CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis.

Autor: Chen X; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Li J; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Chen D; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Zhou Y; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Tu Z; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Lin M; Department of Applied Marine Physics & Engineering, Xiamen University, Xiamen, China., Kang T; Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China., Lin J; Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China., Gong T; Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China., Zhu L; Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China., Zhou J; Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China., Lin OY; Department of Medical Imaging of Southeast Hospital, Medical College of Xiamen University, Xiamen, China., Guo J; Department of Microelectronics and Integrated Circuit, Xiamen University, Xiamen, China., Dong J; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China., Guo D; School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China., Qu X; Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China. Electronic address: quxiaobo@xmu.edu.cn.
Jazyk: angličtina
Zdroj: Journal of magnetic resonance (San Diego, Calif. : 1997) [J Magn Reson] 2024 Jan; Vol. 358, pp. 107601. Date of Electronic Publication: 2023 Nov 29.
DOI: 10.1016/j.jmr.2023.107601
Abstrakt: Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectrum plots and metabolite quantification, the spread of clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: (1) Automatically statistical analysis to find biomarkers for diseases; (2) Consistency verification between the classic and artificial intelligence quantification algorithms; (3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, data of both healthy subjects and patients with mild cognitive impairment are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing at least two years of free access and service. If you are interested, please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2023 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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