Todd R. McNutt, PhD

Modern radiation therapy increasingly requires deforming prior dose to new CT scans for re-irradiation. Current validation methods report whole-organ agreement but lack spatial specificity and corrective guidance. This study developed a subregion evaluation t...

To evaluate a protocol-agnostic machine learning (PlanAI) (Sun Nuclear, Mirion Medical Company, Florida, USA)1 model for automated treatment planning in external-beam radiotherapy for thoracic cancer.

Radiotherapy (RT) for head and neck (HN) cancer frequently induces xerostomia due to radiation‑mediated parotid gland damage. Mechanistic modeling of parotid response may improve understanding of toxicity development and enable more biologically informed pred...

The absence of defined dose tolerances and the uncertainty in radiation sensitivity among airway subsegments highlight the need to evaluate imaging-based airway changes in patients receiving radiotherapy for central and ultracentral thoracic tumours. This stu...

Accurate estimation of lifetime dose accumulation in patients undergoing re-irradiation therapy is essential for assessing long-term toxicity risks and evaluating the effectiveness of multiple radiotherapy (RT) courses. Currently, no standardized practice exi...

Radiation induced xerostomia is a common adverse sequela among head and neck cancer (HNC) patients with ~45,000 new cases treated with radiation in the US annually. Current guidelines focus on sparing the mean dose to the parotid glands to reduce xerostomia....

To develop and validate an auto-planning approach for robust intensity modulated proton therapy (IMPT) using a frontier large language model (LLM), ChatGPT-4o, in a clinical treatment planning system (TPS) for prostate cancer, automatically managing heterogen...