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Related Experiment Video

Updated: Sep 3, 2025

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
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Automated Supra- and Infratentorial Brain Infarct Volume Estimation on Diffusion Weighted Imaging Using the RAPID

Lehel Lakatos1, Manuel Bolognese1, Martin Müller1

  • 1Department of Neurology and Neurorehabilitation, Lucerne Kantonsspital, Lucerne, Switzerland.

Frontiers in Neurology
|July 25, 2022
PubMed
Summary
This summary is machine-generated.

The RAPID AI software shows promise for estimating infarct size in vertebrobasilar ischemia (VBI) and supratentorial ischemia (STI) using diffusion-weighted imaging (DWI). However, small ischemic lesions under 2 ml remain undetected by RAPID.

Keywords:
MRIinterobserver agreementstrokevertebrobasilar artery systemvolume measure

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Area of Science:

  • Neurology
  • Radiology
  • Artificial Intelligence in Medicine

Background:

  • Computerized techniques for estimating ischemic lesion volume, particularly in vertebrobasilar ischemia (VBI), have limitations.
  • Diffusion-weighted imaging (DWI) is a key modality for assessing stroke, but automated analysis accuracy varies.
  • Vertebrobasilar ischemia (VBI) presents unique challenges for infarct volume estimation compared to supratentorial ischemia (STI).

Purpose of the Study:

  • To evaluate the accuracy of RAPID AI software in estimating infarct size in VBI using DWI.
  • To compare the performance of RAPID AI in VBI versus supratentorial ischemia (STI).
  • To assess the reliability of automated infarct volume calculation against manual methods.

Main Methods:

  • 123 stroke patients (41 VBI, 82 STI) underwent DWI.
  • Infarct volumes calculated by RAPID AI were compared to manual estimations by two neurologists using the ABC/2 method.
  • Statistical analyses included intraclass correlation coefficient (ICC), area under the curve (AUC), and Bland-Altman plots.

Main Results:

  • High inter-reader reliability was observed for neurologists and between neurologists and RAPID in the STI group (ICC > 0.946).
  • Reliability was lower but still significant in the VBI group (ICC > 0.757).
  • RAPID AI failed to detect infarct volumes ≤ 2 ml in both VBI and STI cases.

Conclusions:

  • RAPID AI demonstrates comparable performance in estimating infarct size for both VBI and STI on DWI.
  • The software's ability to detect small lesions (≤ 2 ml) remains a limitation in both cerebrovascular territories.
  • Further refinement of AI algorithms is needed for comprehensive infarct volume assessment in all stroke types.