Experimental validation of LET in intensity-modulated proton therapy with a miniaturized pixel detector

<i>Objective.</i>Given the increased interest in incorporating linear energy transfer (LET) as an optimization parameter in intensity-modulated proton therapy (IMPT), a solution for experimental validation of simulations and patient-specific quality assurance (PSQA) in terms of proton LET is needed. Here, we present the methodology and results of LET spectra measurements for spread-out Bragg peak (SOBP) and IMPT plans using a miniaturized pixel detector Timepix3.<i>Approach.</i>We used a MiniPIX Timepix3 detector that provides single-particle tracking, type-resolving power, and spectral information while allowing measurement in quasi-continuous mode. We performed measurements for SOBP and IMPT plans in homogeneous RW3 and heterogeneous CIRS head phantoms with reduced beam current. An artificial intelligence-based model was applied for proton identification and a GPU-accelerated FRED Monte Carlo (MC) code was applied for corresponding MC simulations.<i>Main results.</i>We compared the deposited energy and LET spectra obtained in mixed radiation fields from measurements and MC simulations. The peak positions of deposited energy and LET spectra for the SOBP and IMPT plans agree within the error bars. Discrepancies exceeding the error bars are only visible in the logarithmic scale in high-energy deposition and high-LET tails of the distributions. The mean relative difference of dose-averaged LET values between measurements and MC simulations for individual energy layers is about 5.1%.<i>Significance.</i>This study presents a methodology for assessing radiation quality in proton therapy through energy deposition and LET spectra measurements in uniform and clinical IMPT fields. Findings show an agreement between experimental data and MC simulations, validating our approach. The presented results demonstrate the feasibility of a commercially available Timepix3 detector to validate LET computations in IMPT fields and perform PSQA in terms of LET. This will support the implementation of LET in treatment planning, which will ultimately increase the effectiveness of the treatment.