Petra Gröger

Petra Gröger MSc serves as a Research Associate at the University of Applied Sciences Wiener Neustadt (FHWN), working within the Faculty of Health under the Competence Center for Preclinical Imaging and Medical Technology. She is actively associated with the Master's Program in MedTech – Functional Imaging, Conventional and Ion Radiotherapy, contributing to both research and academic components of the program.

Her research specializes in the integration and validation of preclinical molecular imaging modalities for radiotherapy applications. Dr. Gröger's work bridges multiple disciplines including radiation biology, medical radiation physics, and biomedicine, with particular emphasis on advancing personalized precision radiotherapy techniques. Her research portfolio demonstrates a consistent focus on improving imaging methodologies to enhance the precision and effectiveness of radiation-based cancer treatments.

Analysis of Dr. Gröger's publications reveals a strong emphasis on technical validation of imaging workflows, with particular attention to quantitative accuracy in preclinical settings. Her work spans both PET and SPECT-CT imaging modalities, addressing critical challenges in absolute quantification and workflow optimization for radiotherapy applications.

• Development, evaluation and validation of a novel kinetic model approach using an image-derived arterial input function for absolute micro-PET quantification (2024)
• Design, evaluation and verification of a small animal SPECT-CT workflow for biologic adaptive radiotherapy (2021)

Dr. Gröger is actively engaged in two major research initiatives: the 'Applied Molecular Imaging in Personalized Precision Radiotherapy' project (2021-2026) and the PAIR project (2022-2026). These projects collectively aim to expand the radiobiological understanding of ion beams across multiple biological scales to optimize cancer treatment protocols.

Her contributions to the field focus on advancing radiotherapy techniques through improved imaging methodologies, with potential applications in enhancing cancer treatment outcomes through more precise radiation delivery and personalized treatment planning.