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A general algorithm for distributed treatments of multiple brain metastases.

Mingli Chen1, Zabi Wardak1, Strahinja Stojadinovic1

  • 1Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75390, USA.

Medical Physics
|January 15, 2021
PubMed
Summary
This summary is machine-generated.

This study introduces an automated method for distributing brain metastases (BM) in stereotactic radiosurgery (SRS) to reduce toxicity and treatment time. The novel approach significantly improves upon manual planning, offering more uniform treatment and lower radiation doses.

Keywords:
brain metastases (BM)distributed SRSstereotactic radiosurgery (SRS)

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Area of Science:

  • Medical Physics
  • Radiation Oncology
  • Computational Biology

Background:

  • Stereotactic radiosurgery (SRS) is a key treatment for multiple brain metastases (BM).
  • Distributed SRS requires careful planning to manage treatment time and radiation toxicity.
  • Current manual BM assignment is time-consuming and prone to errors.

Purpose of the Study:

  • To develop and validate a novel automated approach for brain metastasis distribution in Gamma Knife (GK) workflows.
  • To optimize treatment planning for distributed SRS, enhancing efficiency and safety.

Main Methods:

  • Formulated BM distribution as a mixed-integer quadratic programming (MIQP) problem, minimizing total potential energy.
  • Modeled BMs as electrostatic fields with repulsive forces to ensure separation.
  • Retrospectively analyzed eight clinical GK cases, comparing automated MIQP with manual distributions.

Main Results:

  • The MIQP approach solved the distribution problem in under a minute on a personal workstation.
  • Automated distributions demonstrated lower energy objectives (median 25% decrease) and more uniform treatment volumes.
  • Results showed increased BM scattering (median 6 mm increase in mean minimum distance) and reduced overall irradiated volume (median 0.2 cc decrease).
  • Treating all BMs in one session resulted in substantially larger irradiated volumes compared to both manual and automated distributed SRS.

Conclusions:

  • The proposed MIQP approach provides an efficient and effective solution for optimal BM subset selection in distributed SRS.
  • This automated method models clinical practice and has the potential to improve workflow efficiency.
  • Further evaluations are planned to establish this approach as a clinical tool and study the benefits of distributed SRS.