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Proton minibeam (pMBRT) radiation therapy: experimental validation of Monte Carlo dose calculation in the RayStation TPS.

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Collimator position optimization for proton minibeam radiation therapy.

Nimita Shinde1, Yuting Lin1, Hao Gao1

  • 1Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.

Research Square
|February 27, 2026
PubMed
Summary

A new algorithm optimizes proton minibeam radiation therapy (pMBRT) by adjusting multi-slit collimator (MSC) positions. This improves dose distribution and organs-at-risk (OAR) sparing, enhancing treatment planning efficiency.

Keywords:
mixed integer programming (MIP)multi-slit collimator (MSC)proton minibeam radiotherapy (pMBRT)

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Proton minibeam radiation therapy (pMBRT) uses spatially fractionated doses to minimize normal tissue toxicity.
  • The multi-slit collimator (MSC) is crucial for shaping proton beams into narrow minibeams.
  • Precise MSC positioning is critical for optimizing dose patterns and sparing organs-at-risk (OARs).

Purpose of the Study:

  • To develop a novel algorithm for optimizing collimator positions in pMBRT.
  • To improve the quality of pMBRT treatment plans by enabling independent lateral shifts of the MSC at each beam angle.
  • To enhance target coverage and OAR sparing through advanced computational optimization.

Main Methods:

  • Formulated a mixed-integer programming (MIP) model to jointly optimize MSC positions and spot intensities.
  • Employed an augmented Lagrangian framework with iterative convex relaxation and ADMM decomposition to solve the non-convex optimization problem.
  • Validated the algorithm on three clinical cases, comparing results against exhaustive enumeration.

Main Results:

  • The proposed collimator position optimization (CPO) algorithm achieved near-optimal solutions significantly faster than exhaustive methods (e.g., 700s vs. 15,000s).
  • Allowing multiple MSC positions per beam angle consistently improved dosimetric outcomes, especially OAR sparing.
  • Demonstrated a significant reduction in mean oral cavity dose (6.5 Gy to 4.6 Gy) in a head-and-neck case.

Conclusions:

  • The novel CPO algorithm effectively enhances pMBRT plan quality.
  • Optimizing MSC positions leads to significant improvements in OAR sparing and overall treatment efficacy.
  • The algorithm is computationally efficient and suitable for clinical integration into treatment planning workflows.