Prognostic Value of Combined Radiomic Features from Follow-Up DWI and T2-FLAIR in Acute Ischemic Stroke

Alessia Gerbasi*, Praneeta Konduri, Manon Tolhuisen, Fabiano Cavalcante, Leon Rinkel, Manon Kappelhof, Lennard Wolff, Jonathan M Coutinho, Bart J Emmer, Vincent Costalat, Caroline Arquizan, Jeannette Hofmeijer, Maarten Uyttenboogaart, Wim van Zwam, Yvo Roos, Silvana Quaglini, Riccardo Bellazzi, Charles Majoie, Henk Marquering, MR CLEAN-NO IV Investigators

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The biological pathways involved in lesion formation after an acute ischemic stroke (AIS) are poorly understood. Despite successful reperfusion treatment, up to two thirds of patients with large vessel occlusion remain functionally dependent. Imaging characteristics extracted from DWI and T2-FLAIR follow-up MR sequences could aid in providing a better understanding of the lesion constituents. We built a fully automated pipeline based on a tree ensemble machine learning model to predict poor long-term functional outcome in patients from the MR CLEAN-NO IV trial. Several feature sets were compared, considering only imaging, only clinical, or both types of features. Nested cross-validation with grid search and a feature selection procedure based on SHapley Additive exPlanations (SHAP) was used to train and validate the models. Considering features from both imaging modalities in combination with clinical characteristics led to the best prognostic model (AUC = 0.85, 95%CI [0.81, 0.89]). Moreover, SHAP values showed that imaging features from both sequences have a relevant impact on the final classification, with texture heterogeneity being the most predictive imaging biomarker. This study suggests the prognostic value of both DWI and T2-FLAIR follow-up sequences for AIS patients. If combined with clinical characteristics, they could lead to better understanding of lesion pathophysiology and improved long-term functional outcome prediction.

Original languageEnglish
Article number468
Number of pages14
JournalJournal of Cardiovascular Development and Disease
Volume9
Issue number12
DOIs
Publication statusPublished - 19 Dec 2022

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