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Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer
BACKGROUND: Radiomics allows information not readily available to the naked eye to be extracted from high resolution imaging modalities such as CT. Identifying that a cancer has already metastasised at the time of presentation through a radiomic signature will affect the treatment pathway. The abili...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942820/ https://www.ncbi.nlm.nih.gov/pubmed/35340828 http://dx.doi.org/10.1016/j.ejro.2022.100415 |
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author | Devoto, Laurence Ganeshan, Balaji Keller, Deborah Groves, Ashley Endozo, Raymond Arulampalam, Tan Chand, Manish |
author_facet | Devoto, Laurence Ganeshan, Balaji Keller, Deborah Groves, Ashley Endozo, Raymond Arulampalam, Tan Chand, Manish |
author_sort | Devoto, Laurence |
collection | PubMed |
description | BACKGROUND: Radiomics allows information not readily available to the naked eye to be extracted from high resolution imaging modalities such as CT. Identifying that a cancer has already metastasised at the time of presentation through a radiomic signature will affect the treatment pathway. The ability to recognise the existence of metastases earlier will have a significant impact on the survival outcomes. AIM: To create a novel radiomic signature using textural analysis in the evaluation of synchronous liver metastases in colorectal cancer. METHODS: CT images at baseline and subsequent surveillance over a 5-year period of patients with colorectal cancer were processed using textural analysis software. Comparison was made between those patients who developed liver metastases and those that remained disease free to detect differences in the ‘texture’ of the liver. RESULTS: A total of 24 patients were divided into two matched groups for comparison. Significant differences between the two groups scores when using the textural analysis programme were found on coarse filtration (p = 0.044). Patients that went on to develop metastases an average of 18 months after presentation had higher levels of hepatic heterogeneity on CT. CONCLUSION: This initial study demonstrates the potential of using a textural analysis programme to build a radiomic signature to predict the development of hepatic metastases in rectal cancer patients otherwise thought to have clear staging CT scans at time of presentation. |
format | Online Article Text |
id | pubmed-8942820 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-89428202022-03-25 Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer Devoto, Laurence Ganeshan, Balaji Keller, Deborah Groves, Ashley Endozo, Raymond Arulampalam, Tan Chand, Manish Eur J Radiol Open Article BACKGROUND: Radiomics allows information not readily available to the naked eye to be extracted from high resolution imaging modalities such as CT. Identifying that a cancer has already metastasised at the time of presentation through a radiomic signature will affect the treatment pathway. The ability to recognise the existence of metastases earlier will have a significant impact on the survival outcomes. AIM: To create a novel radiomic signature using textural analysis in the evaluation of synchronous liver metastases in colorectal cancer. METHODS: CT images at baseline and subsequent surveillance over a 5-year period of patients with colorectal cancer were processed using textural analysis software. Comparison was made between those patients who developed liver metastases and those that remained disease free to detect differences in the ‘texture’ of the liver. RESULTS: A total of 24 patients were divided into two matched groups for comparison. Significant differences between the two groups scores when using the textural analysis programme were found on coarse filtration (p = 0.044). Patients that went on to develop metastases an average of 18 months after presentation had higher levels of hepatic heterogeneity on CT. CONCLUSION: This initial study demonstrates the potential of using a textural analysis programme to build a radiomic signature to predict the development of hepatic metastases in rectal cancer patients otherwise thought to have clear staging CT scans at time of presentation. Elsevier 2022-03-21 /pmc/articles/PMC8942820/ /pubmed/35340828 http://dx.doi.org/10.1016/j.ejro.2022.100415 Text en © 2022 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Devoto, Laurence Ganeshan, Balaji Keller, Deborah Groves, Ashley Endozo, Raymond Arulampalam, Tan Chand, Manish Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title | Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title_full | Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title_fullStr | Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title_full_unstemmed | Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title_short | Using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
title_sort | using texture analysis in the development of a potential radiomic signature for early identification of hepatic metastasis in colorectal cancer |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8942820/ https://www.ncbi.nlm.nih.gov/pubmed/35340828 http://dx.doi.org/10.1016/j.ejro.2022.100415 |
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