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Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers

Background: The purpose of the study was to determine whether contrast-enhanced CT texture features relate to, and can predict, the presence of specific genetic mutations involved in CRC carcinogenesis. Materials and methods: This retrospective study analyzed the pre-operative CT in the venous phase...

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Autores principales: Crimì, Filippo, Zanon, Chiara, Cabrelle, Giulio, Luong, Kim Duyen, Albertoni, Laura, Bao, Quoc Riccardo, Borsetto, Marta, Baratella, Elisa, Capelli, Giulia, Spolverato, Gaya, Fassan, Matteo, Pucciarelli, Salvatore, Quaia, Emilio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498512/
https://www.ncbi.nlm.nih.gov/pubmed/36136880
http://dx.doi.org/10.3390/tomography8050184
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author Crimì, Filippo
Zanon, Chiara
Cabrelle, Giulio
Luong, Kim Duyen
Albertoni, Laura
Bao, Quoc Riccardo
Borsetto, Marta
Baratella, Elisa
Capelli, Giulia
Spolverato, Gaya
Fassan, Matteo
Pucciarelli, Salvatore
Quaia, Emilio
author_facet Crimì, Filippo
Zanon, Chiara
Cabrelle, Giulio
Luong, Kim Duyen
Albertoni, Laura
Bao, Quoc Riccardo
Borsetto, Marta
Baratella, Elisa
Capelli, Giulia
Spolverato, Gaya
Fassan, Matteo
Pucciarelli, Salvatore
Quaia, Emilio
author_sort Crimì, Filippo
collection PubMed
description Background: The purpose of the study was to determine whether contrast-enhanced CT texture features relate to, and can predict, the presence of specific genetic mutations involved in CRC carcinogenesis. Materials and methods: This retrospective study analyzed the pre-operative CT in the venous phase of patients with CRC, who underwent testing for mutations in the KRAS, NRAS, BRAF, and MSI genes. Using a specific software based on CT images of each patient, for each slice including the tumor a region of interest was manually drawn along the margin, obtaining the volume of interest. A total of 56 texture parameters were extracted that were compared between the wild-type gene group and the mutated gene group. A p-value of <0.05 was considered statistically significant. Results: The study included 47 patients with stage III-IV CRC. Statistically significant differences between the MSS group and the MSI group were found in four parameters: GLRLM RLNU (area under the curve (AUC) 0.72, sensitivity (SE) 77.8%, specificity (SP) 65.8%), GLZLM SZHGE (AUC 0.79, SE 88.9%, SP 65.8%), GLZLM GLNU (AUC 0.74, SE 88.9%, SP 60.5%), and GLZLM ZLNU (AUC 0.77, SE 88.9%, SP 65.8%). Conclusions: The findings support the potential role of the CT texture analysis in detecting MSI in CRC based on pre-treatment CT scans.
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spelling pubmed-94985122022-09-23 Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers Crimì, Filippo Zanon, Chiara Cabrelle, Giulio Luong, Kim Duyen Albertoni, Laura Bao, Quoc Riccardo Borsetto, Marta Baratella, Elisa Capelli, Giulia Spolverato, Gaya Fassan, Matteo Pucciarelli, Salvatore Quaia, Emilio Tomography Article Background: The purpose of the study was to determine whether contrast-enhanced CT texture features relate to, and can predict, the presence of specific genetic mutations involved in CRC carcinogenesis. Materials and methods: This retrospective study analyzed the pre-operative CT in the venous phase of patients with CRC, who underwent testing for mutations in the KRAS, NRAS, BRAF, and MSI genes. Using a specific software based on CT images of each patient, for each slice including the tumor a region of interest was manually drawn along the margin, obtaining the volume of interest. A total of 56 texture parameters were extracted that were compared between the wild-type gene group and the mutated gene group. A p-value of <0.05 was considered statistically significant. Results: The study included 47 patients with stage III-IV CRC. Statistically significant differences between the MSS group and the MSI group were found in four parameters: GLRLM RLNU (area under the curve (AUC) 0.72, sensitivity (SE) 77.8%, specificity (SP) 65.8%), GLZLM SZHGE (AUC 0.79, SE 88.9%, SP 65.8%), GLZLM GLNU (AUC 0.74, SE 88.9%, SP 60.5%), and GLZLM ZLNU (AUC 0.77, SE 88.9%, SP 65.8%). Conclusions: The findings support the potential role of the CT texture analysis in detecting MSI in CRC based on pre-treatment CT scans. MDPI 2022-08-31 /pmc/articles/PMC9498512/ /pubmed/36136880 http://dx.doi.org/10.3390/tomography8050184 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Crimì, Filippo
Zanon, Chiara
Cabrelle, Giulio
Luong, Kim Duyen
Albertoni, Laura
Bao, Quoc Riccardo
Borsetto, Marta
Baratella, Elisa
Capelli, Giulia
Spolverato, Gaya
Fassan, Matteo
Pucciarelli, Salvatore
Quaia, Emilio
Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title_full Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title_fullStr Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title_full_unstemmed Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title_short Contrast-Enhanced CT Texture Analysis in Colon Cancer: Correlation with Genetic Markers
title_sort contrast-enhanced ct texture analysis in colon cancer: correlation with genetic markers
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9498512/
https://www.ncbi.nlm.nih.gov/pubmed/36136880
http://dx.doi.org/10.3390/tomography8050184
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