation and the positron emission were aggregated into histograms (one per voxel), updated by the weights of the activities reconstructed by TOF MLEM. The simulations were restricted to include only the o-Ps decays into back-to-back photons, allowing a linear fitting model to be employed for the estimation of the mean lifetime from each histogram built in the log scale. To suppress the noise, the exclusion of voxels with activity below 2% – 10% of the peak was studied. The estimated o-Ps mean lifetimes were consistent with the simulation and distributed quasi -uniformly at high MLEM iterations. The proposed positronium imaging technique can be further upgraded to include various correction factors, as well as be modified according to realistic o-Ps decay models.

Background: Boron Neutron Capture Therapy (BNCT) is a two-step treatment that can be used in some types of cancers. It involves administering a compound containing boron atoms to the patient and irradiating the affected area of the body with a neutron beam. The success of the therapy depends mainly on the delivery of the boron isotope (10B) to the tumor using an appropriate boron carrier. One of the boron carriers used is boronophenylalanine (BPA). Therefore, in research on the use of boron carriers, it is also important to know the mechanisms of its uptake by cells. Aim: To study the expression of LAT family genes in two melanoma (high melanotic WM115 and low melanotic WM266-4) cell lines and melanocytes (HEMa-Lp) which are responsible for the transport the BPA into cells. Methods: To normalize data from the transcriptomic analysis, the ratio of the median method was used. This allowed the samples to be compared with each other. Comparison metrics included log-fold change (LFC) values. The heatmap of LFC values and the cluster map were created. These graphs show the similarities and differences between the samples. Results: Transcriptomic data show that in melanocytes, LFC for SLC7A5 (LAT1) and SLC3A2 (4Fhc) was higher than in melanoma cell lines, which corresponded with their melanin content. Conclusion: Our results indicate overexpression of BPA transporter genes in normal cells (melanocytes), which may suggest the highest level of these proteins in melanocytes compared to less melanotic melanoma. Therefore, for BNCT, the use of BPA as the 10B carrier will require additional qualifying tests of amino acid transporter expression for patients and specific tumors to develop a personalized BNCT.

Introduction

Cargo carried by extracellular vesicles (EVs) is considered a promising diagnostic marker, especially proteins. EVs can be divided according to their size and way of biogenesis into exosomes (diameter < 200 nm) and ectosomes (diameter > 200 nm). Exosomes are considered to be of endocytic origin, and ectosomes are produced by budding and shedding from the plasma membrane [1].

Methods

The first step of this study was a characterization of the exosome sample. Using Tunable Resistive Pulse Sensing (qNano) size distribution and concentration were measured. The mean size of exosomes was 120±9.17 nm. In the present study, a nano liquid chromatography coupled with tandem mass spectrometry (nanoLCMS/MS) was used to compare protein profiles of exosomes secreted by pancreatic beta cells (1.1B4) grown under normal glucose (NG, 5 mM D-glucose) and high glucose (HG, 25 mM D-glucose) conditions. The EV samples were lysed, and proteins were denatured, digested, and analyzed using a Q-Exactive mass spectrometer coupled with the UltiMate 3000 RSLC nano system. The nanoLC-MS/MS data were searched against the SwissProt Homo sapiens database using MaxQuant software and protein quantitation was done by the MaxLFQ algorithm. Statistical analysis was carried out with Perseus software. Further bioinformatic analysis was performed using the FunRich 3.1.4 software with the UniProt protein database and String [2].

Results

As a result of the nanoLC-MS/MS analysis more than 1,000 proteins were identified and quantified in each sample. The average number of identified proteins in exosomes was 1,397. Label-free quantitative analysis showed that exosome composition differed significantly between those isolated under NG and HG conditions. Many pathways were down-regulated in HG, particularly the ubiquitin-proteasome pathway. In addition, a significant up-regulation of the Ras-proteins pathway was observed in HG.

Conclusion

Our description of exosomes protein content and its related functions provides the first insight into the EV interactome and its role in glucose intolerance development and diabetic complications. The results also indicate the applicability of EV proteins for further investigation regarding their potential as circulating in vivo biomarkers.

Background Lugol’s solution is well known for its unique contrasting properties to biological samples in in microcomputed tomography imaging. On the other hand, iron oxide nanoparticles (IONPs), which have much lower attenuation capabilities to X-ray radiation show decent cell penetration and accumulation properties, are increasingly being used as quantitative contrast agents in biology and medicine. In our research, they were used to stain 3D cell structures called spheroids. Aim In this study, the micro computed tomography (µCT) technique was used to visualize and compare the uptake and accumulation of two contrast agents, Lugol’s solution and iron (II, III ) oxid e nanoparticles (IONPs) in the in vitro human spheroid tumour model. Methods The metastatic human melanoma cell line WM266-4 was cultured, first under standard 2D conditions, and after reaching 90% confluence cells was seeded in a low adhesive plate, which allows spheroid formation. On the 7th day of growth, the spheroids were transferred to the tubes and stained with IONPs or Lugol’s solution and subjected to µCT imaging. Results Our research allows visualization of the regions of absorption at the level of single cells, with relatively short incubation times - 24h - for Lugol’s solution. IONPs proved to be useful only in high concentrations (1 mg/ml) and long incubation times (96h). Conclusions When comparing the reconstructed visualizations of the distribution of these stating agents, it is worth noting that Lugol’s solution spreads evenly throughout the spheroids, whereas IONPs (regardless of their size 5 and 30 nm) accumulate only in the outer layer of the spheroid structure.

Positron-electron annihilation in living organisms occurs in about 30% via the formation of a metastable ortho-positronium atom that annihilates into two 511 keV photons in tissues because of the pick-off and conversion processes. Positronium (Ps) annihilation lifetime and intensities can be used to determine the size and quantity of defects in a material’s microstructure, such as voids or pores in the range of nanometers. This is particularly true for blood clots. Here we present pilot investigations of positronium properties in fibrin clots. The studies are complemented by the use of SEM Edax and micro-computed tomography (µCT) to evaluate the extracted thrombotic material’s properties. µCT is a versatile characterization method offering in situ and in operando possibilities and is a qualitative diagnostic tool. With µCT the presence of pores, cracks, and structural errors can be verified, and hence the 3D inner structure of samples can be investigated.

Objectives: Extracellular vesicles (EVs) are heterogeneous membrane vesicles in diameter of 30-5000 nm, that transport proteins, non-coding RNAs (miRNAs), lipids and metabolites. Major populations include exosomes, ectosomes and apoptotic bodies. The purpose of this study was to compare the distribution of EVs obtained under different conditions of differential centrifugation, including ultracentrifugation, with the results developed based on a theoretical model. Methods: Immortalized endothelial cell line that expresses h-TERT (human telomerase) was used to release of EVs: microvascular TIME. EVs were isolated from the culture medium at different centrifugation parameters. The size distribution of the EVs was measured using TRPS technology on a qNano instrument.