BRAVEHeart: a randomised trial comparing the accuracy of Breathe Well and RPM for deep inspiration breath hold breast cancer radiotherapy.

BACKGROUND: Deep inspiration breath hold (DIBH) reduces radiotherapy cardiac dose for left-sided breast cancer patients. The primary aim of the BRAVEHeart (Breast Radiotherapy Audio Visual Enhancement for sparing the Heart) trial is to assess the accuracy and usability of a novel device, Breathe Well, for DIBH guidance for left-sided breast cancer patients. Breathe Well will be compared to an adapted widely available monitoring system, the Real-time Position Management system (RPM). METHODS: BRAVEHeart is a single institution prospective randomised trial of two DIBH devices. BRAVEHeart will assess the DIBH accuracy for Breathe Well and RPM during left-sided breast cancer radiotherapy. After informed consent has been obtained, 40 patients will be randomised into two equal groups, the experimental arm (Breathe Well) and the control arm (RPM with in-house modification of an added patient screen). The primary hypothesis of BRAVEHeart is that the accuracy of Breathe Well in maintaining the position of the chest during DIBH is superior to the RPM system. Accuracy will be measured by comparing chest wall motion extracted from images acquired of the treatment field during breast radiotherapy for patients treated using the Breathe Well system and those using the RPM system. DISCUSSION: The Breathe Well device uses a depth camera to monitor the chest surface while the RPM system monitors a block on the patient's abdomen. The hypothesis of this trial is that the chest surface is a better surrogate for the internal chest wall motion used as a measure of treatment accuracy. The Breathe Well device aims to deliver an easy-to-use implementation of surface monitoring. The findings from the study will help inform the technology choice for other centres performing DIBH. TRIAL REGISTRATION: ClinicalTrials.gov NCT02881203 . Registered on 26 August 2016.

Thoracic motion-compensated cone-beam computed tomography in under 20 seconds on a fast-rotating linac: A simulation study.

BACKGROUND: Rapid kV cone-beam computed tomography (CBCT) scans are achievable in under 20 s on select linear accelerator systems to generate volumetric images in three dimensions (3D). Daily pre-treatment four-dimensional CBCT (4DCBCT) is recommended in image-guided lung radiotherapy to mitigate the detrimental effects of respiratory motion on treatment quality. PURPOSE: To demonstrate the potential for thoracic 4DCBCT reconstruction using projection data that was simulated using a clinical rapid 3DCBCT acquisition protocol. METHODS: We simulated conventional (1320 projections over 4 min) and rapid (491 projections over 16.6 s) CBCT acquisitions using 4D computed tomography (CT) volumes of 14 lung cancer patients. Conventional acquisition data were reconstructed using the 4D Feldkamp-Davis-Kress (FDK) algorithm. Rapid acquisition data were reconstructed using 3DFDK, 4DFDK, and Motion-Compensated FDK (MCFDK). Image quality was evaluated using Contrast-to-Noise Ratio (CNR), Tissue Interface Width (TIW), Root-Mean-Square Error (RMSE), and Structural SIMilarity (SSIM). RESULTS: The conventional acquisition 4DFDK reconstructions had median phase averaged CNR, TIW, RMSE, and SSIM of 2.96, 8.02 mm, 83.5, and 0.54, respectively. The rapid acquisition 3DFDK reconstructions had median CNR, TIW, RMSE, and SSIM of 2.99, 13.6 mm, 112, and 0.44 respectively. The rapid acquisition MCFDK reconstructions had median phase averaged CNR, TIW, RMSE, and SSIM of 2.98, 10.2 mm, 103, and 0.46, respectively. Rapid acquisition 4DFDK reconstruction quality was insufficient for any practical use due to sparse angular projection sampling. CONCLUSIONS: Results suggest that 4D motion-compensated reconstruction of rapid acquisition thoracic CBCT data are feasible with image quality approaching conventional acquisition CBCT data reconstructed using standard 4DFDK.

Investigating the use of machine learning to generate ventilation images from CT scans.

BACKGROUND: Radiotherapy treatment planning incorporating ventilation imaging can reduce the incidence of radiation-induced lung injury. The gold-standard of ventilation imaging, using nuclear medicine, has limitations with respect to availability and cost. PURPOSE: An alternative type of ventilation imaging to nuclear medicine uses 4DCT (or breath-hold CT [BHCT] pair) with deformable image registration (DIR) and a ventilation metric to produce a CT ventilation image (CTVI). The purpose of this study is to investigate the application of machine learning as an alternative to DIR-based methods when producing CTVIs. METHODS: A patient dataset of 15 inhale and exhale BHCTs and Galligas PET ventilation images were used to train and test a 2D U-Net style convolutional neural network. The neural network established relationships between axial input BHCT image pairs and axial labeled Galligas PET images and was evaluated using eightfold cross-validation. Once trained, the neural network could produce a CTVI from an input BHCT image pair. The CTVIs produced by the neural network were qualitatively assessed visually and quantitatively compared to a Galligas PET ventilation image using a Spearman correlation and Dice similarity coefficient (DSC). The DSC measured the spatial overlap between three segmented equal lung volumes by ventilation (high, medium, and low functioning lung [LFL]). RESULTS: The mean Spearman correlation between the CTVIs and the Galligas PET ventilation images was 0.58 ± 0.14. The mean DSC over high, medium, and LFL between the CTVIs and Galligas PET ventilation images was 0.55 ± 0.06. Visually, a systematic overprediction of ventilation within the lung was observed in the CTVIs with respect to the Galligas PET ventilation images, with jagged regions of ventilation in the sagittal and coronal planes. CONCLUSIONS: A convolutional neural network was developed that could produce a CTVI from a BHCT image pair, which was then compared with a Galligas PET ventilation image. The performance of this machine learning method was comparable to previous benchmark studies investigating a DIR-based CTVI, warranting future development, and investigation of applying machine learning to a CTVI.

Roadmap for metal nanoparticles in radiation therapy: current status, translational challenges, and future directions.

This roadmap outlines the potential roles of metallic nanoparticles (MNPs) in the field of radiation therapy. MNPs made up of a wide range of materials (from Titanium, Z = 22, to Bismuth, Z = 83) and a similarly wide spectrum of potential clinical applications, including diagnostic, therapeutic (radiation dose enhancers, hyperthermia inducers, drug delivery vehicles, vaccine adjuvants, photosensitizers, enhancers of immunotherapy) and theranostic (combining both diagnostic and therapeutic), are being fabricated and evaluated. This roadmap covers contributions from experts in these topics summarizing their view of the current status and challenges, as well as expected advancements in technology to address these challenges.

Radio-enhancement by gold nanoparticles and their impact on water radiolysis for x-ray, proton and carbon-ion beams.

Gold nanoparticle (GNP) radio-enhancement is a promising technique to increase the dose deposition in a tumor while sparing neighboring healthy tissue. Previous experimental studies showed effects on cell survival and tumor control for keV x-rays but surprisingly also for MV-photons, proton and carbon-ion beams. In a systematic study, we use the Monte Carlo simulation tool TOPAS-nBio to model the GNP radio-enhancement within a cell as a function of GNP concentration, size and clustering for a wide range of energies for photons, protons and, for the first time, carbon-ions. Moreover, we include water radiolysis, which has been recognized as a major pathway of GNP mediated radio-enhancement. At a GNP concentration of 0.5% and a GNP diameter of 10 nm, the dose enhancement ratio was highest for 50 keV x-rays (1.36) and decreased in the orthovoltage (1.04 at 250 keV) and megavoltage range (1.01 at 1 MeV). The dose enhancement linearly increased with GNP concentration and decreased with GNP size and degree of clustering for all radiation modalities. While the highest physical dose enhancement at 5% concentrations was only 1.003 for 10 MeV protons and 1.004 for 100 MeV carbon-ions, we find the number of hydroxyl ([Formula: see text]) altered by 23% and 3% after 1 [Formula: see text]s at low, clinically-relevant concentrations. For the same concentration and proton-impact, the G-value is most sensitive to the nanoparticle size with 46 times more radical interactions at GNPs for 2 nm than for 50 nm GNP diameter within 1 [Formula: see text]s. Nanoparticle clustering was found to decrease the number of interactions at GNPs, e.g. for a cluster of 25 GNPs by a factor of 3.4. The changes in G-value correlate to the average distance between the chemical species and the GNPs. While the radiochemistry of GNP-loaded water has yet to be fully understood, this work offers a first relative quantification of radiolysis products for a broad parameter-set.

Technical Note: The first live treatment on a 1.0 Tesla inline MRI-linac.

PURPOSE: This work describes the first live imaging and radiation delivery performed on a prototype 1.0 T inline MRI-Linac system in a rat brain tumor model, which was conducted on 29 January 2019. METHODS: A human scale 1.0 T MRI-Linac was adapted to be suitable for animal studies via a specially constructed open 6-channel receiver radiofrequency (RF) coil. A Fischer rat injected with 9L glioma cells in the right hemisphere was imaged and irradiated at day 11 post surgery as part of a larger cohort survival study. The rat was anesthetized and positioned at the iscocenter of the MRI-Linac. Imaging was used to localize the brain and confirm the presence of a tumor following the administration of a gadolinium nanoparticle contrast agent. A single dose of 10 Gy was delivered using a 2.25 cm × 2.90 cm radiation field covering the whole brain and verified with radiosensitive film in situ. Real-time imaging was used throughout the irradiation period to monitor the animal and target position. RESULTS: The signal-to-noise ratio (SNR) measured in the rat brain was 38. Postcontrast imaging was able to demonstrate a tumor of 5 mm diameter in the upper right hemisphere of the brain approximately 45 min after administration of the nanoparticles. The radiation beam had no impact on SNR and images at the rate of 2 Hz were effective in monitoring both respiration and intrafractional motion. In vivo film dosimetry confirmed the intended dose delivery. The total procedure time was 35 min. CONCLUSIONS: We have successfully used MRI guidance to localize and subsequently deliver a radiation field to the whole brain of a rat with a right hemispheric tumor. Real-time imaging during beam on was of sufficient quality to monitor breathing and perform exception gating of the treatment. This represents the first live use of a high field inline MRI-Linac.

IMPACT OF NANOPARTICLE CLUSTERING ON DOSE RADIO-ENHANCEMENT.

High atomic number nanoparticles (NPs) have been shown to enhance the effects of radiation in vitro and in vivo. However, NPs are often observed to cluster together, leading to inhomogeneous distribution within the tissue and within cells themselves. The effect of this clustering on the capability of NPs to enhance radiation dose has not yet been fully investigated. In this Monte Carlo simulation study, the dependence of radio-enhancement on a separation parameter characterising NP clustering was investigated. A target water cube of side length 100 µm was simulated containing gold NPs constituting ~1% by mass. The NPs were placed in a cubic grid pattern and the separation distance between nanoparticles was varied. For NPs of 100 nm radius widely separated 2 µm apart, 91% of the total energy deposit was found to occur in the surrounding water, compared to only 56% when the NPs were moved closer together to 0.2 µm. The remaining energy deposit was absorbed by the NPs themselves. A similar trend was observed for NPs of radius 50 nm. The clustering effect was found to persist to greater separations for the larger NPs. The proportion of energy deposit in the available water of the target impacts the potential for cellular damage. Energy deposited within nanoparticles is unlikely to cause biological damage, as ionisations in the surrounding water are required to create radical oxygen species which then progress to cause the biological response to radiation. Clustering of nanoparticles is therefore expected to decrease their effectiveness for enhancing radiotherapy.

The integrated two-year check: a model of partnership working.

The Healthy Child Programme, the national universal public health programme for all children and families in the UK, requires health visitors to carry out a health review for children between two and 2.5 years. Similarly, the revised Early Years Foundation Stage statutory framework now places a new requirement on early years practitioners to review a child's learning and development through a progress check at two years. While work is being undertaken nationally for the two-year health review to be delivered jointly by health, early years and early intervention services, this paper discusses the development of an innovative, integrated local model that not only ensures better reach of two-year-old children in Harrow but also ensures best use of professional resources and expertise, and a more joined-up service for children and families.

In silico nanodosimetry: new insights into nontargeted biological responses to radiation.

The long-held view that radiation-induced biological damage must be initiated in the cell nucleus, either on or near DNA itself, is being confronted by mounting evidence to suggest otherwise. While the efficacy of cell death may be determined by radiation damage to nuclear DNA, a plethora of less deterministic biological responses has been observed when DNA is not targeted. These so-called nontargeted responses cannot be understood in the framework of DNA-centric radiobiological models; what is needed are new physically motivated models that address the damage-sensing signalling pathways triggered by the production of reactive free radicals. To this end, we have conducted a series of in silico experiments aimed at elucidating the underlying physical processes responsible for nontargeted biological responses to radiation. Our simulation studies implement new results on very low-energy electromagnetic interactions in liquid water (applicable down to nanoscales) and we also consider a realistic simulation of extranuclear microbeam irradiation of a cell. Our results support the idea that organelles with important functional roles, such as mitochondria and lysosomes, as well as membranes, are viable targets for ionizations and excitations, and their chemical composition and density are critical to determining the free radical yield and ensuing biological responses.