Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy
After neoadjuvant chemoradiotherapy (NCRT) in locally advanced esophageal squamous cell cancer (ESCC), roughly 40% of the patients may achieve pathologic complete response (pCR). Those patients may benefit from organ-saving strategy if the probability of pCR could be correctly identified before esop...
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| Format: | Article |
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Frontiers Media S.A.
2021-02-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2020.615167/full |
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| author | Yue Li Yue Li Jun Liu Hong-xuan Li Xu-wei Cai Zhi-gang Li Xiao-dan Ye Hao-hua Teng Xiao-long Fu Wen Yu |
| author_facet | Yue Li Yue Li Jun Liu Hong-xuan Li Xu-wei Cai Zhi-gang Li Xiao-dan Ye Hao-hua Teng Xiao-long Fu Wen Yu |
| author_sort | Yue Li |
| collection | DOAJ |
| description | After neoadjuvant chemoradiotherapy (NCRT) in locally advanced esophageal squamous cell cancer (ESCC), roughly 40% of the patients may achieve pathologic complete response (pCR). Those patients may benefit from organ-saving strategy if the probability of pCR could be correctly identified before esophagectomy. A reliable approach to predict pathological response allows future studies to investigate individualized treatment plans.MethodAll eligible patients treated in our center from June 2012 to June 2019 were retrospectively collected. Radiomics features extracted from pre-/post-NCRT CT images were selected by univariate logistic and LASSO regression. A radiomics signature (RS) developed with selected features was combined with clinical variables to construct RS+clinical model with multivariate logistic regression, which was internally validated by bootstrapping. Performance and clinical usefulness of RS+clinical model were assessed by receiver operating characteristic (ROC) curves and decision curve analysis, respectively.ResultsAmong the 121 eligible patients, 51 achieved pCR (42.1%) after NCRT. Eighteen radiomics features were selected and incorporated into RS. The RS+clinical model has improved prediction performance for pCR compared with the clinical model (corrected area under the ROC curve, 0.84 vs. 0.70). At the 60% probability threshold cutoff (i.e., the patient would opt for observation if his probability of pCR was >60%), net 13% surgeries could be avoided by RS+clinical model, equivalent to implementing organ-saving strategy in 31.37% of the 51 true-pCR cases.ConclusionThe model built with CT radiomics features and clinical variables shows the potential of predicting pCR after NCRT; it provides significant clinical benefit in identifying qualified patients to receive individualized organ-saving treatment plans. |
| first_indexed | 2024-12-20T08:43:26Z |
| format | Article |
| id | doaj.art-1ad8ec3b069645fa94c2d6b99d3f0f0d |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-20T08:43:26Z |
| publishDate | 2021-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-1ad8ec3b069645fa94c2d6b99d3f0f0d2022-12-21T19:46:19ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-02-011010.3389/fonc.2020.615167615167Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant ChemoradiotherapyYue Li0Yue Li1Jun Liu2Hong-xuan Li3Xu-wei Cai4Zhi-gang Li5Xiao-dan Ye6Hao-hua Teng7Xiao-long Fu8Wen Yu9Department of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaShanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Thoracic Surgery, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Radiology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Pathology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaDepartment of Radiation Oncology, Shanghai Chest Hospital, Shanghai Jiao Tong University, Shanghai, ChinaAfter neoadjuvant chemoradiotherapy (NCRT) in locally advanced esophageal squamous cell cancer (ESCC), roughly 40% of the patients may achieve pathologic complete response (pCR). Those patients may benefit from organ-saving strategy if the probability of pCR could be correctly identified before esophagectomy. A reliable approach to predict pathological response allows future studies to investigate individualized treatment plans.MethodAll eligible patients treated in our center from June 2012 to June 2019 were retrospectively collected. Radiomics features extracted from pre-/post-NCRT CT images were selected by univariate logistic and LASSO regression. A radiomics signature (RS) developed with selected features was combined with clinical variables to construct RS+clinical model with multivariate logistic regression, which was internally validated by bootstrapping. Performance and clinical usefulness of RS+clinical model were assessed by receiver operating characteristic (ROC) curves and decision curve analysis, respectively.ResultsAmong the 121 eligible patients, 51 achieved pCR (42.1%) after NCRT. Eighteen radiomics features were selected and incorporated into RS. The RS+clinical model has improved prediction performance for pCR compared with the clinical model (corrected area under the ROC curve, 0.84 vs. 0.70). At the 60% probability threshold cutoff (i.e., the patient would opt for observation if his probability of pCR was >60%), net 13% surgeries could be avoided by RS+clinical model, equivalent to implementing organ-saving strategy in 31.37% of the 51 true-pCR cases.ConclusionThe model built with CT radiomics features and clinical variables shows the potential of predicting pCR after NCRT; it provides significant clinical benefit in identifying qualified patients to receive individualized organ-saving treatment plans.https://www.frontiersin.org/articles/10.3389/fonc.2020.615167/fullneoadjuvant chemoradiationesophageal cancerresponse predictionorgan-saving treatmentradiomics |
| spellingShingle | Yue Li Yue Li Jun Liu Hong-xuan Li Xu-wei Cai Zhi-gang Li Xiao-dan Ye Hao-hua Teng Xiao-long Fu Wen Yu Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy Frontiers in Oncology neoadjuvant chemoradiation esophageal cancer response prediction organ-saving treatment radiomics |
| title | Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy |
| title_full | Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy |
| title_fullStr | Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy |
| title_full_unstemmed | Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy |
| title_short | Radiomics Signature Facilitates Organ-Saving Strategy in Patients With Esophageal Squamous Cell Cancer Receiving Neoadjuvant Chemoradiotherapy |
| title_sort | radiomics signature facilitates organ saving strategy in patients with esophageal squamous cell cancer receiving neoadjuvant chemoradiotherapy |
| topic | neoadjuvant chemoradiation esophageal cancer response prediction organ-saving treatment radiomics |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2020.615167/full |
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