Infarct Prediction and Treatment Assessment with MRI-based Algorithms in Experimental Stroke Models

• Published in: Journal of cerebral blood flow and metabolism Vol. 27; no. 1; pp. 196 - 204
• Main Authors: Wu, Ona, Sumii, Toshihisa, Asahi, Minoru, Sasamata, Masao, Østergaard, Leif, Rosen, Bruce R, Lo, Eng H, Dijkhuizen, Rick M
• Format: Journal Article
• Language: English
• Published: London, England SAGE Publications 01.01.2007; Lippincott Williams & Wilkins; Sage Publications Ltd
• Subjects: Algorithms; Animals; Biological and medical sciences; Brain Ischemia - pathology; Cardiovascular system; Headache. Facial pains. Syncopes. Epilepsia. Intracranial hypertension. Brain oedema. Cerebral palsy; Infarction, Middle Cerebral Artery - pathology; Linear Models; Magnetic Resonance Imaging; Male; Medical sciences; Models, Neurological; Nervous system (semeiology, syndromes); Neurology; Pharmacology. Drug treatments; Plasminogen Activators - therapeutic use; Predictive Value of Tests; Rats; Rats, Sprague-Dawley; Recombinant Proteins - therapeutic use; Stroke - pathology; Vascular diseases and vascular malformations of the nervous system; Vasodilator agents. Cerebral vasodilators; thrombolysis; magnetic resonance imaging; stroke animal models; mathematical analysis; treatment strategies for acute ischemic stroke; ischemic stroke; Animal model; Cerebral infarction; Stroke; Nervous system diseases; Infarct; Cardiovascular disease; Algorithm; Nuclear magnetic resonance imaging; Cerebral disorder; Vascular disease; Treatment; Central nervous system disease; Brain ischemia; Cerebrovascular disease
• ISSN: 0271-678X; 1559-7016; 1559-7016
• DOI: 10.1038/sj.jcbfm.9600328

There is increasing interest in using algorithms combining multiple magnetic resonance imaging (MRI) modalities to predict tissue infarction in acute human stroke. We developed and tested a voxel-based generalized linear model (GLM) algorithm to predict tissue infarction in an animal stroke model in order to directly compare predicted outcome with the tissue's histologic outcome, and to evaluate the potential for assessing therapeutic efficacy using these multiparametric algorithms. With acute MRI acquired after unilateral embolic stroke in rats (n = 8), a GLM was developed and used to predict infarction on a voxel-wise basis for saline (n = 6) and recombinant tissue plasminogen activator (rt-PA) treatment (n = 7) arms of a trial of delayed thrombolytic therapy in rats. Pretreatment predicted outcome compared with post-treatment histology was highly accurate in saline-treated rats (0.92±0.05). Accuracy was significantly reduced (P=0.04) in rt-PA-treated animals (0.86±0.08), although no significant difference was detected when comparing histologic lesion volumes. Animals that reperfused had significantly lower (P < 0.01) GLM-predicted infarction risk (0.73±0.03) than nonreperfused animals (0.81 ± 0.05), possibly reflecting less severe initial ischemic injury and therefore tissue likely more amenable to therapy. Our results show that acute MRI-based algorithms can predict tissue infarction with high accuracy in animals not receiving thrombolytic therapy. Furthermore, alterations in disease progression due to treatment were more sensitively monitored with our voxel-based analysis techniques than with volumetric approaches. Our study shows that predictive algorithms are promising metrics for diagnosis, prognosis and therapeutic evaluation after acute stroke that can translate readily from preclinical to clinical settings.