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Evaluation of cerebral blood flow data in stroke patients using a mapping system
G Rosadini1, M Cossu, F De Carli
1Institute of Neurophysiopathology, University of Genova, Italy.
Stroke
|September 1, 1989
Summary
Analyzing regional cerebral blood flow (rCBF) in stroke patients, this study found that asymmetry analysis of rCBF data best identified the affected hemisphere. Combining multiple analysis methods achieved 91% sensitivity in detecting stroke-related changes.
Area of Science:
- Neurology
- Radiology
- Medical Imaging
Background:
- Stroke significantly impacts cerebral blood flow, necessitating accurate methods for assessing affected brain regions.
- Computed tomography (CT) provides structural information, but functional imaging is crucial for understanding blood flow dynamics.
Purpose of the Study:
- To evaluate the consistency of regional cerebral blood flow (rCBF) lateralization compared to computed tomographic (CT) imaging in stabilized stroke patients.
- To determine the most sensitive method for identifying the affected hemisphere using rCBF data.
Main Methods:
- Retrospective analysis of rCBF in 78 stabilized stroke patients using the xenon-133 inhalation technique.
- Data processed and analyzed using a custom computer-assisted system for real-time statistical analysis.
- Comparison of CT findings with rCBF lateralization assessed by absolute values, percent distribution, and asymmetries.
Main Results:
- Analysis of asymmetries in rCBF yielded the highest sensitivity (83.3%) for correctly identifying the affected hemisphere.
- Absolute values identified hypoperfusion in 48.7% of patients, while percent distribution identified it in 57.7%.
- Combining all three rCBF analysis methods achieved 91% sensitivity, with the remaining 9% showing other abnormalities.
Conclusions:
- rCBF asymmetry analysis is a sensitive method for lateralizing stroke effects.
- Combined analysis of rCBF data offers high sensitivity in detecting stroke-related cerebral blood flow abnormalities.
- While functional and structural imaging show good agreement, complete overlap should not be expected due to differing sensitivities and methodologies.