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Fast leaf-fitting with generalized underdose/overdose constraints for real-time MLC tracking.

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This study introduces an optimization framework for real-time multileaf collimator (MLC) tracking, improving aperture accuracy during radiotherapy. The new algorithm enhances leaf-fitting quality without compromising speed for intrafraction motion management.

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Area of Science:

  • Medical Physics
  • Radiotherapy
  • Image-Guided Therapy

Background:

  • Real-time multileaf collimator (MLC) tracking is crucial for managing intrafractional tumor motion in thoracic and abdominal radiotherapy.
  • Current MLC tracking involves aperture transformation and leaf refitting, facing challenges in accurately reproducing motion-adapted apertures.
  • An optimization-based framework is presented to address the leaf-fitting problem in real-time.

Purpose of the Study:

  • To develop and evaluate an optimization-based framework for real-time multileaf collimator (MLC) leaf-fitting.
  • To improve the accuracy of motion-adapted apertures during radiotherapy treatments.
  • To enable complex leaf-fitting strategies that balance planning target volume (PTV) coverage and organs at risk (OARs) avoidance.

Main Methods:

  • An optimization framework was designed to determine leaf positions in real-time, considering PTV coverage and OARs avoidance.
  • A novel algorithm was developed to handle general linear transformations of the planned MLC aperture, including 3D translations and in-plane rotations.
  • The algorithm was tested on lung intensity-modulated radiotherapy plans using six-degree-of-freedom motion data, comparing its quality-of-fit and computation time against existing methods.

Main Results:

  • The proposed algorithm achieved leaf-fittings in an average of 0.226 ms, significantly faster than some existing methods.
  • It demonstrated approximately 12% improvement in quality-of-fit compared to the Sawant et al. approach.
  • Performance in quality-of-fit was comparable to the Ruan and Keall algorithms, while significantly outperforming them in speed.

Conclusions:

  • The developed algorithm enhances the quality of leaf-fitting for real-time MLC tracking compared to the Sawant et al. method, without sacrificing computational speed.
  • The optimization framework facilitates advanced leaf-fitting strategies for real-time management of the PTV/OAR trade-off.
  • This approach holds promise for improving the precision and efficacy of radiotherapy for moving tumors.