A bulk Schottky junction for high-sensitivity portable radiation detectors.

The thickness of X-ray detectors needs to reach hundreds of micrometers to absorb X-ray, and therefore, high voltages over tens or hundreds of volts should be applied to extract X-ray-generated carriers. Here, we propose a bulk Schottky junction for X-ray detection using interpenetrated macroporous-carbon electrodes and metal-halide perovskite networks. The X-ray-generated holes are extracted by the macroporous-carbon electrodes under the built-in electric field, while the electrons in the perovskite phase result in a high gain effect.

Dose, dose, dose, but where is the patient dose?

The article reviews the historical developments in radiation dose metrices in medical imaging. It identifies the good, the bad, and the ugly aspects of current-day metrices. The actions on shifting focus from International Commission on Radiological Protection (ICRP) Reference-Man-based population-average phantoms to patient-specific computational phantoms have been proposed and discussed.

A prior-information-based automatic segmentation method for the clinical target volume in adaptive radiotherapy of cervical cancer.

Objective: Adaptive planning to accommodate anatomic changes during treatment often requires repeated segmentation. In this study, prior patient-specific data was integrateda into a registration-guided multi-channel multi-path (Rg-MCMP) segmentation framework to improve the accuracy of repeated clinical target volume (CTV) segmentation.

Methods: This study was based on CT image datasets for a total of 90 cervical cancer patients who received two courses of radiotherapy.

A GPU-based fast Monte Carlo code that supports proton transport in magnetic field for radiation therapy.

This paper presents the effort to extend a previously reported code ARCHER, a GPU-based Monte Carlo (MC) code for coupled photon and electron transport, into protons including the consideration of magnetic fields. The proton transport is modeled using a Class-II condensed-history algorithm with continuous slowing-down approximation. The model includes ionization, multiple scattering, energy straggling, elastic and inelastic nuclear interactions, as well as deflection due to the Lorentz force in magnetic fields.

Investigation of total skin helical tomotherapy using a 3D-printed total skin bolus.

Objective: To investigate the effectiveness of using a 3D-printed total skin bolus in total skin helical tomotherapy for the treatment of mycosis fungoides.

Materials And Methods: A 65-year-old female patient with a 3-year history of mycosis fungoides underwent treatment using an in-house desktop fused deposition modelling printer to create a total skin bolus made of a 5-mm-thick flexible material, which increased the skin dose through dose building. The patient's scan was segmented into upper and lower sections, with the division line placed 10 cm above the patella.

Development and clinical application of a GPU-based Monte Carlo dose verification module and software for 1.5 T MR-LINAC.

Background: Adaptive radiotherapy (ART) has made significant advances owing to magnetic resonance linear accelerator (MR-LINAC), which provides superior soft-tissue contrast, fast speed and rich functional magnetic resonance imaging (MRI) to guide radiotherapy. Independent dose verification plays a critical role in discovering errors, while several challenges remain in MR-LINAC.

Purpose: A Monte Carlo-based GPU-accelerated dose verification module for Unity is proposed and integrated into the commercial software ArcherQA to achieve fast and accurate quality assurance (QA) for online ART.

Dosimetric comparison of deformable image registration and synthetic CT generation based on CBCT images for organs at risk in cervical cancer radiotherapy.

Objective: Anatomical variations existing in cervical cancer radiotherapy treatment can be monitored by cone-beam computed tomography (CBCT) images. Deformable image registration (DIR) from planning CT (pCT) to CBCT images and synthetic CT (sCT) image generation based on CBCT are two methods for improving the quality of CBCT images. This study aims to compare the accuracy of these two approaches geometrically and dosimetrically in cervical cancer radiotherapy.

A Comparison Study Between CNN-Based Deformed Planning CT and CycleGAN-Based Synthetic CT Methods for Improving iCBCT Image Quality.

Purpose: The aim of this study is to compare two methods for improving the image quality of the Varian Halcyon cone-beam CT (iCBCT) system through the deformed planning CT (dpCT) based on the convolutional neural network (CNN) and the synthetic CT (sCT) generation based on the cycle-consistent generative adversarial network (CycleGAN).

Methods: A total of 190 paired pelvic CT and iCBCT image datasets were included in the study, out of which 150 were used for model training and the remaining 40 were used for model testing. For the registration network, we proposed a 3D multi-stage registration network (MSnet) to deform planning CT images to agree with iCBCT images, and the contours from CT images were propagated to the corresponding iCBCT images through a deformation matrix.

Influencing Factors of Total Skin Irradiation With Helical Tomotherapy.

Purpose: To investigate the influencing factors of total skin irradiation (TSI) with helical tomotherapy for guiding the clinical selection of the suitable parameters and optimizing the plan quality and efficiency.

Materials And Methods: Six patients with mycosis fungoides (MF) who received TSI were retrospectively selected. They were all dressed with 5 mm thick diving suits during the CT scan and treatment as a bolus to increase the superficial dose through buildup.

Mechanistic Modelling of Slow and Fast NHEJ DNA Repair Pathways Following Radiation for G0/G1 Normal Tissue Cells.

Mechanistic in silico models can provide insight into biological mechanisms and highlight uncertainties for experimental investigation. Radiation-induced double-strand breaks (DSBs) are known to be toxic lesions if not repaired correctly. Non-homologous end joining (NHEJ) is the major DSB-repair pathway available throughout the cell cycle and, recently, has been hypothesised to consist of a fast and slow component in G0/G1.

New capabilities of the Monte Carlo dose engine ARCHER-RT: Clinical validation of the Varian TrueBeam machine for VMAT external beam radiotherapy.

Purpose: The Monte Carlo radiation transport method is considered the most accurate approach for absorbed dose calculations in external beam radiation therapy. In this study, an efficient and accurate source model of the Varian TrueBeam 6X STx Linac is developed and integrated with a fast Monte Carlo photon-electron transport absorbed dose engine, ARCHER-RT, which is capable of being executed on CPUs, NVIDIA GPUs, and AMD GPUs. This capability of fast yet accurate radiation dose calculation is essential for clinical utility of this new technology.

A fast robust optimizer for intensity modulated proton therapy using GPU.

Robust optimization has been shown to be effective for stabilizing treatment planning in intensity modulated proton therapy (IMPT), but existing algorithms for the optimization process is time-consuming. This paper describes a fast robust optimization tool that takes advantage of the GPU parallel computing technologies. The new robust optimization model is based on nine boundary dose distributions - two for ±range uncertainties, six for ±set-up uncertainties along anteroposterior (A-P), lateral (R-L) and superior-inferior (S-I) directions, and one for nominal situation.

TOPAS Monte Carlo simulation for double scattering proton therapy and dosimetric evaluation.

Purpose: To construct and commission a double scattering (DS) proton beam model in TOPAS Monte Carlo (MC) code. Dose comparisons of MC calculations to the measured and treatment planning system (TPS) calculated dose were performed.

Methods: The TOPAS nozzle model was based on the manufacturer blueprints.

Feasibility study of individualized optimal positioning selection for left-sided whole breast radiotherapy: DIBH or prone.

The deep inspiration breath hold (DIBH) and prone (P) position are two common heart-sparing techniques for external-beam radiation treatment of left-sided breast cancer patients. Clinicians select the position that is deemed to be better for tissue sparing based on their experience. This approach, however, is not always optimum and consistent.

Basic principles in the radiation dosimetry of nuclear medicine.

The basic principles of the use of radiation dosimetry in nuclear medicine are reviewed. The basic structure of the main mathematical equations are given and formal dosimetry systems are discussed. An extensive overview of the history and current status of anthropomorphic models (phantoms) is given.

Modeling respiratory motion for cancer radiation therapy based on patient-specific 4DCT data.

Prediction of respiratory motion has the potential to substantially improve cancer radiation therapy. A nonlinear finite element (FE) model of respiratory motion during full breathing cycle has been developed based on patient specific pressure-volume relationship and 4D Computed Tomography (CT) data. For geometric modeling of lungs and ribcage we have constructed intermediate CAD surface which avoids multiple geometric smoothing procedures.

Computational anthropomorphic models of the human anatomy: the path to realistic Monte Carlo modeling in radiological sciences.

The widespread availability of high-performance computing and popularity of simulations stimulated the development of computational anthropomorphic models of the human anatomy for medical imaging modalities and dosimetry calculations. The widespread interest in molecular imaging spurred the development of more realistic three- to five-dimensional computational models based on the actual anatomy and physiology of individual humans and small animals. These can be defined by either mathematical (analytical) functions or digital (voxel-based) volume arrays (or a combination of both), thus allowing the simulation of medical imaging data that are ever closer to actual patient data.

Improving the visual realism of virtual surgery.

In this work we focus our attention on improving the visual realism of virtual surgery. A synthetic solution by innovative use of various image-based rendering methods is presented for realistic rendering of virtual surgery scenes. We have, for the first time, developed a methodology for generating virtual surgery scenes with realistic glistening effects by a combination of various image-based rendering techniques, including image mosaicing and view-dependent texture mapping.