A narrative review of imaging intratumor heterogeneity in non-small cell lung cancer: current advances.

Background and Objective: Heterogeneity is a hallmark of non-small cell lung cancer (NSCLC), manifesting as molecular, genetic, and phenotypic variations that complicate treatment and drive resistance. Accurate characterization of intratumor heterogeneity (ITH) is crucial for optimizing therapy. This review explores ITH in NSCLC from spatiotemporal perspectives, focusing on advances in imaging-based quantification and its clinical implications. Methods: A systematic literature search was conducted across PubMed, Web of Science, EMBASE, and Cochrane Library (up to June 1, 2025). Two authors independently screened titles/abstracts and performed full-text reviews of relevant English-language studies, with findings synthesized through iterative consensus. Key Content and Findings: NSCLC heterogeneity manifests as dynamic spatial and temporal variations in genetics, the tumor microenvironment, and metabolism. Imaging ITH (IITH), utilizing techniques such as texture analysis, histogram methods, shape/volume features, and habitat imaging, allows for the quantification of biologically distinct subregions within the tumor. IITH biomarkers have been shown to predict treatment response, survival outcomes, histopathological subtypes, and molecular profiles. A reduction in heterogeneity following therapy is associated with improved survival. Furthermore, integrating IITH data with multi-omics information enhances the accuracy of prognostic models that track tumor evolution. However, several critical challenges remain, including the standardization of image acquisition and reconstruction processes, tumor segmentation variability, feature reproducibility, and the need for prospective validation across multicenter cohorts. Conclusions: IITH metrics provide clinically actionable biomarkers for precision oncology. Future work should prioritize multi-omics integration and standardization to advance clinical translation.