Interpretation, Reporting, and Clinical Applications of Liver MR Elastography.

Chronic liver disease is highly prevalent and often leads to fibrosis or cirrhosis and complications such as liver failure and hepatocellular carcinoma. The diagnosis and staging of liver fibrosis is crucial to determine management and mitigate complications. Liver biopsy for histologic assessment has limitations such as sampling bias and high interreader variability that reduce precision, which is particularly challenging in longitudinal monitoring. MR elastography (MRE) is considered the most accurate noninvasive technique for diagnosing and staging liver fibrosis. In MRE, low-frequency vibrations are applied to the abdomen, and the propagation of shear waves through the liver is analyzed to measure liver stiffness, a biomarker for the detection and staging of liver fibrosis. As MRE has become more widely used in clinical care and research, different contexts of use have emerged. This review focuses on the latest developments in the use of MRE for the assessment of liver fibrosis; provides guidance for image acquisition and interpretation; summarizes diagnostic performance, along with thresholds for diagnosis and staging of liver fibrosis; discusses current and emerging clinical applications; and describes the latest technical developments.

Natural language processing pipeline to extract prostate cancer-related information from clinical notes.

OBJECTIVES: To develop an automated pipeline for extracting prostate cancer-related information from clinical notes. MATERIALS AND METHODS: This retrospective study included 23,225 patients who underwent prostate MRI between 2017 and 2022. Cancer risk factors (family history of cancer and digital rectal exam findings), pre-MRI prostate pathology, and treatment history of prostate cancer were extracted from free-text clinical notes in English as binary or multi-class classification tasks. Any sentence containing pre-defined keywords was extracted from clinical notes within one year before the MRI. After manually creating sentence-level datasets with ground truth, Bidirectional Encoder Representations from Transformers (BERT)-based sentence-level models were fine-tuned using the extracted sentence as input and the category as output. The patient-level output was determined by compilation of multiple sentence-level outputs using tree-based models. Sentence-level classification performance was evaluated using the area under the receiver operating characteristic curve (AUC) on 15% of the sentence-level dataset (sentence-level test set). The patient-level classification performance was evaluated on the patient-level test set created by radiologists by reviewing the clinical notes of 603 patients. Accuracy and sensitivity were compared between the pipeline and radiologists. RESULTS: Sentence-level AUCs were ≥ 0.94. The pipeline showed higher patient-level sensitivity for extracting cancer risk factors (e.g., family history of prostate cancer, 96.5% vs. 77.9%, p < 0.001), but lower accuracy in classifying pre-MRI prostate pathology (92.5% vs. 95.9%, p = 0.002) and treatment history of prostate cancer (95.5% vs. 97.7%, p = 0.03) than radiologists, respectively. CONCLUSION: The proposed pipeline showed promising performance, especially for extracting cancer risk factors from patient's clinical notes. CLINICAL RELEVANCE STATEMENT: The natural language processing pipeline showed a higher sensitivity for extracting prostate cancer risk factors than radiologists and may help efficiently gather relevant text information when interpreting prostate MRI. KEY POINTS: When interpreting prostate MRI, it is necessary to extract prostate cancer-related information from clinical notes. This pipeline extracted the presence of prostate cancer risk factors with higher sensitivity than radiologists. Natural language processing may help radiologists efficiently gather relevant prostate cancer-related text information.

Performance of CT With Adrenal-Washout Protocol in Heterogeneous Adrenal Nodules: A Multiinstitutional Study.

BACKGROUND. CT with adrenal-washout protocol (hereafter, adrenal-protocol CT) is commonly performed to distinguish adrenal adenomas from other adrenal tumors. However, the technique's utility among heterogeneous nodules is not well established, and the optimal method for placing ROIs in heterogeneous nodules is not clearly defined. OBJECTIVE. The purpose of our study was to determine the diagnostic performance of adrenal-protocol CT to distinguish adenomas from nonadenomas among heterogeneous adrenal nodules and to compare this performance among different methods for ROI placement. METHODS. This retrospective study included 164 patients (mean age, 59.1 years; 61 men, 103 women) with a total of 164 heterogeneous adrenal nodules evaluated using adrenal-protocol CT at seven institutions. All nodules had an available pathologic reference standard. A single investigator at each institution evaluated the CT images. ROIs were placed on portal venous phase images using four ROI methods: standard ROI, which refers to a single large ROI in the nodule's center; high ROI, a single ROI on the nodule's highest-attenuation area; low ROI, a single ROI the on nodule's lowest-attenuation area; and average ROI, the mean of the three ROIs on the nodule's superior, middle, and inferior thirds using the approach for the standard ROI. ROIs were then placed in identical locations on unenhanced and delayed phase images. Absolute washout was determined for all methods. RESULTS. The nodules comprised 82 adenomas and 82 nonadenomas (36 pheochromocytomas, 20 metastases, 12 adrenocortical carcinomas, and 14 nodules with other pathologies). The mean nodule size was 4.5 ± 2.8 (SD) cm (range, 1.6-23.0 cm). Unenhanced CT attenuation of 10 HU or less exhibited sensitivity and specificity for adenoma of 22.0% and 96.3% for standard-ROI, 11.0% and 98.8% for high-ROI, 58.5% and 84.1% for low-ROI, and 30.5% and 97.6% for average-ROI methods. Adrenal-protocol CT overall (unenhanced attenuation ≤ 10 HU or absolute washout of ≥ 60%) exhibited sensitivity and specificity for adenoma of 57.3% and 84.1% for the standard-ROI method, 63.4% and 51.2% for the high-ROI method, 68.3% and 62.2% for the low-ROI method, and 59.8% and 85.4% for the average-ROI method. CONCLUSION. Adrenal-protocol CT has poor diagnostic performance for distinguishing adenomas from nonadenomas among heterogeneous adrenal nodules regardless of the method used for ROI placement. CLINICAL IMPACT. Adrenal-protocol CT has limited utility in the evaluation of heterogeneous adrenal nodules.

Multimodality Imaging in Metabolic Syndrome: State-of-the-Art Review.

Metabolic syndrome comprises a set of risk factors that include abdominal obesity, impaired glucose tolerance, hypertriglyceridemia, low high-density lipoprotein levels, and high blood pressure, at least three of which must be fulfilled for diagnosis. Metabolic syndrome has been linked to an increased risk of cardiovascular disease and type 2 diabetes mellitus. Multimodality imaging plays an important role in metabolic syndrome, including diagnosis, risk stratification, and assessment of complications. CT and MRI are the primary tools for quantification of excess fat, including subcutaneous and visceral adipose tissue, as well as fat around organs, which are associated with increased cardiovascular risk. PET has been shown to detect signs of insulin resistance and may detect ectopic sites of brown fat. Cardiovascular disease is an important complication of metabolic syndrome, resulting in subclinical or symptomatic coronary artery disease, alterations in cardiac structure and function with potential progression to heart failure, and systemic vascular disease. CT angiography provides comprehensive evaluation of the coronary and systemic arteries, while cardiac MRI assesses cardiac structure, function, myocardial ischemia, and infarction. Liver damage results from a spectrum of nonalcoholic fatty liver disease ranging from steatosis to fibrosis and possible cirrhosis. US, CT, and MRI are useful in assessing steatosis and can be performed to detect and grade hepatic fibrosis, particularly using elastography techniques. Metabolic syndrome also has deleterious effects on the pancreas, kidney, gastrointestinal tract, and ovaries, including increased risk for several malignancies. Metabolic syndrome is associated with cerebral infarcts, best evaluated with MRI, and has been linked with cognitive decline. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material. See the invited commentary by Pickhardt in this issue.

Hepatic Sinusoidal Disorders.

Hepatic sinusoids are highly specialized microcirculatory conduits within the hepatic lobules that facilitate liver functions. The sinusoids can be affected by various disorders, including sinusoidal dilatation, sinusoidal obstruction syndrome (SOS), sinusoidal cellular infiltration, perisinusoidal infiltration, and endothelial neoplasms, such as hemangioendothelioma and angiosarcoma. While these disorders, particularly SOS and neoplasms, can be life threatening, their clinical manifestation is often nonspecific. Patients may present with right upper quadrant pain, jaundice, hepatomegaly, ascites, splenomegaly, and unexplained weight gain, although the exact manifestation depends on the cause, severity, and duration of the disease. Ultimately, invasive tests may be necessary to establish the diagnosis. A comprehensive understanding of imaging manifestations of various sinusoidal disorders contributes to early diagnosis and can help radiologists detect subclinical disease. Additionally, specific imaging features may assist in identifying the cause of the disorder, leading to a more focused and quicker workup. For example, a mosaic pattern of enhancement of the liver parenchyma is suggestive of sinusoidal dilatation; peripheral and patchy reticular hypointensity of the liver parenchyma on hepatobiliary MR images is characteristic of SOS; and associated diffuse multiple hyperintensities on diffusion-weighted images may be specific for malignant sinusoidal cellular infiltration. The authors provide an overview of the pathogenesis, clinical features, and imaging appearances of various hepatic sinusoidal disorders, with a special emphasis on SOS. ©RSNA, 2024 Supplemental material is available for this article.

Deciphering ovarian torsion: insights from CT imaging analysis.

PURPOSE: In the milieu of emergency medicine, pelvic and lower abdominal pain present recurrently, with ovarian torsion posing a formidable diagnostic quandary amid multifarious etiologies. Given the burgeoning reliance on CT in acute care settings, it invariably assumes primacy as the principal imaging modality. This study endeavors to elucidate the CT imaging manifestations encountered by surgically confirmed ovarian torsion patients and utilizing CT to differentiate necrosis. METHODS: A retrospective analysis (January, 2015- April, 2019) utilizing hospital archives was conducted on patients diagnosed with ovarian torsion, post-surgery. Inclusion criteria encompassed patients who underwent CT examinations within one week of diagnosis. A large array of CT findings encompassing midline orientation, uterine deviation, intraovarian hematoma/mass, and multiple others were systematically documented. RESULTS: 90 patients were diagnosed with ovarian torsion- 53 (59%) had CT within one week of diagnosis, 41(77%) underwent a CT with IV contrast and 12 (23%) without IV contrast. Mean age was 43 years (range 19-77 years), with near equal distribution of involvement of each ovary. Mean maximum ovarian diameter was 11.7 ± 6.3 cm (4.2-34.8 cm). Most common imaging features include the presence of thickened pedicle (43/53, 81%), midline ovary (41/53, 77%), presence of thickened fallopian tube (31/49, 63%), and ipsilateral uterine deviation (33/53, 62%). Based on contemporaneous imaging report, torsion was diagnosed in 25/ 53 studies giving a sensitivity of 47%. CONCLUSION: Enlarged ovarian dimensions (> 3.0 cm), thickened vascular pedicle or fallopian tube, midline ovarian disposition with ipsilateral uterine deviation, and the presence of a whirlpool sign emerged as predominant CT imaging features in surgically confirmed ovarian torsion cases, serving as pivotal diagnostic aides for radiologists. Concomitant pelvic free fluid and intraovarian hematoma signify necrotic changes, indicative of ischemic severity and disease progression.