Radiological diagnosis of hepatocellular carcinoma does not preclude biopsy before treatment

The evolving role of liver biopsy: Current applications and future prospects

Histopathologic evaluation of liver biopsy has played a longstanding role in the diagnosis and management of liver disease. However, the utility of liver biopsy has been questioned by some, given the improved imaging modalities, increased availability of noninvasive serologic tests, and development of artificial intelligence over the past several years. In this review, we discuss the current and future role of liver biopsy in both non-neoplastic and neoplastic liver diseases in the era of improved noninvasive laboratory, radiologic, and digital technologies.

Absence of Survival Impact from Hepatitis During Immunotherapy in 193 Patients with Advanced Hepatocellular Carcinoma - An Observational Study from Taiwan

Background

Hepatitis often occurs after initiating immune checkpoint inhibitor (ICI) treatment. The time and grade of hepatitis after ICI starts and the prognostic role of immune-related hepatitis in patients with advanced hepatocellular carcinoma (aHCC) remain unclear.

Methods

In this real-world analysis, we enrolled aHCC patients receiving ICIs, documented the highest level of liver enzymes during/after ICIs, and analyzed the survival impact of different hepatitis patterns.

Results

One hundred and ninety-three aHCC patients receiving ICIs were recruited. During ICIs, 88.6% of patients experienced aspartate transaminase (AST) elevations (Grade III/IV: 7.8%). For alanine transaminase (ALT), 81.3% had elevated levels (Grade III/IV: 3.6%), and 41.5% of patients had elevated bilirubin levels (Grade 3/4: 6.7%). The median AST, ALT, and total bilirubin values significantly increased after ICI treatment initiated (all p < 0.001) and, similarly, after excluding progressive disease (p = 0.014, p = 0.002, p < 0.001). The median time of hepatitis occurrence is from the 4.0th to 15.9th weeks. Multivariable analysis showed that patterns of liver enzyme change of AST and total bilirubin in patients receiving ICIs significantly correlate to overall survival (OS, p = 0.009 and 0.001, respectively). After ICI termination, patients with elevated bilirubin (p = 0.003) and AST (p = 0.005) would indicate poor survival, with adjustment of viral hepatitis and ICI responses.

Conclusion

Hepatitis emerges between the 4th and 20th weeks post-ICI initiation. Changes in liver enzymes during ICI therapy do not directly affect OS, implying the safety of ICI use when corticosteroids are promptly administered if clinically indicated.

Disease modifiers and novel markers in hepatitis B virus-related hepatocellular carcinoma

Chronic hepatitis B (CHB) infection is responsible for 40% of the global burden of hepatocellular carcinoma (HCC) with a high case fatality rate. The risk of HCC differs among CHB subjects owing to differences in host and viral factors. Modifiable risk factors include viral load, use of antiviral therapy, co-infection with other hepatotropic viruses, concomitant metabolic dysfunctionassociated steatotic liver disease or diabetes mellitus, environmental exposure, and medication use. Detecting HCC at early stage improves survival, and current practice recommends HCC surveillance among individuals with cirrhosis, family history of HCC, or above an age cut-off. Ultrasonography with or without serum alpha feto-protein (AFP) every 6 months is widely accepted strategy for HCC surveillance. Novel tumor-specific markers, when combined with AFP, improve diagnostic accuracy than AFP alone to detect HCC at an early stage. To predict the risk of HCC, a number of clinical risk scores have been developed but none of them are clinically implemented nor endorsed by clinical practice guidelines. Biomarkers that reflect viral transcriptional activity and degree of liver fibrosis can potentially stratify the risk of HCC, especially among subjects who are already on antiviral therapy. Ongoing exploration of these novel biomarkers is required to confirm their performance characteristics, replicability and practicability.

Primary liver cancer classification from routine tumour biopsy using weakly supervised deep learning

Background & Aims

The diagnosis of primary liver cancers (PLCs) can be challenging, especially on biopsies and for combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We automatically classified PLCs on routine-stained biopsies using a weakly supervised learning method.

Method

We selected 166 PLC biopsies divided into training, internal and external validation sets: 90, 29 and 47 samples, respectively. Two liver pathologists reviewed each whole-slide hematein eosin saffron (HES)-stained image (WSI). After annotating the tumour/non-tumour areas, tiles of 256x256 pixels were extracted from the WSIs and used to train a ResNet18 neural network. The tumour/non-tumour annotations served as labels during training, and the network's last convolutional layer was used to extract new tumour tile features. Without knowledge of the precise labels of the malignancies, we then applied an unsupervised clustering algorithm.

Results

Pathological review classified the training and validation sets into hepatocellular carcinoma (HCC, 33/90, 11/29 and 26/47), intrahepatic cholangiocarcinoma (iCCA, 28/90, 9/29 and 15/47), and cHCC-CCA (29/90, 9/29 and 6/47). In the two-cluster model, Clusters 0 and 1 contained mainly HCC and iCCA histological features. The diagnostic agreement between the pathological diagnosis and the two-cluster model predictions (major contingent) in the internal and external validation sets was 100% (11/11) and 96% (25/26) for HCC and 78% (7/9) and 87% (13/15) for iCCA, respectively. For cHCC-CCA, we observed a highly variable proportion of tiles from each cluster (cluster 0: 5-97%; cluster 1: 2-94%).

Conclusion

Our method applied to PLC HES biopsy could identify specific morphological features of HCC and iCCA. Although no specific features of cHCC-CCA were recognized, assessing the proportion of HCC and iCCA tiles within a slide could facilitate the identification of cHCC-CCA.

Impact and implications

The diagnosis of primary liver cancers can be challenging, especially on biopsies and for combined hepatocellular-cholangiocarcinoma (cHCC-CCA). We automatically classified primary liver cancers on routine-stained biopsies using a weakly supervised learning method. Our model identified specific features of hepatocellular carcinoma and intrahepatic cholangiocarcinoma. Despite no specific features of cHCC-CCA being recognized, the identification of hepatocellular carcinoma and intrahepatic cholangiocarcinoma tiles within a slide could facilitate the diagnosis of primary liver cancers, and particularly cHCC-CCA.