DOI: 10.1200/po-26-00243 ISSN: 2473-4284

Noncontrast Magnetic Resonance Fingerprinting-Habitat Framework for Intratumoral Heterogeneity Decoding and Isocitrate Dehydrogenase Mutation Prediction in Diffuse Gliomas

Dandan Song, Borui Li, Yan Liu, Peixu Guo, Yaqin Mi, Binju Yang, Haiyuan Qu, Yueluan Jiang, Yang Song, Chengxiu Zhang, Guang Yang, Guoguang Fan, Miao Chang
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PURPOSE

To develop and validate a magnetic resonance fingerprinting (MRF)–based habitat imaging framework for noninvasively decoding intratumoral heterogeneity (ITH) and preoperatively predicting isocitrate dehydrogenase (IDH) mutation status in diffuse gliomas.

MATERIALS AND METHODS

In this prospective study (January 2024-September 2025), 141 adults with diffuse gliomas (56 IDH-mutant, 85 IDH-wildtype) were enrolled. Tumors were segmented into three habitats via K-means clustering of coregistered MRF-derived T2 and free water maps. A habitat-based radiomic model for IDH status was developed in a training cohort (n = 98) and validated in an independent test cohort (n = 43). Its performance was compared against a conventional whole-tumor model using area under the curve (AUC) and net reclassification improvement (NRI). Pathophysiological validation was performed by correlating habitats with the Ki-67 proliferation index, dynamic contrast-enhanced magnetic resonance imaging ( K trans ), and apparent diffusion coefficient (ADC). The prognostic value for progression-free survival (PFS) was also assessed.

RESULTS

The MRF-habitat model outperformed the whole-tumor model for IDH genotyping (test AUC, 0.819 v 0.758; NRI, 0.833, P = .003). It identified a prognostically significant subregion (Subregion1) where T2 uniformity was an independent predictor of PFS (hazard ratio: 0.008; P = .033). Subregion2, a hypoxic-angiogenic niche, correlated with Ki-67 and exhibited higher K trans and lower ADC in IDH-wildtype tumors (both P < .05). Patients stratified as high-risk by the model had significantly shorter median PFS (5.8 months v not reached, P = .043).

CONCLUSION

The MRF-based habitat framework noninvasively decodes ITH, improves preoperative IDH genotyping, and identifies pathophysiologically distinct subregions with prognostic relevance.

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