Statistical prediction of tissue fate in acute ischemic brain injury
UMass Chan Affiliations
Department of NeurologyDocument Type
Journal ArticlePublication Date
2005-04-15Keywords
AlgorithmsAnimals
Brain Ischemia
Cerebrovascular Circulation
Cluster Analysis
*Diffusion Magnetic Resonance Imaging
Infarction, Middle Cerebral Artery
Male
*Models, Statistical
Probability
Prognosis
Rats
Rats, Sprague-Dawley
Regional Blood Flow
Stroke
Neurology
Statistics and Probability
Metadata
Show full item recordAbstract
An algorithm was developed to statistically predict ischemic tissue fate on a pixel-by-pixel basis. Quantitative high-resolution (200 x 200 microm) cerebral blood flow (CBF) and apparent diffusion coefficient (ADC) were measured on acute stroke rats subjected to permanent middle cerebral artery occlusion and an automated clustering (ISODATA) technique was used to classify ischemic tissue types. Probability and probability density profiles were derived from a training data set (n=6) and probability maps of risk of subsequent infarction were computed in another group of animals (n=6) as ischemia progressed. Predictions were applied to overall tissue fate. Performance measures (sensitivity, specificity, and receiver operating characteristic) showed that prediction made based on combined ADC+CBF data outperformed those based on ADC or CBF data alone. At the optimal operating points, combined ADC+CBF predicted tissue infarction with 86%+/-4% sensitivity and 89%+/-6% specificity. More importantly, probability of infarct (P(I)) for different ISODATA-derived ischemic tissue types were also computed: (1) For the 'normal' cluster in the ischemic right hemisphere, P(I) based on combined ADC+CBF data (P(I)[ADC+CBF]) accurately reflected tissue fate, whereas P(I)[ADC] and P(I)[CBF] overestimated infarct probability. (2) For the 'perfusion-diffusion mismatch' cluster, P(I)[ADC+CBF] accurately predicted tissue fate, whereas P(I)[ADC] underestimated and P(I)[CBF] overestimated infarct probability. (3) For the core cluster, P(I)[ADC+CBF], P(I)[ADC], and P(I)[CBF] prediction were high and similar ( approximately 90%). This study shows an algorithm to statistically predict overall, normal, ischemic core, and 'penumbral' tissue fate using early quantitative perfusion and diffusion information. It is suggested that this approach can be applied to stroke patients in a computationally inexpensive manner.Source
J Cereb Blood Flow Metab. 2005 Oct;25(10):1336-45. Link to article on publisher's siteDOI
10.1038/sj.jcbfm.9600126Permanent Link to this Item
http://hdl.handle.net/20.500.14038/37630PubMed ID
15829912Related Resources
Link to article in PubMedae974a485f413a2113503eed53cd6c53
10.1038/sj.jcbfm.9600126