Publications

PURPOSE: The purpose of the study is to determine if a combination of dermal thickening and subcutaneous fluid honeycombing on non-contrast MRI, termed the dermal rim sign (DRS), can be diagnostically analogous to dermal backflow seen on lymphoscintigraphy in patients with secondary upper extremity lymphedema.

MATERIALS AND METHODS: Upper extremity MRI and lymphoscintigraphy were performed on patients referred to a multidisciplinary lymphedema clinic for suspicion of secondary lymphedema. Sensitivity, specificity, and positive and negative predictive values of DRS on MRI in detecting dermal backflow on lymphoscintigraphy and the correlation between DRS, Indocyanine Green (ICG) lymphography, bioimpedence L-Dex® ratio and MRI Lymphedema Staging were calculated. Weighted interobserver agreements on the presence and location of DRS on MRI were calculated.

RESULTS: Of the 45 patients in the study, 91.1% (41/45) of patients had history of breast cancer. The average age was 58.4 ± 10.5 years, with a mean symptom duration of 4.7 ± 4.4 years. The mean BMI was 30.5 ± 7.0 kg/m2. Interobserver agreement on the presence and the extent of DRS on MRI was 0.93 [95% confidence-interval: 0.80-1]. DRS was present in 97% (32/33) of patients who demonstrated dermal backflow on lymphoscintigraphy. Sensitivity, specificity, PPV, and NPV of DRS were 96.6% [81.7%-99.9%], and 75.0% [47.6%-92.7%], 87.5% [74.9%-94.3%], and 92.3% [63.1%-98.8%]. DRS was associated with severity on ICG lymphography and bioimpedance (both p < 0.001).

CONCLUSIONS: DRS on non-contrast MRI is highly predictive of dermal backflow and correlates with clinical measures of lymphedema severity. DRS may be used as an independent diagnostic biomarker to identify patients who would benefit from dedicated exams.

Liver lesions have different enhancement patterns at dynamic contrast-enhanced imaging. The Liver Imaging Reporting and Data System (LI-RADS) applies the enhancement kinetic of liver observations in its algorithms for imaging-based diagnosis of hepatocellular carcinoma (HCC) in at-risk populations. Therefore, careful analysis of the spatial and temporal features of these enhancement patterns is necessary to increase the accuracy of liver mass characterization. The authors focus on enhancement patterns that are found at or around the margins of liver observations-many of which are recognized and defined by LI-RADS, such as targetoid appearance, rim arterial phase hyperenhancement, peripheral washout, peripheral discontinuous nodular enhancement, enhancing capsule appearance, nonenhancing capsule appearance, corona enhancement, and periobservational arterioportal shunts-as well as peripheral and periobservational enhancement in the setting of posttreatment changes. Many of these are considered major or ancillary features of HCC, ancillary features of malignancy in general, features of non-HCC malignancy, features associated with benign entities, or features related to treatment response. Distinction between these different patterns of enhancement can help with achieving a more specific diagnosis of HCC and better assessment of response to local-regional therapy. ©RSNA, 2021.

PURPOSE: NonHispanic Black (NHB) and Hispanic/Afro-Caribbean men have the highest risk of prostate cancer (PCa) compared to nonHispanic White (NHW) men. However, ethnicity-specific outcomes of targeted fusion biopsy (FB) for the detection of PCa are poorly characterized. We compared the outcomes of FB by Prostate Imaging Reporting and Data System (PI-RADS®) score and race/ethnicity among a diverse population.

MATERIALS AND METHODS: We evaluated all men who underwent image-guided FB for suspicious lesions on prostate magnetic resonance imaging (≥PI-RADS 3) over a 2-year period. We examined associations of race/ethnicity and PI-RADS score with risk of PCa or clinically significant PCa (cs-PCa, Gleason Group ≥2) on FB using mixed-effects logistic regression models.

RESULTS: A total of 410 men with 658 lesions were analyzed, with 201 (49.0%) identified as NHB and 125 (30.5%) identified as Hispanic. NHB men had a twofold increase in the odds of detecting cs-PCa (OR=2.7, p=0.045), while Hispanic men had similar odds of detecting cs-PCa compared to NHW men. With regard to all PCa, NHB men had a similar increase in the odds of detecting all PCa (OR=2.4, p=0.050), which was borderline statistically significant compared to NHW men on FB. When we excluded men on active surveillance, NHB men had even stronger associations with detection of cs-PCa (OR=3.10, p=0.047) or all PCa (OR=2.77, p=0.032) compared to NHW men.

CONCLUSIONS: NHB men have higher odds for overall PCa and cs-PCa on FB compared to NHW men. Further work may clarify differences per PI-RADS score. Clinicians should interpret prostate magnetic resonance imaging lesions with more caution in NHB men.

The global pandemic of coronavirus disease 2019 (COVID-19) has revealed a surprising number of extra-pulmonary manifestations of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. While myalgia is a common clinical feature of COVID-19, other musculoskeletal manifestations of COVID-19 were infrequently described early during the pandemic. There have been emerging reports, however, of an array of neuromuscular and rheumatologic complications related to COVID-19 infection and disease course including myositis, neuropathy, arthropathy, and soft tissue abnormalities. Multimodality imaging supports diagnosis and evaluation of musculoskeletal disorders in COVID-19 patients. This article aims to provide a first comprehensive summary of musculoskeletal manifestations of COVID-19 with review of imaging.

Interventional radiology continues to evolve into a more robust and clinically dynamic specialty underpinned by significant advancements in training, education, and practice. This article, prepared by members of the 2020-2021 Association of University Radiologists' task force of the Radiology Research Alliance, will review these developments, highlighting the evolution of interventional radiology pathways with attention to growing educational differences, interrelation to diagnostic radiology training, post-training practice patterns, distribution of procedures and future trends, amongst other key features important to those pursuing a career in interventional radiology as well as those in practice.

BACKGROUND: Body composition is associated with mortality; however its routine assessment is too time-consuming.

PURPOSE: To demonstrate the value of artificial intelligence (AI) to extract body composition measures from routine studies, we aimed to develop a fully automated AI approach to measure fat and muscles masses, to validate its clinical discriminatory value, and to provide the code, training data and workflow solutions to facilitate its integration into local practice.

METHODS: We developed a neural network that quantified the tissue components at the L3 vertebral body level using data from the Liver Tumor Challenge (LiTS) and a pancreatic cancer cohort. We classified sarcopenia using accepted skeletal muscle index cut-offs and visceral fat based its median value. We used Kaplan Meier curves and Cox regression analysis to assess the association between these measures and mortality.

RESULTS: Applying the algorithm trained on LiTS data to the local cohort yielded good agreement [>0.8 intraclass correlation (ICC)]; when trained on both datasets, it had excellent agreement (>0.9 ICC). The pancreatic cancer cohort had 136 patients (mean age: 67 ± 11 years; 54% women); 15% had sarcopenia; mean visceral fat was 142 cm2. Concurrent with prior research, we found a significant association between sarcopenia and mortality [mean survival of 15 ± 12 vs. 22 ± 12 (p < 0.05), adjusted HR of 1.58 (95% CI: 1.03-3.33)] but no association between visceral fat and mortality. The detector analysis took 1 ± 0.5 s.

CONCLUSIONS: AI body composition analysis can provide meaningful imaging biomarkers from routine exams demonstrating AI's ability to further enhance the clinical value of radiology reports.

Primary liver cancer is the fourth leading cause of cancer-related deaths worldwide, with hepatocellular carcinoma (HCC) comprising the vast majority of primary liver malignancies. Imaging plays a central role in HCC diagnosis and management. As a result, the content and structure of radiology reports are of utmost importance in guiding clinical management. The Liver Imaging Reporting and Data System (LI-RADS) provides guidance for standardized reporting of liver observations in patients who are at risk for HCC. LI-RADS standardized reporting intends to inform patient treatment and facilitate multidisciplinary communication and decisions, taking into consideration individual clinical factors. Depending on the context, observations may be reported individually, in aggregate, or as a combination of both. LI-RADS provides two templates for reporting liver observations: in a single continuous paragraph or in a structured format with keywords and imaging findings. The authors clarify terminology that is pertinent to reporting, highlight the benefits of structured reports, discuss the applicability of LI-RADS for liver CT and MRI, review the elements of a standardized LI-RADS report, provide guidance on the description of LI-RADS observations exemplified with two case-based reporting templates, illustrate relevant imaging findings and components to be included when reporting specific clinical scenarios, and discuss future directions. An invited commentary by Yano is available online. Online supplemental material is available for this article. Work of the U.S. Government published under an exclusive license with the RSNA.

The Liver Imaging Reporting and Data System (LI-RADS) is a comprehensive system for standardizing the lexicon, technique, interpretation, reporting, and data collection of liver imaging. Developed specifically for assessment of liver observations in patients at risk for hepatocellular carcinoma (HCC), LI-RADS classifies hepatic observations on the basis of the probability of their being HCC, from LR-1 (definitely benign) to LR-5 (definitely HCC). This article discusses the technical requirements, major features, and ancillary features of and a systematic approach for using the LI-RADS diagnostic algorithm, with special emphasis on MR imaging.

Many survivors from severe coronavirus disease 2019 (COVID-19) suffer from persistent dyspnea and fatigue long after resolution of the active infection. In a cohort of 21 consecutive severe post-COVID-19 survivors admitted to an inpatient rehabilitation hospital, 16 (76%) of them had at least one sonographic abnormality of diaphragm muscle structure or function. This corresponded to a significant reduction in diaphragm muscle contractility as represented by thickening ratio (muscle thickness at maximal inspiration/end-expiration) for the post-COVID-19 compared to non-COVID-19 cohorts. These findings may shed new light on neuromuscular respiratory dysfunction as a contributor to prolonged functional impairments after hospitalization for post-COVID-19.