Academic radiology
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To generate institutional size-specific diagnostic reference levels (DRLs) for computed tomography angiography (CTA) examinations and assess the potential for dose optimization compared to size-independent DRLs. ⋯ We implemented institutional size-specific DRLs for CTA examinations which enabled a more precise analysis compared to national sizeindependent DRLs.
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Delayed-phase acquisition of the computed tomography (CT) angiography is important for the evaluation of type II endoleaks after endovascular aortic aneurysm repair because the endoleak cavity area is associated with aneurysm sac expansion. Contrast enhancement boost (CE-boost) is a postprocessing technique for increasing the degree of contrast enhancement on contrast-enhanced CT. We aimed to investigate the usefulness of the CE-boost technique for the visualization of type II endoleaks. ⋯ The CE-boost technique facilitates clear visualization of type II endoleak cavities.
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We aimed to estimate the self-reported prevalence of burnout in chairs of academic radiology departments in the United States and identify factors associated with high burnout in chairs. ⋯ A significant proportion of chairs of academic radiology departments are experiencing 1 or more symptoms of burnout. Efforts to address burnout in radiology chairs should be initiated promptly at the national, institutional, and departmental levels.
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Glioblastoma multiforme (GBM) is the most common and deadly type of primary malignant tumor of the central nervous system. Accurate risk stratification is vital for a more personalized approach in GBM management. The purpose of this study is to develop and validate a MRI-based prognostic quantitative radiomics classifier in patients with newly diagnosed GBM and to evaluate whether the classifier allows stratification with improved accuracy over the clinical and qualitative imaging features risk models. ⋯ A classifier using radiomics features allows preoperative prediction of survival and risk stratification of patients with GBM, and it shows improved performance compared to that of clinical and qualitative imaging features models.
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The purpose of this study is to develop a radiomics model for predicting the histopathological grades of soft tissue sarcomas preoperatively through magnetic resonance imaging (MRI). ⋯ Good accuracy and AUC could be obtained using only five radiomic features. Therefore, we proposed that three-dimensional imaging features from fat-suppressed T2-weighted imaging could be used as candidate biomarkers for preoperative prediction of histopathological grades of soft tissue sarcomas noninvasively.