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Session: Biologically Weighted Robust Planning of Proton Therapy: Knowledge Gaps, Controversies and Solutions [Return to Session]

Biologically Weighted Robust Planning of Proton Therapy: Knowledge Gaps, Controversies and Solutions

W Liu1*, R Schulte2*, R Mohan3*, K Parodi4*, A McNamara5*, (1) Mayo Clinic Arizona, Phoenix, AZ, (2) Loma Linda University, Grand Terrace, CA, (3) UT MD Anderson Cancer Center, Houston, TX, (4) Ludwig-Maximilians-Universitat Munchen, Garching B. Munich,DE, (5) Harvard / MGH, Boston, MA


WE-FG-202-0 (Wednesday, 7/13/2022) 1:45 PM - 3:45 PM [Eastern Time (GMT-4)]

Room 202

Pencil beam scanning (PBS) proton therapy poses many challenges despite dosimetric benefits. Among them is the depth dependence of relative biological effectiveness (RBE). The biological dose of proton therapy is related to its physical dose and highly dependent on the average energy loss per unit distance traveled by protons, i.e., the linear energy transfer (LET). Recently, the TG-256 report suggested assessing potential clinical consequences based on LET in proton therapy. Despite numerous in vitro and in vivo studies, it is unclear whether contemporary preclinical RBE models apply to patient outcomes. Clinical investigations have shown inconclusive results regarding the impact of LET on patient outcomes. As the number of cancer patients treated with PBS grows worldwide, and as dosimetric evaluation of LET/RBE is increasingly implemented in proton centers, more LET/RBE-related patient outcome studies are being reported. Therefore, we need to learn from these reported results to help guide and improve our clinical PBS proton therapy practice.
Another major challenge of PBS is the high sensitivity of PBS doses to inter-and intra-fractional anatomy changes and other uncertainties. If not adequately addressed, anatomic variations and other uncertainties may result in the significantly different biologically effective dose delivered from what is seen on treatment plans, leading to suboptimal outcomes. Among the solutions being developed and implemented are the improved online, near-time, and real-time image guidance to minimize uncertainties in treatment delivery. However, residual uncertainties will always remain. Different approaches for robust optimization of PBS dose distributions are being explored. Strategies to integrate the in-vivo range verification in treatment planning can promote new approaches exploiting tighter margins and less conservative beam angles for reduced toxicities at comparable or even improved tumor coverage.
The symposium will open with an introductory presentation (by Reinhard Schulte) on the clinical and radiobiological perspectives of robust planning of proton therapy. It will be followed by an overview (by Radhe Mohan) of the current knowledge gaps and controversies in the biologically weighted robust planning of PBS and the ongoing and future research to overcome current limitations. The third presentation (by Katia Parodi) will describe approaches to mitigate uncertainties in proton therapy with image guidance and its implication on PBS treatment planning. The fourth presentation (by Wei Liu) will describe methods to model the LET effects upon adverse events and how to translate the results into routine clinical practice. The fifth presentation (by Aimee McNamara) will describe variable proton RBE modeling methods for treatment planning. Finally, we will have a Q&A session for some further in-depth discussion between session speakers and the audience

Learning Objectives:
1) What is the role of LET/RBE in the correlative clinical studies of proton treatment response and in the evaluation of PBS treatment plans?
2) What are the limitations of the reported results and the clinical consequences of such limitations?
3) What treatment planning-related research needs to be done moving plan optimization and treatment response evaluation forward?
4) How can new imaging methods help mitigate the proton range uncertainties issue, and what are the implications of improved image guidance for treatment planning?
5) Which tradeoffs should be considered when optimizing a plan taking both range and biological uncertainty aspects into account?

Funding Support, Disclosures, and Conflict of Interest: This research was supported by Arizona Biomedical Research Commission Investigator Award, the Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, and the Kemper Marley Foundation.



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