Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics
DC Field | Value | Language |
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dc.contributor.author | Hyun Jung Yoon | - |
dc.contributor.author | Hyunjin Park | - |
dc.contributor.author | Ho Yun Lee | - |
dc.contributor.author | Insuk Sohn | - |
dc.contributor.author | Joonghyun Ahn | - |
dc.contributor.author | Seung-Hak Lee | - |
dc.date.accessioned | 2020-12-22T06:27:30Z | - |
dc.date.accessioned | 2020-12-22T06:27:30Z | - |
dc.date.available | 2020-12-22T06:27:30Z | - |
dc.date.available | 2020-12-22T06:27:30Z | - |
dc.date.created | 2020-09-09 | - |
dc.date.issued | 2020-09 | - |
dc.identifier.issn | 1759-7706 | - |
dc.identifier.uri | https://pr.ibs.re.kr/handle/8788114/8485 | - |
dc.description.abstract | © 2020 The Authors. Thoracic Cancer published by China Lung Oncology Group and John Wiley & Sons Australia, Ltd. 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 | - |
dc.description.uri | 1 | - |
dc.language | 영어 | - |
dc.publisher | WILEY-BLACKWELL | - |
dc.title | Prediction of tumor doubling time of lung adenocarcinoma using radiomic margin characteristics | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.identifier.wosid | 000551398500001 | - |
dc.identifier.scopusid | 2-s2.0-85088363689 | - |
dc.identifier.rimsid | 72817 | - |
dc.contributor.affiliatedAuthor | Hyunjin Park | - |
dc.identifier.doi | 10.1111/1759-7714.13580 | - |
dc.identifier.bibliographicCitation | Thoracic Cancer, v.11, no.9, pp.2600 - 2609 | - |
dc.citation.title | Thoracic Cancer | - |
dc.citation.volume | 11 | - |
dc.citation.number | 9 | - |
dc.citation.startPage | 2600 | - |
dc.citation.endPage | 2609 | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.subject.keywordAuthor | Computed tomography | - |
dc.subject.keywordAuthor | lung adenocarcinoma | - |
dc.subject.keywordAuthor | radiomics | - |
dc.subject.keywordAuthor | tumor doubling time | - |
dc.subject.keywordAuthor | tumor margin | - |