Mixed Effect Modeling of Dose and Linear Energy Transfer Correlations With Brain Image Changes After Intensity Modulated Proton Therapy for Skull Base Head and Neck Cancer

Grete May Engeseth; Renjie He; Dragan Mirkovic; Pablo Yepes; Abdallah Sherif Radwan Mohamed; Sonja Stieb; Clifton Dave Fuller; Richard Wu; Xiadong Zhang; Liv Bolstad Hysing; Helge Egil Seime Pettersen; Camilla Hanquist Stokkevåg; Radhe Mohan; Steven Jay Frank; Gary Brandon Gunn

doi:10.1016/j.ijrobp.2021.06.016

Mixed Effect Modeling of Dose and Linear Energy Transfer Correlations With Brain Image Changes After Intensity Modulated Proton Therapy for Skull Base Head and Neck Cancer

Int J Radiat Oncol Biol Phys. 2021 Nov 1;111(3):684-692. doi: 10.1016/j.ijrobp.2021.06.016. Epub 2021 Jun 19.

Authors

Affiliations

¹ The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, Texas; Haukeland University Hospital, Department of Oncology and Medical Physics, Bergen, Norway; The University of Bergen, Department of Clinical Science, Bergen, Norway. Electronic address: grete.may.engeseth@helse-bergen.no.
² The University of Texas MD Anderson Cancer Center, Department of Radiation Oncology, Houston, Texas.
³ The University of Texas MD Anderson Cancer Center, Department of Radiation Physics, Houston, Texas.
⁴ Rice University, Physics and Astronomy Department, Houston, Texas.
⁵ Haukeland University Hospital, Department of Oncology and Medical Physics, Bergen, Norway; The University of Bergen, Department of Physics and Technology, Bergen, Norway.
⁶ Haukeland University Hospital, Department of Oncology and Medical Physics, Bergen, Norway.

Abstract

Purpose: Intensity modulated proton therapy (IMPT) could yield high linear energy transfer (LET) in critical structures and increased biological effect. For head and neck cancers at the skull base this could potentially result in radiation-associated brain image change (RAIC). The purpose of the current study was to investigate voxel-wise dose and LET correlations with RAIC after IMPT.

Methods and materials: For 15 patients with RAIC after IMPT, contrast enhancement observed on T1-weighted magnetic resonance imaging was contoured and coregistered to the planning computed tomography. Monte Carlo calculated dose and dose-averaged LET (LET_d) distributions were extracted at voxel level and associations with RAIC were modelled using uni- and multivariate mixed effect logistic regression. Model performance was evaluated using the area under the receiver operating characteristic curve and precision-recall curve.

Results: An overall statistically significant RAIC association with dose and LET_d was found in both the uni- and multivariate analysis. Patient heterogeneity was considerable, with standard deviation of the random effects of 1.81 (1.30-2.72) for dose and 2.68 (1.93-4.93) for LET_d, respectively. Area under the receiver operating characteristic curve was 0.93 and 0.95 for the univariate dose-response model and multivariate model, respectively. Analysis of the LET_d effect demonstrated increased risk of RAIC with increasing LET_d for the majority of patients. Estimated probability of RAIC with LET_d = 1 keV/µm was 4% (95% confidence interval, 0%, 0.44%) and 29% (95% confidence interval, 0.01%, 0.92%) for 60 and 70 Gy, respectively. The TD₁₅ were estimated to be 63.6 and 50.1 Gy with LET_d equal to 2 and 5 keV/µm, respectively.

Conclusions: Our results suggest that the LET_d effect could be of clinical significance for some patients; LET_d assessment in clinical treatment plans should therefore be taken into consideration.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Brain
Head and Neck Neoplasms* / diagnostic imaging
Head and Neck Neoplasms* / radiotherapy
Humans
Linear Energy Transfer
Monte Carlo Method
Proton Therapy*
Radiotherapy Dosage
Radiotherapy Planning, Computer-Assisted
Relative Biological Effectiveness
Skull Base

Abstract

Publication types

MeSH terms

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