Heterogeneity matching and IDH prediction in adult-type diffuse gliomas: a DKI-based habitat analysis

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Abstract

Objective: To explain adult-type diffuse gliomas heterogeneity through diffusion kurtosis imaging-based habitat characteristics and develop and validate a comprehensive model for predicting isocitrate dehydrogenase (IDH) status. Materials and methods: In this prospective secondary analysis, 103 participants (mean age, 52 years; range, 21-77; 54 [52%] male) pathologically diagnosed with adult-type diffuse gliomas were enrolled between June 2018 and February 2022. The Otsu method was used to generate habitat maps with mean diffusivity (MD) and mean kurtosis (MK) for a total of 4 subhabitats containing 16 habitat features. Habitat heatmaps were created based on the Pearson correlation coefficient. The Habitat imAging aNd clinicraD INtegrated prEdiction SyStem (HANDINESS) was created by combining clinical features, conventional MRI morphological features, and habitat image features. ROC, calibration curve, and decision curve analyses were used to select the optimal model after 32 pipelines for model training and validation. Results: In the restricted diffusion and high-density subhabitat, MK was highly correlated with MD (R2 = 0.999), volume (0.608) and percentage of volume (0.663), and this region had the highest MK value (P

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Liu, Y., Wang, P., Wang, S., Zhang, H., Song, Y., Yan, X., & Gao, Y. (2023). Heterogeneity matching and IDH prediction in adult-type diffuse gliomas: a DKI-based habitat analysis. Frontiers in Oncology, 13. https://doi.org/10.3389/fonc.2023.1202170

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