Triphasic-aided Liver Lesion Segmentation in Non-contrast CT (TriALS) Challenge
Creators: name: Elbatel, Marawan
name: Yi, Qin
name: Huang, Xuanqi
name: Wang, Haonan
name: Li, Xiaomeng
name: Marinov, Zdravko
name: Stiefelhagen, Rainer
name: Deng, Wenhui
name: Li, Baoxun
name: Mao, Jiaji
name: Hu, Huijun
name: Shen, Jun
name: Ghonim, Mohamed
name: Abouelhoda, Ahmed
name: Salem, Amr Muhammad Abdo
name: Elghitany, Nouran
name: Elghitany, Noha
name: Adel, Amira
name: Adil Ali, Susan
name: Yassin, Aya
Publisher: name: Zenodo
Year: 2025
Subjects: Automated Liver Lesion Segmentation
Non-Contrast CT
Multi-Phase Contrast-Enhanced Imaging
Multi-Center Multi-Vendor Dataset
AI for Resource-Limited Settings
Interactive Segmentation
MICCAI 2025 challenge

description: Liver lesion detection and characterization often rely on contrast agents to enhance the visibility of abnormalities due to the limited soft tissue resolution of non-contrast CT (NCCT) scans. However, global supply chain disruptions caused by COVID-19, combined with economic instability in developing countries, have significantly impacted the availability of contrast agents. In Egypt, liver cancer ranks as the most prevalent cancer, representing 20–35% of all cancer cases, according to the WHO Globocan Report (2020) and the Egyptian National Cancer Registry (2014). Given the high burden of liver cancer, national campaigns targeting hepatitis treatment have been initiated to mitigate its impact on the population.

At MICCAI 2024 in Africa, we established TriALS as a benchmark for liver lesion segmentation on NCCT scans. We demonstrated the potential of utilizing multi-phase data to enhance the training process, thereby improving lesion detection accuracy in NCCT imaging, particularly as a substitute for contrast-enhanced imaging in resource-limited settings. Not only TriALS can mitigate the contrast shortage problem, but it can also help reduce contrast-related complications and significantly lower imaging costs in an already economically affected population.

Despite our progress, the task remains highly challenging, underscoring the need for cross-regional collaboration and external validation. Building on TriALS 2024, we are extending TriALS to MICCAI 2025 in Asia by integrating a diverse, multi-center, multi-vendor dataset encompassing imaging from African (Egyptian) and Asian (Chinese) institutions, providing robust variability for cross-regional training and evaluation. Liver cancer remains a critical global health issue, particularly in Asia, where seven of the top 10 countries worldwide with the highest liver cancer mortality rates are located. Notably, China accounts for approximately 40% of liver cancer cases globally, with 367,657 cases out of the 866,136 reported worldwide, according to the World Cancer Research Fund (2022).

TriALS 2025’s goal is twofold: (1) to advance liver lesion segmentation in regions with limited access to contrast imaging, such as Africa, and (2) to achieve detection accuracy comparable to contrast-enhanced imaging in well-resourced areas like China. Through this effort, TriALS aims to deliver high liver lesion detection accuracy, offering a sustainable and globally relevant solution for liver cancer detection.