Bayesian Analysis of Perfusion-weighted Imaging to Predict Infarct Volume: Comparison with Singular Value Decomposition
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- KUDO Kohsuke
- Division of Ultrahigh Field MRI, Institute of Biomedical Sciences, Iwate Medical University Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital
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- BOUTELIER Timothé
- Department of Research & Innovation, Olea Medical
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- HU Jin-Qing
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
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- HONJO Kaneyoshi
- Department of Pharmacology, Honjo Bioscience Inc.
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- WANG Hai-Bin
- Department of Anesthesiology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine
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- PAUTOT Fabrice
- Department of Research & Innovation, Olea Medical
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- UWANO Ikuko
- Division of Ultrahigh Field MRI, Institute of Biomedical Sciences, Iwate Medical University
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- SASAKI Makoto
- Division of Ultrahigh Field MRI, Institute of Biomedical Sciences, Iwate Medical University
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- SHINTAKU Katsuya
- Department of Pharmacology, Honjo Bioscience Inc.
書誌事項
- 公開日
- 2014
- 資源種別
- journal article
- DOI
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- 10.2463/mrms.2013-0085
- 公開者
- 日本磁気共鳴医学会
この論文をさがす
説明
Purpose: We compared the performances of a Bayesian estimation method and oscillation index singular value decomposition (oSVD) deconvolution for predicting final infarction using data previously obtained from 10 cynomolgus monkeys with permanent unilateral middle cerebral artery (MCA) occlusion.<br/>Methods: We conducted baseline perfusion-weighted imaging 3 hours after MCA occlusion and generated time to peak, first moment of transit, cerebral blood flow, cerebral blood volume, and mean transit time maps using Bayesian and oSVD methods. Final infarct volume was determined by follow-up diffusion-weighted imaging (DWI) scanned 47 hours after MCA occlusion and from histological specimens. We used a region growing technique with various thresholds to determine perfusion abnormality volume. The best threshold was defined when the mean perfusion volume matched the mean final infarct volume, and Pearson's correlation coefficients (r) and intraclass correlations (ICC) were calculated between perfusion abnormality and final infarct volume at that threshold. These coefficients were compared between Bayesian and oSVD using Wilcoxon's signed rank test. P-value < 0.05 was considered a statistically significant difference.<br/>Results: The Pearson's correlation coefficients were larger but not significantly different for the Bayesian technique than oSVD in 4 of 5 perfusion maps when final infarct was determined by specimen volume (P = 0.104). When final infarct volume was defined by DWI volume, all perfusion maps had a significantly higher correlation coefficient by Bayesian technique than oSVD (P = 0.043). For ICC, all perfusion maps had higher value in Bayesian than oSVD calculation, and significant differences were observed both on specimen- and DWI-defined volumes (P = 0.043 for both).<br/>Conclusion: The Bayesian method is more reliable than oSVD deconvolution in estimating final infarct volume.
収録刊行物
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- Magnetic Resonance in Medical Sciences
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Magnetic Resonance in Medical Sciences 13 (1), 45-50, 2014
日本磁気共鳴医学会
