Breast cancer is the most common cancer among women worldwide, and early detection is critical for improving patient outcomes. However, current screening methods (e.g. mammography or ultrasound) have limitations in terms of accessibility, cost, accuracy, and reliability. The societal consequences of breast cancer are significant, affecting not only patients but also their families, caregivers, and the healthcare system as a whole. Oxygen saturation sensing is a non-invasive tool that measures the percentage of haemoglobin in the blood that is bound to oxygen. Tumours have a higher oxygen consumption rate compared to surrounding normal tissue, therefore, low oxygen saturation levels have been associated with the progression of the tumour cells. Measuring oxygen saturation levels in cancerous tissue can provide valuable information about the tumour microenvironment.
Goal
The goal of this assignment is to reach a novel device that combines multiple technologies inspired by the metabolic and mechanical properties of the tumour, e.g. oxygen saturation sensing, force sensing, and artificial intelligence (AI).
Research outcome
This assignment aims to develop a new diagnostic device that can detect tumours at an early stage with high sensitivity and reliability, while also providing a non-invasive, user-friendly, and cost-effective solution for breast cancer screening.
Collaboration *
This work is a collaboration work with the biomechanical engineering group with Prof. Gabrielle Tuijthof and Dr. Izad Tamadon.