Inter-center comparison of proton range verification prototypes with an anthropomorphic head phantom.

. To compare in reproducible and equalized conditions the performance of two independent proton range verification systems based on prompt gamma-ray detectors from two different proton therapy centers..

Supervised deep learning-based synthetic computed tomography from kilovoltage cone-beam computed tomography images for adaptive radiation therapy in head and neck cancer.

Purpose: To generate and investigate a supervised deep learning algorithm for creating synthetic computed tomography (sCT) images from kilovoltage cone-beam computed tomography (kV-CBCT) images for adaptive radiation therapy (ART) in head and neck cancer (HNC).

Materials And Methods: This study generated the supervised U-Net deep learning model using 3,491 image pairs from planning computed tomography (pCT) and kV-CBCT datasets obtained from 40 HNC patients. The dataset was split into 80% for training and 20% for testing.

Delta-based Dosimetric Error Detection in Volumetric-modulated Arc Therapy: Clinical Significance and Implications.

Background: Volumetric-modulated arc therapy (VMAT) is an efficient method of administering intensity-modulated radiotherapy beams. The Delta device was employed to examine patient data.

Aims And Objectives: The utility of the Delta device in identifying errors for patient-specific quality assurance of VMAT plans was studied in this research.

Detectability of Anatomical Changes With Prompt-Gamma Imaging: First Systematic Evaluation of Clinical Application During Prostate-Cancer Proton Therapy.

Purpose: The development of online-adaptive proton therapy (PT) is essential to overcome limitations encountered by day-to-day variations of the patient's anatomy. Range verification could play an essential role in an online feedback loop for the detection of treatment deviations such as anatomical changes. Here, we present the results of the first systematic patient study regarding the detectability of anatomical changes by a prompt-gamma imaging (PGI) slit-camera system.

Automatic detection and classification of treatment deviations in proton therapy from realistically simulated prompt gamma imaging data.

Background: A clinical study regarding the potential of range verification in proton therapy (PT) by prompt gamma imaging (PGI) is carried out at our institution. Manual interpretation of the detected spot-wise range shift information is time-consuming, highly complex, and therefore not feasible in a broad routine application.

Purpose: Here, we present an approach to automatically detect and classify treatment deviations in realistically simulated PGI data for head-and-neck cancer (HNC) treatments using convolutional neural networks (CNNs) and conventional machine learning (ML) approaches.

First-In-Human Validation of CT-Based Proton Range Prediction Using Prompt Gamma Imaging in Prostate Cancer Treatments.

Purpose: Uncertainty in computed tomography (CT)-based range prediction substantially impairs the accuracy of proton therapy. Direct determination of the stopping-power ratio (SPR) from dual-energy CT (DECT) has been proposed (DirectSPR), and initial validation studies in phantoms and biological tissues have proven a high accuracy. However, a thorough validation of range prediction in patients has not yet been achieved by any means.

Classification of the source of treatment deviation in proton therapy using prompt-gamma imaging information.

Purpose: Prompt-gamma imaging (PGI)-based range verification has been successfully implemented in clinical proton therapy recently and its sensitivity to detect treatment deviations is currently investigated. The cause of treatment deviations can be multiple - for example, computed tomography (CT)-based range prediction, patient setup, and anatomical changes. Hence, it would be beneficial, if PGI-based verification would not only detect a treatment deviation but would also be able to directly identify its most probable source.

Multi-institutional evaluation using the end-to-end test for implementation of dynamic techniques of radiation therapy in Thailand.

Aim: In this study, an accuracy survey of intensity-modulated radiation therapy (IMRT) and volumetric arc radiation therapy (VMAT) implementation in radiotherapy centers in Thailand was conducted.

Background: It is well recognized that there is a need for radiotherapy centers to evaluate the accuracy levels of their current practices, and use the related information to identify opportunities for future development.

Materials And Methods: An end-to-end test using a CIRS thorax phantom was carried out at 8 participating centers.

Dosimetric Effect of Jaw Tracking in Volumetric-Modulated Arc Therapy.

The aim of this study was to investigate the potential of jaw tracking with the volumetric-modulated arc therapy (VMAT) to reduce the normal tissue dose. Plans of nasopharynx, lung, and prostate cancers (10 plans for each) were used to perform VMAT with and without jaw tracking. The dose reduction was evaluated in terms of organ doses and integral doses.

Comparison of CT images with average intensity projection, free breathing, and mid-ventilation for dose calculation in lung cancer.

The purpose of this study was to compare three computed tomography (CT) images under different conditions-average intensity projection (AIP), free breathing (FB), mid-ventilation (MidV)-used for radiotherapy contouring and planning in lung cancer patients. Two image sets derived from four-dimensional CT (4DCT) acquisition (AIP and MidV) and three-dimensional CT with FB were generated and used to plan for 29 lung cancer patients. Organs at risk (OARs) were delineated for each image.

Posterior kV-CBCT scanning of the head and neck region minimizes doses to critical organs with sustained image quality.

We evaluated the absorbed dose to critical organs, as well as the image quality, at different partial angles in kV-CBCT (Cone Beam Computed Tomography) scanning of the head and neck region. CBCT images of phantom from a 200° rotation were performed by using three different scanning paths, anterior, posterior, and right lateral with Catphan504 and RANDO phantoms. Critical organ dose was measured using TLD 100H in the RANDO phantom.