Precision and adaptive radiotherapy in thoracic malignancies: integration of quantitative imaging, radiomics and artificial intelligence for treatment personalization

id="offer-description" class="ecl-u-type-heading-2 ecl-u-mt-none ecl-u-mb-l">Offer Description Radiotherapy for thoracic malignancies is evolving toward increasingly personalized models based on the integration of clinical, biological, molecular, dosimetric, and quantitative imaging information. Artificial intelligence represents a further element of innovation, enabling the identification of predictive biomarkers, supporting patient selection, and facilitating dynamic and adaptive treatment strategies. The research program will focus on the development, validation, and clinical translation of precision and adaptive radiotherapy approaches in lung cancer, with particular emphasis on locally advanced NSCLC and oligometastatic and oligoprogressive settings, while maintaining applicability to the major thoracic malignancies. Research activities will include:. • identification and validation of quantitative biomarkers derived from CT, PET/CT and, where available, functional imaging, using radiomics and longitudinal analyses;. • integration of imaging data with clinical, pathological, molecular, and dosimetric information to develop predictive models of response, disease control, toxicity, and survival;. • development and validation of machine learning, deep learning, and explainable artificial intelligence (XAI) models, with particular attention to robustness, reproducibility, and clinical interpretability;. • development and evaluation of adaptive radiotherapy strategies guided