ArticleJournal of applied clinical medical physics2023
Simultaneous spatial and temporal regularization in low-dose dynamic contrast-enhanced CT cerebral perfusion studies.
Article in Journal of applied clinical medical physics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Simultaneous spatial and temporal regularization in low-dose dynamic contrast-enhanced CT cerebral perfusion studies.Journal of applied clinical medical physics · 2023Article
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Abstract
purposeTo apply total generalized variation (TGV) and its combination with low-rank and sparse decomposition (LRSD) (LTGV) to cerebral perfusion studies using low-dose dynamic contrast-enhanced (DCE) CT and to quantitatively evaluate their performances through comparisons with those without any regularizers and those of total variation (TV) and its combination with LRSD (LTV) using simulation and clinical data.
methodsThe simulation study used a realistic digital brain phantom. Low-dose DCE-CT images were reconstructed using the regularizers and primal-dual algorithm. Subsequently, cerebral perfusion parameter (CPP) images were generated from them. Thereafter, their quality was evaluated based on the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM). Further, the accuracy of CPP estimation was evaluated through a linear regression analysis between the CPP values obtained by the above regularizers and those obtained from the noise-free DCE-CT images. In addition, the mean and standard deviation of the CPP were calculated (region analysis). In the clinical study, low-dose DCE-CT images were generated using normal-dose images acquired from a patient, and CPP images were generated from them similar to that in the simulation study.
resultsWhen using LTV and LTGV, both PSNR and SSIM were higher than those of the other methods with increasing regularization parameter values. The results of the linear regression and region analyses demonstrated that TGV generally exhibited the best performance, followed by LTGV, and finally that of TV was significantly different from those of the other regularizers. Despite an overall consistency between the simulation and clinical results, certain inconsistencies appeared owing to the difference in generating low-dose DCE-CT images.
conclusionsThe results implied that TGV and LTGV were useful in improving the accuracy of CPP estimation using low-dose DCE-CT. This study provides an improved understanding of the performance of regularizers and is expected to aid in the selection of a suitable regularizer for low-dose DCE-CT perfusion studies.
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