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Author profile
Shanshan Tang
Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, UT Southwestern Medical Center
Enhancing Delivery Efficiency on the Elekta Unity MR-Linac: A Dosimetric Study on Planning Parameters
One major bottleneck in MRI-guided online adaptive radiotherapy is the prolonged treatment process, particularly extended delivery times, partly due to the relatively low dose rate and high prescription doses. Efficient radiation delivery is essential for mai...
Poster Program · Therapy Physics
Performance of Unity 1.5 T MR-Linac Gating System across Anatomical Sites and Motion Management Strategies
to evaluate performance of Elekta Unity 1.5T MR-Linac Comprehensive Motion Management (CMM) system across multiple gating strategies and anatomical sites: gastrointestinal(GI), genitourinary(GU), and thoracic(lung). This work aims to provide a practical refer...
Poster Program · Therapy Physics
The Feasibility of Direct-to-Treatment Ultra-Hypofractionated Whole-Breast Irradiation Using AI-Enabled Adaptive Radiation Therapy
Direct-to-treatment radiotherapy eliminates CT simulation and pre-planning, reduces consultation-to-treatment intervals from weeks to hours. This study evaluated the feasibility of an ultra-hypofractionated whole-breast workflow that omits simulation and adva...
Poster Program · Therapy Physics
Clinical Implementation of Direct-to-Unit Ultra-Hypofractionated Whole-Breast Irradiation Using AI-Enabled Adaptive Radiation Therapy
Direct-to-unit (DTU) radiotherapy, which bypasses CT simulation and prospective planning, offers an opportunity to markedly shorten the interval from consultation to treatment and expand access to timely breast cancer care. Building on prior feasibility work,...
Proffered Program · Therapy Physics