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Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing
BACKGROUND: Radiofrequency ablation (RFA) is one of the most promising non-surgical treatments for hepatic tumors. The assessment of the therapeutic efficacy of RFA is usually obtained by visual comparison of pre- and post-treatment CT images, but no numerical quantification is performed. METHODS: I...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626768/ https://www.ncbi.nlm.nih.gov/pubmed/23324557 http://dx.doi.org/10.1186/1471-2342-13-3 |
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author | Passera, Katia Selvaggi, Sabrina Scaramuzza, Davide Garbagnati, Francesco Vergnaghi, Daniele Mainardi, Luca |
author_facet | Passera, Katia Selvaggi, Sabrina Scaramuzza, Davide Garbagnati, Francesco Vergnaghi, Daniele Mainardi, Luca |
author_sort | Passera, Katia |
collection | PubMed |
description | BACKGROUND: Radiofrequency ablation (RFA) is one of the most promising non-surgical treatments for hepatic tumors. The assessment of the therapeutic efficacy of RFA is usually obtained by visual comparison of pre- and post-treatment CT images, but no numerical quantification is performed. METHODS: In this work, a novel method aiming at providing a more objective tool for the evaluation of RFA coverage is described. Image registration and segmentation techniques were applied to enable the visualization of the tumor and the corresponding post-RFA necrosis in the same framework. In addition, a set of numerical indexes describing tumor/necrosis overlap and their mutual position were computed. RESULTS: After validation of segmentation step, the method was applied on a dataset composed by 10 tumors, suspected not to be completed treated. Numerical indexes showed that only two tumors were totally treated and the percentage of a residual tumor was in the range of 5.12%-35.92%. CONCLUSIONS: This work represents a first attempt to obtain a quantitative tool aimed to assess the accuracy of RFA treatment. The possibility to visualize the tumor and the correspondent post-RFA necrosis in the same framework and the definition of some synthetic numerical indexes could help clinicians in ameliorating RFA treatment. |
format | Online Article Text |
id | pubmed-3626768 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-36267682013-04-24 Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing Passera, Katia Selvaggi, Sabrina Scaramuzza, Davide Garbagnati, Francesco Vergnaghi, Daniele Mainardi, Luca BMC Med Imaging Technical Advance BACKGROUND: Radiofrequency ablation (RFA) is one of the most promising non-surgical treatments for hepatic tumors. The assessment of the therapeutic efficacy of RFA is usually obtained by visual comparison of pre- and post-treatment CT images, but no numerical quantification is performed. METHODS: In this work, a novel method aiming at providing a more objective tool for the evaluation of RFA coverage is described. Image registration and segmentation techniques were applied to enable the visualization of the tumor and the corresponding post-RFA necrosis in the same framework. In addition, a set of numerical indexes describing tumor/necrosis overlap and their mutual position were computed. RESULTS: After validation of segmentation step, the method was applied on a dataset composed by 10 tumors, suspected not to be completed treated. Numerical indexes showed that only two tumors were totally treated and the percentage of a residual tumor was in the range of 5.12%-35.92%. CONCLUSIONS: This work represents a first attempt to obtain a quantitative tool aimed to assess the accuracy of RFA treatment. The possibility to visualize the tumor and the correspondent post-RFA necrosis in the same framework and the definition of some synthetic numerical indexes could help clinicians in ameliorating RFA treatment. BioMed Central 2013-01-16 /pmc/articles/PMC3626768/ /pubmed/23324557 http://dx.doi.org/10.1186/1471-2342-13-3 Text en Copyright © 2013 Passera et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Technical Advance Passera, Katia Selvaggi, Sabrina Scaramuzza, Davide Garbagnati, Francesco Vergnaghi, Daniele Mainardi, Luca Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title | Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title_full | Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title_fullStr | Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title_full_unstemmed | Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title_short | Radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through CT image processing |
title_sort | radiofrequency ablation of liver tumors: quantitative assessment of tumor coverage through ct image processing |
topic | Technical Advance |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3626768/ https://www.ncbi.nlm.nih.gov/pubmed/23324557 http://dx.doi.org/10.1186/1471-2342-13-3 |
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