Reproducible network and regional topographies of abnormal glucose metabolism associated with progressive supranuclear palsy: Multivariate and univariate analyses in American and Chinese patient cohorts. Issue 7 (13th March 2018)

• Record Type: Journal Article
• Authors: Ge, Jingjie; Wu, Jianjun; Peng, Shichun; Wu, Ping; Wang, Jian; Zhang, Huiwei; Guan, Yihui; Eidelberg, David; Zuo, Chuantao; Ma, Yilong
• Is Part Of: Human brain mapping. Volume 39:Issue 7(2018)
• Page Start: 2842
• Page End: 2858
• Publication Date: 2018-03-13
• Subjects: differential diagnosis -- disease‐related brain network markers -- movement disorders -- multivariate and univariate brain mapping methods -- parkinsonism -- PET; Brain mapping -- Periodicals; 611.81
• DOI: 10.1002/hbm.24044
• Languages: English
• ISSNs: 1065-9471

Abstract

Abstract: Progressive supranuclear palsy (PSP) is a rare movement disorder and often difficult to distinguish clinically from Parkinson's disease (PD) and multiple system atrophy (MSA) in early phases. In this study, we report reproducible disease‐related topographies of brain network and regional glucose metabolism associated with PSP in clinically‐confirmed independent cohorts of PSP, MSA, and PD patients and healthy controls in the USA and China. Using 18 F‐FDG PET images from PSP and healthy subjects, we applied spatial covariance analysis with bootstrapping to identify a PSP‐related pattern (PSPRP) and estimate its reliability, and evaluated the ability of network scores for differential diagnosis. We also detected regional metabolic differences using statistical parametric mapping analysis. We produced a highly reliable PSPRP characterized by relative metabolic decreases in the middle prefrontal cortex/cingulate, ventrolateral prefrontal cortex, striatum, thalamus and midbrain, covarying with relative metabolic increases in the hippocampus, insula and parieto‐temporal regions. PSPRP network scores correlated positively with PSP duration and accurately discriminated between healthy, PSP, MSA and PD groups in two separate cohorts of parkinsonian patients at both early and advanced stages. Moreover, PSP patients shared many overlapping areas with abnormal metabolism in the same cortical and subcortical regions as in the PSPRP. With rigorous cross‐validation, this study demonstrated highly comparable and reproducible PSP‐related metabolic topographies at network and regional levels across different patient populations and PET scanners. Metabolic brain network activity may serve as a reliable and objective marker of PSP, although cross‐validation applying recent diagnostic criteria and classification is warranted.