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Updated: Jun 29, 2026

Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Multicenter validation of amide proton transfer imaging for the classification of adult-type diffuse gliomas
Tongling Jiang1, Minghao Wu2, Junjiao Hu3
1Zhejiang Key Laboratory of Intelligent Sensing Technology and Advanced Medical Instrument and Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou 310027, China; Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
Abstract:
Accurate classification of adult-type diffuse gliomas is essential for treatment planning, particularly following the 2021 WHO classification update. While amide proton transfer (APT) imaging shows promise, multicenter validation is needed to establish its clinical utility. This study aims to evaluate the multicenter performance of the APT-weighted (APTw) metric for differentiating genotypes, grades, and subtypes of adult-type diffuse gliomas. MRI and clinical data were collected from three centers between July 2020 and January 2024. A standardized whole-brain SPACE CEST imaging protocol was used, and molecular diagnoses were confirmed. Tumor core regions were delineated on T2-weighted images, and multi-modality data were co-registered to T1-weighted images. Mean APTw values were assessed for IDH genotyping and grading among three centers, and for subtyping across two centers, using unpaired t-tests and receiver operating characteristic (ROC) curve analysis. A total of 123 patients (mean age: 48 ± 12 years; 67 males) were included. APTw indices were significantly higher in IDH-wildtype and high-grade gliomas compared to IDH-mutant and low-grade groups (p < 0.01). ROC analysis demonstrated strong classification performance: for IDH genotyping, the pooled area under the ROC curve (AUC) value was 0.84 (individual centers: 0.86, 0.84, and 0.93); for glioma grading, the pooled AUC was 0.83 (individual centers: 0.86, 0.84, and 0.83). Subtyping results showed good performance, particularly in differentiating glioblastomas from oligodendrogliomas (AUC: 0.93) and astrocytomas (AUC: 0.81). APT imaging effectively differentiated glioma grades and IDH mutations across centers, demonstrating robust multicenter performance. However, challenges remain in differentiating specific glioma subtypes.

