Search Results (156)

Background/Objectives: Preclinical chest computed tomography (CT) imaging in small animals is often limited by low resolution due to scan time and dose constraints, which hinders accurate detection of subtle lesions. Traditional super-resolution (SR) metrics, such as peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM), may not adequately reflect clinical interpretability. We aimed to evaluate whether deep learning-based SR models could enhance image quality and lesion detectability in rat chest CT, balancing quantitative metrics with radiologist assessment. Methods: We retrospectively analyzed 222 chest CT scans acquired from polyhexamethylene guanidine phosphate (PHMG-p) exposure studies in Sprague Dawley rats. Three SR models were implemented and compared: single-image SR (SinSR), segmentation-guided SinSR with lung cropping (SinSR3), and omni-super-resolution (OmniSR). Models were trained on rat CT data and evaluated using PSNR and SSIM. Two board-certified thoracic radiologists independently performed blinded evaluations of lesion margin clarity, nodule detectability, image noise, artifacts, and overall image quality. Results: SinSR1 achieved the highest PSNR (33.64 ± 1.30 dB), while SinSR3 showed the highest SSIM (0.72 ± 0.08). Despite lower PSNR (29.21 ± 1.46 dB), OmniSR received the highest radiologist ratings for lesion margin clarity, nodule detectability, and overall image quality (mean score 4.32 ± 0.41, κ = 0.74). Reader assessments diverged from PSNR and SSIM, highlighting the limited correlation between conventional metrics and clinical interpretability. Conclusions: Deep learning-based SR improved visualization of rat chest CT images, with OmniSR providing the most clinically interpretable results despite modest numerical scores. These findings underscore the need for reader-centered evaluation when applying SR techniques to preclinical imaging. Full article

Background: Sarcopenia is characterized by a loss of muscle mass and strength, resulting in functional limitations and an increased risk of falls, injuries and fractures. The aim of this study was to obtain detailed information on skeletal muscle changes in patients with multiple myeloma (MM) during treatment. Methods: A total of 51 patients diagnosed with MM who had undergone whole-body low-dose computed tomography acquisition prior to induction therapy (T1) and post autologous stem cell transplantation (T2) were examined retrospectively. Total volume (TV), muscle volume (MV) and intramuscular adipose tissue volume (IMAT) of the autochthonous back muscles, the iliopsoas muscle and the gluteal muscles were evaluated on the basis of the resulting masks of the BOA tool with the fully automated combination of TotalSegmentator and a body composition analysis. An in-house trained artificial intelligence network was used to obtain a fully automated three-dimensional segmentation assessment. Results: Patients’ median age was 58 years (IQR 52–66), 38 were male and follow-up CT-scans were performed after a mean of 11.8 months (SD ± 3). Changes in MV and IMAT correlated significantly with Body-Mass-Index (BMI) (r = 0.7, p < 0.0001). Patients (n = 28) with a decrease in BMI (mean −2.2 kg/m²) during therapy lost MV (T1: 3419 cm³, IQR 3176–4000 cm³ vs. T2: 3226 cm³, IQR 3014–3662 cm³, p < 0.0001) whereas patients (n = 20) with an increased BMI (mean +1.4 kg/m²) showed an increase in IMAT (T1: 122 cm³, IQR 96.8–202.8 cm³ vs. T2: 145.5 cm³, IQR 115–248 cm³, p = 0.0002). Loss of MV varied between different muscle groups and was most prominent in the iliopsoas muscle (−9.8%) > gluteus maximus (−9.1%) > gluteus medius (−5.8%) > autochthonous back muscles (−4.3%) > gluteus minimus (−1.5%). Increase in IMAT in patients who gained weight was similar between muscle groups. Conclusions: The artificial intelligence-based three-dimensional segmentation process is a reliable and time-saving method to acquire in-depth information on sarcopenia in MM patients. Loss of MV and increase in IMAT were reliably detectable and associated with changes in BMI. Loss of MV was highest in muscles with more type 2 muscle fibers (fast-twitch, high energy) whereas muscles with predominantly type 1 fibers (slow-twitch, postural control) were less affected. This study provides valuable insight into muscle changes of MM patients during treatment, which might aid in tailoring exercise interventions more precisely to patients’ needs. Full article

Background: ErisNet, a novel AI model to reduce noise in Computed Tomography images. Methods: We trained ErisNet on 23 post-mortem whole-body CT scans. We assessed the objective performance with mean square error (MSE), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM) measure, visual information fidelity (VIF), edge preservation index (EPI) and noise variance (NV). We assessed the qualitative performance by six radiologists. To support the visual assessment, we placed circular regions of interest (ROI) in the vitreous body, brain, liver and spleen parenchyma and paravertebral muscle. Results: ErisNet achieved MSE 64.07 ± 46.81, PSNR 31.32 ± 3.69 dB, SSIM 0.93 ± 0.06, VIF 0.49 ± 0.09, EPI 0.97 ± 0.01 and NV 64.69 ± 46.80. The ROI analysis showed a reduction in noise: the SD of the HU decreased by 8% in the vitreous body (from 17.6 to 16.2 HU), by 18% in the brain parenchyma (from 18.85 to 15.40 HU) and by 15–19% in the liver, spleen and paravertebral muscle. The six radiologists confirmed these results by assigning high scores (scale from one to five): overall quality 4.5 ± 0.6, noise suppression/detail preservation 4.7 ± 0.5 and diagnostic confidence 4.8 ± 0.4 (p < 0.01). Conclusions: ErisNet improves the quality of CT images and shows strong potential for processing low-dose scans. Full article

Reducing radiation exposure in CT imaging is critical, particularly in routine and repeat examinations. Deep learning image reconstruction (DLIR) has emerged as a key approach for maintaining diagnostic quality at low-dose acquisition settings. This study compared two DLIR algorithms of Philips Precise Image (PI) and GE TrueFidelity (TF) under an 80 kVp low-dose CT scenario, using the AAPM CIRS-610 phantom to replicate clinical imaging conditions. The phantom’s linearity, high-resolution, and artifact modules were scanned with Philips CT 5300 and GE Revolution CT scanners at low-dose parameters. Images were reconstructed using five DLIR presets, including PI (Smoother, Standard, Sharper) and TF (Middle, High), and evaluated with eight quantitative metrics, including SNR, CNR, nRMSE, PSNR, SSIM, FSIM, UQI, GMSD, and gradient magnitude. TF-High delivered the highest SNR (115.0–118.0 across modules), representing a 54–57% improvement over PI-Smoother, and achieved superior PSNR and the lowest GMSD, reflecting better preservation of structure in low-dose images. PI-Sharper provided the strongest gradient magnitude, emphasizing fine edge detail. Under low-dose CT conditions, TF-High offered the optimal balance of noise suppression and structure fidelity, while PI-Sharper highlighted fine detail enhancement. These findings show that DLIR settings must be tailored to clinical needs when operating under low-dose imaging protocols. Full article

An open question in radiobiology concerns whether low doses of radiation are harmful or if cells are able to tolerate such exposure with minimal or no disruption. This issue is relevant for evaluating public health risks associated with the increasing number of medical computed tomography (CT) diagnostic procedures. This study evaluated the impact of CT scan-level exposure on human adipose mesenchymal stem cells (hMSCs) by measuring DNA damage responses (γH2AX, 53BP1, pATM foci), proliferation (Ki-67), senescence (β-galactosidase), and multiple gene expressions. Responses to one or five CT exposures were compared to a 2 Gy X-ray dose at intervals from 1 h to 10 passages post-irradiation. It was shown that CT scan briefly increased DNA damage markers but showed no significant long-term effects. A high dose of 2 Gy X-ray exposure caused sustained DNA damage, decreased proliferation, increased senescence, and significant changes in hundreds of genes even after several cell generations. After a single CT exposure, gene expression changes were minimal, while high-dose exposure led to strong activation of DNA repair and stress response pathways. Five CT scans caused a slight activation of LIF and HSPA1B genes, but these effects were minor compared to the high-dose group. All detected effects from CT scans were not observed by ten cell passages, whereas high-dose effects persisted. In conclusion, typical CT scan exposures have only short-term, mild effects on hMSCs, while high-dose radiation causes lasting cellular and genetic changes. Full article

Background/Objectives: Gastrin-releasing peptide receptor (GRPR) is overexpressed in breast cancer and might be used as a theranostics target. The expression of GRPR strongly correlates with estrogen receptor (ER) expression. Visualization of GRPR-expressing breast tumors might help to select the optimal treatment. Developing GRPR-specific probes for SPECT would permit imaging-guided therapy in regions with restricted access to PET facilities. In this first-in-human study, we evaluated the safety, biodistribution, and dosimetry of the [^99mTc]Tc-DB8 GRPR-antagonistic peptide. We also addressed the important issue of finding the optimal injected peptide mass. Methods: Fifteen female patients with ER-positive primary breast cancer were enrolled and divided into three cohorts receiving [^99mTc]Tc-DB8 (corresponding to three distinct doses of 40, 80, or 120 µg DB8) comprising five patients each. Additionally, four patients with ER-negative primary tumors were injected with 80 µg [^99mTc]Tc-DB8. The injected activity was 360 ± 70 MBq. Planar scintigraphy was performed after 2, 4, 6, and 24 h, and SPECT/CT scans followed planar imaging 2, 4, and 6 h after injection. Results: No adverse events were associated with [^99mTc]Tc-DB8 injections. The effective dose was 0.009–0.014 mSv/MBq. Primary tumors and all known lymph node metastases were visualized irrespective of injected peptide mass. The highest uptake in the ER-positive tumors was 2 h after injection of [^99mTc]Tc-DB8 at a 80 µg DB8 dose (SUV_max 5.3 ± 1.2). Injection of [^99mTc]Tc-DB8 with 80 µg DB8 provided significantly (p < 0.01) higher uptake in primary ER-positive breast cancer lesions than injection with 40 µg DB8 (SUV_max 2.0 ± 0.3) or 120 µg (SUV_max 3.2 ± 1.4). Tumor-to-contralateral breast ratio after injection of 80 μg was also significantly (p < 0.01, ANOVA test) higher than ratios after injection of other peptide masses. The uptake in ER-negative lesions was significantly lower (SUV_max 2.0 ± 0.3) than in ER-positive tumors. Conclusions: Imaging using [^99mTc]Tc-DB8 is safe, tolerable, and associated with low absorbed doses. The tumor uptake is dependent on the injected peptide mass. The injection of an optimal mass (80 µg) provides the highest uptake in ER-positive tumors. At optimal dosing, the uptake was significantly higher in ER-positive than in ER-negative lesions. Full article

Background/Objectives: Red bone marrow irradiation is a major concern for patients with advanced prostate cancer undergoing [¹⁷⁷Lu]Lu-PSMA therapy. However, low uptake in the red bone marrow and the presence of bone lesions complicate image-based red bone marrow dosimetry. This study aimed to investigate the general feasibility of image-based red bone marrow activity estimation for [¹⁷⁷Lu]Lu-PSMA treatment and to develop a fully automated workflow for clinical implementation. Methods: In the first part of the study, 175 virtual patient phantoms with realistic ¹⁷⁷Lu activity distributions were generated based on 639 pre-therapeutic [¹⁸F]F-PSMA-1007 PET/CT scans. The SIMIND Monte Carlo tool was used to simulate the ¹⁷⁷Lu SPECT acquisitions (24 h post-injection (p.i.)), which were used to assess the uncertainty of red bone marrow activity estimation. In the second part, red bone marrow self- and cross-absorbed doses were estimated for four therapy cycles of 20 patients. Results: The simulation study shows a significant overestimation of activity in skeletal sites with bone lesions, with median recovery coefficients (RCs) across all phantoms yielding a median of 225% (range: 106–1015%). In contrast, the median RCs were markedly lower in skeletal sites neighboring or distant to lesion-carrying sites (105% [72–163%] and 107% [77–130%], respectively). The median total absorbed dose to the red bone marrow was 20.8 mGy/GBq (range: 5.6–297.9 mGy/GBq). Median blood levels decreased with an increasing median cumulative total absorbed dose. Conclusions: Reliable estimation of activity concentration in skeletal sites without bone lesion infiltration has been shown to be feasible. Based on this finding, an automated workflow for routine image-based red bone marrow dosimetry was developed. Full article

This study assesses the clinical deployment of SubtlePET™, a commercial AI-based denoising algorithm, across three radiotracers—¹⁸F-FDG, ⁶⁸Ga-PSMA-11, and ¹⁸F-FDOPA—with the goal of improving image quality while reducing injected activity, technologist radiation exposure, and scan time. A retrospective analysis on a digital PET/CT system showed that SubtlePET™ enabled dose reductions exceeding 33% and time savings of over 25%. AI-enhanced images were rated interpretable in 100% of cases versus 65% for standard low-dose reconstructions. Notably, 85% of AI-enhanced scans received the maximum Likert quality score (5/5), indicating excellent diagnostic confidence and noise suppression, compared to only 50% with conventional reconstruction. The quantitative image quality improved significantly across all tracers, with SNR and CNR gains of 50–70%. Radiotracer dose reductions were particularly substantial in low-BMI patients (up to 41% for FDG), and the technologist exposure decreased for high-exposure roles. The daily patient throughput increased by an average of 4.84 cases. These findings support the robust integration of SubtlePET™ into routine clinical PET practice, offering improved efficiency, safety, and image quality without compromising lesion detectability. Full article

Background: Optimization of pulmonary nodule detection across varied imaging protocols remains challenging. We evaluated four DL-CAD systems and manual reading with volume rendering (VR) for performance under varying radiation doses and reconstruction methods. VR refers to a post-processing technique that generates 3D images by assigning opacity and color to CT voxels based on Hounsfield units. Methods: An anthropomorphic phantom with 169 artificial nodules was scanned at three dose levels using two kernels and three reconstruction algorithms (1080 image sets). Performance metrics included sensitivity, specificity, volume error (AVE), and Lung-RADS classification accuracy. Results: DL-CAD systems demonstrated high sensitivity across dose levels and reconstruction settings, with three fully automatic DL-CAD systems (0.92–0.95) outperforming manual CT readings (0.72), particularly for sub-centimeter nodules. However, DL-CAD systems exhibited limitations in volume measurement and Lung-RADS classification accuracy, especially for part-solid nodules. VR-enhanced manual reading outperformed original CT interpretation in nodule detection, particularly benefiting less-experienced radiologists under suboptimal imaging conditions. Conclusions: These findings underscore the potential of DL-CAD for lung cancer screening and the clinical value of VR in low-dose settings, but they highlight the need for improved classification algorithms. Full article

Introduction: Percutaneous cryoablation (PCA) can be a valid alternative to partial nephrectomy for patients with cT1a renal tumors. A potential disadvantage of PCA is radiation exposure for patients, though the exact significance of this is unknown. This study aims to uncover the degree of radiation exposure during PCA and what factors are of influence. Methods: This is a retrospective analysis of a prospectively maintained database of patients who underwent CT-guided PCA for cT1 renal cell carcinoma (RCC) between January 2014 and September 2024. The median effective dose (mSV) of PCA was calculated and compared to the expected cumulative radiation exposure during follow-up. Multivariate linear regression was performed to identify factors predictive of higher radiation exposure (mSV). Results: A total of 164 PCAs were performed, with radiation data available for 133 cases. Mean age was 65 (±11) years and the mean tumor diameter was 28 (±9.6) mm. Median effective dose of the CA procedures was 26 mSV (IQR 18–37). The estimated cumulative effective dose of follow-up CT scans according to 2016 and 2024 European Association of Urology guidelines was 158 (IQR 117–213) and 105 mSV (IQR 78–142), respectively. Multivariate linear regression analysis identified BMI (OR 1.723, p < 0.001), the number of needles used (OR 4.060, p < 0.001), and the necessity for additional procedures (OR 8.056, p < 0.001) as significant predictors of a higher effective dose. Conclusions: We found a median effective dose of 26 mSV for PCA, which is relatively low compared to the cumulative radiation exposure associated with CT scans during follow-up of patients post-ablation according to the guidelines. Furthermore, increased BMI, a higher number of required needles and the execution of additional procedures are all associated with a higher effective dose. Full article

Major mutations of SERPINA1, the gene encoding alpha1-antitrypsin (A1AT), are known to cause severe emphysema. Our study aimed to investigate the role of major mutations modulating A1AT levels in several lung pathologies and control groups. Blood samples were collected from healthy non-smokers (N⁰ = 85), healthy smokers (N⁰ = 291), healthy ex-smokers (N⁰ = 127), smokers with chronic obstructive lung disease (COPD, N⁰ = 187), ex-smokers with COPD (N⁰ = 64), and patients with asthma (N⁰ = 194), interstitial lung disease (ILD) (N⁰ = 93), sarcoidosis (N⁰ = 30) and cystic fibrosis (N⁰ = 26). Clinical and respiratory parameters, A1AT levels, the extent of emphysema and comorbidities on low-dose CT scans were evaluated, and patients answered a smoking history and comorbidity questionnaire. A1AT single-nucleotide polymorphisms were determined for the S, Z, M2/M4, 0 and eQTL locations by SNP probes using real-time PCR. A1AT levels showed significant differences between cigarette smoke-induced and other lung diseases. Compared to controls, A1AT levels were found to be lower in sarcoidosis and increasingly higher in smokers and patients with COPD, ILD and CF, respectively. The presence and pattern of emphysema were found to influence A1AT levels: lower values were observed in COPD patients without emphysema, while higher values were observed in patients with central and panlobular emphysema. Antitrypsin levels increased with COPD GOLD stages and asthma GINA stages. Variable A1AT levels were also found in ILD subgroups. The distribution of variants at the S, Z, M2/M4 and 0 polymorphic sites and the eQTL location showed no significant differences between patient groups with impaired lung function, except for Z heterozygotes, which were prevalent in patients with severe asthma. The eQTL TT genotypes had higher A1AT levels and the occurrence of emphysema and/or bronchitis was increased. A1AT levels correlated with several clinical and respiratory parameters in pulmonary patients, while FEV1/FVC inversely correlated with levels of A1AT. Molar antielastase activity was increased in smokers and patients with lung diseases; however, in COPD, antielastase activity decreased. The most reduced antielastase activity could be found in CF. Certain genotypes were characterized by increased cardiovascular comorbidity scores and antitrypsin levels. Our data suggest that in addition to emphysema, A1AT may play an important role in the development of a wide variety of lung diseases and cardiovascular comorbidities. Further research is needed to clarify the role of A1AT and its regulation in lung pathologies. Full article

Background/Objectives: The primary aim of this study was to evaluate whether the replacement of roughly one-decade-old computed tomography (CT) scanners with new-model CT scanners were associated with an additional reduction in the radiation dose delivered to oncological patients, in a radiological setting where the optimization of protocols had already reached very low radiation doses. An exploratory secondary objective was to evaluate the potential differences in the objective image quality between the CT scans obtained before and after the installation of the new-generation CT scanners. Methods: Chest and abdominal CT examinations conducted for oncologic purposes were retrospectively selected from two time periods—prior to scanner replacement (2022) and following an upgrade (2024)—after five CT systems in our radiology department were replaced. We extracted and compared the CT dose index (CTDI) and dose length product (DLP) for each CT phase. For the objective image quality evaluation, we calculated the signal-to-noise ratio (SNR) and the contrast-to-noise ratio (CNR) at the center of the liver and the aorta. An appropriate statistical analysis was performed and a p-value < 0.05 was considered significant. Results: We included 14,601 CT acquisitions, of which 9013 (61.7%) were performed before and 5588 (38.3%) after the replacement of the CT scanners. There were significantly lower values for the CTDI and DLP with the new CT scanners compared to the old ones. The CTDI with the new CT scanners was significantly lower in all phases (p-value = 0.002 for unenhanced phase, and p < 0.001 for arterial, portal venous, and delayed phases). The DLP using the new CT scanners was significantly lower in the arterial, portal venous, and delayed phases (p < 0.001), and it was not significantly different in the unenhanced phase (p = 0.36). There was no significant difference in the SNR at the liver level (p = 0.72) or at the aorta level (p = 0.51). There was no significant difference in the CNR at the liver level (p = 0.24), whereas the CNR was higher with the new CT scanners at the aorta level (p = 0.03). Conclusions: The transition to new-model CT scanners resulted in a significant reduction in the radiation dose delivered by chest and abdomen CT scans, without compromising the objective image quality. Full article

A 40-year-old woman with a known diagnosis of Ehlers–Danlos syndrome (EDS) began experiencing progressive shortness of breath and reduced exercise tolerance following her second pregnancy. The patient underwent an unenhanced computed tomography (CT) scan that showed a marked elevation of the left diaphragm. Suspecting diaphragm dysfunction, the patient underwent Dynamic Digital Radiography (DDR) that confirmed a reduction in left diaphragm motility, indicative of impaired diaphragm function. Based on the DDR findings, which demonstrated reduced but preserved diaphragmatic motion without paradoxical movement or complete immobility, the thoracic surgeon decided that surgical intervention, such as plication, was not necessary. Instead, rehabilitation exercises, including breathing techniques and diaphragm strengthening, were recommended. EDS includes connective tissue disorders that vary in severity but are typically characterized by hypermobility of the joints, skin hyper-elasticity, and a predisposition to vascular fragility. One of the complications of EDS is weakened connective tissues, which can affect the diaphragm, impairing the contractility of the muscle and leading to impaired mobility and respiratory symptoms such as shortness of breath. Diaphragm dysfunction can manifest as reduced movement, potentially related to the underlying connective tissue weakness. This case highlights the clinical value of DDR as a non-invasive, low-dose, and dynamic imaging modality in the diagnosis of diaphragmatic dysfunction in EDS patients, enabling individualized treatment planning and potentially avoiding unnecessary surgical interventions. Full article

Background: Spectral detector computed tomography (SDCT) has demonstrated superior diagnostic performance and image quality in liver disease assessment compared with traditional CT. Selecting the right reconstruction algorithm and tube voltage is essential to avoid increased noise and diagnostic errors. Objectives: This study evaluated improvements in image quality achieved using various virtual tube voltages and reconstruction algorithms for diagnosing common liver diseases with spectral CT. Methods: This retrospective study involved forty-seven patients who underwent spectral CT scans for liver conditions, including fatty liver, hemangiomas, and metastatic lesions. The assessment utilized signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), with images reconstructed using various algorithms (IMR, iDose) at different levels and virtual tube voltages. Three experienced radiologists analyzed the reconstructed images to identify the best reconstruction methods and tube voltage combinations for diagnosing these liver pathologies. Results: The signal-to-noise ratio (SNR) was highest for spectral CT images using the IMR3 algorithm in metastatic, hemangioma, and fatty liver cases. A strong positive correlation was found between IMR3 at 120 keV and 70 keV (p-value = 0.000). In contrast, iDOSE2 at 120 keV and 70 keV showed a low correlation of 0.291 (p-value = 0.045). Evaluators noted that IMR1 at 70 keV provided the best visibility for liver lesions (mean = 3.58), while IMR3 at 120 keV had the lowest image quality (mean = 2.65). Conclusions: Improvements in image quality were noted with SDCT, especially in SNR values for liver tissues at low radiation doses and a specific IMR level. The IMR1 algorithm reduced noise, enhancing the visibility of liver lesions for better diagnosis. Full article

Background and Objectives: Single-photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) is a well-established technique for evaluating myocardial perfusion and function in patients with suspected or known coronary artery disease. While conventional dual-detector SPECT scanners have limitations in spatial resolution and photon detection sensitivity, recent advancements, including full-ring solid-state cadmium zinc telluride (CZT) detectors, offer enhanced image quality and improved diagnostic accuracy. This study aimed to compare the performance of Veriton-CT, a full-ring CZT SPECT system, with GE Discovery 530c, a dedicated cardiac fixed-angle gamma camera, in myocardial perfusion imaging and their correlation with coronary angiography findings. Materials and Methods: This was a prospective study that analyzed 21 patients who underwent MPI at the Department of Nuclear Medicine, Lithuanian University of Health Sciences, Kauno Klinikos. A one-day stress–rest protocol using 99mTc-Sestamibi was employed, with stress testing performed via bicycle ergometry or pharmacological induction. MPI was first conducted using GE Discovery 530c (GE Health Care, Boston, MA, USA), followed by imaging on Veriton-CT, which included low-dose CT for attenuation correction. The summed stress score (SSS), summed rest score (SRS), and summed difference score (SDS) were analyzed and compared between both imaging modalities. Coronary angiography results were retrospectively collected, and lesion-based analysis was performed to assess the correlation between imaging results and the presence of significant coronary artery stenosis (≥35% and ≥70% narrowing). Image quality and the certainty of distinguishing the inferior myocardial wall from extracardiac structures were also evaluated by two independent researchers with differing levels of experience. Results: Among the 14 patients included in the final analysis, Veriton-CT was more likely to classify MPI scans as normal (64.3%) compared to GE Discovery 530c (28.6%). Additionally, Veriton-CT provided a better assessment of the right coronary artery (RCA) basin, showing greater agreement with coronary angiography findings than GE Discovery 530c, although the difference was not statistically significant. No significant differences in lesion overlap were observed for the left anterior descending artery (LAD) or left circumflex artery (LCx) basins. Furthermore, the image quality assessment revealed slightly better delineation of extracardiac structures using Veriton-CT (Spectrum Dynamics Medical, Caesarea, Israel), particularly when evaluated by an experienced researcher. However, no significant difference was observed when assessed by a less experienced observer. Conclusions: Our findings suggest that Veriton-CT, with its full-ring CZT detector system, may offer advantages over fixed-angle gamma cameras in improving image quality and reducing attenuation artifacts in MPI. Although the difference in correlations with coronary angiography findings was not statistically significant, Veriton-CT showed a trend toward better agreement, particularly in the RCA basin. These results indicate that full-ring SPECT imaging could improve the diagnostic accuracy of non-invasive MPI, potentially reducing the need for unnecessary invasive angiography. Further studies with larger patient cohorts are required to confirm these findings and evaluate the clinical impact of full-ring SPECT technology in myocardial perfusion imaging. Full article