Deep learning-based compressed SENSE improved diffusion-weighted image quality and liver cancer detection: A prospective study

PURPOSE

To assess whether diffusion-weighted imaging (DWI) with Compressed SENSE (CS) and deep learning (DL-CS-DWI) can improve image quality and lesion detection in patients at risk for hepatocellular carcinoma (HCC).

METHODS

This single-center prospective study enrolled consecutive at-risk participants who underwent 3.0 T gadoxetate disodium-enhanced MRI. Conventional DWI was acquired using parallel imaging (PI) with SENSE (PI-DWI). In CS-DWI and DL-CS-DWI, CS but not PI with SENSE was used to accelerate the scan with 2.5 as the acceleration factor. Qualitative and quantitative image quality were independently assessed by two masked reviewers, and were compared using the Wilcoxon signed-rank test. The detection rates of clinically-relevant (LR-4/5/M based on the Liver Imaging Reporting and Data System v2018) liver lesions for each DWI sequence were independently evaluated by another two masked reviewers against their consensus assessments based on all available non-DWI sequences, and were compared by the McNemar test.

RESULTS

67 participants (median age, 58.0 years; 56 males) with 197 clinically-relevant liver lesions were enrolled. Among the three DWI sequences, DL-CS-DWI showed the best qualitative and quantitative image qualities (p range, <0.001-0.039). For clinically-relevant liver lesions, the detection rates (91.4%-93.4%) of DL-CS-DWI showed no difference with CS-DWI (87.3%-89.8%, p = 0.230-0.231) but were superior to PI-DWI (82.7%-85.8%, p = 0.015-0.025). For lesions located in the hepatic dome, DL-CS-DWI demonstrated the highest detection rates (94.8%-97.4% vs 76.9%-79.5% vs 64.1%-69.2%, p = 0.002-0.045) among the three DWI sequences.

CONCLUSION

In patients at high-risk for HCC, DL-CS-DWI improved image quality and detection for clinically-relevant liver lesions, especially for the hepatic dome.

A Method for Efficient De-identification of DICOM Metadata and Burned-in Pixel Text

De-identification of DICOM images is an essential component of medical image research. While many established methods exist for the safe removal of protected health information (PHI) in DICOM metadata, approaches for the removal of PHI "burned-in" to image pixel data are typically manual, and automated high-throughput approaches are not well validated. Emerging optical character recognition (OCR) models can potentially detect and remove PHI-bearing text from medical images but are very time-consuming to run on the high volume of images found in typical research studies. We present a data processing method that performs metadata de-identification for all images combined with a targeted approach to only apply OCR to images with a high likelihood of burned-in text. The method was validated on a dataset of 415,182 images across ten modalities representative of the de-identification requests submitted at our institution over a 20-year span. Of the 12,578 images in this dataset with burned-in text of any kind, only 10 passed undetected with the method. OCR was only required for 6050 images (1.5% of the dataset).

LI-RADS CT and MRI Ancillary Feature Association with Hepatocellular Carcinoma and Malignancy: An Individual Participant Data Meta-Analysis

Background The independent contribution of each Liver Imaging Reporting and Data System (LI-RADS) CT or MRI ancillary feature (AF) has not been established. Purpose To evaluate the association of LI-RADS AFs with hepatocellular carcinoma (HCC) and malignancy while adjusting for LI-RADS major features through an individual participant data (IPD) meta-analysis. Materials and Methods Medline, Embase, Cochrane Central Register of Controlled Trials, and Scopus were searched from January 2014 to January 2022 for studies evaluating the diagnostic accuracy of CT and MRI for HCC using LI-RADS version 2014, 2017, or 2018. Using a one-step approach, IPD across studies were pooled. Adjusted odds ratios (ORs) and 95% CIs were derived from multivariable logistic regression models of each AF combined with major features except threshold growth (excluded because of infrequent reporting). Liver observation clustering was addressed at the study and participant levels through random intercepts. Risk of bias was assessed using a composite reference standard and Quality Assessment of Diagnostic Accuracy Studies 2. Results Twenty studies comprising 3091 observations (2456 adult participants; mean age, 59 years ± 11 [SD]; 1849 [75.3%] men) were included. In total, 89% (eight of nine) of AFs favoring malignancy were associated with malignancy and/or HCC, 80% (four of five) of AFs favoring HCC were associated with HCC, and 57% (four of seven) of AFs favoring benignity were negatively associated with HCC and/or malignancy. Nonenhancing capsule (OR = 3.50 [95% CI: 1.53, 8.01]) had the strongest association with HCC. Diffusion restriction (OR = 14.45 [95% CI: 9.82, 21.27]) and mild-moderate T2 hyperintensity (OR = 10.18 [95% CI: 7.17, 14.44]) had the strongest association with malignancy. The strongest negative associations with HCC were parallels blood pool enhancement (OR = 0.07 [95% CI: 0.01, 0.49]) and marked T2 hyperintensity (OR = 0.18 [95% CI: 0.07, 0.45]). Seventeen studies (85%) had a high risk of bias. Conclusion Most LI-RADS AFs were independently associated with HCC, malignancy, or benignity as intended when adjusting for major features. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Crivellaro in this issue.

Are dilution, slow injection and care bolus technique the causal solution to mitigating arterial-phase artifacts on gadoxetic acid-enhanced MRI? A large-cohort study

OBJECTIVE

Arterial-phase artifacts are gadoxetic acid (GA)-enhanced MRI's major drawback, ranging from 5 to 39%. We evaluate the effect of dilution and slow injection of GA using automated fluoroscopic triggering on liver MRI arterial-phase (AP) acquisition timing, artifact frequency, and lesion visibility.

METHODS AND MATERIALS

Saline-diluted 1:1 GA was injected at 1 ml/s into 1413 patients for 3 T liver MRI. Initially, one senior abdominal radiologist, i.e., principal investigator (PI), assessed all MR exams and compared them to previous and follow-up images, as well as the radiology report on record, determining the standard of reference for lesion detection and characterization. Then, three other readers independently evaluated the AP images for artifact type (truncation (TA), transient severe motion (TSM) or mixed), artifact severity (on a 5-point scale), acquisition timing (on a 4-point scale) and visibility (on a 5-point scale) of hypervascular lesions ≥ 5 mm, selected by the PI. Artifact score ≥ 4 and artifact score ≤ 3 were considered significant and non-significant artifacts, respectively.

RESULTS

Of the 1413 exams, diagnostic-quality arterial-phase images included 1100 (77.8%) without artifacts, 220 (15.6%) with minimal, and 77 (5.4%) with moderate artifacts. Only 16 exams (1.1%) had significant artifacts, 13 (0.9%) with severe artifacts (score 4), and three (0.2%) non-diagnostic artifacts (score 5). AP acquisition timing was optimal in 1369 (96.8%) exams. Of the 449 AP hypervascular lesions, 432 (96.2%) were detected.

CONCLUSION

Combined dilution and slow injection of GA with MR results in well-timed arterial-phase images in 96.8% and a reduction of exams with significant artifacts to 1.1%.

CLINICAL RELEVANCE STATEMENT

Hypervascular lesions, in particular HCC detection, hinge on arterial-phase hyperenhancement, making well-timed, artifact-free arterial-phase images a prerequisite for accurate diagnosis. Saline dilution 1:1, slow injection (1 ml/s), and automated bolus triggering reduce artifacts and optimize acquisition timing.

KEY POINTS

• There was substantial agreement among the three readers regarding the presence and type of arterial-phase (AP) artifacts, acquisition timing, and lesion visibility. • Impaired AP hypervascular lesion visibility occurred in 17 (3.8%) cases; in eight lesions due to mistiming and in nine lesions due to significant artifacts. • When AP timing was suboptimal, it was too late in 40 exams (3%) and too early in 4 exams (0.2%) of exams.

Abbreviated MRI Protocols in the Abdomen and Pelvis

Abbreviated MRI (AMRI) protocols rely on the acquisition of a limited number of sequences tailored to a specific question. The main objective of AMRI protocols is to reduce exam duration and costs, while maintaining an acceptable diagnostic performance. AMRI is of increasing interest in the radiology community; however, challenges limiting clinical adoption remain. In this review, we will address main abdominal and pelvic applications of AMRI in the liver, pancreas, kidney, and prostate, including diagnostic performance, pitfalls, limitations, and cost effectiveness will also be discussed. Level of Evidence: 3 Technical Efficacy Stage: 3.

Design of the phase 3 MAESTRO clinical program to evaluate resmetirom for the treatment of nonalcoholic steatohepatitis

BACKGROUND

Non-alcoholic steatohepatitis (NASH) is a progressive form of non-alcoholic fatty liver disease (NAFLD) associated with steatosis, hepatocellular injury, inflammation and fibrosis. In a Phase 2 trial in adults with NASH (NCT02912260), resmetirom, an orally administered, liver-targeted thyroid hormone receptor-β selective agonist, significantly reduced hepatic fat (via imaging) and resolved NASH without worsening fibrosis (via liver biopsy) in a significant number of patients compared with placebo.

AIMS

To present the design of the Phase 3 MAESTRO clinical programme evaluating resmetirom for treatment of NASH (MAESTRO-NAFLD-1 [NCT04197479], MAESTRO-NAFLD-OLE [NCT04951219], MAESTRO-NASH [NCT03900429], MAESTRO-NASH-OUTCOMES [NCT05500222]).

METHODS

MAESTRO-NASH is a pivotal serial biopsy trial in up to 2000 adults with biopsy-confirmed at-risk NASH. Patients are randomised to a once-daily oral placebo, 80 mg resmetirom, or 100 mg resmetirom. Liver biopsies are conducted at screening, week 52 and month 54. MAESTRO-NAFLD-1 is a 52-week safety trial in ~1400 adults with NAFLD/presumed NASH (based on non-invasive testing); ~700 patients from MAESTRO-NAFLD-1 are enrolled in MAESTRO-NAFLD-OLE, a 52-week active treatment extension to further evaluate safety. MAESTRO-NASH-OUTCOMES is enrolling 700 adults with well-compensated NASH cirrhosis to evaluate the potential for resmetirom to slow progression to hepatic decompensation events. Non-invasive tests (biomarkers, imaging) are assessed longitudinally throughout, in addition to validated patient-reported outcomes.

CONCLUSION

The MAESTRO clinical programme was designed in conjunction with regulatory authorities to support approval of resmetirom for treatment of NASH. The surrogate endpoints, based on week 52 liver biopsy, serum biomarkers and imaging, are confirmed by long-term clinical liver-related outcomes in MAESTRO-NASH (month 54) and MAESTRO-NASH-OUTCOMES (time to event).

Diagnosis and Monitoring of Nonalcoholic Steatohepatitis: Current State and Future Directions

Nonalcoholic fatty liver disease (NAFLD) is a common liver disease, with a worldwide prevalence of 25%. NAFLD is a spectrum that includes nonalcoholic fatty liver defined histologically by isolated hepatocytes steatosis without inflammation and nonalcoholic steatohepatitis (NASH) is the inflammatory subtype of NAFLD and is associated with disease progression, development of cirrhosis, and increased rates of liver-specific and overall mortality. The differentiation between NAFLD and NASH as well as staging NASH are important yet challenging clinical problems. Liver biopsy is currently the standard for disease diagnosis and fibrosis staging. However, this procedure is invasive, costly, and cannot be used for longitudinal monitoring. Therefore, several noninvasive quantitative imaging biomarkers have been proposed that can estimate the severity of hepatic steatosis and fibrosis. Despite this, noninvasive diagnosis of NASH and accurate risk stratification remain unmet needs. In this work, the most relevant available imaging biomarkers are reviewed and their application in patients with NAFLD are discussed.

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.

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.

Development of a Model including MRI Features for Predicting Advanced-stage Recurrence of Hepatocellular Carcinoma after Liver Resection

Background Identifying patients at high risk for advanced-stage hepatocellular carcinoma (HCC) recurrence after liver resection may improve patient survival. Purpose To develop a model including MRI features for predicting postoperative advanced-stage HCC recurrence. Materials and Methods This single-center, retrospective study includes consecutive adult patients who underwent preoperative contrast-enhanced MRI and curative-intent resection for early- to intermediate-stage HCC (from December 2011 to April 2021). Three radiologists evaluated 52 qualitative features on MRI scans. In the training set, Fine-Gray proportional subdistribution hazard analysis was performed to identify clinical, laboratory, imaging, pathologic, and surgical variables to include in the predictive model. In the test set, the concordance index (C-index) was computed to compare the developed model with current staging systems. The Kaplan-Meier survival curves were compared using the log-rank test. Results The study included 532 patients (median age, 54 years; IQR, 46-62 years; 465 male patients), 302 patients from the training set (median age, 54 years; IQR, 46-63 years; 265 male patients), and 128 patients from the test set (median age, 53 years; IQR, 46-63 years; 108 male patients). Advanced-stage recurrence was observed in 38 of 302 (12.6%) and 15 of 128 (11.7%) of patients from the training and test sets, respectively. Serum neutrophil count (109/L), tumor size (in centimeters), and arterial phase hyperenhancement proportion on MRI scans were associated with advanced-stage recurrence (subdistribution hazard ratio range, 1.16-3.83; 95% CI: 1.02, 7.52; P value range, <.001 to .02) and included in the predictive model. The model showed better test set prediction for advanced-stage recurrence than four staging systems (2-year C-indexes, 0.82 [95% CI: 0.74, 0.91] vs 0.63-0.68 [95% CI: 0.52, 0.82]; P value range, .001-.03). Patients at high risk for HCC recurrence (model score, ≥15 points) showed increased advanced-stage recurrence and worse all-stage recurrence-free survival (RFS), advanced-stage RFS, and overall survival than patients at low risk for HCC recurrence (P value range, <.001 to .02). Conclusion A model combining serum neutrophil count, tumor size, and arterial phase hyperenhancement proportion predicted advanced-stage HCC recurrence better than current staging systems and may identify patients at high risk. Published under a CC BY 4.0 license. Supplemental material is available for this article. See also the editorial by Tsai and Mellnick in this issue.

Resmetirom for nonalcoholic fatty liver disease: a randomized, double-blind, placebo-controlled phase 3 trial

Nonalcoholic steatohepatitis (NASH) is a progressive liver disease with no approved treatment. MAESTRO-NAFLD-1 was a 52-week randomized, double-blind, placebo-controlled phase 3 trial evaluating the safety of resmetirom in adults with nonalcoholic fatty liver disease and presumed NASH. Patients were randomized to three double-blind arms (100 mg resmetirom (n = 325), 80 mg resmetirom (n = 327) or placebo (n = 320)) or open-label 100 mg resmetirom (n = 171). The primary end point was incidence of treatment-emergent adverse events (TEAEs) over 52 weeks and key secondary end points were LDL-C, apoB, triglycerides (over 24 weeks), hepatic fat (over 16 and 52 weeks) and liver stiffness (over 52 weeks). Resmetirom was safe and well tolerated. TEAEs occurred in 86.5% (open-label 100 mg resmetirom), 86.1% (100 mg resmetirom), 88.4% (80 mg resmetirom) and 81.8% (placebo) of patients. TEAEs in excess of placebo included diarrhea and nausea at the initiation of treatment. Key secondary end points included least square means difference from placebo at 80 mg, 100 mg resmetirom: LDL-C (-11.1%, -12.6%), apoB (-15.6%, -18.0%), triglycerides (-15.4%, -20.4%), 16-week hepatic fat (-34.9%, -38.6%), (P < 0.0001) and liver stiffness (-1.02, -1.70) and 52-week hepatic fat (-28.8, -33.9). These findings demonstrate resmetirom was safe and well tolerated in adults with presumed NASH, supporting a role for further clinical development. (ClinicalTrials.gov identifier NCT04197479 ).

ACR Appropriateness Criteria® Abnormal Liver Function Tests

Liver function tests are commonly obtained in symptomatic and asymptomatic patients. Various overlapping lab patterns can be seen due to derangement of hepatocytes and bile ducts function. Imaging tests are pursued to identify underlying etiology and guide management based on the lab results. Liver function tests may reveal mild, moderate, or severe hepatocellular predominance and can be seen in alcoholic and nonalcoholic liver disease, acute hepatitis, and acute liver injury due to other causes. Cholestatic pattern with elevated alkaline phosphatase with or without elevated γ-glutamyl transpeptidase can be seen with various causes of obstructive biliopathy. Acute or subacute cholestasis with conjugated or unconjugated hyperbilirubinemia can be seen due to prehepatic, intrahepatic, or posthepatic causes. We discuss the initial and complementary imaging modalities to be used in clinical scenarios presenting with abnormal liver function tests. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.

Prognostic MRI features to predict postresection survivals for very early to intermediate stage hepatocellular carcinoma

OBJECTIVES

Contrast-enhanced MRI can provide individualized prognostic information for hepatocellular carcinoma (HCC). We aimed to investigate the value of MRI features to predict early (≤ 2 years)/late (> 2 years) recurrence-free survival (E-RFS and L-RFS, respectively) and overall survival (OS).

MATERIALS AND METHODS

Consecutive adult patients at a tertiary academic center who received curative-intent liver resection for very early to intermediate stage HCC and underwent preoperative contrast-enhanced MRI were retrospectively enrolled from March 2011 to April 2021. Three masked radiologists independently assessed 54 MRI features. Uni- and multivariable Cox regression analyses were conducted to investigate the associations of imaging features with E-RFS, L-RFS, and OS.

RESULTS

This study included 600 patients (median age, 53 years; 526 men). During a median follow-up of 55.3 months, 51% of patients experienced recurrence (early recurrence: 66%; late recurrence: 34%), and 17% died. Tumor size, multiple tumors, rim arterial phase hyperenhancement, iron sparing in solid mass, tumor growth pattern, and gastroesophageal varices were associated with E-RFS and OS (largest p = .02). Nonperipheral washout (p = .006), markedly low apparent diffusion coefficient value (p = .02), intratumoral arteries (p = .01), and width of the main portal vein (p = .03) were associated with E-RFS but not with L-RFS or OS, while the VICT2 trait was specifically associated with OS (p = .02). Multiple tumors (p = .048) and radiologically-evident cirrhosis (p < .001) were the only predictors for L-RFS.

CONCLUSION

Twelve visually-assessed MRI features predicted postoperative E-RFS (≤ 2 years), L-RFS (> 2 years), and OS for very early to intermediate-stage HCCs.

CLINICAL RELEVANCE STATEMENT

The prognostic MRI features may help inform personalized surgical planning, neoadjuvant/adjuvant therapies, and postoperative surveillance, thus may be included in future prognostic models.

KEY POINTS

• Tumor size, multiple tumors, rim arterial phase hyperenhancement, iron sparing, tumor growth pattern, and gastroesophageal varices predicted both recurrence-free survival within 2 years and overall survival. • Nonperipheral washout, markedly low apparent diffusion coefficient value, intratumoral arteries, and width of the main portal vein specifically predicted recurrence-free survival within 2 years, while the VICT2 trait specifically predicted overall survival. • Multiple tumors and radiologically-evident cirrhosis were the only predictors for recurrence-free survival beyond 2 years.

Best Practice for MRI Diagnostic Accuracy Research With Lessons and Examples from the LI-RADS Individual Participant Data Group

Medical imaging diagnostic test accuracy research is strengthened by adhering to best practices for study design, data collection, data documentation, and study reporting. In this review, key elements of such research are discussed, and specific recommendations provided for optimizing diagnostic accuracy study execution to improve uniformity, minimize common sources of bias and avoid potential pitfalls. Examples are provided regarding study methodology and data collection practices based on insights gained by the liver imaging reporting and data system (LI-RADS) individual participant data group, who have evaluated raw data from numerous MRI diagnostic accuracy studies for risk of bias and data integrity. The goal of this review is to outline strategies for investigators to improve research practices, and to help reviewers and readers better contextualize a study's findings while understanding its limitations. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY: Stage 3.

AHRR Hypomethylation mediates the association between maternal smoking and metabolic profiles in children

BACKGROUND

Tobacco smoking during pregnancy is associated with metabolic dysfunction in children, but mechanistic insights remain limited. Hypomethylation of cg05575921 in the aryl hydrocarbon receptor repressor (AHRR) gene is associated with in utero tobacco smoke exposure. In this study, we evaluated whether AHRR hypomethylation mediates the association between maternal smoking and metabolic dysfunction in children.

METHODS

We assessed metabolic dysfunction using liver fat content (LFC), serum, and clinical data in children aged 7-12 years (n=78) followed since birth. Maternal smoking was self-reported at 12 weeks gestation. Methylation was measured by means of pyrosequencing at 3 sequential CpG sites, including cg05575921, at birth and at ages 7-12. Regression models were used to evaluate whether AHRR methylation mediated the association between maternal smoking and child metabolic dysfunction.

RESULTS

Average AHRR methylation at birth was significantly higher among children of nonsmoking mothers compared with children of mothers who smoked (69.8% ± 4.4% vs. 63.5% ± 5.5, p=0.0006). AHRR hypomethylation at birth was associated with higher liver fat content (p=0.01), triglycerides (p=0.01), and alanine aminotransferase levels (p=0.03), and lower HDL cholesterol (p=0.01) in childhood. AHRR hypomethylation significantly mediated associations between maternal smoking and liver fat content (indirect effect=0.213, p=0.018), triglycerides (indirect effect=0.297, p=0.044), and HDL cholesterol (indirect effect = -0.413, p=0.007). AHRR methylation in childhood (n=78) was no longer significantly associated with prenatal smoke exposure or child metabolic parameters (p>0.05).

CONCLUSIONS

AHRR hypomethylation significantly mediates the association between prenatal tobacco smoke exposure and features of childhood metabolic dysfunction, despite the lack of persistent hypomethylation of AHRR into childhood. Further studies are needed to replicate these findings and to explore their causal and long-term significance.

Duke Liver Dataset: A Publicly Available Liver MRI Dataset with Liver Segmentation Masks and Series Labels

The Duke Liver Dataset contains 2146 abdominal MRI series from 105 patients, including a majority with cirrhotic features, and 310 image series with corresponding manually segmented liver masks.

Imaging prognostication and tumor biology in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.

A Multicenter Assessment of Interreader Reliability of LI-RADS Version 2018 for MRI and CT

Background Various limitations have impacted research evaluating reader agreement for Liver Imaging Reporting and Data System (LI-RADS). Purpose To assess reader agreement of LI-RADS in an international multicenter multireader setting using scrollable images. Materials and Methods This retrospective study used deidentified clinical multiphase CT and MRI and reports with at least one untreated observation from six institutions and three countries; only qualifying examinations were submitted. Examination dates were October 2017 to August 2018 at the coordinating center. One untreated observation per examination was randomly selected using observation identifiers, and its clinically assigned features were extracted from the report. The corresponding LI-RADS version 2018 category was computed as a rescored clinical read. Each examination was randomly assigned to two of 43 research readers who independently scored the observation. Agreement for an ordinal modified four-category LI-RADS scale (LR-1, definitely benign; LR-2, probably benign; LR-3, intermediate probability of malignancy; LR-4, probably hepatocellular carcinoma [HCC]; LR-5, definitely HCC; LR-M, probably malignant but not HCC specific; and LR-TIV, tumor in vein) was computed using intraclass correlation coefficients (ICCs). Agreement was also computed for dichotomized malignancy (LR-4, LR-5, LR-M, and LR-TIV), LR-5, and LR-M. Agreement was compared between research-versus-research reads and research-versus-clinical reads. Results The study population consisted of 484 patients (mean age, 62 years ± 10 [SD]; 156 women; 93 CT examinations, 391 MRI examinations). ICCs for ordinal LI-RADS, dichotomized malignancy, LR-5, and LR-M were 0.68 (95% CI: 0.61, 0.73), 0.63 (95% CI: 0.55, 0.70), 0.58 (95% CI: 0.50, 0.66), and 0.46 (95% CI: 0.31, 0.61) respectively. Research-versus-research reader agreement was higher than research-versus-clinical agreement for modified four-category LI-RADS (ICC, 0.68 vs 0.62, respectively; P = .03) and for dichotomized malignancy (ICC, 0.63 vs 0.53, respectively; P = .005), but not for LR-5 (P = .14) or LR-M (P = .94). Conclusion There was moderate agreement for LI-RADS version 2018 overall. For some comparisons, research-versus-research reader agreement was higher than research-versus-clinical reader agreement, indicating differences between the clinical and research environments that warrant further study. © RSNA, 2023 Supplemental material is available for this article. See also the editorials by Johnson and Galgano and Smith in this issue.

ACR Appropriateness Criteria® Right Upper Quadrant Pain: 2022 Update

Acute right upper quadrant pain is one of the most common presenting symptoms in hospital emergency departments, as well as outpatient settings. Although gallstone-related acute cholecystitis is a leading consideration in diagnosis, a myriad of extrabiliary sources including hepatic, pancreatic, gastroduodenal, and musculoskeletal should also be considered. This document focuses on the diagnostic accuracy of imaging studies performed specifically to evaluate acute right upper quadrant pain, with biliary etiologies including acute cholecystitis and its complications being the most common. An additional consideration of extrabiliary sources such as acute pancreatitis, peptic ulcer disease, ascending cholangitis, liver abscess, hepatitis, and painful liver neoplasms remain a diagnostic consideration in the right clinical setting. The use of radiographs, ultrasound, nuclear medicine, CT, and MRI for these indications are discussed. The ACR Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

MRI Quantification of Placebo Effect in Nonalcoholic Steatohepatitis Clinical Trials

Background Several early-phase clinical trials for the treatment of nonalcoholic steatohepatitis (NASH) use liver fat content as measured with the MRI-derived proton density fat fraction (PDFF) for a primary outcome. These trials have shown relative reductions in liver fat content with placebo treatment alone, a phenomenon termed "the placebo effect." This phenomenon confounds the results and limits generalizability to future trials. Purpose To quantify the effect of placebo treatment on change in the absolute PDFF value and to identify variables associated with this observed change. Materials and Methods This is a secondary analysis of prospectively collected data from seven early phase clinical trials that included participants with a diagnosis of NASH based on MRI and/or liver biopsy who received placebo treatment. The primary outcome was a greater than or equal to 30% relative reduction in PDFF after placebo treatment. Normalization of PDFF, relative change in alanine aminotransferase (ALT) level, and normalization of ALT level were also examined. An exploratory linear mixed-effects model was used to estimate an overall change in absolute PDFF and to explore parameters associated with this response. Results A total of 187 participants (median age, 52 years [IQR, 43-60 years]; 114 women) who received placebo treatment were evaluated. A greater than or equal to 30% relative reduction in baseline PDFF was seen in 20% of participants after 12 weeks of placebo treatment (10 of 49), 9% of participants after 16 weeks (two of 22), and 28% of participants after 24 weeks (34 of 122). A repeated-measures linear mixed-effects model estimated a decrease of 2.3 units (median relative reduction of 13%) in absolute PDFF values after 24 weeks of placebo treatment (95% CI: 3.2, 1.4; P < .001). Conclusion In this analysis of 187 participants, a clinically relevant decrease in PDFF was observed with placebo treatment. Based on the study model, assuming an absolute PDFF decrease of approximately 3 units (upper limit of 95% CI) to account for this "placebo effect" in sample size calculations for future clinical trials is suggested. Clinical trial registration nos. NCT01066364, NCT01766713, NCT01963845, NCT02443116, NCT02546609, NCT02316717, and NCT02442687 © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Yoon in this issue.

VICT2 Trait: Prognostic Alternative to Peritumoral Hepatobiliary Phase Hypointensity in HCC

Background Peritumoral hepatobiliary phase (HBP) hypointensity is an established prognostic imaging feature in hepatocellular carcinoma (HCC), often associated with microvascular invasion (MVI). Similar prognostic features are needed for non-HBP MRI. Purpose To propose a non-hepatobiliary-specific MRI tool with similar prognostic value to peritumoral HBP hypointensity. Materials and Methods From December 2011 to November 2021, consecutive patients with HCC who underwent preoperative contrast-enhanced MRI were retrospectively enrolled and followed up until recurrence. All MRI scans were reviewed by two blinded radiologists with 7 and 10 years of experiences with liver MRI. A scoring system based on non-hepatobiliary-specific features that highly correlated with peritumoral HBP hypointensity was identified in a stratified sampling-derived training set of the gadoxetate disodium (EOB) group by means of multivariable logistic regression, and its values to predict MVI and recurrence-free survival (RFS) were assessed. Results There were 660 patients (551 men; median age, 53 years; IQR, 45-61 years) enrolled. Peritumoral portal venous phase hypoenhancement (odds ratio [OR] = 8.8), incomplete "capsule" (OR = 3.3), corona enhancement (OR, 2.6), and peritumoral mild-moderate T2 hyperintensity (OR, 2.2) (all P < .001) were associated with peritumoral HBP hypointensity and constituted the "VICT2 trait" (test set area under the receiver operating characteristic curve = 0.84; 95% CI: 0.78, 0.90). For the EOB group, both peritumoral HBP hypointensity (OR for MVI = 2.5, P = .02; hazard ratio for RFS = 2.5, P < .001) and the VICT2 trait (OR for MVI = 5.1, P < .001; hazard ratio for RFS = 2.3, P < .001) were associated with MVI and RFS, despite a higher specificity of the VICT2 trait for MVI (89% vs 80%, P = .01). These values of the VICT2 trait were confirmed in the extracellular contrast agent group (OR for MVI = 4.0; hazard ratio for RFS = 1.7; both P < .001). Conclusion Based on four non-hepatobiliary-specific MRI features, the VICT2 trait was comparable to peritumoral hepatobiliary phase hypointensity in predicting microvascular invasion and postoperative recurrence of hepatocellular carcinoma. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Harmath in this issue.

Changes in abdominal adipose tissue depots assessed by MRI correlate with hepatic histologic improvement in non-alcoholic steatohepatitis

BACKGROUND & AIMS

Non-alcoholic steatohepatitis (NASH) is prevalent in adults with obesity and can progress to cirrhosis. In a secondary analysis of prospectively acquired data from the multicenter, randomized, placebo-controlled FLINT trial, we investigated the relationship between reduction in adipose tissue compartment volumes and hepatic histologic improvement.

METHODS

Adult participants in the FLINT trial with paired liver biopsies and abdominal MRI exams at baseline and end-of-treatment (72 weeks) were included (n = 76). Adipose tissue compartment volumes were obtained using MRI.

RESULTS

Treatment and placebo groups did not differ in baseline adipose tissue volumes, or in change in adipose tissue volumes longitudinally (p = 0.107 to 0.745). Deep subcutaneous adipose tissue (dSAT) and visceral adipose tissue volume reductions were associated with histologic improvement in NASH (i.e., NAS [non-alcoholic fatty liver disease activity score] reductions of ≥2 points, at least 1 point from lobular inflammation and hepatocellular ballooning, and no worsening of fibrosis) (p = 0.031, and 0.030, respectively). In a stepwise logistic regression procedure, which included demographics, treatment group, baseline histology, baseline and changes in adipose tissue volumes, MRI hepatic proton density fat fraction (PDFF), and serum aminotransferases as potential predictors, reductions in dSAT and PDFF were associated with histologic improvement in NASH (regression coefficient = -2.001 and -0.083, p = 0.044 and 0.033, respectively).

CONCLUSIONS

In adults with NASH in the FLINT trial, those with greater longitudinal reductions in dSAT and potentially visceral adipose tissue volumes showed greater hepatic histologic improvements, independent of reductions in hepatic PDFF.

CLINICAL TRIAL NUMBER

NCT01265498.

IMPACT AND IMPLICATIONS

Although central obesity has been identified as a risk factor for obesity-related disorders including insulin resistance and cardiovascular disease, the role of central obesity in non-alcoholic steatohepatitis (NASH) warrants further clarification. Our results highlight that a reduction in central obesity, specifically deep subcutaneous adipose tissue and visceral adipose tissue, may be related to histologic improvement in NASH. The findings from this analysis should increase awareness of the importance of lifestyle intervention in NASH for clinical researchers and clinicians. Future studies and clinical practice may design interventions that assess the reduction of deep subcutaneous adipose tissue and visceral adipose tissue as outcome measures, rather than simply weight reduction.

Evaluation of Frailty Measures and Short-term Outcomes After Lung Transplantation

BACKGROUND

Frailty, measured as a single construct, is associated variably with poor outcomes before and after lung transplantation. The usefulness of a comprehensive frailty assessment before transplantation is unknown.

RESEARCH QUESTION

How are multiple frailty constructs, including phenotypic and cumulative deficit models, muscle mass, exercise tolerance, and social vulnerabilities, measured before transplantation, associated with short-term outcomes after lung transplantation?

STUDY DESIGN AND METHODS

We conducted a retrospective cohort study of 515 lung recipients who underwent frailty assessments before transplantation, including the short physical performance battery (SPPB), transplant-specific frailty index (FI), 6-min walk distance (6MWD), thoracic sarcopenia, and social vulnerability indexes. We tested the association between frailty measures before transplantation and outcomes after transplantation using logistic regression to model 1-year survival and zero-inflated negative binomial regression to model hospital-free days (HFDs) in the first 90 days after transplantation. Adjustment covariates included age, sex, native lung disease, transplantation type, lung allocation score, BMI, and primary graft dysfunction.

RESULTS

Before transplantation, 51.3% of patients were frail by FI (FI ≥ 0.25) and no patients were frail by SPPB. In multivariate adjusted models that also included FI, SPPB, and 6MWD, greater frailty by FI, but not SPPB, was associated with fewer HFDs (-0.006 per 0.01 unit worsening; 95% CI, -0.01 to -0.002 per 0.01 unit worsening) among discharged patients. Greater SPPB deficits were associated with decreased odds of 1-year survival (OR, 0.51 per 1 unit worsening; 95% CI, 0.28-0.93 per 1 unit worsening). Correlation among frailty measurements overall was poor. No association was found between thoracic sarcopenia, 6MWD, or social vulnerability assessments and short-term outcomes after lung transplantation.

INTERPRETATION

Both phenotypic and cumulative deficit models measured before transplantation are associated with short-term outcomes after lung transplantation. Cumulative deficit measures of frailty may be more relevant in the first 90 days after transplantation, whereas phenotypic frailty may have a stronger association with 1-year survival.

A Faster Prostate MRI: Comparing a Novel Denoised, Single-Average T2 Sequence to the Conventional Multiaverage T2 Sequence Regarding Lesion Detection and PI-RADS Score Assessment

BACKGROUND

The T₂ w sequence is a standard component of a prostate MRI examination; however, it is time-consuming, requiring multiple signal averages to achieve acceptable image quality.

PURPOSE/HYPOTHESIS

To determine whether a denoised, single-average T₂ sequence (T₂ -R) is noninferior to the standard multiaverage T₂ sequence (T₂ -S) in terms of lesion detection and PI-RADS score assessment.

STUDY TYPE

Retrospective.

POPULATION

A total of 45 males (age range 60-75 years) who underwent clinically indicated prostate MRI examinations, 21 of whom had pathologically proven prostate cancer.

FIELD STRENGTH/SEQUENCE

A 3 T; T₂ w FSE, DWI with ADC maps, and dynamic contrast-enhanced images with color-coded perfusion maps. T₂ -R images were created from the raw data utilizing a single "average" with iterative denoising.

ASSESSMENT

Nine readers randomly assessed complete exams including T₂ -R and T₂ -S images in separate sessions. PI-RADS version 2.1 was used. All readers then compared the T₂ -R and T₂ -S images side by side to evaluate subjective preference. An additional detailed image quality assessment was performed by three senior level readers.

STATISTICAL TESTS

Generalized linear mixed effects models for differences in lesion detection, image quality features, and overall preference between T₂ -R and T₂ -S sequences. Intraclass correlation coefficients (ICC) were used to assess reader agreement for all comparisons. A significance threshold of P = 0.05 was used for all statistical tests.

RESULTS

There was no significant difference between sequences regarding identification of lesions with PI-RADS ≥3 (P = 0.10) or PI-RADS score (P = 0.77). Reader agreement was excellent for lesion identification (ICC = 0.84). There was no significant overall preference between the two sequences regarding image quality (P = 0.07, 95% CI: [-0.23, 0.01]). Reader agreement was good regarding sequence preference (ICC = 0.62).

DATA CONCLUSION

Use of single-average, denoised T₂ -weighted images was noninferior in prostate lesion detection or PI-RADS scoring when compared to standard multiaverage T₂ -weighted images.

EVIDENCE LEVEL

3.

TECHNICAL EFFICACY

Stage 3.

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.

Universal Liver Imaging Lexicon: Imaging Atlas for Research and Clinical Practice

The use of standardized terms in assessing and reporting disease processes has well-established benefits, such as clear communication between radiologists and other health care providers, improved diagnostic accuracy and reproducibility, and the enhancement and facilitation of research. Recently, the Liver Imaging Reporting and Data System (LI-RADS) Steering Committee released a universal liver imaging lexicon. The current version of the lexicon includes 81 vetted and precisely defined terms that are relevant to acquisition of images using all major liver imaging modalities and contrast agents, as well as lesion- and organ-level features. Most terms in the lexicon are applicable to all patients undergoing imaging of the liver, and only a minority of the terms are strictly intended to be used for patients with high risk factors for hepatocellular carcinoma. This pictorial atlas familiarizes readers with the liver imaging lexicon and includes discussion of general concepts, providing sample definitions, schematics, and clinical examples for a subset of the terms in the liver imaging lexicon. The authors discuss general, technical, and imaging feature terms used commonly in liver imaging, with the goal of illustrating their use for clinical and research applications. Work of the U.S. Government published under an exclusive license with the RSNA. Online supplemental material is available for this article.

Towards optimal deep fusion of imaging and clinical data via a model-based description of fusion quality

BACKGROUND

Due to intrinsic differences in data formatting, data structure, and underlying semantic information, the integration of imaging data with clinical data can be non-trivial. Optimal integration requires robust data fusion, that is, the process of integrating multiple data sources to produce more useful information than captured by individual data sources. Here, we introduce the concept of fusion quality for deep learning problems involving imaging and clinical data. We first provide a general theoretical framework and numerical validation of our technique. To demonstrate real-world applicability, we then apply our technique to optimize the fusion of CT imaging and hepatic blood markers to estimate portal venous hypertension, which is linked to prognosis in patients with cirrhosis of the liver.

PURPOSE

To develop a measurement method of optimal data fusion quality deep learning problems utilizing both imaging data and clinical data.

METHODS

Our approach is based on modeling the fully connected layer (FCL) of a convolutional neural network (CNN) as a potential function, whose distribution takes the form of the classical Gibbs measure. The features of the FCL are then modeled as random variables governed by state functions, which are interpreted as the different data sources to be fused. The probability density of each source, relative to the probability density of the FCL, represents a quantitative measure of source-bias. To minimize this source-bias and optimize CNN performance, we implement a vector-growing encoding scheme called positional encoding, where low-dimensional clinical data are transcribed into a rich feature space that complements high-dimensional imaging features. We first provide a numerical validation of our approach based on simulated Gaussian processes. We then applied our approach to patient data, where we optimized the fusion of CT images with blood markers to predict portal venous hypertension in patients with cirrhosis of the liver. This patient study was based on a modified ResNet-152 model that incorporates both images and blood markers as input. These two data sources were processed in parallel, fused into a single FCL, and optimized based on our fusion quality framework.

RESULTS

Numerical validation of our approach confirmed that the probability density function of a fused feature space converges to a source-specific probability density function when source data are improperly fused. Our numerical results demonstrate that this phenomenon can be quantified as a measure of fusion quality. On patient data, the fused model consisting of both imaging data and positionally encoded blood markers at the theoretically optimal fusion quality metric achieved an AUC of 0.74 and an accuracy of 0.71. This model was statistically better than the imaging-only model (AUC = 0.60; accuracy = 0.62), the blood marker-only model (AUC = 0.58; accuracy = 0.60), and a variety of purposely sub-optimized fusion models (AUC = 0.61-0.70; accuracy = 0.58-0.69).

CONCLUSIONS

We introduced the concept of data fusion quality for multi-source deep learning problems involving both imaging and clinical data. We provided a theoretical framework, numerical validation, and real-world application in abdominal radiology. Our data suggests that CT imaging and hepatic blood markers provide complementary diagnostic information when appropriately fused.

Leveraging Artificial Intelligence to Enhance Peer Review: Missed Liver Lesions on Computed Tomography Pulmonary Angiography

OBJECTIVE

To utilize artificial intelligence to facilitate peer review for detection of missed suspicious liver lesions (SLLs) on CT pulmonary angiography (CTPA).

METHODS

This retrospective study included one month of consecutive CTPAs from a multisite teleradiology practice. Visual classification (VC) software analyzed images for the presence (+) or absence (-) of SLLs (>1 cm, >20 HU). Separately, a natural language processing (NLP) algorithm evaluated corresponding reports for description (+) of an SLL (or lack thereof [-]). Studies containing possible missed SLL (VC+/NLP-) were reviewed by three abdominal radiologists in a two-step adjudication process to confirm if an SLL was missed by the interpreting radiologist. The number of VC+/NLP- cases, number of images needing radiologist review, and number of cases with confirmed missed SLL were recorded. Interobserver agreement for SLLs was calculated for the radiologist readers.

RESULTS

2,573 CTPAs were assessed, and 136 were classified as potentially containing missed SLLs (VC+/NLP-). After radiologist review, 13 cases with missed SLL were confirmed, representing 0.5% of analyzed CTs. Using AI, the ratio of CTs requiring review to missed SLL identified was 10:1; the ratio without the help of AI would be at least 66:1. Among the 136 cases reviewed by radiologists, interobserver agreement for SLLs was excellent (κ =0.91).

CONCLUSION

Artificial intelligence can accelerate meaningful peer review by rapidly assessing thousands of examinations to identify potentially clinically significant errors. Although radiologist involvement is necessary, the amount of effort required after initial AI screening is dramatically reduced.

Imaging Features of Premalignant Biliary Lesions and Predisposing Conditions with Pathologic Correlation

Biliary malignancies include those arising from the intrahepatic and extrahepatic bile ducts as well as the gallbladder and hepatopancreatic ampulla of Vater. The majority of intrahepatic and extrahepatic malignancies are cholangiocarcinomas (CCAs). They arise owing to a complex interplay between the patient-specific genetic background and multiple risk factors and may occur in the liver (intrahepatic CCA), hilum (perihilar CCA), or extrahepatic bile ducts (distal CCA). Biliary-type adenocarcinoma constitutes the most common histologic type of ampullary and gallbladder malignancies. Its prognosis is poor and surgical resection is considered curative, so early detection is key, with multimodality imaging playing a central role in making the diagnosis. There are several risk factors for biliary malignancy as well as predisposing conditions that increase the risk; this review highlights the pertinent imaging features of these entities with histopathologic correlation. The predisposing factors are broken down into three major categories: (a) congenital malformations such as choledochal cyst and pancreaticobiliary maljunction; (b) infectious or inflammatory conditions such as parasitic infections, hepatolithiasis, primary sclerosing cholangitis, and porcelain gallbladder; and (c) preinvasive epithelial neoplasms such as biliary intraepithelial neoplasm, intraductal papillary neoplasm of the bile duct, intra-ampullary papillary tubular neoplasm, and intracholecystic papillary neoplasm of the gallbladder. Recognizing the baseline features of these premalignant biliary entities and changes in their appearance over time that indicate the advent of malignancy in high-risk patients can lead to early diagnosis and potentially curative management. An invited commentary by Volpacchio is available online. Online supplemental material is available for this article. ^©RSNA, 2022.

Radiomics: a primer on high-throughput image phenotyping

Radiomics is a high-throughput approach to image phenotyping. It uses computer algorithms to extract and analyze a large number of quantitative features from radiological images. These radiomic features collectively describe unique patterns that can serve as digital fingerprints of disease. They may also capture imaging characteristics that are difficult or impossible to characterize by the human eye. The rapid development of this field is motivated by systems biology, facilitated by data analytics, and powered by artificial intelligence. Here, as part of Abdominal Radiology's special issue on Quantitative Imaging, we provide an introduction to the field of radiomics. The technique is formally introduced as an advanced application of data analytics, with illustrating examples in abdominal radiology. Artificial intelligence is then presented as the main driving force of radiomics, and common techniques are defined and briefly compared. The complete step-by-step process of radiomic phenotyping is then broken down into five key phases. Potential pitfalls of each phase are highlighted, and recommendations are provided to reduce sources of variation, non-reproducibility, and error associated with radiomics.

Modifying LI-RADS on Gadoxetate Disodium-Enhanced MRI: A Secondary Analysis of a Prospective Observational Study

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) is widely used for diagnosing hepatocellular carcinoma (HCC), however, with unsatisfactory sensitivity, complex ancillary features, and inadequate integration with gadoxetate disodium (EOB)-enhanced MRI.

PURPOSE

To modify LI-RADS (mLI-RADS) on EOB-MRI.

STUDY TYPE

Secondary analysis of a prospective observational study.

POPULATION

Between July 2015 and September 2018, 224 consecutive high-risk patients (median age, 51 years; range, 26-83; 180 men; training/testing sets: 169/55 patients) with 742 (median size, 13 mm; interquartile range, 7-27; 498 HCCs) LR-3/4/5 observations.

FIELD STRENGTH/SEQUENCE

3.0 T T₂ -weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar, and 3D T₁ -weighted gradient echo sequences.

ASSESSMENT

Three radiologists (with 5, 5, and 10 years of experience in liver MR imaging, respectively) blinded to the reference standard (histopathology or imaging follow-up) reviewed all MR images independently. In the training set, the optimal LI-RADS version 2018 (v2018) features selected by Random Forest analysis were used to develop mLI-RADS via decision tree analysis.

STATISTICAL TESTS

In an independent testing set, diagnostic performances of mLI-RADS, LI-RADS v2018, and the Korean Liver Cancer Association (KLCA) guidelines were computed using a generalized estimating equation model and compared with McNemar's test. A two-tailed P < 0.05 was statistically significant.

RESULTS

Five features (nonperipheral "washout," restricted diffusion, nonrim arterial phase hyperenhancement [APHE], mild-moderate T2 hyperintensity, and transitional phase hypointensity) constituted mLI-RADS, and mLR-5 was nonperipheral washout coupled with either nonrim APHE or restricted diffusion. In the testing set, mLI-RADS was significantly more sensitive (72%) and accurate (80%) than LI-RADS v2018 (sensitivity, 61%; accuracy 74%; both P < 0.001) and the KLCA guidelines (sensitivity, 64%; accuracy 74%; both P < 0.001), without sacrificing positive predictive value (mLI-RADS, 94%; LI-RADS v2018, 94%; KLCA guidelines, 92%).

DATA CONCLUSION

In high-risk patients, the EOB-MRI-based mLI-RADS was simpler and more sensitive for HCC than LI-RADS v2018 while maintaining high positive predictive value.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 2.

Aldafermin in patients with non-alcoholic steatohepatitis (ALPINE 2/3): a randomised, double-blind, placebo-controlled, phase 2b trial

BACKGROUND

Non-alcoholic steatohepatitis (NASH) is characterised by hepatic steatosis, inflammation, and injury, and is associated with an increased risk of liver transplantation and death. NASH affects more than 16 million people in the USA, and there is no approved therapy. The aim of this study was to evaluate the safety and efficacy of aldafermin, an engineered analogue of the gut hormone fibroblast growth factor 19 (FGF19).

METHODS

In this randomised, double-blind, placebo-controlled, phase 2b study (ALPINE 2/3) in patients with biopsy-confirmed NASH and stage 2 or 3 fibrosis, we randomly assigned patients stratified by fibrosis stage in a 1:1:1:1 ratio to receive placebo, aldafermin 0·3 mg, 1·0 mg, or 3·0 mg once daily for 24 weeks at 30 study sites in the USA. Patients, investigators, the funder, and all other staff, were masked to treatment assignment throughout the study. The primary endpoint was an improvement in liver fibrosis of at least one stage with no worsening of NASH at week 24. Analyses were done by intention-to-treat. This trial is registered with ClinicalTrials.gov, number NCT03912532, and has been completed.

FINDINGS

Between May 16, 2019, and Sept 4, 2020, 786 patients were screened, of whom 171 were randomly assigned to a treatment group and included in the intention-to-treat population: 43 in the 0·3 mg aldafermin group, 42 in the 1·0 mg group, 43 in the 3·0 mg group, and 43 in the placebo group. In total, 145 (85%) of patients completed treatment. At week 24, among patients with biopsies at both baseline and week 24, was seven (19%) of 36 patients in the placebo group, 11 (31%) of 36 in the 0·3 mg aldafermin group (difference 90% CI 12% [-9 to 33]; p=0·11), five (15%) of 34 patients in the 1·0 mg group (difference -5% [-24 to 13]; p=0·80), and 11 (30%) of 37 patients in the 3·0 mg group (difference 10% [-9 to 30]; p=0·12) had an improvement in liver fibrosis of at least one stage with no worsening of NASH, without meeting the prespecified significance for dose response (p=0·55). Adverse events were mostly mild or moderate in severity. Diarrhoea occurred in six (14%) of 43 patients in the placebo group, three (7%) of 43 patients in the 0·3 mg aldafermin group, five (12%) of 41 patients in the 1·0 mg group, and ten (23%) of 43 patients in the 3·0 mg group. Incidences of serious adverse events and discontinuations owing to adverse events were similar between groups.

INTERPRETATION

Aldafermin was generally well tolerated but did not produce a significant dose response on fibrosis improvement of at least one stage with no worsening of NASH, despite positive effects on a number of secondary endpoints. The findings of this trial may have implications for the design of future NASH trials.

FUNDING

NGM Biopharmaceuticals.

Predicting microvascular invasion in hepatocellular carcinoma: A dual-institution study on gadoxetate disodium-enhanced MRI

BACKGROUND & AIMS

Microvascular invasion (MVI) is an important risk factor in hepatocellular carcinoma (HCC), but its diagnosis mandates postoperative histopathologic analysis. We aimed to develop and externally validate a predictive scoring system for MVI.

METHODS

From July 2015 to November 2020, consecutive patients underwent surgery for HCC with preoperative gadoxetate disodium (EOB)-enhanced MRI was retrospectively enrolled. All MR images were reviewed independently by two radiologists who were blinded to the outcomes. In the training centre, a radio-clinical MVI score was developed via logistic regression analysis against pathology. In the testing centre, areas under the receiver operating curve (AUCs) of the MVI score and other previous MVI schemes were compared. Overall survival (OS) and recurrence-free survival (RFS) were analysed by the Kaplan-Meier method with the log-rank test.

RESULTS

A total of 417 patients were included, 195 (47%) with pathologically-confirmed MVI. The MVI score included: non-smooth tumour margin (odds ratio [OR] = 4.4), marked diffusion restriction (OR = 3.0), internal artery (OR = 3.0), hepatobiliary phase peritumoral hypointensity (OR = 2.5), tumour multifocality (OR = 1.6), and serum alpha-fetoprotein >400 ng/mL (OR = 2.5). AUCs for the MVI score were 0.879 (training) and 0.800 (testing), significantly higher than those for other MVI schemes (testing AUCs: 0.648-0.684). Patients with model-predicted MVI had significantly shorter OS (median 61.0 months vs not reached, P < .001) and RFS (median 13.0 months vs. 42.0 months, P < .001) than those without.

CONCLUSIONS

A preoperative MVI score integrating five EOB-MRI features and serum alpha-fetoprotein level could accurately predict MVI and postoperative survival in HCC. Therefore, this score may aid in individualized treatment decision making.

3D Pyramid Pooling Network for Abdominal MRI Series Classification

Recognizing and organizing different series in an MRI examination is important both for clinical review and research, but it is poorly addressed by the current generation of picture archiving and communication systems (PACSs) and post-processing workstations. In this paper, we study the problem of using deep convolutional neural networks for automatic classification of abdominal MRI series to one of many series types. Our contributions are three-fold. First, we created a large abdominal MRI dataset containing 3717 MRI series including 188,665 individual images, derived from liver examinations. 30 different series types are represented in this dataset. The dataset was annotated by consensus readings from two radiologists. Both the MRIs and the annotations were made publicly available. Second, we proposed a 3D pyramid pooling network, which can elegantly handle abdominal MRI series with varied sizes of each dimension, and achieved state-of-the-art classification performance. Third, we performed the first ever comparison between the algorithm and the radiologists on an additional dataset and had several meaningful findings.

Predicting Genomic Alterations of Phosphatidylinositol-3 Kinase Signaling in Hepatocellular Carcinoma: A Radiogenomics Study Based on Next-Generation Sequencing and Contrast-Enhanced CT

BACKGROUND

Exploring the genomic landscape of hepatocellular carcinoma (HCC) provides clues for therapeutic decision-making. Phosphatidylinositol-3 kinase (PI3K) signaling is one of the key pathways regulating HCC aggressiveness, and its genomic alterations have been correlated with sorafenib response. In this study, we aimed to predict somatic mutations of the PI3K signaling pathway in HCC samples through machine-learning-based radiomic analysis.

METHODS

HCC patients who underwent next-generation sequencing and preoperative contrast-enhanced CT were recruited from West China Hospital and The Cancer Genome Atlas for model training and validation, respectively. Radiomic features were extracted from volumes of interest (VOIs) covering the tumor (VOItumor) and peritumoral areas (5 mm [VOI5mm], 10 mm [VOI10mm], and 20 mm [VOI20mm] from tumor margin). Factor analysis, logistic regression analysis, least absolute shrinkage and selection operator, and random forest analysis were applied for feature selection and model construction. Model performance was characterized based on the area under the receiver operating characteristic curve (AUC).

RESULTS

A total of 132 HCC patients (mean age: 61.1 ± 14.7 years; 108 men) were enrolled. In the training set, the AUCs of radiomic signatures based on single CT phases were moderate (AUC 0.694-0.771). In the external validation set, the radiomic signature based on VOI10mm in arterial phase demonstrated the highest AUC (0.733) among all models. No improvement in model performance was achieved after adding the tumor radiomic features or manually assessed qualitative features.

CONCLUSIONS

Machine-learning-based radiomic analysis had potential for characterizing alterations of PI3K signaling in HCC and could help identify potential candidates for sorafenib treatment.

Impact of Reference Standard on CT, MRI, and Contrast-enhanced US LI-RADS Diagnosis of Hepatocellular Carcinoma: A Meta-Analysis

See also the editorial by Ronot in this issue. Online supplemental material is available for this article.

Data-Driven Modification of the LI-RADS Major Feature System on Gadoxetate Disodium-Enhanced MRI: Toward Better Sensitivity and Simplicity

BACKGROUND

The Liver Imaging Reporting and Data System (LI-RADS) is widely accepted as a reliable diagnostic scheme for hepatocellular carcinoma (HCC) in at-risk patients. However, its application is hampered by substantial complexity and suboptimal diagnostic sensitivity.

PURPOSE

To propose data-driven modifications to the LI-RADS version 2018 (v2018) major feature system (rLI-RADS) on gadoxetate disodium (EOB)-enhanced magnetic resonance imaging (MRI) to improve sensitivity and simplicity while maintaining high positive predictive value (PPV) for detecting HCC.

STUDY TYPE

Retrospective.

POPULATION

Two hundred and twenty-four consecutive at-risk patients (training dataset: 169, independent testing dataset: 55) with 742 LR-3 to LR-5 liver observations (HCC: N = 498 [67%]) were analyzed from a prospective observational registry collected between July 2015 and September 2018.

FIELD STRENGTH/SEQUENCE

3.0 T/T2-weighted fast spin-echo, diffusion-weighted spin-echo based echo-planar and three-dimensional (3D) T1-weighted gradient echo sequences.

ASSESSMENT

All images were evaluated by three independent abdominal radiologists who were blinded to all clinical, pathological, and follow-up information. Composite reference standards of either histopathology or imaging follow-up were used.

STATISTICAL TESTS

In the training dataset, LI-RADS v2018 major features were used to develop rLI-RADS based on their associated PPV for HCC. In an independent testing set, diagnostic performances of LI-RADS v2018 and rLI-RADS were computed using a generalized estimating equation model and compared with McNemar's test. A P value <0.05 was considered statistically significant.

RESULTS

The median (interquartile range) size of liver observations was 13 mm (7-27 mm). The diagnostic table for rLI-RADS encompassed 9 cells, as opposed to 16 cells for LI-RADS v2018. In the testing set, compared to LI-RADS v2018, rLI-RADS category 5 demonstrated a significantly superior sensitivity (76% vs. 61%) while maintaining comparably high PPV (92.5% vs. 94.1%, P = 0.126).

DATA CONCLUSION

Compared with LI-RADS v2018, rLI-RADS demonstrated improved simplicity and significantly superior diagnostic sensitivity for HCC in at-risk patients.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

CT/MRI and CEUS LI-RADS Major Features Association with Hepatocellular Carcinoma: Individual Patient Data Meta-Analysis

Background The Liver Imaging Reporting and Data System (LI-RADS) assigns a risk category for hepatocellular carcinoma (HCC) to imaging observations. Establishing the contributions of major features can inform the diagnostic algorithm. Purpose To perform a systematic review and individual patient data meta-analysis to establish the probability of HCC for each LI-RADS major feature using CT/MRI and contrast-enhanced US (CEUS) LI-RADS in patients at high risk for HCC. Materials and Methods Multiple databases (MEDLINE, Embase, Cochrane Central Register of Controlled Trials, and Scopus) were searched for studies from January 2014 to September 2019 that evaluated the accuracy of CT, MRI, and CEUS for HCC detection using LI-RADS (CT/MRI LI-RADS, versions 2014, 2017, and 2018; CEUS LI-RADS, versions 2016 and 2017). Data were centralized. Clustering was addressed at the study and patient levels using mixed models. Adjusted odds ratios (ORs) with 95% CIs were determined for each major feature using multivariable stepwise logistic regression. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2) (PROSPERO protocol: CRD42020164486). Results A total of 32 studies were included, with 1170 CT observations, 3341 MRI observations, and 853 CEUS observations. At multivariable analysis of CT/MRI LI-RADS, all major features were associated with HCC, except threshold growth (OR, 1.6; 95% CI: 0.7, 3.6; P = .07). Nonperipheral washout (OR, 13.2; 95% CI: 9.0, 19.2; P = .01) and nonrim arterial phase hyperenhancement (APHE) (OR, 10.3; 95% CI: 6.7, 15.6; P = .01) had stronger associations with HCC than enhancing capsule (OR, 2.4; 95% CI: 1.7, 3.5; P = .03). On CEUS images, APHE (OR, 7.3; 95% CI: 4.6, 11.5; P = .01), late and mild washout (OR, 4.1; 95% CI: 2.6, 6.6; P = .01), and size of at least 20 mm (OR, 1.6; 95% CI: 1.04, 2.5; P = .04) were associated with HCC. Twenty-five studies (78%) had high risk of bias due to reporting ambiguity or study design flaws. Conclusion Most Liver Imaging Reporting and Data System major features had different independent associations with hepatocellular carcinoma; for CT/MRI, arterial phase hyperenhancement and washout had the strongest associations, whereas threshold growth had no association. © RSNA, 2021 Online supplemental material is available for this article.

Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer

PURPOSE

We aimed to develop a noninvasive artificial intelligence (AI) model to diagnose signet-ring cell carcinoma (SRCC) of gastric cancer (GC) and identify patients with SRCC who could benefit from postoperative chemotherapy based on preoperative contrast-enhanced computed tomography (CT).

METHODS

A total of 855 GC patients with 855 single GCs were included, of which 249 patients were diagnosed as SRCC by histopathologic examinations. The AI model was generated with clinical, hand-crafted radiomic, and deep learning features. Model diagnostic performance was measured by area under the receiver operating characteristic curve (AUC), sensitivity, and specificity, while predictive performance was measured by Kaplan-Meier curves.

RESULTS

In the test cohort (n = 257), the AUC, sensitivity, and specificity of our AI model for diagnosing SRCC were 0.786 (95% CI: 0.721-0.845), 77.3%, and 69.2%, respectively. For the entire cohort, patients with AI-predicted high risk had a significantly shorter median OS compared with those with low risk (median overall survival (OS), 38.8 vs. 64.2 months, p = 0.009). Importantly, in pathologically-confirmed advanced SRCC patients, AI-predicted high-risk status was indicative of a shorter overall survival (median overall survival (OS), 31.0 vs. 54.4 months, p = 0.036) and marked chemotherapy resistance, whereas AI-predicted low-risk status had substantial chemotherapy benefit (median OS [without vs. with chemotherapy], 26.0 vs. not reached, p = 0.013).

CONCLUSIONS

The CT-based AI model demonstrated good performance for diagnosing SRCC, stratifying patient prognosis, and predicting chemotherapy responses. Advanced SRCC patients with AI-predicted low-risk status may benefit substantially from adjuvant chemotherapy. This article is protected by copyright. All rights reserved.

ACR Appropriateness Criteria® Epigastric Pain

Epigastric pain can have multiple etiologies including myocardial infarction, pancreatitis, acute aortic syndromes, gastroesophageal reflux disease, esophagitis, peptic ulcer disease, gastritis, duodenal ulcer disease, gastric cancer, and hiatal hernia. This document focuses on the scenarios in which epigastric pain is accompanied by symptoms such as heartburn, regurgitation, dysphagia, nausea, vomiting, and hematemesis, which raise suspicion for gastroesophageal reflux disease, esophagitis, peptic ulcer disease, gastritis, duodenal ulcer disease, gastric cancer, or hiatal hernia. Although endoscopy may be the test of choice for diagnosing these entities, patients may present with nonspecific or overlapping symptoms, necessitating the use of imaging prior to or instead of endoscopy. The utility of fluoroscopic imaging, CT, MRI, and FDG-PET for these indications are discussed. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.