Purpose: To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients.
Methods: This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images. Subsequently, multivariate LR (logistic regression) analysis incorporating both radiomic scores and clinical factors was performed to construct a nomogram. Finally, Receiver operating characteristics (ROC) curve analysis and decision curve analysis (DCA) were employed to evaluate and validate the diagnostic accuracy and effectiveness of the nomogram.
Results: A total of 1122 patients were included in this study. Among them, 427 patients exhibited a favorable response to NAC chemotherapy, while 695 patients demonstrated a poor response to NAC therapy. The radiomics model achieved an AUC value of 0.84 in the training cohort and 0.83 in the validation cohort. The ultrasound-based radiomics-clinical nomogram achieved an AUC value of 0.90 in the training cohort and 0.91 in the validation cohort.
Conclusions: Ultrasound-based radiomics-clinical nomogram can accurately predict the effectiveness of NAC therapy by predicting RCB grading in breast cancer patients.
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http://dx.doi.org/10.1002/jcu.23666 | DOI Listing |
J Clin Ultrasound
June 2024
Department of Ultrasound, Fujian Medical University Union Hospital, Fuzhou, China.
Purpose: To assess the predictive value of an ultrasound-based radiomics-clinical nomogram for grading residual cancer burden (RCB) in breast cancer patients.
Methods: This retrospective study of breast cancer patients who underwent neoadjuvant therapy (NAC) and ultrasound scanning between November 2020 and July 2023. First, a radiomics model was established based on ultrasound images.
Transl Cancer Res
January 2024
Department of Ultrasound Imaging, The Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou, China.
Background: Conventional ultrasound (CUS) technology has proven to be successful in the identification of thyroid nodules. Moreover, the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) was developed for the purpose of evaluating the risk of thyroid nodules based on ultrasound imaging. Nevertheless, identifying papillary thyroid microcarcinoma (PTMC) from TI-RADS 3 nodules using this system can be difficult due to overlapping morphological features.
View Article and Find Full Text PDFBiomed Eng Online
December 2023
State Key Laboratory of Ultrasound in Medicine and Engineering, College of Biomedical Engineering, Chongqing Medical University, Chongqing, 400016, China.
Background: Prediction of non-perfusion volume ratio (NPVR) is critical in selecting patients with uterine fibroids who will potentially benefit from ultrasound-guided high-intensity focused ultrasound (HIFU) treatment, as it reduces the risk of treatment failure. The purpose of this study is to construct an optimal model for predicting NPVR based on T2-weighted magnetic resonance imaging (T2MRI) radiomics features combined with clinical parameters by machine learning.
Materials And Methods: This retrospective study was conducted among 223 patients diagnosed with uterine fibroids from two centers.
J Ultrasound Med
February 2024
Department of Medical Ultrasound, The First Affiliated Hospital of Guangxi Medical University, Nanning, China.
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