PET radiomics-based lymphovascular invasion prediction in lung cancer using multiple segmentation and multi-machine learning algorithms.

The current study aimed to predict lymphovascular invasion (LVI) using multiple machine learning algorithms and multi-segmentation positron emission tomography (PET) radiomics in non-small cell lung cancer (NSCLC) patients, offering new avenues for personalized treatment strategies and improving patient outcomes. One hundred and twenty-six patients with NSCLC were enrolled in this study. Various automated and semi-automated PET image segmentation methods were applied, including Local Active Contour (LAC), Fuzzy-C-mean (FCM), K-means (KM), Watershed, Region Growing (RG), and Iterative thresholding (IT) with different percentages of the threshold.

Development of novel low-cost readout electronics for large field-of-view gamma camera detectors.

Purpose: Large scintillation crystals-based gamma cameras play a crucial role in nuclear medicine imaging. In this study, a large field-of-view (FOV) gamma detector consisting of 48 square PMTs developed using a new readout electronics, reducing 48 (6 × 8) analog signals to 14 (6 + 8) analog sums of each row and column, with reduced complexity and cost while preserving image quality.

Methods: All 14 analog signals were converted to digital signals using AD9257 high-speed analog to digital (ADC) converters driven by the SPARTAN-6 family of field-programmable gate arrays (FPGA) in order to calculate the signal integrals.

The effect of harmonization on the variability of PET radiomic features extracted using various segmentation methods.

Purpose: This study aimed to examine the robustness of positron emission tomography (PET) radiomic features extracted via different segmentation methods before and after ComBat harmonization in patients with non-small cell lung cancer (NSCLC).

Methods: We included 120 patients (positive recurrence = 46 and negative recurrence = 74) referred for PET scanning as a routine part of their care. All patients had a biopsy-proven NSCLC.

Multimodality radiomics prediction of radiotherapy-induced the early proctitis and cystitis in rectal cancer patients: a machine learning study.

This study aims to predict radiotherapy-induced rectal and bladder toxicity using computed tomography (CT) and magnetic resonance imaging (MRI) radiomics features in combination with clinical and dosimetric features in rectal cancer patients.A total of sixty-three patients with locally advanced rectal cancer who underwent three-dimensional conformal radiation therapy (3D-CRT) were included in this study. Radiomics features were extracted from the rectum and bladder walls in pretreatment CT and MR-T2W-weighted images.

Accurate modeling and performance evaluation of a total-body pet scanner using Monte Carlo simulations.

Background: The limited axial field-of-view (FOV) of conventional clinical positron emission tomography (PET) scanners (∼15 to 26 cm) allows detecting only 1% of all coincidence photons, hence limiting significantly their sensitivity. To overcome this limitation, the EXPLORER consortium developed the world's first total-body PET/CT scanner that significantly increased the sensitivity, thus enabling to decrease the scan duration or injected dose.

Purpose: The purpose of this study is to perform and validate Monte Carlo simulations of the uEXPLORER PET scanner, which can be used to devise novel conceptual designs and geometrical configurations through obtaining features that are difficult to obtain experimentally.

Generation ofF-FDG PET standard scan images from short scans using cycle-consistent generative adversarial network.

To improve positron emission tomography (PET) image quality, we aim to generate images of quality comparable to standard scan duration images using short scan duration (1/8 and 1/16 standard scan duration) inputs and assess the generated standard scan duration images quantitative and qualitatively. Also, the effect of training dataset properties (i.e.

Harmonization based on quantitative analysis of standardized uptake value variations across PET/CT scanners: a multicenter phantom study.

Objectives: This study aimed to measure standardized uptake value (SUV) variations across different PET/computed tomography (CT) scanners to harmonize quantification across systems.

Methods: We acquired images using the National Electrical Manufacturers Association International Electrotechnical Commission phantom from three PET/CT scanners operated using routine imaging protocols at each site. The SUVs of lesions were assessed in the presence of reference values by a digital reference object (DRO) and recommendations by the European Association of Nuclear Medicine (EANM/EARL) to measure inter-site variations.

Potential advantages of FDG-PET radiomic feature map for target volume delineation in lung cancer radiotherapy.

Purpose: To investigate the potential benefits of FDG PET radiomic feature maps (RFMs) for target delineation in non-small cell lung cancer (NSCLC) radiotherapy.

Methods: Thirty-two NSCLC patients undergoing FDG PET/CT imaging were included. For each patient, nine grey-level co-occurrence matrix (GLCM) RFMs were generated.

Synergistic impact of motion and acquisition/reconstruction parameters on F-FDG PET radiomic features in non-small cell lung cancer: Phantom and clinical studies.

Objectives: This study is aimed at examining the synergistic impact of motion and acquisition/reconstruction parameters on F-FDG PET image radiomic features in non-small cell lung cancer (NSCLC) patients, and investigating the robustness of features performance in differentiating NSCLC histopathology subtypes.

Methods: An in-house developed thoracic phantom incorporating lesions with different sizes was used with different reconstruction settings, including various reconstruction algorithms, number of subsets and iterations, full-width at half-maximum of post-reconstruction smoothing filter and acquisition parameters, including injected activity and test-retest with and without motion simulation. To simulate motion, a special motor was manufactured to simulate respiratory motion based on a normal patient in two directions.

Leveraging deep neural networks to improve numerical and perceptual image quality in low-dose preclinical PET imaging.

The amount of radiotracer injected into laboratory animals is still the most daunting challenge facing translational PET studies. Since low-dose imaging is characterized by a higher level of noise, the quality of the reconstructed images leaves much to be desired. Being the most ubiquitous techniques in denoising applications, edge-aware denoising filters, and reconstruction-based techniques have drawn significant attention in low-count applications.

Development and characterization of an all-in-one gamma probe with auto-peak detection for sentinel lymph node biopsy based on NEMA NU3-2004 standard.

Background: A gamma probe is a handheld device used for intraoperative interventions following interstitial injection of a radiotracer to locate regional lymph nodes through the external detection of radiation. This work reports on the design and performance evaluation of a novel fully integrated gamma probe (GammaPen), recently developed by our group.

Materials And Methods: GammaPen is an all-in-one pocket gamma probe with low weight and adequate dimensions, consisting of a detector, a control unit and output all together.

Dynamic functional connectivity in temporal lobe epilepsy: a graph theoretical and machine learning approach.

Purpose: Functional magnetic resonance imaging (fMRI) in resting state can be used to evaluate the functional organization of the human brain in the absence of any task or stimulus. The functional connectivity (FC) has non-stationary nature and consented to be varying over time. By considering the dynamic characteristics of the FC and using graph theoretical analysis and a machine learning approach, we aim to identify the laterality in cases of temporal lobe epilepsy (TLE).

Evaluation of gamma and electron radiations impact on vitamins for onion preservation.

Food irradiation is a process in which food and other consumer products are exposed to gamma rays, X-rays or electron beams after extraction. This method is particularly important in order to reduce infectious agents and to extend the shelf life of the product. The target radiation is done with different devices, so self-sufficient radiation and panoramic radiation -including product and source overlap, planar and categorical radiation- is the major characteristics.

Advances in Preclinical PET Instrumentation.

In the light of ever-increasing demands for PET scanner with better resolvability, higher sensitivity and wide accessibility for noninvasive screening of small structures and physiological processes in laboratory rodents, several dedicated PET scanners were developed and evaluated. Understanding conceptual design constraints pros and cons of different configurations and impact of the major components will be helpful to further establish the crucial role of these miniaturized systems in a broad spectrum of modern research. Hence, a comprehensive review of preclinical PET scanners developed till early 2020 with particular emphasis on innovations in instrumentation and geometrical designs is provided.

RADIATION DOSE ASSESSMENT TO FAMILY MEMBERS TAKING CARE OF NON-CANCEROUS THYROID PATIENTS TREATED WITH I-131 THERAPY IN NUCLEAR MEDICINE DEPARTMENT.

This study aimed to determine the effective doses of caregivers taking care of non-cancerous patients treated with iodine-131 (I-131). Patients (administered 185-1110 MBq of I-131) were given specific radiation safety instructions (RSI). Afterwards, caregivers were provided with thermoluminescent (TLD) dosimeter badges to be worn for 12-28 days when taking care of the patients.

Deep-JASC: joint attenuation and scatter correction in whole-body F-FDG PET using a deep residual network.

Objective: We demonstrate the feasibility of direct generation of attenuation and scatter-corrected images from uncorrected images (PET-nonASC) using deep residual networks in whole-body F-FDG PET imaging.

Methods: Two- and three-dimensional deep residual networks using 2D successive slices (DL-2DS), 3D slices (DL-3DS) and 3D patches (DL-3DP) as input were constructed to perform joint attenuation and scatter correction on uncorrected whole-body images in an end-to-end fashion. We included 1150 clinical whole-body F-FDG PET/CT studies, among which 900, 100 and 150 patients were randomly partitioned into training, validation and independent validation sets, respectively.

Guidelines for TMS/tES clinical services and research through the COVID-19 pandemic.

Background: The COVID-19 pandemic has broadly disrupted biomedical treatment and research including non-invasive brain stimulation (NIBS). Moreover, the rapid onset of societal disruption and evolving regulatory restrictions may not have allowed for systematic planning of how clinical and research work may continue throughout the pandemic or be restarted as restrictions are abated. The urgency to provide and develop NIBS as an intervention for diverse neurological and mental health indications, and as a catalyst of fundamental brain research, is not dampened by the parallel efforts to address the most life-threatening aspects of COVID-19; rather in many cases the need for NIBS is heightened including the potential to mitigate mental health consequences related to COVID-19.

Standard SPECT myocardial perfusion estimation from half-time acquisitions using deep convolutional residual neural networks.

Introduction: The purpose of this work was to assess the feasibility of acquisition time reduction in MPI-SPECT imaging using deep leering techniques through two main approaches, namely reduction of the acquisition time per projection and reduction of the number of angular projections.

Methods: SPECT imaging was performed using a fixed 90° angle dedicated dual-head cardiac SPECT camera. This study included a prospective cohort of 363 patients with various clinical indications (normal, ischemia, and infarct) referred for MPI-SPECT.

Performance evaluation of developed dedicated breast PET scanner and improvement of the spatial resolution by wobbling: a Monte Carlo study.

Purpose: Molecular imaging, particularly PET scanning, has become an important cancer diagnostic tool. Whole-body PET is not effective for local staging of cancer because of their declining efficiency in detecting small lesions. The preliminary results of the performance evaluation of designed dedicated breast PET scanner presented.

Computationally Efficient System Matrix Calculation Techniques in Computed Tomography Iterative Reconstruction.

Background: Relative to classical methods in computed tomography, iterative reconstruction techniques enable significantly improved image qualities and/or lowered patient doses. However, the computational speed is a major concern for these iterative techniques. In the present study, we present a method for fast system matrix calculation based on the line integral model (LIM) to speed up the computations without compromising the image quality.

The impact of iterative reconstruction protocol, signal-to-background ratio and background activity on measurement of PET spatial resolution.

Objectives: The present study aims to assess the impact of acquisition time, different iterative reconstruction protocols as well as image context (including contrast levels and background activities) on the measured spatial resolution in PET images.

Methods: Discovery 690 PET/CT scanner was used to quantify spatial resolutions in terms of full width half maximum (FWHM) as derived (i) directly from capillary tubes embedded in air and (ii) indirectly from 10 mm-diameter sphere of the NEMA phantom. Different signal-to-background ratios (SBRs), background activity levels and acquisition times were applied.

Joint compensation of motion and partial volume effects by iterative deconvolution incorporating wavelet-based denoising in oncologic PET/CT imaging.

Objectives: We aim to develop and rigorously evaluate an image-based deconvolution method to jointly compensate respiratory motion and partial volume effects (PVEs) for quantitative oncologic PET imaging, including studying the impact of various reconstruction algorithms on quantification performance.

Procedures: An image-based deconvolution method that incorporated wavelet-based denoising within the Lucy-Richardson algorithm was implemented and assessed. The method was evaluated using phantom studies with signal-to-background ratios (SBR) of 4 and 8, and clinical data of 10 patients with 42 lung lesions ≤30 mm in diameter.

NEMA NU-4 2008 performance evaluation of Xtrim-PET: A prototype SiPM-based preclinical scanner.

Purpose: Xtrim-PET is a newly designed Silicon Photomultipliers (SiPMs)-based prototype PET scanner dedicated for small laboratory animal imaging. We present the performance evaluation of the Xtrim-PET scanner following NEMA NU-4 2008 standards to help optimizing scanning protocols which can be achieved through standard and reliable system performance characterization.

Methods: The performance assessment was conducted according to the National Electrical Manufacturers Association (NEMA) NU-4 2008 standards in terms of spatial resolution, sensitivity, counting rate performance, scatter fraction and image quality.

Targeted gold nanoparticles enable molecular CT imaging of head and neck cancer: An in vivo study.

The development of various cost-effective multifunctional contrast agent for specific targeting molecular imaging of tumors presents a great challenge. We report here the in vivo targeting imaging of folic acid (FA) gold nanoparticles (AuNPs) through cysteamine (Cys) linking for targeted of human nasopharyngeal head and neck cancer by computed tomography (CT). The toxicity of nanoparticles in kidney, heart, spleen, brain and liver was evaluated by H&E (hematoxylin and eosin) assay.