AJR. American Journal of Roentgenology

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Alcohol-associated liver disease (ALD) continues to be a global health concern, responsible for a significant number of deaths worldwide. While most individuals who consume alcohol do not develop ALD, heavy drinkers and binge drinkers are at increased risk. Unfortunately, ALD is often undetected until it reaches advanced stages, frequently associated with portal hypertension and hepatocellular carcinoma (HCC). ALD is now the leading indication for liver transplantation. The incidence of alcohol-associated hepatitis (AH) surged during the COVID-19 pandemic...

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Background: Precise risk stratification through MRI/US fusion-guided targeted biopsy (TBx) can guide optimal prostate cancer (PCa) management. Objective: The purpose of this study was to compare PI-RADS version 2.0 (v2.0) and PI-RADS version 2.1 (v2.1) in terms of the rates of International Society of Urological Pathology (ISUP) grade group (GG) upgrade and down grade from TBx to radical prostatectomy (RP). Methods: This study entailed a retrospective post-hoc analysis of patients who underwent 3-T prostate MRI at a single institution from May 2015 to March 2023 as part of prospective clinical trials...

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard...

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Background: Timely and accurate interpretation of chest radiographs obtained to evaluate endotracheal tube (ETT) position is important for facilitating prompt adjustment if needed. Objective: To evaluate the performance of a deep learning (DL)-based artificial intelligence (AI) system for detecting ETT presence and position on chest radiographs in three patient samples from two different institutions. Methods: This retrospective study included 539 chest radiographs obtained immediately after ETT insertion from January 1, 2020 to March 31, 2020 in 505 patients (293 men, 212 women; mean age, 63 years) from institution A (sample A); 637 chest radiographs obtained from January 1, 2020 to January 3, 2020 in 304 patients (158 men, 147 women; mean age, 63 years) in the ICU (with or without an ETT) from institution A (sample B); and 546 chest radiographs obtained from January 1, 2020 to January 20, 2020 in 83 patients (54 men, 29 women; mean age, 70 years) in the ICU (with or without an ETT) from institution B (sample C)...

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The importance of developing a robust remote workforce in academic radiology has come to the forefront due to several converging factors. COVID-19, and the abrupt transformation it precipitated in terms of how radiologists worked, has been the biggest impetus for change; concurrent factors such as increasing examination volumes and radiologist burnout have also contributed. How to best advance the most desirable and favorable aspects of remote work while preserving an academic environment that fulfills the tripartite mission is a critical challenge that nearly all academic institutions face today...