Dataset Information

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: A voxel-based morphometry approach exploiting Monte Carlo simulations.

ABSTRACT:

Purpose

In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of treatment.

Methods

We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the change.

Results

The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of treatment.

Conclusions

The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments.

SUBMITTER: Kraan AC

PROVIDER: S-EPMC9303286 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BackgroundProton pencil beam (PB) dose calculation algorithms have limited accuracy within heterogeneous tissues of lung cancer patients, which may be addressed by modern commercial Monte Carlo (MC) algorithms. We investigated clinical pencil beam scanning (PBS) dose differences between PB and MC-based treatment planning for lung cancer patients.MethodsWith IRB approval, a comparative dosimetric analysis between RayStation MC and PB dose engines was performed on ten patient plans. PBS gantry plans were generated using single-field optimization technique to maintain target coverage under range and setup uncertainties. Dose differences between PB-optimized (PBopt), MC-recalculated (MCrecalc), and MC-optimized (MCopt) plans were recorded for the following region-of-interest metrics: clinical target volume (CTV) V95, CTV homogeneity index (HI), total lung V20, total lung VRX (relative lung volume receiving prescribed dose or higher), and global maximum dose. The impact of PB-based and MC-based planning on robustness to systematic perturbation of range (±3% density) and setup (±3 mm isotropic) was assessed. Pairwise differences in dose parameters were evaluated through non-parametric Friedman and Wilcoxon sign-rank testing.ResultsIn this ten-patient sample, CTV V95 decreased significantly from 99-100% for PBopt to 77-94% for MCrecalc and recovered to 99-100% for MCopt (P<10-5). The median CTV HI (D95/D5) decreased from 0.98 for PBopt to 0.91 for MCrecalc and increased to 0.95 for MCopt (P<10-3). CTV D95 robustness to range and setup errors improved under MCopt (ΔD95 =-1%) compared to MCrecalc (ΔD95 =-6%, P=0.006). No changes in lung dosimetry were observed for large volumes receiving low to intermediate doses (e.g., V20), while differences between PB-based and MC-based planning were noted for small volumes receiving high doses (e.g., VRX). Global maximum patient dose increased from 106% for PBopt to 109% for MCrecalc and 112% for MCopt (P<10-3).ConclusionsMC dosimetry revealed a reduction in target dose coverage under PB-based planning that was regained under MC-based planning along with improved plan robustness. MC-based optimization and dose calculation should be integrated into clinical planning workflows of lung cancer patients receiving actively scanned proton therapy.

Project description:Relative motion between a tumor and a scanning proton beam results in a degradation of the dose distribution (interplay effect). This study investigates the relationship between beam scanning parameters and the interplay effect, with the goal of finding parameters that minimize interplay. 4D Monte Carlo simulations of pencil beam scanning proton therapy treatments were performed using the 4DCT geometry of five lung cancer patients of varying tumor size (50.4-167.1 cc) and motion amplitude (2.9-30.1 mm). Treatments were planned assuming delivery in 35 × 2.5 Gy(RBE) fractions. The spot size, time to change the beam energy (?es), time required for magnet settling (?ss), initial breathing phase, spot spacing, scanning direction, scanning speed, beam current and patient breathing period were varied for each of the five patients. Simulations were performed for a single fraction and an approximation of conventional fractionation. For the patients considered, the interplay effect could not be predicted using the superior-inferior motion amplitude alone. Larger spot sizes (? ~ 9-16 mm) were less susceptible to interplay, giving an equivalent uniform dose (EUD) of 99.0 ± 4.4% (1 standard deviation) in a single fraction compared to 86.1 ± 13.1% for smaller spots (? ~ 2-4 mm). The smaller spot sizes gave EUD values as low as 65.3% of the prescription dose in a single fraction. Reducing the spot spacing improved the target dose homogeneity. The initial breathing phase can have a significant effect on the interplay, particularly for shorter delivery times. No clear benefit was evident when scanning either parallel or perpendicular to the predominant axis of motion. Longer breathing periods decreased the EUD. In general, longer delivery times led to lower interplay effects. Conventional fractionation showed significant improvement in terms of interplay, giving a EUD of at least 84.7% and 100.0% of the prescription dose for the small and larger spot sizes respectively. The interplay effect is highly patient specific, depending on the motion amplitude, tumor location and the delivery parameters. Large degradations of the dose distribution in a single fraction were observed, but improved significantly using conventional fractionation.