A Machine Learning Approach to Predict Acute Ischemic Stroke Thrombectomy Reperfusion using Discriminative MR Image Features

Haoyue Zhang, Jennifer Polson, Kambiz Nael, Noriko Salamon, Bryan Yoo, William Speier, Corey Arnold

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Mechanical thrombectomy (MTB) is one of the two standard treatment options for Acute Ischemic Stroke (AIS) patients. Current clinical guidelines instruct the use of pretreatment imaging to characterize a patient's cerebrovascular flow, as there are many factors that may underlie a patient's successful response to treatment. There is a critical need to leverage pretreatment imaging, taken at admission, to guide potential treatment avenues in an automated fashion. The aim of this study is to develop and validate a fully automated machine learning algorithm to predict the final modified thrombolysis in cerebral infarction (mTICI) score following MTB. A total 321 radiomics features were computed from segmented pretreatment MRI scans for 141 patients. Successful recanalization was defined as mTICI score >= 2c. Different feature selection methods and classification models were examined in this study. Our best performance model achieved 74.42±2.52% AUC, 75.56±4.44% sensitivity, and 76.75±4.55% specificity, showing a good prediction of reperfusion quality using pretreatment MRI. Results suggest that MR images can be informative to predicting patient response to MTB, and further validation with a larger cohort can determine the clinical utility.

Original languageEnglish (US)
Title of host publicationBHI 2021 - 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665403580
DOIs
StatePublished - 2021
Event2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021 - Virtual, Online, Greece
Duration: Jul 27 2021Jul 30 2021

Publication series

NameBHI 2021 - 2021 IEEE EMBS International Conference on Biomedical and Health Informatics, Proceedings

Conference

Conference2021 IEEE EMBS International Conference on Biomedical and Health Informatics, BHI 2021
Country/TerritoryGreece
CityVirtual, Online
Period7/27/217/30/21

Keywords

  • Machine learning
  • Radiomics
  • Stroke treatment
  • Structural MRI

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Health Informatics
  • Health(social science)

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