core needle biopsy
Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ
To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the diagnosis of ductal carcinoma in situ (DCIS) by core needle biopsy. The data was collected from 2000 to 2014. In this institutional review board-approved study, we analyzed dynamic contrast-enhanced fat-saturated T1-weighted MRI sequences from 131 patients with a core needle biopsy-confirmed diagnosis of DCIS. We explored two different deep learning approaches to predict whether there was an occult invasive component in the analyzed tumors that was ultimately identified at surgical excision. In the first approach, we adopted the transfer learning strategy.
Researchers harness machine learning to predict breast cancer
A Dartmouth research team is harnessing machine learning technology to predict malignant breast cancer lesions. Saeed Hassanpour, assistant professor of biomedical data science and epidemology at the Geisel School of Medicine, and his team are focused on developing this technology to predict the possibility that a breast lesion found during medical examinations is or will become cancerous. Hassanpour said that breast cancer screenings are widely used, but can induce a false positive, which put women in danger of overdiagnosis and overtreatment. He explained that typically, if a lesion is found after a mammography, doctors perform a core needle biopsy on the patient. If a marker for high risk breast cancer incidences, known as atypical ductal hyperplasia, is found, surgery is performed to determine whether the lesion is malignant or benign, according to Hassanpour.
New machine learning method could spare some women from unnecessary breast surgery
LEBANON, NH - Atypical ductal hyperplasia (ADH) is a breast lesion associated with a four- to five-fold increase in the risk of breast cancer. ADH is primarily found using mammography and identified on core needle biopsy. Despite multiple passes of the lesion during biopsy, only portions of the lesions are sampled. Other variable factors influence sampling and accuracy such that the presence of cancer may be underestimated by 10-45%. Currently, surgical removal is recommended for all ADH cases found on core needle biopsies to determine if the lesion is cancerous.