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Stefani Longshamp

Breast Cancer Research

Improving Therapeutic Strategies for High Risk Breast Cancer.  

Neoadjuvant Chemotherapy for High Risk Breast Cancer.

Breast cancer is the second leading cause of cancer-related mortality in women, and accounts for approximately one third of new malignancies (DeSantis et al., 2014).  Nearly 20% of cases present as locally advanced breast cancer (LABC), which are characterized as stage IIB or stage III disease; thus, having large/bulky tumours which are often >5 cm in size and involving the lymph nodes or skin (Giordano, 2003, Whitman and Strom, 2009).  Survival outcomes for LABC are poor; only 50% of patients survive beyond 5 years (Lee and Newman, 2007).    Current treatment guidelines recommend neoadjuvant chemotherapy (NAC; i.e. pre-operative chemotherapy) for clinical management to downstage tumours prior to locoregional treatment with surgery and radiotherapy (Lee and Newman, 2007, Cance et al., 2002).  However, variable tumour responses have been shown in patients receiving NAC and there is evidence to suggest that favourable response to NAC correlates to improved disease free survival (DFS) (von Minckwitz et al., 2012, Mathew et al., 2009). 
Our research team is looking for robust ways, using imaging biomarkers, to predict a patient's response to NAC.  In doing so, chemotherapy treatments can be adapted for patients so that they can have the best possible outcomes.

Quantitative Digital Pathology Imaging (QDPI) Biomarkers to Predict Chemotherapy Response .

Our laboratory focusses on developing artificial intelligence (AI)-driven techniques for rapid analysis of quantitative digital pathology images. These include automatic tumor cell detection, characterizing the tumor microenvironment, and detecting subtle differences in digital images of the tumor to provide richer clinical information for better treatment-decision making in the breast oncology clinic. 

AI-Enhanced Pathology.


State-of-the-art computer vision techniques are being developed to increase efficiency in diagnosing breast cancer and detecting aggressive breast cancer that may demonstrate biological signs of chemotherapy resistance.   

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