Considerations of target surface area and the risk of radiosurgical toxicity


Autoři: Strahinja Stojadinovic aff001;  Yulong Yan aff001;  Andrew Leiker aff001;  Chul Ahn aff002;  Zabi Wardak aff001;  Tu Dan aff001;  Lucien Nedzi aff001;  Robert Timmerman aff001;  Toral Patel aff003;  Samuel Barnett aff003;  Bruce Mickey aff003;  Jeffrey Meyer aff004
Působiště autorů: Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, United States of America aff001;  Department of Population and Data Sciences, University of Texas Southwestern Medical Center, Dallas, TX, United States of America aff002;  Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, TX, United States of America aff003;  Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, United States of America aff004
Vyšlo v časopise: PLoS ONE 14(10)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224047

Souhrn

Objective

The goal of this study was to explore conceptual benefits of characterizing delineated target volumes based on surface area and to utilize the concept for assessing risk of therapeutic toxicity in radiosurgery.

Methods and materials

Four computer-generated targets, a sphere, a cylinder, an ellipsoid and a box, were designed for two distinct scenarios. In the first scenario, all targets had identical volumes, and in the second one, all targets had identical surface areas. High quality stereotactic radiosurgery plans with at least 95% target coverage and selectivity were created for each target in both scenarios. Normal brain volumes V12Gy, V14Gy and V16Gy corresponding to received dose of 12 Gy, 14 Gy and 16 Gy, respectively, were computed and analyzed. Additionally, V12Gy and V14Gy volumes and values for seven prospective toxicity variables were recorded for 100 meningioma patients after Gamma Knife radiosurgery. Multivariable stepwise linear regression and best subset linear regression analyses were performed in two statistical software packages, SAS/STAT and R, respectively.

Results

In a phantom study, for the constant volume targets, the volumes of 12 Gy, 14 Gy and 16 Gy isodose clouds were the lowest for the spherical target as an expected corollary of the isoperimetric inequality. For the constant surface area targets, a conventional wisdom is confirmed, as the target volume increases the corresponding volumes V12Gy, V14Gy and V16Gy also increase. In the 100-meningioma patient cohort, the best univariate model featured tumor surface area as the most significantly associated variable with both V12Gy and V14Gy volumes, corresponding to the adjusted R2 values of 0.82 and 0.77, respectively. Two statistical methods converged to matching multivariable models.

Conclusions

In a univariate model, target surface area is a better predictor of spilled dose to normal tissue than target largest dimension or target volume itself. In complex multivariate models, target surface area is an independent variable for modeling radiosurgical normal tissue toxicity risk.

Klíčová slova:

Cancer treatment – Dose prediction methods – Linear regression analysis – Meningioma – Predictive toxicology – Radiation therapy – Toxicity – Gamma Knife radiosurgery


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Článek vyšel v časopise

PLOS One


2019 Číslo 10