|
1
|
Yan L, Wen C, Lu Q, Jing L, Mao W, Shen X, Zheng F, Wang W, Ma Y, Huang B. Quantitative Indicators of Retraction Phenomenon on an Automated Breast Volume Scanner: Initial Study in the Diagnosis and Prognostic Prediction of Breast Tumors. Ultrasound Med Biol 2022; 48:1496-1508. [PMID: 35618533 DOI: 10.1016/j.ultrasmedbio.2022.03.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/15/2022] [Accepted: 03/19/2022] [Indexed: 06/15/2023]
Abstract
Retraction phenomenon is a unique sign on an automated breast volume scanner coronal plane image and has high specificity in differentiating benign lesions from malignant breast cancer. The purpose of this study was to quantify the retraction phenomenon by setting different rules to describe connected regions from different dimensions. In total, six quantitative indicators (FΩ1,FΓ,FS,FΩ2,FΩ3and FL) were obtained. FΩ1, FΩ2 and FΩ3 represent the relative areas of the connected region under different rules. FΓandFS represent the number ratio and absolute area of the connected region, respectively. FL represents the ratio of edge numbers. Two hundred fourteen patients with 214 lesions (90 benign and 124 malignant) were enrolled in this study. All quantitative indicators in the malignant group were significantly higher than those in the benign group (all p values <0.001). The indicator FΓ achieved the highest area under the receiver operating characteristic curve (AUC) (0.701, 95% confidence interval: 0.631-0.771). Both FΓ and FS had significant associations with axillary lymph node metastasis (p = 0.023 and 0.049). Compared with the classic texture feature gray-level co-occurrence matrix, retraction phenomenon quantization improved the AUC by 8.3%. The results indicate that retraction phenomenon quantitative indicators have certain value in distinguishing benign and malignant breast lesions and seem to be associated with axillary lymph node metastasis.
Collapse
Affiliation(s)
- Lixia Yan
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Chuan Wen
- School of Information Science and Technology, Fudan University, Shanghai, China
| | - Qing Lu
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Luxia Jing
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Wujian Mao
- Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China
| | - Xinmeng Shen
- School of Information Science and Technology, Fudan University, Shanghai, China
| | - Fengyang Zheng
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Wenping Wang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China
| | - Yu Ma
- School of Information Science and Technology, Fudan University, Shanghai, China
| | - Beijian Huang
- Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
| |
Collapse
|