Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

PLoS Biology Volume 17 Issue 4 Page e3000042- published_at 2019-04-18

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Title ( eng )	Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias
Creator	Yamashita Ayumu Yahata Noriaki Itahashi Takashi Lisi Giuseppe Yamada Takashi Ichikawa Naho Takamura Masahiro Yoshihara Yujiro Kunimatsu Akira Okada Naohiro Yamagata Hirotaka Matsuo Koji Hashimoto Ryuichiro Okada Go Sakai Yuki Morimoto Jun Narumoto Jin Shimada Yasuhiro Kasai Kiyoto Kato Nobumasa Takahashi Hidehiko Okamoto Yasumasa Tanaka Saori C. Kawato Mitsuo Yamashita Okito Imamizu Hiroshi
Source Title	PLoS Biology
Volume	17
Issue	4
Start Page	e3000042
Abstract	When collecting large amounts of neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent a barrier when acquiring multisite neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multisite, multidisorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. The effects on resting-state functional MRI connectivity based on pairwise correlations because of both bias types were greater than or equal to psychiatric disorder differences. Furthermore, our findings indicated that each site can sample only from a subpopulation of participants. This result suggests that it is essential to collect large amounts of neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using a traveling-subject dataset and achieved the reduction of the measurement bias by 29% and improvement of the signal-to-noise ratios by 40%. Our results provide fundamental knowledge regarding site effects, which is important for future research using multisite, multidisorder resting-state functional MRI data.
Descriptions	This study was conducted under the contract research Grant Number JP18dm0307008, JP17dm0107044 (“Development of BMI Technologies for Clinical Application” of the Strategic Research Program for Brain Sciences), JP18dm0307002, JP18dm0307004, and JP18dm0307009 supported by the Japan Agency for Medical Research and Development (AMED). This study was also partially supported by the ImPACT Program of the Council for Science, Technology and Innovation (Cabinet Office, Government of Japan). H.I. was partially supported by JSPS KAKENHI 26120002. A.Y. was partially supported by JSPS KAKENHI 15J06788.
Language	eng
Resource Type	journal article
Publisher	Public Library of Science
Date of Issued	2019-04-18
Rights	© 2019 Yamashita et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Publish Type	Version of Record
Access Rights	open access
Source Identifier	[ISSN] 1544-9173 [ISSN] 1545-7885 [DOI] 10.1371/journal.pbio.3000042 [PMID] 30998673 [DOI] https://doi.org/10.1371/journal.pbio.3000042