Development and validation of a nomogram for discriminating between benign and malignant breast masses by conventional ultrasound and dual-mode elastography: a multicenter study

Yang, Keen1,2; Ye, Xiuqin1,2; Tian, Hongtian1,2; Li, Qiaoying3; Liu, Qinghua4; Li, Jingjing4; Guo, Jinhan5; Xu, Jinfeng1,2,6; Dong, Fajin1,2,6

2023-02-01

10.21037/qims-22-237

QUANTITATIVE IMAGING IN MEDICINE AND SURGERY   影响因子和分区

2223-4292

2223-4306

Background: This study developed and validated an ultrasound nomogram based on conventional ultrasound and dual-mode elastography to differentiate breast masses. Methods: The data of 234 patients were collected before they underwent breast mass puncture or surgery at 4 different centers between 2016 and 2021. Patients were divided into 5 datasets: internal validation and development sets from the same hospital, and external validation sets from the 3 other hospitals. In the development cohort, age and 294 different ultrasound and elastography features were obtained from ultrasound images. Univariate logistic regression and least absolute shrinkage and selection operator (LASSO) regression were used for data reduction and visualization. Multivariable logistic regression analysis was used to develop the prediction model and ultrasound nomogram. Receiver operating characteristic (ROC) curve analysis, calibration curves, integrated discrimination improvement, and the net reclassification index were used to evaluate nomogram performance; decision curve analysis (DCA) and clinical impact curves were used to estimate clinical usefulness. wave elastography value of 1.5 mm surrounding tissues in a breast mass) divided by (the mean shear wave elastography value of the breast mass)-shell mean/A mean1.5(E), (the ratio of strain elastography of adipose tissue near a breast mass) divided by [the ratio of strain elastography of (the breast mass adds the 1.5 mm surrounding tissues in the breast mass)]-B/A'1.5 were selected as predictors in multivariable logistic regression analysis, comprising Model 1. Among the 5 cohorts, Model 1 performed best, with areas under the curve (AUC) of 0.92, 0.84, 0.87, 0.93, and 0.89, respectively. The AUCs were 0.90, 0.82, 0.83, 0.91, and 0.85, respectively, in Model 2 (margin + posterior features + shape + vascularity) and 0.80, 0.76, 0.77, 0.87, Conclusions: Our ultrasound nomograms facilitate exposure to the features and visualization of breast are superior at identifying breast cancer, and are worthy of further clinical investigation.

Breast cancer elastography nomogram prediction model ultrasound

SCI

英语

通讯

Commission of Science and Technology of Shenzhen[GJHZ20200731095401004]

Radiology, Nuclear Medicine & Medical Imaging

Radiology, Nuclear Medicine & Medical Imaging

WOS:000992519700001

AME PUBLISHING COMPANY

Web of Science

1.Jinan Univ, Shenzhen Peoples Hosp, Dept Ultrasound, Clin Med Coll 2, Guangzhou, Peoples R China
2.Southern Univ Sci & Technol, Affiliated Hosp 1, Shenzhen, Peoples R China
3.Fourth Mil Med Univ, Tangdu Hosp, Dept Ultrasound, Xian, Peoples R China
4.Rizhao Peoples Hosp, Dept Ultrasound, Rizhao, Peoples R China
5.Shenzhen Peoples Hosp, Dept Ultrasound, Longhua Branch, Shenzhen, Peoples R China
6.Shenzhen Peoples Hosp, Dept Ultrasound, 1017 Dongmen North Rd, Shenzhen 518020, Peoples R China

Yang, Keen,Ye, Xiuqin,Tian, Hongtian,et al. Development and validation of a nomogram for discriminating between benign and malignant breast masses by conventional ultrasound and dual-mode elastography: a multicenter study[J]. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY,2023,13(2).

Yang, Keen.,Ye, Xiuqin.,Tian, Hongtian.,Li, Qiaoying.,Liu, Qinghua.,...&Dong, Fajin.(2023).Development and validation of a nomogram for discriminating between benign and malignant breast masses by conventional ultrasound and dual-mode elastography: a multicenter study.QUANTITATIVE IMAGING IN MEDICINE AND SURGERY,13(2).

Yang, Keen,et al."Development and validation of a nomogram for discriminating between benign and malignant breast masses by conventional ultrasound and dual-mode elastography: a multicenter study".QUANTITATIVE IMAGING IN MEDICINE AND SURGERY 13.2(2023).