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Related Concept Videos

Brain Imaging01:14

Brain Imaging

235
Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans),  magnetic resonance imaging (MRI),  functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...
235

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Proposed Protocols for Artificial Intelligence Imaging Database in Acute Stroke Imaging.

Minjae Kim1, Seung Chai Jung1, Soo Chin Kim1

  • 1Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea.

Neurointervention
|October 17, 2023
PubMed
Summary
This summary is machine-generated.

Standardizing acute stroke imaging protocols is crucial for building artificial intelligence (AI) databases. Current practices vary significantly, necessitating common protocols for AI development in stroke care.

Keywords:
Acute strokeArtificial intelligenceCerebrovascular stroke

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Area of Science:

  • Neuroimaging
  • Artificial Intelligence in Medicine
  • Stroke Management

Background:

  • Significant heterogeneity exists in current acute stroke imaging protocols across South Korean tertiary hospitals.
  • Existing variations pose challenges for developing robust artificial intelligence (AI) databases for stroke diagnosis and management.
  • Evolving AI models require specific imaging sequences for accurate diagnostic and prognostic applications.

Purpose of the Study:

  • To propose standardized and feasible imaging protocols for constructing an artificial intelligence (AI) database in acute stroke.
  • To assess current acute stroke imaging practices in South Korean tertiary hospitals.
  • To review AI model requirements for stroke imaging data.

Main Methods:

  • A nationwide survey of 43 tertiary hospitals in South Korea regarding acute stroke imaging protocols (April-May 2021).
  • Assessment of imaging protocols for endovascular thrombectomy (EVT) in early/late windows and follow-up.
  • Review of clinical AI applications in stroke imaging and data requirements for AI model development.

Main Results:

  • Considerable heterogeneity observed in imaging protocols for EVT candidates, particularly in late time windows and posterior circulation stroke.
  • Computed tomography (CT)-based protocols were prevalent (70%), with single-session noncontrast CT, CT angiography, and CT perfusion being common.
  • Magnetic resonance imaging (MRI) use increased in late windows/posterior circulation; Diffusion-weighted imaging (DWI) and FLAIR were most frequent, but with variations.
  • AI diagnostic models primarily required noncontrast CT, CT angiography, and DWI; prognostic models additionally needed FLAIR, dynamic susceptibility contrast perfusion, and T1-weighted imaging (T1WI).

Conclusions:

  • Standardized and feasible imaging protocols are essential due to heterogeneity in current acute stroke imaging practices.
  • Essential sequences for AI database construction include noncontrast CT, DWI, CT/MR angiography, and CT/MR perfusion.
  • FLAIR and T1WI may be additionally required for specific AI applications, particularly prognostic modeling.