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Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures
High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575781/ https://www.ncbi.nlm.nih.gov/pubmed/34750471 http://dx.doi.org/10.1038/s41598-021-01414-z |
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author | Streeter, Samuel S. Hunt, Brady Zuurbier, Rebecca A. Wells, Wendy A. Paulsen, Keith D. Pogue, Brian W. |
author_facet | Streeter, Samuel S. Hunt, Brady Zuurbier, Rebecca A. Wells, Wendy A. Paulsen, Keith D. Pogue, Brian W. |
author_sort | Streeter, Samuel S. |
collection | PubMed |
description | High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available. |
format | Online Article Text |
id | pubmed-8575781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85757812021-11-09 Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures Streeter, Samuel S. Hunt, Brady Zuurbier, Rebecca A. Wells, Wendy A. Paulsen, Keith D. Pogue, Brian W. Sci Rep Article High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available. Nature Publishing Group UK 2021-11-08 /pmc/articles/PMC8575781/ /pubmed/34750471 http://dx.doi.org/10.1038/s41598-021-01414-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Streeter, Samuel S. Hunt, Brady Zuurbier, Rebecca A. Wells, Wendy A. Paulsen, Keith D. Pogue, Brian W. Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title | Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title_full | Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title_fullStr | Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title_full_unstemmed | Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title_short | Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
title_sort | developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8575781/ https://www.ncbi.nlm.nih.gov/pubmed/34750471 http://dx.doi.org/10.1038/s41598-021-01414-z |
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