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A Novel Inverse Algorithm To Solve the Integrated Optimization of Dose, Dose Rate, and Linear Energy Transfer of
Nathan Harrison1, Minglei Kang2, Ruirui Liu3
1Emory University, Atlanta, Georgia.
International Journal of Radiation Oncology, Biology, Physics
|December 17, 2023
Summary
This study introduces an advanced proton therapy planning method for faster, more precise cancer treatments. The new approach optimizes dose, dose rate, and linear energy transfer (LET) for improved patient outcomes and reduced preclinical research needs.
Area of Science:
- Medical Physics
- Radiation Oncology
- Computational Biology
Background:
- Integrated Physical Optimization Intensity Modulated Proton Therapy (IPO-IMPT) enables simultaneous optimization of dose, dose rate, and linear energy transfer (LET) for ultra-high dose rate (FLASH) proton therapy.
- Computational challenges have limited the application of IPO-IMPT, hindering its use in clinical and preclinical settings.
- An inverse solution is needed to specify sparse filter geometry and proton intensity map weights for reduced organ-at-risk dose and fewer animal studies.
Purpose of the Study:
- To develop and demonstrate an inverse solution for IPO-IMPT that simultaneously optimizes dose, dose rate, and LET.
- To enable precise control over proton beam characteristics for both human cancer treatment and preclinical research.
- To reduce computational complexity in advanced proton therapy planning.
Main Methods:
- Developed an inverse IPO-IMPT solution involving simultaneous optimization of sparse range compensation, sparse range modulation, and spot intensity.
- Utilized a distributed computing framework, Simultaneous Intensity and Energy Modulation and Compensation (SIEMAC), to address computational challenges.
- Validated the SIEMAC framework on a human patient with central lung cancer and a minipig model.
Main Results:
- SIEMAC successfully improved spot intensity maps and generated patient-field-specific sparse range compensators and modulators.
- For a lung cancer patient, dose rate coverage above 100 Gy/s increased significantly (57% to 96% in lung, 93% to 100% in heart) with reduced LET coverage in critical areas.
- In a minipig model, SIEMAC decreased the full-width half-maximum of dose, dose rate, and LET distributions, reducing uncertainty in preclinical studies.
Conclusions:
- The developed inverse solution for IPO-IMPT effectively modulates sub-spot proton energy and intensity distributions.
- This advancement supports both clinical applications for improved cancer treatment and preclinical studies for enhanced biologic dose modeling.
- SIEMAC offers a computationally feasible approach to advanced proton therapy planning.
