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Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients

Rectal cancer is the eighth most prevalent malignancy worldwide with a 3.2% mortality rate and 3.9% incidence rate. Radiologists still have difficulty in correctly diagnosing lymph node metastases that have been suspected preoperatively. To assess the effectiveness of a model combining clinical and...

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Autores principales: Li, Yehan, Zeng, Chen, Du, Yong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Lippincott Williams & Wilkins 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637426/
https://www.ncbi.nlm.nih.gov/pubmed/37960749
http://dx.doi.org/10.1097/MD.0000000000036004
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author Li, Yehan
Zeng, Chen
Du, Yong
author_facet Li, Yehan
Zeng, Chen
Du, Yong
author_sort Li, Yehan
collection PubMed
description Rectal cancer is the eighth most prevalent malignancy worldwide with a 3.2% mortality rate and 3.9% incidence rate. Radiologists still have difficulty in correctly diagnosing lymph node metastases that have been suspected preoperatively. To assess the effectiveness of a model combining clinical and radiomics features for the preoperative prediction of lymph node metastasis in rectal cancer. We retrospectively analyzed data from 104 patients with rectal cancer. All patients were selected as samples for the training (n = 72) and validation cohorts (n = 32). Lymph nodes (LNs) in diffusion-weighted images were analyzed to obtain 842 radiomic characteristics, which were then used to draw the region of interest. Logistic regression, least absolute shrinkage and selection operator, and between-group and within-group correlation analyses were combined to establish the radiomic score (rad-score). Receiver operating characteristic curves were used to estimate the prediction accuracy of the model. A calibration curve was constructed to test the predictive ability of the model. A decision curve analysis was performed to analyze the model’s value in clinical application. The area under the curve for the radiomics-clinical, clinical, and radiomics models was 0.856, 0.810, and 0.781, respectively, in the training cohort and 0.880, 0.849, and 0.827, respectively, in the validation cohort. The calibration curve and DCA showed that the radiomics-clinical prediction model had good prediction accuracy, which was higher than that of the other models. The radiomics-clinical model showed a favorable predictive performance for the preoperative prediction of LN metastasis in patients with rectal cancer.
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spelling pubmed-106374262023-11-15 Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients Li, Yehan Zeng, Chen Du, Yong Medicine (Baltimore) 5700 Rectal cancer is the eighth most prevalent malignancy worldwide with a 3.2% mortality rate and 3.9% incidence rate. Radiologists still have difficulty in correctly diagnosing lymph node metastases that have been suspected preoperatively. To assess the effectiveness of a model combining clinical and radiomics features for the preoperative prediction of lymph node metastasis in rectal cancer. We retrospectively analyzed data from 104 patients with rectal cancer. All patients were selected as samples for the training (n = 72) and validation cohorts (n = 32). Lymph nodes (LNs) in diffusion-weighted images were analyzed to obtain 842 radiomic characteristics, which were then used to draw the region of interest. Logistic regression, least absolute shrinkage and selection operator, and between-group and within-group correlation analyses were combined to establish the radiomic score (rad-score). Receiver operating characteristic curves were used to estimate the prediction accuracy of the model. A calibration curve was constructed to test the predictive ability of the model. A decision curve analysis was performed to analyze the model’s value in clinical application. The area under the curve for the radiomics-clinical, clinical, and radiomics models was 0.856, 0.810, and 0.781, respectively, in the training cohort and 0.880, 0.849, and 0.827, respectively, in the validation cohort. The calibration curve and DCA showed that the radiomics-clinical prediction model had good prediction accuracy, which was higher than that of the other models. The radiomics-clinical model showed a favorable predictive performance for the preoperative prediction of LN metastasis in patients with rectal cancer. Lippincott Williams & Wilkins 2023-11-10 /pmc/articles/PMC10637426/ /pubmed/37960749 http://dx.doi.org/10.1097/MD.0000000000036004 Text en Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc. https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial License 4.0 (CCBY-NC) (https://creativecommons.org/licenses/by-nc/4.0/) , where it is permissible to download, share, remix, transform, and buildup the work provided it is properly cited. The work cannot be used commercially without permission from the journal.
spellingShingle 5700
Li, Yehan
Zeng, Chen
Du, Yong
Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title_full Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title_fullStr Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title_full_unstemmed Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title_short Use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
title_sort use of a radiomics-clinical model based on magnetic diffusion-weighted imaging for preoperative prediction of lymph node metastasis in rectal cancer patients
topic 5700
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10637426/
https://www.ncbi.nlm.nih.gov/pubmed/37960749
http://dx.doi.org/10.1097/MD.0000000000036004
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AT duyong useofaradiomicsclinicalmodelbasedonmagneticdiffusionweightedimagingforpreoperativepredictionoflymphnodemetastasisinrectalcancerpatients