Influence of Methods Used to Establish Sarcopenia Cutoff Values for Skeletal Muscle Measures Using Unenhanced and Contrast-Enhanced Computed Tomography Images

2019 ◽  
Vol 43 (8) ◽  
pp. 1028-1036 ◽  
Author(s):  
Zhichao Feng ◽  
Pengfei Rong ◽  
Muqing Luo ◽  
Xianxi Sun ◽  
Wei Wang
Keyword(s):  
Computed Tomography ◽  
Skeletal Muscle ◽  
Computed Tomography Images ◽  
Cutoff Values ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

scholarly journals e-ASPECTS software is non-inferior to neuroradiologists in applying the ASPECT score to computed tomography scans of acute ischemic stroke patients

2016 ◽  
Vol 12 (6) ◽  
pp. 615-622 ◽  
Author(s):  
Simon Nagel ◽  
Devesh Sinha ◽  
Diana Day ◽  
Wolfgang Reith ◽  
René Chapot ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Ischemic Stroke ◽  
Correlation Coefficients ◽  
Ground Truth ◽  
Stroke Patients ◽  
Computed Tomography Images ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Sensitivity Specificity ◽  
Contrast Enhanced Computed Tomography

Background The Alberta Stroke Program Early Computed Tomography Score (ASPECTS) is an established 10-point quantitative topographic computed tomography scan score to assess early ischemic changes. We performed a non-inferiority trial between the e-ASPECTS software and neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute ischemic stroke patients. Methods In this multicenter study, e-ASPECTS and three independent neuroradiologists retrospectively and blindly assessed baseline non-contrast enhanced computed tomography images of 132 patients with acute anterior circulation ischemic stroke. Follow-up scans served as ground truth to determine the definite area of infarction. Sensitivity, specificity, and accuracy for region- and score-based analysis, receiver-operating characteristic curves, Bland-Altman plots and Matthews correlation coefficients relative to the ground truth were calculated and comparisons were made between neuroradiologists and different pre-specified e-ASPECTS operating points. The non-inferiority margin was set to 10% for both sensitivity and specificity on region-based analysis. Results In total 2640 (132 patients × 20 regions per patient) ASPECTS regions were scored. Mean time from onset to baseline computed tomography was 146 ± 124 min and median NIH Stroke Scale (NIHSS) was 11 (6–17, interquartile range). Median ASPECTS for ground truth on follow-up imaging was 8 (6.5–9, interquartile range). In the region-based analysis, two e-ASPECTS operating points (sensitivity, specificity, and accuracy of 44%, 93%, 87% and 44%, 91%, 85%) were statistically non-inferior to all three neuroradiologists (all p-values <0.003). Both Matthews correlation coefficients for e-ASPECTS were higher (0.36 and 0.34) than those of all neuroradiologists (0.32, 0.31, and 0.3). Conclusions e-ASPECTS was non-inferior to three neuroradiologists in scoring ASPECTS on non-contrast enhanced computed tomography images of acute stroke patients.

scholarly journals The ‘step-clipping’ method: a guide for identifying a previously bleeding colonic diverticulum

2020 ◽  
Vol 08 (01) ◽  
pp. E64-E69
Author(s):  
Hirosato Tamari ◽  
Taiki Aoyama ◽  
Kenjiro Shigita ◽  
Naoki Asayama ◽  
Akira Fukumoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Target Lesion ◽  
Diverticular Bleeding ◽  
Computed Tomography Images ◽  
Contrast Enhanced ◽  
Before And After ◽  
Colonic Diverticular Bleeding ◽  
Enhanced Computed Tomography ◽  
Short Time ◽  
Contrast Enhanced Computed Tomography

Abstract Background and study aims Unsatisfactory detectability of a previously bleeding diverticulum by colonoscopy results from difficulty in precisely locating the target lesion, even with presence of an extravasation on contrast-enhanced computed tomography (CECT). This study aimed to evaluate the usefulness of the step-clipping method to overcome this limitation. Patients and methods Step-clipping was indicated for patients with colonic diverticular bleeding and presence of extravasation on CECT, but with absence of active bleeding on subsequent colonoscopy. The target diverticulum was identified by comparing computed tomography images before and after step clipping, which provided a positional relationship between each clip and the target lesion. Results Based on data from 21 consecutive cases meeting our inclusion criteria (14 men and 7 women; mean age, 73.2 years), the target diverticulum was endoscopically identified in 20 cases (95 %), in a median time of 5 minutes, and successfully treated. No adverse events were observed with the step-clipping method. Conclusion Step-clipping provided easy guidance to the target site for treatment in a short time, despite spontaneous cessation of bleeding at the diverticulum.

The left brachiocephalic vein ‘spur’: A cadaveric and contrast computed tomography study

2019 ◽  
Vol 34 (10) ◽  
pp. 690-697
Author(s):  
Hiroki Mitsuoka ◽  
Munekazu Naito ◽  
Yusuke Ohmichi ◽  
Makiyo Hagihara ◽  
Kanae Umemoto ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Superior Vena ◽  
Vena Cava ◽  
Cadaveric Study ◽  
Brachiocephalic Vein ◽  
Left Brachiocephalic Vein ◽  
Computed Tomography Images ◽  
Contrast Enhanced ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography

Objectives This study investigated the presence of the ‘spur’ which separates the lumen in the left brachiocephalic vein (LBV). Method We macroscopically observed the lumen of the bilateral brachiocephalic veins and the superior vena cava in 56 cadavers. The samples were treated with haematoxylin and eosin staining and immunostaining using an α-smooth muscle action antibody. Contrast-enhanced computed tomography images from 170 subjects were analysed. Results The septal structure was found in only 7% of LBVs included in the cadaveric study and 1.2% of LBVs included in the contrast-enhanced computed tomography image analysis. In the cadaveric study, the septal structure was identified as a ‘spur’ using histopathology. In both studies, a non-septal structure was found in the right brachiocephalic vein. Conclusions This is the first report indicating the existence of an LBV ‘spur’.

scholarly journals Distinguishing cardiac myxomas from cardiac thrombi by a radiomics signature based on cardiovascular contrast-enhanced computed tomography images

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Wen-lei Qian ◽  
Yu Jiang ◽  
Xi Liu ◽  
Ying-kun Guo ◽  
Yuan Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
High Morbidity ◽  
Clinical Model ◽  
Naked Eye ◽  
Computed Tomography Images ◽  
Contrast Enhanced ◽  
Cardiac Myxomas ◽  
Enhanced Computed Tomography ◽  
Contrast Enhanced Computed Tomography ◽  
Radiomics Signature

Abstract Background Cardiac myxomas (CMs) and thrombi are associated with high morbidity and mortality. These two conditions need totally different treatments. However, they are difficult to distinguish using naked eye. In clinical, misdiagnoses occur now and then. This study aimed to compare the characteristics of CMs and cardiac thrombi and investigate the value of a radiomics signature in distinguishing CMs from cardiac thrombi, based on cardiovascular contrast-enhanced computed tomography (CECT) images. Methods A total of 109 patients who had CMs (n = 59) and cardiac thrombi (n = 50) were enrolled in this retrospective study from 2009 to 2019. First, the lesion characteristics of cardiovascular CECT images were documented and compared by two radiologists. Then all patients were randomly allotted to either a primary group or a validation group according to a 7:3 ratio. Univariate analysis and the least absolute shrinkage and selection operator were used to select robust features. The best radiomics signature was constructed and validated using multivariate logistic regression. An independent clinical model was created for comparison. Results The best radiomics signature was developed using eight selected radiomics. The classification accuracies of the radiomics signature were 90.8% and 90.9%, and the area under the receiver operating characteristic curves were 0.969 and 0.926 in the training and testing cohorts, respectively. Cardiovascular CECT images showed that the two diseases had significant differences in location, surface, Hydrothorax, pericardial effusion and heart enlargement. The naked eye findings were used to create the clinical model. All metrics of the radiomics signature were higher than those of clinical model. Conclusions Compared with clinical model, the radiomics signature based on cardiovascular CECT performed better in differentiating CMs and thrombi, suggesting that it could help improving the diagnostic efficiency.

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