Addressing challenges in low-income and middle-income countries through novel radiotherapy research opportunities.

Although radiotherapy continues to evolve as a mainstay of the oncological armamentarium, research and innovation in radiotherapy in low-income and middle-income countries (LMICs) faces challenges. This third Series paper examines the current state of LMIC radiotherapy research and provides new data from a 2022 survey undertaken by the International Atomic Energy Agency and new data on funding. In the context of LMIC-related challenges and impediments, we explore several developments and advances-such as deep phenotyping, real-time targeting, and artificial intelligence-to flag specific opportunities with applicability and relevance for resource-constrained settings. Given the pressing nature of cancer in LMICs, we also highlight some best practices and address the broader need to develop the research workforce of the future. This Series paper thereby serves as a resource for radiation professionals.

Changes in serial multiparametric MRI and FDG-PET/CT functional imaging during radiation therapy can predict treatment response in patients with head and neck cancer.

OBJECTIVES: To test if tumour changes measured using combination of diffusion-weighted imaging (DWI) MRI and FDG-PET/CT performed serially during radiotherapy (RT) in mucosal head and neck carcinoma can predict treatment response. METHODS: Fifty-five patients from two prospective imaging biomarker studies were analysed. FDG-PET/CT was performed at baseline, during RT (week 3), and post RT (3 months). DWI was performed at baseline, during RT (weeks 2, 3, 5, 6), and post RT (1 and 3 months). The ADCmean from DWI and FDG-PET parameters SUVmax, SUVmean, metabolic tumour volume (MTV), and total lesion glycolysis (TLG) were measured. Absolute and relative change (%∆) in DWI and PET parameters were correlated to 1-year local recurrence. Patients were categorised into favourable, mixed, and unfavourable imaging response using optimal cut-off (OC) values of DWI and FDG-PET parameters and correlated to local control. RESULTS: The 1-year local, regional, and distant recurrence rates were 18.2% (10/55), 7.3% (4/55), and 12.7% (7/55), respectively. ∆Week 3 ADCmean (AUC 0.825, p = 0.003; OC ∆ > 24.4%) and ∆MTV (AUC 0.833, p = 0.001; OC ∆ > 50.4%) were the best predictors of local recurrence. Week 3 was the optimal time point for assessing DWI imaging response. Using a combination of ∆ADCmean and ∆MTV improved the strength of correlation to local recurrence (p ≤ 0.001). In patients who underwent both week 3 MRI and FDG-PET/CT, significant differences in local recurrence rates were seen between patients with favourable (0%), mixed (17%), and unfavourable (78%) combined imaging response. CONCLUSIONS: Changes in mid-treatment DWI and FDG-PET/CT imaging can predict treatment response and could be utilised in the design of future adaptive clinical trials. CLINICAL RELEVANCE STATEMENT: Our study shows the complementary information provided by two functional imaging modalities for mid-treatment response prediction in patients with head and neck cancer. KEY POINTS: •FDG-PET/CT and DWI MRI changes in tumour during radiotherapy in head and neck cancer can predict treatment response. •Combination of FDG-PET/CT and DWI parameters improved correlation to clinical outcome. •Week 3 was the optimal time point for DWI MRI imaging response assessment.

Comparison between [68Ga]Ga-PSMA-617 and [18F]FET PET as Imaging Biomarkers in Adult Recurrent Glioblastoma.

The aim of this prospective clinical study was to evaluate the potential of the prostate specific membrane antigen (PSMA) targeting ligand, [68Ga]-PSMA-Glu-NH-CO-NH-Lys-2-naphthyl-L-Ala-cyclohexane-DOTA ([68Ga]Ga-PSMA-617) as a positron emission tomography (PET) imaging biomarker in recurrent glioblastoma patients. Patients underwent [68Ga]Ga-PSMA-617 and O-(2-[18F]-fluoroethyl)-L-tyrosine ([18F]FET) PET scans on two separate days. [68Ga]Ga-PSMA-617 tumour selectivity was assessed by comparing tumour volume delineation and by assessing the intra-patient correlation between tumour uptake on [68Ga]Ga-PSMA-617 and [18F]FET PET images. [68Ga]Ga-PSMA-617 tumour specificity was evaluated by comparing its tumour-to-brain ratio (TBR) with [18F]FET TBR and its tumour volume with the magnetic resonance imaging (MRI) contrast-enhancing (CE) tumour volume. Ten patients were recruited in this study. [68Ga]Ga-PSMA-617-avid tumour volume was larger than the [18F]FET tumour volume (p = 0.063). There was a positive intra-patient correlation (median Pearson r = 0.51; p < 0.0001) between [68Ga]Ga-PSMA-617 and [18F]FET in the tumour volume. [68Ga]Ga-PSMA-617 had significantly higher TBR (p = 0.002) than [18F]FET. The [68Ga]Ga-PSMA-617-avid tumour volume was larger than the CE tumour volume (p = 0.0039). Overall, accumulation of [68Ga]-Ga-PSMA-617 beyond [18F]FET-avid tumour regions suggests the presence of neoangiogenesis in tumour regions that are not overly metabolically active yet. Higher tumour specificity suggests that [68Ga]-Ga-PSMA-617 could be a better imaging biomarker for recurrent tumour delineation and secondary treatment planning than [18F]FET and CE MRI.

A systematic review of assessment approaches to predict opioid misuse in people with cancer.

CONTEXT: Cancer prevalence is increasing, with many patients requiring opioid analgesia. Clinicians need to ensure patients receive adequate pain relief. However, opioid misuse is widespread, and cancer patients are at risk. OBJECTIVES: This study aims (1) to identify screening approaches that have been used to assess and monitor risk of opioid misuse in patients with cancer; (2) to compare the prevalence of risk estimated by each of these screening approaches; and (3) to compare risk factors among demographic and clinical variables associated with a positive screen on each of the approaches. METHODS: Medline, Cochrane Controlled Trial Register, PubMed, PsycINFO, and Embase databases were searched for articles reporting opioid misuse screening in cancer patients, along with handsearching the reference list of included articles. Bias was assessed using tools from the Joanna Briggs Suite. RESULTS: Eighteen studies met the eligibility criteria, evaluating seven approaches: Urine Drug Test (UDT) (n = 8); the Screener and Opioid Assessment for Patients with Pain (SOAPP) and two variants, Revised and Short Form (n = 6); the Cut-down, Annoyed, Guilty, Eye-opener (CAGE) tool and one variant, Adapted to Include Drugs (n = 6); the Opioid Risk Tool (ORT) (n = 4); Prescription Monitoring Program (PMP) (n = 3); the Screen for Opioid-Associated Aberrant Behavior Risk (SOABR) (n = 1); and structured/specialist interviews (n = 1). Eight studies compared two or more approaches. The rates of risk of opioid misuse in the studied populations ranged from 6 to 65%, acknowledging that estimates are likely to have varied partly because of how specific to opioids the screening approaches were and whether a single or multi-step approach was used. UDT prompted by an intervention or observation of aberrant opioid behaviors (AOB) were conclusive of actual opioid misuse found to be 6.5-24%. Younger age, found in 8/10 studies; personal or family history of anxiety or other mental ill health, found in 6/8 studies; and history of illicit drug use, found in 4/6 studies, showed an increased risk of misuse. CONCLUSIONS: Younger age, personal or familial mental health history, and history of illicit drug use consistently showed an increased risk of opioid misuse. Clinical suspicion of opioid misuse may be raised by data from PMP or any of the standardized list of AOBs. Clinicians may use SOAPP-R, CAGE-AID, or ORT to screen for increased risk and may use UDT to confirm suspicion of opioid misuse or monitor adherence. More research into this important area is required. SIGNIFICANCE OF RESULTS: This systematic review summarized the literature on the use of opioid misuse risk approaches in people with cancer. The rates of reported risk range from 6 to 65%; however, true rate may be closer to 6.5-24%. Younger age, personal or familial mental health history, and history of illicit drug use consistently showed an increased risk of opioid misuse. Clinicians may choose from several approaches. Limited data are available on feasibility and patient experience. PROSPERO registration number. CRD42020163385.

Results from the AAPM Task Group 324 respiratory motion management in radiation oncology survey.

PURPOSE: To quantify the clinical practice of respiratory motion management in radiation oncology. METHODS: A respiratory motion management survey was designed and conducted based on clinician survey guidelines. The survey was administered to American Association of Physicists in Medicine (AAPM) members on 17 August 2020 and closed on 13 September 2020. RESULTS: A total of 527 respondents completed the entire survey and 651 respondents completed part of the survey, with the partially completed surveys included in the analysis. Overall, 84% of survey respondents used deep inspiration breath hold for left-sided breast cancer. Overall, 83% of respondents perceived respiratory motion management for thoracic and abdominal cancer radiotherapy patients to be either very important or required. Overall, 95% of respondents used respiratory motion management for thoracic and abdominal sites, with 36% of respondents using respiratory motion management for at least 90% of thoracic and abdominal patients. The majority (60%) of respondents used the internal target volume method to treat thoracic and abdominal cancer patients, with 25% using breath hold or abdominal compression and 13% using gating or tracking. CONCLUSIONS: A respiratory motion management survey has been completed by AAPM members. Respiratory motion management is generally considered very important or required and is widely used for breast, thoracic, and abdominal cancer treatments.

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 .

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.

Influence of respiratory motion management technique on radiation pneumonitis risk with robotic stereotactic body radiation therapy.

PURPOSE/OBJECTIVES: For lung stereotactic body radiation therapy (SBRT), real-time tumor tracking (RTT) allows for less radiation to normal lung compared to the internal target volume (ITV) method of respiratory motion management. To quantify the advantage of RTT, we examined the difference in radiation pneumonitis risk between these two techniques using a normal tissue complication probability (NTCP) model. MATERIALS/METHOD: 20 lung SBRT treatment plans using RTT were replanned with the ITV method using respiratory motion information from a 4D-CT image acquired at the original simulation. Risk of symptomatic radiation pneumonitis was calculated for both plans using a previously derived NTCP model. Features available before treatment planning that identified significant increase in NTCP with ITV versus RTT plans were identified. RESULTS: Prescription dose to the planning target volume (PTV) ranged from 22 to 60 Gy in 1-5 fractions. The median tumor diameter was 3.5 cm (range 2.1-5.5 cm) with a median volume of 14.5 mL (range 3.6-59.9 mL). The median increase in PTV volume from RTT to ITV plans was 17.1 mL (range 3.5-72.4 mL), and the median increase in PTV/lung volume ratio was 0.46% (range 0.13-1.98%). Mean lung dose and percentage dose-volumes were significantly higher in ITV plans at all levels tested. The median NTCP was 5.1% for RTT plans and 8.9% for ITV plans, with a median difference of 1.9% (range 0.4-25.5%, pairwise P < 0.001). Increases in NTCP between plans were best predicted by increases in PTV volume and PTV/lung volume ratio. CONCLUSIONS: The use of RTT decreased the risk of radiation pneumonitis in all plans. However, for most patients the risk reduction was minimal. Differences in plan PTV volume and PTV/lung volume ratio may identify patients who would benefit from RTT technique before completing treatment planning.

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.

An EPID-based system for gantry-resolved MLC quality assurance for VMAT.

Multileaf collimator (MLC) positions should be precisely and independently mea-sured as a function of gantry angle as part of a comprehensive quality assurance (QA) program for volumetric-modulated arc therapy (VMAT). It is also ideal that such a QA program has the ability to relate MLC positional accuracy to patient-specific dosimetry in order to determine the clinical significance of any detected MLC errors. In this work we propose a method to verify individual MLC trajectories during VMAT deliveries for use as a routine linear accelerator QA tool. We also extend this method to reconstruct the 3D patient dose in the treatment planning sys-tem based on the measured MLC trajectories and the original DICOM plan file. The method relies on extracting MLC positions from EPID images acquired at 8.41fps during clinical VMAT deliveries. A gantry angle is automatically tagged to each image in order to obtain the MLC trajectories as a function of gantry angle. This analysis was performed for six clinical VMAT plans acquired at monthly intervals for three months. The measured trajectories for each delivery were compared to the MLC positions from the DICOM plan file. The maximum mean error detected was 0.07 mm and a maximum root-mean-square error was 0.8 mm for any leaf of any delivery. The sensitivity of this system was characterized by introducing random and systematic MLC errors into the test plans. It was demonstrated that the system is capable of detecting random and systematic errors on the range of 1-2mm and single leaf calibration errors of 0.5 mm. The methodology developed in the work has potential to be used for efficient routine linear accelerator MLC QA and pretreatment patient-specific QA and has the ability to relate measured MLC positional errors to 3D dosimetric errors within a patient volume.

Audiovisual biofeedback breathing guidance for lung cancer patients receiving radiotherapy: a multi-institutional phase II randomised clinical trial.

BACKGROUND: There is a clear link between irregular breathing and errors in medical imaging and radiation treatment. The audiovisual biofeedback system is an advanced form of respiratory guidance that has previously demonstrated to facilitate regular patient breathing. The clinical benefits of audiovisual biofeedback will be investigated in an upcoming multi-institutional, randomised, and stratified clinical trial recruiting a total of 75 lung cancer patients undergoing radiation therapy. METHODS/DESIGN: To comprehensively perform a clinical evaluation of the audiovisual biofeedback system, a multi-institutional study will be performed. Our methodological framework will be based on the widely used Technology Acceptance Model, which gives qualitative scales for two specific variables, perceived usefulness and perceived ease of use, which are fundamental determinants for user acceptance. A total of 75 lung cancer patients will be recruited across seven radiation oncology departments across Australia. Patients will be randomised in a 2:1 ratio, with 2/3 of the patients being recruited into the intervention arm and 1/3 in the control arm. 2:1 randomisation is appropriate as within the interventional arm there is a screening procedure where only patients whose breathing is more regular with audiovisual biofeedback will continue to use this system for their imaging and treatment procedures. Patients within the intervention arm whose free breathing is more regular than audiovisual biofeedback in the screen procedure will remain in the intervention arm of the study but their imaging and treatment procedures will be performed without audiovisual biofeedback. Patients will also be stratified by treating institution and for treatment intent (palliative vs. radical) to ensure similar balance in the arms across the sites. Patients and hospital staff operating the audiovisual biofeedback system will complete questionnaires to assess their experience with audiovisual biofeedback. The objectives of this clinical trial is to assess the impact of audiovisual biofeedback on breathing motion, the patient experience and clinical confidence in the system, clinical workflow, treatment margins, and toxicity outcomes. DISCUSSION: This clinical trial marks an important milestone in breathing guidance studies as it will be the first randomised, controlled trial providing the most comprehensive evaluation of the clinical impact of breathing guidance on cancer radiation therapy to date. This study is powered to determine the impact of AV biofeedback on breathing regularity and medical image quality. Objectives such as determining the indications and contra-indications for the use of AV biofeedback, evaluation of patient experience, radiation toxicity occurrence and severity, and clinician confidence will shed light on the design of future phase III clinical trials. TRIAL REGISTRATION: This trial has been registered with the Australian New Zealand Clinical Trials Registry (ANZCTR), its trial ID is ACTRN12613001177741 .

The Remove-the-Mask Open-Source head and neck Surface-Guided radiation therapy system.

Background and Purpose: Surface Guided Radiotherapy (SGRT) for head and neck radiotherapy is challenging as obstructions are common and non-rigid facial motion can compromise surface accuracy. The purpose of this work was to develop and benchmark the Remove the Mask (RtM) SGRT system, an open-source system especially designed to address the challenges faced in radiotherapy of head and neck cancer. Materials and Methods: The accuracy of the RtM SGRT system was benchmarked using a head phantom positioned on a robotic motion platform capable of sub-millimetre accuracy which was used to induce unidirectional shifts and to reproduce three real head motion traces. We also assessed the accuracy of the system in ten humans volunteers. The ground truth motion of the volunteers was obtained using a commercial motion capture system with an accuracy < 0.3 mm. Results: The mean tracking error of the RtM SGRT system for the ten volunteers was of -0.1 ± 0.4 mm -0.6 ± 0.6 mm and 0.3 ± 0.2 mm, and 0.0 ± 0.2° 0.0 ± 0.1° and 0.0 ± 0.2° for translations and rotations along the left-right, superior-inferior and anterior-posterior axes respectively and we also found similar results in measurements with the head phantom. Forced facial motion was associated with lower tracking accuracy. The RtM SGRT system achieved submillimetre accuracy. Conclusion: The RtM SGRT system is a low-cost, easy to build and open-source SGRT system that can achieve an accuracy that meets international commissioning guidelines. Its open-source and modular design allows for the development and easy translation of novel surface tracking techniques.

Super-resolution neural networks improve the spatiotemporal resolution of adaptive MRI-guided radiation therapy.

BACKGROUND: Magnetic resonance imaging (MRI) offers superb non-invasive, soft tissue imaging of the human body. However, extensive data sampling requirements severely restrict the spatiotemporal resolution achievable with MRI. This limits the modality's utility in real-time guidance applications, particularly for the rapidly growing MRI-guided radiation therapy approach to cancer treatment. Recent advances in artificial intelligence (AI) could reduce the trade-off between the spatial and the temporal resolution of MRI, thus increasing the clinical utility of the imaging modality. METHODS: We trained deep learning-based super-resolution neural networks to increase the spatial resolution of real-time MRI. We developed a framework to integrate neural networks directly onto a 1.0 T MRI-linac enabling real-time super-resolution imaging. We integrated this framework with the targeting system of the MRI-linac to demonstrate real-time beam adaptation with super-resolution-based imaging. We tested the integrated system using large publicly available datasets, healthy volunteer imaging, phantom imaging, and beam tracking experiments using bicubic interpolation as a baseline comparison. RESULTS: Deep learning-based super-resolution increases the spatial resolution of real-time MRI across a variety of experiments, offering measured performance benefits compared to bicubic interpolation. The temporal resolution is not compromised as measured by a real-time adaptation latency experiment. These two effects, an increase in the spatial resolution with a negligible decrease in the temporal resolution, leads to a net increase in the spatiotemporal resolution. CONCLUSIONS: Deployed super-resolution neural networks can increase the spatiotemporal resolution of real-time MRI. This has applications to domains such as MRI-guided radiation therapy and interventional procedures.

Magnetic resonance imaging (MRI) is a medical imaging modality that is used to image organs such as the brain, lungs, and liver as well as diseases such as cancer. MRI scans taken at high resolution are of overly long duration. This time constraint limits the accuracy of MRI-guided cancer radiation therapy, where imaging must be fast to adapt treatment to tumour motion. Here, we deployed artificial intelligence (AI) models to achieve fast and high detail MRI. We additionally validated our AI models across various scenarios. These AI-based models could potentially enable people with cancer to be treated with higher accuracy and precision.

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.

Real-time motion management in MRI-guided radiotherapy: Current status and AI-enabled prospects.

MRI-guided radiotherapy (MRIgRT) is a highly complex treatment modality, allowing adaptation to anatomical changes occurring from one treatment day to the other (inter-fractional), but also to motion occurring during a treatment fraction (intra-fractional). In this vision paper, we describe the different steps of intra-fractional motion management during MRIgRT, from imaging to beam adaptation, and the solutions currently available both clinically and at a research level. Furthermore, considering the latest developments in the literature, a workflow is foreseen in which motion-induced over- and/or under-dosage is compensated in 3D, with minimal impact to the radiotherapy treatment time. Considering the time constraints of real-time adaptation, a particular focus is put on artificial intelligence (AI) solutions as a fast and accurate alternative to conventional algorithms.

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.

Time-resolved dose reconstruction by motion encoding of volumetric modulated arc therapy fields delivered with and without dynamic multi-leaf collimator tracking.

BACKGROUND: Organ motion during treatment delivery in radiotherapy (RT) may lead to deterioration of the planned dose, but can be mitigated by dynamic multi-leaf collimator (DMLC) tracking. The purpose of this study was to implement and experimentally validate a method for time-resolved motion including dose reconstruction for volumetric modulated arc therapy (VMAT) treatments delivered with and without DMLC tracking. MATERIAL AND METHODS: Tracking experiments were carried out on a linear accelerator (Trilogy, Varian) with a prototype DMLC tracking system. A motion stage carrying a biplanar dosimeter phantom (Delta4PT, Scandidos) reproduced eight representative clinical tumor trajectories (four lung, four prostate). For each trajectory, two single-arc 6 MV VMAT treatments with low and high modulation were delivered to the moving phantom with and without DMLC tracking. An existing in-house developed program that adds target motion to treatment plans was extended with the ability to split an arc plan into any number of sub-arcs, allowing the calculated dose for different parts of the treatment to be examined individually. For each VMAT sub-arc, reconstructed and measured doses were compared using dose differences and 3%/3 mm γ-tests. RESULTS: For VMAT sub-arcs the reconstructed dose distributions had a mean root-mean-square (rms) dose difference of 2.1% and mean γ failure rate of 2.0% when compared with the measured doses. For final accumulated doses the mean rms dose difference was 1.6% and the γ failure rate was 0.7%. CONCLUSION: The time-resolved motion including dose reconstruction was experimentally validated for complex tracking and non-tracking treatments with patient-measured tumor motion trajectories. The reconstructed dose will be of high value for evaluation of treatment plan robustness facing organ motion and adaptive RT.

TopasOpt: An open-source library for optimization with Topas Monte Carlo.

PURPOSE: To describe and test TopasOpt: a free, open-source and extensible library for performing mathematical optimization of Monte Carlo simulations in Topas. METHODS: TopasOpt enables any Topas model to be transformed into an optimization problem, and any parameter within the model to be treated as an optimization variable. Three case studies are presented. The starting model consists of a 10 MeV electron beam striking a tungsten target. The resulting bremsstrahlung X-ray spectrum is collimated by a primary and secondary collimator before being scored in a water tank. In the first case study (electron phase space optimization), five parameters describing the electron beam were treated as optimization variables and assigned a random starting value. An objective function was defined based on differences of depth-dose and profiles in water between the original (ground truth) model and a given model generated by TopasOpt. The problem was solved using Bayesian Optimization and the Nelder-Mead method. One hundred iterations were run in each case. In the second case study, (collimator geometry optimization), this process was repeated, but three geometric parameters defining the secondary collimator were treated as optimization variables and assigned random starting values, and forty iterations were run. In the third case study, the optimization was repeated with different number of primary particles to study the effect of noise on convergence. RESULTS: For case 1 (phase space optimization), both optimization algorithms successfully minimized the objective function, with absolute mean differences in profile dose of 0.4% (Bayesian) and 0.3% (Nelder-Mead) and 0.2% in depth-dose for both algorithms. The beam energy was recovered to within 1%, however some parameters had relative errors of up to 171% - a result consistent with the known X-ray dose is insensitivity to many electron beam parameters. For case 2 (geometry optimization), absolute mean differences in profile dose were 0.6% (Bayesian) and 0.9% (Nelder-Mead), and 0.5% and 0.9% in depth-dose. The maximum percentage error in any parameter was 9% with Bayesian Optimization and 28% with Nelder-Mead. Finally, the Bayesian Optimization algorithm was demonstrated to be robust to moderate levels of noise; when the standard deviation of the objective function was 16% of the mean, the maximum error in any parameter value was 16%, and the absolute mean difference in dose was 0.9% (profile) and 0.8% (depth-dose). CONCLUSIONS: An open-source library for optimization with Topas Monte Carlo has been developed, tested, and released. This tool will improve accuracy and efficiency in any situation in which the optimal value of a parameter in a Monte Carlo simulation is unknown. Applications for this tool include (1) The design of new components (2) Reverse engineering of models based on limited experimental or published data, and (3) Tuning of Monte Carlo "hyper parameters" such as variance reduction, physics settings, or scoring parameters.