TY - JOUR
T1 - Outcome Prediction Based on Automatically Extracted Infarct Core Image Features in Patients with Acute Ischemic Stroke
AU - Tolhuisen, Manon L.
AU - Hoving, Jan W.
AU - Koopman, Miou S.
AU - Kappelhof, Manon
AU - van Voorst, Henk
AU - Bruggeman, Agnetha E.
AU - Demchuck, Adam M.
AU - Dippel, Diederik W.J.
AU - Emmer, Bart J.
AU - Bracard, Serge
AU - Guillemin, Francis
AU - van Oostenbrugge, Robert J.
AU - Mitchell, Peter J.
AU - van Zwam, Wim H.
AU - Hill, Michael D.
AU - Roos, Yvo B.W.E.M.
AU - Jovin, Tudor G.
AU - Berkhemer, Olvert A.
AU - Campbell, Bruce C.V.
AU - Saver, Jeffrey
AU - White, Phil
AU - Muir, Keith W.
AU - Goyal, Mayank
AU - Marquering, Henk A.
AU - Majoie, Charles B.
AU - Caan, Matthan W.A.
AU - on behalf of the, CLEAN NO IV and HERMES investigators
N1 - Funding Information:
The CONTRAST consortium is supported by the Netherlands Cardiovascular Research Initiative (CVON), an initiative of the Dutch Heart Foundation, and by the Brain Foundation Netherlands, Medtronic, and Cerenovus. AMC and Erasmus MC received additional unrestricted funding on behalf of CONTRAST for the execution of MR CLEAN-NO IV from Stryker European Operations BV.
Publisher Copyright:
© 2022 by the authors.
PY - 2022/7/23
Y1 - 2022/7/23
N2 - Infarct volume (FIV) on follow-up diffusion-weighted imaging (FU-DWI) is only moderately associated with functional outcome in acute ischemic stroke patients. However, FU-DWI may contain other imaging biomarkers that could aid in improving outcome prediction models for acute ischemic stroke. We included FU-DWI data from the HERMES, ISLES, and MR CLEAN-NO IV databases. Lesions were segmented using a deep learning model trained on the HERMES and ISLES datasets. We assessed the performance of three classifiers in predicting functional independence for the MR CLEAN-NO IV trial cohort based on: (1) FIV alone, (2) the most important features obtained from a trained convolutional autoencoder (CAE), and (3) radiomics. Furthermore, we investigated feature importance in the radiomic-feature-based model. For outcome prediction, we included 206 patients: 144 scans were included in the training set, 21 in the validation set, and 41 in the test set. The classifiers that included the CAE and the radiomic features showed AUC values of 0.88 and 0.81, respectively, while the model based on FIV had an AUC of 0.79. This difference was not found to be statistically significant. Feature importance results showed that lesion intensity heterogeneity received more weight than lesion volume in outcome prediction. This study suggests that predictions of functional outcome should not be based on FIV alone and that FU-DWI images capture additional prognostic information.
AB - Infarct volume (FIV) on follow-up diffusion-weighted imaging (FU-DWI) is only moderately associated with functional outcome in acute ischemic stroke patients. However, FU-DWI may contain other imaging biomarkers that could aid in improving outcome prediction models for acute ischemic stroke. We included FU-DWI data from the HERMES, ISLES, and MR CLEAN-NO IV databases. Lesions were segmented using a deep learning model trained on the HERMES and ISLES datasets. We assessed the performance of three classifiers in predicting functional independence for the MR CLEAN-NO IV trial cohort based on: (1) FIV alone, (2) the most important features obtained from a trained convolutional autoencoder (CAE), and (3) radiomics. Furthermore, we investigated feature importance in the radiomic-feature-based model. For outcome prediction, we included 206 patients: 144 scans were included in the training set, 21 in the validation set, and 41 in the test set. The classifiers that included the CAE and the radiomic features showed AUC values of 0.88 and 0.81, respectively, while the model based on FIV had an AUC of 0.79. This difference was not found to be statistically significant. Feature importance results showed that lesion intensity heterogeneity received more weight than lesion volume in outcome prediction. This study suggests that predictions of functional outcome should not be based on FIV alone and that FU-DWI images capture additional prognostic information.
UR - http://www.scopus.com/inward/record.url?scp=85137408323&partnerID=8YFLogxK
U2 - 10.3390/diagnostics12081786
DO - 10.3390/diagnostics12081786
M3 - Article
C2 - 35892499
AN - SCOPUS:85137408323
SN - 2075-4418
VL - 12
JO - Diagnostics
JF - Diagnostics
IS - 8
M1 - 1786
ER -