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Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis

BACKGROUND: Development of a radiomics model for predicting lymph node metastasis status in rectal cancer patients based on 3-dimensional endoanal rectal ultrasound images. METHODS: This study retrospectively included 79 patients (41 with lymph node metastasis positive and 38 with lymph node metasta...

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Autores principales: Li, Jin, Chen, Shao-Na, Lin, Yun-Yong, Wu, Yi-Wen, Lu, Wen-Jie, Ye, Da-Lin, Chen, Fei, Qiu, Shao-Dong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Turkish Society of Gastroenterology 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10334677/
https://www.ncbi.nlm.nih.gov/pubmed/37158536
http://dx.doi.org/10.5152/tjg.2023.22257
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author Li, Jin
Chen, Shao-Na
Lin, Yun-Yong
Wu, Yi-Wen
Lu, Wen-Jie
Ye, Da-Lin
Chen, Fei
Qiu, Shao-Dong
author_facet Li, Jin
Chen, Shao-Na
Lin, Yun-Yong
Wu, Yi-Wen
Lu, Wen-Jie
Ye, Da-Lin
Chen, Fei
Qiu, Shao-Dong
author_sort Li, Jin
collection PubMed
description BACKGROUND: Development of a radiomics model for predicting lymph node metastasis status in rectal cancer patients based on 3-dimensional endoanal rectal ultrasound images. METHODS: This study retrospectively included 79 patients (41 with lymph node metastasis positive and 38 with lymph node metastasis negative) diagnosed with rectal cancer in our hospital from January 2018 to February 2022. The tumor’s region of interest is first delineated by radiologists, from which radiomics features are extracted. Radiomics features were then selected by independent samples t-test, correlation coefficient analysis between features, and least absolute shrinkage and regression with selection operator. Finally, a multilayer neural network model is developed using the selected radiomics features, and nested cross-validation is performed on it. These models were validated by assessing their diagnostic performance and comparing the areas under the curve and recall rate curve in the test set. RESULTS: The areas under the curve of radiologist was 0.662 and the F1 score was 0.632. Thirty-four radiomics features were significantly associated with lymph node metastasis (P < .05), and 10 features were finally selected for developing multilayer neural network models. The areas under the curve of the multilayer neural network models were 0.787, 0.761, 0.853, and the mean areas under the curve was 0.800. The F1 scores of the multilayer neural network models were 0.738, 0.740, and 0.818, and the mean F1 score was 0.771. CONCLUSIONS: Radiomics models based on 3-dimensional endoanal rectal ultrasound can be used to identify lymph node metastasis status in rectal cancer patient with good diagnostic performance.
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spelling pubmed-103346772023-07-12 Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis Li, Jin Chen, Shao-Na Lin, Yun-Yong Wu, Yi-Wen Lu, Wen-Jie Ye, Da-Lin Chen, Fei Qiu, Shao-Dong Turk J Gastroenterol Original Article BACKGROUND: Development of a radiomics model for predicting lymph node metastasis status in rectal cancer patients based on 3-dimensional endoanal rectal ultrasound images. METHODS: This study retrospectively included 79 patients (41 with lymph node metastasis positive and 38 with lymph node metastasis negative) diagnosed with rectal cancer in our hospital from January 2018 to February 2022. The tumor’s region of interest is first delineated by radiologists, from which radiomics features are extracted. Radiomics features were then selected by independent samples t-test, correlation coefficient analysis between features, and least absolute shrinkage and regression with selection operator. Finally, a multilayer neural network model is developed using the selected radiomics features, and nested cross-validation is performed on it. These models were validated by assessing their diagnostic performance and comparing the areas under the curve and recall rate curve in the test set. RESULTS: The areas under the curve of radiologist was 0.662 and the F1 score was 0.632. Thirty-four radiomics features were significantly associated with lymph node metastasis (P < .05), and 10 features were finally selected for developing multilayer neural network models. The areas under the curve of the multilayer neural network models were 0.787, 0.761, 0.853, and the mean areas under the curve was 0.800. The F1 scores of the multilayer neural network models were 0.738, 0.740, and 0.818, and the mean F1 score was 0.771. CONCLUSIONS: Radiomics models based on 3-dimensional endoanal rectal ultrasound can be used to identify lymph node metastasis status in rectal cancer patient with good diagnostic performance. Turkish Society of Gastroenterology 2023-05-01 /pmc/articles/PMC10334677/ /pubmed/37158536 http://dx.doi.org/10.5152/tjg.2023.22257 Text en © 2023 authors https://creativecommons.org/licenses/by/4.0/ Content of this journal is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. (https://creativecommons.org/licenses/by/4.0/)
spellingShingle Original Article
Li, Jin
Chen, Shao-Na
Lin, Yun-Yong
Wu, Yi-Wen
Lu, Wen-Jie
Ye, Da-Lin
Chen, Fei
Qiu, Shao-Dong
Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title_full Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title_fullStr Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title_full_unstemmed Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title_short Development and Validation of a Radiomics Model Based on 3-Dimensional Endoanal Rectal Ultrasound of Rectal Cancer for Predicting Lymph Node Metastasis
title_sort development and validation of a radiomics model based on 3-dimensional endoanal rectal ultrasound of rectal cancer for predicting lymph node metastasis
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10334677/
https://www.ncbi.nlm.nih.gov/pubmed/37158536
http://dx.doi.org/10.5152/tjg.2023.22257
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