A Novel Nomogram Based on Imaging Biomarkers of Shear Wave Elastography, Angio Planewave Ultrasensitive Imaging, and Conventional Ultrasound for Preoperative Prediction of Malignancy in Patients with Breast Lesions

Author:

Guo Guoqiang1,Feng Jiaping12ORCID,Jin Chunchun1,Gong Xuehao12,Chen Yihao1,Chen Sihan1,Wei Zhanghong3ORCID,Xiong Huahua12,Lu Jianghao1

Affiliation:

1. Department of Ultrasound, Shenzhen Second People’s Hospital, The First Affiliated Hospital of Shenzhen University, Sungang West Road 3002, Futian District, Shenzhen 518025, China

2. Graduate School, Guangzhou Medical University, Guangzhou 510180, China

3. Department of Ultrasound, Heping People’s Hospital, Dongshan Road 10, Yangming Town, Heping County, Heyuan 517299, China

Abstract

Several studies have demonstrated the difficulties in distinguishing malignant lesions of the breast from benign lesions owing to overlapping morphological features on ultrasound. Consequently, we aimed to develop a nomogram based on shear wave elastography (SWE), Angio Planewave Ultrasensitive imaging (Angio PLUS (AP)), and conventional ultrasound imaging biomarkers to predict malignancy in patients with breast lesions. This prospective study included 117 female patients with suspicious lesions of the breast. Features of lesions were extracted from SWE, AP, and conventional ultrasound images. The least absolute shrinkage and selection operator (Lasso) algorithms were used to select breast cancer-related imaging biomarkers, and a nomogram was developed based on six of the 16 imaging biomarkers. This model exhibited good discrimination (area under the receiver operating characteristic curve (AUC): 0.969; 95% confidence interval (CI): 0.928, 0.989) between malignant and benign breast lesions. Moreover, the nomogram also showed demonstrated good calibration and clinical usefulness. In conclusion, our nomogram can be a potentially useful tool for individually-tailored diagnosis of breast tumors in clinical practice.

Funder

Key Disciplines of Shenzhen

Shenzhen Science and Technology Innovation Committee

MOOC Curriculum Development and Simulation Medical Education Reform

Heyuan Science and Technology Plan Project

Publisher

MDPI AG

Subject

Clinical Biochemistry

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