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Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics
BACKGROUND: Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation betwee...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons Australia, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471031/ https://www.ncbi.nlm.nih.gov/pubmed/32705793 http://dx.doi.org/10.1111/1759-7714.13580 |
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author | Yoon, Hyun Jung Park, Hyunjin Lee, Ho Yun Sohn, Insuk Ahn, Joonghyun Lee, Seung‐Hak |
author_facet | Yoon, Hyun Jung Park, Hyunjin Lee, Ho Yun Sohn, Insuk Ahn, Joonghyun Lee, Seung‐Hak |
author_sort | Yoon, Hyun Jung |
collection | PubMed |
description | BACKGROUND: Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth. METHODS: We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume‐based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected. RESULTS: Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface‐to‐volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface‐to‐volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness. CONCLUSIONS: This study demonstrated the potential of margin‐related radiomic features to predict tumor DT in lung ADCs. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: We found a relationship between margin‐related radiomic features and tumor doubling time. WHAT THIS STUDY ADDS: Margin‐related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies. |
format | Online Article Text |
id | pubmed-7471031 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | John Wiley & Sons Australia, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-74710312020-09-09 Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics Yoon, Hyun Jung Park, Hyunjin Lee, Ho Yun Sohn, Insuk Ahn, Joonghyun Lee, Seung‐Hak Thorac Cancer Original Articles BACKGROUND: Because shape or irregularity along the tumor perimeter can result from interactions between the tumor and the surrounding parenchyma, there could be a difference in tumor growth rate according to tumor margin or shape. However, no attempt has been made to evaluate the correlation between margin or shape features and tumor growth. METHODS: We evaluated 52 lung adenocarcinoma (ADC) patients who had at least two computed tomographic (CT) examinations before curative resection. Volume‐based doubling times (DTs) were calculated based on CT scans, and patients were divided into two groups according to the growth pattern (GP) of their ADCs (gradually growing tumors [GP I] vs. growing tumors with a temporary decrease in DT [GP II]). CT radiomic features reflecting margin characteristics were extracted, and radiomic features reflective of tumor DT were selected. RESULTS: Among the 52 patients, 41 (78.8%) were assigned to GP I and 11 (21.2%) to GP II. Of the 94 radiomic features extracted, eccentricity, surface‐to‐volume ratio, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5) were ultimately selected for tumor DT prediction. Selected radiomic features in GP I were surface‐to‐volume ratio, contrast, LoG uniformity (σ = 3.5), and LoG skewness (σ = 0.5), similar to those for total subjects, whereas the radiomic features in GP II were solidity, energy, and busyness. CONCLUSIONS: This study demonstrated the potential of margin‐related radiomic features to predict tumor DT in lung ADCs. KEY POINTS: SIGNIFICANT FINDINGS OF THE STUDY: We found a relationship between margin‐related radiomic features and tumor doubling time. WHAT THIS STUDY ADDS: Margin‐related radiomic features can potentially be used as noninvasive biomarkers to predict tumor doubling time in lung adenocarcinoma and inform treatment strategies. John Wiley & Sons Australia, Ltd 2020-07-23 2020-09 /pmc/articles/PMC7471031/ /pubmed/32705793 http://dx.doi.org/10.1111/1759-7714.13580 Text en © 2020 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Original Articles Yoon, Hyun Jung Park, Hyunjin Lee, Ho Yun Sohn, Insuk Ahn, Joonghyun Lee, Seung‐Hak Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title_full | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title_fullStr | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title_full_unstemmed | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title_short | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
title_sort | prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics |
topic | Original Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7471031/ https://www.ncbi.nlm.nih.gov/pubmed/32705793 http://dx.doi.org/10.1111/1759-7714.13580 |
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