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

Abstract

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.

Keywords: Cancer treatment; Habitat imaging; Tumor heterogeneity.

Fig. 1

A schematics of habitat imaging analysis

Fig. 2

An example of habitat imaging based on T1- and T2-weighted images of an esophageal cancer patient using two-steps method (A) and one-step method (B). The region of interest is the gross tumor volume. Both T1 and T2 images are preprocessed using central normalization. (A) Each of T1 and T2 images generates 2 clusters (1 and 2) derived from histogram and 4 habitats (11, 12, 21, and 22) created by intersections between T1 habitat map and T2 habitat map for the final habitat map; (B) The scatter plot (left) and map (right) share the same color map to identify the 3 clusters using K-mean algorithm