Predicting Final Extent of Ischemic Infarction Using Artificial Neural Network Analysis of Multi-Parametric MRI in Patients with Stroke

• Published in: PloS one Vol. 6; no. 8; p. e22626
• Main Authors: Bagher-Ebadian, Hassan, Jafari-Khouzani, Kourosh, Mitsias, Panayiotis D., Lu, Mei, Soltanian-Zadeh, Hamid, Chopp, Michael, Ewing, James R.
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 10.08.2011; Public Library of Science (PLoS)
• Subjects: Adult; Aged; Artificial neural networks; Biology; Cerebral infarction; Cerebral Infarction - complications; Cerebral Infarction - diagnosis; Cerebral Infarction - pathology; Demography; Driving while intoxicated; Female; Humans; Infarction; Ischemia; Lesions; Magnetic Resonance Imaging; Male; Medicine; Middle Aged; Network analysis; Neural networks; Neural Networks (Computer); Optimization; Patients; Prognosis; Proton density (concentration); ROC Curve; Stroke; Stroke - complications; Stroke - diagnosis; Stroke - pathology; Stroke patients; Training; United States > US; Detroit Michigan; Michigan

In hemispheric ischemic stroke, the final size of the ischemic lesion is the most important correlate of clinical functional outcome. Using a set of acute-phase MR images (Diffusion-weighted--DWI, T(1)-weighted--T1WI, T(2)-weighted--T2WI, and proton density weighted--PDWI) for inputs, and the chroni...