Prediction of Infarct Volume and Neurologic Outcome by Using Automated Multiparametric Perfusion-weighted Magnetic Resonance Imaging in a Primate Model of Permanent Middle Cerebral Artery Occlusion

Overview

Journal J Cereb Blood Flow Metab

Publisher Sage Publications

Specialties Cardiology & Vascular Diseases
Endocrinology
Neurology

Date 2010 Jul 1

PMID 20588314

Citations 10

Authors

Makoto Sasaki

Kohsuke Kudo

Kaneyoshi Honjo

Jin-Qing Hu

Hai-Bin Wang

Katsuya Shintaku

Affiliations

Soon will be listed here.

Abstract

By optimizing thresholds, we identified the perfusion-weighted magnetic resonance imaging (PWI) parameters that accurately predict final infarct volume and neurologic outcome in a primate model of permanent middle cerebral artery (MCA) occlusion. Ten cynomolgus monkeys underwent PWI and diffusion-weighted imaging (DWI) at 3 and 47 hours, respectively, after right MCA occlusion using platinum coils, and were killed at 48 hours. Volumes of the hypoperfused areas on PWI were automatically measured using different thresholds and 11 parametric maps to determine the optimum threshold (at which least difference was found between the average volumes on PWI and those determined using specimens or DWI). In the case of arrival time (AT), cerebral blood volume (CBV), time to peak (TTP), time to maximum (T(max)), and cerebral blood flow (CBF) determined using deconvolution techniques, the volume of the hypoperfused area significantly correlated with the infarct volumes and the neurologic deficit scores with small variations, whereas in the case of mean transit time and nondeconvolution CBF, relatively poor correlations with large variations were seen. At optimum threshold, AT, CBV, TTP, T(max), and deconvolution CBF can accurately predict the final infarct volume and neurologic outcome in monkeys with permanent MCA occlusion.

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References

Wirestam R, Andersson L, Ostergaard L, Bolling M, Aunola J, Lindgren A . Assessment of regional cerebral blood flow by dynamic susceptibility contrast MRI using different deconvolution techniques. Magn Reson Med. 2000; 43(5):691-700. DOI: 10.1002/(sici)1522-2594(200005)43:5<691::aid-mrm11>3.0.co;2-b. View

Hjort N, Butcher K, Davis S, Kidwell C, Koroshetz W, Rother J . Magnetic resonance imaging criteria for thrombolysis in acute cerebral infarct. Stroke. 2004; 36(2):388-97. DOI: 10.1161/01.STR.0000152268.47919.be. View

Ostergaard L, Sorensen A, Kwong K, Weisskoff R, Gyldensted C, Rosen B . High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results. Magn Reson Med. 1996; 36(5):726-36. DOI: 10.1002/mrm.1910360511. View

Calamante F, Gadian D, Connelly A . Delay and dispersion effects in dynamic susceptibility contrast MRI: simulations using singular value decomposition. Magn Reson Med. 2000; 44(3):466-73. DOI: 10.1002/1522-2594(200009)44:3<466::aid-mrm18>3.0.co;2-m. View

Albers G, Thijs V, Wechsler L, Kemp S, Schlaug G, Skalabrin E . Magnetic resonance imaging profiles predict clinical response to early reperfusion: the diffusion and perfusion imaging evaluation for understanding stroke evolution (DEFUSE) study. Ann Neurol. 2006; 60(5):508-517. DOI: 10.1002/ana.20976. View

Furlan A, Eyding D, Albers G, Al-Rawi Y, Lees K, Rowley H . Dose Escalation of Desmoteplase for Acute Ischemic Stroke (DEDAS): evidence of safety and efficacy 3 to 9 hours after stroke onset. Stroke. 2006; 37(5):1227-31. DOI: 10.1161/01.STR.0000217403.66996.6d. View

Wintermark M, Flanders A, Velthuis B, Meuli R, van Leeuwen M, Goldsher D . Perfusion-CT assessment of infarct core and penumbra: receiver operating characteristic curve analysis in 130 patients suspected of acute hemispheric stroke. Stroke. 2006; 37(4):979-85. DOI: 10.1161/01.STR.0000209238.61459.39. View

Rivers C, Wardlaw J, Armitage P, Bastin M, Carpenter T, Cvoro V . Do acute diffusion- and perfusion-weighted MRI lesions identify final infarct volume in ischemic stroke?. Stroke. 2005; 37(1):98-104. DOI: 10.1161/01.STR.0000195197.66606.bb. View

Ibaraki M, Shimosegawa E, Toyoshima H, Takahashi K, Miura S, Kanno I . Tracer delay correction of cerebral blood flow with dynamic susceptibility contrast-enhanced MRI. J Cereb Blood Flow Metab. 2005; 25(3):378-90. DOI: 10.1038/sj.jcbfm.9600037. View

10.

Butcher K, Parsons M, MacGregor L, Barber P, Chalk J, Bladin C . Refining the perfusion-diffusion mismatch hypothesis. Stroke. 2005; 36(6):1153-9. DOI: 10.1161/01.str.0000166181.86928.8b. View

11.

Hacke W, Furlan A, Al-Rawi Y, Davalos A, Fiebach J, Gruber F . Intravenous desmoteplase in patients with acute ischaemic stroke selected by MRI perfusion-diffusion weighted imaging or perfusion CT (DIAS-2): a prospective, randomised, double-blind, placebo-controlled study. Lancet Neurol. 2008; 8(2):141-50. PMC: 2730486. DOI: 10.1016/S1474-4422(08)70267-9. View

12.

Kudo K, Sasaki M, Yamada K, Momoshima S, Utsunomiya H, Shirato H . Differences in CT perfusion maps generated by different commercial software: quantitative analysis by using identical source data of acute stroke patients. Radiology. 2009; 254(1):200-9. DOI: 10.1148/radiol.254082000. View

13.

Shih L, Saver J, Alger J, Starkman S, Leary M, Vinuela F . Perfusion-weighted magnetic resonance imaging thresholds identifying core, irreversibly infarcted tissue. Stroke. 2003; 34(6):1425-30. DOI: 10.1161/01.STR.0000072998.70087.E9. View

14.

Ostergaard L, Weisskoff R, Chesler D, Gyldensted C, Rosen B . High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis. Magn Reson Med. 1996; 36(5):715-25. DOI: 10.1002/mrm.1910360510. View

15.

Olivot J, Mlynash M, Thijs V, Kemp S, Lansberg M, Wechsler L . Optimal Tmax threshold for predicting penumbral tissue in acute stroke. Stroke. 2008; 40(2):469-75. PMC: 2670783. DOI: 10.1161/STROKEAHA.108.526954. View

16.

Kito G, Nishimura A, Susumu T, Nagata R, Kuge Y, Yokota C . Experimental thromboembolic stroke in cynomolgus monkey. J Neurosci Methods. 2001; 105(1):45-53. DOI: 10.1016/s0165-0270(00)00351-4. View

17.

Davis S, Donnan G, Parsons M, Levi C, Butcher K, Peeters A . Effects of alteplase beyond 3 h after stroke in the Echoplanar Imaging Thrombolytic Evaluation Trial (EPITHET): a placebo-controlled randomised trial. Lancet Neurol. 2008; 7(4):299-309. DOI: 10.1016/S1474-4422(08)70044-9. View

18.

Hacke W, Albers G, Al-Rawi Y, Bogousslavsky J, Davalos A, Eliasziw M . The Desmoteplase in Acute Ischemic Stroke Trial (DIAS): a phase II MRI-based 9-hour window acute stroke thrombolysis trial with intravenous desmoteplase. Stroke. 2004; 36(1):66-73. DOI: 10.1161/01.STR.0000149938.08731.2c. View

19.

Wu O, Ostergaard L, Weisskoff R, Benner T, Rosen B, Sorensen A . Tracer arrival timing-insensitive technique for estimating flow in MR perfusion-weighted imaging using singular value decomposition with a block-circulant deconvolution matrix. Magn Reson Med. 2003; 50(1):164-74. DOI: 10.1002/mrm.10522. View

20.

Lu M, Mitsias P, Ewing J, Soltanian-Zadeh H, Bagher-Ebadian H, Zhao Q . Predicting final infarct size using acute and subacute multiparametric MRI measurements in patients with ischemic stroke. J Magn Reson Imaging. 2005; 21(5):495-502. DOI: 10.1002/jmri.20313. View