Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer
ObjectiveTo investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spre...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-10-01
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| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2023.1194120/full |
| _version_ | 1797659212934807552 |
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| author | Xue Dong Gang Ren Yanhong Chen Huifang Yong Tingting Zhang Qiufeng Yin Zhongyang Zhang Shijun Yuan Yaqiong Ge Shaofeng Duan Huanhuan Liu Dengbin Wang |
| author_facet | Xue Dong Gang Ren Yanhong Chen Huifang Yong Tingting Zhang Qiufeng Yin Zhongyang Zhang Shijun Yuan Yaqiong Ge Shaofeng Duan Huanhuan Liu Dengbin Wang |
| author_sort | Xue Dong |
| collection | DOAJ |
| description | ObjectiveTo investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm).MethodsThis retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI. Minimum redundancy and maximum relevance (mRMR) and support vector machine were performed to select the best performed radiomics features for predicting LN metastasis. Multivariate logistic regression analysis was then used to construct the clinical and clinical-radiomics combined models. The model performance for predicting LN metastasis was assessed by receiver operator characteristic curve (ROC) and clinical utility implementing a nomogram and decision curve analysis (DCA). The predictive performance for LN metastasis was also compared between the combined model and human readers (2 seniors).ResultsFourteen radiomics features and 2 clinical characteristics were selected for predicting LN metastasis. In the testing cohort, a higher positive predictive value of 75.9% for the combined model was achieved than those of the clinical model (44.8%) and two readers (reader 1: 54.9%, reader 2: 56.3%) in identifying LN metastasis. The interobserver agreement between 2 readers was moderate with a kappa value of 0.416. A clinical-radiomics nomogram and decision curve analysis demonstrated that the combined model was clinically useful.ConclusionT2WI-based radiomics combined with clinical data could improve the efficacy in noninvasively evaluating LN metastasis for the low T-staging rectal cancer and aid in tailoring treatment strategies. |
| first_indexed | 2024-03-11T18:10:39Z |
| format | Article |
| id | doaj.art-e3a031bc15544c26bc9e620290bf2ca9 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-03-11T18:10:39Z |
| publishDate | 2023-10-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-e3a031bc15544c26bc9e620290bf2ca92023-10-16T15:20:08ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2023-10-011310.3389/fonc.2023.11941201194120Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancerXue Dong0Gang Ren1Yanhong Chen2Huifang Yong3Tingting Zhang4Qiufeng Yin5Zhongyang Zhang6Shijun Yuan7Yaqiong Ge8Shaofeng Duan9Huanhuan Liu10Dengbin Wang11Department of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Integrated Traditional Chinese and Western Medicine Hospital, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Medicine, GE Healthcare China, Shanghai, ChinaDepartment of Medicine, GE Healthcare China, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaDepartment of Radiology, Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, ChinaObjectiveTo investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm).MethodsThis retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI. Minimum redundancy and maximum relevance (mRMR) and support vector machine were performed to select the best performed radiomics features for predicting LN metastasis. Multivariate logistic regression analysis was then used to construct the clinical and clinical-radiomics combined models. The model performance for predicting LN metastasis was assessed by receiver operator characteristic curve (ROC) and clinical utility implementing a nomogram and decision curve analysis (DCA). The predictive performance for LN metastasis was also compared between the combined model and human readers (2 seniors).ResultsFourteen radiomics features and 2 clinical characteristics were selected for predicting LN metastasis. In the testing cohort, a higher positive predictive value of 75.9% for the combined model was achieved than those of the clinical model (44.8%) and two readers (reader 1: 54.9%, reader 2: 56.3%) in identifying LN metastasis. The interobserver agreement between 2 readers was moderate with a kappa value of 0.416. A clinical-radiomics nomogram and decision curve analysis demonstrated that the combined model was clinically useful.ConclusionT2WI-based radiomics combined with clinical data could improve the efficacy in noninvasively evaluating LN metastasis for the low T-staging rectal cancer and aid in tailoring treatment strategies.https://www.frontiersin.org/articles/10.3389/fonc.2023.1194120/fullrectal cancermagnetic resonance imagingradiomicslymph nodemetastasis |
| spellingShingle | Xue Dong Gang Ren Yanhong Chen Huifang Yong Tingting Zhang Qiufeng Yin Zhongyang Zhang Shijun Yuan Yaqiong Ge Shaofeng Duan Huanhuan Liu Dengbin Wang Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer Frontiers in Oncology rectal cancer magnetic resonance imaging radiomics lymph node metastasis |
| title | Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer |
| title_full | Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer |
| title_fullStr | Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer |
| title_full_unstemmed | Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer |
| title_short | Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer |
| title_sort | effects of mri radiomics combined with clinical data in evaluating lymph node metastasis in mrt1 3a staging rectal cancer |
| topic | rectal cancer magnetic resonance imaging radiomics lymph node metastasis |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2023.1194120/full |
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