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Related Concept Videos

Hemorrhagic Stroke l: Introduction01:17

Hemorrhagic Stroke l: Introduction

A hemorrhagic stroke is an acute neurological event that occurs when a weakened cerebral blood vessel ruptures, allowing blood to accumulate within or around the brain. The sudden release of blood forms a focal hematoma that increases intracranial pressure, displaces neural tissue, and can obstruct cerebrospinal fluid pathways. These effects may be compounded by intraventricular extension of the hemorrhage, cerebral edema, or compression of adjacent structures, all of which contribute to...

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Automated Cerebral Hemorrhage Detection Using RAPID.

J J Heit1, H Coelho2, F O Lima3

  • 1From the Department of Radiology, Neuroimaging, and Neurointervention Division (J.J.H.), Stanford University School of Medicine, Stanford, California jheit@stanford.edu.

AJNR. American Journal of Neuroradiology
|December 28, 2020
PubMed
Summary
This summary is machine-generated.

RAPID ICH, an AI tool, accurately detects intracranial hemorrhage (ICH) on head CT scans. It also precisely quantifies hemorrhage volume, aiding in expedited diagnosis and patient management.

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Area of Science:

  • Neuroradiology
  • Artificial Intelligence in Medicine
  • Medical Imaging Analysis

Background:

  • Intracranial hemorrhage (ICH) diagnosis relies on head computed tomography (CT) scans.
  • Increased CT utilization can delay timely ICH identification.
  • Automated tools are needed to expedite ICH diagnosis.

Purpose of the Study:

  • To evaluate the accuracy of RAPID ICH, an AI application, for detecting ICH on head non-contrast CT (NCCT).
  • To assess RAPID ICH's ability to quantify ICH volumes.
  • To determine if RAPID ICH can facilitate expedited ICH diagnosis.

Main Methods:

  • RAPID ICH analyzed NCCT scans for ICH detection.
  • Expert neuroradiologists provided consensus for criterion standard comparison.
  • RAPID ICH volumetric quantification was compared against manual segmentation by an expert.

Main Results:

  • RAPID ICH demonstrated high sensitivity (0.956) and specificity (0.953) for ICH detection.
  • The AI tool showed strong correlation (r=0.983) in volumetric quantification of hemorrhages.
  • Median absolute error for volume quantification was 3 mL.

Conclusions:

  • RAPID ICH is a highly accurate AI tool for detecting intracranial hemorrhage on NCCT.
  • The application provides precise volumetric quantification of intraparenchymal and intraventricular hemorrhages.
  • RAPID ICH shows potential for expediting ICH diagnosis and management.