Patterns of brain volume and metabolism predict clinical features in the progressive supranuclear palsy spectrum

被引:1
作者
Ali, Farwa [1 ]
Clark, Heather [1 ]
Machulda, Mary [2 ]
Senjem, Matthew L. [3 ]
Lowe, Val J. [3 ]
Jack Jr, Clifford R. [3 ]
Josephs, Keith A. [1 ]
Whitwell, Jennifer [3 ]
Botha, Hugo [1 ]
机构
[1] Mayo Clin, Dept Neurol, 200 1st St SW, Rochester, MN 55905 USA
[2] Mayo Clin, Dept Psychiat & Psychol, Rochester, MN 55905 USA
[3] Mayo Clin, Dept Radiol, Rochester, MN 55905 USA
关键词
neurodegeneration; tauopathy; machine learning; diagnosis; neuroimaging; CORTICAL THICKNESS; PURE AKINESIA; RATING-SCALE; DIAGNOSIS; CRITERIA; DEGENERATION; APRAXIA; PSP; PARCELLATION; PHENOTYPES;
D O I
10.1093/braincomms/fcae233
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Progressive supranuclear palsy (PSP) is a neurodegenerative tauopathy that presents with highly heterogenous clinical syndromes. We perform cross-sectional data-driven discovery of independent patterns of brain atrophy and hypometabolism across the entire PSP spectrum. We then use these patterns to predict specific clinical features and to assess their relationship to phenotypic heterogeneity. We included 111 patients with PSP (60 with Richardson syndrome and 51 with cortical and subcortical variant subtypes). Ninety-one were used as the training set and 20 as a test set. The presence and severity of granular clinical variables such as postural instability, parkinsonism, apraxia and supranuclear gaze palsy were noted. Domains of akinesia, ocular motor impairment, postural instability and cognitive dysfunction as defined by the Movement Disorders Society criteria for PSP were also recorded. Non-negative matrix factorization was used on cross-sectional MRI and fluorodeoxyglucose-positron emission tomography (FDG-PET) scans. Independent models for each as well as a combined model for MRI and FDG-PET were developed and used to predict the granular clinical variables. Both MRI and FDG-PET were better at predicting presence of a symptom than severity, suggesting identification of disease state may be more robust than disease stage. FDG-PET predicted predominantly cortical abnormalities better than MRI such as ideomotor apraxia, apraxia of speech and frontal dysexecutive syndrome. MRI demonstrated prediction of cortical and more so sub-cortical abnormalities, such as parkinsonism. Distinct neuroanatomical foci were predictive in MRI- and FDG-PET-based models. For example, vertical gaze palsy was predicted by midbrain atrophy on MRI, but frontal eye field hypometabolism on FDG-PET. Findings also differed by scale or instrument used. For example, prediction of ocular motor abnormalities using the PSP Saccadic Impairment Scale was stronger than with the Movement Disorders Society Diagnostic criteria for PSP oculomotor impairment designation. Combination of MRI and FDG-PET demonstrated enhanced detection of parkinsonism and frontal syndrome presence and apraxia, cognitive impairment and bradykinesia severity. Both MRI and FDG-PET patterns were able to predict some measures in the test set; however, prediction of global cognition measured by Montreal Cognitive Assessment was the strongest. MRI predictions generalized more robustly to the test set. PSP leads to neurodegeneration in motor, cognitive and ocular motor networks at cortical and subcortical foci, leading to diverse yet overlapping clinical syndromes. To advance understanding of phenotypic heterogeneity in PSP, it is essential to consider data-driven approaches to clinical neuroimaging analyses. Ali et al. define data-driven patterns of brain atrophy and hypometabolism across the phenotypic spectrum of progressive supranuclear palsy to capture disease heterogeneity. The relationship between imaging patterns and fine-grained clinical measures illustrates distinct foci of cortical and subcortical brain dysfunction. Graphical Abstract
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页数:15
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