Banff 2022 Liver Group Meeting report: Monitoring long-term allograft health.

The Banff Working Group on Liver Allograft Pathology met in September 2022. Participants included hepatologists, surgeons, pathologists, immunologists, and histocompatibility specialists. Presentations and discussions focused on the evaluation of long-term allograft health, including noninvasive and tissue monitoring, immunosuppression optimization, and long-term structural changes. Potential revision of the rejection classification scheme to better accommodate and communicate late T cell-mediated rejection patterns and related structural changes, such as nodular regenerative hyperplasia, were discussed. Improved stratification of long-term maintenance immunosuppression to match the heterogeneity of patient settings will be central to improving long-term patient survival. Such personalized therapeutics are in turn contingent on a better understanding and monitoring of allograft status within a rational decision-making approach, likely to be facilitated in implementation with emerging decision-support tools. Proposed revisions to rejection classification emerging from the meeting include the incorporation of interface hepatitis and fibrosis staging. These will be opened to online testing, modified accordingly, and subject to consensus discussion leading up to the next Banff conference.

Prediction of the histopathologic findings of intrahepatic cholangiocarcinoma: qualitative and quantitative assessment of diffusion-weighted imaging.

OBJECTIVE: To correlate qualitative and quantitative diffusion weighted imaging (DWI) characteristics of intrahepatic cholangiocarcinoma (ICC) with histopathologic tumour grade and fibrosis content. METHODS: Fifty-one patients (21M/30F; mean age 61y) with ICC and MRI including DWI were included in this IRB-approved multicentre retrospective study. Qualitative tumour features were assessed. Tumour apparent diffusion coefficient (ADC) mean, minimum, and normalized (nADCliver) values were computed. Tumour grade [well(G1), moderately(G2), or poorly differentiated(G3)] and tumour fibrosis content [minimal(1), moderate(2), or abundant(3)] were categorized pathologically. Imaging findings and ADC values were compared with pathologic measures. Utility of ADC values for predicting tumour grade was assessed using ROC analysis. RESULTS: 51 ICCs (mean size 6.5±1.1 cm) were assessed. 33/51(64%) of ICCs demonstrated diffuse hyperintensity and 15/51(29%) demonstrated target appearance on DWI. Infiltrative morphology (p=0.02) and tumour size (p=0.04) were associated with G3. ADCmean and nADCmean of G3 (1.32±0.47x10-3 mm2/sec and 0.97±0.95) were lower than G1+G2 (1.57±0.39x10-3 mm2/sec and 1.24±0.49; p=0.03 and p=0.04). ADCmean and nADCmean were inversely correlated with tumour grade (p<0.025). No correlation was found between ADC and tumour fibrosis content. AUROC, sensitivity and specificity of nADCmean for G3 versus G1+G2 were 0.71, 89.5% and 55.5%. CONCLUSION: ADC quantification has reasonable accuracy for predicting ICC grade. KEY POINTS: • ADC quantification was useful for predicting ICC tumour grade. • Infiltrative tumour morphology and size were associated with poorly differentiated ICCs. • ADC values depended more on ICC tumour grade than fibrosis content. • Ability to predict ICC tumour grade non-invasively could impact patient management.

Feasibility and reproducibility of liver surface nodularity quantification for the assessment of liver cirrhosis using CT and MRI.

PURPOSE: To assess intra-observer, inter-observer and inter-modality (CT vs. MRI) reproducibility of liver surface nodularity (LSN) scores measured with software used for detection of liver fibrosis. METHODS: This IRB-approved retrospective study included patients with both abdominal CT and MRI within 6 months of histopathologic sampling. Two independent observers used post-processing software to quantify LSN scores on axial non-contrast CT (NCT), axial contrast-enhanced CT (CECT), axial T2-weighted (T2W) HASTE, and axial and coronal post-gadoxetic acid T1-weighted (T1W) images obtained during the hepatobiliary phase (HBP). Ten slices were used to acquire the LSN scores. Intra-observer, inter-observer, and inter-modality (CT vs. MRI) reproducibility were assessed with intraclass correlation coefficient (ICC) and coefficients of variability (CV). Accuracy for detection of cirrhosis was evaluated for each technique. RESULTS: 26 patients (M/F 19/7, mean age 57 years), including 7 with cirrhosis (26.9%), were assessed. Technical failure occurred with NCT (1/23, 4.3%) and T2 HASTE (8/28, 28.6%). Intra-observer reproducibility was excellent for NCT, CECT, axial and coronal T1W HBP [ICC ≥ 0.92, CV ≤ 8%]. Inter-observer reproducibility was also excellent for NCT and CECT (ICC ≥ 0.95, CV ≤ 7.3%) and for coronal T1W HBP (ICC = 0.84, CV = 5.6%). There was fair to moderate agreement between CT and MRI (ICC 0.20-0.44). There were significant differences in mean LSN scores between non-cirrhotic and cirrhotic patients with NCT (2.6 vs. 4.2, p = 0.04) and T1W HBP (3.7 vs. 4.6; p = 0.01) images, with AUCs of 0.81 and 0.82, respectively. CONCLUSIONS: LSN measurement is highly reproducible with NCT and post-contrast T1W HBP on MRI, with different results obtained between CT and MRI.

Primary sclerosing cholangitis: detailed histologic assessment and integration using bioinformatics highlights arterial fibrointimal hyperplasia as a novel feature.

OBJECTIVES: Liver biopsy diagnosis of primary sclerosing cholangitis (PSC) is difficult. We performed a detailed histologic analysis of PSC cases using novel bioinformatics analysis to identify histologic features that may be useful in its diagnosis. METHODS: PSC liver explants were examined and compared with primary biliary cirrhosis and hepatitis C explants to act as controls. Demographic, macroscopic, and histologic variables were analyzed using both conventional statistics and an integrative bioinformatics approach, significance analysis of microarrays (SAM), and hierarchical clustering analysis (HCA). RESULTS: The PSC group was younger and had distinctive PSC features, including bile duct scars, onion-skin fibrosis, and arterial fibrointimal hyperplasia. SAM allowed the integration of variables by comparing PSC and control groups, whereas HCA was able to correctly categorize each group. CONCLUSIONS: This study demonstrates characteristic PSC histology as well as arterial hyperplasia to be distinctive features that may aid in PSC diagnosis and be confirmed by bioinformatics.