Related papers: Neural Network-Driven Direct CBCT-Based Dose Calcu…
In radiotherapy, a trade-off exists between computational workload/speed and dose calculation accuracy. Calculation methods like pencil-beam convolution can be much faster than Monte-Carlo methods, but less accurate. The dose difference,…
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 stochastic Monte Carlo (MC)…
Adaptive Radiation Therapy (ART) was developed based on Image-guided Radiation Therapy (IGRT) and it is the trend of photon radiation therapy. To get a better use of Cone Beam CT (CBCT) images for ART, the CBCT system model was established…
The treatment planning process for patients with head and neck (H&N) cancer is regarded as one of the most complicated due to large target volume, multiple prescription dose levels, and many radiation-sensitive critical structures near the…
Purpose: Estimation of patient-specific organ doses is required for more comprehensive dose metrics, such as effective dose. Currently, available methods are performed retrospectively using the CT images themselves, which can only be done…
Adaptive radiotherapy is a growing field of study in cancer treatment due to it's objective in sparing healthy tissue. The standard of care in several institutions includes longitudinal cone-beam computed tomography (CBCT) acquisitions to…
Purpose: To develop a DL-based PBSPT dose prediction workflow with high accuracy and balanced complexity to support on-line adaptive proton therapy clinical decision and subsequent replanning. Methods: PBSPT plans of 103 prostate cancer…
Conventional radiotherapy dose calculation algorithms are often computationally slow and non-differentiable, creating bottlenecks for online adaptive radiotherapy (ART) and limiting end-to-end automatic planning. Deep learning provides…
Proton beam therapy has been developed to irradiate the tumor with higher precision and dose conformity compared to conventional X-ray irradiation. The dose conformity of this treatment modality may be further improved if narrower proton…
Non-coplanar Intensity-Modulated Radiation Therapy (IMRT) goes a step further by orienting the gantry carrying the radiation beam and the patient couch in a non-coplanar manner to accurately target the cancer region and better avoid…
The interplay between the beam delivery time structure and the patient motion makes 4D dose calculation (4DDC) important when treating moving tumors with intensity modulated proton therapy. 4DDC based on phase sorting of a 4DCT suffers from…
Purpose: This paper describes a new method to apply deep-learning algorithms for automatic segmentation of radiosensitive organs from 3D tomographic CT images before computing organ doses using a GPU-based Monte Carlo code. Methods: A deep…
Accurate dose calculations in proton therapy rely on high-quality CT images. While planning CTs (pCTs) serve as a reference for dosimetric planning, Cone Beam CT (CBCT) is used throughout Adaptive Radiotherapy (ART) to generate sCTs for…
Background: Dose calculation and optimization algorithms in proton therapy treatment planning often have high computational requirements regarding time and memory. This can hinder the implementation of efficient workflows in clinics and…
$Objective$. Obtaining the intrinsic dose distributions in particle therapy is a challenging problem that needs to be addressed by imaging algorithms to take advantage of secondary particle detectors. In this work, we investigate the…
Online adaptive proton therapy (APT) is an ideal solution theoretically, which however is challenging to proton clinics. Although multiple groups have been endeavoring to develop online APT technology, there is a concern in the radiotherapy…
Purpose: Organ-at-risk (OAR) delineation is a key step for cone-beam CT (CBCT) based adaptive radiotherapy planning that can be a time-consuming, labor-intensive, and subject-to-variability process. We aim to develop a fully automated…
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…
With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have improved, but at the cost of increased treatment plan complexity and planning time. The accurate prediction of dose distributions would…
Early identification of head and neck cancer (HNC) patients who would experience significant anatomical change during radiotherapy (RT) is important to optimize patient clinical benefit and treatment resources. This study aims to assess the…