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Improving the prediction of final infarct size in acute stroke with bolus delay–corrected perfusion MRI measures

✍ Scribed by Stephen E. Rose; Andrew L. Janke; Mark Griffin; Mark W. Strudwick; Simon Finnigan; James Semple; Jonathan B. Chalk


Publisher
John Wiley and Sons
Year
2004
Tongue
English
Weight
302 KB
Volume
20
Category
Article
ISSN
1053-1807

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✦ Synopsis


Abstract

Purpose

To investigate whether bolus delay‐corrected dynamic susceptibility contrast (DSC) perfusion MRI measures allowed a more accurate estimation of eventual infarct volume in 14 acute stroke patients using a predictive tissue classifier algorithm.

Materials and Methods

Tissue classification was performed using a expectation maximization and k‐means clustering algorithm utilizing diffusion and T2 measures (diffusion‐weighted imaging [DWI], apparent diffusion coefficient [ADC], and T2) combined with uncorrected perfusion measures cerebral blood flow ((CBF) and mean transit time [MTT]), bolus delay–corrected perfusion measures (cCBF and cMTT), and bolus delay–corrected perfusion indices (cCBF and cMTT with bolus delay).

Results

The mean similarity index (SI), a kappa‐based correlation statistic reflecting the pixel‐by‐pixel classification agreement between predicted and 30‐day T2 lesion volumes, were 0.55 ± 0.19, 0.61 ± 0.15 (P < 0.02) and 0.60 ± 0.17 (P <0.03), respectively. Spearman's correlation coefficients, comparing predicted and final lesion volumes were 0.56 (P < 0.05), 0.70 (P < 0.01), and 0.84 (P < 0.001), respectively. We found a more significant correlation between predicted infarct volumes derived from bolus delay–corrected perfusion measures than from conventional perfusion measures when combined with diffusion measures and compared with final lesion volumes measured on 30‐day T2 MRI scans.

Conclusion

Bolus delay–corrected perfusion measures enable an improved prediction of infarct evolution and evaluation of the hemodynamic status of neuronal tissue in acute stroke. J. Magn. Reson. Imaging 2004;20:941–947. © 2004 Wiley‐Liss, Inc.