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Robustness to noise of arterial blood flow estimation methods in CT perfusion
BACKGROUND: Perfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning b...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152598/ https://www.ncbi.nlm.nih.gov/pubmed/25130498 http://dx.doi.org/10.1186/1756-0500-7-540 |
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author | Romano, Maria D’Antò, Michela Bifulco, Paolo Fiore, Francesco Cesarelli, Mario |
author_facet | Romano, Maria D’Antò, Michela Bifulco, Paolo Fiore, Francesco Cesarelli, Mario |
author_sort | Romano, Maria |
collection | PubMed |
description | BACKGROUND: Perfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning both clinical and technical aspects. In this study, we dealt with the comparison of two widely employed mathematical models (dual input one compartment model – DOCM - and maximum slope – SM -) analyzing their robustness to the noise. METHODS: We carried out a computer simulation process to quantify effect of noise on the evaluation of an important perfusion parameter (Arterial Blood Flow – BFa) in liver tumours. A total of 4500 liver TAC, corresponding to 3 fixed BFa values, were simulated using different arterial and portal TAC (computed from 5 real CT images) at 10 values of signal to noise ratio (SNR). BFa values were calculated by applying four different algorithms, specifically developed, to these noisy simulated curves. Three algorithms were developed to implement SM (one semiautomatic, one automatic and one automatic with filtering) and the last for the DOCM method. RESULTS: In all the simulations, DOCM provided the best results, i.e., those with the lowest percentage error compared to the reference value of BFa. Concerning SM, the results are variable. Results obtained with the automatic algorithm with filtering are close to the reference value, but only if SNR is higher than 50. Vice versa, results obtained by means of the semiautomatic algorithm gave, in all simulations, the lowest results with the lowest standard deviation of the percentage error. CONCLUSIONS: Since the use of DOCM is limited by the necessity that portal vein is visible in CT scans, significant restriction for patients’ follow-up, we concluded that SM can be reliably employed. However, a proper software has to be used and an estimation of SNR would be carried out. |
format | Online Article Text |
id | pubmed-4152598 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-41525982014-09-04 Robustness to noise of arterial blood flow estimation methods in CT perfusion Romano, Maria D’Antò, Michela Bifulco, Paolo Fiore, Francesco Cesarelli, Mario BMC Res Notes Research Article BACKGROUND: Perfusion CT is a technology which allows functional evaluation of tissue vascularity. Due to this potential, it is finding increasing utility in oncology. Although since its introduction continuous advances have interested CT technique, some issues have to be still defined, concerning both clinical and technical aspects. In this study, we dealt with the comparison of two widely employed mathematical models (dual input one compartment model – DOCM - and maximum slope – SM -) analyzing their robustness to the noise. METHODS: We carried out a computer simulation process to quantify effect of noise on the evaluation of an important perfusion parameter (Arterial Blood Flow – BFa) in liver tumours. A total of 4500 liver TAC, corresponding to 3 fixed BFa values, were simulated using different arterial and portal TAC (computed from 5 real CT images) at 10 values of signal to noise ratio (SNR). BFa values were calculated by applying four different algorithms, specifically developed, to these noisy simulated curves. Three algorithms were developed to implement SM (one semiautomatic, one automatic and one automatic with filtering) and the last for the DOCM method. RESULTS: In all the simulations, DOCM provided the best results, i.e., those with the lowest percentage error compared to the reference value of BFa. Concerning SM, the results are variable. Results obtained with the automatic algorithm with filtering are close to the reference value, but only if SNR is higher than 50. Vice versa, results obtained by means of the semiautomatic algorithm gave, in all simulations, the lowest results with the lowest standard deviation of the percentage error. CONCLUSIONS: Since the use of DOCM is limited by the necessity that portal vein is visible in CT scans, significant restriction for patients’ follow-up, we concluded that SM can be reliably employed. However, a proper software has to be used and an estimation of SNR would be carried out. BioMed Central 2014-08-18 /pmc/articles/PMC4152598/ /pubmed/25130498 http://dx.doi.org/10.1186/1756-0500-7-540 Text en © Romano et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Romano, Maria D’Antò, Michela Bifulco, Paolo Fiore, Francesco Cesarelli, Mario Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title | Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title_full | Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title_fullStr | Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title_full_unstemmed | Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title_short | Robustness to noise of arterial blood flow estimation methods in CT perfusion |
title_sort | robustness to noise of arterial blood flow estimation methods in ct perfusion |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4152598/ https://www.ncbi.nlm.nih.gov/pubmed/25130498 http://dx.doi.org/10.1186/1756-0500-7-540 |
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