MRI-based habitat imaging in cancer treatment: current technology, applications, and challenges

作者：Shaolei Li, Yongming Dai, Jiayi Chen, Fuhua Yan, Yingli Yang · 发表于：Cancer Imaging · 年份：2024 · DOI：10.1186/s40644-024-00758-9 · 被引用次数：96 · 研究领域：Radiomics and Machine Learning in Medical Imaging、Cancer Genomics and Diagnostics、MRI in cancer diagnosis

Extensive efforts have been dedicated to exploring the impact of tumor heterogeneity on cancer treatment at both histological and genetic levels. To accurately measure intra-tumoral heterogeneity, a non-invasive imaging technique, known as habitat imaging, was developed. The technique quantifies intra-tumoral heterogeneity by dividing complex tumors into distinct sub- regions, called habitats. This article reviews the following aspects of habitat imaging in cancer treatment, with a focus on radiotherapy: (1) Habitat imaging biomarkers for assessing tumor physiology; (2) Methods for habitat generation; (3) Efforts to combine radiomics, another imaging quantification method, with habitat imaging; (4) Technical challenges and potential solutions related to habitat imaging; (5) Pathological validation of habitat imaging and how it can be utilized to evaluate cancer treatment by predicting treatment response including survival rate, recurrence, and pathological response as well as ongoing open clinical trials.