Congestive Hepatopathy: Pathophysiology, Workup, and Imaging Findings with Pathologic Correlation.

Liver congestion is increasingly encountered in clinical practice and presents diagnostic pitfalls of which radiologists must be aware. The complex altered hemodynamics associated with liver congestion leads to diffuse parenchymal changes and the development of benign and malignant nodules. Distinguishing commonly encountered benign hypervascular lesions, such as focal nodular hyperplasia (FNH)-like nodules, from hepatocellular carcinoma (HCC) can be challenging due to overlapping imaging features. FNH-like lesions enhance during the hepatic arterial phase and remain isoenhancing relative to the background liver parenchyma but infrequently appear to wash out at delayed phase imaging, similar to what might be seen with HCC. Heterogeneity, presence of an enhancing capsule, washout during the portal venous phase, intermediate signal intensity at T2-weighted imaging, restricted diffusion, and lack of uptake at hepatobiliary phase imaging point toward the diagnosis of HCC, although these features are not sensitive individually. It is important to emphasize that the Liver Imaging Reporting and Data System (LI-RADS) algorithm cannot be applied in congested livers since major LI-RADS features lack specificity in distinguishing HCC from benign hypervascular lesions in this population. Also, the morphologic changes and increased liver stiffness caused by congestion make the imaging diagnosis of cirrhosis difficult. The authors discuss the complex liver macro- and microhemodynamics underlying liver congestion; propose a more inclusive approach to and conceptualization of liver congestion; describe the pathophysiology of liver congestion, hepatocellular injury, and the development of benign and malignant nodules; review the imaging findings and mimics of liver congestion and hypervascular lesions; and present a diagnostic algorithm for approaching hypervascular liver lesions. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Artificial Intelligence in Radiology: Opportunities and Challenges.

Artificial intelligence's (AI) emergence in radiology elicits both excitement and uncertainty. AI holds promise for improving radiology with regards to clinical practice, education, and research opportunities. Yet, AI systems are trained on select datasets that can contain bias and inaccuracies. Radiologists must understand these limitations and engage with AI developers at every step of the process - from algorithm initiation and design to development and implementation - to maximize benefit and minimize harm that can be enabled by this technology.

Gynecologic oncology tumor board: the central role of the radiologist.

This manuscript is a collaborative, multi-institutional effort by members of the Society of Abdominal Radiology Uterine and Ovarian Cancer Disease Focus Panel and the European Society of Urogenital Radiology Women Pelvic Imaging working group. The manuscript reviews the key role radiologists play at tumor board and highlights key imaging findings that guide management decisions in patients with the most common gynecologic malignancies including ovarian cancer, cervical cancer, and endometrial cancer.

Clinical and ultrasound features of dermoid-associated adnexal torsion.

PURPOSE: To determine the clinical and ultrasound features of dermoid-associated adnexal torsion. METHODS: Forty-four patients with at least one dermoid and ultrasound ≤ 30 days of surgery were retrospectively reviewed by three radiologists. Ultrasound and clinical findings were compared to intra-operative findings using Fisher's exact test or Mann-Whitney test with p < 0.05 to determine statistical significance.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Correct. No edit RESULTS: Twenty patients had torsion, while 24 patients did not. Patients with dermoid-associated torsion were more likely to present to emergency department (ED) (100% vs 13%; p < 0.001) and have acute unilateral pelvic pain (100% vs 42%; p < 0.001). On ultrasound, patients with torsion had larger dermoids (median largest dimension 9.0 cm (IQR 7.7-11.1) vs 6.0 cm (IQR 4.4-7.5); p < 0.001), displaced dermoid anterior or superior to the uterus (59% vs 21%; p = 0.016), and ipsilateral adnexal fluid (41% vs 4%; p = 0.003). Displaced dermoid and ipsilateral adnexal fluid had substantial (kappa = 0.72) and moderate inter-rater agreement (kappa = 0.49), respectively. The combination of ED presentation and each statistically significant ultrasound feature (dermoid size ≥ 5.0 cm, displaced dermoid, and ipsilateral adnexal fluid) yielded high specificity and positive predictive value (ranging from 93-100% to 92-100%, respectively). The combination of ED presentation and dermoid size ≥ 5.0 cm yielded the highest sensitivity, negative predicative value, and accuracy (100%, 100%, and 96%, respectively).Please check and confirm whether the edit made to the article title is in order.Looks great. No edits. Thank you! CONCLUSION: Although the diagnosis of adnexal torsion in the presence of an ovarian dermoid is traditionally challenging, the combination of ED presentation and ultrasound features increase diagnostic confidence of dermoid-associated adnexal torsion.

Automated Identification and Measurement Extraction of Pancreatic Cystic Lesions from Free-Text Radiology Reports Using Natural Language Processing.

Purpose: To automatically identify a cohort of patients with pancreatic cystic lesions (PCLs) and extract PCL measurements from historical CT and MRI reports using natural language processing (NLP) and a question answering system. Materials and Methods: Institutional review board approval was obtained for this retrospective Health Insurance Portability and Accountability Act-compliant study, and the requirement to obtain informed consent was waived. A cohort of free-text CT and MRI reports generated between January 1991 and July 2019 that covered the pancreatic region were identified. A PCL identification model was developed by modifying a rule-based information extraction model; measurement extraction was performed using a state-of-the-art question answering system. The system's performance was evaluated against radiologists' annotations. Results: For this study, 430 426 free-text radiology reports from 199 783 unique patients were identified. The NLP model for identifying PCL was applied to 1000 test samples. The interobserver agreement between the model and two radiologists was almost perfect (Fleiss κ = 0.951), and the false-positive rate and true-positive rate were 3.0% and 98.2%, respectively, against consensus of radiologists' annotations as ground truths. The overall accuracy and Lin concordance correlation coefficient for measurement extraction were 0.958 and 0.874, respectively, against radiologists' annotations as ground truths. Conclusion: An NLP-based system was developed that identifies patients with PCLs and extracts measurements from a large single-institution archive of free-text radiology reports. This approach may prove valuable to study the natural history and potential risks of PCLs and can be applied to many other use cases.Keywords: Informatics, Abdomen/GI, Pancreas, Cysts, Computer Applications-General (Informatics), Named Entity Recognition Supplemental material is available for this article. © RSNA, 2022See also commentary by Horii in this issue.

Effect of Right-Sided Versus Left-Sided Contrast Injection on Intra-arterial Opacification Characteristics of Head and Neck Computed Tomography Angiograms and Interactions With Patient Sex, Weight, and Cardiac Output.

OBJECTIVE: The aims of this study were to support the standard clinical assumption that preferential right-sided injection (RSI) over left-sided injection (LSI) results in improved head and neck computed tomography angiograms and to determine which patients most benefit from RSIs. METHODS: Head and neck computed tomography angiograms of 453 RSIs and 419 LSIs were included. Interactions between injection side, age, weight, body mass index, and left ventricular ejection fraction with mean vessel Hounsfield units (HU) were compared. Statistical analysis was performed using 2-tailed Student t tests, Mann-Whitney U tests, and simple linear (SL) and multiple linear regressions. RESULTS: Right-sided injection yielded higher HU for patients older than 40 years (eg, RSI of the right common carotid artery [RCCA] vs LSI of the RCCA; P < 0.01). Body mass index (eg, RCCA; r = -0.31, P < 0.01 [SL]) and weight (eg, RCCA; r = -0.39, P < 0.01 [SL]) were negatively correlated with HU. Female had higher HU (mean ± SE, +39.7 ± 7.6 HU; P < 0.01 [multiple linear]). Left ventricular ejection fraction had no interactions with injection side or HU. CONCLUSIONS: The findings support preferential RSI in patients older than 40 years with higher body mass index and weight, particularly male.