Qualitative and quantitative evaluation of rigid and deformable motion correction algorithms using dual-energy CT images in view of application to CT perfusion measurements in abdominal organs affected by breathing motion.

OBJECTIVE To compare six different scenarios for correcting for breathing motion in abdominal dual-energy CT (DECT) perfusion measurements. METHODS Rigid [RRComm(80 kVp)] and non-rigid [NRComm(80 kVp)] registration of commercially available CT perfusion software, custom non-rigid registration [NRCustom(80 kVp], demons algorithm) and a control group [CG(80 kVp)] without motion correction were evaluated using 80 kVp images. Additionally, NRCustom was applied to dual-energy (DE)-blended [NRCustom(DE)] and virtual non-contrast [NRCustom(VNC)] images, yielding six evaluated scenarios. After motion correction, perfusion maps were calculated using a combined maximum slope/Patlak model. For qualitative evaluation, three blinded radiologists independently rated motion correction quality and resulting perfusion maps on a four-point scale (4 = best, 1 = worst). For quantitative evaluation, relative changes in metric values, R(2) and residuals of perfusion model fits were calculated. RESULTS For motion-corrected images, mean ratings differed significantly [NRCustom(80 kVp) and NRCustom(DE), 3.3; NRComm(80 kVp), 3.1; NRCustom(VNC), 2.9; RRComm(80 kVp), 2.7; CG(80 kVp), 2.7; all p < 0.05], except when comparing NRCustom(80 kVp) with NRCustom(DE) and RRComm(80 kVp) with CG(80 kVp). NRCustom(80 kVp) and NRCustom(DE) achieved the highest reduction in metric values [NRCustom(80 kVp), 48.5%; NRCustom(DE), 45.6%; NRComm(80 kVp), 29.2%; NRCustom(VNC), 22.8%; RRComm(80 kVp), 0.6%; CG(80 kVp), 0%]. Regarding perfusion maps, NRCustom(80 kVp) and NRCustom(DE) were rated highest [NRCustom(80 kVp), 3.1; NRCustom(DE), 3.0; NRComm(80 kVp), 2.8; NRCustom(VNC), 2.6; CG(80 kVp), 2.5; RRComm(80 kVp), 2.4] and had significantly higher R(2) and lower residuals. Correlation between qualitative and quantitative evaluation was low to moderate. CONCLUSION Non-rigid motion correction improves spatial alignment of the target region and fit of CT perfusion models. Using DE-blended and DE-VNC images for deformable registration offers no significant improvement. ADVANCES IN KNOWLEDGE Non-rigid algorithms improve the quality of abdominal CT perfusion measurements but do not benefit from DECT post processing.

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