Land-based measures to mitigate climate change: Potential and feasibility by country.

Land-based climate mitigation measures have gained significant attention and importance in public and private sector climate policies. Building on previous studies, we refine and update the mitigation potentials for 20 land-based measures in >200 countries and five regions, comparing "bottom-up" sectoral estimates with integrated assessment models (IAMs). We also assess implementation feasibility at the country level. Cost-effective (available up to $100/tCO2 eq) land-based mitigation is 8-13.8 GtCO2 eq yr-1 between 2020 and 2050, with the bottom end of this range representing the IAM median and the upper end representing the sectoral estimate. The cost-effective sectoral estimate is about 40% of available technical potential and is in line with achieving a 1.5°C pathway in 2050. Compared to technical potentials, cost-effective estimates represent a more realistic and actionable target for policy. The cost-effective potential is approximately 50% from forests and other ecosystems, 35% from agriculture, and 15% from demand-side measures. The potential varies sixfold across the five regions assessed (0.75-4.8 GtCO2eq yr-1 ) and the top 15 countries account for about 60% of the global potential. Protection of forests and other ecosystems and demand-side measures present particularly high mitigation efficiency, high provision of co-benefits, and relatively lower costs. The feasibility assessment suggests that governance, economic investment, and socio-cultural conditions influence the likelihood that land-based mitigation potentials are realized. A substantial portion of potential (80%) is in developing countries and LDCs, where feasibility barriers are of greatest concern. Assisting countries to overcome barriers may result in significant quantities of near-term, low-cost mitigation while locally achieving important climate adaptation and development benefits. Opportunities among countries vary widely depending on types of land-based measures available, their potential co-benefits and risks, and their feasibility. Enhanced investments and country-specific plans that accommodate this complexity are urgently needed to realize the large global potential from improved land stewardship.

Study protocol of the LARK (TROG 17.03) clinical trial: a phase II trial investigating the dosimetric impact of Liver Ablative Radiotherapy using Kilovoltage intrafraction monitoring.

BACKGROUND: Stereotactic Ablative Body Radiotherapy (SABR) is a non-invasive treatment which allows delivery of an ablative radiation dose with high accuracy and precision. SABR is an established treatment for both primary and secondary liver malignancies, and technological advances have improved its efficacy and safety. Respiratory motion management to reduce tumour motion and image guidance to achieve targeting accuracy are crucial elements of liver SABR. This phase II multi-institutional TROG 17.03 study, Liver Ablative Radiotherapy using Kilovoltage intrafraction monitoring (LARK), aims to investigate and assess the dosimetric impact of the KIM real-time image guidance technology. KIM utilises standard linear accelerator equipment and therefore has the potential to be a widely available real-time image guidance technology for liver SABR. METHODS: Forty-six patients with either hepatocellular carcinoma or oligometastatic disease to the liver suitable for and treated with SABR using Kilovoltage Intrafraction Monitoring (KIM) guidance will be included in the study. The dosimetric impact will be assessed by quantifying accumulated patient dose distribution with or without the KIM intervention. The patient treatment outcomes of local control, toxicity and quality of life will be measured. DISCUSSION: Liver SABR is a highly effective treatment, but precise dose delivery is challenging due to organ motion. Currently, there is a lack of widely available options for performing real-time tumour localisation to assist with accurate delivery of liver SABR. This study will provide an assessment of the impact of KIM as a potential solution for real-time image guidance in liver SABR. TRIAL REGISTRATION: This trial was registered on December 7th 2016 on ClinicalTrials.gov under the trial-ID NCT02984566 .

How necessary and feasible are reductions of methane emissions from livestock to support stringent temperature goals?

Agriculture is the largest single source of global anthropogenic methane (CH4) emissions, with ruminants the dominant contributor. Livestock CH4 emissions are projected to grow another 30% by 2050 under current policies, yet few countries have set targets or are implementing policies to reduce emissions in absolute terms. The reason for this limited ambition may be linked not only to the underpinning role of livestock for nutrition and livelihoods in many countries but also diverging perspectives on the importance of mitigating these emissions, given the short atmospheric lifetime of CH4. Here, we show that in mitigation pathways that limit warming to 1.5°C, which include cost-effective reductions from all emission sources, the contribution of future livestock CH4 emissions to global warming in 2050 is about one-third of that from future net carbon dioxide emissions. Future livestock CH4 emissions, therefore, significantly constrain the remaining carbon budget and the ability to meet stringent temperature limits. We review options to address livestock CH4 emissions through more efficient production, technological advances and demand-side changes, and their interactions with land-based carbon sequestration. We conclude that bringing livestock into mainstream mitigation policies, while recognizing their unique social, cultural and economic roles, would make an important contribution towards reaching the temperature goal of the Paris Agreement and is vital for a limit of 1.5°C. This article is part of a discussion meeting issue 'Rising methane: is warming feeding warming? (part 1)'.

Real-time high spatial resolution dose verification in stereotactic motion adaptive arc radiotherapy.

PURPOSE: Radiation treatments delivered with real-time multileaf collimator (MLC) tracking currently lack fast pretreatment or real-time quality assurance. The purpose of this study is to test a 2D silicon detector, MagicPlate-512 (MP512), in a complex clinical environment involving real-time reconfiguration of the MLC leaves during target tracking. METHODS: MP512 was placed in the center of a solid water phantom and mounted on a motion platform used to simulate three different patient motions. Electromagnetic target tracking was implemented using the Calypso system (Varian Medical Systems, Palo Alto, CA, USA) and an MLC tracking software. A two-arc VMAT plan was delivered and 2D dose distributions were reconstructed by MP512, EBT3 film, and the Eclipse treatment planning system (TPS). Dose maps were compared using gamma analysis with 2%/2 mm and 3%/3 mm acceptance criteria. Dose profiles were generated in sup-inf and lateral directions to show the agreement of MP512 to EBT3 and to highlight the efficacy of the MLC tracking system in mitigating the effect of the simulated patient motion. RESULTS: Using a 3%/3 mm acceptance criterion for 2D gamma analysis, MP512 to EBT3 film agreement was 99% and MP512 to TPS agreement was 100%. For a 2%/2 mm criterion, the agreement was 95% and 98%, respectively. Full width at half maximum and 80%/20% penumbral width of the MP512 and EBT3 dose profiles agreed within 1 mm and 0.5 mm, respectively. Patient motion increased the measured dose profile penumbral width by nearly 2 mm (with respect to the no-motion case); however, the MLC tracking strategy was able to mitigate 80% of this effect. CONCLUSIONS: MP512 is capable of high spatial resolution 2D dose reconstruction during adaptive MLC tracking, including arc deliveries. It shows potential as an effective tool for 2D small field dosimetry and pretreatment quality assurance for MLC tracking modalities. These results provide confidence that detector-based pretreatment dosimetry is clinically feasible despite fast real-time MLC reconfigurations.

Stereotactic prostate adaptive radiotherapy utilising kilovoltage intrafraction monitoring: the TROG 15.01 SPARK trial.

BACKGROUND: This paper describes the multi-institutional prospective phase II clinical trial, SPARK: Stereotactic Prostate Adaptive Radiotherapy utilizing Kilovoltage Intrafraction Monitoring (KIM). KIM is a real-time image guided radiotherapy technology being developed and clinically pioneered for prostate cancer treatment in Australia. It has potential for widespread use for target radiotherapy treatment of cancers of the pelvis, thorax and abdomen. METHODS: In the SPARK trial we will measure the cancer targeting accuracy and patient outcomes for 48 prostate cancer patients who will be treated in five treatment sessions as opposed to the conventional 40 sessions. The reduced number of treatment sessions is enabled by the KIM's increased cancer targeting accuracy. DISCUSSION: Real-time imaging in radiotherapy has the potential to decrease the time taken during cancer treatment and reduce the imaging dose required. With the imaging being acquired during the treatment, and the analysis being automated, there is potential for improved throughput. The SPARK trial will be conducted under the auspices of the Trans-Tasman Radiation Oncology Group (TROG). TRIAL REGISTRATION: This trial was registered on ClinicalTrials.gov on 09 March 2015. The identifier is: NCT02397317.

Technical note: TROG 15.01 SPARK trial multi-institutional imaging dose measurement.

PURPOSE: The Trans-Tasman Radiation Oncology Group (TROG) 15.01 Stereotactic Prostate Adaptive Radiotherapy utilizing Kilovoltage intrafraction monitoring (SPARK) trial is a multicenter trial using Kilovoltage Intrafraction Monitoring (KIM) to monitor prostate position during the delivery of prostate radiation therapy. KIM increases the accuracy of prostate radiation therapy treatments and allows for hypofractionation. However, an additional imaging dose is delivered to the patient. A standardized procedure to determine the imaging dose per frame delivered using KIM was developed and applied at four radiation therapy centers on three different types of linear accelerator. METHODS: Dose per frame for kilovoltage imaging in fluoroscopy mode was measured in air at isocenter using an ion chamber. Beam quality and dose were determined for a Varian Clinac iX linear accelerator, a Varian Trilogy, four Varian Truebeams and one Elekta Synergy at four different radiation therapy centers. The imaging parameters used on the Varian machines were 125 kV, 80 mA, and 13 ms. The Elekta machine was measured at 120 kV, 80 mA, and 12 ms. Absorbed doses to the skin and the prostate for a typical SBRT prostate treatment length were estimated according to the IPEMB protocol. RESULTS: The average dose per kV frame to the skin was 0.24 ± 0.03 mGy. The average estimated absorbed dose to the prostate for all five treatment fractions across all machines measured was 39.9 ± 2.6 mGy for 1 Hz imaging, 199.7 ± 13.2 mGy for 5 Hz imaging and 439.3 ± 29.0 mGy for 11 Hz imaging. CONCLUSIONS: All machines measured agreed to within 20%. Additional dose to the prostate from using KIM is at most 1.3% of the prescribed dose of 36.25 Gy in five fractions delivered during the trial.

Real-time intrafraction prostate motion during linac based stereotactic radiotherapy with rectal displacement.

BACKGROUND: Kilovoltage Intrafraction Monitoring (KIM) is a method which determines the three-dimensional position of the prostate from two-dimensional kilovoltage (kV) projections taken during linac based radiotherapy treatment with real-time feedback. Rectal displacement devices (RDDs) allow for improved rectal dosimetry during prostate cancer treatment. This study used KIM to perform a preliminary investigation of prostate intrafraction motion observed in patients with an RDD in place. METHODS: Ten patients with intermediate to high-risk prostate cancer were treated with a Rectafix RDD in place during two boost fractions of 9.5-10 Gy delivered using volumetric modulated arc therapy (VMAT) on Clinac iX and Truebeam linacs. Two-dimensional kV projections were acquired during treatment. KIM software was used following treatment to determine the displacement of the prostate over time. The displacement results were analyzed to determine the percentage of treatment time the prostate spent within 1 mm, between 1 and 2 mm, between 2 and 3 mm and greater than 3 mm from its initial position. RESULTS: KIM successfully measured displacement for 19 prostate stereotactic boost fractions. The prostate was within 1 mm of its initial position for 84.8%, 1-2 mm for 14%, 2-3 mm 1.2% and ≥3 mm only 0.4% of the treatment time. CONCLUSIONS: In this preliminary study using KIM, KIM was successfully used to measure prostate intrafraction motion, which was found to be small in the presence of a rectal displacement device. TRIAL REGISTRATION: The Hunter New England Human Research Ethics Committee reference number is 14/08/20/3.01.

On the accuracy of dose prediction near metal fixation devices for spine SBRT.

The metallic fixations used in surgical procedures to support the spine mechani-cally usually consist of high-density materials. Radiation therapy to palliate spinal cord compression can include prophylactic inclusion of potential tumor around the site of such fixation devices. Determination of the correct density and shape of the spine fixation device has a direct effect on the dose calculation of the radiation field. Even with the application of modern computed tomography (CT), under- or overestimation of dose, both immediately next to the device and in the surround-ing tissues, can occur due to inaccuracies in the dose prediction algorithm. In this study, two commercially available dose prediction algorithms (Eclipse AAA and ACUROS), EGSnrc Monte Carlo, and GAFchromic film measurements were com-pared for a clinical spine SBRT case to determine their accuracy. An open six-field plan and a clinical nine-field IMRT plan were applied to a phantom containing a metal spine fixation device. Dose difference and gamma analysis were performed in and around the tumor region adjacent to the fixation device. Dose calculation inconsistency was observed in the open field plan. However, in the IMRT plan, the dose perturbation effect was not observed beyond 5 mm. Our results suggest that the dose effect of the metal fixation device to the spinal cord and the tumor volume is not observable, and all dose calculation algorithms evaluated can provide clinically acceptable accuracy in the case of spinal SBRT, with the tolerance of 95% for gamma criteria of 3%/3 mm.

Six-degrees-of-freedom pelvic bone monitoring on 2D kV intrafraction images to enable multi-target tracking for locally advanced prostate cancer.

BACKGROUND: Patients with locally advanced prostate cancer require the prostate and pelvic lymph nodes to be irradiated simultaneously during radiation therapy treatment. However, relative motion between treatment targets decreases dosimetric conformity. Current treatment methods mitigate this error by having large treatment margins and often prioritize the prostate at patient setup at the cost of lymph node coverage. PURPOSE: Treatment accuracy can be improved through real-time multi-target adaptation which requires simultaneous motion monitoring of both the prostate and lymph node targets. This study developed and evaluated an intrafraction pelvic bone motion monitoring method as a surrogate for pelvic lymph node displacement to be combined with prostate motion monitoring to enable multi-target six-degrees-of-freedom (6DoF) tracking using 2D kV projections acquired during treatment. MATERIAL AND METHODS: A method to monitor pelvic bone translation and rotation was developed and retrospectively applied to images from 20 patients treated in the TROG 15.01 Stereotactic Prostate Ablative Radiotherapy with Kilovoltage Intrafraction Monitoring (KIM) trial. The pelvic motion monitoring method performed template matching to calculate the 6DoF position of the pelvis from 2D kV images. The method first generated a library of digitally reconstructed radiographs (DRRs) for a range of imaging angles and pelvic rotations. The normalized 2D cross-correlations were then calculated for each incoming kV image and a subset of DRRs and the DRR with the maximum correlation coefficient was used to estimate the pelvis translation and rotation. Translation of the pelvis in the unresolved direction was calculated using a 3D Gaussian probability estimation method. Prostate motion was measured using the KIM marker tracking method. The pelvic motion monitoring method was compared to the ground truth obtained from a 6DoF rigid registration of the CBCT and CT. RESULTS: The geometric errors of the pelvic motion monitoring method demonstrated sub-mm and sub-degree accuracy and precision in the translational directions ( T LR ${{T}_{{\mathrm{LR}}}}$ , T SI ${{T}_{{\mathrm{SI}}}}$ , T AP ${{T}_{{\mathrm{AP}}}}$ ) and rotational directions ( R LR ${{R}_{{\mathrm{LR}}}}$ , R SI ${{R}_{{\mathrm{SI}}}}$ , R AP ${{R}_{{\mathrm{AP}}}}$ ). The 3D relative displacement between the prostate and pelvic bones exceeded 2, 3, 5, and 7 mm for approximately 66%, 44%, 12%, and 7% of the images. CONCLUSIONS: Accurate intrafraction pelvic bone motion monitoring in 6DoF was demonstrated on 2D kV images, providing a necessary tool for real-time multi-target motion-adapted treatment.

Cardiac substructure delineation in radiation therapy - A state-of-the-art review.

Delineation of cardiac substructures is crucial for a better understanding of radiation-related cardiotoxicities and to facilitate accurate and precise cardiac dose calculation for developing and applying risk models. This review examines recent advancements in cardiac substructure delineation in the radiation therapy (RT) context, aiming to provide a comprehensive overview of the current level of knowledge, challenges and future directions in this evolving field. Imaging used for RT planning presents challenges in reliably visualising cardiac anatomy. Although cardiac atlases and contouring guidelines aid in standardisation and reduction of variability, significant uncertainties remain in defining cardiac anatomy. Coupled with the inherent complexity of the heart, this necessitates auto-contouring for consistent large-scale data analysis and improved efficiency in prospective applications. Auto-contouring models, developed primarily for breast and lung cancer RT, have demonstrated performance comparable to manual contouring, marking a significant milestone in the evolution of cardiac delineation practices. Nevertheless, several key concerns require further investigation. There is an unmet need for expanding cardiac auto-contouring models to encompass a broader range of cancer sites. A shift in focus is needed from ensuring accuracy to enhancing the robustness and accessibility of auto-contouring models. Addressing these challenges is paramount for the integration of cardiac substructure delineation and associated risk models into routine clinical practice, thereby improving the safety of RT for future cancer patients.

CBCT-DRRs superior to CT-DRRs for target-tracking applications for pancreatic SBRT.

Objective.In current radiograph-based intra-fraction markerless target-tracking, digitally reconstructed radiographs (DRRs) from planning CTs (CT-DRRs) are often used to train deep learning models that extract information from the intra-fraction radiographs acquired during treatment. Traditional DRR algorithms were designed for patient alignment (i.e.bone matching) and may not replicate the radiographic image quality of intra-fraction radiographs at treatment. Hypothetically, generating DRRs from pre-treatment Cone-Beam CTs (CBCT-DRRs) with DRR algorithms incorporating physical modelling of on-board-imagers (OBIs) could improve the similarity between intra-fraction radiographs and DRRs by eliminating inter-fraction variation and reducing image-quality mismatches between radiographs and DRRs. In this study, we test the two hypotheses that intra-fraction radiographs are more similar to CBCT-DRRs than CT-DRRs, and that intra-fraction radiographs are more similar to DRRs from algorithms incorporating physical models of OBI components than DRRs from algorithms omitting these models.Approach.DRRs were generated from CBCT and CT image sets collected from 20 patients undergoing pancreas stereotactic body radiotherapy. CBCT-DRRs and CT-DRRs were generated replicating the treatment position of patients and the OBI geometry during intra-fraction radiograph acquisition. To investigate whether the modelling of physical OBI components influenced radiograph-DRR similarity, four DRR algorithms were applied for the generation of CBCT-DRRs and CT-DRRs, incorporating and omitting different combinations of OBI component models. The four DRR algorithms were: a traditional DRR algorithm, a DRR algorithm with source-spectrum modelling, a DRR algorithm with source-spectrum and detector modelling, and a DRR algorithm with source-spectrum, detector and patient material modelling. Similarity between radiographs and matched DRRs was quantified using Pearson's correlation and Czekanowski's index, calculated on a per-image basis. Distributions of correlations and indexes were compared to test each of the hypotheses. Distribution differences were determined to be statistically significant when Wilcoxon's signed rank test and the Kolmogorov-Smirnov two sample test returnedp≤ 0.05 for both tests.Main results.Intra-fraction radiographs were more similar to CBCT-DRRs than CT-DRRs for both metrics across all algorithms, with allp≤ 0.007. Source-spectrum modelling improved radiograph-DRR similarity for both metrics, with allp< 10-6. OBI detector modelling and patient material modelling did not influence radiograph-DRR similarity for either metric.Significance.Generating DRRs from pre-treatment CBCT-DRRs is feasible, and incorporating CBCT-DRRs into markerless target-tracking methods may promote improved target-tracking accuracies. Incorporating source-spectrum modelling into a treatment planning system's DRR algorithms may reinforce the safe treatment of cancer patients by aiding in patient alignment.

Prospective Randomized Trial Comparing 2 Devices for Deep Inspiration Breath Hold Management in Breast Radiation Therapy: Results of the BRAVEHeart Trial.

Purpose: The Breast Radiotherapy Audio Visual Enhancement for sparing the Heart (BRAVEHeart) trial prospectively randomized patients with left-sided breast cancer to 1 of 2 deep inspiration breath hold biofeedback devices: a novel chest surface tracking system and an abdominal block tracking system. The primary hypothesis was that the accuracy of chest tracking would be higher than that of abdominal tracking as the chest is a more direct surrogate of the breast target. Methods and Materials: Patients with left-sided breast cancer were treated in deep inspiration breath hold with intensity modulated radiation therapy delivery. Patients were randomized to either the novel chest surface system or abdominal block system for active management of breath hold with visual feedback. On both trial arms, the unallocated system was monitored passively. A total of 239,296 cine electronic portal imaging device images were analyzed retrospectively to extract the chest wall position. Treatment accuracy was quantified as the deviation of the internal chest wall during treatment relative to the planned position from the digitally reconstructed radiograph. The correlation between motion of the external surrogate and internal chest wall was calculated per-breath hold. Ease of use was assessed with questionnaires for both radiation therapists and patients and appointment length recorded. Results: Data from 26 participants were available for analysis. No difference was found in delivered treatment accuracy between arms. Across all patients and fractions, the median correlation between internal chest wall movement and external surrogate was 0.69 for the chest surface and 0.17 for the abdominal block. Patients found it easy to follow visual feedback from both systems. No difference was found in appointment length between arms. Conclusions: No statistical evidence was found for superior treatment accuracy, satisfaction, or appointment length for the novel chest surface tracking device compared with the abdominal block system. During deep inspiration breath hold, the median per-breath hold correlation of internal chest wall movement to the motion of the chest surface was higher than the median correlation of the abdominal block to the chest surface.

The first clinical implementation of real-time 6 degree-of-freedom image-guided radiotherapy for liver SABR patients.

PURPOSE: Multiple survey results have identified a demand for improved motion management for liver cancer IGRT. Until now, real-time IGRT for liver has been the domain of dedicated and expensive cancer radiotherapy systems. The purpose of this study was to clinically implement and characterise the performance of a novel real-time 6 degree-of-freedom (DoF) IGRT system, Kilovoltage Intrafraction Monitoring (KIM) for liver SABR patients. METHODS/MATERIALS: The KIM technology segmented gold fiducial markers in intra-fraction x-ray images as a surrogate for the liver tumour and converted the 2D segmented marker positions into a real-time 6DoF tumour position. Fifteen liver SABR patients were recruited and treated with KIM combined with external surrogate guidance at three radiotherapy centres in the TROG 17.03 LARK multi-institutional prospective clinical trial. Patients were either treated in breath-hold or in free breathing using the gating method. The KIM localisation accuracy and dosimetric accuracy achieved with KIM + external surrogate were measured and the results were compared to those with the estimated external surrogate alone. RESULTS: The KIM localisation accuracy was 0.2±0.9 mm (left-right), 0.3±0.6 mm (superior-inferior) and 1.2±0.8 mm (anterior-posterior) for translations and -0.1◦±0.8◦ (left-right), 0.6◦±1.2◦ (superior-inferior) and 0.1◦±0.9◦ (anterior-posterior) for rotations. The cumulative dose to the GTV with KIM + external surrogate was always within 5% of the plan. In 2 out of 15 patients, >5% dose error would have occurred to the GTV and an organ-at-risk with external surrogate alone. CONCLUSIONS: This work demonstrates that real-time 6DoF IGRT for liver can be implemented on standard radiotherapy systems to improve treatment accuracy and safety. The observations made during the treatments highlight the potential false assurance of using traditional external surrogates to assess tumour motion in patients and the need for ongoing improvement of IGRT technologies.

Real-World Implementation of Simulation-Free Radiation Therapy (SFRT-1000): A Propensity Score-Matched Analysis of 1000 Consecutive Palliative Courses Delivered in Routine Care.

PURPOSE: The feasibility of simulation-free radiation therapy (SFRT) has been demonstrated but information regarding its routine care impact and scalability is lacking. METHODS AND MATERIALS: In this single-institution, retrospective cohort study, all patients receiving palliative radiation therapy at an Australian tertiary cancer center were eligible for consideration of SFRT unless mask immobilization, a stereotactic technique, or a definitive dose was indicated. Coprimary endpoints were SFRT utilization, impact on consultation-to-RT time, and on-couch treatment duration. Timing metrics were compared with a contemporary local cohort that received simulation-based palliative radiation therapy using unadjusted Wilcoxon rank-sum tests and a propensity score-matched regression. Electronic patient-reported outcomes captured 2-week toxicity and pain response. RESULTS: Between April 2018 and February 2024, 2849 palliative radiation courses were delivered, of which 1904 were eligible. Of the 1904 courses, 1000 (52.5% SFRT utilization) received SFRT, including 668 using intensity-modulated radiation therapy/volumetric-modulated arc therapy. A total of 788 individual patients received SFRT and the median age was 71 years (IQR, 61-80) with 59% being male and 42% being Eastern Collaborative Oncology Group 2-4. SFRT utilization increased from 41% to 54% between years 2018-2019 and 2022-2024. SFRT reduced median consultation-to-RT time from 7.0 to 5.1 days (P < .0001) corresponding to an adjusted average treatment effect in the treated of -2.1 days (95% CI, -2.8 to -1.3). SFRT increased median on-couch treatment duration from 17.8 to 20.5 minutes (P < .0001; adjusted average treatment effect in the treated 2.6 minutes, 95% CI, 1.3-3.9). Patient-Reported Outcomes Version of the Common Terminology Criteria for Adverse Events grade 3 acute toxicity was 9% and at 4 weeks after RT, patients with moderate/severe pain at baseline (≥5/10) had a mean pain reduction of 3.5 points (7.1-3.6; P < .0001). CONCLUSIONS: Using widely available technologies, the SFRT-1000 cohort demonstrates routine care scalability with patient-centered and workflow benefits. SFRT is an attractive new paradigm implementable in most settings following adaptation to local requirements. Thus, SFRT opens new avenues to potentially improve access to palliative RT, which remains a global area of need.

An investigation of image guidance dose for breast radiotherapy.

Cone-beam computed tomography (CBCT) is used for external-beam radiation therapy setup and target localization. As with all medical applications of ionizing radiation, radiation exposure should be managed safely and optimized to achieve the necessary image quality using the lowest possible dose. The present study investigates doses from standard kilovoltage kV radiographic and CBCT imaging protocol, and proposes two novel reduced dose CBCT protocols for the setup of breast cancer patients undergoing external beam radiotherapy. The standard thorax kV and low-dose thorax CBCT protocols available on Varian's On-Board Imaging system was chosen as the reference technique for breast imaging. Two new CBCT protocols were created by modifying the low-dose thorax protocol, one with a reduced gantry rotation range ("Under breast" protocol) and the other with a reduced tube current-time product setting ("Low dose thorax 10ms" protocol). The absorbed doses to lungs, heart, breasts, and skin were measured using XRQA2 radiochromic film in an anthropomorphic female phantom. The absorbed doses to lungs, heart, and breasts were also calculated using the PCXMC Monte Carlo simulation software. The effective dose was calculated using the measured doses to the included organs and the ICRP 103 tissue weighting factors. The deviation between measured and simulated organ doses was between 3% and 24%. Reducing the protocol exposure time to half of its original value resulted in a reduction in the absorbed doses of the organs of 50%, while the reduced rotation range resulted in a dose reduction of at least 60%. Absorbed doses obtained from "Low dose thorax 10ms" protocol were higher than the doses from our departments orthogonal kV-kV imaging protocol. Doses acquired from "Under breast" protocol were comparable to the doses measured from the orthogonal kV-kV imaging protocol. The effective dose per fraction using the CBCT for standard low-dose thorax protocol was 5.00 ± 0.30 mSv; for the "Low dose thorax 10ms" protocol it was 2.44 ± 0.21 mSv; and for the "Under breast" protocol it was 1.23 ± 0.25 mSv when the image isocenter was positioned at the phantom center and 1.17 ± 0.30 mSv when the image isocenter was positioned in the middle of right breast. The effective dose per fraction using the orthogonal kV-kV protocol was 1.14 ± 0.16 mSv. The reduction of the scan exposure time or beam rotation range of the CBCT imaging significantly reduced the dose to the organs investigated. The doses from the "Under breast" protocol and orthogonal kV-kV imaging protocol were comparable. Simulated organ doses correlated well with measured doses. Effective doses from imaging techniques should be considered with the increase use of kV imaging protocols in order to support the use of IGRT.

Deep learning enables MV-based real-time image guided radiation therapy for prostate cancer patients.

Objective. Using MV images for real-time image guided radiation therapy (IGRT) is ideal as it does not require additional imaging equipment, adds no additional imaging dose and provides motion data in the treatment beam frame of reference. However, accurate tracking using MV images is challenging due to low contrast and modulated fields. Here, a novel real-time marker tracking system based on a convolutional neural network (CNN) classifier was developed and evaluated on retrospectively acquired patient data for MV-based IGRT for prostate cancer patients.Approach. MV images, acquired from 29 volumetric modulated arc therapy (VMAT) prostate cancer patients treated in a multi-institutional clinical trial, were used to train and evaluate a CNN-based marker tracking system. The CNN was trained using labelled MV images from 9 prostate cancer patients (35 fractions) with implanted markers. CNN performance was evaluated on an independent cohort of unseen MV images from 20 patients (78 fractions), using a Precision-Recall curve (PRC), area under the PRC plot (AUC) and sensitivity and specificity. The accuracy of the tracking system was evaluated on the same unseen dataset and quantified by calculating mean absolute (±1 SD) and [1st, 99th] percentiles of the geometric tracking error in treatment beam co-ordinates using manual identification as the ground truth.Main results. The CNN had an AUC of 0.99, sensitivity of 98.31% and specificity of 99.87%. The mean absolute geometric tracking error was 0.30 ± 0.27 and 0.35 ± 0.31 mm in the lateral and superior-inferior directions of the MV images, respectively. The [1st, 99th] percentiles of the error were [-1.03, 0.90] and [-1.12, 1.12] mm in the lateral and SI directions, respectively.Significance. The high classification performance on unseen MV images demonstrates the CNN can successfully identify implanted prostate markers. Furthermore, the sub-millimetre accuracy and precision of the marker tracking system demonstrates potential for adaptation to real-time applications.

Evaluation of the clinical feasibility of cone-beam computed tomography guided online adaption for simulation-free palliative radiotherapy.

Background and purpose: Simulation-free radiotherapy, where diagnostic imaging is used for treatment planning, improves accessibility of radiotherapy for eligible palliative patients. Combining this pathway with online adaptive radiotherapy (oART) may improve accuracy of treatment, expanding the number of eligible patients. This study evaluated the adaptive process duration, plan dose volume histogram (DVH) metrics and geometric accuracy of a commercial cone-beam computed tomography (CBCT)-guided oART system for simulation-free, palliative radiotherapy. Materials and methods: Ten previously treated palliative cases were used to compare system-generated contours against clinician contours in a test environment with Dice Similarity Coefficient (DSC). Twenty simulation-free palliative patients were treated clinically using CBCT-guided oART. Analysis of oART clinical treatment data included; evaluation of the geometric accuracy of system-generated synthetic CT relative to session CBCT anatomy using a Likert scale, comparison of adaptive plan dose distributions to unadapted, using DVH metrics and recording the duration of key steps in the oART workflow. Results: Auto-generated contours achieved a DSC of higher than 0.85, excluding the stomach which was attributed to CBCT image quality issues. Synthetic CT was locally aligned to CBCT anatomy for approximately 80% of fractions, with the remaining suboptimal yet clinically acceptable. Adaptive plans achieved a median CTV V95% of 99.5%, compared to 95.6% for unadapted. The median overall oART process duration was found to be 13.2 mins, with contour editing being the most time-intensive adaptive step. Conclusions: The CBCT-guided oART system utilising a simulation-free planning approach was found to be sufficiently accurate for clinical implementation, this may further streamline and improve care for palliative patients.

Evaluation of deep learning based implanted fiducial markers tracking in pancreatic cancer patients.

Real-time target position verification during pancreas stereotactic body radiation therapy (SBRT) is important for the detection of unplanned tumour motions. Fast and accurate fiducial marker segmentation is a Requirement of real-time marker-based verification. Deep learning (DL) segmentation techniques are ideal because they don't require additional learning imaging or prior marker information (e.g., shape, orientation). In this study, we evaluated three DL frameworks for marker tracking applied to pancreatic cancer patient data. The DL frameworks evaluated were (1) a convolutional neural network (CNN) classifier with sliding window, (2) a pretrained you-only-look-once (YOLO) version-4 architecture, and (3) a hybrid CNN-YOLO. Intrafraction kV images collected during pancreas SBRT treatments were used as training data (44 fractions, 2017 frames). All patients had 1-4 implanted fiducial markers. Each model was evaluated on unseen kV images (42 fractions, 2517 frames). The ground truth was calculated from manual segmentation and triangulation of markers in orthogonal paired kV/MV images. The sensitivity, specificity, and area under the precision-recall curve (AUC) were calculated. In addition, the mean-absolute-error (MAE), root-mean-square-error (RMSE) and standard-error-of-mean (SEM) were calculated for the centroid of the markers predicted by the models, relative to the ground truth. The sensitivity and specificity of the CNN model were 99.41% and 99.69%, respectively. The AUC was 0.9998. The average precision of the YOLO model for different values of recall was 96.49%. The MAE of the three models in the left-right, superior-inferior, and anterior-posterior directions were under 0.88 ± 0.11 mm, and the RMSE were under 1.09 ± 0.12 mm. The detection times per frame on a GPU were 48.3, 22.9, and 17.1 milliseconds for the CNN, YOLO, and CNN-YOLO, respectively. The results demonstrate submillimeter accuracy of marker position predicted by DL models compared to the ground truth. The marker detection time was fast enough to meet the requirements for real-time application.

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.

The MANGO study: a prospective investigation of oxygen enhanced and blood-oxygen level dependent MRI as imaging biomarkers of hypoxia in glioblastoma.

Background: Glioblastoma (GBM) is the most aggressive type of brain cancer, with a 5-year survival rate of ~5% and most tumours recurring locally within months of first-line treatment. Hypoxia is associated with worse clinical outcomes in GBM, as it leads to localized resistance to radiotherapy and subsequent tumour recurrence. Current standard of care treatment does not account for tumour hypoxia, due to the challenges of mapping tumour hypoxia in routine clinical practice. In this clinical study, we aim to investigate the role of oxygen enhanced (OE) and blood-oxygen level dependent (BOLD) MRI as non-invasive imaging biomarkers of hypoxia in GBM, and to evaluate their potential role in dose-painting radiotherapy planning and treatment response assessment. Methods: The primary endpoint is to evaluate the quantitative and spatial correlation between OE and BOLD MRI measurements and [18F]MISO values of uptake in the tumour. The secondary endpoints are to evaluate the repeatability of MRI biomarkers of hypoxia in a test-retest study, to estimate the potential clinical benefits of using MRI biomarkers of hypoxia to guide dose-painting radiotherapy, and to evaluate the ability of MRI biomarkers of hypoxia to assess treatment response. Twenty newly diagnosed GBM patients will be enrolled in this study. Patients will undergo standard of care treatment while receiving additional OE/BOLD MRI and [18F]MISO PET scans at several timepoints during treatment. The ability of OE/BOLD MRI to map hypoxic tumour regions will be evaluated by assessing spatial and quantitative correlations with areas of hypoxic tumour identified via [18F]MISO PET imaging. Discussion: MANGO (Magnetic resonance imaging of hypoxia for radiation treatment guidance in glioblastoma multiforme) is a diagnostic/prognostic study investigating the role of imaging biomarkers of hypoxia in GBM management. The study will generate a large amount of longitudinal multimodal MRI and PET imaging data that could be used to unveil dynamic changes in tumour physiology that currently limit treatment efficacy, thereby providing a means to develop more effective and personalised treatments.