Detail

Keywords

Early Detection of Cancer; Idiopathic Interstitial Pneumonias; Lung; Lung Diseases, Interstitial

Research interests

My research focuses on thoracic imaging, with particular emphasis on lung cancer screening, pulmonary nodule assessment, lung cancer staging, and interstitial lung diseases. I am interested in developing and evaluating imaging strategies that enable earlier diagnosis, more accurate disease characterization, and improved monitoring of treatment response. A further focus is the translation of artificial intelligence and machine-learning methods into clinical radiology, including their use for quantitative imaging, risk assessment, and personalized clinical decision-making. My work combines imaging research with multidisciplinary and multicentre collaboration to support the implementation of evidence-based, patient-centred diagnostic pathways in routine clinical care.

Techniques, methods & infrastructure

My work is based on advanced thoracic imaging techniques, including low-dose CT for lung cancer screening, high-resolution CT for the assessment of interstitial lung diseases, and CT-based evaluation of pulmonary nodules and thoracic malignancies. Methods include structured image analysis, quantitative imaging, radiomics, longitudinal assessment of disease progression and treatment response, and image-guided thoracic biopsy. In collaboration with imaging scientists and clinical partners, I develop and validate artificial intelligence and machine-learning methods for automated image analysis, risk stratification, and clinical decision support. The available infrastructure includes state-of-the-art CT and MRI systems, access to large clinical imaging datasets, multidisciplinary thoracic oncology and interstitial lung disease boards, and national and international multicentre research networks.