Predicting Breast Cancer in Breast Imaging Reporting and Data System (BI-RADS) Ultrasound Category 4 or 5 Lesions: A Nomogram Combining Radiomics and BI-RADS
Autor: | Wei-quan Luo, Hang-Tong Hu, Fu-qiang Zeng, Wei Wang, Qing-xiu Huang, Xiao-Wen Huang |
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Rok vydání: | 2019 |
Předmět: |
0301 basic medicine
Adult Research Report medicine.medical_specialty Breast imaging lcsh:Medicine BI-RADS Breast Neoplasms Article 03 medical and health sciences 0302 clinical medicine Breast cancer Radiomics medicine Humans lcsh:Science Ultrasonography Multidisciplinary Receiver operating characteristic business.industry lcsh:R Ultrasound Reproducibility of Results Nomogram Middle Aged medicine.disease Confidence interval Nomograms 030104 developmental biology ROC Curve Area Under Curve Calibration lcsh:Q Female Radiology business 030217 neurology & neurosurgery Algorithms |
Zdroj: | Scientific Reports Scientific Reports, Vol 9, Iss 1, Pp 1-11 (2019) |
ISSN: | 2045-2322 |
Popis: | Radiomics reflects the texture and morphological features of tumours by quantitatively analysing the grey values of medical images. We aim to develop a nomogram incorporating radiomics and the Breast Imaging Reporting and Data System (BI-RADS) for predicting breast cancer in BI-RADS ultrasound (US) category 4 or 5 lesions. From January 2017 to August 2018, a total of 315 pathologically proven breast lesions were included. Patients from the study population were divided into a training group (n = 211) and a validation group (n = 104) according to a cut-off date of March 1st, 2018. Each lesion was assigned a category (4A, 4B, 4C or 5) according to the second edition of the American College of Radiology (ACR) BI-RADS US. A radiomics score was generated from the US image. A nomogram was developed based on the results of multivariate regression analysis from the training group. Discrimination, calibration and clinical usefulness of the nomogram for predicting breast cancer were assessed in the validation group. The radiomics score included 9 selected radiomics features. The radiomics score and BI-RADS category were independently associated with breast malignancy. The nomogram incorporating the radiomics score and BI-RADS category showed better discrimination (area under the receiver operating characteristic curve [AUC]: 0.928; 95% confidence interval [CI]: 0.876, 0.980) between malignant and benign lesions than either the radiomics score (P = 0.029) or BI-RADS category (P = 0.011). The nomogram demonstrated good calibration and clinical usefulness. In conclusion, the nomogram combining the radiomics score and BI-RADS category is potentially useful for predicting breast malignancy in BI-RADS US category 4 or 5 lesions. |
Databáze: | OpenAIRE |
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