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Titolo:
Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging
Autore:
Wu, O; Koroshetz, WJ; Ostergaard, L; Buonanno, FS; Copen, WA; Gonzalez, RG; Rordorf, G; Rosen, BR; Schwamm, LH; Weisskoff, RM; Sorensen, AG;
Indirizzi:
Massachusetts Gen Hosp, MGH NMR Ctr, Dept Radiol, Boston, MA 02129 USA Massachusetts Gen Hosp Boston MA USA 02129 t Radiol, Boston, MA 02129 USA Massachusetts Gen Hosp, Dept Neurol, Boston, MA 02129 USA Massachusetts Gen Hosp Boston MA USA 02129 t Neurol, Boston, MA 02129 USA MIT, Cambridge, MA 02139 USA MIT Cambridge MA USA 02139MIT, Cambridge, MA 02139 USA
Titolo Testata:
STROKE
fascicolo: 4, volume: 32, anno: 2001,
pagine: 933 - 942
SICI:
0039-2499(200104)32:4<933:PTOIAH>2.0.ZU;2-I
Fonte:
ISI
Lingua:
ENG
Soggetto:
HIGH-RESOLUTION MEASUREMENT; TRACER BOLUS PASSAGES; ACUTE STROKE; BLOOD-FLOW; HYPERACUTE STROKE; TIME-COURSE; PENUMBRA; MODEL; RECANALIZATION; THRESHOLDS;
Keywords:
cerebral ischemia; magnetic resonance imaging, diffusion-weighted; magnetic resonance imaging, perfusion-weighted; stroke, acute;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Clinical Medicine
Life Sciences
Citazioni:
48
Recensione:
Indirizzi per estratti:
Indirizzo: Wu, O Massachusetts Gen Hosp, MGH NMR Ctr, Dept Radiol, Mailcode CNY149-2301, Boston, MA 02129 USA Massachusetts Gen Hosp Mailcode CNY149-2301 BostonMA USA 02129 USA
Citazione:
O. Wu et al., "Predicting tissue outcome in acute human cerebral ischemia using combined diffusion- and perfusion-weighted MR imaging", STROKE, 32(4), 2001, pp. 933-942

Abstract

Background and Purpose-Tissue signatures from acute MR imaging of the brain may be able to categorize physiological status and thereby assist clinical decision making. We designed and analyzed statistical algorithms to evaluate the risk of infarction for each voxel of tissue using acute human functional MRI. Methods-Diffusion-weighted MR images (DWI) and perfusion-weighted MR images (PWI) from acute stroke patients scanned within 12 hours of symptom onsetwere retrospectively studied and used to develop thresholding and generalized Linear model (GLM) algorithms predicting tissue outcome as determined by follow-up MRI, The performances of the algorithms were evaluated for eachpatient by using receiver operating characteristic curves. Results-At their optimal operating points, thresholding algorithms combining DWI and PWI provided 66% sensitivity and 83% specificity, and GLM algorithms combining DWI and PWI predicted with 66% sensitivity and 84% specificity voxels that proceeded to infarct, Thresholding algorithms that combined DWI and PWI provided significant improvement to algorithms that utilized DWI alone (P=0.02) but no significant improvement over algorithms utilizing PWI alone (P=0.21). GLM algorithms that combined DWI and PWI showed significant improvement over algorithms that used only DWI (P=0.02) or PWI (P=0.04). The performances of thresholding and GLM algorithms were comparable (P>0.2). Conclusions-Algorithms that combine acute DWI and PWI can assess the risk of infarction with higher specificity and sensitivity than algorithms that use DWI or PWI individually. Methods for quantitatively assessing the risk of infarction on a voxel-by-voxel basis show promise as techniques for investigating the natural spatial evolution of ischemic damage in humans.

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Documento generato il 18/01/20 alle ore 01:47:51