An anatomically realistic lung model for Monte Carlo-based dose calculations

3D-printable lung phantom for distal falloff verification of proton Bragg peak

In proton therapy, the Bragg peak of a proton beam reportedly deteriorates when passing though heterogeneous structures such as human lungs. Previous studies have used heterogeneous random voxel phantoms, in which soft tissues and air are randomly allotted to render the phantoms the same density as human lungs, for conducting Monte Carlo (MC) simulations. However, measurements of these phantoms are complicated owing to their difficult‐to‐manufacture shape. In the present study, we used Voronoi tessellation to design a phantom that can be manufactured, and prepared a Voronoi lung phantom for which both measurement and MC calculations are possible. Our aim was to evaluate the effectiveness of this phantom as a new lung phantom for investigating proton beam Bragg peak deterioration. For this purpose, we measured and calculated the percentage depth dose and the distal falloff widths (DFW) passing through the phantom. For the 155 MeV beam, the measured and calculated DFW values with the Voronoi lung phantom were 0.40 and 0.39 cm, respectively. For the 200 MeV beam, the measured and calculated DFW values with the Voronoi lung phantom were both 0.48 cm. Our results indicate that both the measurements and MC calculations exhibited high reproducibility with plastinated lung sample from human body in previous studies. We found that better results were obtained using the Voronoi lung phantom than using other previous phantoms. The designed phantom may contribute significantly to the improvement of measurement precision. This study suggests that the Voronoi lung phantom is useful for simulating the effects of the heterogeneous structure of lungs on proton beam deterioration.

Radio-sensitization efficacy of gold nanoparticles in inhalational nanomedicine and the adverse effect of nano-detachment due to coating inactivation

Gold nanoparticles (GNPs) are an emerging area of interest in radiation therapy due to their unique radio-sensitizing properties. In the literature, the enhancing capability of GNPs is usually quantified using the metric dose enhancement ratio (DER). Traditionally, the focus of the vast majority of studies has always been on intravenous administration of GNPs. However, recent work showed the potential of using GNP inhalation, rather than intravenous injection, to enhance the dose to the lung. Yet, some of these studies are employing simplistic analytical methods to calculate DER and, thus far, there are no detailed computations of the enhancement profiles therein. Moreover, the coating on the GNP surface can be adversely affected by the large gradient of the radiation dose in the immediate vicinity of GNPs, leading to the rupture of ligands and detachment of GNPs from the surface of the membrane, and hence the loss of its efficacy. In this study, a next-generation deterministic code was used to resolve the DER profile at the interface between the septum, air, and surface of GNPs when they are attached and detached. The results show that the large values of DER in conjunction with the developed hot spots are very effective in lung treatment; on the other hand, coating rupture can lead to significant reduction in DER that may reach 64%. Thus, GNPs can be beneficial in inhalational medicine to treat lung cancer, provided that more comprehensive studies on the characteristics of the coating are addressed to maximize the radio-therapeutic benefit of GNPs.

The effect of disease and respiration on airway shape in patients with moderate persistent asthma

Computational models of gas transport and aerosol deposition frequently utilize idealized models of bronchial tree structure, where airways are considered a network of bifurcating cylinders. However, changes in the shape of the lung during respiration affect the geometry of the airways, especially in disease conditions. In this study, the internal airway geometry was examined, concentrating on comparisons between mean lung volume (MLV) and total lung capacity (TLC). A set of High Resolution CT images were acquired during breath hold on a group of moderate persistent asthmatics at MLV and TLC after challenge with a broncho-constrictor (methacholine) and the airway trees were segmented and measured. The airway hydraulic diameter (Dh) was calculated through the use of average lumen area (Ai) and average internal perimeter (Pi) at both lung volumes and was found to be systematically higher at TLC by 13.5±9% on average, with the lower lobes displaying higher percent change in comparison to the lower lobes. The average internal diameter (Din) was evaluated to be 12.4±6.8% (MLV) and 10.8±6.3% (TLC) lower than the Dh, for all the examined bronchi, a result displaying statistical significance. Finally, the airway distensibility per bronchial segment and per generation was calculated to have an average value of 0.45±0.28, exhibiting high variability both between and within lung regions and generations. Mixed constriction/dilation patterns were recorded between the lung volumes, where a number of airways either failed to dilate or even constricted when observed at TLC. We conclude that the Dh is higher than Din, a fact that may have considerable effects on bronchial resistance or airway loss at proximal regions. Differences in caliber changes between lung regions are indicative of asthma-expression variability in the lung. However, airway distensibility at generation 3 seems to predict distensibility more distally.

Uncertainties in planned dose due to the limited voxel size of the planning CT when treating lung tumors with proton therapy

Dose calculation for lung tumors can be challenging due to the low density and the fine structure of the geometry. The latter is not fully considered in the CT image resolution used in treatment planning causing the prediction of a more homogeneous tissue distribution. In proton therapy, this could result in predicting an unrealistically sharp distal dose falloff, i.e. an underestimation of the distal dose falloff degradation. The goal of this work was the quantification of such effects. Two computational phantoms resembling a two-dimensional heterogeneous random lung geometry and a swine lung were considered applying a variety of voxel sizes for dose calculation. Monte Carlo simulations were used to compare the dose distributions predicted with the voxel size typically used for the treatment planning procedure with those expected to be delivered using the finest resolution. The results show, for example, distal falloff position differences of up to 4 mm between planned and expected dose at the 90% level for the heterogeneous random lung (assuming treatment plan on a 2 × 2 × 2.5 mm(3) grid). For the swine lung, differences of up to 38 mm were seen when airways are present in the beam path when the treatment plan was done on a 0.8 × 0.8 × 2.4 mm(3) grid. The two-dimensional heterogeneous random lung phantom apparently does not describe the impact of the geometry adequately because of the lack of heterogeneities in the axial direction. The differences observed in the swine lung between planned and expected dose are presumably due to the poor axial resolution of the CT images used in clinical routine. In conclusion, when assigning margins for treatment planning for lung cancer, proton range uncertainties due to the heterogeneous lung geometry and CT image resolution need to be considered.