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This study proposes a markerless Augmented Reality (AR) surgical framework for breast lesion removal using a depth sensor and 3D breast Computed Tomography (CT) images. A patient mesh in the real coordinate system is acquired through a patient 3D scan using a depth sensor for registration. The patient mesh on the virtual coordinate system is obtained by contrast-based skin segmentation in 3D mesh generated from breast CT scans. Then, the nipple area is detected based on the gradient in the segmented skin area. The region of interest (ROI) is set based on the detection result to select the vertices in the virtual coordinate system. The mesh on the real and virtual coordinate systems is first aligned by matching the center of mass, and the Iterative Closest Point (ICP) method is applied to perform more precise registration. Experimental results of 20 patients' data showed 98.35 ± 0.71% skin segmentation accuracy in terms of Dice Similarity Coefficient (DSC) value, 2.79 ± 1.54 mm nipple detection error, and 4.69 ± 1.95 mm registration error. Experiments using phantom and patient data also confirmed high accuracy in AR visualization. The proposed method in this study showed that the 3D AR visualization of medical data on the patient's body is possible by using a single depth sensor without having to use markers. [ABSTRACT FROM AUTHOR]

Background: Despite the dramatic increase in the use of medical imaging in various therapeutic fields of clinical trials, the first step of image quality check (image QC), which aims to check whether images are uploaded appropriately according to the predefined rules, is still performed manually by image analysts, which requires a lot of manpower and time. Methods: In this retrospective study, 1669 computed tomography (CT) images with five specific anatomical locations were collected from Asan Medical Center and Kangdong Sacred Heart Hospital. To generate the ground truth, two radiologists reviewed the anatomical locations and presence of contrast enhancement using the collected data. The individual deep learning model is developed through InceptionResNetv2 and transfer learning, and we propose Image Quality Check-Net (Image QC-Net), an ensemble AI model that utilizes it. To evaluate their clinical effectiveness, the overall accuracy and time spent on image quality check of a conventional model and ImageQC-net were compared. Results: ImageQC-net body part classification showed excellent performance in both internal (precision, 100%; recall, 100% accuracy, 100%) and external verification sets (precision, 99.8%; recovery rate, 99.8%, accuracy, 99.8%). In addition, contrast enhancement classification performance achieved 100% precision, recall, and accuracy in the internal verification set and achieved (precision, 100%; recall, 100%; accuracy 100%) in the external dataset. In the case of clinical effects, the reduction of time by checking the quality of artificial intelligence (AI) support by analysts 1 and 2 (49.7% and 48.3%, respectively) was statistically significant (p < 0.001). Conclusions: Comprehensive AI techniques to identify body parts and contrast enhancement on CT images are highly accurate and can significantly reduce the time spent on image quality checks. [ABSTRACT FROM AUTHOR]

Background: The latest International Myeloma Working Group (IMWG) guideline recommends low-dose whole-body (WB) computed tomography (CT) as the first-line imaging technique for the initial diagnosis of plasma cell disorders. Purpose: To evaluate diagnostic performances of CT and diffusion-weighted imaging (DWI) as the first-line imaging modalities and assess misclassification rates obtained following the guideline. Material and Methods: Two independent radiologists analyzed CT (acquired as PET/CT) and DWI (3-T; b-values = 50 and 900 s/mm2) of patients newly diagnosed with plasma cell disorder, categorizing the number of bone lesions. Diagnostic performance of CT and DWI was compared using the McNemar test, and misclassification rates were calculated with a consensus WB-MRI reading as the reference standard. Differences in lesion number categories were assessed using marginal homogeneity and kappa statistics. Results: Of 56 patients (36 men; mean age = 63.5 years), 39 had myeloma lesions. DWI showed slightly higher sensitivity for detecting myeloma lesions (97.4%) than CT (84.6%–92.3%; P > 0.05). CT showed significantly higher specificity (88.2%) than DWI (52.9%–58.8%; P <0.05). CT had a higher additional study requirement rate than DWI (7.7%–15.4% vs. 2.6%), but a lower unnecessary treatment rate (11.8% vs. 41.2%–47.1%). Both readers showed significant differences in categorization of the number of lesions on CT compared with the reference standard (P < 0.001), and one reader showed a significant difference on DWI (P = 0.006 and 0.098). Conclusion: CT interpreted according to the IMWG guideline is a diagnostically effective first-line modality with relatively high sensitivity and specificity. DWI alone may not be an acceptable first-line imaging modality because of low specificity. [ABSTRACT FROM AUTHOR]

Aim: To examine the association between type 2 diabetes and the amount and quality of trunk muscle as assessed by computed tomography (CT) scan. Materials and methods: A total of 20,986 subjects (13,007 men and 7979 women) who underwent abdominal CT scan as part of a routine health check‐up were included. The total abdominal muscle area (TAMA) measured at the third lumbar vertebrae was classified into skeletal muscle area (SMA), and intermuscular adipose tissue area. SMA was divided into good quality muscles (normal attenuation muscle area [NAMA]) and poor quality muscles (low attenuation muscle area). NAMA/TAMA index was calculated. Results: Subjects with type 2 diabetes had higher values of TAMA and SMA but significantly lower values of NAMA and NAMA/TAMA index. Compared with those in the lowest quartile of NAMA/TAMA index, subjects in the highest quartile had metabolically favourable laboratory findings, a lower prevalence of type 2 diabetes (Q1 vs. Q4: 19.3% vs. 9.5% in men, 12.3% vs. 3.0% in women) and inverse association with type 2 diabetes (odds ratio for Q2, Q3, and Q4: 0.87, 0.78, and 0.75 in men; 0.82, 0.70, and 0.68 in women) after multivariable adjustment. Conclusions: The amount of good quality muscle on CT scan was associated with a lower prevalence of type 2 diabetes. [ABSTRACT FROM AUTHOR]

Simple Summary: Pheochromocytoma is regarded as a good human model for investigating the impact of sympathetic hyperactivity on various pathologic conditions. To determine the influence of catecholamine excess on human body composition, we compared computed tomography (CT)-based fat and skeletal muscle indices over time in a large patient population with histologically confirmed pheochromocytoma who underwent surgery. We observed considerable elevation in CT-measured visceral fat area and subcutaneous fat area, and the prevalence of visceral obesity after adrenalectomy in patients with pheochromocytoma. In contrast, there were no changes in skeletal muscle area, skeletal muscle index, and prevalence of sarcopenia. Furthermore, we observed that the severity of catecholamine excess was associated with a higher increase, especially in the subcutaneous fat area after surgery. These data provide important clinical evidence that sympathetic hyperactivity contributes to lipolysis in visceral and subcutaneous adipose tissues, whereas its impact on human skeletal muscle remains undetermined. Despite the potential biological importance of the sympathetic nervous system on fat and skeletal muscle metabolism in animal and in vitro studies, its relevance in humans remains undetermined. To clarify the influence of catecholamine excess on human body composition, we performed a retrospective longitudinal cohort study including 313 consecutive patients with histologically confirmed pheochromocytoma who underwent repeat abdominal computed tomography (CT) scans before and after adrenalectomy. Changes in CT-determined visceral fat area (VFA), subcutaneous fat area (SFA), skeletal muscle area (SMA), and skeletal muscle index (SMI) were measured at the level of the third lumbar vertebra. The mean age of all patients was 50.6 ± 13.6 years, and 171/313 (54.6%) were women. The median follow-up duration for repeat CTs was 25.0 months. VFA and SFA were 14.5% and 15.8% higher, respectively (both p < 0.001), after adrenalectomy, whereas SMA and SMI remained unchanged. Similarly, patients with visceral obesity significantly increased from 103 (32.9%) at baseline to 138 (44.1%) following surgery (p < 0.001); however, the prevalence of sarcopenia was unchanged. This study provides important clinical evidence that sympathetic hyperactivity can contribute to lipolysis in visceral and subcutaneous adipose tissues, but its impact on human skeletal muscle is unclear. [ABSTRACT FROM AUTHOR]

As sarcopenia research has been gaining emphasis, the need for quantification of abdominal muscle on computed tomography (CT) is increasing. Thus, a fully automated system to select L3 slice and segment muscle in an end-to-end manner is demanded. We aimed to develop a deep learning model (DLM) to select the L3 slice with consideration of anatomic variations and to segment cross-sectional areas (CSAs) of abdominal muscle and fat. Our DLM, named L3SEG-net, was composed of a YOLOv3-based algorithm for selecting the L3 slice and a fully convolutional network (FCN)-based algorithm for segmentation. The YOLOv3-based algorithm was developed via supervised learning using a training dataset (n = 922), and the FCN-based algorithm was transferred from prior work. Our L3SEG-net was validated with internal (n = 496) and external validation (n = 586) datasets. Ground truth L3 level CT slice and anatomic variation were identified by a board-certified radiologist. L3 slice selection accuracy was evaluated by the distance difference between ground truths and DLM-derived results. Technical success for L3 slice selection was defined when the distance difference was < 10 mm. Overall segmentation accuracy was evaluated by CSA error and DSC value. The influence of anatomic variations on DLM performance was evaluated. In the internal and external validation datasets, the accuracy of automatic L3 slice selection was high, with mean distance differences of 3.7 ± 8.4 mm and 4.1 ± 8.3 mm, respectively, and with technical success rates of 93.1% and 92.3%, respectively. However, in the subgroup analysis of anatomic variations, the L3 slice selection accuracy decreased, with distance differences of 12.4 ± 15.4 mm and 12.1 ± 14.6 mm, respectively, and with technical success rates of 67.2% and 67.9%, respectively. The overall segmentation accuracy of abdominal muscle areas was excellent regardless of anatomic variation, with CSA errors of 1.38–3.10 cm2. A fully automatic system was developed for the selection of an exact axial CT slice at the L3 vertebral level and the segmentation of abdominal muscle areas. [ABSTRACT FROM AUTHOR]

Background: The incidence of hepatocellular carcinoma (HCC) has been increasing among the elderly populations. Trans-arterial chemoembolization (TACE), a widely used first-line non-curative therapy for HCCs is an issue in geriatrics. We investigated the prognosis of elderly HCC patients treated with TACE and determined the factors that affect the overall survival.Methods: We included 266 patients who were older than 65 years and had received TACE as initial treatment for HCC. We analyzed the skeletal muscle index (SMI) and visceral-to-subcutaneous fat ratio (VSR) around the third lumbar vertebrae using computed tomography scans. Muscle depletion with visceral adiposity (MDVA) was defined by falling below the median SMI and above the median VSR value sex-specifically. We evaluated the overall survival in association with MDVA and other clinical factors.Results: The mean age was 69.9 ± 4.5 years, and 70.3% of the patients were men. According to the Barcelona Clinic Liver Cancer (BCLC) staging system, 29, 136, and 101 patients were classified as BCLC 0, A, and B stages, respectively, and 79 (29.7%) had MDVA. During the median follow-up of 4.1 years, patients with MDVA had a shorter life expectancy than those without MDVA (P = 0.007) even though MDVA group had a higher objective response rate after the first TACE (82.3% vs. 75.9%, P = 0.035). Multivariate analysis revealed that MDVA (Hazard ratio [HR] 1.515) age (HR 1.057), liver function (HR 1.078), tumor size (HR 1.083), serum albumin level (HR 0.523), platelet count (HR 0.996), tumor stage (stage A, HR 1.711; stage B, HR 2.003), and treatment response after the first TACE treatment (HR 0.680) were associated with overall survival.Conclusions: MDVA is a critical prognostic factor for predicting survival in the elderly patients with HCC who have undergone TACE. [ABSTRACT FROM AUTHOR]

Objectives: To develop and validate a combined radiomics-clinical model to predict malignancy of vertebral compression fractures on CT. Methods: One hundred sixty-five patients with vertebral compression fractures were allocated to training (n = 110 [62 acute benign and 48 malignant fractures]) and validation (n = 55 [30 acute benign and 25 malignant fractures]) cohorts. Radiomics features (n = 144) were extracted from non-contrast-enhanced CT images. Radiomics score was constructed by applying least absolute shrinkage and selection operator regression to reproducible features. A combined radiomics-clinical model was constructed by integrating significant clinical parameters with radiomics score using multivariate logistic regression analysis. Model performance was quantified in terms of discrimination and calibration. The model was internally validated on the independent data set. Results: The combined radiomics-clinical model, composed of two significant clinical predictors (age and history of malignancy) and the radiomics score, showed good calibration (Hosmer-Lemeshow test, p > 0.05) and discrimination in both training (AUC, 0.970) and validation (AUC, 0.948) cohorts. Discrimination performance of the combined model was higher than that of either the radiomics score (AUC, 0.941 in training cohort and 0.852 in validation cohort) or the clinical predictor model (AUC, 0.924 in training cohort and 0.849 in validation cohort). The model stratified patients into groups with low and high risk of malignant fracture with an accuracy of 98.2% in the training cohort and 90.9% in the validation cohort. Conclusions: The combined radiomics-clinical model integrating clinical parameters with radiomics score could predict malignancy in vertebral compression fractures on CT with high discriminatory ability. Key Points: • A combined radiomics-clinical model was constructed to predict malignancy of vertebral compression fractures on CT by combining clinical parameters and radiomics features. • The model showed good calibration and discrimination in both training and validation cohorts. • The model showed high accuracy in the stratification of patients into groups with low and high risk of malignant vertebral compression fractures. [ABSTRACT FROM AUTHOR]

Objectives: To establish inter-reader reliability of CT Liver Imaging Reporting and Data System (LI-RADS) and explore factors that affect it. Methods: MEDLINE and EMBASE databases were searched from January 2014 to March 2020 to identify original articles reporting the inter-reader reliability of CT LI-RADS. The imaging analysis methodology of each study was identified, and pooled intraclass correlation coefficient (ICC) or kappa values (κ) were calculated for lesion size, major features (arterial-phase hyperenhancement [APHE], nonperipheral washout [WO], and enhancing capsule [EC]), and LI-RADS categorization (LR) using random-effects models. Subgroup analyses of pooled κ were performed for the number of readers, average reader experience, differences in reader experience, and LI-RADS version. Results: In the 12 included studies, the pooled ICC or κ of lesion size, APHE, WO, EC, and LR were 0.99 (0.96−1.00), 0.69 (0.58–0.81), 0.67 (0.53–0.82), 0.65 (0.54–0.76), and 0.70 (0.59–0.82), respectively. The experience and number of readers varied: studies using readers with ≥ 10 years of experience showed significantly higher κ for LR (0.82 vs. 0.45, p = 0.01) than those with < 10 years of reader experience. Studies with multiple readers including inexperienced readers showed significantly lower κ for APHE (0.55 vs. 0.76, p = 0.04) and LR (0.45 vs. 0.79, p = 0.02) than those with all experienced readers. Conclusions: CT LI-RADS showed substantial inter-reader reliability for major features and LR. Inter-reader reliability differed significantly according to average reader experience and differences in reader experience. Reported results for inter-reader reliability of CT LI-RADS should be understood with consideration of the imaging analysis methodology. Key Points: • The CT Liver Imaging Reporting and Data System (LI-RADS) provides substantial inter-reader reliability for three major features and category assignment. • The imaging analysis methodology varied across studies. • The inter-reader reliability of CT LI-RADS differed significantly according to the average reader experience and the difference in reader experience. [ABSTRACT FROM AUTHOR]

Objectives: To develop and evaluate a deep learning–based model capable of detecting primary hepatic malignancies in multiphase CT images of patients at high risk for hepatocellular carcinoma (HCC). Methods: A total of 1350 multiphase CT scans of 1280 hepatic malignancies (1202 HCCs and 78 non-HCCs) in 1320 patients at high risk for HCC were retrospectively analyzed. Following the delineation of the focal hepatic lesions according to reference standards, the CT scans were categorized randomly into the training (568 scans), tuning (193 scans), and test (589 scans) sets. Multiphase CT information was subjected to multichannel integration, and livers were automatically segmented before model development. A deep learning–based model capable of detecting malignancies was developed using a mask region–based convolutional neural network. The thresholds of the prediction score and the intersection over union were determined on the tuning set corresponding to the highest sensitivity with < 5 false-positive cases per CT scan. The sensitivity and the number of false-positives of the proposed model on the test set were calculated. Potential causes of false-negatives and false-positives on the test set were analyzed. Results: This model exhibited a sensitivity of 84.8% with 4.80 false-positives per CT scan on the test set. The most frequent potential causes of false-negatives and false-positives were determined to be atypical enhancement patterns for HCC (71.7%) and registration/segmentation errors (42.7%), respectively. Conclusions: The proposed deep learning–based model developed to automatically detect primary hepatic malignancies exhibited an 84.8% of sensitivity with 4.80 false-positives per CT scan in the test set. Key Points: • Image processing, including multichannel integration of multiphase CT and automatic liver segmentation, enabled the application of a deep learning–based model to detect primary hepatic malignancy. • Our model exhibited a sensitivity of 84.8% with a false-positive rate of 4.80 per CT scan. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to examine whether higher skeletal muscle mass is associated with a metabolically healthy phenotype and whether muscle quality affects metabolic health.Methods: This cross-sectional analysis included 20,659 participants (7,966 women) who underwent abdominal computed tomography scans during health checkups. The total abdominal muscle area (TAMA) on the third lumbar vertebral level was demarcated. Intermuscular adipose tissue and skeletal muscle area were measured. The skeletal muscle area was divided into normal attenuation muscle area (NAMA) and low attenuation muscle area (LAMA). The NAMA/TAMA index was calculated. The metabolically unhealthy phenotype was defined as having two or more components of metabolic syndrome or the presence of hypertension or diabetes.Results: TAMA and skeletal muscle area were not significantly different or even lower in metabolically healthy phenotypes compared with metabolically unhealthy phenotypes. However, metabolically healthy phenotypes had significantly higher NAMA (except in women with obesity) and NAMA/TAMA index than in the metabolically unhealthy phenotypes. In people without obesity, lower NAMA/TAMA index was independently associated with higher risk of the metabolically unhealthy phenotype in the fully adjusted model.Conclusions: The metabolically healthy phenotypes had more good-quality muscles than did the metabolically unhealthy phenotypes. These results suggest that not only muscle mass but also muscle quality (i.e., degree of myosteatosis) are associated with metabolic health. [ABSTRACT FROM AUTHOR]

Background: Skeletal muscle depletion is prevalent in elderly patients and is associated with unfavorable outcomes in patients with chronic diseases. However, the relationship between skeletal muscle mass and neurological outcomes following in-hospital cardiac arrest (IHCA) has not been evaluated. The aim of this study was to investigate whether skeletal muscle status before cardiac arrest is an independent factor affecting neurological outcomes in patients with IHCA. Methods: We reviewed a prospectively enrolled registry of IHCA patients. Consecutive adult patients (>18 years) admitted to a tertiary care hospital from 2013 to 2019 were included in the study. Of these, 421 patients who underwent abdominopelvic computed tomography within 3 months of cardiac arrest were included. Skeletal muscle index (SMI) was measured at the third lumbar vertebra, and skeletal muscle depletion was defined using sex- and body mass index-specific cutoffs of SMI. The primary outcome was a Cerebral Performance Category score of 1 or 2 at 6 months after cardiac arrest, which was considered a good neurological outcome. Results: Of the 421 patients, 248 (58.9%) had skeletal muscle depletion before IHCA. The patients without skeletal muscle depletion showed significantly better neurological outcomes at 6 months after cardiac arrest than those with pre-arrest muscle depletion (20.8 vs. 10.9%, p = 0.004). The absence of skeletal muscle depletion was significantly associated with good neurological outcomes in a multivariable logistic analysis (OR = 3.49, 95% confidence intervals: 1.83–6.65, p < 0.001), along with the absence of diabetes, presence of active cancer, shockable rhythm, and short resuscitation duration. Conclusion: Pre-arrest skeletal muscle depletion was associated with long-term mortality and poor neurological outcomes after IHCA. Skeletal muscle depletion may be used as a tool to identify at-risk patients who may benefit from aggressive treatments. [ABSTRACT FROM AUTHOR]

Objectives: To systematically determine the diagnostic performance of computed tomography (CT) and magnetic resonance imaging (MRI) for differentiating autoimmune pancreatitis (AIP) from pancreatic ductal adenocarcinoma (PDAC), with a comparison between the two imaging modalities. Methods: Literature search was conducted using PubMed and EMBASE databases to identify original articles published between 2009 and 2019 reporting the diagnostic performance of CT and MRI for differentiating AIP from PDAC. The meta-analytic sensitivity and specificity of CT and MRI were calculated, and compared using a bivariate random effects model. Subgroup analysis for differentiating focal AIP from PDAC was performed. Results: Of the 856 articles screened, 11 eligible articles are remained, i.e., five studies for CT, four for MRI, and two for both. The meta-analytic summary sensitivity and specificity of CT were 59% (95% confidence interval [CI], 41–75%) and 99% (95% CI, 88–100%), respectively, while those of MRI were 84% (95% CI, 68–93%) and 97% (95% CI, 87–99%). MRI had a significantly higher meta-analytic summary sensitivity than CT (84% vs. 59%, p = 0.02) but a similar specificity (97% vs. 99%, p = 0.18). In the subgroup analysis for focal AIP, the sensitivity for distinguishing between focal AIP and PDAC was lower than that for the overall analysis. MRI had a higher sensitivity than CT (76% vs. 50%, p = 0.28) but a similar specificity (97% vs. 98%, p = 0.07). Conclusion: MRI might be clinically more useful to evaluate patients with AIP, particularly for differentiating AIP from PDAC. Key Points: • MRI had an overall good diagnostic performance to differentiate AIP from PDAC with a meta-analytic summary estimate of 83% for sensitivity and of 97% for specificity. • CT had a very high specificity (99%), but a suboptimal sensitivity (59%) for differentiating AIP from PDAC. • Compared with CT, MRI had a higher sensitivity, but a similar specificity. [ABSTRACT FROM AUTHOR]

Background: Patients with gastric cancer have an increased nutritional risk and experience a significant skeletal muscle loss after surgery. We aimed to determine whether muscle loss during the first postoperative year and preoperative nutritional status are indicators for predicting prognosis.Methods: From a gastric cancer registry, a total of 958 patients who received curative gastrectomy followed by chemotherapy for stage 2 and 3 gastric cancer and survived longer than 1 year were investigated. Clinical and laboratory data were collected. Skeletal muscle index (SMI) was assessed based on the muscle area at the L3 level on abdominal computed tomography.Results: Preoperative nutritional risk index (NRI) and postoperative decrement of SMI (dSMI) were significantly associated with overall survival (hazards ratio: 0.976 [95% CI: 0.962-0.991] and 1.060 [95% CI: 1.035-1.085], respectively) in a multivariate Cox regression analysis. Recurrence, tumor stage, comorbidity index were also significant prognostic indicators. Kaplan-Meier analyses exhibited that patients with higher NRI had a significantly longer survival than those with lower NRI (5-year overall survival: 75.8% vs. 63.0%, P <  0.001). In addition, a significantly better prognosis was observed in a patient group with less decrease of SMI (5-year overall survival: 75.7% vs. 66.2%, P = 0.009). A logistic regression analysis demonstrated that the performance of preoperative NRI and dSMI in mortality prediction was quite significant (AUC: 0.63, P <  0.001) and the combination of clinical factors enhanced the predictive accuracy to the AUC of 0.90 (P <  0.001). This prognostic relevance of NRI and dSMI was maintained in patients experiencing tumor recurrence and highlighted in those with stage 3 gastric adenocarcinoma.Conclusions: Preoperative NRI is a predictor of overall survival in stage 2 or 3 gastric cancer patients and skeletal muscle loss during the first postoperative year was significantly associated with the prognosis regardless of relapse in stage 3 tumors. These factors could be valuable adjuncts for accurate prediction of prognosis in gastric cancer patients. [ABSTRACT FROM AUTHOR]

Background: Although computed tomography (CT) is considered the gold standard for investigating skeletal muscles, diagnostic cutoff points for sarcopenia have not been established. We therefore suggested clinically relevant diagnostic cutoff points for sarcopenia based on reference values of skeletal muscle area (SMA) measured by CT scan in a large-sized healthy Asian population.Methods: This cross-sectional analysis included 11,845 subjects (7,314 men, 4,531 women) who underwent abdominal CT scans in South Korea. SMA including all muscles on the selected axial images of the L3 lumbar vertebrae level was demarcated using predetermined thresholds (-29 to +150 Hounsfield units). SMA indices (height-, weight-, and body mass index [BMI]-adjusted) were calculated.Results: When T-score < -2.0 was used as the cutoff for defining sarcopenia, the sex-specific cutoff points of SMA, SMA/height2, SMA/weight, and SMA/BMI were 119.3 and 74.2 cm2, 39.8 and 28.4 cm2/m2, 1.65 and 1.38 cm2/kg, and 4.97 and 3.46 in men and women, respectively. In both sexes, the SMA/BMI values peaked in the 20s and decreased gradually. The SMA/BMI yielded the highest diagnostic rate of sarcopenia (4.2% in men, 8.7% in women), while SMA/height2 provided the lowest yield (2.8% in men, 1.0% in women).Conclusions: This is the first study to report the reference values of SMA and skeletal muscle indices (SMIs) measured on CT scans and to suggest cutoff points for diagnosis of sarcopenia based on T-score in Asian subjects. BMI-adjusted index (SMA/BMI) was the best index of CT-measured SMA to reflect the age-related muscle changes and to maximize the diagnostic yield for sarcopenia. [ABSTRACT FROM AUTHOR]

Objectives: To identify CT features distinguishing neuroendocrine carcinomas (NECs) of pancreas from well-differentiated neuroendocrine tumors (NETs) according to the World Health Organization 2017 and 2019 classification systems.Methods: This retrospective study included 69 patients with pathologically confirmed pancreatic neuroendocrine neoplasms who underwent dynamic CT (17, 17, 18, and 17 patients for well-differentiated grade 1, 2, 3 NET and NEC, respectively). CT was used to perform qualitative analysis (component, homogeneity, calcification, peripancreatic infiltration, main pancreatic ductal dilatation, bile duct dilatation, intraductal extension, and vascular invasion) and quantitative analysis (interface between tumor and parenchyma [delta], arterial enhancement ratio [AER], portal enhancement ratio [PER], and dynamic enhancement pattern). Uni- and multivariate logistic regression analyses were performed to identify features indicating NEC. Optimal cutoff values for enhancement ratios were determined.Results: NECs demonstrated significantly higher frequencies of main pancreatic ductal dilatation, bile duct dilatation, vascular invasion, and significantly lower delta (i.e., lower conspicuity), AER, and PER than well-differentiated NET (p < 0.05). On multivariate analysis, PER was the only independent factor selected by the model for differentiation of NEC from well-differentiated NET (odds ratio, < 0.001; 95% confidence interval [CI], < 0.001-0.012). PER < 0.8 showed the sensitivity of 94.1% (95% CI, 71.3-99.9) and the specificity of 88.5% (95% CI, 76.6-95.6). When three significant CT features were combined, the sensitivity and specificity for diagnosing NEC were 88.2% and 88.5%, respectively.Conclusions: Tumor-parenchyma enhancement ratio in portal phase is a useful CT feature to distinguish NECs from well-differentiated NETs. Combining qualitative and quantitative CT features may aid in achieving good diagnostic accuracy in the differentiation between NEC and well-differentiated NET.Key Points: • Neuroendocrine carcinoma of the pancreas should be distinguished from well-differentiated neuroendocrine tumor in line with the revised grading and staging system. • Neuroendocrine carcinoma of the pancreas can be differentiated from well-differentiated neuroendocrine tumor on dynamic CT based on assessment of the portal enhancement ratio, arterial enhancement ratio, tumor conspicuity, dilatation of the main pancreatic duct or bile duct, and vascular invasion. • Tumor-parenchyma enhancement ratio in portal phase of dynamic CT is a useful feature, which may help to distinguish neuroendocrine carcinoma from well-differentiated neuroendocrine tumor of the pancreas. [ABSTRACT FROM AUTHOR]

Background: Determining if a given patient with primary pancreatic adenocarcinoma (PDA) has hepatic metastasis is important for treatment planning. Several previous studies reported on the diagnostic performance of MRI for liver metastasis in patients with PDA. But the reported data are quite variable.Purpose: To systematically determine the diagnostic performance of MRI for liver metastasis in patients with PDA, including comparing it with computed tomography (CT).Study Type: Systemic review and meta-analysis.Subjects: In all, 457 patients from five eligible articles.Field Strength/sequence: Conventional MR sequences with or without contrast enhancement at 1.5T and 3T.Assessment: Two reviewers independently performed the data extraction. The reviewers identified and reviewed the original articles reporting the diagnostic performance of MRI for liver metastases in patients with PDA, including those articles making comparisons with CT.Statistical Tests: Meta-analytic summary sensitivity and specificity were calculated on a per-patient basis using a bivariate random effects model. We compared the meta-analytic summary sensitivity and specificity between MRI and CT.Results: The meta-analytic summary sensitivity and specificity were 85% (95% confidence interval [CI], 74-92%; I2 = 0%) and 98% (95% CI, 78-100%; I2 = 85%), respectively. In comparison with CT, MRI showed a higher sensitivity (85% vs. 75%) but similar specificity (98% vs. 94%).Data Conclusion: MRI had good overall diagnostic performance for liver metastasis in patients with PDA, with a higher sensitivity than CT.Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:1737-1744. [ABSTRACT FROM AUTHOR]

Objective: To evaluate predictive values of sarcopenia and visceral obesity measured from preoperative CT/MRIs for postoperative pancreatic fistula (POPF) after pancreaticoduodenectomy in patients with periampullary malignancies.Methods: From the prospectively constructed surgical registry, we included adult patients treated with pancreaticoduodenectomy. Based on CT/MRIs, body morphometric analysis was performed to evaluate the visceral obesity and sarcopenia, based on the areas of visceral fat and skeletal muscle measured at the L3 vertebrae level. We retrieved various perioperative factors from registry. As outcomes of postoperative complications, we evaluated POPF and major complications based on the Clavien-Dindo classification. Multivariate logistic regression analyses were performed.Results: From a total of 284 patients (163 males, 121 females) who met the inclusion/exclusion criteria, POPF, major complications, and 60-day mortality occurred in 52 (18.3%), 34 (12.0%), and 6 (2.1%), respectively. Sarcopenia and visceral obesity were noted in 123 (75.5%) and 66 (40.5%) of men and 68 (56.2%) and 53 (43.8%) of women, respectively. Combination of sarcopenia and obesity (sarcopenic obesity) was noted in 31.9% (52/163) of men and in 26.4% (32/121) of women. In multivariate logistic regression analyses, sarcopenic obesity was the only independent predictor for POPF (OR 2.65, 95% CI 1.43-4.93), and the vascular resection during pancreaticoduodenectomy was the only independent predictor for severe complications (OR 3.75, 95% CI 1.61-8.70).Conclusion: Sarcopenic obesity might be highly predictive for POPF. Body morphometric analysis in preoperative CT/MRI combined with assessment of perioperative clinical features may help to identify high-risk patients and determine perioperative management strategies.Key Points: • Sarcopenic obesity might be predictive for postoperative pancreatic fistula after pancreaticoduodenectomy. • The vascular resection during pancreaticoduodenectomy might be predictive of major complications. • Body morphometric analysis might be helpful for identifying high-risk patients. [ABSTRACT FROM AUTHOR]

Background: Imaging studies, including computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET), have an essential role in the detection and localization of colorectal liver metastasis (CRLM).Purpose: To systematically determine the diagnostic accuracy of multidetector row CT (MDCT), gadoxetate disodium-enhanced MRI, and PET/CT for diagnosing CRLM and the sources of heterogeneity between the reported results.Study Type: Systematic review and meta-analysis.Subjects: In all, 2151 lesions in CT studies, 2301 lesions in MRI studies, 1846 lesions in PET/CT studies, FIELD STRENGTH: 1.5T and 3.0T.Assessment: We identified research studies that investigated MDCT, gadoxetate disodium-enhanced MRI, and PET/CT to diagnose CRLM by performing a systematic search of PubMed MEDLINE and EMBASE. Study quality was assessed using Quality Assessment of Diagnostic Accuracy Studies (QUADAS-2).Statistical Tests: According to the types of imaging tests, study heterogeneity and the threshold effect were analyzed and the meta-analytic summary of sensitivity and specificity were estimated. Meta-regression analysis was performed to further investigate study heterogeneity.Results: Of the 860 articles screened, we found 36 studies from 24 articles reporting a diagnosis of CRLM (11 CT studies, 12 MRI studies, and 13 PET/CT studies). The meta-analytic summary sensitivity for CT, MRI, and PET/CT were 82.1% (95% confidence interval [CI], 74.0-88.1%), 93.1% (95% CI, 88.4-96.0%), and 74.1% (95% CI, 62.1-83.3%), respectively. The meta-analytic summary specificity for CT, MRI, and PET/CT were 73.5% (95% CI, 53.7-86.9%), 87.3% (95% CI, 77.5-93.2%), and 93.9% (95% CI, 83.9-97.8%), respectively. There was no threshold effect in any of the imaging tests. Neoadjuvant chemotherapy significantly decreased the sensitivity of CT and MRI (P < 0.01), although it did not significantly affect the sensitivity of PET/CT. The study design, type of reference standard, and study quality also affected the diagnostic performances of imaging studies.Data Conclusion: Despite the heterogeneous accuracy between studies, gadoxetate disodium-enhanced MRI showed the highest sensitivity, and gadoxetate disodium-enhanced MRI and PET/CT had similar specificities for diagnosing CRLM.Level Of Evidence: 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1237-1250. [ABSTRACT FROM AUTHOR]

Background: This study analyzes the clinicopathologic and radiologic characteristics of malignant serous cystic neoplasm (SCN) of the pancreas through systematic review and an institutional case report. Methods: A comprehensive literature search was performed in the MEDLINE database to identify studies on malignant SCNs of the pancreas that had detailed clinicopathologic and radiologic information. A computerized systematic search of our institutional database was also performed to identify cases of malignant SCN for addition to the systematic review. Using the final included cases, we analyzed the clinicopathologic and radiologic features of malignant SCNs of the pancreas. Results: A review of 136 candidate articles identified 26 studies with 26 cases that had detailed clinical information. Our institutional data search added one case. The systematic review of the 27 cases revealed that primary tumors (mean diameter 10.2 ± 4.0 cm) mainly involved the body and tail of the pancreas (n = 16) and frequently invaded adjacent organs (n = 19). Distant metastases occurred in 14 patients (synchronous, n = 5; metachronous, n = 8; both, n = 1), most commonly in the liver (n = 13). Imaging features of malignant SCNs of the pancreas were identical to the benign counterpart, except local invasion or distant metastases. The prognosis was excellent in that 17 were alive at the time of writing with a median follow-up period of 2 years. Conclusions: The malignant potential of SCNs of the pancreas should be considered in the diagnosis and management of patients with pancreatic SCNs. [ABSTRACT FROM AUTHOR]

Objectives: To evaluate the prognostic value of CT to predict recurrence-free and overall survival in patients with pancreatic neuroendocrine neoplasms (PanNENs).Methods: Between January 2004 and December 2012, 161 consecutive patients who underwent preoperative triphasic CT and surgical resection with curative intent for PanNENs were identified. The tumour consistency, margin, presence of calcification, pancreatic duct dilatation, bile duct dilatation, vascular invasion, and hepatic metastases were evaluated. The tumour size, arterial enhancement ratio, and portal enhancement ratio were measured. The Cox proportional hazard model was used to determine the association between CT features and recurrence-free survival and overall survival.Results: By multivariate analysis, tumour size (>3 cm) (hazard ratio, 3.314; p = 0.006), portal enhancement ratio (≤1.1) (hazard ratio, 2.718; p = 0.006), and hepatic metastases (hazard ratio, 4.374; p = 0.003) were independent significant variables for worse recurrence-free survival. Portal enhancement ratio (≤1.1) (hazard ratio, 5.951; p = 0.001) and hepatic metastases (hazard ratio, 4.122; p = 0.021) were independent significant variables for worse overall survival.Conclusions: Portal enhancement ratio (≤1.1) and hepatic metastases assessed on CT were common independent prognostic factors for worse recurrence-free survival and overall survival in patients with PanNENs.Key Points: • CT is useful to predict survival outcomes in patients with PanNENs. • Survival outcomes are associated with portal enhancement ratio and hepatic metastases. • Portal enhancement ratio is prognostic CT biomarker in patients with PanNENs. [ABSTRACT FROM AUTHOR]

A Correction to this paper has been published: https://doi.org/10.1007/s00330-021-07949-z [ABSTRACT FROM AUTHOR]

Background: Detection and quantification of intra-abdominal free fluid (ie, ascites) on computed tomography (CT) images are essential processes for finding emergent or urgent conditions in patients. In an emergency department, automatic detection and quantification of ascites will be beneficial.Objective: We aimed to develop an artificial intelligence (AI) algorithm for the automatic detection and quantification of ascites simultaneously using a single deep learning model (DLM).Methods: We developed 2D DLMs based on deep residual U-Net, U-Net, bidirectional U-Net, and recurrent residual U-Net (R2U-Net) algorithms to segment areas of ascites on abdominopelvic CT images. Based on segmentation results, the DLMs detected ascites by classifying CT images into ascites images and nonascites images. The AI algorithms were trained using 6337 CT images from 160 subjects (80 with ascites and 80 without ascites) and tested using 1635 CT images from 40 subjects (20 with ascites and 20 without ascites). The performance of the AI algorithms was evaluated for diagnostic accuracy of ascites detection and for segmentation accuracy of ascites areas. Of these DLMs, we proposed an AI algorithm with the best performance.Results: The segmentation accuracy was the highest for the deep residual U-Net model with a mean intersection over union (mIoU) value of 0.87, followed by U-Net, bidirectional U-Net, and R2U-Net models (mIoU values of 0.80, 0.77, and 0.67, respectively). The detection accuracy was the highest for the deep residual U-Net model (0.96), followed by U-Net, bidirectional U-Net, and R2U-Net models (0.90, 0.88, and 0.82, respectively). The deep residual U-Net model also achieved high sensitivity (0.96) and high specificity (0.96).Conclusions: We propose a deep residual U-Net-based AI algorithm for automatic detection and quantification of ascites on abdominopelvic CT scans, which provides excellent performance. [ABSTRACT FROM AUTHOR]

Abstract: Purpose: To evaluate the diagnostic values of CT findings of nutcracker syndrome (NCS). Methods and materials: Twenty seven subjects that underwent CT and renal venography, were divided into three groups based on the venographic renocaval pressure gradient (PG) and collateral veins of the left renal vein (LRV): non-compensated NCS patients with PG≥3mm Hg (group 1, n =12), partially compensated NCS patients with borderline PG (1<3mm Hg) and collateral veins (group 2, n =6), and control group with low PG (0–1mm Hg) without collateral veins (group 3, n =9). The CT findings were analyzed with regard to abrupt narrowing of the LRV with an acute angle (beak sign), aortomesenteric angle between the superior mesenteric artery and aorta on sagittal images, and LRV diameter ratio (hilar-aortomesenteric). Results: Beak sign of the LRV was found in 91.7% (11/12) of group 1, 50% (3/6) of group 2, and in 11.1% (1/9) of group 3 with the significant difference between groups 1 and 3 (P <.05, χ 2 test). Mean values of all quantitative CT parameters differed significantly only between groups 1 and 3 (P <.05, one-way ANOVA test). For differentiating the non-compensated NCS from the control group, the beak sign showed 91.7% sensitivity and 88.9% specificity. Of the various CT parameters, the beak sign and LRV diameter ratio of ≥4.9 showed the greatest diagnostic accuracy (AUC 0.903, ROC analysis). Conclusion: Beak sign of the LRV and CT findings can be useful in diagnosing the non-compensated NCS. [Copyright &y& Elsevier]

Abstract: Purpose: The purpose of this study was to retrospectively assess possible clinical predictors of malignant pleural effusion in patients with ovarian cancer. Materials and methods: This review was performed on 38 ovarian cancer patients that showed pleural effusion in a CT scan and who underwent thoracocentesis before treatment. CT scans were obtained using a 4-channel multi-detector CT scanner. Fisher''s exact test was used to determine the probability of malignant pleural effusion as a function of; amount of ascites, lymph node enlargement, amount of pleural effusion, pleural nodules, and pleural thickening. Results: Sixteen (42.1%) of the 38 patients had malignant pleural effusion and malignant pleural effusion amounts were greater than those with nonmalignant effusion. Pleural nodules were more frequently found in the malignant pleural effusion group (eight [50%] patients) than in the nonmalignant group (zero [0%] patient) (p <0.001). Supradiaphragmatic lymph node enlargement (with short axis diameter 1cm or more) was more frequent in malignant group (12 [75%] patients) than in the nonmalignant group (two [9.1%] patients) (p <0.001). Conclusion: The probability of malignant pleural effusion in patients with ovarian cancer was found to be correlated with the amount of pleural effusion, the presence of pleural nodules, and supradiaphragmatic lymph node enlargement. [Copyright &y& Elsevier]

Objective: We aimed to describe radiologic signs and time-course of imatinib-associated fluid retention (FR) in patients with gastrointestinal stromal tumor (GIST), and its implications for management. Materials and Methods In this Institutional Review Board-approved, retrospective study of 403 patients with GIST treated with imatinib, 15 patients with imaging findings of FR were identified by screening radiology reports, followed by manual confirmation. Subcutaneous edema, ascites, pleural effusion, and pericardial effusion were graded on a four-point scale on CT scans; total score was the sum of these four scores. Results: The most common radiologic sign of FR was subcutaneous edema (15/15, 100%), followed by ascites (12/15, 80%), pleural effusion (11/15, 73%), and pericardial effusion (6/15, 40%) at the time of maximum FR. Two distinct types of FR were observed: 1) acute/progressive FR, characterized by acute aggravation of FR and rapid improvement after management, 2) intermittent/steady FR, characterized by occasional or persistent mild FR. Acute/progressive FR always occurred early after drug initiation/dose escalation (median 1.9 month, range 0.3-4.0 months), while intermittent/steady FR occurred at any time. Compared to intermittent/steady FR, acute/progressive FR was severe (median score, 5 vs. 2.5, p = 0.002), and often required drug-cessation/dose-reduction. Conclusion: Two distinct types (acute/progressive and intermittent/steady FR) of imatinib-associated FR are observed and each type requires different management.

Objective: To comprehensively analyze the spectrum of imaging features of the primary tumors and metastatic patterns of the Extraskeletal Ewing sarcoma family of tumors (EES) in adults. Materials and Methods We performed a computerized search of our hospital's data-warehouse from 1996 to 2013 using codes for Ewing sarcoma and primitive neuroectodermal tumors as well as the demographic code for ≥ 18 years of age. We selected subjects who were histologically confirmed to have Ewing sarcoma of extraskeletal origin. Imaging features of the primary tumor and metastatic disease were evaluated for lesion location, size, enhancement pattern, necrosis, margin, and invasion of adjacent organs. Results: Among the 70 patients (mean age, 35.8 ± 15.6 years; range, 18-67 years) included in our study, primary tumors of EES occurred in the soft tissue and extremities (n = 20), abdomen and pelvis (n = 18), thorax (n = 14), paravertebral space (n = 8), head and neck (n = 6), and an unknown primary site (n = 4). Most primary tumors manifested as large and bulky soft-tissue masses (mean size, 9.0 cm; range, 1.3-23.0 cm), frequently invading adjacent organs (45.6%) and showed heterogeneous enhancement (73.7%), a well-defined (66.7%) margin, and partial necrosis/cystic degeneration (81.9%). Notably, 29 patients had metastatic disease detected at their initial diagnosis. The most frequent site of metastasis was lymph nodes (75.9%), followed by bone (31.0%), lung (20.7%), abdominal solid organs (13.8%), peritoneum (13.8%), pleura (6.9%), and brain (3.4%). Conclusion: Primary tumors of EES can occur anywhere and mostly manifest as large and bulky, soft-tissue masses. Lymph nodes are the most frequent metastasis sites.

Previous studies on changes in body composition of pancreatic cancer patients have only focused on short-term survivors. We studied longitudinal body composition changes and factors affecting them in long-term survivors by analyzing many abdominal computed tomography images using artificial intelligence technology. Of 302 patients who survived for >36 months after surgery were analyzed. Multivariate logistic regression analysis for factors affecting body composition changes and repeated-measures analysis of variance to observe differences in the course of change according to each factor were performed. In logistic analysis, preoperative sarcopenia and recurrence were the main factors influencing body composition changes at 1 and 3 years after surgery, respectively. In changes of longitudinal body composition, the decrease in body composition was the greatest at 3–6 months postoperatively, and the preoperative status did not recover even 3 years after surgery. Especially, males showed a greater reduction in skeletal muscle (SKM) after surgery than females (p < 0.01). In addition, SKM (p < 0.001) and subcutaneous adipose tissue (p < 0.05) mass rapidly decreased in case of recurrence. In conclusion, long-term survivors of pancreatic cancer did not recover their preoperative body composition status, and preoperative sarcopenia and recurrence influenced body composition changes. [ABSTRACT FROM AUTHOR]

Simple Summary: The average human life expectancy is increasing worldwide, which is leading to increases in the proportion of elderly patients (≥80 years) with gastric cancer. Endoscopic submucosal dissection (ESD) is widely regarded as a safe and effective treatment for early gastric cancer (EGC), even in aged or high-risk patients. We investigated the oncologic outcomes in elderly patients who underwent endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) by focusing on the impact of comorbidities, sarcopenia, and nutritional status. Over a median follow-up period of 70.5 months, the 3- and 5-year overall survival (OS) rates were 89.5% and 77.1%, respectively; of the114 patients who died, only four (3.5%) were due to gastric cancer. A total of 173 (61.8%) had sarcopenia, and they had lower rates of 3-year (88.4% vs. 91.4%) and 5-year (73.1% vs. 84.0%; p = 0.046) OS than did those without sarcopenia. In multivariable analyses, prognostic nutritional index (hazard ratio [HR], 0.93; 95% confidence interval [CI]: 0.90–0.98; p = 0.002) and Charlson comorbidity index (HR 1.19; 95% CI: 1.03–1.37; p = 0.018) showed that ESD was a feasible and safe therapeutic method to use in elderly patients, whose long-term survival was significantly associated with nutritional status and comorbidities. Background/Aim: We investigated the oncologic outcomes in elderly patients who underwent endoscopic submucosal dissection (ESD) for early gastric cancer (EGC) by focusing on the impact of comorbidities, sarcopenia, and nutritional status. Methods: Between 2005 and 2016, 280 patients aged ≥ 80 years with 289 EGCs underwent ESD at a tertiary care center. The short- and long-term survival outcomes were assessed. Cox regression analysis was used to identify factors associated with survival, including clinicopathologic factors and abdominal muscle area measured by computed tomography. Results: The rates of en bloc, R0, and, curative resection were 99.3%, 90.0%, and 69.2%, respectively. The rates of post-ESD bleeding and perforation rates were 2.1% and 3.1%, respectively, and no cases showed significant life-threatening adverse events. Over a median follow-up period of 70.5 months, the 3- and 5-year overall survival (OS) rates were 89.5% and 77.1%, respectively; of the114 patients who died, only four (3.5%) were due to gastric cancer. A total of 173 (61.8%) had sarcopenia, and they had lower rates of 3-year (88.4% vs. 91.4%) and 5-year (73.1% vs. 84.0%; p = 0.046) OS than did those without sarcopenia. In multivariable analyses, prognostic nutritional index (hazard ratio [HR], 0.93; 95% confidence interval [CI]: 0.90–0.98; p = 0.002) and Charlson comorbidity index (HR 1.19; 95% CI: 1.03–1.37; p = 0.018) were significant factors associated with overall survival. Conclusions: ESD was a feasible and safe therapeutic method to use in elderly patients, whose long-term survival was significantly associated with nutritional status and comorbidities. These results suggest the need for a possible extension of the curative criteria for ESD in elderly patients with EGC. [ABSTRACT FROM AUTHOR]

Simple Summary: The number of colorectal cancer survivors is increasing due to improvements in oncologic outcomes. Therefore, the risks of metachronous cancer and second cancer are also increased, as well as recurrences. The influence of muscle mass measured as sarcopenia on long-term survival has been studied recently in colorectal cancer patients. Sarcopenia is a factor controllable by lifestyle modification and has gained interest more recently. This study showed an influence of changes in sarcopenia on long-term oncologic outcomes in colorectal cancer and suggests a basis for further investigation of body composition factors, including sarcopenia. The effect of perioperative sarcopenic changes on prognosis remains unclear. We conducted a retrospective cohort study with 2333 non-metastatic colorectal cancer patients treated between January 2009 and December 2012 at the Asan Medical Center. The body composition at diagnosis was measured via abdominopelvic computed tomography (CT) using Asan-J software. Patients underwent CT scans preoperatively, as well as at 6 months–1 year and 2–3 years postoperatively. The primary outcome was the association between perioperative sarcopenic changes and survival. According to sarcopenic criteria, 1155 (49.5%), 890 (38.2%), and 893 (38.3%) patients had sarcopenia preoperatively, 6 months–1 year, and 2–3 years postoperatively, respectively. The 5-year overall survival (OS) (95.8% vs. 92.1%, hazard ratio (HR) = 2.234, p < 0.001) and 5-year recurrence-free survival (RFS) (93.2% vs. 86.2%, HR = 2.251, p < 0.001) rates were significantly lower in patients with preoperative sarcopenia. Both OS and RFS were lower in patients with persistent sarcopenia 2–3 years postoperatively than in those who recovered (OS: 96.2% vs. 90.2%, p = 0.001; RFS: 91.1% vs. 83.9%, p = 0.002). In multivariate analysis, postoperative sarcopenia was confirmed as an independent factor associated with decreased OS and RFS. Pre- and postoperative sarcopenia and changes in the condition during surveillance were associated with oncological outcomes. [ABSTRACT FROM AUTHOR]

To assess the additional value of 2-deoxy-2-[18F] fluoro-d-glucose ([18F]FDG) positron emission tomography (PET) or PET/CT over conventional morphological imaging techniques in the treatment response assessment of gastrointestinal stromal tumor (GIST) to molecular targeted therapy (MTT), we performed a meta-analysis of all the available studies to compare the predictive value of [18F]FDG PET or PET/CT and conventional imaging techniques for assessing the response to MTT in GIST. We determined the sensitivities and specificities across studies, we calculated the positive and negative likelihood ratios (LR) and made summary receiver operating characteristic curves (SROC) using hierarchical regression models. Pooled analysis included 4 studies comprising 88 patients. The performance characteristics in [18F]FDG PET or PET/CT and CT were as follows: sensitivity, 89% (95% confidence interval (CI) 78, 95), 52% (39, 64); specificity, 65% (44, 83), 92% (75, 99); diagnostic odds ratios (DOR), 5.8 (2.0, 16.8 4.9 (1.5, 16.1); positive LR, 1.9 (1.1, 3.4), 3.0 (1.1, 8.1); and negative LR, 0.23 (0.03, 1.6), 0.66 (0.42, 1.0), respectively. In SROC curves, the area under the curve (AUC) was 0.81 (SE, 0.11) and 0.71 (SE, 0.13) and the Q* index was 0.74 and 0.66, respectively. [18F]FDG PET/CT had higher sensitivity, while DOR and SROC curves showed better diagnostic performance in [18F]FDG PET and PET/CT studies as compared to CT. [ABSTRACT FROM AUTHOR]

A decrease in skeletal muscle mass has been shown to increase hospital mortality. Nevertheless, little is known about the association between progressive muscle loss over time and clinical outcomes. We aimed to evaluate whether progressive loss of muscle mass in septic shock patients was associated with mortality. We reviewed prospectively enrolled registry of septic shock which had 817 consecutive patients. Of these, 175 patients who had computed tomography (CT) at a time of admission as well as 3–6 months prior to admission were included. Between these two CTs, the change in total abdominal muscle area index (TAMAI) was evaluated for progressive muscle loss. The change in TAMAI was higher in the non-survivors (−7.6 cm2/m2, 19.0% decrease) than the survivors (−4.0 cm2/m2, 10.5% decrease) with statistical significance (p = 0.002). Multiple logistic regression showed that the patients who had more than a 6.4 cm2/m2 (16.7%) reduction of TAMAI had a 4.42-fold higher risk for mortality at 28 days (OR, 4.42; 95% CI, 1.41–13.81, p = 0.011). Our study suggested that progressive loss of muscle mass might be a useful prognostic factor for septic shock patients. This implication will need to be further explored in future prospective studies. [ABSTRACT FROM AUTHOR]

In this paper, we propose a rapid rigid registration method for the fusion visualization of intraoperative 2D X-ray angiogram (XA) and preoperative 3D computed tomography angiography (CTA) images. First, we perform the cardiac cycle alignment of a patient's 2D XA and 3D CTA images obtained from a different apparatus. Subsequently, we perform the initial registration through alignment of the registration space and optimal boundary box. Finally, the two images are registered where the distance between two vascular structures is minimized by using the local distance map, selective distance measure, and optimization of transformation function. To improve the accuracy and robustness of the registration process, the normalized importance value based on the anatomical information of the coronary arteries is utilized. The experimental results showed fast, robust, and accurate registration using 10 cases, each of the left coronary artery (LCA) and right coronary artery (RCA). Our method can be used as a computer-aided technology for percutaneous coronary intervention (PCI). Our method can be applied to the study of other types of vessels. [ABSTRACT FROM AUTHOR]

• Myosteatosis, excessive fat in muscle, is an emerging distinct disease entity and increases with aging. • Myosteatosis is most widely diagnosed by evaluation of muscle radiodensity on CT. • Heterogeneity in diagnosis of myosteatosis which needs to be standardized. • Negative impact of myosteatosis on survival and complications on various diseases. • Further research is needed regarding molecular mechanism of myosteatosis on mortality. Myosteatosis, which is excessive fat infiltration in the skeletal muscle, is now considered a distinct disease from sarcopenia. Advances in imaging technique have made muscle parameters an evaluable biomarker, and many studies have proved association between myosteatosis and aging or disease process. However, the diagnosis and clinical impact of myosteatosis have not been well established. Thus, we aim to provide a systematic summary with a qualitive review of 73 eligible studies regarding these issues. First, the most widely used modality to diagnose myosteatosis is abdominal computed tomography, based on evaluation of the muscle radiodensity of the total abdominal muscle area predominantly at the L3 vertebral level. However, there was significant heterogeneity in the diagnostic methods and cutoff values used to diagnose myosteatosis (32 different cutoff values among 73 studies). Second, the clinical impact of myosteatosis on prognosis was very straightforward, and most studies have shown a negative impact of myosteatosis on overall survival and complications related to underlying diseases. However, the mechanism of the myosteatosis on mortality has not been explored well, and metabolic dysfunction (i.e. insulin resistance, systemic inflammation) would be a possible explanation. Providing systemic review of current issues can elucidate future directions for developing standardized diagnosis and management of myosteatosis. [ABSTRACT FROM AUTHOR]