Grant: Collaborative Health Research Projects (NSERC partnered)

In this project will be developing methods to predict chemotherapy and radiotherapy responses inadvance of treatment based on ultrasound and photoacoustic characteristics of tumours and machine learning approaches. We have recently discovered that quantitative ultrasound and optical spectroscopy parameters obtained before any chemotherapy is administered can be used to predict chemotherapy outcomes. First results have demonstrated sensitivities and specificities of over 85-90% each for predicting ultimate clinical response based on quantitative ultrasound data before starting 4-6 months of chemotherapy or many weeks of radiotherapy (1,2). The research will develop methods to predict tumour responses to treatment. We will develop a platform for use in patients; optimal ultrasound and photoacoustic predictive characteristics for tumours will be determined based on patient data and clinical outcomes using traditional classification methods and machine learning approaches. The overarching goal of this research is to transform ultrasound and photoacoustics, which are non-invasive, inexpensive and portable, such that they can be used to predict cancer therapy outcomes through functional imaging. By predicting tumour response in advance and/or early on during a treatment rather than using traditional anatomical assessments that take place weeks to months after the completion of 4-6 months of therapy, ineffective therapies could be avoided in favour of more efficacious treatments. This has the potential of increasing the response rate which is associated with improved long term outcome improving survival in addition to sparing patients unnecessary side effects of treatments that may span weeks to months.