Journal of computer assisted tomography
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J Comput Assist Tomogr · Mar 2021
ReviewCross-sectional Imaging Manifestations of Extrapulmonary Involvement in COVID-19 Disease.
Coronavirus disease 2019 (COVID-19) disease has spread worldwide since it was first discovered in China's Hubei province in December 2019. Respiratory illness is the primary manifestation of COVID-19 disease, and its pathophysiology as well as the clinical and cross-sectional imaging manifestations has been adequately reported. ⋯ There is still limited understanding with regard to the extrapulmonary involvement in this disease. This review aims to put together the prevalence, proposed pathophysiology, and the spectrum of clinical and cross-sectional imaging manifestations of associated extrapulmonary findings in COVID-19 disease.
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J Comput Assist Tomogr · Mar 2021
Use of a Dual Artificial Intelligence Platform to Detect Unreported Lung Nodules.
To investigate the performance of Dual-AI Deep Learning Platform in detecting unreported pulmonary nodules that are 6 mm or greater, comprising computer-vision (CV) algorithm to detect pulmonary nodules, with positive results filtered by natural language processing (NLP) analysis of the dictated report. ⋯ Dual-AI platform detected actionable unreported nodules in 2.8% of chest CT scans, yet minimized intrusion to radiologist's workflow by avoiding alerts for most already-reported nodules.
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J Comput Assist Tomogr · Jan 2021
Comparative StudyComparison of Radiomics Analyses Based on Different Magnetic Resonance Imaging Sequences in Grading and Molecular Genomic Typing of Glioma.
To investigate the value of radiomics analyses based on different magnetic resonance (MR) sequences in the noninvasive evaluation of glioma characteristics for the differentiation of low-grade glioma versus high-grade glioma, isocitrate dehydrogenase (IDH)1 mutation versus IDH1 wild-type, and mutation status and 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation (+) versus MGMT promoter methylation (-) glioma. ⋯ The results demonstrate that state-of-the-art radiomics analysis methods based on multiparametric MR image data and radiomics features can significantly contribute to pretreatment glioma grading and molecular subtype classification.
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J Comput Assist Tomogr · Jan 2021
Uterine Cervical Carcinoma: Evaluation Using Non-Gaussian Diffusion Kurtosis Imaging and Its Correlation With Histopathological Findings.
The aim of the study was to assess non-Gaussian diffusion kurtosis imaging (DKI)'s usefulness as a noninvasive method to evaluate tumor invasion depth, histological grade, and lymph node metastasis in cervical carcinoma (CC) patients. ⋯ Non-Gaussian DKI may be clinically useful for noninvasive evaluation of tumor invasion depth, histological grade, and lymph node metastasis in CC patients.
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J Comput Assist Tomogr · Nov 2020
Comparative StudyCollateral Status in Ischemic Stroke: A Comparison of Computed Tomography Angiography, Computed Tomography Perfusion, and Digital Subtraction Angiography.
To compare assessment of collaterals by single-phase computed tomography (CT) angiography (CTA) and CT perfusion-derived 3-phase CTA, multiphase CTA and temporal maximum-intensity projection (tMIP) images to digital subtraction angiography (DSA), and relate collateral assessments to clinical outcome in patients with acute ischemic stroke. ⋯ Concordance between assessments on CT and DSA was poor. Collateral status evaluated on 3-phase CTA and multiphase CTA, but not on DSA, was associated with clinical outcome.