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Preoperative prediction of IDH genotypes and prognosis in adult-type diffuse gliomas: intratumor heterogeneity habitat analysis using dynamic contrast-enhanced MRI and diffusion-weighted imaging

异柠檬酸脱氢酶 接收机工作特性 胶质瘤 医学 核医学 有效扩散系数 比例危险模型 磁共振成像 曲线下面积 磁共振弥散成像 病理 放射科 内科学 核磁共振 癌症研究 物理
作者
Xingrui Wang,Zhenhui Xie,Xiaoqing Wang,Yang Song,Shiteng Suo,Yan Ren,Wentao Hu,Yi Zhu,Mengqiu Cao,Yan Zhou
出处
期刊:Cancer Imaging [BioMed Central]
卷期号:25 (1) 被引量:1
标识
DOI:10.1186/s40644-025-00829-5
摘要

Abstract Background Intratumor heterogeneity (ITH) is a key biological characteristic of gliomas. This study aimed to characterize ITH in adult-type diffuse gliomas and assess the feasibility of using habitat imaging based on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and diffusion-weighted imaging (DWI) to preoperatively predict isocitrate dehydrogenase (IDH) genotypes and prognosis. Methods Sixty-three adult-type diffuse gliomas with known IDH genotypes were enrolled. Volume transfer constant (K trans ) and apparent diffusion coefficient (ADC) maps were acquired from DCE-MRI and DWI, respectively. After tumor segmentation, the k-means algorithm clustered K trans and ADC image voxels to generate spatial habitats and extract quantitative image features. Receiver operating characteristic (ROC) curves and area under the curve (AUC) were used to evaluate IDH predictive performance. Multivariable logistic regression models were constructed and validated using leave-one-out cross-validation, and the contrast-enhanced subgroup was analyzed independently. Kaplan-Meier and Cox proportional hazards regression analyses were used to investigate the relationship between tumor habitats and progression-free survival (PFS) in the two IDH groups. Results Three habitats were identified: Habitat 1 (hypo-vasopermeability and hyper-cellularity), Habitat 2 (hypo-vasopermeability and hypo-cellularity), and Habitat 3 (hyper-vasopermeability). Compared to the IDH wild-type group, the IDH mutant group exhibited lower mean K trans values in Habitats 1 and 2 (both P < 0.001), higher volume ( P < 0.05) and volume percentage (pVol, P < 0.01) of Habitat 2, and lower volume and pVol of Habitat 3 (both P < 0.001). The optimal logistic regression model for IDH prediction yielded an AUC of 0.940 (95% confidence interval [CI]: 0.880–1.000), which improved to 0.948 (95% CI: 0.890–1.000) after cross-validation. Habitat 2 contributed the most to the model, consistent with the findings in the contrast-enhanced subgroup. In IDH wild-type group, pVol of Habitat 2 was identified as a significant risk factor for PFS (high- vs. low-pVol subgroup, hazard ratio = 2.204, 95% CI: 1.061–4.580, P = 0.034), with a value below 0.26 indicating a 5-month median survival benefit. Conclusions Habitat imaging employing DCE-MRI and DWI may facilitate the characterization of ITH in adult-type diffuse gliomas and serve as a valuable adjunct in the preoperative prediction of IDH genotypes and prognosis. Clinical trial number Not applicable.
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