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The Journal of Headache and Pain

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Open Access 01-12-2023 | Aura | Research

Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging data

Authors: Katarina Mitrović, Andrej M. Savić, Aleksandra Radojičić, Marko Daković, Igor Petrušić

Published in: The Journal of Headache and Pain | Issue 1/2023

Abstract

Background

Previous studies have developed the Migraine Aura Complexity Score (MACS) system. MACS shows great potential in studying the complexity of migraine with aura (MwA) pathophysiology especially when implemented in neuroimaging studies. The use of sophisticated machine learning (ML) algorithms, together with deep profiling of MwA, could bring new knowledge in this field. We aimed to test several ML algorithms to study the potential of structural cortical features for predicting the MACS and therefore gain a better insight into MwA pathophysiology.

Methods

The data set used in this research consists of 340 MRI features collected from 40 MwA patients. Average MACS score was obtained for each subject. Feature selection for ML models was performed using several approaches, including a correlation test and a wrapper feature selection methodology. Regression was performed with the Support Vector Machine (SVM), Linear Regression, and Radial Basis Function network.

Results

SVM achieved a 0.89 coefficient of determination score with a wrapper feature selection. The results suggest a set of cortical features, located mostly in the parietal and temporal lobes, that show changes in MwA patients depending on aura complexity.

Conclusions

The SVM algorithm demonstrated the best potential in average MACS prediction when using a wrapper feature selection methodology. The proposed method achieved promising results in determining MwA complexity, which can provide a basis for future MwA studies and the development of MwA diagnosis and treatment.

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Title: Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging data
Authors: Katarina Mitrović
Andrej M. Savić
Aleksandra Radojičić
Marko Daković
Igor Petrušić
Publication date: 01-12-2023
Publisher: Springer Milan
Keywords: Aura
Migraine
Magnetic Resonance Imaging
Magnetic Resonance Imaging
Published in: The Journal of Headache and Pain / Issue 1/2023
Print ISSN: 1129-2369
Electronic ISSN: 1129-2377
DOI: https://doi.org/10.1186/s10194-023-01704-z

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Machine learning approach for Migraine Aura Complexity Score prediction based on magnetic resonance imaging data

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

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