Combination of Medical Imaging and Demographic Data for Parkinson’s Disease Diagnosis

Helena Rico Pereira, José Manuel Fonseca, Hugo Alexandre Ferreira

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)

Abstract

The identification of biomarkers to discriminate Parkinson’s Disease from other motor diseases is crucial to provide suitable treatment to patients. This study proposes a novel approach for the classification of structural Magnetic Resonance Imaging (MRI), Dopamine Transporter scan data (DaTscan) and demographic information (age and gender) to differentiate PD patients, “Scans Without Evidence for Dopaminergic Deficit” (SWEDD) patients and healthy control subjects using Convolutional Neural Networks (CNN). In Control vs PD, the accuracy of the classifier increased by adding subject gender from 94.5% to 96.0%, while in PD vs SWEDD adding age lead to 88.7% accuracy using slices encompassing the basal ganglia. The CNN was not able to successfully discriminate SWEDD vs Control. Our results suggested that pattern changes in slices encompassing the basal ganglia and the mesencephalon are relevant biomarkers for PD suggesting that this approach may have the potential to aid in PD biomarkers detection.

Original languageEnglish
Title of host publicationTechnological Innovation for Life Improvement - 11th IFIP WG 5.5/SOCOLNET Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020, Proceedings
EditorsLuis M. Camarinha-Matos, Nastaran Farhadi, Fábio Lopes, Helena Pereira
Place of PublicationCham
PublisherSpringer
Pages339-346
Number of pages8
ISBN (Electronic)978-3-030-45124-0
ISBN (Print)978-3-030-45123-3
DOIs
Publication statusPublished - 2020
Event11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020 - Costa de Caparica, Portugal
Duration: 1 Jul 20203 Jul 2020

Publication series

NameIFIP Advances in Information and Communication Technology
PublisherSpringer
Volume577
ISSN (Print)1868-4238
ISSN (Electronic)1868-422X

Conference

Conference11th Advanced Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2020
CountryPortugal
CityCosta de Caparica
Period1/07/203/07/20

Keywords

  • Convolutional Neural Networks
  • DaTscan SPECT
  • MRI
  • Parkinson’s Disease
  • SWEDD

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