Faculty Bibliography

Renal oncocytic neoplasms present diagnostic challenges, both at imaging and pathologic evaluation. The World Health Organization classification of renal neoplasms defines a spectrum of oncocytic neoplasms, including emerging entities that help define previously uncharacterized or mischaracterized tumors. Low-grade oncocytic tumors and eosinophilic vacuolated tumors are distinguishable from other oncocytic neoplasms at pathologic evaluation and typically demonstrate indolent behavior. Nomenclature regarding hybrid neoplasms has been clarified in reference to hereditary cases associated with Birt-Hogg-Dubé syndrome. Preoperative diagnostic difficulties at imaging contribute to high rates of resected benign renal tumors, the majority being renal oncocytomas. The imaging appearances of oncocytic neoplasms are similar, and the inability to confidently diagnose them at imaging has led to increased resection rates. Preoperative renal mass biopsy may be preventative, but its utilization remains low, diagnoses can be equivocal, and establishing tumor aggressiveness may not always be reliable. Malignant renal oncocytic tumors, including chromophobe renal cell carcinoma, are generally considered the less aggressive subtypes of renal cell carcinoma. However, distinguishing them from the more aggressive clear cell subtype remains challenging, despite imaging frameworks designed to aid categorization. Active surveillance is a safe management option among biopsy-confirmed renal oncocytic neoplasms, but it remains uncertain which patients are suitable for this approach. Diagnostic imaging may assist in risk-stratifying oncocytic neoplasms, with mass enhancement, heterogeneity, and calcification potentially differentiating benign from malignant oncocytic neoplasms. Mass attenuation and heterogeneity may differentiate low-grade and high-grade cancers. Molecular imaging and other emerging techniques, such as MR fingerprinting, may play a role in the future. ^©RSNA, 2026 Supplemental material is available for this article.

The clinical management of hepatocellular carcinoma (HCC) has evolved significantly over the past decade. Key advances include the introduction of immune-based treatment options, which now serve as the foundation for systemic therapies. Additionally, innovations in surgical techniques, such as robotic surgery, have broadened the scope of resection to include selected patients previously deemed unsuitable due to factors like tumor location or the presence of portal hypertension. HCC downstaging has also gained recognition as a viable strategy in appropriately selected patients, demonstrating outcomes comparable to those achieved under conventional listing criteria. Consequently, the management of HCC has become increasingly complex, underscoring the critical importance of multidisciplinary collaboration and shared decision-making. In this review, we provide a concise overview of practical recommendations for HCC management, encompassing aspects such as risk stratification, early detection, diagnosis, and treatment strategies.

BACKGROUND:Liver Imaging Reporting and Data System M (LR-M) lesions may appear targetoid or nontargetoid, but their clinicopathologic and prognostic differences remain unclear. PURPOSE/OBJECTIVE:To compare clinical, pathological, and prognostic features of targetoid and nontargetoid LR-M lesions on dynamic contrast enhanced-MRI (DCE-MRI). STUDY TYPE/METHODS:Retrospective. SUBJECTS/METHODS:119 consecutive patients (82 male, mean age = 62.9 ± 10.3 years) with 119 LR-M observations (75 targetoid, 44 nontargetoid) and at least 2 years of follow-up. FIELD STRENGTH/SEQUENCE/UNASSIGNED:1.5T and 3.0T; T2-weighted fast spin echo sequence, diffusion-weighted image, and dynamic T1-weighted-gradient-echo sequence using an extracellular contrast agent. ASSESSMENT/RESULTS:Three radiologists categorized lesions as targetoid or nontargetoid. Clinical, laboratory, imaging, and histopathologic data were collected. STATISTICAL TESTS/METHODS:Group differences were evaluated using t-tests and chi-square/Fisher's exact tests. Survival outcomes were assessed using Kaplan-Meier method with log-rank test and Cox proportional hazards regression. Inverse probability of treatment weighting (IPTW) was applied before survival analysis. A p-value < 0.05 was considered significant. RESULTS:The nontargetoid group had significantly higher serum AFP (6684.7 ± 15,988 vs. 194.9 ± 898.4 ng/mL), larger lesion size (9.10 ± 5.55 cm vs. 3.55 ± 2.96 cm), cirrhosis (95% vs. 76%), extrahepatic disease (50% vs. 19%), and malignancy (95% vs. 82%). Nontargetoid group showed significantly higher mortality (75% vs. 41%), progression (77% vs. 45%), shorter overall survival (477 ± 629 vs. 1226 ± 1147 days), and time-to-progression (333 vs. 1003 days). On multivariable analysis with Cox proportional hazards regression, targetoid morphology was significantly associated with improved overall survival (HR = 0.28) and progression-free survival (HR = 0.36), whereas histology was not significant (HCC vs. non-HCC). DATA CONCLUSION/CONCLUSIONS:Targetoid morphology is significantly associated with improved survival and delayed progression, supporting its role as a prognostic imaging biomarker. EVIDENCE LEVEL/METHODS:3. TECHNICAL EFFICACY/UNASSIGNED:Stage 5.

MR imaging of the scrotum is a valuable adjunct to ultrasonography, offering superior soft tissue contrast resolution and multiplanar imaging capabilities for evaluating scrotal abnormalities. While ultrasonography is the first-line imaging modality to evaluate scrotal pathology, MR imaging is particularly useful when sonographic findings are inconclusive. In these instances, MR imaging aids in lesion localization, characterization of extratesticular pathologies, and surgical planning. MR imaging also plays a role in local staging of testicular neoplasms, evaluating undescended testes, and assessing acute scrotal conditions. Emerging applications, including radiomics and diffusion tensor imaging, demonstrate promise in the assessment of select testicular pathologies.

The establishment of the Liver Imaging Reporting and Data System (LI-RADS) in 2011 provided a comprehensive approach to standardized imaging, interpretation, and reporting of liver observations in patients diagnosed with or at risk for hepatocellular carcinoma (HCC). Each set of algorithms provides criteria pertinent to the various components of HCC management including surveillance, diagnosis, staging, and treatment response supported by a detailed lexicon of terms applicable to a wide range of liver imaging scenarios. Before its widespread adoption, the variability in the terminology of diagnostic criteria and definitions of imaging features led to significant challenges in patient management and made it difficult to replicate findings or apply them consistently. The integration of LI-RADS into the clinical setting has enhanced the efficiency and clarity of communication between radiologists, referring providers, and patients by employing a uniform language that averts miscommunications. LI-RADS has been strengthened with its integration into the American Association for Study of Liver Diseases practice guidelines. We will provide the background on the initial development of LI-RADS and reasons for development to serve as a starting point for conveying the system's benefits and evolution over the years. We will also suggest strategies for the implementation and maintenance of a LI-RADS program will be discussed.

ComBat harmonization has been developed to remove non-biological variations for data in multi-center research applying artificial intelligence (AI). We investigated the effectiveness of ComBat harmonization on radiomic and deep features extracted from large, multi-center abdominal MRI data. A retrospective study was conducted on T2-weighted (T2W) abdominal MRI data retrieved from individual patients with suspected or known chronic liver disease at three study sites. MRI data were acquired using systems from three manufacturers and two field strengths. Radiomic features and deep features were extracted using the PyRadiomics pipeline and a Swin Transformer. ComBat was used to harmonize radiomic and deep features across different manufacturers and field strengths. Student's t-test, ANOVA test, and Cohen's F score were applied to assess the difference in individual features before and after ComBat harmonization. Between two field strengths, 76.7%, 52.9%, and 26.7% of radiomic features, and 89.0%, 56.5%, and 0.1% of deep features from three manufacturers were significantly different. Among the three manufacturers, 90.1% and 75.0% of radiomic features and 89.3% and 84.1% of deep features from two field strengths were significantly different. After ComBat harmonization, there were no significant differences in radiomic and deep features among manufacturers or field strengths based on t-tests or ANOVA tests. Reduced Cohen's F scores were consistently observed after ComBat harmonization. ComBat harmonization effectively harmonizes radiomic and deep features by removing the non-biological variations due to system manufacturers and/or field strengths in large multi-center clinical abdominal MRI datasets.

A wide spectrum of benign and malignant primary mesenchymal tumors and tumor-like lesions of the spleen has been recently included under the umbrella term 'stroma-derived' neoplasms and tumor-like lesions. These include dendritic cell neoplasms such as follicular dendritic cell sarcoma, EBV-positive inflammatory follicular dendritic cell sarcoma, and fibroblastic reticular cell tumor; smooth muscle and myofibroblastic lesions such as inflammatory pseudotumor, EBV-associated smooth muscle tumor and undifferentiated pleomorphic sarcoma as well as a diverse spectrum of vascular and vascular-stromal tumors and tumor-like lesions. While some tumor and tumor-like lesions are unique to the spleen, others may also occur in diverse extra-splenic viscera. These tumors and tumor-like lesions demonstrate characteristic histopathology, immunocytochemistry and biological behavior. While cross-sectional imaging studies allow detection, staging and limited characterization of these splenic lesions, histopathological confirmation permits optimal management and surveillance strategies.

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.

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related deaths worldwide. Early detection of HCC is a key factor in enabling curative therapies and improving overall survival. Worldwide, several guidelines are available for surveillance of at-risk populations and diagnosis of HCC. This article provides a current comprehensive update on screening and diagnosis of HCC.

OBJECTIVE:To perform image quality comparison between deep learning-based multiband diffusion-weighted sequence (DL-mb-DWI), accelerated multiband diffusion-weighted sequence (accelerated mb-DWI), and conventional multiband diffusion-weighted sequence (conventional mb-DWI) in patients undergoing clinical liver magnetic resonance imaging (MRI). METHODS:Fifty consecutive patients who underwent clinical MRI of the liver at a 1.5-T scanner, between September 1, 2021, and January 31, 2022, were included in this study. Three radiologists independently reviewed images using a 5-point Likert scale for artifacts and image quality factors, in addition to assessing the presence of liver lesions and lesion conspicuity. RESULTS:DL-mb-DWI acquisition time was 65.0 ± 2.4 seconds, significantly (P < 0.001) shorter than conventional mb-DWI (147.5 ± 19.2 seconds) and accelerated mb-DWI (94.3 ± 1.8 seconds). DL-mb-DWI received significantly higher scores than conventional mb-DWI for conspicuity of the left lobe (P < 0.001), sharpness of intrahepatic vessel margin (P < 0.001), sharpness of the pancreatic contour (P < 0.001), in-plane motion artifact (P = 0.002), and overall image quality (P = 0.005) by reader 2. DL-mb-DWI received significantly higher scores for conspicuity of the left lobe (P = 0.006), sharpness of the pancreatic contour (P = 0.020), and in-plane motion artifact (P = 0.042) by reader 3. DL-mb-DWI received significantly higher scores for strength of fat suppression (P = 0.004) and sharpness of the pancreatic contour (P = 0.038) by reader 1. The remaining quality parameters did not reach statistical significance for reader 1. CONCLUSIONS:Novel diffusion-weighted MRI sequence with deep learning-based image reconstruction demonstrated significantly decreased acquisition times compared with conventional and accelerated mb-DWI sequences, while maintaining or improving image quality for routine abdominal MRI. DL-mb-DWI offers a potential alternative to conventional mb-DWI in routine clinical liver MRI.