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

被引:28
|
作者
Zhang, Hongxi [1 ]
Liu, Kuiyuan [2 ]
Ba, Ruicheng [2 ]
Zhang, Zelin [2 ]
Zhang, Yi [2 ]
Chen, Ye [3 ]
Gu, Weizhong [4 ]
Shen, Zhipeng [5 ]
Shu, Qiang [6 ]
Fu, Junfen [7 ]
Wu, Dan [1 ,2 ,8 ]
机构
[1] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Dept Radiol,Sch Med, Hangzhou, Peoples R China
[2] Zhejiang Univ, Coll Biomed Engn & Instrument Sci, Dept Biomed Engn, Hangzhou, Peoples R China
[3] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Sch Med, Hangzhou, Peoples R China
[4] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Dept Pathol,Sch Med, Hangzhou, Peoples R China
[5] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Dept Neurosurg,Sch Med, Hangzhou, Peoples R China
[6] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Dept Cardiol,Sch Med, Hangzhou, Peoples R China
[7] Zhejiang Univ, Childrens Hosp, Natl Clin Res Ctr Child Hlth, Dept Endocrinol,Sch Med, Hangzhou, Peoples R China
[8] Zhejiang Univ, Dept Biomed Engn, Room 525,Zhou Yiqing Bldg,Yuquan Campus, Hangzhou 310027, Peoples R China
基金
中国国家自然科学基金;
关键词
diffusion MRI; microstructure; pediatric glioma; histological grading; CENTRAL-NERVOUS-SYSTEM; MIDLINE GLIOMAS; CELL-SIZE; QUANTIFICATION; CELLULARITY; COEFFICIENT; CHILDHOOD; TUMORS;
D O I
10.1093/neuonc/noad003
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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 t(d)-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 t(d)-dMRI with pulsed and oscillating gradient diffusion sequences on a 3T scanner. dMRI data acquired at varying t(d)s were fitted into a 2-compartment microstructural model to obtain intracellular fraction (f(in)), 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 t(d)-dMRI estimated f(in) correlated well with the histological ground truth with r = 0.7. Conclusions The t(d)-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.
引用
收藏
页码:1146 / 1156
页数:11
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