Towards a Novel Way to Predict Deficits After a Brain Lesion: A Stroke Example

Georgios Klados, Michalis E. Zervakis, Rosalia Dacosta-Aguayo, Antonio Fratini, Manousos Klados

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

Many studies have addressed the relations between different human brain regions and their role in cognitive, motor and sensory functions in patients that have suffered a brain lesion (stroke, traumatic brain injury, tissue removal). Nowadays, it is well established that the brain works as a network and the symptoms in a person are a combination of the direct impact of the lesion in a single region and its connectivity with other healthy brain regions. The aim of the present study is the development of a user-friendly desktop application to predict the induced cognitive deficits in patients who have suffered a brain lesion. The herein presented application is based on Neurosynth platform, and takes as an input a MRI mask that describes a lesion. Then our software exploits the knowledge that already exists in Neurosynth platform, so as to predict the potential deficits by grouping the Neurosynth's terms that have increased Z scores with our mask. In addition, we have embedded two types of visualization methods: One to present the slices of the brain mask and another to show the 3D volume of the mask into 3D semitransparent human brain. The added value of the presented application is that it may give us a clue about which mechanisms are probably affected by a lesion in a specific region, while in the future it could provide neurosurgeons with insightful knowledge helping them in the plannification of a forthcoming surgical procedure. The proposed software was tested on 7 stroke patients, predicting accurately the 91% of the measured deficits found during a neuropsychological assessment.
Original languageEnglish
Title of host publication2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE)
PublisherIEEE
ISBN (Electronic)978-1-7281-4617-1
ISBN (Print)978-1-7281-4618-8
DOIs
Publication statusPublished - 26 Dec 2019
Event2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE). -
Duration: 28 Oct 201930 Oct 2019

Publication series

Name2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE)
PublisherIEEE
ISSN (Print)2159-5410
ISSN (Electronic)2471-7819

Conference

Conference2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE).
Period28/10/1930/10/19

Bibliographical note

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  • Cite this

    Klados, G., Zervakis, M. E., Dacosta-Aguayo, R., Fratini, A., & Klados, M. (2019). Towards a Novel Way to Predict Deficits After a Brain Lesion: A Stroke Example. In 2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE) (2019 IEEE 19th International Conference on Bioinformatics and Bioengineering (BIBE)). IEEE. https://doi.org/10.1109/BIBE.2019.00138