A E Othman1,2, S Afat1, C Brockmann1, O Nikoubashman1, G Bier2, M A Brockmann1, K Nikolaou2, J H Tai3, Z P Yang4, J H Kim5,6,7, M Wiesmann1. 1. Department of Diagnostic and Interventional Neuroradiology, RWTH Aachen University, 52074, Aachen, Germany. 2. Department for Diagnostic and Interventional Radiology, Eberhard Karls University Tuebingen, University Hospital Tuebingen, 72076, Tübingen, Germany. 3. Center for Medical-IT Convergence Technology Research, Advanced Institute of Convergence Technology, 433-270, Suwon, South Korea. 4. Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, 433-270, Suwon, South Korea. 5. Department of Transdisciplinary Studies, Graduate School of Convergence Science and Technology, Seoul National University, 433-270, Suwon, South Korea. kimjhyo@snu.ac.kr. 6. Department of Radiology, Seoul National University College of Medicine, 101 Daehak-Ro, Chongno-gu, 110-744, Seoul, South Korea. kimjhyo@snu.ac.kr. 7. Center for Medical-IT Convergence Technology Research, Advanced Institute of Convergence Technology, 433-270, Suwon, South Korea. kimjhyo@snu.ac.kr.
Abstract
PURPOSE: We aimed to compare different computed tomography (CT) perfusion post-processing algorithms regarding image quality of perfusion maps from low-dose volume perfusion CT (VPCT) and their diagnostic performance regarding the detection of ischemic brain lesions. METHODS AND MATERIALS: We included VPCT data of 21 patients with acute stroke (onset < 6h), which were acquired at 80 kV and 180 mAs. Low-dose VPCT datasets with 72 mAs (40 % of original dose) were generated using realistic low-dose simulation. Perfusion maps (cerebral blood volume (CBV); cerebral blood flow (CBF) from original and low-dose datasets were generated using two different commercially available post-processing methods: deconvolution-based method (DC) and maximum slope algorithm (MS). The resulting DC and MS perfusion maps were compared regarding perfusion values, signal-to-noise ratio (SNR) as well as image quality and diagnostic accuracy as rated by two blinded neuroradiologists. RESULTS: Quantitative perfusion parameters highly correlated for both algorithms and both dose levels (r ≥ 0.613, p < 0.001). Regarding SNR levels and image quality of the CBV maps, no significant differences between DC and MS were found (p ≥ 0.683). Low-dose MS CBF maps yielded significantly higher SNR levels (p < 0.001) and quality scores (p = 0.014) than those of DC. Low-dose CBF and CBV maps from both DC and MS yielded high sensitivity and specificity for the detection of ischemic lesions (sensitivity ≥ 0.82, specificity ≥ 0.90). CONCLUSION: Our results indicate that both methods produce diagnostically sufficient perfusion maps from simulated low-dose VPCT. However, MS produced CBF maps with significantly higher image quality and SNR than DC, indicating that MS might be more suitable for low-dose VPCT imaging.
PURPOSE: We aimed to compare different computed tomography (CT) perfusion post-processing algorithms regarding image quality of perfusion maps from low-dose volume perfusion CT (VPCT) and their diagnostic performance regarding the detection of ischemic brain lesions. METHODS AND MATERIALS: We included VPCT data of 21 patients with acute stroke (onset < 6h), which were acquired at 80 kV and 180 mAs. Low-dose VPCT datasets with 72 mAs (40 % of original dose) were generated using realistic low-dose simulation. Perfusion maps (cerebral blood volume (CBV); cerebral blood flow (CBF) from original and low-dose datasets were generated using two different commercially available post-processing methods: deconvolution-based method (DC) and maximum slope algorithm (MS). The resulting DC and MS perfusion maps were compared regarding perfusion values, signal-to-noise ratio (SNR) as well as image quality and diagnostic accuracy as rated by two blinded neuroradiologists. RESULTS: Quantitative perfusion parameters highly correlated for both algorithms and both dose levels (r ≥ 0.613, p < 0.001). Regarding SNR levels and image quality of the CBV maps, no significant differences between DC and MS were found (p ≥ 0.683). Low-dose MS CBF maps yielded significantly higher SNR levels (p < 0.001) and quality scores (p = 0.014) than those of DC. Low-dose CBF and CBV maps from both DC and MS yielded high sensitivity and specificity for the detection of ischemic lesions (sensitivity ≥ 0.82, specificity ≥ 0.90). CONCLUSION: Our results indicate that both methods produce diagnostically sufficient perfusion maps from simulated low-dose VPCT. However, MS produced CBF maps with significantly higher image quality and SNR than DC, indicating that MS might be more suitable for low-dose VPCT imaging.
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