High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision
ObjectiveThis study aimed to develop a nomogram that combines intratumoral and peritumoral radiomics based on multi-parametric MRI for predicting the postoperative pathological upgrade of high-risk breast lesions and sparing unnecessary surgeries.MethodsIn this retrospective study, 138 patients with...
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Frontiers Media S.A.
2024-12-01
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| Series: | Frontiers in Oncology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2024.1479565/full |
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| author | Tingting Liao Yuting Yang Xiaohui Lin Rushan Ouyang Yaohong Deng Jie Ma |
| author_facet | Tingting Liao Yuting Yang Xiaohui Lin Rushan Ouyang Yaohong Deng Jie Ma |
| author_sort | Tingting Liao |
| collection | DOAJ |
| description | ObjectiveThis study aimed to develop a nomogram that combines intratumoral and peritumoral radiomics based on multi-parametric MRI for predicting the postoperative pathological upgrade of high-risk breast lesions and sparing unnecessary surgeries.MethodsIn this retrospective study, 138 patients with high-risk breast lesions (January 1, 2019, to January 1, 2023) were randomly divided into a training set (n=96) and a validation set (n=42) at a 7:3 ratio. The best-performing MRI sequence for intratumoral radiomics was selected to develop individual and combined radiomics scores (Rad-Scores). The best Rad-Score was integrated with independent clinical and radiological risk factors by a nomogram. The diagnostic performance of the nomogram was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, along with accuracy, specificity, and sensitivity analysis.ResultsThe nomogram based on the combined intratumoral and peritumoral Rad-Score of the dynamic contrast-enhanced MRI and clinical-radiological features achieved superior diagnostic efficacy in the training (AUC=0.914) and validation set (AUC=0.867) compared to other models. It also achieved a specificity and accuracy of 85.1% and 82.3% during training and 66.7% and 76.2% during validation.ConclusionThe nomogram encapsulating the combined intratumoral and peritumoral radiomics demonstrated superior diagnostic efficacy in postoperative pathological upgrades of high-risk breast lesions, enabling clinicians to make more informed decisions about interventions and follow-up strategies. |
| format | Article |
| id | doaj-art-ed54c38f8ca84cd0bd940aa9daffb7b1 |
| institution | Kabale University |
| issn | 2234-943X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Frontiers Media S.A. |
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| series | Frontiers in Oncology |
| spelling | doaj-art-ed54c38f8ca84cd0bd940aa9daffb7b12024-12-18T06:43:51ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2024-12-011410.3389/fonc.2024.14795651479565High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excisionTingting Liao0Yuting Yang1Xiaohui Lin2Rushan Ouyang3Yaohong Deng4Jie Ma5Department of Radiology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, ChinaDepartment of Radiology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, ChinaDepartment of Radiology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, ChinaDepartment of Radiology, The Eighth Affiliated Hospital, Sun Yat-sen University, Shenzhen, ChinaDepartment of Research & Development, Yizhun Medical AI Co. Ltd., Beijing, ChinaDepartment of Radiology, Shenzhen People’s Hospital, The Second Clinical Medical College of Jinan University, Shenzhen, ChinaObjectiveThis study aimed to develop a nomogram that combines intratumoral and peritumoral radiomics based on multi-parametric MRI for predicting the postoperative pathological upgrade of high-risk breast lesions and sparing unnecessary surgeries.MethodsIn this retrospective study, 138 patients with high-risk breast lesions (January 1, 2019, to January 1, 2023) were randomly divided into a training set (n=96) and a validation set (n=42) at a 7:3 ratio. The best-performing MRI sequence for intratumoral radiomics was selected to develop individual and combined radiomics scores (Rad-Scores). The best Rad-Score was integrated with independent clinical and radiological risk factors by a nomogram. The diagnostic performance of the nomogram was evaluated using the area under the curve (AUC) of the receiver operating characteristic curve, along with accuracy, specificity, and sensitivity analysis.ResultsThe nomogram based on the combined intratumoral and peritumoral Rad-Score of the dynamic contrast-enhanced MRI and clinical-radiological features achieved superior diagnostic efficacy in the training (AUC=0.914) and validation set (AUC=0.867) compared to other models. It also achieved a specificity and accuracy of 85.1% and 82.3% during training and 66.7% and 76.2% during validation.ConclusionThe nomogram encapsulating the combined intratumoral and peritumoral radiomics demonstrated superior diagnostic efficacy in postoperative pathological upgrades of high-risk breast lesions, enabling clinicians to make more informed decisions about interventions and follow-up strategies.https://www.frontiersin.org/articles/10.3389/fonc.2024.1479565/fullbreastradiomicsmagnetic resonance imagingnomogramshigh-risk |
| spellingShingle | Tingting Liao Yuting Yang Xiaohui Lin Rushan Ouyang Yaohong Deng Jie Ma High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision Frontiers in Oncology breast radiomics magnetic resonance imaging nomograms high-risk |
| title | High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| title_full | High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| title_fullStr | High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| title_full_unstemmed | High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| title_short | High-risk breast lesions: a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| title_sort | high risk breast lesions a combined intratumoral and peritumoral radiomics nomogram model to predict pathologic upgrade and reduce unnecessary surgical excision |
| topic | breast radiomics magnetic resonance imaging nomograms high-risk |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2024.1479565/full |
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