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EnglishComputed Tomography perfusion (CTp) is a promising technique for estimating perfusion parameters, by analysing Time Concentration Curves (TCCs) of the administered contrast agent. However, several artefacts can degrade the signal quality, jeopardizing quantitative measurements. Despite different methods exploit TCCs to compute perfusion parameters, none of them has investigated how TCC fitting errors may affect final perfusion values. The first goal of this work is to investigate residuals distributions in significant signal’s portions, then relating them to Blood Flow (BF). The Gamma Variate (GV) function is addressed to fit TCCs. Voxel-based BF is computed with the two most spread methods in literature, Maximum Slope (MS) and Deconvolution (DV). Experimental results prove that residuals coming from a Gaussian distribution yield percent errors maps locally smooth, thus attaining residuals-independent BF values. Besides results, the methodological approach can be spent in future researches in order to encourage CTp reproducibility.
| Titolo: | Analysis of the effects of fitting errors of DCE-CT signals on perfusion parameters | |
| Autore/i: | Alessandro Bevilacqua; Margherita Mottola | |
| Autore/i Unibo: | ||
| Anno: | 2018 | |
| Rivista: | ||
| Titolo del libro: | Proceedings of the IEEE International Symposium on Circuits and Systems (ISCAS) | |
| Pagina iniziale: | 1 | |
| Pagina finale: | 5 | |
| Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/ISCAS.2018.8351204 | |
| Abstract: | Computed Tomography perfusion (CTp) is a promising technique for estimating perfusion parameters, by analysing Time Concentration Curves (TCCs) of the administered contrast agent. However, several artefacts can degrade the signal quality, jeopardizing quantitative measurements. Despite different methods exploit TCCs to compute perfusion parameters, none of them has investigated how TCC fitting errors may affect final perfusion values. The first goal of this work is to investigate residuals distributions in significant signal’s portions, then relating them to Blood Flow (BF). The Gamma Variate (GV) function is addressed to fit TCCs. Voxel-based BF is computed with the two most spread methods in literature, Maximum Slope (MS) and Deconvolution (DV). Experimental results prove that residuals coming from a Gaussian distribution yield percent errors maps locally smooth, thus attaining residuals-independent BF values. Besides results, the methodological approach can be spent in future researches in order to encourage CTp reproducibility. | |
| Data stato definitivo: | 4-nov-2019 | |
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