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

Author:

Zhang Hongxi1,Liu Kuiyuan2,Ba Ruicheng2,Zhang Zelin2,Zhang Yi2,Chen Ye3,Gu Weizhong4,Shen Zhipeng5,Shu Qiang6,Fu Junfen7,Wu Dan2ORCID

Affiliation:

1. Department of Radiology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

2. Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University , Hangzhou , China

3. Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

4. Department of Pathology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

5. Department of Neurosurgery, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

6. Department of Cardiology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

7. Department of Endocrinology, Children’s Hospital, Zhejiang University School of Medicine, National Clinical Research Center for Child Health , Hangzhou , China

Abstract

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.

Funder

Ministry of Science and Technology of the People's Republic of China

National Natural Science Foundation of China

Science and Technology Department of Zhejiang Province

Publisher

Oxford University Press (OUP)

Subject

Cancer Research,Neurology (clinical),Oncology

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