Utility of pelvic CT in patients undergoing surveillance for hepatocellular carcinoma: A retrospective multi-institutional study.

OBJECTIVE: To determine the frequency, characteristics and clinical significance of incidental pelvic findings reported on abdominopelvic CT performed for hepatocellular carcinoma (HCC) surveillance in at-risk patients. MATERIAL AND METHODS: This two-center retrospective study received institutional review board approval with a waiver of informed consent. The radiologic reports of the CT exams performed 1/1/2010-2/28/2023 for HCC surveillance were reviewed. Exams were obtained with intravenous contrast material and included hepatic arterial and portal venous phases of the abdomen; images of the pelvis were acquired during the portal venous phase. Reported imaging findings and imaging-related recommendations either by the radiologists or the corresponding caregiver, if present, were retrospectively tabulated. The patient's medical records were reviewed to determine if there were any recommendations that were considered clinically important and culminated in any further interventions or treatments. RESULTS: 259 adults (1st center: mean age, 60 ± 11 years, 49% male and 2nd center: 56.26 ± 6.2 years, 48% male) at risk for HCC underwent 327 abdominopelvic CT exams for HCC surveillance at two centers. A total of 622 pelvic findings (mean, 2.2/ exam) were reported, including 131 bladder, 120 alimentary tract, 133 vascular, 51 gynecologic, 37 prostate, 33 lymph node, 27 inguinal, 44 peritoneal, and 46 skeletal. 52 of 622 reported findings (8.3%) were associated with actionable recommendations. 24 of the 52 actionable recommendations/clinical suggestions were implemented as follows: five complimentary imaging, ten additional laboratory tests, and nine non-imaging recommendations. Of note, only eight applied recommendations culminated in a clinical outcome, which included four urinary tract infection treatments. CONCLUSION: Pelvic CT findings were associated with a clinical benefit to the patient in 1.3% of exams. These results suggest that pelvic imaging should be omitted from CT-based HCC surveillance. CLINICAL RELEVANCE: Without compromising valuable information, patients undergoing HCC surveillance-CT may not require additional pelvic coverage.

Performance of LI-RADS category 5 vs combined categories 4 and 5: a systemic review and meta-analysis.

OBJECTIVE: Computed tomography (CT)/magnetic resonance imaging (MRI) Liver Imaging Reporting and Data System (LI-RADS, LR) category 5 has high specificity and modest sensitivity for diagnosis of hepatocellular carcinoma (HCC). The purpose of this study was to compare the diagnostic performance of LR-5 vs combined LR-4 and LR-5 (LR-4/5) for HCC diagnosis. METHODS: MEDLINE and EMBASE databases through January 03, 2023 were searched for studies reporting the performance of LR-5 and combined LR-4/5 for HCC diagnosis, using CT/MRI LI-RADS version 2014, 2017, or 2018. A bivariate random-effects model was used to calculate the pooled per-observation diagnostic performance. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material. RESULTS: Sixty-nine studies (15,108 observations, 9928 (65.7%) HCCs) were included. Compared to LR-5, combined LR-4/5 showed significantly higher pooled sensitivity (83.0% (95% CI [80.3-85.8%]) vs 65.7% (95% CI [62.4-69.1%]); p < 0.001), lower pooled specificity (75.0% (95% CI [70.5-79.6%]) vs 91.7% (95% CI [90.2-93.1%]); p < 0.001), lower pooled positive likelihood ratio (3.60 (95% CI [3.06-4.23]) vs 6.18 (95% CI [5.35-7.14]); p < 0.001), and lower pooled negative likelihood ratio (0.22 (95% CI [0.19-0.25]) vs 0.38 (95% CI [0.35-0.41]) vs; p < 0.001). Similar results were seen in all subgroups. CONCLUSIONS: Our meta-analysis showed that combining LR-4 and LR-5 would increase sensitivity but decrease specificity, positive likelihood ratio, and negative likelihood ratio. These findings may inform management guidelines and individualized management. CLINICAL RELEVANCE STATEMENT: This meta-analysis estimated the magnitude of changes in the sensitivity and specificity of imaging criteria when LI-RADS categories 4 and 5 were combined; these findings can inform management guidelines and individualized management. KEY POINTS: There is no single worldwide reporting system for liver imaging, partly due to regional needs. Combining LI-RADS categories 4 and 5 increased sensitivity and decreased specificity and positive and negative likelihood ratios. Changes in the sensitivity and specificity of imaging criteria can inform management guidelines and individualized management.

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

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

Artificial intelligence in liver cancer research: a scientometrics analysis of trends and topics.

Background and aims: With the rapid growth of artificial intelligence (AI) applications in various fields, understanding its impact on liver cancer research is paramount. This scientometrics project aims to investigate publication trends and topics in AI-related publications in liver cancer. Materials and Methods: We employed a search strategy to identify AI-related publications in liver cancer using Scopus database. We analyzed the number of publications, author affiliations, and journals that publish AI-related publications in liver cancer. Finally, the publications were grouped based on intended application. Results: We identified 3950 eligible publications (2695 articles, 366 reviews, and 889 other document types) from 1968 to August 3, 2023. There was a 12.7-fold increase in AI-related publications from 2013 to 2022. By comparison, the number of total publications on liver cancer increased by 1.7-fold. Our analysis revealed a significant shift in trends of AI-related publications on liver cancer in 2019. We also found a statistically significant consistent increase in numbers of AI-related publications over time (tau = 0.756, p < 0.0001). Eight (53%) of the top 15 journals with the most publications were radiology journals. The largest number of publications were from China (n=1156), the US (n=719), and Germany (n=236). The three most common publication categories were "medical image analysis for diagnosis" (37%), "diagnostic or prognostic biomarkers modeling & bioinformatics" (19%), and "genomic or molecular analysis" (18%). Conclusion: Our study reveals increasing interest in AI for liver cancer research, evidenced by a 12.7-fold growth in related publications over the past decade. A common application of AI is in medical imaging analysis for various purposes. China, the US, and Germany are leading contributors.

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.

MASH Resolution Index: development and validation of a non-invasive score to detect histological resolution of MASH.

BACKGROUND: Dynamic changes in non-invasive tests, such as changes in alanine aminotransferase (ALT) and MRI proton-density-fat-fraction (MRI-PDFF), may help to detect metabolic dysfunction-associated steatohepatitis (MASH) resolution, but a combination of non-invasive tests may be more accurate than either alone. We developed a novel non-invasive score, the MASH Resolution Index, to detect the histological resolution of MASH. METHODS: This study included a derivation cohort of 95 well-characterised adult participants (67% female) with biopsy-confirmed MASH who underwent contemporaneous laboratory testing, MRI-PDFF and liver biopsy at two time points. The primary objective was to develop a non-invasive score to detect MASH resolution with no worsening of fibrosis. The most predictive logistic regression model was selected based on the highest area under the receiver operating curve (AUC), and the lowest Akaike information criterion and Bayesian information criterion. The model was then externally validated in a distinct cohort of 163 participants with MASH from a clinical trial. RESULTS: The median (IQR) age and body mass index were 55 (45-62) years and 32.0 (30-37) kg/m2, respectively, in the derivation cohort. The most accurate model (MASH Resolution Index) included MRI-PDFF, ALT and aspartate aminotransferase. The index had an AUC of 0.81 (95% CI 0.69 to 0.93) for detecting MASH resolution in the derivation cohort. The score calibrated well and performed robustly in a distinct external validation cohort (AUC 0.83, 95% CI 0.76 to 0.91), and outperformed changes in ALT and MRI-PDFF. CONCLUSION: The MASH Resolution Index may be a useful score to non-invasively identify MASH resolution.

Liver Imaging Reporting and Data System version 2018 category 5 for diagnosing hepatocellular carcinoma: an updated meta-analysis.

OBJECTIVE: We performed an updated meta-analysis to determine the diagnostic performance of Liver Imaging Reporting and Data System (LI-RADS, LR) 5 category for hepatocellular carcinoma (HCC) using LI-RADS version 2018 (v2018), and to evaluate differences by imaging modalities and type of MRI contrast material. METHODS: The MEDLINE and Embase databases were searched for studies reporting the performance of LR-5 using v2018 for diagnosing HCC. A bivariate random-effects model was used to calculate the pooled per-observation sensitivity and specificity. Subgroup analysis was performed based on imaging modalities and type of MRI contrast material. RESULTS: Forty-eight studies qualified for the meta-analysis, comprising 9031 patients, 10,547 observations, and 7216 HCCs. The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC were 66% (95% CI, 61-70%) and 91% (95% CI, 89-93%), respectively. In the subgroup analysis, MRI with extracellular agent (ECA-MRI) showed significantly higher pooled sensitivity (77% [95% CI, 70-82%]) than CT (66% [95% CI, 58-73%]; p = 0.023) or MRI with gadoxetate (Gx-MRI) (65% [95% CI, 60-70%]; p = 0.001), but there was no significant difference between ECA-MRI and MRI with gadobenate (gadobenate-MRI) (73% [95% CI, 61-82%]; p = 0.495). Pooled specificities were 88% (95% CI, 80-93%) for CT, 92% (95% CI, 86-95%) for ECA-MRI, 93% (95% CI, 91-95%) for Gx-MRI, and 91% (95% CI, 84-95%) for gadobenate-MRI without significant differences (p = 0.084-0.803). CONCLUSIONS: LI-RADS v2018 LR-5 provides high specificity for HCC diagnosis regardless of modality or contrast material, while ECA-MRI showed higher sensitivity than CT or Gx-MRI. CLINICAL RELEVANCE STATEMENT: Refinement of the criteria for improving sensitivity while maintaining high specificity of LR-5 for HCC diagnosis may be an essential future direction. KEY POINTS: • The pooled per-observation sensitivity and specificity of LR-5 for diagnosing HCC using LI-RADSv2018 were 66% and 91%, respectively. • ECA-MRI showed higher sensitivity than CT (77% vs 66%, p = 0.023) or Gx-MRI (77% vs 65%, p = 0.001). • LI-RADS v2018 LR-5 provides high specificity (88-93%) for HCC diagnosis regardless of modality or contrast material type.

Marked difference in liver fat measured by histology vs. magnetic resonance-proton density fat fraction: A meta-analysis.

Background & Aims: Pathologists quantify liver steatosis as the fraction of lipid droplet-containing hepatocytes out of all hepatocytes, whereas the magnetic resonance-determined proton density fat fraction (PDFF) reflects the tissue triacylglycerol concentration. We investigated the linearity, agreement, and correspondence thresholds between histological steatosis and PDFF across the full clinical spectrum of liver fat content associated with non-alcoholic fatty liver disease. Methods: Using individual patient-level measurements, we conducted a systematic review and meta-analysis of studies comparing histological steatosis with PDFF determined by magnetic resonance spectroscopy or imaging in adults with suspected non-alcoholic fatty liver disease. Linearity was assessed by meta-analysis of correlation coefficients and by linear mixed modelling of pooled data, agreement by Bland-Altman analysis, and thresholds by receiver operating characteristic analysis. To explain observed differences between the methods, we used RNA-seq to determine the fraction of hepatocytes in human liver biopsies. Results: Eligible studies numbered 9 (N = 597). The relationship between PDFF and histology was predominantly linear (r = 0.85 [95% CI, 0.80-0.89]), and their values approximately coincided at 5% steatosis. Above 5% and towards higher levels of steatosis, absolute values of the methods diverged markedly, with histology exceeding PDFF by up to 3.4-fold. On average, 100% histological steatosis corresponded to a PDFF of 33.0% (29.5-36.7%). Targeting at a specificity of 90%, optimal PDFF thresholds to predict histological steatosis grades were ≥5.75% for ≥S1, ≥15.50% for ≥S2, and ≥21.35% for S3. Hepatocytes comprised 58 ± 5% of liver cells, which may partly explain the lower values of PDFF vs. histology. Conclusions: Histological steatosis and PDFF have non-perfect linearity and fundamentally different scales of measurement. Liver fat values obtained using these methods may be rendered comparable by conversion equations or threshold values. Impact and implications: Magnetic resonance-proton density fat fraction (PDFF) is increasingly being used to measure liver fat in place of the invasive liver biopsy. Understanding the relationship between PDFF and histological steatosis fraction is important for preventing misjudgement of clinical status or treatment effects in patient care. Our analysis revealed that histological steatosis fraction is often significantly higher than PDFF, and their association varies across the spectrum of fatty liver severity. These findings are particularly important for physicians and clinical researchers, who may use these data to interpret PDFF measurements in the context of histologically evaluated liver fat content.

Cost-Effectiveness Analysis of Hepatocellular Carcinoma Surveillance in Nonalcoholic Fatty Liver Disease Cirrhosis Using US Visualization Score C-Triggered Abbreviated MRI.

INTRODUCTION: Ultrasound (US) is associated with severe visualization limitations (US Liver Imaging Reporting and Data System visualization score C) in one-third of patients with nonalcoholic fatty liver disease (NAFLD) cirrhosis undergoing hepatocellular carcinoma (HCC) screening. Data suggest abbreviated MRI (aMRI) may improve HCC screening efficacy. This study analyzed the cost-effectiveness of HCC screening strategies, including an US visualization score-based approach with aMRI, in patients with NAFLD cirrhosis. METHODS: We constructed a Markov model simulating adults with compensated NAFLD cirrhosis in the United States undergoing HCC screening, comparing strategies of US plus visualization score, US alone, or no surveillance. We modeled aMRI in patients with visualization score C and negative US, while patients with scores A/B did US alone. We performed a sensitivity analysis comparing US plus visualization score with US plus alpha fetoprotein or no surveillance. The primary outcome was the incremental cost-effectiveness ratio (ICER), with a willingness-to-pay threshold of $100,000 per quality-adjusted life-year. Sensitivity analyses were performed for all variables. RESULTS: US plus visualization score was the most cost-effective strategy, with an ICER of $59,005 relative to no surveillance. The ICER for US alone to US plus visualization score was $822,500. On sensitivity analysis, screening using US plus visualization score remained preferred across several parameters. Even with alpha fetoprotein added to US, the US plus visualization score strategy remained cost-effective, with an ICER of $62,799 compared with no surveillance. DISCUSSION: HCC surveillance using US visualization score-based approach, using aMRI for visualization score C, seems to be the most cost-effective strategy in patients with NAFLD cirrhosis.

Repeatability of MRI Biomarkers in Nonalcoholic Fatty Liver Disease: The NIMBLE Consortium.

Background There is a need for reliable noninvasive methods for diagnosing and monitoring nonalcoholic fatty liver disease (NAFLD). Thus, the multidisciplinary Non-invasive Biomarkers of Metabolic Liver disease (NIMBLE) consortium was formed to identify and advance the regulatory qualification of NAFLD imaging biomarkers. Purpose To determine the different-day same-scanner repeatability coefficient of liver MRI biomarkers in patients with NAFLD at risk for steatohepatitis. Materials and Methods NIMBLE 1.2 is a prospective, observational, single-center short-term cross-sectional study (October 2021 to June 2022) in adults with NAFLD across a spectrum of low, intermediate, and high likelihood of advanced fibrosis as determined according to the fibrosis based on four factors (FIB-4) index. Participants underwent up to seven MRI examinations across two visits less than or equal to 7 days apart. Standardized imaging protocols were implemented with six MRI scanners from three vendors at both 1.5 T and 3 T, with central analysis of the data performed by an independent reading center (University of California, San Diego). Trained analysts, who were blinded to clinical data, measured the MRI proton density fat fraction (PDFF), liver stiffness at MR elastography (MRE), and visceral adipose tissue (VAT) for each participant. Point estimates and CIs were calculated using χ2 distribution and statistical modeling for pooled repeatability measures. Results A total of 17 participants (mean age, 58 years ± 8.5 [SD]; 10 female) were included, of which seven (41.2%), six (35.3%), and four (23.5%) participants had a low, intermediate, or high likelihood of advanced fibrosis, respectively. The different-day same-scanner mean measurements were 13%-14% for PDFF, 6.6 L for VAT, and 3.15 kPa for two-dimensional MRE stiffness. The different-day same-scanner repeatability coefficients were 0.22 L (95% CI: 0.17, 0.29) for VAT, 0.75 kPa (95% CI: 0.6, 0.99) for MRE stiffness, 1.19% (95% CI: 0.96, 1.61) for MRI PDFF using magnitude reconstruction, 1.56% (95% CI: 1.26, 2.07) for MRI PDFF using complex reconstruction, and 19.7% (95% CI: 15.8, 26.2) for three-dimensional MRE shear modulus. Conclusion This preliminary study suggests that thresholds of 1.2%-1.6%, 0.22 L, and 0.75 kPa for MRI PDFF, VAT, and MRE, respectively, should be used to discern measurement error from real change in patients with NAFLD. ClinicalTrials.gov registration no. NCT05081427 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Kozaka and Matsui in this issue.

Diagnostic performance of circulating biomarkers for non-alcoholic steatohepatitis.

There are no approved diagnostic biomarkers for at-risk non-alcoholic steatohepatitis (NASH), defined by the presence of NASH, high histological activity and fibrosis stage ≥2, which is associated with higher incidence of liver-related events and mortality. FNIH-NIMBLE is a multi-stakeholder project to support regulatory approval of NASH-related biomarkers. The diagnostic performance of five blood-based panels was evaluated in an observational (NASH CRN DB2) cohort (n = 1,073) with full spectrum of non-alcoholic fatty liver disease (NAFLD). The panels were intended to diagnose at-risk NASH (NIS4), presence of NASH (OWLiver) or fibrosis stages >2, >3 or 4 (enhanced liver fibrosis (ELF) test, PROC3 and FibroMeter VCTE). The prespecified performance metric was an area under the receiver operating characteristic curve (AUROC) ≥0.7 and superiority over alanine aminotransferase for disease activity and the FIB-4 test for fibrosis severity. Multiple biomarkers met these metrics. NIS4 had an AUROC of 0.81 (95% confidence interval: 0.78-0.84) for at-risk NASH. The AUROCs of the ELF test, PROC3 and FibroMeterVCTE for clinically significant fibrosis (≥stage 2), advanced fibrosis (≥stage 3) or cirrhosis (stage 4), respectively, were all ≥0.8. ELF and FibroMeter VCTE outperformed FIB-4 for all fibrosis endpoints. These data represent a milestone toward qualification of several biomarker panels for at-risk NASH and also fibrosis severity in individuals with NAFLD.

Prevalence of different LI-RADS v2018 categories in high-risk patients undergoing CT- or MRI-based screening for hepatocellular carcinoma.

PURPOSE: To estimate the prevalence of Liver Imaging Reporting and Data System (LI-RADS, LR) v2018 categories reported on CT or MRI performed for hepatocellular carcinoma (HCC) screening. MATERIALS AND METHODS: This retrospective study included all reports for CT and MRI exams performed for HCC screening patients between 8/2018 and 4/2020. Patients with ultrasound, CT, or MRI of the abdomen within two years of the index exam were excluded. From each radiology report, we extracted number of reported liver observations, and LI-RADS v2018 category for each observation. RESULTS: There were 329 patients (170 [52%] male, mean age 59 years [SD 12]), of whom 177 (54%) had MRI with gadoxetate, 72 (22%) had MRI with extracellular contrast, 7 (2%) had MRI with unspecified contrast, and 73 (22%) had CT. Of 329 patients, 199 (60%) had no reported observations; 130 patients had 166 reported observations: 114 (68.7%) LR-1, 8 (4.8%) LR-2, 21 (12.6%) LR-3, 6 (3.6%) LR-4, 13 (7.8%) LR-5, 3 (1.8%) LR-M, and 1 (0.6%) LR-TIV. Of 114 LR-1 observations, 78 (68%) were cysts, 17 (15%) were hemangiomas, 12 (11%) were vascular shunts, 3 (3%) were focal nodular hyperplasia, 2 (2%) were siderotic nodules, 1 (1%) was a lipoma, and 1 (1%) was biliary hamartoma. There were 23 observations with probably or definitely malignant categories (LR-4, LR-5, LR-M or LR- TIV), reported in 20/329 (6%) of patients. CONCLUSION: In a cohort of at-risk patients undergoing contrast-enhanced CT/MRI for HCC screening, 60% of had no liver observations, and 6 % had probably or definitely malignant observations. IMPLICATIONS FOR PATIENT CARE: The prevalence of LI-RADS v2018 categories on CT or MR exams used for HCC screening can help develop screening criteria and assess cost-effectiveness of surveillance strategies with CT and MRI.

Multi-Modality, Multi-Dimensional Characterization of Pediatric Non-Alcoholic Fatty Liver Disease.

Non-alcoholic fatty liver disease is a multifaceted disease that progresses through multiple phases; it involves metabolic as well as structural changes. These alterations can be measured directly or indirectly through blood, non-invasive imaging, and/or tissue analyses. While some studies have evaluated the correlations between two sets of measurements (e.g., histopathology with cross-sectional imaging or blood biomarkers), the interrelationships, if any, among histopathology, clinical blood profiles, cross-sectional imaging, and metabolomics in a pediatric cohort remain unknown. We created a multiparametric clinical MRI-histopathologic NMR network map of pediatric NAFLD through multimodal correlation networks, in order to gain insight into how these different sets of measurements are related. We found that leptin and other blood markers were correlated with many other measurements; however, upon filtering out the blood biomarkers, the network was decomposed into three independent hubs centered around histopathological features, each with associated MRI and plasma metabolites. These multi-modality maps could serve as a framework for characterizing disease status and progression and could potentially guide medical interventions.

Hepatocellular carcinoma surveillance - utilization, barriers and the impact of changing aetiology.

Hepatocellular carcinoma (HCC) is the third leading cause of cancer death worldwide. Surveillance for HCC is critical for early detection and treatment, but fewer than one-quarter of individuals at risk of HCC undergo surveillance. Multiple failures across the screening process contribute to the underutilization of surveillance, including limited disease awareness among patients and health-care providers, knowledge gaps, and difficulty recognizing patients who are at risk. Non-alcoholic fatty liver disease and alcohol-associated liver disease are the fastest-rising causes of HCC-related death worldwide and are associated with unique barriers to surveillance. In particular, more than one-third of patients with HCC related to non-alcoholic fatty liver disease do not have cirrhosis and therefore lack a routine indication for HCC surveillance on the basis of current practice guidelines. Semi-annual abdominal ultrasound with measurement of α-fetoprotein levels is recommended for HCC surveillance, but the sensitivity of this approach for early HCC is limited, especially for patients with cirrhosis or obesity. In this Review, we discuss the current status of HCC surveillance and the remaining challenges, including the changing aetiology of liver disease. We also discuss strategies to improve the utilization and quality of surveillance for HCC.

Alzheimer Disease Pathology and Neurodegeneration in Midlife Obesity: A Pilot Study.

Obesity and excess adiposity at midlife are risk factors for Alzheimer disease (AD). Visceral fat is known to be associated with insulin resistance and a pro-inflammatory state, the two mechanisms involved in AD pathology. We assessed the association of obesity, MRI-determined abdominal adipose tissue volumes, and insulin resistance with PET-determined amyloid and tau uptake in default mode network areas, and MRI-determined brain volume and cortical thickness in AD cortical signature in the cognitively normal midlife population. Thirty-two middle-aged (age: 51.27±6.12 years, 15 males, body mass index (BMI): 32.28±6.39 kg/m2) cognitively normal participants, underwent bloodwork, brain and abdominal MRI, and amyloid and tau PET scan. Visceral and subcutaneous adipose tissue (VAT, SAT) were semi-automatically segmented using VOXel Analysis Suite (Voxa). FreeSurfer was used to automatically segment brain regions using a probabilistic atlas. PET scans were acquired using [11C]PiB and AV-1451 tracers and were analyzed using PET unified pipeline. The association of brain volumes, cortical thicknesses, and PiB and AV-1451 standardized uptake value ratios (SUVRs) with BMI, VAT/SAT ratio, and insulin resistance were assessed using Spearman's partial correlation. VAT/SAT ratio was associated significantly with PiB SUVRs in the right precuneus cortex (p=0.034) overall, controlling for sex. This association was significant only in males (p=0.044), not females (p=0.166). Higher VAT/SAT ratio and PiB SUVRs in the right precuneus cortex were associated with lower cortical thickness in AD-signature areas predominantly including bilateral temporal cortices, parahippocampal, medial orbitofrontal, and cingulate cortices, with age and sex as covariates. Also, higher BMI and insulin resistance were associated with lower cortical thickness in bilateral temporal poles. In midlife cognitively normal adults, we demonstrated higher amyloid pathology in the right precuneus cortex in individuals with a higher VAT/SAT ratio, a marker of visceral obesity, along with a lower cortical thickness in AD-signature areas associated with higher visceral obesity, insulin resistance, and amyloid pathology.

Imaging Findings in Cirrhotic Liver: Pearls and Pitfalls for Diagnosis of Focal Benign and Malignant Lesions.

Cirrhosis is the end stage of chronic liver disease and causes architectural distortion and perfusional anomalies. It is a major risk factor for developing hepatocellular carcinoma (HCC). Common disease entities in noncirrhotic livers, such as hemangiomas, can be rare in cirrhotic livers, and benign entities such as confluent hepatic fibrosis and focal nodular hyperplasia-like lesions may mimic the appearance of malignancies,. HCC usually has typical imaging characteristics, such as the major features established by the Liver Imaging Reporting and Data System. However, HCC can also have a spectrum of atypical or uncommon appearances, such as cystic HCC, hypovascular HCC, or macroscopic fat-containing HCC. HCCs with certain genetic mutations such as CTNNB-1-mutated HCC can harbor unique imaging features not seen in other types of HCC. In addition, malignancies that are less common than HCC, such as cholangiocarcinoma and metastases, which can be difficult to differentiate, can still occur in cirrhotic livers. Atypical imaging features of benign and malignant lesions can be challenging to accurately diagnose. Therefore, familiarity with these features and an understanding of the prevalence of disease entities in cirrhotic livers are key in the daily practice of radiologists for evaluation of cirrhotic livers. The authors illustrate the typical and atypical features of benign and malignant lesions in cirrhosis and discuss the technical pitfalls and unique advantages associated with various imaging modalities in assessing cirrhotic livers, including noncontrast and contrast-enhanced US, CT, and MRI. Work of the U.S. Government published under an exclusive license with the RSNA. Quiz questions for this article are available in the supplemental material.

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

BACKGROUND. The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon method to calculate signal fat fraction (FF) from conventional T1-weighted in- and opposed-phase (IOP) images, although signal FF is prone to biases, leading to inaccurate quantification. OBJECTIVE. The purpose of this study was to compare hepatic fat quantification by use of PDFF inferred from conventional T1-weighted IOP images and deep-learning convolutional neural networks (CNNs) with quantification by use of two-point Dixon signal FF with CSE-MRI PDFF as the reference standard. METHODS. This study entailed retrospective analysis of data from 292 participants (203 women, 89 men; mean age, 53.7 ± 12.0 [SD] years) enrolled at two sites from September 1, 2017, to December 18, 2019, in the Strong Heart Family Study (a prospective population-based study of American Indian communities). Participants underwent liver MRI (site A, 3 T; site B, 1.5 T) including T1-weighted IOP MRI and CSE-MRI (used to reconstruct CSE PDFF and CSE R2* maps). With CSE PDFF as reference, a CNN was trained in a random sample of 218 (75%) participants to infer voxel-by-voxel PDFF maps from T1-weighted IOP images; testing was performed in the other 74 (25%) participants. Parametric values from the entire liver were automatically extracted. Per-participant median CNN-inferred PDFF and median two-point Dixon signal FF were compared with reference median CSE-MRI PDFF by means of linear regression analysis, intraclass correlation coefficient (ICC), and Bland-Altman analysis. The code is publicly available at github.com/kang927/CNN-inference-of-PDFF-from-T1w-IOP-MR. RESULTS. In the 74 test-set participants, reference CSE PDFF ranged from 1% to 32% (mean, 11.3% ± 8.3% [SD]); reference CSE R2* ranged from 31 to 457 seconds-1 (mean, 62.4 ± 67.3 seconds-1 [SD]). Agreement metrics with reference to CSE PDFF for CNN-inferred PDFF were ICC = 0.99, bias = -0.19%, 95% limits of agreement (LoA) = (-2.80%, 2.71%) and for two-point Dixon signal FF were ICC = 0.93, bias = -1.11%, LoA = (-7.54%, 5.33%). CONCLUSION. Agreement with reference CSE PDFF was better for CNN-inferred PDFF from conventional T1-weighted IOP images than for two-point Dixon signal FF. Further investigation is needed in individuals with moderate-to-severe iron overload. CLINICAL IMPACT. Measurement of CNN-inferred PDFF from widely available T1-weighted IOP images may facilitate adoption of hepatic PDFF as a quantitative bio-marker for liver fat assessment, expanding opportunities to screen for hepatic steatosis and nonalcoholic fatty liver disease.