A research group from the Rovira i Virgili University, led by the Professor Domènec Puig, classifies the types of breast cancer and predict the probability of metastasis.
Domènec Puig, on the left, and Hatem Rashwan, two of those responsible for the BosomShield project on behalf of the URV
The Universitat Rovira i Virgili is taking the lead in an ambitious international project known as BosomShield, with the potential to play a pivotal role in the detection and prevention of breast cancer. At its core, BosomShield is focused on the development of a sophisticated software platform designed to analyze both radiological and histopathological images. This groundbreaking approach brings together the analysis of traditional imaging methods like mammograms and MRIs with the examination of microscopic cell-level images. By amalgamating these two types of images, the project seeks to enhance the precision of breast cancer classification, predict the severity of the condition, and estimate the probability of metastasis recurrence. This collaborative endeavor is spearheaded by the URV’s Laboratory of Intelligent Robotics and Vision, led by researcher Domènec Puig, and is a part of the ITAKA research group within the Department of Computer Engineering and Mathematics. Notably, BosomShield enjoys the support of universities, hospitals, biomedical research groups, and technology centers in Europe, Asia, and North America, with funding secured from the European Union’s Marie-Sklodowska Curie Actions program, set to run until 2026.
BosomShield comprises ten distinct subprojects, each undertaken by one of the collaborating institutions, addressing various stages of the process. These encompass the analysis of radiological and histopathological images, prediction of recurrence possibilities, and platform design. Doctoral candidates selected by the participating institutions lead each subproject, fostering an enriching international exchange of expertise among researchers. The URV team, for instance, is overseeing the first subproject, aiming to determine the molecular subtype of breast cancer through multimodal radiological images. This endeavor leverages deep learning and artificial intelligence to identify tumor markers in radiological images, providing crucial insights into the potential danger and likelihood of recurrence, particularly in collaboration with Swedish partners. Ultimately, the BosomShield project aspires to create a practical clinical platform accessible within hospitals, offering specialists alerts and valuable assistance in making well-informed and efficient decisions regarding breast cancer diagnosis and treatment. It represents the culmination of collaborative efforts between the URV and IISPV, signaling a significant stride towards a universal and effective breast cancer diagnosis system.