Differential putaminal morphology in Huntington’s disease, frontotemporal dementia and Alzheimer’s disease

Abstract

Objective Direct neuronal loss or deafferentation of the putamen, a critical hub in corticostriatal circuits, may result in diverse and distinct cognitive and motoric dysfunction in neurodegenerative disease. Differential putaminal morphology, as a quantitative measure of corticostriatal integrity, may thus be evident in Huntington disease (HD), Alzheimer Disease (AD) and Frontotemporal Dementia (FTD), diseases with differential clinical dysfunction. Method HD (n=17), FTD (n=33) and AD (n=13) patients were diagnosed according to international consensus criteria, and with healthy controls (n=17), were scanned on the same MRI scanner. Patients underwent brief cognitive testing using the Neuropsychiatry unit cognitive assessment tool (NUCOG). Ten MRI scans from this dataset were manually segmented as a training set for the Adaboost algorithm, which automatically segmented all remaining scans for the putamen, yielding the following subset of the data: 9 left and 12 right putamen segmentations for AD; 25 left and 26 right putamina for FTD; 16 left and 15 right putamina for HD; 12 left and 12 right putamina for controls. Shape analysis was performed at each point on the surface of each structure using a multiple regression controlling for age and sex to compare radial distance across diagnostic groups. Results Age, but not sex and ICV, were significantly different in the segmentation subgroups by diagnosis. The AD group showed significantly poorer performance on cognitive testing than FTD. Mean putaminal volumes were HD<FTD<AD≤Controls, controlling for age and ICV. The greatest putaminal shape deflation was evident in HD, followed by FTD, in regions corresponding to the interconnections to motoric cortex. Conclusions Differential patterns of putaminal atrophy in HD, FTD and AD, with relevance to corticostriatal circuits, suggest the putamen may be a suitable clinical biomarker in neurodegenerative disease.

The power of neuroimaging biomarkers for screening frontotemporal dementia

“…Our analyses focused on logistic regression in an effort to facilitate interpretation, but future work is required to directly compare different types of statistical classifiers. Other studies have also focused on sophisticated analyses of an anatomical structure such as shape-based analyses of the hippocampus (Lindberg et al, 2012) or putamen (Looi et al, 2012) and these detailed anatomical analyses may prove to be more sensitive than voxelwise anatomical analyses such as those reported in this study.…”

Neuroimaging predictors of brain amyloidosis in mild cognitive impairment

“…These heterogeneities in the prediction model MCI cohort may have contributed to the brain amyloidosis and atrophy covariations in unexpected brain regions, including the midbrain and basal ganglia regions. 45,46 Validation cohort MCI subjects identified as having etiology other than AD and=or with nonmemory features presented with relatively lower sMRI-BAS (ie, mean sMRI-BAS of 21.73 compared to mean sMRI-BAS of 21.35 estimated for amnestic MCI due to AD), resulting in greater FPRs in predicting brain amyloidosis in this subgroup. A proper study with a larger sample size is warranted to better model the etiological and pathological heterogeneities in prediction of brain amyloidosis in MCI.…”

“…Specific to our prediction model cohort, 8% of the MCI subjects were diagnosed with additional nonmemory features, 6% were identified as due to etiology other than AD, and about 4% presented with depressive symptoms. These heterogeneities in the prediction model MCI cohort may have contributed to the brain amyloidosis and atrophy covariations in unexpected brain regions, including the midbrain and basal ganglia regions . Validation cohort MCI subjects identified as having etiology other than AD and/or with nonmemory features presented with relatively lower sMRI‐BAS (ie, mean sMRI‐BAS of −1.73 compared to mean sMRI‐BAS of −1.35 estimated for amnestic MCI due to AD), resulting in greater FPRs in predicting brain amyloidosis in this subgroup.…”

Striatal Atrophy in the Behavioural Variant of Frontotemporal Dementia: Correlation with Diagnosis, Negative Symptoms and Disease Severity

“…Following on from this theoretical work, in addition to recent studies investigating the pattern of cortical changes in bvFTD there have also been a number of studies specifically examining brain changes in subcortical structures in this disease [ 8 ]. Change in the striatum has been demonstrated, with caudate nucleus shape differences occurring in a pattern that differs from that of other neurodegenerative disorders [ 9 , 10 ] and differs within subtypes of FTLD [ 11 ]. Similar changes in the putamen have also been demonstrated [ 9 , 12 ], with striatal changes appearing to be more frequent in tau-positive disorder [ 13 ], but disproportionate caudate changes have also been observed in disease characterised by the fused in sarcoma protein (FUS) [ 14 ].…”

“…Change in the striatum has been demonstrated, with caudate nucleus shape differences occurring in a pattern that differs from that of other neurodegenerative disorders [ 9 , 10 ] and differs within subtypes of FTLD [ 11 ]. Similar changes in the putamen have also been demonstrated [ 9 , 12 ], with striatal changes appearing to be more frequent in tau-positive disorder [ 13 ], but disproportionate caudate changes have also been observed in disease characterised by the fused in sarcoma protein (FUS) [ 14 ]. Resting state fMRI studies support the concept of a diaschisis between cortical and subcortical structures driving some of the behavioural symptoms of bvFTD and other dementias, showing that specific intrinsic connectivity networks tend to degenerate in cortical and subcortical areas as a group [ 15 , 16 ].…”