An Automatic DWI/FLAIR Mismatch Assessment of Stroke Patients

Jacob Johansen*, Cecilie Mørck Offersen*, Jonathan Frederik Carlsen, Silvia Ingala, Adam Espe Hansen, Michael Bachmann Nielsen, Sune Darkner, Akshay Pai

*Corresponding author for this work

Abstract

DWI/FLAIR mismatch assessment for ischemic stroke patients shows promising results in determining if patients are eligible for recombinant tissue-type plasminogen activator (r-tPA) treatment. However, the mismatch criteria suffer from two major issues: binary classification of a non-binary problem and the subjectiveness of the assessor. In this article, we present a simple automatic method for segmenting stroke-related parenchymal hyperintensities on FLAIR, allowing for an automatic and continuous DWI/FLAIR mismatch assessment. We further show that our method's segmentations have comparable inter-rater agreement (DICE 0.820, SD 0.12) compared to that of two neuro-radiologists (DICE 0.856, SD 0.07), that our method appears robust to hyper-parameter choices (suggesting good generalizability), and lastly, that our methods continuous DWI/FLAIR mismatch assessment correlates to mismatch assessments made for a cohort of wake-up stroke patients at hospital submission. The proposed method shows promising results in automating the segmentation of parenchymal hyperintensity within ischemic stroke lesions and could help reduce inter-observer variability of DWI/FLAIR mismatch assessment performed in clinical environments as well as offer a continuous assessment instead of the current binary one.

Original languageEnglish
Article number69
JournalDiagnostics
Volume14
Issue number1
ISSN2075-4418
DOIs
Publication statusPublished - 27 Dec 2023

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