Research
Current Projects
BREST Registry: Breast Research in Surgical Treatment Registry
Breast cancer is the most common malignancy among women in BC, and surgery is a key part of treatment. To help facilitate research that aims to improve breast cancer care, we are developing the Breast Research in Surgical Treatment (BREST) Registry. This is a comprehensive database capturing high quality and accessible data related to patients with breast cancer. Anonymized data for approximately 3000 patients will be available in the registry. This is the first surgically focused regional registry in the province. It will drive research on safety, efficiency, equity, and patient-centered care, ultimately improving surgical outcomes across the Interior Health region. This database fills a unique gap by providing data that can be queried to answer critical research questions and that serve the breast cancer patient population. Collaborators: Dr. Scott Williamson (Plastic and microvascular surgeon)
​Lymphedema
Prevention
Lymphedema (swelling of the arm) is a disfiguring and potentially life-altering condition, affecting up to 30% of patients after lymph node removal. Dr. Chris Baliski, in collaboration with Dr. Scott Williamson, have introduced a promising surgical technique that reconnects lymphatics to nearby blood vessels to help restore normal lymphatic flow and reduce the risk of lymphedema. Early results are encouraging, and expanding this work could significantly improve quality of life for cancer patients in our community, without waiting years for broader adoption. Thanks to the generous support of the BC Cancer Foundation and its donors, the program acquired a perometer (link to news), which is a highly sensitive optical scanner that measures arm fluid volume in at-risk patients. Additionally, a knowledge exchange with the University of Calgary brought advanced techniques to Kelowna, including training for local surgeons and a presentation at the BC Cancer provincial Grand Rounds by Dr. Temple-Oberle.
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Surveillance of Lymphedema & Dysfunction of Shoulder (SLEDS)
In collaboration with BC Cancer Physiatrist, Dr. Lauren Capozzi, our team is conducting a study to better understand how lymph node surgery for breast cancer treatment affects lymphedema (arm swelling) and shoulder function over time. Participants are followed before and after surgery for up to three years. Throughout the study, researchers track symptoms, arm measurements, shoulder mobility, and quality‑of‑life outcomes to better understand recovery over time. The goal is to identify which patients are at greatest risk of developing lymphedema and movement difficulties, and to learn how rehabilitation can be tailored to support recovery. Findings from this research may help improve long-term outcomes and quality of life for people undergoing breast cancer treatment. Collaborators: Dr. Lauren Capozzi, Andrea Knox (clinical nurse specialist)
Patient Reported
Outcomes Studies
We have completed important studies focused on patient-reported outcomes following breast cancer surgery. Many patients with early breast cancer have multiple options, including breast conserving surgery, along with mastectomy with or without reconstruction. Decisions can be complex and involve discussions regarding recurrence, but also treatment pathways, and quality of life considerations. The goal was to better understand how different surgical approaches impact patient satisfaction and well-being, helping future patients make more informed decisions. (Jay article) Newer approaches to breast conserving surgery include the use of oncoplastic surgery, which can expand patient eligibility for breast conservation surgery. Oncoplastic breast surgery utilizes novel techniques of tissue transfer to enable the removal of larger tumours, while allowing preservation of the appearance of the breast. Traditional breast-conserving surgery has been compared with oncoplastic breast surgery, as well as evaluation of different oncoplastic approaches. (Solano ref). Our latest work found patients reported slightly higher satisfaction with breast appearance, but they experienced lower chest wall well-being—likely due to the more extensive nature of the procedure. These findings are helping shape more personalized surgical care and improve quality of life for breast cancer patients in our community.
Evaluating the Impact of Mental Health & Social Determinants of Health on Patient-Reported Outcomes Following Breast Cancer Surgery
Social determinants of health as defined by the WHO are personal and situational factors that can impact health care equity. We are investigating the impact of these factors on access to breast cancer surgical care, as well as evaluating their impact on patient reported outcomes. UBC medical students involved in the FLEX program (flexible and enhanced learning program- a series of courses for medical students that are designed to foster innovation, creativity, critical thought, and community engagement) contribute to this study. This opportunity to gain hands on experience in research, data analysis, and manuscript preparation, is building future leaders in surgical oncology research.  Collaborators: Dr. Juan-Jose Nunez, Dr. Helen McTaggart-Cowen Students: Luigi Russo and Parneet Deo ​
Clinical Patient Reported Outcomes Following Breast Cancer and Melanoma Surgery
A quality improvement initiative to implement validated patient-reported outcome tools into clinical care is being implemented. This includes both the BREAST-Q for breast cancer surgery, and the LYMPH-Q for breast cancer and melanoma surgery. This initiative aims to enhance patient engagement, provide meaningful insights into satisfaction and quality of life, inform clinical decision-making, and ultimately improve patient-centered outcomes.
De-escalating the Treatment of Patients with Melanoma
PRISM has successfully completed enrollment in the international ME-15 clinical trial, which is a phase III randomized controlled trial investigating 1cm vs 2cm wide excision margins in patients with melanoma skin cancer. The study is investigating the use of smaller surgical margins to reduce the extent of surgery in melanoma patients and improve quality of life. The results could help change how melanoma surgery is performed, an approach that has remained largely unchanged for several decades. If the study shows that smaller amounts of healthy tissue can be safely removed, patients may experience less scarring, fewer surgical complications, as well as improved quality of life, while maintaining effective cancer treatment.
Assessment of Personalized Risk in Patients with Melanoma
A risk assessment tool has been developed to help better inform patients on their risk of recurrence from melanoma skin cancer. (Impact of extra-nodal extension and AJCC lymph node staging in predicting recurrence following lymphadenectomy in patients with melanoma - PubMed) We have validated this tool in our region to ensure that it provides accurate information. This information can be used by physicians to help advise patients on the seriousness of their cancer diagnosis, and decide on further treatments, including immunotherapy.
Use of Artificial Intelligence to Enhance Mammographic Tumour Size Evaluation in Breast Cancer
A multidisciplinary team of researchers are completing a study that will develop and evaluate an AI based algorithm for estimating breast cancer tumour size and extent on preoperative mammography, and to compare its accuracy with standard radiologist interpretation. By improving the accuracy, the way tumors are assessed before surgery, this research aims to help surgeons remove the cancer more completely the first time and reduce the need for additional surgeries. Accurate preoperative assessment of tumour extent is critical to surgical success. Mammography remains the most widely used imaging modality, yet its accuracy in estimating true tumour size is modest and frequently affected by breast density and tumour biology. Underestimation can lead to positive margins, while overestimation may result in unnecessary tissue removal or mastectomy. Although AI has demonstrated strong performance in screening mammography, its role in preoperative tumour size estimation has been minimally studied. Given rapid advances in deep learning methodologies, further evaluation is warranted. Understanding whether AI can improve mammographic tumour accuracy, and identifying factors that affect its performance has the potential to meaningfully reduce re‑excision rates, optimize surgical planning, and improve patient outcomes. Collaborators: Dr. Rasika Rajapakshe, Dr. Angel Arnout, Dr. Michael Partrick, Dr. Patricia Lasserre Students: Alex Niaz, Ruben Ispiryan