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IMAGE: Dartmouth researchers led by Saeed Hassanpour, PhD, found a machine learning method to predict the likelihood that a high-risk ADH breast lesion is cancerous. The approach can identify 98% of… view more 

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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. About 20-30% of ADH cases are upgraded to cancer after surgical excision. However, this means that 70-80% of women undergo a costly and invasive surgical procedure for a benign (but high-risk) lesion.

A Dartmouth research team led by Saeed Hassanpour, PhD, found a machine learning method to predict ADH upgrade to cancer. Having this information can potentially help clinicians and low-risk patients decide whether active surveillance and hormonal therapy is a reasonable alternative to surgical excision. Evaluation

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