Dataset Information

FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.

ABSTRACT:

Background

The development of therapeutic interventions for Parkinson disease (PD) is challenged by disease complexity and subjectivity of symptom evaluation. A Parkinson's Disease Related Pattern (PDRP) of glucose metabolism via fluorodeoxyglucose positron emission tomography (FDG-PET) has been reported to correlate with motor symptom scores and may aid the detection of disease-modifying therapeutic effects.

Objectives

We sought to independently evaluate the potential utility of the PDRP as a biomarker for clinical trials of early-stage PD.

Methods

Two machine learning approaches (Scaled Subprofile Model (SSM) and NPAIRS with Canonical Variates Analysis) were performed on FDG-PET scans from 17 healthy controls (HC) and 23 PD patients. The approaches were compared regarding discrimination of HC from PD and relationship to motor symptoms.

Results

Both classifiers discriminated HC from PD (p?2?=?0.24, p?2?=?0.23, p?2?=?0.25, p?2?=?0.16, p?ConclusionsTwo independent analyses performed in a cohort of mild PD patients replicated key features of the PDRP, confirming that FDG-PET and multivariate classification can provide an objective, sensitive biomarker of disease stage with the potential to detect treatment effects on PD progression.

SUBMITTER: Matthews DC

PROVIDER: S-EPMC6120603 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Publications

FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.

Matthews Dawn C DC Lerman Hedva H Lukic Ana A Andrews Randolph D RD Mirelman Anat A Wernick Miles N MN Giladi Nir N Strother Stephen C SC Evans Karleyton C KC Cedarbaum Jesse M JM Even-Sapir Einat E

NeuroImage. Clinical 20180810

<h4>Background</h4>The development of therapeutic interventions for Parkinson disease (PD) is challenged by disease complexity and subjectivity of symptom evaluation. A Parkinson's Disease Related Pattern (PDRP) of glucose metabolism via fluorodeoxyglucose positron emission tomography (FDG-PET) has been reported to correlate with motor symptom scores and may aid the detection of disease-modifying therapeutic effects.<h4>Objectives</h4>We sought to independently evaluate the potential utility of ...[more]

PMID: 30186761

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Project description:UnlabelledIn the recently revised diagnostic criteria for Alzheimer disease (AD), the National Institute on Aging and Alzheimer Association suggested that confidence in diagnosing dementia due to AD and mild cognitive impairment (MCI) due to AD could be improved by the use of certain biomarkers, such as (18)F-FDG PET evidence of hypometabolism in AD-affected brain regions. Three groups have developed automated data analysis techniques to characterize the AD-related pattern of hypometabolism in a single measurement. In this study, we sought to directly compare the ability of these three (18)F-FDG PET data analysis techniques--the PMOD Alzheimer discrimination analysis tool, the hypometabolic convergence index, and a set of meta-analytically derived regions of interest reflecting AD hypometabolism pattern (metaROI)--to distinguish moderate or mild AD dementia patients and MCI patients who subsequently converted to AD dementia from cognitively normal older adults.MethodsOne hundred sixty-six (18)F-FDG PET patients from the AD Neuroimaging Initiative, 308 from the Network for Efficiency and Standardization of Dementia Diagnosis, and 176 from the European Alzheimer Disease Consortium PET study were categorized, with masking of group classification, as AD, MCI, or healthy control. For each AD-related (18)F-FDG PET index, receiver-operating-characteristic curves were used to characterize and compare subject group classifications.ResultsThe 3 techniques were roughly comparable in their ability to distinguish each of the clinical groups from cognitively normal older adults with high sensitivity and specificity. Accuracy of classification (in terms of area under the curve) in each clinical group varied more as a function of dataset than by technique. All techniques were differentially sensitive to disease severity, with the classification accuracy for MCI due to AD to moderate AD varying from 0.800 to 0.949 (PMOD Alzheimer tool), from 0.774 to 0.967 (metaROI), and from 0.801 to 0.983 (hypometabolic convergence index).ConclusionThe 3 tested techniques have the potential to help detect AD in research and clinical settings. Additional efforts are needed to clarify their ability to address particular scientific and clinical questions. Their incremental diagnostic value over other imaging and biologic markers makes them easier to implement by other groups for these purposes.

Project description:We used positron emission tomography imaging with [11C]-3-amino-4-(2-dimethylaminomethylphenylsulfanyl)- benzonitrile (DASB) and principal component analysis to investigate whether a specific Parkinson's disease (PD)-related spatial covariance pattern could be identified for the serotonergic system. We also explored if non-manifesting leucine-rich repeat kinase 2 (LRRK2) mutation carriers, with normal striatal dopaminergic innervation as measured with [11C]-dihydrotetrabenazine (DTBZ), exhibit a distinct spatial covariance pattern compared to healthy controls and subjects with manifest PD. 15 subjects with sporadic PD, eight subjects with LRRK2 mutation-associated PD, nine LRRK2 non-manifesting mutation carriers, and nine healthy controls participated in the study. The analysis was applied to the DASB non-displaceable binding potential values evaluated in 42 pre-defined regions of interest. PD was found to be associated with a specific spatial covariance pattern, comprising relatively decreased DASB binding in the caudate, putamen and substantia nigra and relatively preserved binding in the hypothalamus and hippocampus; the expression of this pattern in PD subjects was significantly higher than in healthy controls (P < 0.001) and correlated significantly with disease duration (P < 0.01) and with DTBZ binding in the more affected putamen (P < 0.01). The LRRK2 non-manifesting mutation carriers expressed a different pattern, also significantly different from healthy controls (P < 0.001), comprising relatively decreased DASB binding in the pons, pedunculopontine nucleus, thalamus and rostral raphe nucleus, and with relatively preserved binding in the hypothalamus, amygdala, hippocampus and substantia nigra. This pattern was not present in either sporadic or LRRK2 mutation-associated PD subjects. These findings, although obtained with a relatively limited number of subjects, suggest that specific and overall distinct spatial serotonergic patterns may be associated with PD and LRRK2 mutations. Alterations in regions where relative upregulation is observed in both patterns may be indicative of compensatory mechanisms preceding or protecting from disease manifestation.

Dataset Information

FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.

Background

Objectives

Methods

Results

Publications

FDG PET Parkinson's disease-related pattern as a biomarker for clinical trials in early stage disease.

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