Multistep Lattice-Voxel method utilizing lattice function for Monte-Carlo treatment planning with pixel based voxel model

A physically constrained Monte Carlo-Neural Network coupling algorithm for BNCT dose calculation

BACKGROUND

In boron neutron capture therapy (BNCT)-a form of binary radiotherapy-the primary challenge in treatment planning systems for dose calculations arises from the time-consuming nature of the Monte Carlo (MC) method. Recent progress, including the use of neural networks (NN), has been made to accelerate BNCT dose calculations. However, this approach may result in significant dose errors in both the tumor and the skin, with the latter being a critical organ in BNCT. Furthermore, owing to the lack of physical processes in purely NN-based approaches, their reliability for clinical dose calculations in BNCT is questionable.

PURPOSE

In this study, a physically constrained MC-NN (PCMC-NN) coupling algorithm is proposed to achieve fast and accurate computation of the BNCT three-dimensional (3D) therapeutic dose distribution. This approach synergizes the high precision of the MC method with the speed of the NN and utilizes physical conservation laws to constrain the coupling process. It addresses the time-consuming issue of the traditional MC method while reducing dose errors.

METHODS

Clinical data were collected from 113 glioblastoma patients. For each patient, the 3D dose distributions for both the coarse and detailed dose grids were calculated using the MC code PHITS. Among these patients, the data from 14 patients were allocated to the test set, 9 to the validation set, and the remaining to the training set. A neural network, 3D-Unet, was built based on the coarse grid dose and patient CT information to enable fast and accurate computation of the 3D detailed grid dose distribution of BNCT.

RESULTS

Statistical evaluations, including relative deviation, dose deviation, mean absolute error (MAE), and mean absolute percentage error (MAPE) were conducted. Our findings suggested that the PCMC-NN algorithm substantially outperformed the traditional NN and interpolation methods. Furthermore, the proposed algorithm significantly reduced errors, particularly in the skin and GTV, and improved computational accuracy (hereinafter referred to simply as 'accuracy') with a MAPE range of 1.6%-4.0% and a maximum MAE of 0.3 Gy (IsoE) for different organs. The dose-volume histograms generated by the PCMC-NN aligned well with those obtained from the MC method, further validating its accuracy.

CONCLUSIONS

The PCMC-NN algorithm enhanced the speed and accuracy of BNCT dose calculations by combining the MC method with the NN algorithm. This indicates the significant potential of the proposed algorithm for clinical applications in optimizing treatment planning.

Multi-scale hybrid models for radiopharmaceutical dosimetry with Geant4

The accuracy of radiopharmaceutical absorbed dose distributions computed through Monte Carlo (MC) simulations is mostly limited by the low spatial resolution of 3D imaging techniques used to define the simulation geometry. This issue also persists with the implementation of realistic hybrid models built using polygonal mesh and/or NURBS as they require to be simulated in their voxel form in order to reduce computation times. The existing trade-off between voxel size and simulation speed leads on one side, in an overestimation of the size of small radiosensitive structures such as the skin or hollow organs walls and, on the other, to unnecessarily detailed voxelization of large, homogeneous structures.We developed a set of computational tools based on VTK and Geant4 in order to build multi-resolution organ models. Our aim is to use different voxel sizes to represent anatomical regions of different clinical relevance: the MC implementation of these models is expected to improve spatial resolution in specific anatomical structures without significantly affecting simulation speed. Here we present the tools developed through a proof of principle example. Our approach is validated against the standard Geant4 technique for the simulation of voxel geometries.