# An Updated Review of Combined Hepatocellular Cholangiocarcinoma: A Rare and Poorly Understood Neoplasm

## TL;DR

This paper reviews combined hepatocellular cholangiocarcinoma, a rare liver cancer that is difficult to diagnose and treat, and explores the potential of AI in improving diagnosis and outcomes.

## Contribution

The paper introduces the potential of radiomics AI for differentiating cHCC-CC from other liver cancers and predicting survival.

## Key findings

- cHCC-CC is often misdiagnosed as HCC or ICC due to overlapping features.
- There is no consensus on the optimal treatment strategy for cHCC-CC.
- Radiomics AI may help improve lesion differentiation and predict post-treatment outcomes.

## Abstract

Combined hepatocellular cholangiocarcinoma (cHCC-CC) is a rare and poorly understood primary liver cancer. First identified over a century ago, it has been referred to by various names and reclassified multiple times since the initial description. Diagnosis is extremely challenging as the tumor can mimic hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICC) on imaging or show overlapping features of both. The tumor may also be incorrectly diagnosed with biopsy due to inadequate tissue sampling. As such, many tumors are only correctly diagnosed histologically following surgical resection or transplantation for presumptive HCC. A variety of treatment options are available, although no national or international consensus exists regarding the optimal treatment strategy. Treatment outcomes vary with cHCC-CC showing an intermediate prognosis between HCC and ICC. In this updated review, we provide a conceptual overview of this intriguing neoplasm, including its classification and origins, epidemiology, clinical characteristics, and diagnostic and treatment options. Finally, we discuss the use of radiomics artificial intelligence (AI) to address challenges in lesion differentiation from HCC and ICC, and in predicting post-treatment survival and recurrence.