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Respiratory motion‐induced image blurring and artifacts can compromise image quality in dynamic contrast‐enhanced MRI (DCE‐MRI) of the liver. Despite remarkable advances in respiratory motion detection and compensation in past years, these techniques have not yet seen widespread clinical adoption. The accuracy of image‐based motion detection can be especially compromised in the presence of contrast enhancement and/or in situations involving deep and/or irregular breathing patterns. This work proposes a framework that combines GRASP‐Pro (Golden‐angle RAdial Sparse Parallel MRI with imProved performance) MRI with a new radial sampling scheme called navi‐stack‐of‐stars for free‐breathing DCE‐MRI of the liver without the need for explicit respiratory motion compensation. A prototype 3D golden‐angle radial sequence with a navi‐stack‐of‐stars sampling scheme that intermittently acquires a 2D navigator was implemented. Free‐breathing DCE‐MRI of the liver was conducted in 24 subjects at 3T including 17 volunteers and 7 patients. GRASP‐Pro reconstruction was performed with a temporal resolution of 0.34–0.45 s per volume, whereas standard GRASP reconstruction was performed with a temporal resolution of 15 s per volume. Motion compensation was not performed in all image reconstruction tasks. Liver images in different contrast phases from both GRASP and GRASP‐Pro reconstructions were visually scored by two experienced abdominal radiologists for comparison. The nonparametric paired two‐tailed Wilcoxon signed‐rank test was used to compare image quality scores, and the Cohen's kappa coefficient was calculated to evaluate the inter‐reader agreement. GRASP‐Pro MRI with sub‐second temporal resolution consistently received significantly higher image quality scores (P < 0.05) than standard GRASP MRI throughout all contrast enhancement phases and across all assessment categories. There was a substantial inter‐reader agreement for all assessment categories (ranging from 0.67 to 0.89). The proposed technique using GRASP‐Pro reconstruction with navi‐stack‐of‐stars sampling holds great promise for free‐breathing DCE‐MRI of the liver without respiratory motion compensation. [ABSTRACT FROM AUTHOR]

This work proposes MP‐Grasp4D (magnetization‐prepared golden‐angle radial sparse parallel 4D) MRI, a free‐breathing, inversion recovery (IR)‐prepared, time‐resolved 4D MRI technique with improved T1‐weighted contrast. MP‐Grasp4D MRI acquisition incorporates IR preparation into a radial gradient echo sequence. MP‐Grasp4D employs a golden‐angle navi‐stack‐of‐stars sampling scheme, where imaging data of rotating radial stacks and navigator stacks (acquired at a consistent rotation angle) are alternately acquired. The navigator stacks are used to estimate a temporal basis for low‐rank subspace‐constrained reconstruction. This allows for the simultaneous capture of both IR‐induced contrast changes and respiratory motion. One temporal frame of the imaging volume in MP‐Grasp4D MRI is reconstructed from a single stack and an adjacent navigator stack on average, resulting in a nominal temporal resolution of 0.16 seconds per volume. Images corresponding to the optimal inversion time (TI) can be retrospectively selected for providing the best image contrast. Reader studies were conducted to assess the performance of MP‐Grasp4D MRI in liver imaging across 30 subjects in comparison with standard Grasp4D MRI without IR preparation. MP‐Grasp4D MRI received significantly higher scores (P < 0.05) than Grasp4D in all assessment categories. There was a moderate to almost perfect agreement (kappa coefficient from 0.42 to 0.9) between the two readers for image quality assessment. When the scan time is reduced, MP‐Grasp4D MRI preserves image contrast and quality, demonstrating additional acceleration capability. MP‐Grasp4D MRI improves T1‐weighted contrast for free‐breathing time‐resolved 4D MRI and eliminates the need for explicit motion compensation. This method is expected to be valuable in different MRI applications such as MR‐guided radiotherapy. [ABSTRACT FROM AUTHOR]

The Liver Imaging and Reporting Data System (LI-RADS) is a comprehensive system for standardizing the terminology, technique, interpretation, reporting, and data collection of liver imaging with the overarching goal of improving communication, clinical care, education, and research relating to patients at risk for or diagnosed with hepatocellular carcinoma (HCC). In 2018, the American Association for the Study of Liver Diseases (AASLD) integrated LI-RADS into its clinical practice guidance for the imaging-based diagnosis of HCC. The harmonization between the AASLD and LI-RADS diagnostic imaging criteria required minor modifications to the recently released LI-RADS v2017 guidelines, necessitating a LI-RADS v2018 update. This article provides an overview of the key changes included in LI-RADS v2018 as well as a look at the LI-RADS v2018 diagnostic algorithm and criteria, technical recommendations, and management suggestions. Substantive changes in LI-RADS v2018 are the removal of the requirement for visibility on antecedent surveillance ultrasound for LI-RADS 5 (LR-5) categorization of 10-19 mm observations with nonrim arterial phase hyper-enhancement and nonperipheral "washout", and adoption of the Organ Procurement and Transplantation Network definition of threshold growth (≥ 50% size increase of a mass in ≤ 6 months). Nomenclatural changes in LI-RADS v2018 are the removal of -us and -g as LR-5 qualifiers.

Diversity, equity, inclusion, and representation in various sectors have garnered increasing attention in the past two decades, including healthcare. In this report we investigate representation of females and underrepresented minorities (URM) in the field of radiology and asses for significant growth trends in representation in residency training programs in the United States. De-identified trainee demographic information for active radiology trainees from 2016 to 2021 was queried using the Accreditation Council for Graduate Medical Education (ACGME), and new radiology trainees using the National Resident Matching Program (NRMP)'s Main Residency Match Data and Reports databooks. In 2021 females represented 26.7% of DR residency trainees and 22% of IR integrated trainees. In the same year URM trainees represented 11.3% of trainees and 8.7% of IR integrated trainees. From 2017 to 2021, diagnostic radiology had a compound average growth rate (CAGR) 1% (p <0.01) of female representation and 1.12% (p<0.01) of URM representation. This study quantifies female and underrepresented minority representation among radiology trainees for diagnostic radiology and radiology subspecialities, identifying modest uptrends in representation within both demographics. [ABSTRACT FROM AUTHOR]