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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...

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Related Experiment Video

Updated: Jun 27, 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

Understanding CT Perfusion in Acute Ischemic Stroke: How Algorithms Shape Perfusion Maps.

Nicola Morelli1, Marco Spallazzi2, Marina Biondi1

  • 1Neuroradiology Unit, Guglielmo da Saliceto Hospital, 29121 Piacenza, Italy.

Diagnostics (Basel, Switzerland)
|June 26, 2026
PubMed
Summary
This summary is machine-generated.

CT perfusion (CTP) algorithms estimate ischemic stroke tissue, but results vary by software and methods. Integrate CTP findings with other clinical data for accurate treatment decisions.

Keywords:
Bayesian algorithmCT perfusionTmaxacute ischemic strokedeconvolutionischemic coreperfusion imagingstroke imaging

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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:

  • Neuroradiology
  • Medical Imaging Analysis

Background:

  • CT perfusion (CTP) is crucial for acute ischemic stroke treatment selection, especially beyond standard timeframes.
  • Automated CTP maps are estimations, not direct measures of irreversible tissue damage.
  • Algorithm choices significantly impact perfusion map interpretation.

Purpose of the Study:

  • To explain how CTP algorithms influence ischemic core and hypoperfused tissue estimation.
  • To highlight variability in CTP outputs due to different algorithms and software.
  • To guide clinicians in interpreting CTP findings for stroke management.

Main Methods:

  • Review of CTP algorithms, including deconvolution strategies, temporal correction, and dispersion handling.
  • Focus on singular value decomposition (SVD) and Bayesian approaches.
  • Analysis of timing parameters like Tmax, Delay, TTP, and MTT.

Main Results:

  • Differences in residue function estimation and thresholding lead to variable CTP outputs across platforms.
  • Perfusion thresholds are not universally interchangeable.
  • Algorithm-specific parameters critically shape the final perfusion maps.

Conclusions:

  • CTP findings are estimates influenced by algorithmic choices and software.
  • Perfusion thresholds require careful, context-specific interpretation.
  • Integrate CTP with clinical data, CTA, and treatment context for optimal decision support.