Surface Guided Radiation Therapy (SGRT) has become an important component of modern radiotherapy. The LUNA 3D SGRT system enables precise patient positioning for each treatment fraction and supports reliable motion monitoring during treatment. Its comprehensive reporting capabilities allow traceable records of patient positioning and motion throughout the treatment course.

This presentation outlines the testing, implementation, and clinical evaluation of LAP’s LUNA 3D SGRT installed on C-arm linacs. Acceptance testing was performed in accordance with the ESTRO-ACROP guideline, including End-to-end testing encompassing a laser-free workflow. Post-clinical implementation evaluation was performed, including a comparison of patient positioning achieved with LUNA 3D and a conventional laser-based setup. All test results were within manufacturer’s specifications and ESTRO guideline tolerances.

Speakers’ Biography：

Dr. Hui Khee Looe is the Deputy Head of Medical Physics at Pius-Hospital in Oldenburg, Germany, and a scientist in the “Medical Radiation Physics” group at the University of Oldenburg. He leads a research group focusing on mathematical and computational methods in dosimetry, and works actively with the clinical team to improve clinical workflow and patient outcomes using the LUNA 3D SGRT system.

Talk 2: Open-Source Tools for the Clinic – Browser Based Tools

This session presents five browser-based, open-source tools developed within the Clinical Physics Innovations team at Siemens Healthineers. The tools cover dose constraint conversion/template creation, dosimetric scorecard evaluation, plan delivery visualization, SFRT sphere lattice generation and virtual cone planning. Each runs entirely in a modern browser with no installation required and no patient data leaving the local machine.

Speakers’ Biography：

Ryan Clark is a Senior Research Scientist in Medical Affairs at Siemens Healthineers, connecting clinical practice, research and product development to improve workflows for radiation therapy professionals. He also develops open-source radiation therapy software using AI to translate clinical knowledge directly into working software. 

Learning Objectives:

1. Identify browser-based open-source tools designed to address common workflow gaps in radiation therapy planning.
2. Describe how AI-assisted development can enable clinicians to build and share practical tools with the broader radiation therapy community.