Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson’s disease using multi-atlas based segmentation

Sivaranjini, S.; Sujatha, C. M.

doi:10.1007/s11571-021-09671-4

Research Article
Published: 14 March 2021

Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson’s disease using multi-atlas based segmentation

Cognitive Neurodynamics volume 15, pages 835–845 (2021)Cite this article

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Abstract

Cognitive impairment in Parkinson’s Disease (PD) is the most prevalent non-motor symptom that requires analysis of anatomical associations to cognitive decline in PD. The objective of this study is to analyse the morphological variations of the subcortical structures to assess cognitive dysfunction in PD. In this study, T1 MR images of 58 Healthy Control (HC) and 135 PD subjects categorised as 91 Cognitively normal PD (NC-PD), 25 PD with Mild Cognitive Impairment (PD-MCI) and 19 PD with Dementia (PD-D) subjects, based on cognitive scores are utilised. The 132 anatomical regions are segmented using spatially localized multi-atlas model and volumetric analysis is carried out. The morphological alterations through textural features are captured to differentiate among the HC and PD subjects under different cognitive domains. The volumetric differences in the segmented subcortical structures of accumbens, amygdala, caudate, putamen and thalamus are able to predict cognitive impairment in PD. The volumetric distribution of the subcortical structures in PD-MCI subjects exhibit an overlap with the HC group due to lack of spatial specificity in their atrophy levels. The 3D GLCM features extracted from the significant subcortical structures could discriminate HC, NC-PD, PD-MCI and PD-D subjects with better classification accuracies. The disease related atrophy levels of the subcortical structures captured through morphological analysis provide sensitive evaluation of cognitive impairment in PD.

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Acknowledgements

Data used in the preparation of this article were obtained from the Parkinson’s Progression Markers Initiative (PPMI) database (www.ppmi-info.org/data). For up-to-date information on the study, visit www.ppmi-info.org. PPMI is a public-private partnership, funded by The Michael J. Fox Foundation for Parkinson’s Research and funding partners, including AbbVie, Allergan, Amathus, Avid, Biogen, BioLegend, Bristol-Myers Squibb, Celgene, Denali, GE Healthcare, Genentech, GSK, Golub Capital, Handle Therapeutics, Insitro, Janssen Neuroscience, Lilly, Lundbeck, Merck, Meso Scale Discovery, Neurocrine, Pfizer, Piramal, Prevail Therapeutics, Roche, Sanofi Genzyme, Servier, Takeda, TEVA, UCB, Verily and Voyager Therapeutics (www.ppmi-info.org/fundingpartners).

Funding

This work was supported by Anna Centenary Research Fellowship (Procs. No. CFR/ACRF/2018/AR1) offered by the Centre for Research, Anna University to S. Sivaranjini.

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Department of Electronics and Communication Engineering, College of Engineering (CEG), Anna University, Chennai, India
S. Sivaranjini & C. M. Sujatha

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S. Sivaranjini
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Sivaranjini, S., Sujatha, C.M. Morphological analysis of subcortical structures for assessment of cognitive dysfunction in Parkinson’s disease using multi-atlas based segmentation. Cogn Neurodyn 15, 835–845 (2021). https://doi.org/10.1007/s11571-021-09671-4

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Received: 11 September 2020
Revised: 27 January 2021
Accepted: 25 February 2021
Published: 14 March 2021
Issue Date: October 2021
DOI: https://doi.org/10.1007/s11571-021-09671-4

Keywords

Magnetic resonance imaging
Parkinson’s disease
Cognitive impairment
Morphology
Multi-atlas segmentation