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Improving ultrasound diagnostic Precision for breast cancer and adenosis with modality-specific enhancement (MSE) - Breast Net.
Lin, Zimei; Chen, Libin; Wang, Yunzhong; Zhang, Tao; Huang, Pintong.
Afiliação
  • Lin Z; Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China.
  • Chen L; Department of Ultrasound in Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, 315201, China.
  • Wang Y; Department of Ultrasound in Medicine, The First Affiliated Hospital of Ningbo University, Ningbo, 315201, China.
  • Zhang T; Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China. Electronic address: zhangtao-us@zju.edu.cn.
  • Huang P; Department of Ultrasound in Medicine, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, China; Research Center of Ultrasound in Medicine and Biomedical Engineering, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, 310009, C
Cancer Lett ; 596: 216977, 2024 Aug 01.
Article em En | MEDLINE | ID: mdl-38795759
ABSTRACT
Adenosis is a benign breast condition whose lesions can mimic breast carcinoma and is evaluated for malignancy with the Breast Imaging-Reporting and Data System (BI-RADS). We construct and validate the performance of modality-specific enhancement (MSE)-Breast Net based on multimodal ultrasound images and compare it to the BI-RADS in differentiating adenosis from breast cancer. A total of 179 patients with breast carcinoma and 229 patients with adenosis were included in this retrospective, two-institution study, then divided into a training cohort (institution I, n = 292) and a validation cohort (institution II, n = 116). In the training cohort, the final model had a significantly greater AUC (0.82; P < 0.05) than B-mode-based model (0.69, 95% CI [0.49-0.90]). In the validation cohort, the AUC of the final model was 0.81, greater than that of the BI-RADS (0.75, P < 0.05). The multimodal model outperformed the individual and bimodal models, reaching a significantly greater AUC of 0.87 (95% CI = 0.69-1.0) (P < 0.05). MSE-Breast Net, based on multimodal ultrasound images, exhibited better diagnostic performance than the BI-RADS in differentiating adenosis from breast cancer and may contribute to clinical diagnosis and treatment.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Ultrassonografia Mamária Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Cancer Lett Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Ultrassonografia Mamária Limite: Adult / Aged / Female / Humans / Middle aged Idioma: En Revista: Cancer Lett Ano de publicação: 2024 Tipo de documento: Article País de afiliação: China