Application of deep learning to identify ductal carcinoma in situ and microinvasion of the breast using ultrasound imaging.

ABSTRACT:

Background

The treatment and prognosis of breast ductal carcinoma in situ (DCIS) with and without microinvasion (MIC) are different. Ultrasound imaging shows that DCIS is a heterogeneous breast tumor with diverse manifestations. DCIS means that the cancer cells are confined in the duct without penetrating the basement membrane, MIC means that the cancer cells penetrate the basement membrane and the maximum diameter of any largest invasive lesion is less than or equal to 1 mm. This study was designed to evaluate how deep learning can be used to identify DCIS with MIC on ultrasound images.

Methods

The clinical and ultrasound data of 467 consecutive inpatients diagnosed with DCIS (213 with MIC) in West China Hospital of Sichuan University were collected from January 2013 to Apr

SUBMITTER: Zhu M 

PROVIDER: S-EPMC9403599 | biostudies-literature | 2022 Sep

REPOSITORIES: biostudies-literature