Microwave Imaging and GenAI for personalised cancer screening

Recently, intensified efforts in Microwave Imaging (MWI) with a focus on cancers developing in superficial soft tissue organs, such as the breast and thyroid, have been carried out. Higher sensitivity, of such imaging, has the potential to enable the detection of cancer cells at earlier stages even in dense tissues and with better specificity, avoiding unnecessary patient call-backs, supplementary imaging, biopsies (associated with stress, financial burden for the health system, delays in patient management and extended diagnosis-to-treatment timelines). This screening modality is safe, as it does not use ionising radiation, and the procedure is painless.

Over the past decades, extensive screening imaging data has been collected from various methods, each providing unique images of tumours. Integrating all this historical data and new images into one single Generative AI (GenAI) diagnostic tool, could greatly enhance personalised cancer diagnosis and treatment. Advances in Artificial Intelligence have enabled the development of sophisticated tools capable of functioning autonomously.

This project aims to create a comprehensive GenAI platform that uses, alternatively or in combination, a range of historical imaging data, a new advanced approach to Microwave Imaging (MWI), and other health data, to create a personalised approach to cancer care. This initial approach includes screening and early diagnosis, achieving both improved overall sensitivity and better specificity by supporting the discrimination of malignant from benign lesions. For both objectives, the personalised approach is related to the modelling of patient profile information and its integration into MWI parameterisation and diagnosis/decision-making. The concept will be demonstrated on breast cancer as proof of concept (PoC). The platform will be built and enhanced by Generative AI, capable of generating advanced analytics, predictive modelling and personalised recommendations. In addition to historical screening data, the model will incorporate Microwave Images obtained under novel, beyond the state-of-the-art approaches, as well as diagnostic features, providing enhanced specificity and sensitivity. In the future, the tool may be augmented to include apart from imaging data, pathology/histological analysis data, personal health data and treatment information, towards enhanced diagnostic capability, while also supporting individualised prognosis of disease and treatment recommendations.

The project represents a transformative leap in early cancer detection, combining cutting-edge MWI with advanced AI-driven analytics to deliver a fully autonomous, radiation-free diagnostic platform. Designed for future deployment in everyday settings such as shopping centres, it is meant to bring peace of mind to the public by enabling safe, painless, and accessible screening that can either reassure healthy individuals or prompt timely medical follow-up. Anchored in breast imaging but inherently adaptable to other superficial soft-tissue cancers like thyroid, this innovation will merge novel physics and electronics research with generative AI to engineer a high-sensitivity, high-specificity clinical system.

Its impact is not only technological but also economic and societal: by increasing sensitivity in dense breast tissue to over 75%, compared to 62% with traditional mammography, and significantly reducing false positives, the enviosioned diagnostic platform can lower the number of unnecessary biopsies and follow-up imaging. These improvements could have an estimated €175 million annually in a national screening program involving 2 million women. Beyond cost savings, such a system has the potential to significantly enhance patient experience, reduce psychological stress, and accelerate clinical decision-making marking a pivotal shift toward safer, more equitable, and economically sustainable cancer care. This paradigm shift redefines the future of personalised, preventive oncology on a global scale.

MIMA Technologies will contribute its microwave radar imaging and diagnostics expertise to the project, in collaboration with its long-lasting partner, University of Galway, bringing-in its high-standard clinical research and breast cancer management expertise.

Partners to contribute to the AI components of the project are being sought.