Differentiating Parkinson's disease motor subtypes using automated volume‐based morphometry incorporating white matter and deep gray nuclear lesion load

Abstract

Background Periventricular leukoaraiosis may be an important pathological change in postural instability gait disorder (PIGD), a motor subtype of Parkinson's disease (PD). Clinical diagnosis of PIGD may be challenging for the general neurologist. Purpose To evaluate 1) the utility of a fully automated volume‐based morphometry (Vol‐BM) in characterizing imaging diagnostic markers in PD and PIGD, including, 2) novel deep gray nuclear lesion load (GMab), and 3) discriminatory performance of a Vol‐BM model construct in classifying the PIGD subtype. Study Type Prospective. Subjects In all, 23 PIGD, 21 PD, and 20 age‐matched healthy controls (HC) underwent MRI brain scans and clinical assessments. Field Strength/Sequence 3.0T, sagittal 3D‐magnetization‐prepared rapid gradient echo (MPRAGE), and fluid‐attenuated inversion recovery imaging (FLAIR) sequences. Assessment Clinical assessment was conducted by a movement disorder neurologist. The MR brain images were then segmented using an automated multimodal Vol‐BM algorithm (MorphoBox) and reviewed by two authors independently. Statistical Testing Brain segmentation and clinical parameter differences and dependence were assessed using analysis of variance (ANOVA) and regression analysis, respectively. Logistic regression was performed to differentiate PIGD from PD, and discriminative reliability was evaluated using receiver operating characteristic (ROC) analysis. Results Significantly higher white matter lesion load (WMab) (P < 0.01), caudate GMab (P < 0.05), and lateral and third ventricular (P < 0.05) volumetry were found in PIGD, compared with PD and HC. WMab, caudate and putamen GMab, and caudate, lateral, and third ventricular volumetry showed significant coefficients (P < 0.005) in linear regressions with balance and gait assessments in both patient groups. A model incorporating WMab, caudate GMab, and caudate GM discriminated PIGD from PD and HC with a sensitivity = 0.83 and specificity = 0.76 (AUC = 0.84). Data Conclusion Fast, unbiased quantification of microstructural brain changes in PD and PIGD is feasible using automated Vol‐BM. Composite lesion load in the white matter and caudate, and caudate volumetry discriminated PIGD from PD and HC, and showed potential in classification of these disorders using supervised machine learning. Level of Evidence: 1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2020;51:748–756.

The effect of the PARK16 rs11240572 variant on brain structure in Parkinson's disease

“…These results suggest that the rs11240572-A variant may slow down the progression of PD, consistent with previous reports suggesting that it has a protective function (Chang et al, 2013;Tan et al, 2010;Yan et al, 2011). The pathogenesis of PD involves the basal ganglia, including the caudate nucleus and putamen, resulting in impaired movement control (Fang et al 2020) as well as poor cognition such as impaired learning, planning, memory, and emotion (Obeso et al, 2008;Gao et al, 2017). Previous studies have found that PD patients have a variable GMV in the putamen, caudate nucleus, cerebellum and cerebral cortex.…”

Neuroimaging Detectable Differences between Parkinson's Disease Motor Subtypes: A Systematic Review

“…Furthermore, increased thalamic and GP volumes found in TD suggest this regional enlargement indicates that TD are initially protected from a damaged basal ganglia‐thalamocortical circuitry and could potentially explain why the TD subtype does not experience PIGD symptoms associated with BG degeneration 26 . These results are further supported by a recent lesion study showing PIGD patients have higher novel deep gray nuclear lesion load in the caudate compared to non‐PIGD and healthy controls (HC) 56 . GM analysis appears to support current PD circuitry models that underlie motor subtype differentiation of neuronal loss in key relay nuclei and stands as a valuable tool in the diagnostics and evaluation of PD subtypes.…”

“…When TD patients were compared to PIGD, PIGD patients were associated with additional degradations of white matter such as higher leukoaraiosis grade 53, 55 . More recently, when compared to non‐PIGD and HC, PIGD patients showed a significantly higher white matter lesion (WML) load 56 . In reference 27, researchers also showed PIGD to have higher WML volume compared to TD while reference 57 showed PIGD exhibited more WM degradation relative to TD.…”

Cognitive and motor correlates of grey and white matter pathology in Parkinson’s disease

“…Previous studies investigating the impact of MRI measures on cognitive and motor symptoms in PD have mostly been cross sectional in their WMH and GM assessments ( Zeighami et al, 2015 , Dadar et al, 2018a , de Schipper et al, 2019 , Toda et al, 2019 , Stojkovic et al, 2018 , Dadar, et al, 2020 , Zeighami et al, 2017 , Fang et al, 2020 , Wan et al, 2019 ), are mainly from the Parkinson's Progression Markers Initiative (PPMI) study which includes only de novo PD patients at baseline ( Zeighami et al, 2015 , Zeighami et al, 2019 , Dadar et al, 2018a , Dadar, et al, 2020 , Zeighami et al, 2017 , Chahine et al, 2019 ), and most don’t assess the impact of grey matter and white matter measures in the same setting ( Zeighami et al, 2015 , Zeighami et al, 2019 , de Schipper et al, 2019 , Pozorski et al, 2019 , Toda et al, 2019 , Stojkovic et al, 2018 , Dadar, et al, 2020 , Zeighami et al, 2017 , Wan et al, 2019 , Chahine et al, 2019 ). In comparison, there are several strengths to the present study.…”