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Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy
BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive pancreatic precursor lesions that can potentially develop into invasive pancreatic ductal adenocarcinoma. Currently, the International Consensus Guidelines (ICG) for IPMNs provides the basis for evaluating suspected IPMNs...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Baishideng Publishing Group Inc
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327792/ https://www.ncbi.nlm.nih.gov/pubmed/32655269 http://dx.doi.org/10.3748/wjg.v26.i24.3458 |
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author | Polk, Stuart L Choi, Jung W McGettigan, Melissa J Rose, Trevor Ahmed, Abraham Kim, Jongphil Jiang, Kun Balagurunathan, Yoganand Qi, Jin Farah, Paola T Rathi, Alisha Permuth, Jennifer B Jeong, Daniel |
author_facet | Polk, Stuart L Choi, Jung W McGettigan, Melissa J Rose, Trevor Ahmed, Abraham Kim, Jongphil Jiang, Kun Balagurunathan, Yoganand Qi, Jin Farah, Paola T Rathi, Alisha Permuth, Jennifer B Jeong, Daniel |
author_sort | Polk, Stuart L |
collection | PubMed |
description | BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive pancreatic precursor lesions that can potentially develop into invasive pancreatic ductal adenocarcinoma. Currently, the International Consensus Guidelines (ICG) for IPMNs provides the basis for evaluating suspected IPMNs on computed tomography (CT) imaging. Despite using the ICG, it remains challenging to accurately predict whether IPMNs harbor high grade or invasive disease which would warrant surgical resection. A supplementary quantitative radiological tool, radiomics, may improve diagnostic accuracy of radiological evaluation of IPMNs. We hypothesized that using CT whole lesion radiomics features in conjunction with the ICG could improve the diagnostic accuracy of predicting IPMN histology. AIM: To evaluate whole lesion CT radiomic analysis of IPMNs for predicting malignant histology compared to International Consensus Guidelines. METHODS: Fifty-one subjects who had pancreatic surgical resection at our institution with histology demonstrating IPMN and available preoperative CT imaging were included in this retrospective cohort. Whole lesion semi-automated segmentation was performed on each preoperative CT using Healthmyne software (Healthmyne, Madison, WI). Thirty-nine relevant radiomic features were extracted from each lesion on each available contrast phase. Univariate analysis of the 39 radiomics features was performed for each contrast phase and values were compared between malignant and benign IPMN groups using logistic regression. Conventional quantitative and qualitative CT measurements were also compared between groups, via χ(2) (categorical) and Mann Whitney U (continuous) variables. RESULTS: Twenty-nine subjects (15 males, age 71 ± 9 years) with high grade or invasive tumor histology comprised the "malignant" cohort, while 22 subjects (11 males, age 70 ± 7 years) with low grade tumor histology were included in the "benign" cohort. Radiomic analysis showed 18/39 precontrast, 19/39 arterial phase, and 21/39 venous phase features differentiated malignant from benign IPMNs (P < 0.05). Multivariate analysis including only ICG criteria yielded two significant variables: thickened and enhancing cyst wall and enhancing mural nodule < 5 mm with an AUC (95%CI) of 0.817 (0.709-0.926). Multivariable post contrast radiomics achieved an AUC (95%CI) of 0.87 (0.767-0.974) for a model including arterial phase radiomics features and 0.834 (0.716-0.953) for a model including venous phase radiomics features. Combined multivariable model including conventional variables and arterial phase radiomics features achieved an AUC (95%CI) of 0.93 (0.85-1.0) with a 5-fold cross validation AUC of 0.90. CONCLUSION: Multi-phase CT radiomics evaluation could play a role in improving predictive capability in diagnosing malignancy in IPMNs. Future larger studies may help determine the clinical significance of our findings. |
format | Online Article Text |
id | pubmed-7327792 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Baishideng Publishing Group Inc |
record_format | MEDLINE/PubMed |
spelling | pubmed-73277922020-07-09 Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy Polk, Stuart L Choi, Jung W McGettigan, Melissa J Rose, Trevor Ahmed, Abraham Kim, Jongphil Jiang, Kun Balagurunathan, Yoganand Qi, Jin Farah, Paola T Rathi, Alisha Permuth, Jennifer B Jeong, Daniel World J Gastroenterol Retrospective Cohort Study BACKGROUND: Intraductal papillary mucinous neoplasms (IPMNs) are non-invasive pancreatic precursor lesions that can potentially develop into invasive pancreatic ductal adenocarcinoma. Currently, the International Consensus Guidelines (ICG) for IPMNs provides the basis for evaluating suspected IPMNs on computed tomography (CT) imaging. Despite using the ICG, it remains challenging to accurately predict whether IPMNs harbor high grade or invasive disease which would warrant surgical resection. A supplementary quantitative radiological tool, radiomics, may improve diagnostic accuracy of radiological evaluation of IPMNs. We hypothesized that using CT whole lesion radiomics features in conjunction with the ICG could improve the diagnostic accuracy of predicting IPMN histology. AIM: To evaluate whole lesion CT radiomic analysis of IPMNs for predicting malignant histology compared to International Consensus Guidelines. METHODS: Fifty-one subjects who had pancreatic surgical resection at our institution with histology demonstrating IPMN and available preoperative CT imaging were included in this retrospective cohort. Whole lesion semi-automated segmentation was performed on each preoperative CT using Healthmyne software (Healthmyne, Madison, WI). Thirty-nine relevant radiomic features were extracted from each lesion on each available contrast phase. Univariate analysis of the 39 radiomics features was performed for each contrast phase and values were compared between malignant and benign IPMN groups using logistic regression. Conventional quantitative and qualitative CT measurements were also compared between groups, via χ(2) (categorical) and Mann Whitney U (continuous) variables. RESULTS: Twenty-nine subjects (15 males, age 71 ± 9 years) with high grade or invasive tumor histology comprised the "malignant" cohort, while 22 subjects (11 males, age 70 ± 7 years) with low grade tumor histology were included in the "benign" cohort. Radiomic analysis showed 18/39 precontrast, 19/39 arterial phase, and 21/39 venous phase features differentiated malignant from benign IPMNs (P < 0.05). Multivariate analysis including only ICG criteria yielded two significant variables: thickened and enhancing cyst wall and enhancing mural nodule < 5 mm with an AUC (95%CI) of 0.817 (0.709-0.926). Multivariable post contrast radiomics achieved an AUC (95%CI) of 0.87 (0.767-0.974) for a model including arterial phase radiomics features and 0.834 (0.716-0.953) for a model including venous phase radiomics features. Combined multivariable model including conventional variables and arterial phase radiomics features achieved an AUC (95%CI) of 0.93 (0.85-1.0) with a 5-fold cross validation AUC of 0.90. CONCLUSION: Multi-phase CT radiomics evaluation could play a role in improving predictive capability in diagnosing malignancy in IPMNs. Future larger studies may help determine the clinical significance of our findings. Baishideng Publishing Group Inc 2020-06-28 2020-06-28 /pmc/articles/PMC7327792/ /pubmed/32655269 http://dx.doi.org/10.3748/wjg.v26.i24.3458 Text en ©The Author(s) 2020. Published by Baishideng Publishing Group Inc. All rights reserved. http://creativecommons.org/licenses/by-nc/4.0/ This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. |
spellingShingle | Retrospective Cohort Study Polk, Stuart L Choi, Jung W McGettigan, Melissa J Rose, Trevor Ahmed, Abraham Kim, Jongphil Jiang, Kun Balagurunathan, Yoganand Qi, Jin Farah, Paola T Rathi, Alisha Permuth, Jennifer B Jeong, Daniel Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title | Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title_full | Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title_fullStr | Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title_full_unstemmed | Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title_short | Multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
title_sort | multiphase computed tomography radiomics of pancreatic intraductal papillary mucinous neoplasms to predict malignancy |
topic | Retrospective Cohort Study |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7327792/ https://www.ncbi.nlm.nih.gov/pubmed/32655269 http://dx.doi.org/10.3748/wjg.v26.i24.3458 |
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