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Updated: Jan 18, 2026
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Assessing Cortical Cerebral Microinfarcts on High Resolution MR Images
Published on: November 20, 2015
13.9K
Cerebral microstructural alterations as an imaging biomarker for Post-COVID-condition.
Alexander Rau1, Philipp G Arnold2, Sibylle Frase3
1Department of Neuroradiology, Faculty of Medicine, Medical Center-University of Freiburg, University of Freiburg, Freiburg, Germany.
Scientific Reports
|September 12, 2025
Summary
Researchers developed an imaging biomarker approach to diagnose Post-COVID-condition (PCC) using MRI scans. Microstructural imaging metrics showed high accuracy in differentiating PCC patients from controls, paving the way for potential clinical tools.
Area of Science:
- Neuroimaging
- Biomarker Discovery
- Medical Diagnostics
Background:
- Post-COVID-condition (PCC) presents a significant challenge in diagnosis and management.
- Objective diagnostic tools are needed to identify individuals with PCC.
- Magnetic Resonance Imaging (MRI) offers potential for identifying neuroimaging biomarkers.
Purpose of the Study:
- To develop and validate an imaging biomarker-based approach for diagnosing Post-COVID-condition (PCC) at the individual patient level.
- To identify specific MRI metrics and brain regions that can differentiate PCC patients from healthy controls.
- To assess the diagnostic performance of a machine learning model trained on these imaging biomarkers.
Main Methods:
- Prospective cohort study comparing PCC patients (n=89) with unimpaired COVID-19 survivors (n=38).
- Acquisition and analysis of MRI data including macrostructure, diffusion tensor imaging (DTI), and multi-shell microstructure imaging.
- Training a linear support vector machine (SVM) using extracted atlas-based imaging metrics.
Main Results:
- Microstructural imaging parameters yielded the highest diagnostic performance.
- The optimal SVM model achieved an Area Under the Receiver Operating Characteristic Curve (AUROC) of 0.95, with 94% sensitivity and 85% specificity.
- Key discriminatory regions included gray matter areas (cortical regions, putamen, thalamus) and white matter tracts (corpus callosum, frontal white matter).
Conclusions:
- Microstructural MRI data analyzed with SVM can effectively differentiate PCC patients from controls with high sensitivity.
- The findings represent a significant advancement toward a biomarker-based diagnosis of PCC.
- Further validation in larger, multicentric cohorts is necessary due to moderate specificity and monocentric design before clinical application.
