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.
Keywords: Low-dose perfusion CT; Post-processing, Perfusion CT; Radiation dose; Stroke.