Dissemin is shutting down on January 1st, 2025

Published in

Nature Research, Scientific Data, 1(11), 2024

DOI: 10.1038/s41597-024-03013-9

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An open relaxation-diffusion MRI dataset in neurosurgical studies

Journal article published in 2024 by Ye Wu ORCID, Xiaoming Liu, Yunzhi Huang, Tao Zhou ORCID, Fan Zhang ORCID
This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Preprint: archiving allowed
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Postprint: archiving forbidden
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Published version: archiving allowed
Data provided by SHERPA/RoMEO

Abstract

AbstractDiffusion MRI (dMRI) is a safe and noninvasive technique that provides insight into the microarchitecture of brain tissue. Relaxation-diffusion MRI (rdMRI) is an extension of traditional dMRI that captures diffusion imaging data at multiple TEs to detect tissue heterogeneity between relaxation and diffusivity. rdMRI has great potential in neurosurgical research including brain tumor grading and treatment response evaluation. However, the lack of available data has limited the exploration of rdMRI in clinical settings. To address this, we are sharing a high-quality rdMRI dataset from 18 neurosurgical patients with different types of lesions, as well as two healthy individuals as controls. The rdMRI data was acquired using 7 TEs, where at each TE multi-shell dMRI with high spatial and angular resolutions is obtained at each TE. Each rdMRI scan underwent thorough artifact and distortion corrections using a specially designed processing pipeline. The dataset’s quality was assessed using standard practices, including quality control and assurance. This resource is a valuable addition to neurosurgical studies, and all data are openly accessible.