Abdominal Computed Tomography Scan Research Articles

DLLabelsCT: Annotation tool using deep transfer learning to assist in creating new datasets from abdominal computed tomography scans, case study: Pancreas.

The utilization of artificial intelligence (AI) is expanding significantly within medical research and, to some extent, in clinical practice. Deep learning (DL) applications, which use large convolutional neural networks (CNN), hold considerable potential, especially in optimizing radiological evaluations. However, training DL algorithms to clinical standards requires extensive datasets, and their processing is labor-intensive. In this study, we developed an annotation tool named DLLabelsCT that utilizes CNN models to accelerate the image analysis process. To validate DLLabelsCT, we trained a CNN model with a ResNet34 encoder and a UNet decoder to segment the pancreas on an open-access dataset and used the DL model to assist in annotating a local dataset, which was further used to refine the model. DLLabelsCT was also tested on two external testing datasets. The tool accelerates annotation by 3.4 times compared to a completely manual annotation method. Out of 3,715 CT scan slices in the testing datasets, 50% did not require editing when reviewing the segmentations made by the ResNet34-UNet model, and the mean and standard deviation of the Dice similarity coefficient was 0.82±0.24. DLLabelsCT is highly accurate and significantly saves time and resources. Furthermore, it can be easily modified to support other deep learning models for other organs, making it an efficient tool for future research involving larger datasets.

Use of the vertebrae and iliac bone as references for localizing the appendix vermiformis in computed tomography.

The appendix vermiformis is a part of the gastrointestinal tract, situated in the lower right quadrant of the abdomen. Acute appendicitis, acute inflammation of the appendix vermiformis, is the most common cause of acute abdomen requiring surgical intervention. Although computed tomography (CT) offers high diagnostic efficacy in assessing the appendix across various anatomical positions, it also involves radiation exposure. Reducing exposure factors and narrowing the field of view (FOV) are ways to decrease the radiation dose to the patient. To narrow the FOV, appendix locations within the population must be defined using metric markers. To determine the location of the appendix vermiformis on CT using the vertebrae and the right iliac bone as anatomical landmarks. This retrospective study examined 470 patients presenting with abdominal pain who underwent abdominal CT scans between January 01, 2015 and January 01, 2018. Forty-three patients were excluded due to various reasons. The most superior and inferior points and the origin of the appendix were measured separately in relation to the vertebrae and right iliac bone for localization. The population was divided into normal and acute appendicitis groups, and the relationship between appendix location and anthropometric parameters relationship was examined. P values below 0.05 were considered statistically significant. The final analysis included 427 adult patients (206 females and 221 males) with a mean age of 42.1 ± 19.5 years. An ascending appendix course was the most common (90.4%). The appendix ranged from the L2 vertebral body level to the coccygeal vertebral level relative to the vertebrae. The appendix ranged between (-) 140.5 mm and (+) 87.4 mm relative to the right iliac bone. A negative correlation was found between patient age, height, body mass index, and the highest and lowest points of the appendix in regard to the vertebrae. The study's findings unveiled the locations of the appendix in the population in relation to the bony anatomical landmarks. These data can be used as the basis for future research aimed at reducing patient exposure to ionizing radiation.

Meckel's diverticulum as a cause of gastrointestinal bleeding.

Meckel's diverticulum, the most common congenital anomaly of the gastrointestinal tract, is often asymptomatic. Lack of complete resorption of the omphalomesenteric duct is an important cause of Meckel's diverticulum. Gastrointestinal (GI) bleeding is a major complication of Meckel's diverticulum. Herein, we reported a case of obscure gastrointestinal bleeding secondary to Meckel's diverticulum in small intestine detected by double-balloon enteroscopy. A 32-year-old male was admitted to the Department of Gastroenterology due to a 4-year history of intermittent hematochezia. Half a month before this admission, abdominal computed tomography scans showed high density in intestinal tract, and magnetron capsule endoscopy showed dark red blood from the end of the ileum to the ascending colon, but did not identify the source of bleeding. At this admission, hemoglobin concentration was 117 g/L. Double-balloon enteroscopy via anal route was performed, and found a large diverticulum in the middle part of the ileum, which was marked by two metal clips, with a superficial ulcer on its inner wall. Thus, Meckel's diverticulum was diagnosed. Subsequently, he underwent surgery. During surgery, a small intestinal diverticulum with a size of about 5.0cm×2.0cm was located nearly 120cm away from the ileocecal part. Small intestinal diverticulectomy was performed. He did not develop any recurrent hematochezia during follow-up.

Evaluation of SR-DLR in low-dose abdominal CT: superior image quality and noise reduction.

To evaluate the effectiveness of super-resolution deep learning reconstruction (SR-DLR) in low-dose abdominal computed tomography (CT) imaging compared with hybrid iterative reconstruction (HIR) and conventional deep learning reconstruction (cDLR) algorithms. We retrospectively analyzed abdominal CT scans performed using a low-dose protocol. Three different image reconstruction algorithms-HIR, cDLR, and SR-DLR-were applied to the same raw image data. Objective evaluations included noise magnitude and contrast-to-noise ratio (CNR), as well as noise power spectrum (NPS) and edge rise slope (ERS). Subjective evaluations were performed by radiologists, who assessed image quality in terms of noise, artifacts, sharpness, and overall diagnostic utility. Raw CT image data were obtained from 35 patients (mean CTDIvol 11.0 mGy; mean DLP 344.8 mGy/cm). cDLR yielded the lowest noise levels and highest CNR (p < 0.001). However, SR-DLR outperformed cDLR in terms of noise texture and resolution, achieving the lowest NPS peak and highest ERS (p < 0.001 and p = 0.005, respectively). Subjectively, SR-DLR was rated highest across all categories, including noise, artifacts, sharpness, and overall image quality, with statistically significant differences compared to cDLR and HIR (p < 0.001). SR-DLR was the most effective reconstruction algorithm for low-dose abdominal CT imaging, offering superior image quality and noise reduction compared to cDLR and HIR. This suggests that SR-DLR can enhance the reliability and diagnostic accuracy of abdominal imaging, particularly in low-dose settings, making it a valuable tool in clinical practice.

EDI&amp;S SO04 Accuracy of Outsourced Radiology Reports in Emergency Surgical Care; Do they provide a high-quality cost-effective service?

Abstract Background Computed Tomography (CT) scans play a crucial role in emergency surgical care enabling proper management and prompt decision making. In our study we aimed to compare abdominal CT scan reports created by inhouse radiologists to those created by outsourced radiology reporting service for patients admitted with acute surgical pathologies. The study also looked at the impact of the reporting style (free text or structured format) on the quality of scan reports. Method The study was conducted in a busy general surgery unit located in the North West of England. Patients who were admitted acutely under the surgical specialty and had abdominal CT scans over a period of three months from August 2023 to October 2023 were included. Patients who were admitted following trauma or had non abdominal CT scans have been excluded. Statistical analysis was conducted to compare inhouse radiology reports to outsourced ones. Scan reports were thoroughly scrutinised to identify whether they included all relevant information needed and whether they were written in structured or free text format. Results A total of 192 patients were identified with a median age of 59 years. Outsourced radiology reports were found to be significantly underreporting comments on the biliary system (OR=0.369, P=0.046), spleen (OR=0.414, P=0.044), kidneys (OR=0.354, P=0.027), lymph nodes (OR=0.412, P=0.011), mesentery and peritoneum (OR=0.364, P=0.004), vasculature (OR=0.381, P=0.002), bones and soft tissues (OR=0.273, P=0.003), as well as lung bases (OR=0.300, P=0.009). Structured format was found to outperform free text style on comments on spleen (OR=8.064, P=0.044), adrenals (OR=8.468, P=0.039), mesentery and peritoneum (OR=4.618, P=0.000), as well as bone and soft tissues (OR=9.295, P=0.031). Conclusion CT scans reported by outsourced radiology service were found to be significantly underreporting certain key elements. Additionally, free style reporting format was found to miss some crucial aspects of abdominal scan reports. That adds further challenges to clinicians assessing and managing acute surgical patients. Further studies auditing different outsourced companies are recommended to ensure patients are provided with high-quality cost-effective emergency service.

Validating a Practical Correction for Intravenous Contrast on Computed Tomography–Based Muscle Density

Objective Computed tomography (CT) measured muscle density is prognostic of health outcomes. However, the use of intravenous contrast obscures prognoses by artificially increasing CT muscle density. We previously established a correction to equalize contrast and noncontrast muscle density measurements. While this correction was validated internally, the objective of this study was to obtain external validation using different patient cohorts, muscle regions, and CT series. Methods CT images from 109 patients with kidney tumors who received abdominal CT scans with a multiphase intravenous contrast protocol were analyzed. Paraspinal muscle density measurements taken during noncontrast, venous phase, and delayed phase contrast scans were collected. An a priori correction of −7.5 Hounsfield units (HU) was applied to muscle measurements. Equivalence testing was utilized to determine statistical similarity. Results In the sample of 109 patients (mean age: 63 years [SD: 14.3]; 41.3% female), densities in smaller regions of interest within the paraspinal muscles and the entire paraspinal muscle density (PS) in venous and delayed phase contrast scans were higher than in noncontrast. Equivalence testing showed that average corrected contrast and noncontrast muscle densities were within 3 HU for both muscle measures for the total patient sample, and for a majority of male and female subsamples. The correction is suitable for regions of interests of venous contrast (90% CI: −1.90, −0.69 HU) and delayed contrast scans (90% CI: 0.075, 1.29 HU) and within the PS measures of venous contrast (90% CI: −2.04, −0.94 HU) and delayed contrast scans (90% CI: −0.11, 0.89 HU) Conclusions The previously established correction for contrast of −7.5 HU was applied in a new patient population, axial muscle region, muscle measurement size, and expanded on previously studied contrast phases. The correction produced contrast-corrected muscle densities that were statistically equivalent to noncontrast muscle densities. The simplicity of the correction gives clinicians a tool that seamlessly integrates into practice or research to improve harmonization of data between contrast and noncontrast scans.

Abstract 4117834: Utility of Abdominal Aortic Calcification Assessment for the Prediction of Major Adverse Cardiovascular Events in Liver Transplant Patients

Background: Cardiovascular disease is a leading cause of postoperative morbidity and mortality following liver transplantation (LT). Presence of abdominal aortic calcification (AAC) has been linked to cardiovascular events in the general population. We investigated whether AAC on pre-transplant computed tomography (CT) predicts major adverse cardiovascular events (MACE) post-LT. Methods: Consecutive LT patients between 2010-2018 from the Victorian Liver Transplant Unit (Australia) were included. Extent of AAC was quantified in a blinded fashion, with high AAC defined as a calcium score of ≥500. MACE was defined as any recorded episodes of acute coronary syndrome (ACS), ventricular arrhythmia, decompensated heart failure, or stroke. The primary outcome was post-LT MACE at 30 days and the secondary outcome was all-cause mortality at maximal follow-up. Results: Of 461 patients undergoing LT, 350 had suitable CTs for analysis, of which 90 (25.7%) had also undergone CT coronary angiography. High AAC was identified in 98 patients (28.0%). This finding demonstrated a moderate correlation with high coronary artery calcium score (CACS) ≥400 (r=0.52, p&lt;0.001). Fifty-eight MACE occurred in 42 patients (12.0%) within 30-days. High AAC was associated with increased risk of 30-day MACE (OR=2.68 (95%CI 1.39-5.17), p=0.004), and long-term mortality (HR=2.52 (95%CI 1.29-4.92), p=0.007) at a median follow-up of 4.0 years. In addition, high AAC predicted an increased risk of ACS (OR 3.80 (95%CI 1.18-12.27), p=0.025), heart failure (OR 3.07 (95%CI 1.21-7.80), p=0.020) and atrial fibrillation (OR 2.04 (95%CI 1.02-4.07), p=0.048), with a trend to increased prevalence of ventricular arrhythmia (OR 2.67 (95%CI 0.84-8.50), p=0.10). Following multivariate analysis, high AAC remained a strong independent predictor of MACE (OR=3.49, 95%CI 1.21-10.06, p=0.021). Addition of AAC to the revised cardiac risk index (RCRI) improved model fit for predicting MACE (net reclassification improvement of 52.7% (p&lt;0.001)). Conclusions: This study demonstrates for the first time that high AAC on routine abdominal CT scans is associated with a 3-fold increased risk of 30-day MACE post-LT, and improves cardiovascular risk prediction compared to traditional risk scores. Quantification of AAC may offer a simple method of improving cardiovascular risk assessment and implementation of preventative strategies in liver transplant patients, using pre-existing scans without additional cost or patient risk.

An insight to PDAC tumor heterogeneity across pancreatic subregions using computed tomography images.

Pancreatic Ductal Adenocarcinoma (PDAC) is an exceptionally deadly form of pancreatic cancer with an extremely low survival rate. From diagnosis to treatment, PDAC is highly challenging to manage. Studies have demonstrated that PDAC tumors in distinct regions of the pancreas exhibit unique characteristics, influencing symptoms, treatment responses, and survival rates. Gaining insight into the heterogeneity of PDAC tumors based on their location in the pancreas can significantly enhance overall management of PDAC. Previous studies have explored PDAC tumor heterogeneity across pancreatic subregions based on their genetic and molecular profiles through biopsy-based histologic assessment. However, biopsy examinations are highly invasive and impractical for large populations. Abdominal imaging, such as Computed Tomography (CT) offers a completely non-invasive means to evaluate PDAC tumor heterogeneity across pancreatic subregions and an opportunity to correlate image feature of tumors with treatment outcome and monitoring. In this study, we explored the inter-tumor heterogeneity in PDAC tumors across three primary pancreatic subregions: the head, body, and tail. Utilizing contrast-enhanced abdominal CT scans and a thorough radiomic analysis of PDAC tumors, several morphological and textural tumor features were identified to be notably different between tumors in the head and those in the body and tail regions. To validate the significance of the identified features, a machine learning ML model was trained to automatically classify PDAC tumors into their respective regions i.e. head or body/tail subregion using their CT features. The study involved 200 CT abdominal scans, with 100 used for radiomic analysis and model training, and the remaining 100 for model testing. The ML model achieved an average classification accuracy, sensitivity, and specificity of 87%, 86%, and 88% on the testing scans respectively. Evaluating the heterogeneity of PDAC tumors across pancreatic subregions provides valuable insights into tumor composition and has the potential to enhance diagnosis and personalize treatment based on tumor characteristics and location.

Mesocolic schwannoma mimicking gastrointestinal stromal tumor: A case report and review of literature.

Schwannomas are common peripheral nerve tumors originating from Schwann cells, primarily occurring in the head and neck, limbs, and trunk. Schwannomas occurring in the mesocolon are rare and often have no specific manifestations. Abdominal schwannomas need to be differentiated from common abdominal tumors such as gastrointestinal stromal tumors. We report a case of a mesocolic schwannoma in a 59-year-old female presenting with gastrointestinal symptoms of acid reflux. At an outside hospital, gastroscopy, colonoscopy, and abdominal computed tomography scans revealed a soft tissue mass adjacent to the greater curvature of the stomach, leading to a suspicion of a gastric mesenchymal tumor. Mesocolic schwannoma. Laparoscopy was performed at our hospital. Intraoperatively, the tumor was found to be closely related to the transverse colon and was initially diagnosed as a mass originating from the transverse colon. Consequently, a resection of the mass along with the adherent portion of the transverse colon was performed. Postoperative pathology and immunohistochemistry confirmed that the tumor was a schwannoma of the mesentery and did not originate from the transverse colon. Schwannomas can be distinguished from gastrointestinal stromal tumors by immunohistochemical staining, and surgical treatment is effective for benign schwannomas.

Myosteatosis: diagnostic significance and assessment by imaging approaches.

Myosteatosis has emerged as an important concept in muscle health as it is associated with an increased risk of adverse health outcomes, a higher rate of complications, and increased mortality associated with ageing, chronic systemic and neuromuscular diseases, cancer, metabolic syndromes, degenerative events, and trauma. Myosteatosis involves ectopic infiltration of fat into skeletal muscle, and it exhibits a negative correlation with muscle mass, strength, and mobility representing a contributing factor to decreased muscle quality. While myosteatosis serves as an additional biomarker for sarcopenia, cachexia, and metabolic syndromes, it is not synonymous with sarcopenia. Myosteatosis induces proinflammatory changes that contribute to decreased muscle function, compromise mitochondrial function, and increase inflammatory response in muscles. Imaging techniques such as computed tomography (CT), particularly opportunistic abdominal CT scans, and magnetic resonance imaging (MRI) or magnetic resonance spectroscopy (MRS), have been used in both clinical practice and research. And in recent years, ultrasound has emerged as a promising bedside tool for measuring changes in muscle tissue. Various techniques, including CT-based muscle attenuation (MA) and intermuscular adipose tissue (IMAT) quantification, MRI-based proton density fat fraction (PDFF) and T1-T2 mapping, and musculoskeletal ultrasound (MSUS)-based echo intensity (EI) and shear wave elastography (SWE), are accessible in clinical practice and can be used as adjunct biomarkers of myosteatosis to assess various debilitating muscle health conditions. However, a stan¬dard definition of myosteatosis with a thorough understanding of the pathophysiological mechanisms, and a consensus in assessment methods and clinical outcomes has not yet been established. Recent developments in image acquisition and quantification have attempted to develop an appropriate muscle quality index for the assessment of myosteatosis. Additionally, emerging studies on artificial intelligence (AI) may provide further insights into quantification and automated assessment, including MRS analysis. In this review, we discuss the pathophysiological aspects of myosteatosis, all the current imaging techniques and recent advances in imaging assessment as potential biomarkers of myosteatosis, and the most common clinical conditions involved.

CT-based sarcopenia assessment: Predicting outcomes in acute infection patients.

In this retrospective cohort study, we investigated the prognostic value of sarcopenia evaluated by Computed Tomography (CT)-based indices for adverse hospitalization outcomes in patients with acute infections. We analyzed data from 225 patients admitted to the hospital for acute infections between 2019 and 2020. Patients who had undergone an abdominal CT scan either up to 1 month before or within the first 3 days of hospitalization were included. CT image analysis was used to evaluate skeletal muscle mass (by skeletal muscle index (SMI)) and muscle quality (by psoas muscle density, pMD). Low pMD was associated with higher in-hospital mortality (31% vs 11.4% p < 0.001) as well as higher longer-term mortality rates (p = 0.008 for 30 days and <0.001 for 90- and 1-year mortality). Low pMD remained an independent poor prognostic factor after controlling for confounders, with an adjusted odds ratio (aOR) of 2.74, (95% CI 1.33-5.67, p = 0.006) for 1-year mortality, and aOR of 2.61, (95% CI 1.23-5.55) for a prolonged hospital stay. Low SMI was associated with adverse outcomes, although this association was not independent after controlling for confounders. Notably, patients with both low SMI and pMD exhibited the poorest hospitalization outcomes: aOR for 1-year mortality 5.015 (95% CI 1.767-14.23, p = 0.002), and prolonged length of stay aOR 3.197, (95% CI 1.159-8.821, p = 0.025). CT-based muscle indices serve as independent prognostic factors in medical patients admitted with acute infection. Incorporating radiological assessments of sarcopenia into routine care for hospitalized patients with acute infection may enable risk stratification and early intervention in reversible conditions.

MaskAppendix: Backbone-Enriched Mask R-CNN Based on Grad-CAM for Automatic Appendix Segmentation.

A leading cause of emergency abdominal surgery, appendicitis is a common condition affecting millions of people worldwide. Automatic and accurate segmentation of the appendix from medical imaging is a challenging task, due to its small size, variability in shape, and proximity to other anatomical structures. In this study, we propose a backbone-enriched Mask R-CNN architecture (MaskAppendix) on the Detectron platform, enhanced with Gradient-weighted Class Activation Mapping (Grad-CAM), for precise appendix segmentation on computed tomography (CT) scans. In the proposed MaskAppendix deep learning model, ResNet101 network is used as the backbone. By integrating Grad-CAM into the MaskAppendix network, our model improves feature localization, allowing it to better capture subtle variations in appendix morphology. We conduct extensive experiments on a dataset of abdominal CT scans, demonstrating that our method achieves state-of-the-art performance in appendix segmentation, outperforming traditional segmentation techniques in terms of both accuracy and robustness. In the automatic segmentation of the appendix region in CT slices, a DSC score of 87.17% was achieved with the proposed approach, and the results obtained have the potential to improve clinical diagnostic accuracy. This framework provides an effective tool for aiding clinicians in the diagnosis of appendicitis and other related conditions, reducing the potential for diagnostic errors and enhancing clinical workflow efficiency.

Evaluation of Health Associations With Height-Normalised Abdominal Body Composition Indices: A Single-Centre Cross-Sectional Study.

Traditional metrics such as body mass index (BMI) and waist circumference (WC) fail to accurately assess the health outcomes associated with abdominal adiposity, because they neglect the intricacies of adipose tissue distribution. Notably, the variability in body composition scaled to height remains underexplored in Chinese demographics. This study introduces height-normalised indices of abdominal adiposity using computed tomography (CT) scans and further assesses their associations with various health outcomes. In a large, diverse Chinese population (n = 1054 healthy individuals; n = 1159 with dyslipidemia; n = 803 with diabetes; n = 1289 with cardio-cerebrovascular diseases; n = 1108 with cancers; and n = 509 with abnormal bone mas), abdominal CT scans were performed and allometric growth model analyses were used to derive height-normalised indices (body composition/heightβ). Logistic regression models assessed the associations between these indices and health outcomes. Distinct scaling powers were observed for visceral adipose tissue (VAT), subcutaneous adipose tissue (SAT) and total abdominal adipose tissue (TAT), as well as for sagittal diameter (SAD), with marked sex differences. Powers for VAT were 1.786 ± 1.270 for males and 1.274 ± 0.692 for females. Powers for SAT were 2.266 ± 0.856 for males and 1.656 ± 0.497 for females. Powers for TAT were 2.141 ± 0.967 for males and 1.438 ± 0.489 for females. Powers for SAD were 0.646 ± 0.217 for males and 0.678 ± 0.141 for females. After controlling for age, BMI and WC, VAT/heightβ, TAT/heightβ and SAD/heightβ retained their significantly positive associations with the odds of health outcomes, whereas SAT/heightβ did not. Our findings endorse the clinical utility of height-normalised indices, particularly VAT/heightβ, TAT/heightβ and SAD/heightβ, in health outcomes assessment. These indices, grounded in robust empirical data, underscore the necessity of a nuanced approach in obesity-related health evaluations, advocating for a departure from conventional methods like BMI.

An anatomical analysis of liver volume and quality by ethnicity in a New Zealand population.

Post-hepatectomy liver failure is a major cause of mortality, where future liver remnant (FLR) is the key controllable factor. Recommended minimum FLR is influenced by quality of liver parenchyma. Historical research has often failed to include Māori and Pacific Island (PI) populations despite worse health outcomes. Liver analysis by ethnicity is one such example of this. The aims were to determine digital FLR for various anatomical hepatectomies, investigate any correlations between computed tomography (CT) hepatic textural analysis and body mass index (BMI); and assess the variance of these relationships for different ethnicities. One hundred and fifty-one patients who underwent abdominal CT scans at Burwood Hospital, Christchurch were retrospectively analysed. Māori and PI patients were selectively recruited to represent New Zealand's diversity. Liver volumetry, segmental ratio, and intra-hepatic fat deposits (IHFD) per ethnicity were examined. Median age of the cohort was 66 (19-95) and 75 (50%) were males. 68%, 23% and 9% patients identified as being European, Māori/PI and Asian, respectively. No statistically significant difference in volume or segment/total volume ratio were noted across different ethnicities. Obese patients had higher IHFD compared with overweight and normal BMI groups. When stratified across ethnic groups, higher IHFD were observed in Asian compared with Māori/PI populations, despite lower BMI. No significant variances in liver volumetry were found across different ethnic groups in New Zealand. However association between BMI and IHFD varied across different ethnic cohorts. Consequently, knowledge of liver volumetry is not enough; patient liver quality and ethnicity should considered for hepatic-surgery planning.

Measuring Spatial Radiation Dose Distribution During Abdominal Computed Tomography Scanning with Optically Stimulated Luminescence Dosimeters

PurposeAs the proportion of medical radiation exposure increases, the exposure dose has received increasing attention. When performing interventional radiological diagnosis, examiners are often exposed to radiation. Therefore, patients and medical personnel are exposed to higher amounts of radiation dose. Accordingly, we used optically stimulated luminescence dosimeters (OSLDs) to measure the ambient air kerma during abdominal CT scanning to observe the spatial distribution of the doses.MethodsAn abdominal CT scan under a voltage of 120 kVp was performed, and OSLDs were used for the measurement. The measurement range extended from the examination couch that serves as the center point to the walls and was divided into four areas. The OSLD measurements were undertaken at three different heights (i.e., 85, 140, and 150 cm from the floor) for spatial dose detection. The OSLDs were fixed up to lines at the three height levels. Each dosimetry point was 50 cm apart. In addition, the surface incident doses of the prosthesis's mammary gland, liver, and gonad were estimated.ResultsAccording to the spatial dose distribution at the three different heights, the maximum dose and minimum dose in front of the bore were 0.194 ± 0.008 and 0.006 ± 0.001 mGy, respectively; 2 m away from the bore, the dose reduced to 9% of the maximum dose. The surface incident doses of the mammary gland, liver, and gonad were 1.321 ± 0.121, 13.083 ± 0.642, and 13.441 ± 0.658 mGy, respectively.ConclusionThe spatial dose distribution revealed that the dose was the highest at the height of 140 cm and in front of the bore. The dose on the left side was higher than that on the right side. In addition, the dose was inversely proportional to the square of the distance. If the examiners must perform interventional radiological diagnosis during CT scanning, they should put on radiation protection equipment and stand behind the bore to minimize the radiation exposure.

Relationships Between Hepatic Steatosis and Frailty Differ by HIV Serostatus.

Frailty is associated with obesity-related comorbidities, but the relationship with nonalcoholic fatty liver disease (NAFLD) in people with HIV has been incompletely described. Our objective was to assess the associations between NAFLD and frailty. Cross-sectional and longitudinal analysis of men in the Multicenter AIDS Cohort Study. NAFLD was defined as a liver/spleen ratio <1.0 on abdominal computed tomography scans; frailty was defined by the frailty phenotype as having 3 of the following: weakness, slowness, weight loss, exhaustion, and low physical activity. Men without (n = 200) and with HIV (n = 292) were included. NAFLD prevalence was 21% vs 16% and frailty 12% vs 17%, respectively. Among men with NAFLD, frailty was more prevalent in men without HIV (21% vs 11%). In multivariate analysis, NAFLD was significantly associated with frailty after controlling for significant variables. Men without HIV and NAFLD had 2.6 times higher probability [95% confidence interval (CI): 1.2- to 5.7] of frailty relative to men with neither HIV nor NAFLD. This association was not seen in men with HIV. The probability of frailty was higher among men without HIV with NAFLD (27% vs 10% in men without NAFLD) but lower among men with HIV with NAFLD (14% vs 19% in men without NAFLD). No significant relationships were found in longitudinal analyses. NAFLD was independently associated with frailty among men without HIV but not men with HIV, despite increased prevalence of frailty among men with HIV. The mechanisms of the muscle-liver-adipose tissue axis underlying NAFLD might differ by HIV serostatus.

A Reference Interval for CT-Based Liver Volume in Dogs without Hepatic Disease.

In both human and veterinary medicine, computed tomography (CT) volumetry provides a quantitative and accurate measure of liver volume. While CT volumetry is recognized as a useful method for assessing liver volume in dogs, a statistically significant reference interval for liver volume in dogs with no history of hepatic disease has not been reported. The purpose of the present study was to define a reference interval for liver volume with no history of hepatic disease using CT volumetry. Medical records from 2 June 2020 to 25 July 2022 were retrospectively reviewed, including 121 dogs that underwent abdominal CT scans and had no history of hepatic disease. Liver volumes were measured using CT volumetry and normalized by body weight. The median of normalized CT-based liver volume in 121 dogs was 22.2 cm3/kg. Based on these data, a weight-based reference interval lower limit of 11.1-15.5 (90% confidence interval [CI]) to an upper limit of 31.9-42.6 (90% CI) cm3/kg for CT-based liver volume was defined in dogs without hepatic disease. This study provides an accurate assessment of liver volume changes in dogs with various hepatic diseases.

Investigating the causes and pattern of peritoneal involvement in CT scan and comparison with ultrasound findings in peritoneal conditions: A two-center, cross-sectional study.

Ultrasound and computed tomography (CT) scans can be used as methods to help make a more accurate diagnosis in diseases involving the omentum and peritoneum. The present study was conducted to determine etiology and CT scan pattern of peritoneal involvement and compare it with ultrasound findings. Patients referred to Ghaem and Imam Reza hospitals who had undergone CT scans and had involvement of peritoneum in abdominal CT scans were included in the study. The findings identified in the CT scan were recorded. According to the underlying cause determined by laparotomy or laparoscopy sample, each disease's most common pattern of involvement and types of patterns were examined. An ultrasound was conducted for every patient and the obtained information was analyzed. A total of 101 patients were included in the study, of which 61 patients (59.8%) were female and the rest were male. The most common involvement patterns in CT scans included nodular (37.6%), mixed (21.8%), and omental cake (17.8%), respectively. In 80 patients (79.2%), CT scan findings were consistent with ultrasound, but in 21 patients (20.8%), CT scan findings were not visible in ultrasound. The most common diagnoses of the patients were colorectal adenocarcinoma and gastric adenocarcinoma (20 cases, 19.8% each), followed by ovarian and uterine adenocarcinoma (19 cases, 18.8%). The most common patterns of involvement of peritoneum in CT scans include nodular pattern, mix, and omental cake. The most common diseases that lead to the involvement of peritoneum are gastrointestinal cancers, uterine and ovarian cancers, and peritonitis.

Virtual non-contrast images in photon-counting computed tomography: impact of different contrast phases.

Photon-counting computed tomography (PCCT) enables new ways of image reconstruction, e.g. material decomposition and creation of virtual non-contrast (VNC) series with higher resolution and lower radiation dose than standard computed tomography (CT). Clinical experiences of this are limited. To compare true non-contrast (TNC) series with VNC series derived from non-enhanced (VNCu), arterial phase (VNCa) and portal venous phase (VNCv) in clinically approved PCCT. A total of 45 clinical, tri-phasic abdominal CT scans from the PCCT Naetom Alpha, between February 2022 and November 2022, were retrospectively assessed. Placing a region of interest in six different locations in each VNC series - right liver parenchyma, left liver parenchyma, spleen, aorta, erector spinae muscle, and in the subcutaneous fat - absolute Hounsfield values (HU) and standard deviations (SD) were collected. Differences in HU (ΔHU) were compared and statistically analyzed. Statistically significant differences between VNC and TNC were seen in all measurements, with the largest difference in the subcutaneous fat and the smallest difference in the erector spinae muscle. Only small differences were seen between VNCa and VNCv, where the largest differences were seen in the left and right liver lobes. VNC images from the first-generation clinically approved PCCT showed a significant difference between VNC and TNC images. The differences vary with the type of tissue. Only small differences were seen depending from which contrast phase the VNC was derived.

A giant solitary fibrous tumor of the abdominal pelvic cavity: A case report and literature review.

Solitary fibrous tumor (SFT) is a rare mesenchymal tumor, especially the giant one from the abdominal pelvic cavity. We report on a rare case of a giant SFT of the abdominal pelvic cavity to review the existing literature in detail to improve the diagnosis and treatment of SFT. The patient is a 52-year-old female who presented with 2 weeks of abdominal distension. Abdominal magnetic resonance imaging showed a giant mass (>20 cm) in the abdominal pelvic cavity, considered a mesenchymal tumor. She denies a history of tumor disease. A whole abdomen bulge and a mass of about 18 cm × 10 cm on the right side and middle side were found in the physical examination after admission. Abdominal enhanced computed tomography revealed a giant cystic-solid mass located on the middle and right side of the abdominal pelvic cavity, measuring approximately 20.4 cm × 11.7 cm, with multiple cystic changes and necrosis and compression of adjacent organs and tissues, and marked inhomogeneous enhancement. The patient underwent an open abdominal pelvic cavity giant tumor operation to achieve a radical resection, and did not undergo chemotherapy or radiotherapy. The patient underwent open complete resection of a giant abdominal pelvic tumor with no complications and was diagnosed as SFT according to the pathology, immunohistochemistry showed that the tumor tested positive for CD34(+), STAT-6(+), and Ki-67 (10%). Abdominal computed tomography scans were performed 6 months after resection, and no signs of recurrence or metastasis were found. The clinical symptoms and imaging features of giant abdominal pelvic cavity SFT are not typical. Preoperative diagnosis is difficult and has the potential for malignancy. Based on the results of the current study, there is no standard treatment strategy around the world and the therapeutic effect of radiation therapy and chemotherapy is relatively limited. Thus, complete surgical resection and close clinical follow-up are advocated.