Clinical Research Collaboration for Stroke in Korea Imaging Repository:A Prospective Multicenter Neuroimaging Repository

Journal: medRxiv
Published Date:

Abstract

Background: Prospective stroke registries have advanced our understanding of cerebrovascular disease, yet most reduce neuroimaging to categorical variables, forfeiting the multidimensional information inherent in clinical imaging. We describe the CRCS-K Imaging Repository, a prospective multicenter platform that systematically collects all stroke neuroimaging and integrates artificial intelligence (AI)-based automated quantification with clinical and outcome data through a dedicated research platform, AISCAN. Methods: Building upon the Clinical Research Collaboration for Stroke in Korea (CRCS-K), a nationwide prospective registry, all neuroimaging (computed tomography [CT], magnetic resonance [MR], and angiography) performed during index hospitalization of consecutive acute ischemic stroke patients was collected from 18 comprehensive stroke centers. Imaging underwent centralized quality verification, sequence classification, and AI-based quantification. As a proof-of-concept application, we examined the association between pre-treatment imaging modality, treatment workflow efficiency, and functional outcomes in patients receiving intravenous thrombolysis (IVT) or endovascular treatment (EVT). Results: From June 2022 through May 2025, 225,159 imaging sequences were collected from 20,792 patients. AI-based quantification modules converted these into standardized numeric features encompassing ischemic lesion volumes, perfusion parameters, white matter hyperintensity burden, and cerebral microbleed counts. Substantial inter-hospital variation in imaging modality selection was observed, with MR-first workflows ranging from 1.0% to 56.7% across centers. In the proof-of-concept analysis, each additional imaging sequence was associated with prolonged door-to-treatment times for both IVT and EVT. Propensity score overlap-weighted analyses suggested numerically more favorable functional outcomes with CT-based imaging among EVT-treated patients, whereas differences among IVT-treated patients were smaller and less consistent. Conclusions: The CRCS-K Imaging Repository demonstrates the feasibility of large-scale, prospective neuroimaging collection integrated with AI-based quantification and clinical data. The infrastructure enables clinically consequential questions that conventional registries cannot address.

Authors

  • Kim
  • B. J.; Ryu
  • W.-S.; Lee
  • M.; Kang
  • K.; Kim
  • J. G.; Lee
  • S. J.; Cha
  • J.-K.; Park
  • T. H.; Lee
  • J.-Y.; Lee
  • K.; Kwon
  • D. H.; Lee
  • J.; Park
  • H.-K.; Cho
  • Y.-J.; Hong
  • K.-S.; Lee
  • M.; Oh
  • M. S.; Yu
  • K.-H.; Gwak
  • D.-S.; Kim
  • D.-E.; Kim
  • H.; Kim
  • J.-T.; Kim
  • J.-G.; Choi
  • J. C.; Kim
  • W.-J.; Weon
  • Y. C.; Kwon
  • J.-H.; Yum
  • K. S.; Shin
  • D.-I.; Hong
  • J.-H.; Sohn
  • S.-I.; Lee
  • S.-H.; Kim
  • C.; Jeong
  • H.-B.; Park
  • K.-Y.; Kim
  • C. K.; Kang
  • J.; Kim
  • J. Y.; Kim
  • D. Y.; Kim
  • J.; Kim
  • N.; Menon
  • B. K.; Lin
  • L.; Parsons
  • M.; Bae
  • H.-J.

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