Biliary Duct Dilatation: AJR Expert Panel Narrative Review.

Biliary duct dilatation is a common incidental finding in practice, but it is unlikely to indicate biliary obstruction in the absence of clinical symptoms or elevated levels on liver function tests (LFTs). However, the clinical presentation may be nonspecific, and LFTs may either be unavailable or difficult to interpret. The goal of this AJR Expert Panel Narrative Review is to highlight a series of topics fundamental to the management of biliary duct dilatation, providing consensus recommendations in a question-and-answer format. We start by covering a basic approach to interpreting LFT results, the strengths and weaknesses of the biliary imaging modalities, and how and where to measure the extrahepatic bile duct. Next, we define the criteria for biliary duct dilatation, including patients with prior cholecystectomy and advanced age, and discuss when and whether biliary duct dilatation can be attributed to papillary stenosis or sphincter of Oddi dysfunction. Subsequently, we discuss two conditions in which the duct is pathologically dilated but not obstructed: congenital cystic dilatation (i.e., choledochal cyst) and intraductal papillary neoplasm of the bile duct. Finally, we provide guidance regarding when to recommend obtaining additional imaging or testing, such as endoscopic ultrasound or ERCP, and include a discussion of future directions in biliary imaging.

Individual Participant Data Meta-Analysis of LR-5 in LI-RADS Version 2018 versus Revised LI-RADS for Hepatocellular Carcinoma Diagnosis.

Background A simplification of the Liver Imaging Reporting and Data System (LI-RADS) version 2018 (v2018), revised LI-RADS (rLI-RADS), has been proposed for imaging-based diagnosis of hepatocellular carcinoma (HCC). Single-site data suggest that rLI-RADS category 5 (rLR-5) improves sensitivity while maintaining positive predictive value (PPV) of the LI-RADS v2018 category 5 (LR-5), which indicates definite HCC. Purpose To compare the diagnostic performance of LI-RADS v2018 and rLI-RADS in a multicenter data set of patients at risk for HCC by performing an individual patient data meta-analysis. Materials and Methods Multiple databases were searched for studies published from January 2014 to January 2022 that evaluated the diagnostic performance of any version of LI-RADS at CT or MRI for diagnosing HCC. An individual patient data meta-analysis method was applied to observations from the identified studies. Quality Assessment of Diagnostic Accuracy Studies version 2 was applied to determine study risk of bias. Observations were categorized according to major features and either LI-RADS v2018 or rLI-RADS assignments. Diagnostic accuracies of category 5 for each system were calculated using generalized linear mixed models and compared using the likelihood ratio test for sensitivity and the Wald test for PPV. Results Twenty-four studies, including 3840 patients and 4727 observations, were analyzed. The median observation size was 19 mm (IQR, 11-30 mm). rLR-5 showed higher sensitivity compared with LR-5 (70.6% [95% CI: 60.7, 78.9] vs 61.3% [95% CI: 45.9, 74.7]; P < .001), with similar PPV (90.7% vs 92.3%; P = .55). In studies with low risk of bias (n = 4; 1031 observations), rLR-5 also achieved a higher sensitivity than LR-5 (72.3% [95% CI: 63.9, 80.1] vs 66.9% [95% CI: 58.2, 74.5]; P = .02), with similar PPV (83.1% vs 88.7%; P = .47). Conclusion rLR-5 achieved a higher sensitivity for identifying HCC than LR-5 while maintaining a comparable PPV at 90% or more, matching the results presented in the original rLI-RADS study. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Sirlin and Chernyak in this issue.

Comparative Performance of 2018 LI-RADS versus Modified LIRADS (mLI-RADS): An Individual Participant Data Meta-Analysis.

BACKGROUND: LI-RADS version 2018 (v2018) is used for non-invasive diagnosis of hepatocellular carcinoma (HCC). A recently proposed modification (known as mLI-RADS) demonstrated improved sensitivity while maintaining specificity and positive predictive value (PPV) of LI-RADS category 5 (definite HCC) for HCC. However, mLI-RADS requires multicenter validation. PURPOSE: To evaluate the performance of v2018 and mLI-RADS for liver lesions in a large, heterogeneous, multi-national cohort of patients at risk for HCC. STUDY TYPE: Systematic review and meta-analysis using individual participant data (IPD) [Study Protocol: https://osf.io/duys4]. POPULATION: 2223 observations from 1817 patients (includes all LI-RADS categories; females = 448, males = 1361, not reported = 8) at elevated risk for developing HCC (based on LI-RADS population criteria) from 12 retrospective studies. FIELD STRENGTH/SEQUENCE: 1.5T and 3T; complete liver MRI with gadoxetate disodium, including axial T2w images and dynamic axial fat-suppressed T1w images precontrast and in the arterial, portal venous, transitional, and hepatobiliary phases. Diffusion-weighted imaging was used when available. ASSESSMENT: Liver observations were categorized using v2018 and mLI-RADS. The diagnostic performance of each system's category 5 (LR-5 and mLR-5) for HCC were compared. STATISTICAL TESTS: The Quality Assessment of Diagnostic Accuracy Studies version 2 (QUADAS-2 was applied to determine risk of bias and applicability. Diagnostic performances were assessed using the likelihood ratio test for sensitivity and specificity and the Wald test for PPV. The significance level was P < 0.05. RESULTS: 17% (2/12) of the studies were considered low risk of bias (244 liver observations; 164 patients). When compared to v2018, mLR-5 demonstrated higher sensitivity (61.3% vs. 46.5%, P < 0.001), similar PPV (85.3% vs. 86.3%, P = 0.89), and similar specificity (85.8% vs. 90.8%, P = 0.16) for HCC. DATA CONCLUSION: This study confirms mLR-5 has higher sensitivity than LR-5 for HCC identification, while maintaining similar PPV and specificity, validating the mLI-RADS proposal in a heterogeneous, international cohort. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Comparing Survival Outcomes of Patients With LI-RADS-M Hepatocellular Carcinomas and Intrahepatic Cholangiocarcinomas.

BACKGROUND: There is a sparsity of data evaluating outcomes of patients with Liver Imaging Reporting and Data System (LI-RADS) (LR)-M lesions. PURPOSE: To compare overall survival (OS) and progression free survival (PFS) between hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (iCCA) meeting LR-M criteria and to evaluate factors associated with prognosis. STUDY TYPE: Retrospective. SUBJECTS: Patients at risk for HCC with at least one LR-M lesion with histologic diagnosis, from 8 academic centers, yielding 120 patients with 120 LR-M lesions (84 men [mean age 62 years] and 36 women [mean age 66 years]). FIELD STRENGTH/SEQUENCE: A 1.5 and 3.0 T/3D T1 -weighted gradient echo, T2 -weighted fast spin-echo. ASSESSMENT: The imaging categorization of each lesion as LR-M was made clinically by a single radiologist at each site and patient outcome measures were collected. STATISTICAL TESTS: OS, PFS, and potential independent predictors were evaluated by Kaplan-Meier method, log-rank test, and Cox proportional hazard model. A P value of <0.05 was considered significant. RESULTS: A total of 120 patients with 120 LR-M lesions were included; on histology 65 were HCC and 55 were iCCA. There was similar median OS for patients with LR-M HCC compared to patients with iCCA (738 days vs. 769 days, P = 0.576). There were no significant differences between patients with HCC and iCCA in terms of sex (47:18 vs. 37:18, P = 0.549), age (63.0 ± 8.4 vs. 63.4 ± 7.8, P = 0.847), etiology of liver disease (P = 0.202), presence of cirrhosis (100% vs. 100%, P = 1.000), tumor size (4.73 ± 3.28 vs. 4.75 ± 2.58, P = 0.980), method of lesion histologic diagnosis (P = 0.646), and proportion of patients who underwent locoregional therapy (60.0% vs. 38.2%, P = 0.100) or surgery (134.8 ± 165.5 vs. 142.5 ± 205.6, P = 0.913). Using multivariable analysis, nonsurgical compared to surgical management (HR, 4.58), larger tumor size (HR, 1.19), and higher MELD score (HR, 1.12) were independently associated with worse OS. DATA CONCLUSION: There was similar OS in patients with LR-M HCC and LR-M iCCA, suggesting that LR-M imaging features may more closely reflect patient outcomes than histology. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 5.

Low-Field-Strength Body MRI: Challenges and Opportunities at 0.55 T.

Advances in MRI technology have led to the development of low-field-strength (hereafter, "low-field") (0.55 T) MRI systems with lower weight, fewer shielding requirements, and lower cost than those of traditional (1.5-3 T) systems. The trade-offs of lower signal-to-noise ratio (SNR) at 0.55 T are partially offset by patient safety and potential comfort advantages (eg, lower specific absorption rate and a more cost-effective larger bore diameter) and physical advantages (eg, decreased T2* decay, shorter T1 relaxation times). Image reconstruction advances leveraging developing technologies (such as deep learning-based denoising) can be paired with traditional techniques (such as increasing the number of signal averages) to improve SNR. The overall image quality produced by low-field MRI systems, although perhaps somewhat inferior to 1.5-3 T MRI systems in terms of SNR, is nevertheless diagnostic for a broad variety of body imaging applications. Effective low-field body MRI requires (a) an understanding of the trade-offs resulting from lower field strengths, (b) an approach to modifying routine sequences to overcome SNR challenges, and (c) a workflow for carefully selecting appropriate patients. The authors describe the rationale, opportunities, and challenges of low-field body MRI; discuss important considerations for low-field imaging with common body MRI sequences; and delineate a variety of use cases for low-field body MRI. The authors also include lessons learned from their preliminary experience with a new low-field MRI system at a tertiary care center. Finally, they explore the future of low-field MRI, summarizing current limitations and potential future developments that may enhance the clinical adoption of this technology. ©RSNA, 2023 Supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center. See the invited commentary by Venkatesh in this issue.

Renal Mass Imaging with MRI Clear Cell Likelihood Score: A User's Guide.

Small solid renal masses (SRMs) are frequently detected at imaging. Nearly 20% are benign, making careful evaluation with MRI an important consideration before deciding on management. Clear cell renal cell carcinoma (ccRCC) is the most common renal cell carcinoma subtype with potentially aggressive behavior. Thus, confident identification of ccRCC imaging features is a critical task for the radiologist. Imaging features distinguishing ccRCC from other benign and malignant renal masses are based on major features (T2 signal intensity, corticomedullary phase enhancement, and the presence of microscopic fat) and ancillary features (segmental enhancement inversion, arterial-to-delayed enhancement ratio, and diffusion restriction). The clear cell likelihood score (ccLS) system was recently devised to provide a standardized framework for categorizing SRMs, offering a Likert score of the likelihood of ccRCC ranging from 1 (very unlikely) to 5 (very likely). Alternative diagnoses based on imaging appearance are also suggested by the algorithm. Furthermore, the ccLS system aims to stratify which patients may or may not benefit from biopsy. The authors use case examples to guide the reader through the evaluation of major and ancillary MRI features of the ccLS algorithm for assigning a likelihood score to an SRM. The authors also discuss patient selection, imaging parameters, pitfalls, and areas for future development. The goal is for radiologists to be better equipped to guide management and improve shared decision making between the patient and treating physician. © RSNA, 2023 Quiz questions for this article are available in the supplemental material. See the invited commentary by Pedrosa in this issue.

Quality Control of Magnetic Resonance Elastography Using Percent Measurable Liver Volume Estimation.

BACKGROUND: Although studies have described factors associated with failed magnetic resonance elastography (MRE), little is known about what factors influence usable elastography data. PURPOSE: To identify factors that have a negative impact on percent measurable liver volume (pMLV), defined as the proportion of usable liver elastography data relative to the volume of imaged liver in patients undergoing MRE. STUDY TYPE: Retrospective. SUBJECTS: A total of 264 patients (n = 132 males, n = 132 females; mean age = 57 years) with suspected or known chronic liver disease underwent MRE paired with a liver protocol MRI. FIELD STRENGTH/SEQUENCE: MRE was performed on a single 1.5 T scanner using a two-dimensional gradient-recalled echo phase-contrast sequence with a passive acoustic driver overlying the right hemiliver. ASSESSMENT: Stiffness maps (usable data at 95% confidence) and liver contours on magnitude images of the MRE acquisition were manually traced and used to assess mean stiffness and pMLV. Hepatic fat fraction and R2 * values were also calculated. The distance from the acoustic wave generator on the skin surface to the liver edge was measured. Two radiologists performed the MR analyses with 50 overlapping cases for inter-reader analysis. STATISTICAL TESTS: Linear regression was performed to identify factors significantly associated with pMLV. Intraclass correlation was performed for inter-reader reliability. RESULTS: pMLV was 31% ± 20% (range 0%-86%). Complete MRE failure (i.e. pMLV = 0%) occurred in 10 patients (4%). Multivariate linear regression identified higher hepatic fat fraction, R2 *, BMI, and driver-to-liver surface distance; male sex; and lower mean liver stiffness was significantly independently associated with lower pMLV. Intraclass correlation for pMLV was 0.96, suggestive of excellent reliability. DATA CONCLUSION: Higher fat fraction, R2 *, BMI, driver-to-liver surface distance, male sex, and lower mean liver stiffness were associated with lower pMLV. Optimization of image acquisition parameters and driver placement may improve MRE quality, and pMLV likely serves as a diagnostic utility quality control metric. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY STAGE: 2.

Body MRI: Imaging Protocols, Techniques, and Lessons Learned.

Body MRI has evolved from a niche subspecialty to a standard modality in the practice of abdominal radiology. However, the practicing radiologist may feel uncomfortable interpreting body MRI studies owing to a lack of case volume and inconsistent exposure. The authors highlight teaching points and subtleties central to better acquisition and interpretation of body MRI studies. Appropriate contrast agent selection and arterial phase acquisition timing provide greater diagnostic certainty in answering common clinical questions at liver MRI, such as assessing cirrhosis and evaluating focal liver lesions. Clinically relevant artifacts and physiologic phenomena, such as magnetic susceptibility and transient hepatic intensity difference, must be recognized and appropriately used when reading a study. Fat within organs and lesions is commonly encountered at body MRI. The authors discuss the nuances of common and uncommon entities, how to address fat suppression failure, assessment of bone marrow at body MRI, and an organized approach to fat-containing renal and adrenal masses. Motion artifacts are more commonly encountered at body MRI than at MRI of other anatomic regions, and understanding the various techniques, their benefits, and trade-offs will aid the body imager in protocol design and moving beyond "nondiagnostic" examinations. Challenging anatomic sites to evaluate at body MRI are reviewed. Finally, the authors offer tips for accurate interpretation of diffusion-weighted imaging, hepatobiliary phase imaging, and posttreatment imaging studies. By reviewing this article, the abdominal imager will be better prepared to perform and interpret body MRI studies confidently and accurately. An invited commentary by Kalb is available online. Online supplemental material is available for this article. ©RSNA, 2022.

Validation of choledocholithiasis predictors from the "2019 ASGE Guideline for the role of endoscopy in the evaluation and management of choledocholithiasis."

BACKGROUND AND AIMS: Identifying patients likely to have CDL is an important clinical dilemma because endoscopic retrograde cholangiopancreatography (ERCP), carries a 5-7% risk of adverse events. The purpose of this study was to compare the diagnostic test performance of the 2010 and 2019 ASGE criteria used to help risk stratify patients with suspected CDL. METHODS: Consecutive patients evaluated for possible CDL from 2013 to 2019 were identified from surgical, endoscopic, and radiologic databases at a single academic center. Inclusion criteria included all patients who underwent ERCP and/or cholecystectomy with intraoperative cholangiogram (IOC) for suspected CDL. We calculated the diagnostic test performance of criteria from both guidelines and compared their discrimination using the receiver operator curve. Univariate and multivariate analysis was used to identify the strongest component predictors. RESULTS: 1098 patients [age 57.9 ± 19.0 years, 62.8% (690) F] were included. 66.3% (728) were found to have CDL on ERCP and/or IOC. When using the 2019 guidelines, the sensitivity, specificity, PPV, NPV, and accuracy are 65.8, 78.9, 86.3, 54.1, and 70.4%, respectively. Using the 2010 guidelines, the sensitivity, specificity, PPV, NPV, and accuracy are 50.5, 78.9, 82.5, 44.8, and 60.1%, respectively. The AUC for high-risk criteria using the 2019 guidelines [0.726 (0.695, 0.758)] was greater than for the 2010 guidelines [0.647 (0.614, 0.681)]. The key difference providing the increased discrimination was the inclusion of stones on any imaging modality, which increased the sensitivity to 55.0% from 29.1%. Not including CDL on imaging or cholangitis, a dilated CBD was the strongest individual predictor of CDL on multivariate analysis (OR 3.70, CI 2.80, 4.89). CONCLUSION: Compared to 2010, the 2019 high-risk criterion improves diagnostic test performance, but still performs suboptimally. Less invasive tests, such as EUS or MRCP, should be considered in patients with suspected CDL prior to ERCP.

Targetoid appearance on T2-weighted imaging and signs of tumor vascular involvement: diagnostic value for differentiating HCC from other primary liver carcinomas.

OBJECTIVES: To evaluate targetoid appearance on T2-weighted imaging and signs of tumor vascular involvement as potential new LI-RADS features for differentiating hepatocellular carcinoma (HCC) from other non-HCC primary liver carcinomas (PLCs). METHODS: This IRB-approved, retrospective study was performed at two liver transplant centers. The final population included 375 patients with pathologically proven lesions imaged between 2007 and 2017 with contrast-enhanced CT or MRI. The cohort consisted of 165 intrahepatic cholangiocarcinomas and 74 combined hepatocellular-cholangiocarcinomas, with the addition of 136 HCCs for control. Two abdominal radiologists (R1; R2) independently reviewed the imaging studies (112 CT; 263 MRI) and recorded the presence of targetoid appearance on T2-weighted images and features of tumor vascular involvement including encasement, narrowing, tethering, occlusion, and obliteration. The sensitivity and specificity of each feature were calculated for the diagnosis of non-HCC PLCs. Cohen's kappa (k) test was used to assess inter-reader agreement. RESULTS: The sensitivity of targetoid appearance on T2-weighted images for the diagnosis of non-HCC PLCs was 27.5% and 32.6% (R1 and R2) and the specificity was 98.2% and 97.3% (R1 and R2). Among the features of tumor vascular involvement, those providing the highest sensitivity for non-HCC PLCs were vascular encasement (R1: 34.3%; R2: 37.2%) and obliteration (R1: 25.5%; R2: 29.7%). The highest specificity for non-HCC PLCs was provided by tethering (R1: 100%; R2: 97.1%) and occlusion (R1: 99.3%; R2: 99.3%). The inter-reader agreement was moderate to substantial (k = 0.48-0.77). CONCLUSIONS: Targetoid appearance on T2-weighted images and features of tumor vascular involvement demonstrated high specificity for non-HCC malignancy. KEY POINTS: • Targetoid appearance on T2-weighted imaging and signs of tumor vascular involvement have high specificity (92-100%) for the diagnosis of non-HCC PLCs, regardless of the presence of liver risk factors. • In the subset of patients with risk factors for HCC, the sensitivity of signs of tumor vascular involvement decreases for both readers (1.7-20.3%), while the specificity increases reaching values higher than 94.2%. • The inter-reader agreement is substantial for targetoid appearance on T2-weighted images (k = 0.74) and moderate to substantial for signs of tumor vascular involvement (k = 0.48-0.77).

Imaging Biomarkers of Hepatic Fibrosis: Reliability and Accuracy of Hepatic Periportal Space Widening and Other Morphologic Features on MRI.

OBJECTIVE. The purpose of this article was to assess the reliability and accuracy of hepatic periportal space widening and other qualitative imaging features for the prediction of hepatic fibrosis. MATERIALS AND METHODS. This single-center retrospective study identified consecutive patients who had undergone liver MR elastography. Two abdominal radiologists independently reviewed anatomic images, assessing multiple qualitative features of chronic liver disease (CLD) including periportal space widening. Each reader also measured the periportal space at the main portal vein (MPV) and right portal vein (RPV). Interrater reliability analysis was then performed. Sensitivity and specificity were determined for the detection of any hepatic fibrosis (stage I or higher) and of advanced fibrosis (stage III or higher) using stiffness on MR elastography as the reference standard. RESULTS. Of 229 subjects, 157 (69%) had fibrosis and 78 (34%) had advanced fibrosis. Agreement for periportal space widening was moderate (κ = 0.47), and agreement for remaining features was moderate to substantial (κ = 0.42-0.80). Agreement for the periportal space at the MPV was moderate (ICC, 0.55), and agreement for the periportal space at the RPV was near perfect (ICC, 0.83). Periportal space widening had the highest sensitivity (83.0%) for any fibrosis, with limited specificity (61.3%). Surface nodularity had the highest specificity (94.4%) for any fibrosis, with limited sensitivity (51.6%). Periportal space widening plus one or more additional imaging feature of CLD or the presence of surface nodularity alone had sensitivity of 72.6% and specificity of 76.1%. A periportal space at the MPV greater than 9.5 mm had substantial agreement with qualitative periportal space widening (κ = 0.74). CONCLUSION. Periportal space widening has a high sensitivity for hepatic fibrosis, with moderate specificity when combined with additional anatomic features of CLD.

Contemporary Imaging of the Surgically Placed Hepatic Arterial Infusion Chemotherapy Pump.

Hepatic arterial infusion (HAI) of chemotherapy is a locoregional treatment strategy for hepatic malignancy involving placement of a surgically implanted pump or percutaneous port-catheter device into a branch of the hepatic artery. HAI has been used for metastatic colorectal cancer for decades but has recently attracted new attention because of its potential impact on survival, when combined with systemic therapy, in patients presenting with unresectable hepatic disease. Although various HAI device-related complications have been described, little attention has been given to their appearance on imaging. Radiologists are uniquely positioned to identify these complications given that patients receiving HAI therapy typically undergo frequent imaging and may have complications that are delayed or clinically unsuspected. Therefore, this article reviews the multimodality imaging considerations of surgically implanted HAI devices. The role of imaging in routine perioperative assessment, including the normal postoperative appearance of the device, is described. The imaging findings of potential complications, including pump pocket complications, catheter or arterial complications, and toxic or ischemic complications, are presented, with a focus on CT. Familiarity with the device and its complications will aid radiologists in playing an important role in the treatment of patients undergoing HAI therapy.

Magnetic Resonance Angiography of the Thoracic Vasculature: Technique and Applications.

Magnetic resonance angiography (MRA) is a powerful clinical tool for evaluation of the thoracic vasculature. MRA can be performed on nearly any magnetic resonance imaging (MRI) scanner, and provides images of high diagnostic quality without the use of ionizing radiation. While computed tomographic angiography (CTA) is preferred in the evaluation of hemodynamically unstable patients, MRA represents an important tool for evaluation of the thoracic vasculature in stable patients. Contrast-enhanced MRA is generally performed unless there is a specific contraindication, as it shortens the duration of the exam and provides images of higher diagnostic quality than noncontrast MRA. However, intravenous contrast is often not required to obtain a diagnostic evaluation for most clinical indications. Indeed, a variety of noncontrast MRA techniques are used for thoracic imaging, often in conjunction with contrast-enhanced MRA, each of which has a differing degree of reliance on flowing blood to produce the desired vascular signal. In this article we review contrast-enhanced MRA, with a focus on contrast agents, methods of bolus timing, and considerations in imaging acquisition. Next, we cover the mechanism of contrast, strengths, and weaknesses of various noncontrast MRA techniques. Finally, we present an approach to protocol development and review representative protocols used at our institution for a variety of thoracic applications. Further attention will be devoted to additional techniques employed to address specific clinical questions, such as delayed contrast-enhanced imaging, provocative maneuvers, electrocardiogram and respiratory gating, and phase-contrast imaging. The purpose of this article is to review basic techniques and methodology in thoracic MRA, discuss an approach to protocol development, and illustrate commonly encountered pathology on thoracic MRA examinations. Level of Evidence 5 Technical Efficacy Stage 3.

Assessment of primary liver carcinomas other than hepatocellular carcinoma (HCC) with LI-RADS v2018: comparison of the LI-RADS target population to patients without LI-RADS-defined HCC risk factors.

OBJECTIVES: To determine whether the LI-RADS imaging features of primary liver carcinomas (PLCs) other than hepatocellular carcinoma (non-HCC PLCs) differ between patients considered high risk (RF+) versus not high risk (RF-) for HCC and to compare rates of miscategorization as probable or definite HCC between the RF+ and RF- populations. METHODS: This retrospective study included all pathology-proven non-HCC PLCs imaged with liver-protocol CT or MRI from 2007 to 2017 at two liver transplant centers. Patients were defined per LI-RADS v2018 criteria as RF+ or RF-. Two independent, blinded readers (R1, R2) categorized 265 lesions using LI-RADS v2018. Logistic regression was utilized to assess for differences in imaging feature frequencies between RF+ and RF- patients. Fisher's exact test was used to assess for differences in miscategorization rates. RESULTS: Non-HCC PLCs were significantly more likely to exhibit nonrim arterial phase hyperenhancement (R1: OR = 2.94; R2: OR = 7.09) and nonperipheral "washout" (R1: OR = 3.65; R2: OR = 7.69) but significantly less likely to exhibit peripheral "washout" (R1: OR = 0.30; R2: OR = 0.10) and delayed central enhancement (R1: OR = 0.18; R2: OR = 0.25) in RF+ patients relative to RF- patients. Consequently, non-HCC PLCs were more often miscategorized as probable or definite HCC in RF+ versus RF- patients (R1: 23.3% vs. 3.6%, p < 0.001; R2: 11.0% vs. 2.6%, p = 0.009). CONCLUSIONS: Non-HCC PLCs are more likely to mimic HCCs on CT and MRI in the LI-RADS target population than in patients without LI-RADS-defined HCC risk factors. KEY POINTS: • The presence of LI-RADS-defined risk factors for HCC tends to alter the imaging appearances of non-HCC PLCs, resulting in higher frequencies of major features and lower frequencies of LR-M features. • Non-HCC PLCs are more likely to be miscategorized as probable or definite HCC in the LI-RADS target population than in patients without LI-RADS-defined HCC risk factors.

Apparent Diffusion Coefficient Distinguishes Malignancy in T1-Hyperintense Small Renal Masses.

OBJECTIVE. Small renal masses (< 4 cm) can be difficult to accurately classify as benign or malignant, particularly when they appear T1 hyperintense on MRI. This intrinsic signal, potentially related to intralesional hemorrhage, may limit evaluation of signal intensity on DWI. The purpose of this study was to test whether apparent diffusion coefficient (ADC) measurements may distinguish malignancy. MATERIALS AND METHODS. This single-center retrospective study identified patients with a T1-hyperintense renal mass less than 4 cm on MRI. Malignant lesions were pathologically proven; a benign mass was established by a predefined hierarchy of pathologic proof, follow-up ultrasound, or follow-up imaging showing more than 5 years of stability. T1 hyperintensity, defined as a signal intensity equivalent to or greater than the adjacent renal cortex, was confirmed by a senior abdominal radiologist. Two additional abdominal radiologists independently measured ADC of the lesion, which was normalized to the ADC of the background ipsilateral kidney and represented as ADCratio. RESULTS. The final cohort included 58 benign and 37 malignant renal lesions in 95 patients. Interrater agreement for ADC measurements was almost perfect (κ = 0.836-0.934). ADCratio was significantly lower in malignant compared with benign lesions (0.65 ± 0.29 vs 1.03 ± 0.32; p < 0.001). Malignant lesions were significantly larger than benign lesions (2.66 ± 0.86 cm vs 1.50 ± 0.65 cm; p < 0.001); however, after controlling for lesion size, ADCratio remained a significant predictor of malignancy (p < 0.001). CONCLUSION. ADCratio was highly reproducible for T1-hyperintense small renal masses and was significantly lower in malignant compared with benign renal masses.

Building blocks for thoracic MRI: Challenges, sequences, and protocol design.

Thoracic MRI presents important and unique challenges. Decreased proton density in the lung in combination with respiratory and cardiac motion can degrade image quality and render poorly executed sequences uninterpretable. Despite these challenges, thoracic MRI has an important clinical role, both as a problem-solving tool and in an increasing array of clinical indications. Advances in scanner and sequence design have also helped to drive this development, presenting the radiologist with improved techniques for thoracic MRI. Given this evolving landscape, radiologists must be familiar with what thoracic MR has to offer. The first step in developing an effective thoracic MRI practice requires the creation of efficient and malleable protocols that can answer clinical questions. To do this, radiologists must have a working knowledge of the MR sequences that are used in the thorax, many of which have been adapted from use elsewhere in the body. These sequences can be broadly divided into three categories: traditional/anatomic, functional, and cine based. Traditional/anatomic sequences allow for the depiction of anatomy and pathologic processes with the ability for characterization of signal intensity and contrast enhancement. Functional sequences, including diffusion-weighted imaging, and high temporal resolution dynamic contrast enhancement, allow for the noninvasive measurement of tissue-specific parameters. Cine-based sequences can depict the motion of structures in the thorax, either with retrospective ECG gating or in real time. The purpose of this article is to review these categories, the building block sequences that comprise them, and identify basic questions that should be considered in thoracic MRI protocol design. Level of Evidence: 5 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2019;50:682-701.

Diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS) v2017 in predicting malignant liver lesions in pediatric patients: a preliminary study.

BACKGROUND: Liver Imaging Reporting and Data System (LI-RADS) has standardized the evaluation of hepatic lesions in adults at risk of developing hepatocellular carcinoma (HCC). There is no accepted imaging algorithm for diagnosing HCC in the pediatric population. OBJECTIVE: The aim of our study was to evaluate the diagnostic accuracy and inter-rater reliability of LI-RADS version 2017 (v2017) for diagnosing HCC in a pediatric cohort. MATERIALS AND METHODS: This retrospective, Institutional Review Board-approved study involved review of all abdominal dynamic contrast-enhanced imaging at a tertiary children's hospital during a 10-year period, yielding 151 liver lesions in patients <18 years. Cases with active extrahepatic malignancy or an inadequate reference standard were excluded. Two readers independently evaluated all included hepatic lesions using LI-RADS criteria. Pathology and imaging follow-up were used as reference standards. RESULTS: A total of 41 lesions in 41 patients met criteria for evaluation (3 HCCs, 8 non-HCC malignancies, 30 benign lesions). A LI-RADS designation of definite HCC had high sensitivity (Reader 1/Reader 2: 100%, 95% confidence interval [CI] 31-100%) and high specificity (Reader 1: 84%, 95% CI: 68-93%; Reader 2: 97%, 95% CI: 85-100%) for predicting HCC. However, positive predictive value was only 33% (95% CI: 9-69%) and 75% (95% CI: 22-99%) for Reader 1 and Reader 2, respectively. For predicting any type of hepatic malignancy, a LI-RADS designation of definitely or likely malignant (i.e. not necessarily HCC) had a sensitivity of 100% (95% CI: 74-100%) and 90% (95% CI: 61-100%) for Reader 1 and Reader 2, respectively, and a negative predictive value (NPV) of 100% (95% CI: 81-100%) and 96% (95% CI: 83-99%) for Reader 1 and Reader 2, respectively. Interobserver agreement was substantial for the overall LI-RADS category (weighted κ=0.62; 95% CI: 0.38-0.86). CONCLUSION: The positive predictive value of LI-RADS v2017 for diagnosing HCC was limited by the low frequency of HCC among pediatric patients. However, a LI-RADS designation of definitely or likely malignant had high sensitivity and NPV for any type of hepatic malignancy and may serve to direct clinical management by selecting patients for tissue sampling.

Expanding the Liver Imaging Reporting and Data System (LI-RADS) v2018 diagnostic population: performance and reliability of LI-RADS for distinguishing hepatocellular carcinoma (HCC) from non-HCC primary liver carcinoma in patients who do not meet strict LI-RADS high-risk criteria.

BACKGROUND: Hepatocellular carcinoma (HCC) can be diagnosed using imaging criteria in patients at high-risk for HCC, according to Liver Imaging Reporting and Data System (LI-RADS) guidelines. The aim of this study was to determine the diagnostic performance and inter-rater reliability (IRR) of LI-RADS v2018 for differentiating HCC from non-HCC primary liver carcinoma (PLC), in patients who are at increased risk for HCC but not included in the LI-RADS 'high-risk' population. METHODS: This retrospective HIPAA-compliant study included a 10-year experience of pathologically-proven PLC at two liver transplant centers, and included patients with non-cirrhotic hepatitis C infection, non-cirrhotic non-alcoholic fatty liver disease, and fibrosis. Two readers evaluated each lesion and assigned an overall LI-RADS diagnostic category, additionally scoring all major, LR-M, and ancillary features. RESULTS: The final study cohort consisted of 27 HCCs and 104 non-HCC PLC in 131 patients. The specificity of a 'definite HCC' designation was 97% for reader 1 and 100% for reader 2. The IRR was fair for overall LI-RADS category and substantial for most major features. CONCLUSION: In a population at increased risk for HCC but not currently included in the LI-RADS 'high-risk' population, LI-RADS v2018 demonstrated very high specificity for distinguishing pathologically-proven HCC from non-HCC PLC.