Evaluating Pareto optimal tradeoffs for hippocampal avoidance whole brain radiotherapy with knowledge-based multicriteria optimization

Tsegawbizu Gebru; Kirk Luca; Jonathan Wolf; Oluwatosin Kayode; Xiaofeng Yang; Justin Roper; Jiahan Zhang

doi:10.1016/j.meddos.2023.07.002

Evaluating Pareto optimal tradeoffs for hippocampal avoidance whole brain radiotherapy with knowledge-based multicriteria optimization

Med Dosim. 2023;48(4):273-278. doi: 10.1016/j.meddos.2023.07.002. Epub 2023 Jul 24.

Authors

Tsegawbizu Gebru¹, Kirk Luca², Jonathan Wolf³, Oluwatosin Kayode², Xiaofeng Yang², Justin Roper², Jiahan Zhang⁴

Affiliations

¹ Medical Dosimetry Program, Southern Illinois University, Carbondale, IL, USA.
² Department of Radiation Oncology, Emory University, Atlanta, GA, USA.
³ Northeast Georgia Health System, Atlanta, GA, USA.
⁴ Department of Radiation Oncology, Emory University, Atlanta, GA, USA. Electronic address: jiahancheung@gmail.com.

PMID: 37495460
DOI: 10.1016/j.meddos.2023.07.002

Abstract

The goal of this study is to investigate the Pareto optimal tradeoffs between target coverage and hippocampal sparing using knowledge-based multicriteria optimization (MCO). Ten prior clinical cases were selected that were treated with hippocampal avoidance whole brain radiotherapy (HA-WBRT) using VMAT. A new, balanced plan was generated for each case using an in-house RapidPlan model in the Eclipse V16.1 treatment planning system. The MCO decision support tool was used to create 4 Pareto optimal plans. The Pareto optimal plans were created using PTV D_min and hippocampus D_max as tradeoff criteria. The tradeoff plans were generated for each patient by adjusting PTV D_min from the value achieved by the corresponding balanced plan in fixed intervals as follows: -4 Gy, -2 Gy, +2 Gy, and +4 Gy. All plans were normalized so that 95% of the PTV was covered by the prescription dose. A 1-way ANOVA, with Geisser-Greenhouse correction, was used for statistical analysis. When evaluating the achieved PTV D_min and D_98%, the results showed the dose to the hippocampus decreased as coverage lowered and in comparison, D_98% was higher when the PTV coverage was increased. When comparing multiple tradeoffs, the p-value for PTV D_98% was 0.0026, and the p-values for PTV D_2%, PTV D_min, Hippocampus D_max, D_min, and D_mean were all less than 0.0001, indicating that the tradeoff plans achieved statistically significant differences. The results also showed that Pareto optimal plans failed to reduce hippocampal dose beyond a certain point, indicating more limited achievability of the MCO-navigated plans than the interface suggested. This study presents valuable data for planning results for HA-WBRT using MCO. MCO has shown to be mostly effective in adjusting the tradeoff between PTV coverage and hippocampal dose.

Keywords: Hippocampus sparing; Knowledge-based planning; Multicriteria optimization; RapidPlan; Whole brain radiotherapy.

MeSH terms

Hippocampus
Humans
Organ Sparing Treatments* / methods
Organs at Risk
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted / methods
Radiotherapy, Intensity-Modulated* / methods

Substances

MCO