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About

Theresa Hofmann is a leading researcher in the field of robotic radiosurgery, with a primary focus on CyberKnife treatment planning and optimization. Her work addresses critical challenges in stereotactic body radiation therapy (SBRT), particularly in developing AI-driven solutions for beam generation and adaptive replanning. Hofmann's key contributions include pioneering the use of CNN-based candidate beam generation to streamline the computationally intensive treatment planning process, and advancing constrained reoptimization techniques for managing non-periodic intra-fractional motion during robotic SBRT. Her clinical research spans diverse applications, from small choroidal melanomas and arteriovenous malformations to prostate cancer, with her most cited work on self-shielding gyroscopic radiosurgery (16 citations) demonstrating significant clinical impact. Notably, her 2020 feasibility study on CNN-based beam generation (8 citations) represents a foundational contribution to AI-optimized radiosurgery, while her investigations into MRI-based treatment planning for cerebral AVMs and ultrasound-guided prostate therapy showcase her commitment to integrating advanced imaging modalities. Through her research, Hofmann continues to push the boundaries of precision and efficiency in robotic radiosurgery, making treatment more adaptable and accessible.