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Related Concept Videos

Ischemic Stroke ll: Pathophysiology01:15

Ischemic Stroke ll: Pathophysiology

An ischemic stroke occurs when a cerebral blood vessel becomes obstructed, most often by a thrombus or embolus, interrupting the delivery of oxygen and glucose to brain tissue. Because neurons rely on continuous aerobic metabolism, energy failure begins within minutes of reduced perfusion. The region receiving the least blood flow becomes the infarct core, an area of irreversible cellular death. Surrounding this core lies the penumbra, a zone of hypoperfused but still viable tissue that is...
Ischemic Stroke l: Introduction01:15

Ischemic Stroke l: Introduction

Ischemic stroke is an acute cerebrovascular condition in which blood flow to a brain region is suddenly interrupted, leading to tissue infarction. Neurons depend on continuous oxygen and glucose supply, so even brief reductions in perfusion cause energy failure, ionic imbalance, and irreversible injury. Ischemic strokes are classified into thrombotic and embolic types based on their underlying mechanisms.Thrombotic MechanismsThrombotic stroke develops when a clot forms within a cerebral artery.
Stroke: Introduction and Types01:29

Stroke: Introduction and Types

A stroke is an acute neurological event caused by the sudden disruption of cerebral blood flow, leading to rapid loss of neuronal function. Neurons depend on continuous oxygen and glucose supply, so even brief interruptions can cause irreversible injury within minutes. Strokes are classified into ischemic and hemorrhagic types.Ischemic StrokeIschemic strokes are most common and occur due to arterial occlusion, depriving brain tissue of oxygen and nutrients. This leads to energy failure, ionic...

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Related Experiment Video

Updated: May 11, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping

Published on: September 25, 2019

Acute stroke: automatic perfusion lesion outlining using level sets.

Kim Mouridsen1, Kartheeban Nagenthiraja, Kristjana Ýr Jónsdóttir

  • 1Center of Functionally Integrative Neuroscience, Department of Neuroradiology, Århus University Hospital, Nørrebrogade 44, Bldg 10G, 5th Floor, DK-8000 Århus C, Denmark.

Radiology
|May 21, 2013
PubMed
Summary
This summary is machine-generated.

A new algorithm accurately outlines hypoperfused tissue on perfusion-weighted images, outperforming standard methods for acute stroke assessment. This automated approach improves the evaluation of perfusion lesions in stroke patients.

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Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke
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Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Published on: June 2, 2023

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Last Updated: May 11, 2026

Brain Infarct Segmentation and Registration on MRI or CT for Lesion-symptom Mapping
10:25

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Published on: September 25, 2019

Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke
06:45

Integrated Photoacoustic, Ultrasound, and Angiographic Tomography (PAUSAT) for NonInvasive Whole-Brain Imaging of Ischemic Stroke

Published on: June 2, 2023

Area of Science:

  • Medical Imaging
  • Neurology
  • Radiology

Background:

  • Accurate delineation of hypoperfused tissue is crucial for acute stroke treatment.
  • Existing methods for outlining perfusion lesions may lack user independence and optimal performance.

Purpose of the Study:

  • To develop a user-independent algorithm for delineating hypoperfused tissue on perfusion-weighted images.
  • To evaluate the algorithm's performance against a standard threshold method in simulated and clinical data.

Main Methods:

  • An algorithm was developed to identify hypoperfused tissue by minimizing mean square error around a smooth boundary in mean transit time maps.
  • Performance was assessed in 14 acute stroke patients using volumetric (Bland-Altman) and spatial (Dice coefficient) agreement with manual outlines.
  • Comparison with a standard threshold approach was conducted using the Wilcoxon signed rank test.

Main Results:

  • The automated algorithm demonstrated superior performance with a higher Dice coefficient (0.71) compared to the threshold approach (0.50).
  • Volumetric agreement between automated and manual outlines showed a mean difference of -9.0 mL ± 44.5 mL.
  • Expert consensus for lesion outlines yielded a Dice coefficient of 0.79.

Conclusions:

  • The developed user-independent algorithm provides accurate delineation of perfusion lesions, comparable to expert consensus.
  • This automated method is superior to the standard threshold approach for assessing perfusion images in acute stroke.
  • The algorithm has the potential to enhance the assessment of perfusion imaging in acute stroke management.