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Human disease: frontotemporal dementia3
Predicting behavioral variant frontotemporal dementia with pattern classification in multi-center structural MRI data.
LIFE Adult

Abstract (Expand)

PURPOSE: Frontotemporal lobar degeneration (FTLD) is a common cause of early onset dementia. Behavioral variant frontotemporal dementia (bvFTD), its most common subtype, is characterized by deep … alterations in behavior and personality. In 2011, new diagnostic criteria were suggested that incorporate imaging criteria into diagnostic algorithms. The study aimed at validating the potential of imaging criteria to individually predict diagnosis with machine learning algorithms. MATERIALS & METHODS: Brain atrophy was measured with structural magnetic resonance imaging (MRI) at 3 Tesla in a multi-centric cohort of 52 bvFTD patients and 52 healthy control subjects from the German FTLD Consortium's Study. Beside group comparisons, diagnosis bvFTD vs. controls was individually predicted in each subject with support vector machine classification in MRI data across the whole brain or in frontotemporal, insular regions, and basal ganglia known to be mainly affected based on recent meta-analyses. Multi-center effects were controlled for with a new method, "leave one center out" conjunction analyses, i.e. repeatedly excluding subjects from each center from the analysis. RESULTS: Group comparisons revealed atrophy in, most consistently, the frontal lobe in bvFTD beside alterations in the insula, basal ganglia and temporal lobe. Most remarkably, support vector machine classification enabled predicting diagnosis in single patients with a high accuracy of up to 84.6%, where accuracy was highest in a region-of-interest approach focusing on frontotemporal, insular regions, and basal ganglia in comparison with the whole brain approach. CONCLUSION: Our study demonstrates that MRI, a widespread imaging technology, can individually identify bvFTD with high accuracy in multi-center imaging data, paving the road to personalized diagnostic approaches in the future.

Authors: S. Meyer, K. Mueller, K. Stuke, S. Bisenius, J. Diehl-Schmid, F. Jessen, J. Kassubek, J. Kornhuber, A. C. Ludolph, J. Prudlo, A. Schneider, K. Schuemberg, I. Yakushev, M. Otto, M. L. Schroeter

Date Published: 29th Mar 2017

Publication Type: Journal article

Human Diseases: frontotemporal dementia

Frontomedian cortex is central for moral deficits in behavioural variant frontotemporal dementia.
LIFE Adult

Abstract

Not specified

Authors: M. L. Schroeter, D. Bzdok, S. B. Eickhoff, J. Neumann

Date Published: 25th Sep 2014

Publication Type: Not specified

Human Diseases: frontotemporal dementia

Conceptualizing neuropsychiatric diseases with multimodal data-driven meta-analyses - the case of behavioral variant frontotemporal dementia.
LIFE Adult

Abstract (Expand)

INTRODUCTION: Uniform coordinate systems in neuroimaging research have enabled comprehensive systematic and quantitative meta-analyses. Such approaches are particularly relevant for neuropsychiatric … diseases, the understanding of their symptoms, prediction and treatment. Behavioral variant frontotemporal dementia (bvFTD), a common neurodegenerative syndrome, is characterized by deep alterations in behavior and personality. Investigating this 'nexopathy' elucidates the healthy social and emotional brain. METHODS: Here, we combine three multimodal meta-analyses approaches - anatomical and activation likelihood estimates and behavioral domain profiles - to identify neural correlates of bvFTD in 417 patients and 406 control subjects and to extract mental functions associated with this disease by meta-analyzing functional activation studies in the comprehensive probabilistic functional brain atlas of the BrainMap database. RESULTS: The analyses identify the frontomedian cortex, basal ganglia, anterior insulae and thalamus as most relevant hubs, with a regional dissociation between atrophy and hypometabolism. Neural networks affected by bvFTD were associated with emotion and reward processing, empathy and executive functions (mainly inhibition), suggesting these functions as core domains affected by the disease and finally leading to its clinical symptoms. In contrast, changes in theory of mind or mentalizing abilities seem to be secondary phenomena of executive dysfunctions. CONCLUSIONS: The study creates a novel conceptual framework to understand neuropsychiatric diseases by powerful data-driven meta-analytic approaches that shall be extended to the whole neuropsychiatric spectrum in the future.

Authors: M. L. Schroeter, A. R. Laird, C. Chwiesko, C. Deuschl, E. Schneider, D. Bzdok, S. B. Eickhoff, J. Neumann

Date Published: 26th Apr 2014

Publication Type: Not specified

Human Diseases: frontotemporal dementia

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