Prediction of individual clinical scores in patients with Parkinson's disease using resting-state functional magnetic resonance imaging.
Neuroimaging holds the promise that it may one day aid the clinical assessment. However, the vast majority of studies using resting-state functional magnetic resonance imaging (fMRI) have reported average differences between Parkinson's disease (PD) patients and healthy controls, which do not permit inferences at the level of individuals. This study was to develop a model for the prediction of PD illness severity ratings from individual fMRI brain scan. The resting-state fMRI scans were obtained from 84 patients with PD and the Unified Parkinson's Disease Rating Scale-III (UPDRS-III) scores were obtained before scanning. The RVR method was used to predict clinical scores (UPDRS-III) from fMRI scans. The application of RVR to whole-brain resting-state fMRI data allowed prediction of UPDRS-III scores with statistically significant accuracy (correlation=0.35, P-value=0.001; mean sum of squares=222.17, P-value=0.002). This prediction was informed strongly by negative weight areas including prefrontal lobe and medial occipital lobe, and positive weight areas including medial parietal lobe. It was suggested that fMRI scans contained sufficient information about neurobiological change in patients with PD to permit accurate prediction about illness severity, on an individual subject basis. Our results provided preliminary evidence, as proof-of-concept, to support that fMRI might be possible to be a clinically useful quantitative assessment aid in PD at individual level. This may enable clinicians to target those uncooperative patients and machines to replace human for a more efficient use of health care resources.
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
YanBing
Y
Hou
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
ChunYan
C
Luo
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Jing
J
Yang
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
RuWei
R
Ou
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Wei
W
Song
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
QianQian
Q
Wei
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Bei
B
Cao
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Bi
B
Zhao
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
Ying
Y
Wu
Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address: hfshang2002@163.com.
Hui-Fang
HF
Shang
Huaxi MR Research Center, Department of Radiology, West China Hospital, Sichuan University, Chengdu, Sichuan, China. Electronic address: qiyonggong@hmrrc.org.cn.
QiYong
Q
Gong
D000328:Adult; D000368:Aged; D001921:Brain / Q000000981:diagnostic imaging*; D001931:Brain Mapping / Q000379:methods; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010300:Parkinson Disease / Q000000981:diagnostic imaging*; D012146:Rest; D012720:Severity of Illness Index
Parkinson's disease; Prediction; Relevance vector regression; Resting-state functional magnetic resonance imaging