Sub-second photon dose prediction via transformer neural networks

Background: Fast dose calculation is critical for online and real-time adaptive therapy workflows. While modern physics-based dose algorithms must compromise accuracy to achieve low computation times, deep learning models can potentially perform dose prediction tasks with both high fidelity and speed. Purpose: We present a deep learning...

Modeling ray angles in deep learning based dose calculation algorithms

A fundamental tool in radiotherapy treatment planning is the dose calculation algorithm, which models the dose that will be distributed for given beam parameters and patient geometry. Various available algorithms include Monte Carlo simulations (MC) and pencil beam algorithms (PBA), with the former being computationally expensive but offering...

Implementing beam shape variations in a deep learning based proton dose calculation algorithm

In this report, a transformer based deep learning proton dose calculation algorithm called Dose Transformer Algorithm (DoTA) is described. This model learns to predict proton dose distributions by being trained with Monte Carlo generated data. Monte Carlo is the golden standard of proton dose calculation because it is very accurate, but it has...

Quantifying secondary particle dose contributions in proton therapy

In order to create radiotherapy treatment plans for cancer patients, dose calculations need to be done as quickly as possible to get accurate results. However, current dose calculation algorithms take too much time to be deployed effectively. The current in house algorithm of the Medical Physics and Technology Section at the TU Delft, attempts...

Millisecond speed deep learning based proton dose calculation with Monte Carlo accuracy

Objective. Next generation online and real-time adaptive radiotherapy workflows require precise particle transport simulations in sub-second times, which is unfeasible with current analytical pencil beam algorithms (PBA) or Monte Carlo (MC) methods. We present a deep learning based millisecond speed dose calculation algorithm (DoTA)...

Evaluating the effect of nuclear interactions on proton dose distributions through convolution methods

Cancer is a disease that causes almost 10 million deaths each year. Currently, there is no perfect treatment for it. However, there is a promising treatment called proton radiotherapy. This works almost the same as one of the older cancer treatments called photon radiotherapy. However, radiotherapy with protons has an advantage in comparison...

Proton Therapy Dose Calculations Using A Transformer Deep Learning Algorithm

Proton therapy is a great way to treat cancer, since protons can concentrate energy on one single spot, which minimises the irradiated healthy tissue. Because of this property protons are sensitive to uncertainties. Since the tumour is not stationary throughout the treatment, multiple scans are essential. With the current dose calculation...

Exploring QA methods for realtime MRI guided radiotherapy

Purpose:The MR-linac is a novel hybrid system that is used in radiotherapy (RT) and combines irradiation with MR imaging. Novel adaptive image-guided radiotherapy techniques are developed for this machine. However, new qualityassurance (QA) techniques are required that check if the (adapted) planned radiation dose is the same as the dose given...

Predicting high order Reduced Order Model coefficients for proton therapy dose approximations using deep learning

The advantage of using protons to irradiate a tumour in cancer treatment, is that the energy can be delivered very precisely to the tumour without irradiating much of the surrounding tissue. The disadvantage of this is that small displacements of a patient can result in large deviations in the planned dose delivery according to the treatment...

Towards Real Time Radiotherapy Simulation

We propose a novel reconfigurable hardware architecture to implement Monte Carlo based simulation of physical dose accumulation for intensity-modulated adaptive radiotherapy. The long term goal of our effort is to provide accurate dose calculation in real-time during patient treatment. This will allow wider adoption of personalised patient...

Towards real time radiotherapy simulation

We propose a novel reconfigurable hardware architecture to implement Monte Carlo based simulation of physical dose accumulation for intensity-modulated adaptive radiotherapy. The long term goal of our effort is to provide accurate online dose calculation in real-time during patient treatment. This will allow wider adoption of personalised...

Gd-PSMA Neutron Capture Therapy: A computational feasibility and method development study

Dose Calculation in Proton Therapy using Finite Element Methods to solve the Fokker-Planck Transport Equation

In proton therapy the development of dose calculation methods is of great importance<br/>to optimize the dose. In this work a method is presented to solve the Fokker-Planck<br/>transport equation using ray-tracing techniques and nite element methods.<br/>The idea of the method is dividing the Fokker-Planck equation in two seperate equa-<br/...