Histological and molecular classifications of pediatric glioma with time-dependent diffusion MRI-based microstructural mapping

胶质瘤 磁共振弥散成像 接收机工作特性 有效扩散系数 热扩散率 组织学 医学 核医学 病理 材料科学 磁共振成像 放射科 内科学 物理 癌症研究 量子力学
作者
Hongxi Zhang,Liang‐Ru Ke,Ruicheng Ba,Zelin Zhang,Yi Zhang,Ye Chen,Weizhong Gu,Zhipeng Shen,Qiang Shu,Junfen Fu,Dan Wu
出处
期刊:Neuro-oncology [Oxford University Press]
卷期号:25 (6): 1146-1156 被引量:8
标识
DOI:10.1093/neuonc/noad003
摘要

Abstract Background Gliomas are the most common type of central nervous system tumors in children, and the combination of histological and molecular classification is essential for prognosis and treatment. Here, we proposed a newly developed microstructural mapping technique based on diffusion-time-dependent diffusion MRI td-dMRI theory to quantify tumor cell properties and tested these microstructural markers in identifying histological grade and molecular alteration of H3K27. Methods This prospective study included 69 pediatric glioma patients aged 6.14 ± 3.25 years old, who underwent td-dMRI with pulsed and oscillating gradient diffusion sequences on a 3T scanner. dMRI data acquired at varying tds were fitted into a 2-compartment microstructural model to obtain intracellular fraction (fin), cell diameter, cellularity, etc. Apparent diffusivity coefficient (ADC) and T1 and T2 relaxation times were also obtained. H&E stained histology was used to validate the estimated microstructural properties. Results For histological classification of low- and high-grade pediatric gliomas, the cellularity index achieved the highest area under the receiver-operating-curve (AUC) of 0.911 among all markers, while ADC, T1, and T2 showed AUCs of 0.906, 0.885, and 0.886. For molecular classification of H3K27-altered glioma in 39 midline glioma patients, cell diameter showed the highest discriminant power with an AUC of 0.918, and the combination of cell diameter and extracellular diffusivity further improved AUC to 0.929. The td-dMRI estimated fin correlated well with the histological ground truth with r = 0.7. Conclusions The td-dMRI-based microstructural properties outperformed routine MRI measurements in diagnosing pediatric gliomas, and the different microstructural features showed complementary strength in histological and molecular classifications.
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