BREAST CANCER MANAGEMENT

ISSN:

1758-1923

国家:

Australia

影响因子:

SCIE收录情况:

JCR分区:

Ahmad, Rani; Ahmad, Rani; Ahmed, Basem; Ahmed, Bassam
2022-06-01

摘要

Artificial intelligence techniques for the diagnosis of disease continue to develop with rapid pace. This review article systematically determines incremental accuracy and other parameters of current methods, including sensitivity, specificity, positive predictive value and negative predictive value with regard to breast MRI as a screening tool for women under 50 years. Articles were included from the databases of health technology assessment agencies from 2000 to 2019, using various medical subject heading terms. A total of 23 eligible studies were included incorporating a total of 11,688 patients out of which two were multicentered, four were accuracy studies, seven were prospective studies and four were retrospective studies. MRI screening showed an adequate detection of invasive cancers, premalignant lesions and pre-invasive cancers, suggesting that MRI is a powerful surveillance tool to detect cancer in high-risk populations. These findings have indicated that MRI has particular sensitivity and specificity for the diagnosis of breast cancer.

artificial intelligence; breast cancer; MRI; screening

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