TY - JOUR

T1 - An Automatic DWI/FLAIR Mismatch Assessment of Stroke Patients

AU - Johansen, Jacob

AU - Offersen, Cecilie Mørck

AU - Carlsen, Jonathan Frederik

AU - Ingala, Silvia

AU - Hansen, Adam Espe

AU - Nielsen, Michael Bachmann

AU - Darkner, Sune

AU - Pai, Akshay

N1 - Publisher Copyright: © 2023 by the authors.

PY - 2024

Y1 - 2024

N2 - 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.

AB - 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.

KW - DWI/FLAIR mismatch

KW - ischemic stroke

KW - MRI

KW - r-tPA

KW - wake-up stroke

U2 - 10.3390/diagnostics14010069

DO - 10.3390/diagnostics14010069

M3 - Journal article

C2 - 38201378

AN - SCOPUS:85181902212

VL - 14

JO - Diagnostics

JF - Diagnostics

SN - 2075-4418

IS - 1

M1 - 69

ER -