Dynamic Modulated Arc Therapy (DMAT): An Intent-Driven, Time-Aware Framework for Next-Generation Radiotherapy Delivery
Taoran Li, Esa Kuusela, Emmi Ruokokoski, Heini Hyv\"onen, Jerry Jaboin, Mirko Myllykoski, Jussi Nurminen, Riku Paananen, Jarkko Peltola, Marko Rusanen, Martin Sabel, Kevin Moore, Christopher Boylan (Varian Medical Systems Inc. - a Siemens Healthineers company, Palo Alto, USA)

TL;DR
DMAT is a novel, intent-driven framework for radiotherapy that co-optimizes dosimetric quality, delivery time, and modulation complexity by integrating machine dynamics and adaptive control.
Contribution
Introduces DMAT, a framework that jointly optimizes treatment quality, time, and complexity considering machine dynamics and clinical cost functions.
Findings
Higher modulation increases MU/Gy and delivery time.
Adaptive CP allocation improves dose quality in high-reward sectors.
Prioritizing efficiency reduces modulation and delivery time with minor quality loss.
Abstract
Traditional VMAT optimization often ignores dynamic machine limits, treating delivery time as an emergent property rather than a steerable parameter. This work introduces Dynamic Modulated Arc Therapy (DMAT), an intent-driven framework that jointly co-optimizes dosimetric quality, delivery time, and modulation complexity. DMAT couples machine emulation accounting for axis synchronization and finite acceleration with dynamic modulation control and clinical cost functions. A user-selected level (-3 to +3) governs leaf-travel, MU behavior, and CP density. Plans are created by initializing CP geometry, leaf positions, and MU, then iteratively alternating dosimetric updates with sequencing updates (penalties for motion, velocity changes, MU uniformity, and complexity), followed by post-processing. CP density is adapted by first optimizing with a uniform distribution and then redistributing…
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