Application of the pencil-beam redefinition algorithm in heterogeneous media for proton beam therapy

Proton range verification in inhomogeneous tissue: Treatment planning system vs. measurement vs. Monte Carlo simulation

In particle radiotherapy, range uncertainty is an important issue that needs to be overcome. Because high-dose conformality can be achieved using a particle beam, a small uncertainty can affect tumor control or cause normal-tissue complications. From this perspective, the treatment planning system (TPS) must be accurate. However, there is a well-known inaccuracy regarding dose computation in heterogeneous media. This means that verifying the uncertainty level is one of the prerequisites for TPS commissioning. We evaluated the range accuracy of the dose computation algorithm implemented in a commercial TPS, and Monte Carlo (MC) simulation against measurement using a CT calibration phantom. A treatment plan was produced for eight different materials plugged into a phantom, and two-dimensional doses were measured using a chamber array. The measurement setup and beam delivery were simulated by MC code. For an infinite solid water phantom, the gamma passing rate between the measurement and TPS was 97.7%, and that between the measurement and MC was 96.5%. However, gamma passing rates between the measurement and TPS were 49.4% for the lung and 67.8% for bone, and between the measurement and MC were 85.6% for the lung and 100.0% for bone tissue. For adipose, breast, brain, liver, and bone mineral, the gamma passing rates computed by TPS were 91.7%, 90.6%, 81.7%, 85.6%, and 85.6%, respectively. The gamma passing rates for MC for adipose, breast, brain, liver, and bone mineral were 100.0%, 97.2%, 95.0%, 98.9%, and 97.8%, respectively. In conclusion, the described procedure successfully evaluated the allowable range uncertainty for TPS commissioning. The TPS dose calculation is inefficient in heterogeneous media with large differences in density, such as lung or bone tissue. Therefore, the limitations of TPS in heterogeneous media should be understood and applied in clinical practice.

Evaluating the accuracy of a three-term pencil beam algorithm in heterogeneous media

The goal of this work was to evaluate the accuracy of our in-house analytical dose calculation code against MCNPX data in heterogeneous phantoms. The analytical model utilizes a pencil beam model based on Fermi-Eyges theory to account for multiple Coulomb scattering and a least-squares fit to Monte Carlo data to account for nonelastic nuclear interactions as well as any remaining, uncharacterized scatter (the 'nuclear halo'). The model characterized dose accurately (up to 1% of maximum dose in broad fields (4  ×  4 cm² and 10  ×  10 cm²) and up to 0.01% in a narrow field (0.1  ×  0.1 cm²) fit to MCNPX data). The accuracy of the model was benchmarked in three types of stylized phantoms: (1) homogeneous, (2) laterally infinite slab heterogeneities, and (3) laterally finite slab heterogeneities. Results from homogeneous phantoms and laterally infinite slab heterogeneities showed high levels of accuracy (>98% of points within 2% or 0.1 cm distance-to-agreement (DTA)). However, because range straggling and secondary particle production were not included in our model, central-axis dose differences of 2-4% were observed in laterally infinite slab heterogeneities when compared to Monte Carlo dose. In the presence of laterally finite slab heterogeneities, the analytical model resulted in lower pass rates (>96% of points within 2% or 0.1 cm DTA), which was attributed to the use of the central-axis approximation.

A correction scheme for a simplified analytical random walk model algorithm of proton dose calculation in distal Bragg peak regions

The lateral homogeneity assumption is used in most analytical algorithms for proton dose, such as the pencil-beam algorithms and our simplified analytical random walk model. To improve the dose calculation in the distal fall-off region in heterogeneous media, we analyzed primary proton fluence near heterogeneous media and propose to calculate the lateral fluence with voxel-specific Gaussian distributions. The lateral fluence from a beamlet is no longer expressed by a single Gaussian for all the lateral voxels, but by a specific Gaussian for each lateral voxel. The voxel-specific Gaussian for the beamlet of interest is calculated by re-initializing the fluence deviation on an effective surface where the proton energies of the beamlet of interest and the beamlet passing the voxel are the same. The dose improvement from the correction scheme was demonstrated by the dose distributions in two sets of heterogeneous phantoms consisting of cortical bone, lung, and water and by evaluating distributions in example patients with a head-and-neck tumor and metal spinal implants. The dose distributions from Monte Carlo simulations were used as the reference. The correction scheme effectively improved the dose calculation accuracy in the distal fall-off region and increased the gamma test pass rate. The extra computation for the correction was about 20% of that for the original algorithm but is dependent upon patient geometry.

Site-specific range uncertainties caused by dose calculation algorithms for proton therapy

The purpose of this study was to assess the possibility of introducing site-specific range margins to replace current generic margins in proton therapy. Further, the goal was to study the potential of reducing margins with current analytical dose calculations methods. For this purpose we investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict the range of proton fields. Dose distributions predicted by an analytical pencil-beam algorithm were compared with those obtained using Monte Carlo (MC) simulations (TOPAS). A total of 508 passively scattered treatment fields were analyzed for seven disease sites (liver, prostate, breast, medulloblastoma-spine, medulloblastoma-whole brain, lung and head and neck). Voxel-by-voxel comparisons were performed on two-dimensional distal dose surfaces calculated by pencil-beam and MC algorithms to obtain the average range differences and root mean square deviation for each field for the distal position of the 90% dose level (R90) and the 50% dose level (R50). The average dose degradation of the distal falloff region, defined as the distance between the distal position of the 80% and 20% dose levels (R80-R20), was also analyzed. All ranges were calculated in water-equivalent distances. Considering total range uncertainties and uncertainties from dose calculation alone, we were able to deduce site-specific estimations. For liver, prostate and whole brain fields our results demonstrate that a reduction of currently used uncertainty margins is feasible even without introducing MC dose calculations. We recommend range margins of 2.8% + 1.2 mm for liver and prostate treatments and 3.1% + 1.2 mm for whole brain treatments, respectively. On the other hand, current margins seem to be insufficient for some breast, lung and head and neck patients, at least if used generically. If no case specific adjustments are applied, a generic margin of 6.3% + 1.2 mm would be needed for breast, lung and head and neck treatments. We conclude that the currently used generic range uncertainty margins in proton therapy should be redefined site specific and that complex geometries may require a field specific adjustment. Routine verifications of treatment plans using MC simulations are recommended for patients with heterogeneous geometries.

Quantification of proton dose calculation accuracy in the lung

PURPOSE

To quantify the accuracy of a clinical proton treatment planning system (TPS) as well as Monte Carlo (MC)-based dose calculation through measurements and to assess the clinical impact in a cohort of patients with tumors located in the lung.

METHODS AND MATERIALS

A lung phantom and ion chamber array were used to measure the dose to a plane through a tumor embedded in the lung, and to determine the distal fall-off of the proton beam. Results were compared with TPS and MC calculations. Dose distributions in 19 patients (54 fields total) were simulated using MC and compared to the TPS algorithm.

RESULTS

MC increased dose calculation accuracy in lung tissue compared with the TPS and reproduced dose measurements in the target to within ±2%. The average difference between measured and predicted dose in a plane through the center of the target was 5.6% for the TPS and 1.6% for MC. MC recalculations in patients showed a mean dose to the clinical target volume on average 3.4% lower than the TPS, exceeding 5% for small fields. For large tumors, MC also predicted consistently higher V5 and V10 to the normal lung, because of a wider lateral penumbra, which was also observed experimentally. Critical structures located distal to the target could show large deviations, although this effect was highly patient specific. Range measurements showed that MC can reduce range uncertainty by a factor of ~2: the average (maximum) difference to the measured range was 3.9 mm (7.5 mm) for MC and 7 mm (17 mm) for the TPS in lung tissue.

CONCLUSION

Integration of Monte Carlo dose calculation techniques into the clinic would improve treatment quality in proton therapy for lung cancer by avoiding systematic overestimation of target dose and underestimation of dose to normal lung. In addition, the ability to confidently reduce range margins would benefit all patients by potentially lowering toxicity.