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Quantitative Indicators of Retraction Phenomenon on an Automated Breast Volume Scanner: Initial Study in the Diagnosis and Prognostic Prediction of Breast Tumors.
Yan, Lixia; Wen, Chuan; Lu, Qing; Jing, Luxia; Mao, Wujian; Shen, Xinmeng; Zheng, Fengyang; Wang, Wenping; Ma, Yu; Huang, Beijian.
Afiliação
  • Yan L; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
  • Wen C; School of Information Science and Technology, Fudan University, Shanghai, China.
  • Lu Q; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
  • Jing L; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
  • Mao W; Department of Nuclear Medicine, Zhongshan Hospital, Fudan University, Shanghai, China.
  • Shen X; School of Information Science and Technology, Fudan University, Shanghai, China.
  • Zheng F; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
  • Wang W; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China.
  • Ma Y; School of Information Science and Technology, Fudan University, Shanghai, China.
  • Huang B; Department of Ultrasound, Zhongshan Hospital, Fudan University, Shanghai, China; Shanghai Institute of Medical Imaging, Shanghai, China. Electronic address: huang.beijian@zs-hospital.sh.cn.
Ultrasound Med Biol ; 48(8): 1496-1508, 2022 08.
Article em En | MEDLINE | ID: mdl-35618533
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Interpretação de Imagem Assistida por Computador Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Ultrasound Med Biol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Interpretação de Imagem Assistida por Computador Tipo de estudo: Diagnostic_studies / Prognostic_studies / Risk_factors_studies Limite: Female / Humans Idioma: En Revista: Ultrasound Med Biol Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China País de publicação: Reino Unido