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Combined cluster analysis of time evolution and tissue type with total variation denoising (CCTV) for QQ-based oxygen extract fraction mapping
Junghun Cho1, Pascal Spincemaille1, Thanh D Nguyen1, Ajay Gupta1, and Yi Wang1,2
1Radiology, Weill Cornell Medicine, New York, NY, United States, 2Biomedical Engineering, Cornell University, Ithaca, NY, United States
A Combined Cluster analysis and Total Variation denoising algorithm (CCTV) for oxygen extraction fraction (OEF) maps based on QSM+qBOLD (QQ) improved detection of lesion OEF abnormality in stroke patients compared to cluster analysis only without total variation denoising.
Comparison between the OEF obtained by QQ-CAT and QQ-CCTV in 6 stroke patients imaged between 6hrs and 10 days post stroke onset. QQ-CCTV generally shows more uniform OEF maps compared to QQ-CAT. In 7 and 9 days post-onset patients, low OEF areas in QQ-CCTV agree better with DWI-defined lesions.
Figure 1. Comparison between the OEF obtained by QQ-CAT and QQ-CCTV in a simulated stroke dataset. The numbers indicate RMSE (yellow) and MSD (white). On average, QQ-CCTV provide greater accuracy (MAE: 4.5 and 3.5%) and precision (MSD: 5.1 vs 1.7%). The OEFavg and OEFstd indicates the average and standard deviation OEF map among 5 trials, respectively.