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
Yoshihara Yujiro
Kunimatsu Akira
Okada Naohiro
Yamagata Hirotaka
Matsuo Koji
Hashimoto Ryuichiro
Sakai Yuki
Morimoto Jun
Narumoto Jin
Shimada Yasuhiro
Kasai Kiyoto
Kato Nobumasa
Takahashi Hidehiko
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