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MEAI: an artificial intelligence platform for predicting distant and lymph node metastases directly from primary breast cancer.
Fan, Jiansong; Zhang, Lei; Lv, Tianxu; Liu, Yuan; Sun, Heng; Miao, Kai; Jiang, Chunjuan; Li, Lihua; Pan, Xiang.
Afiliación
  • Fan J; School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu, China.
  • Zhang L; Department of Vascular Surgery, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
  • Lv T; Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China.
  • Liu Y; School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu, China.
  • Sun H; School of Artificial Intelligence and Computer Science, Jiangnan University, Wuxi, Jiangsu, China.
  • Miao K; Cancer Center, Faculty of Health Sciences, University of Macau, Macau SAR, China.
  • Jiang C; MOE Frontier Science Centre for Precision Oncology, University of Macau, Macau SAR, China.
  • Li L; Department of Nuclear Medicine, PET Image Center, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China.
  • Pan X; Institute of Biomedical Engineering and Instrumentation, Hangzhou Dianzi University, Hangzhou, Zhejiang, China.
J Cancer Res Clin Oncol ; 149(11): 9229-9241, 2023 Sep.
Article en En | MEDLINE | ID: mdl-37199837
ABSTRACT

PURPOSE:

Breast cancer patients typically have decent prognoses, with a 5-year survival rate of more than 90%, but when the disease metastases to lymph node or distant, the prognosis drastically declines. Therefore, it is essential for future treatment and patient survival to quickly and accurately identify tumor metastasis in patients. An artificial intelligence system was developed to recognize lymph node and distant tumor metastases on whole-slide images (WSIs) of primary breast cancer.

METHODS:

In this study, a total of 832 WSIs from 520 patients without tumor metastases and 312 patients with breast cancer metastases (including lymph node, bone, lung, liver, and other) were gathered. Based on the WSIs were randomly divided into the training and testing cohorts, a brand-new artificial intelligence system called MEAI was built to identify lymph node and distant metastases in primary breast cancer.

RESULTS:

The final AI system attained an area under the receiver operating characteristic curve of 0.934 in a test set of 187 patients. In addition, the potential for AI system to increase the precision, consistency, and effectiveness of tumor metastasis detection in patients with breast cancer was highlighted by the AI's achievement of an AUROC higher than the average of six board-certified pathologists (AUROC 0.811) in a retrospective pathologist evaluation.

CONCLUSION:

The proposed MEAI system can provide a non-invasive approach to assess the metastatic probability of patients with primary breast cancer.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: J Cancer Res Clin Oncol Año: 2023 Tipo del documento: Article País de afiliación: China

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Neoplasias de la Mama Tipo de estudio: Observational_studies / Prognostic_studies / Risk_factors_studies Límite: Female / Humans Idioma: En Revista: J Cancer Res Clin Oncol Año: 2023 Tipo del documento: Article País de afiliación: China