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Grant: Project Grant

Queen's University (Kingston, Ontario)

$692,326.00

Real-time molecular-imaging guidance of breast conserving surgery

FY 2022-23

Summary
Breast cancer affects 1 in 8 women and is the second leading cause of female cancer related deaths. The ideal treatment for its early stage is breast-conserving surgery to completely remove cancer while retaining healthy tissue. Current approaches to surgical resection fall short in both of these objectives. On average, 1 of 3 women undergoing breast conserving surgery require additional surgery due to incomplete tumor resection or "positive margins". Repeat surgery leads to increased risk of complications, impaired cosmetics, delayed therapy, increased distress, and extra costs and risks of anesthesia. It could also lead to mastectomy, a traumatic experience for a patient expecting curative treatment with breast conservation. As early-stage breast cancer is not palpable or visible, surgeons apply generous safety margins around the tumor, removing a great deal of healthy tissue. Patients, therefore, often experience severe breast deformity that requires reconstruction, yet they must often wait for many years for treatment due to lack of reconstructive surgical capacity. To address this need, we propose a turnkey technology, NaviKnife, as the next-generation breast conserving surgery navigation system to achieve complete tumor resection with minimal tissue loss. NaviKnife builds on novel real-time metabolomic tissue typing, machine learning and image-guided tracking to assist the surgeon identify and trace the tumor boundary during resection. Our objective is to establish the efficacy of this technology in breast conserving surgery. In a series of clinical studies, we will develop and deploy the technology across two institutions. NaviKnife is expected to positively and rapidly benefit the lives of all breast cancer patients. Collaboration with leading investigators in Canada, the UK and the US will create an effective environment for international development of next-generation surgical oncology approaches.
Program
Project Grant
Location
Ontario, Canada
Type
Grant
Source
CIHR Funding Decisions Database

As published

Id
478297
Name
Mousavi Parvin
Region
Ontario
Country
Canada
Orgtype
Institution Paid; Research Institution
Instname2
Cancer Research
Theme2
Biomedical
Prcname2
Medical Physics & Imaging
Projecttitle
Real-time molecular-imaging guidance of breast conserving surgery
Programtype2
Operating Grants
Orgnameinp2
Queen's University (Kingston, Ontario)
Cihramount2
$692,326
Cihrequipment2
$0
Programname2
Project Grant
Keyworddelim
Breast Cancer Surgery; Machine Learning; Margin Delineation; Mass Spectrometry; Metabolomic Imaging; Surgical Navigation; Tissue Characterization
Abstract
Breast cancer affects 1 in 8 women and is the second leading cause of female cancer related deaths. The ideal treatment for its early stage is breast-conserving surgery to completely remove cancer while retaining healthy tissue. Current approaches to surgical resection fall short in both of these objectives. On average, 1 of 3 women undergoing breast conserving surgery require additional surgery due to incomplete tumor resection or "positive margins". Repeat surgery leads to increased risk of complications, impaired cosmetics, delayed therapy, increased distress, and extra costs and risks of anesthesia. It could also lead to mastectomy, a traumatic experience for a patient expecting curative treatment with breast conservation. As early-stage breast cancer is not palpable or visible, surgeons apply generous safety margins around the tumor, removing a great deal of healthy tissue. Patients, therefore, often experience severe breast deformity that requires reconstruction, yet they must often wait for many years for treatment due to lack of reconstructive surgical capacity. To address this need, we propose a turnkey technology, NaviKnife, as the next-generation breast conserving surgery navigation system to achieve complete tumor resection with minimal tissue loss. NaviKnife builds on novel real-time metabolomic tissue typing, machine learning and image-guided tracking to assist the surgeon identify and trace the tumor boundary during resection. Our objective is to establish the efficacy of this technology in breast conserving surgery. In a series of clinical studies, we will develop and deploy the technology across two institutions. NaviKnife is expected to positively and rapidly benefit the lives of all breast cancer patients. Collaboration with leading investigators in Canada, the UK and the US will create an effective environment for international development of next-generation surgical oncology approaches.
Competitiondate
202303
Approvedterm2
5 yrs 0 mth
Pinamesdelim
Mousavi, Parvin; Engel, Cecil J; Fichtinger, Gabor
Approvedterm
5 ans 0 mois
Cihrcontribution2
~ $692,326~ $0~
Queen's University (Kingston, Ontario) - $692,326 Gra… | Canada Spends