Treatment Workflow Research Articles

Cone beam computed tomography image guidance within a magnetic resonance imaging-only planning workflow.

Magnetic Resonance Imaging (MRI)-only planning workflows offer many advantages but raises challenges regarding image guidance. The study aimed to assess the viability of MRI to Cone Beam Computed Tomography (CBCT) based image guidance for MRI-only planning treatment workflows. An MRI matching training package was developed. Ten radiation therapists, with a range of clinical image guidance experience and experience with MRI, completed the training package prior to matching assessment. The matching assessment was performed on four match regions: prostate gold seed, prostate soft tissue, rectum/anal canal and gynaecological. Each match region consisted of five patients, with three CBCTs per patient, resulting in fifteen CBCTs for each match region. The ten radiation therapists performed the CBCT image matching to CT and to MRI for all regions and recorded the match values. The median inter-observer variation for MRI-CBCT matching and CT-CBCT matching for all regions were within 2mm and 1 degree. There was no statistically significant association in the inter-observer variation in mean match values and radiation therapist image guidance experience levels. There was no statistically significant association in inter-observer variation in mean match values for MRI experience levels for prostate soft tissue and gynaecological match regions, while there was a statistically significant difference for prostate gold seed and rectum match regions. The results of this study support the concept that with focussed training, an MRI to CBCT image guidance approach can be successfully implemented in a clinical planning workflow.

Best practices in epidermal growth factor receptor T790M testing for advanced non-small-cell lung cancer in Hong Kong.

The T790M mutation in the epidermal growth factor receptor gene causes most acquired resistance to firstor second-line epidermal growth factor receptor-tyrosine kinase inhibitors in advanced non-small-cell lung cancer. The results of T790M testing can guide subsequent treatment. Despite the availability of guidelines from international organisations, T790M testing practices in Hong Kong must be streamlined and adapted to the Hospital Authority setting. To address this issue, a panel of experts in oncology and pathology met for discussion of key topics regarding T790M testing practices in Hong Kong, including the appropriate timing of testing and re-testing, as well as optimal testing methods. All panel members voted on the results of the discussion to achieve consensus. Items supported by a majority vote were adopted as consensus statements regarding current best practices for T790M testing in Hong Kong. Among the topics discussed, the panel agreed that T790M testing should be initiated upon radiological progression, including symptomatic disease progression or central nervous system-only progression. The experts also preferred initial testing with liquid biopsy, using the widely available digital polymerase chain reaction platform. This document provides the final consensus statements, as well as a testing and treatment workflow, for clinicians in Hong Kong to use as guidance in T790M testing.

Radiation Exposure in Interventional Stroke Treatment

PurposeTo evaluate patient-related radiation exposure in interventional stroke treatment by analyzing data from the German Society for Interventional Radiology and Minimally Invasive Therapy (DeGIR) and the German Society of Neuroradiology (DGNR) quality registry from 2019–2021.MethodsThe DeGIR/DGNR registry is the largest database of radiological interventions in Germany. Since the introduction of the registry in 2012, the participating hospitals have entered clinical and dose-related data on the procedures performed. To evaluate the current diagnostic reference level (DRL) for mechanical thrombectomy (MT) in stroke patients, we analyzed interventional data from 2019 to 2021 with respect to the reported dose area product (DAP) and factors that might contribute to the radiation dose, such as the localization of the occlusion, technical success using the modified treatment in cerebral ischemia (mTICI) score, number of passages, technical approach, additional intracranial/extracranial stenting, and case volume per center.ResultsA total of 41,538 performed MTs from 180 participating hospitals were analyzed. The median DAP for MT was 7337.5 cGy∙cm2 and the corresponding interquartile range (IQR) Q25 = 4064 cGy∙cm2 to Q75 = 12,263 cGy∙cm2. In addition, we discovered that the dose was significantly influenced by occlusion location, number of passages, case volume per center, recanalization score, and additional stenting.ConclusionWe conducted a retrospective study on radiation exposure during MT in Germany. Based on the results of more than 41,000 procedures, we observed that the DRL of 14,000 cGy·cm2 is currently appropriate but may be lowered over the next years. Furthermore, we identified several factors that contribute to high radiation exposure. This can aid in detecting the cause of an exceeded DRL and optimize the treatment workflow.

Joint radial trajectory correction for accelerated T2 * mapping on an MR-Linac.

T2 * mapping can characterize tumor hypoxia, which may be associated with resistance to therapy. Acquiring T2 * maps during MR-guided radiotherapy could inform treatment adaptation by, for example, escalating the dose to resistant sub-volumes. The purpose of this work is to demonstrate the feasibility of the accelerated T2 * mapping technique using model-based image reconstruction with integrated trajectory auto-correction (TrACR) for MR-guided radiotherapy on an MR-Linear accelerator (MR-Linac). The proposed method was validated in a numerical phantom, where two T2 * mapping approaches (sequential and joint) were compared for different noise levels (0,0.1,0.5,1) and gradient delays ([1, -1] and [1, -2] in units of dwell time for x- and y-axis, respectively). Fully sampled k-space was retrospectively undersampled using two different undersampling patterns. Root mean square errors (RMSEs) were calculated between reconstructed T2 * maps and ground truth. In vivo data was acquired twice weekly in one prostate and one head and neck cancer patient undergoing treatment on a 1.5 T MR-Linac. Data were retrospectively undersampled and T2 * maps reconstructed, with and without trajectory corrections were compared. Numerical simulations demonstrated that, for all noise levels, T2 * maps reconstructed with a joint approach demonstrated less error compared to an uncorrected and sequential approach. For a noise level of 0.1, uniform undersampling and gradient delay [1, -1] (in units of dwell time for x- and y-axis, respectively), RMSEs for sequential and joint approaches were 13.01 and 9.32ms, respectively, which reduced to 10.92 and 5.89ms for a gradient delay of [1, 2]. Similarly, for alternate undersampling and gradient delay [1, -1], RMSEs for sequential and joint approaches were 9.80 and 8.90ms, respectively, which reduced to 9.10 and 5.40ms for gradient delay [1, 2]. For in vivo data, T2 * maps reconstructed with our proposed approach resulted in less artifacts and improved visual appearance compared to the uncorrected approach. For both prostate and head and neck cancer patients, T2 * maps reconstructed from different treatment fractions showed changes within the planning target volume (PTV). Using the proposed approach, a retrospective data-driven gradient delay correction can be performed, which is particularly relevant for hybrid devices, where full information on the machine configuration is not available for image reconstruction. T2 * maps were acquired in under 5 min and can be integrated into MR-guided radiotherapy treatment workflows, which minimizes patient burden and leaves time for additional imaging for online adaptive radiotherapy on an MR-Linac.

3D imaging assistance impact on atrial fibrillation cryoablation efficiency, a method validation study

Abstract Funding Acknowledgements Type of funding sources: Other. Main funding source(s): CGRA: CARD; CGRB: 31’297 Background Pulmonary vein isolation (PVI) by cryoballoon ablation is a well-known therapy for the treatment of atrial fibrillation (AF). Current 3D-navigation technologies usually used with RF ablation allow for a drastic reduction of intra-procedural X-ray exposure and imaging aided/guided methods allow for better anatomical characterization improving acute and long-term procedural results. 3D imaging fusion on real-time fluoroscopy is a well-known technology but the incremental value of 3D imaging fusion as a guiding tool on AF cryoballoon ablation therapy has not been studied yet. Purpose To increase procedural efficiency by integration of 3D imaging guidance in conventional cryoballoon PVI. Methods Using semi-automatic segmentation (Alphenix, Canon Medical Systems Corporation) obtained from pre-procedural cardiac computed tomography (CT); two anatomic volumes were fused on the real-time fluoroscopy display: left atrium (LA), including pulmonary veins (PV) and spine with proximal rib section (most radio-opaque body part in the thoracic area). The merging was performed by 3D registration of the bone segment with fluoroscopic acquisitions in three standard positions (AP, LAO, RAO), acquired at the beginning of the procedure. To standardize treatment workflow, the study was restricted to patients with paroxysmal atrial fibrillation. Results Twenty patients were included in the study: 10 in the control group (conventional fluoroscopy based cryoballoon ablation), and 10 in the 3D assisted group. Mean age was 59±15 SD years for the conventional group and 61.3±15.1 SD years for the 3D group with an 80% male population, in both groups. Acute PVI was achieved in all 20 patients. A decrease of both procedure time 86.8±16.1 SD in the control group Vs. 78.4±15.32 SD in the 3D group, and left sided dwelling time 69.7±14.31 SD in the control group Vs. 63.9±13.96 SD in the 3D group, although this trend did not reach statistical significance, while radiation time and cryo application time remained similar. Conclusions 3D imaging integration is feasible and safe and allows for an exact PV anatomy depiction on fluoroscopy. The assistance workflow might help increase AF cryoablation efficiency and safety (lower left sided dwelling time). Further research is needed to evaluate the incremental value of 3D imaging to assist fluoroscopy-based cryoballoon ablation. This could also impact long-term results since 3D Imaging assistance could reduce the likeability of missing intermediate PVs during AF ablation procedures.

Diagnostic and treatment workflow of the otorhinolaryngologists and dentists in patients suffering from the Syndrome of Obstructive sleep apnea and snoring

Diagnostic and treatment workflow of the otorhinolaryngologists and dentists in patients suffering from the Syndrome of Obstructive sleep apnea and snoring

Development, implementation, and feasibility of site-specific hepatitis C virus treatment workflows for treating vulnerable, high-risk populations: protocol of the Erase Hep C study — a prospective single-arm intervention trial

BackgroundHepatitis C virus (HCV) is the leading indication for liver transplantation and liver-related mortality. The development of direct-acting antivirals (DAA) and a simplified treatment algorithm with a > 97% cure rate should make global elimination of HCV an achievable goal. Yet, vulnerable populations with high rates of HCV still have limited access to treatment. By designing locally contextualized site-specific HCV treatment workflows, we aim to cure HCV in vulnerable, high-risk populations, including people experiencing homelessness (PEH) and people who inject drugs (PWID), in Austin, TX, USA.MethodsOur implementation science study will utilize a qualitative and design thinking approach to characterize patient and systemic barriers and facilitators to HCV treatment in vulnerable, high-risk populations seeking care across seven diverse primary care clinics serving PEHs and PWIDs. Qualitative interviews guided by the Practical, Robust Implementation and Sustainability Model (PRISM) framework will identify barriers and facilitators by leveraging knowledge and experience from both clinic staff and patients. Data synthesized using thematic analysis and design thinking will feed into workshops with clinic stakeholders for idea generation to design site-specific HCV treatment workflows. Providers will be trained on the use of a simplified HCV treatment algorithm with DAAs and clinic staff on the new site-specific HCV treatment workflows. These workflows will be implemented by the seven diverse primary care clinics serving vulnerable, high-risk populations. Implementation and clinical outcomes will be measured using data collected through interviews with staff as well as through medical chart review.DiscussionOur study provides a model of how to contextualize and implement site-specific HCV treatment workflows targeting vulnerable, high-risk populations in other geographic locations. This model can be adopted for future implementation research programs aiming to develop and implement site-specific treatment workflows for vulnerable, high-risk populations and in primary care clinical settings for other disease states beyond just HCV.Trial registrationRegistered on ClinicalTrials.gov on July, 14, 2022. Identifier: NCT05460130.

PD-0313 Time analysis of CBCT-guided online adaptive radiotherapy in Prostate cancer treatment workflow

PD-0313 Time analysis of CBCT-guided online adaptive radiotherapy in Prostate cancer treatment workflow

The New Role of the Dental Assistant and Nurse in the Age of Advanced Artificial Intelligence in Telehealth Orthodontic Care with Dental Monitoring: Preliminary Report

This paper explores the impact of Artificial Intelligence (AI) on the role of dental assistants and nurses in orthodontic practices, as there is a gap in understanding the currently evolving impact on orthodontic treatment workflows. The introduction of AI-language models such as ChatGPT 4 is changing patient-office communication and transforming the role of orthodontic nurses. Teledentistry is now heavily reliant on AI implementation in orthodontics. This paper presents the proof of a novel concept: an AI-powered orthodontic workflow that provides new responsibilities for an orthodontic nurse. It also provides a report of an assessment of such a workflow in an orthodontic practice that uses an AI solution called Dental Monitoring over a period of three years. The paper evaluates the benefits and drawbacks of daily automated assessments of orthodontic treatment progress, the impact of AI on personalized care, and the new role of a dental assistant. The paper concludes that AI will improve dental practice through more precise and personalized treatment, bringing new roles and responsibilities for trained medical professionals but raising new ethical and legal issues for dental practices.

Reproducibility of surface-based deep inspiration breath-hold technique for lung stereotactic body radiotherapy on a closed-bore gantry linac.

Tumor motion and delivery efficiency are two main challenges of lung stereotactic body radiotherapy (SBRT). The present work implemented the deep inspiration breath hold technique (DIBH) with surface guided radiation therapy (SGRT) on closed-bore linacs and investigated the correlation between SGRT data and internal target position. Thirteen lung SBRT patients treated in DIBH using a closed-bore gantry linac and a ring-mounted SGRT system were retrospectively analysed. Visual coaching was used to achieve DIBH with a±1mm threshold window in the anterior-posterior direction. Three kV-CBCTs were added to the treatment workflow and examined offline to verify intra-fraction tumor position. Surface-based DIBH was analysed using SGRT treatment reports and an in-house python script. Data from 73 treatment sessions and 175kV-CBCTs were studied. Correlations between target and surface positions were studied with Linear Mixed Models. Median intra-fraction tumor motion was 0.8mm (range: 0.7-1.3 mm) in the anterior-posterior direction, 1.2mm (range: 1-1.7 mm) in the superior-inferior direction, and 1mm (range: 0.7-1.1 mm) in the left-right direction, with rotations of <1° (range: 0.6°-1.1°) degree in all three directions. Planned target volumes and healthy lung volumes receiving 12.5Gy and 13.5Gy were reduced on average by 67% and 54%, respectively. Lung SBRT in DIBH with the ring-mounted SGRT system proved reproducible. The surface monitoring provided by SGRT was found to be a reliable surrogate for internal target motion. Moreover, the implementation of DIBH technique helped reduce target volumes and lung doses.

End-to-End QA with Polymer Gel Dosimeter for Photon Beam Radiation Therapy.

With the complexity and high demands on quality assurance (QA) of photon beam radiation therapy, end-to-end (E2E) QA is necessary to validate the entire treatment workflow from pre-treatment imaging to beam delivery. A polymer gel dosimeter is a promising tool for three-dimensional (3D) dose distribution measurement. The purpose of this study is to design a fast "one delivery" polymethyl methacrylate (PMMA) phantom with a polymer gel dosimeter for the E2E QA test of the photon beam. The one delivery phantom is composed of ten calibration cuvettes for the calibration curve measurement, two 10 cm gel dosimeter inserts for the dose distribution measurement, and three 5.5 cm gel dosimeters for the square field measurement. The one delivery phantom holder is comparable in size and shape to that of a human thorax and abdomen. In addition, an anthropomorphic head phantom was employed to measure the patient-specific dose distribution of a VMAT plan. The E2E dosimetry was verified by undertaking the whole RT procedure (immobilization, CT simulation, treatment planning, phantom set-up, imaged-guided registration, and beam delivery). The calibration curve, field size, and patient-specific dose were measured with a polymer gel dosimeter. The positioning error can be mitigated with the one-delivery PMMA phantom holder. The delivered dose measured with a polymer gel dosimeter was compared with the planned dose. The gamma passing rate is 86.64% with the MAGAT-f gel dosimeter. The results ascertain the feasibility of the one delivery phantom with a polymer gel dosimeter for a photon beam in E2E QA. The QA time can be reduced with the designed one delivery phantom.

Technical note: First implementation of a one-stop solution of radiotherapy with full-workflow automation based on CT-linac combination.

Radiotherapy initiation is a laborious and time-consuming process that involves multiple steps and units. Workflow automation is in demand to improve the work efficiency and patient experience. The purposes of this study are to describe the technical characteristics and clinical performance of an AI-powered one-stop radiotherapy workflow for initial treatment based on CT-linac combination, and provide insight into the behavior of full-workflow automation in radiotherapy. Based on a CT-integrated linear accelerator and AI model implementation, the so-called "All-in-One" workflow incorporates routine procedures from simulation, autosegmentation, autoplanning, image guidance, beam delivery, and in vivo quality assurance (QA) into one scheme, while the patient is on the treatment couch. Clinical outcomes of the new workflow were evaluated for 10 enrolled patients with rectal cancer. For the enrolled patients, manual modifications of the autosegmented target volumes were necessary. The Dice similarity coefficient and 95% Hausdorff distance before and after the modifications were 0.892±0.061 and 18.2±13.0mm, respectively. The autosegmented normal tissues and automatic plans were clinically acceptable without any modifications or reoptimization. The pretreatment IGRT corrections were within 2mm in all directions, and the EPID-based in vivo QA showed γ passing rate of above 97% (3%/3mm/10% threshold) at all the checkpoints, better than the results of rectal patients who followed a routine workflow. The duration of the whole process was 23.2±3.5 minutes for the enrolled patients, depending mostly on the time required for manual modification and plan evaluation. The All-in-One workflow enables full-process automation of radiotherapy via seamless procedure integration. Compared to the routine workflow, the one-stop solution shortens the time scale it takes to ready the first treatment from days to minutes, significantly improving the patient experience and the workflow efficiency, and it also shows potential to facilitate clinical application of online adaptive replanning.

Initiating a Magnetic Resonance-Guided Focused Ultrasound Program: Comprehensive Workflow and Lessons Learned from the Initial 116 Cases

Introduction: Magnetic resonance-guided focused ultrasound (MRgFUS) represents an incisionless treatment option for essential or parkinsonian tremor. The incisionless nature of this procedure has garnered interest from both patients and providers. As such, an increasing number of centers are initiating new MRgFUS programs, necessitating development of unique workflows to optimize patient care and safety. Herein, we describe establishment of a multi-disciplinary team, workflow processes, and outcomes for a new MRgFUS program. Methods: This is a single-academic center retrospective review of 116 consecutive patients treated for hand tremor between 2020 and 2022. MRgFUS team members, treatment workflow, and treatment logistics were reviewed and categorized. Tremor severity and adverse events were evaluated at baseline, 3, 6, and 12 months post-MRgFUS with the Clinical Rating Scale for Tremor Part B (CRST-B). Trends in outcome and treatment parameters over time were assessed. Workflow and technical modifications were noted. Results: The procedure, workflow, and team members remained consistent throughout all treatments. Technique modifications were attempted to reduce adverse events. A significant reduction in CRST-B score was achieved at 3 months (84.5%), 6 months (79.8%), and 12 months (72.2%) post-procedure (p < 0.0001). The most common post-procedure adverse events in the acute period (<1 day) were gait imbalance (61.1%), fatigue and/or lethargy (25.0%), dysarthria (23.2%), headache (20.4%), and lip/hand paresthesia (13.9%). By 12 months, the majority of adverse events had resolved with a residual 17.8% reporting gait imbalance, 2.2% dysarthria, and 8.9% lip/hand paresthesia. No significant trends in treatment parameters were found. Conclusions: We demonstrate the feasibility of establishing an MRgFUS program with a relatively rapid increase in evaluation and treatment of patients while maintaining high standards of safety and quality. While efficacious and durable, adverse events occur and can be permanent in MRgFUS.

Delivering acute stroke care in a middle-income country. The Mexican model: "ResISSSTE Cerebro".

Founded in 2019, the "ResISSSTE Cerebro" program is the first and only stroke network within the Mexican public health system. One advanced stroke center (ASC) and seven essential stroke centers (ESC) provide acute stroke (AS) care through a modified hub-and-spoke model. This study describes the workflow, metrics, and outcomes in AS obtained during the program's third year of operation. Participants were adult beneficiaries of the ISSSTE health system in Mexico City with acute focal neurological deficit within 24 h of symptom onset. Initial evaluation could occur at any facility, but the stroke team at the ASC took all decisions regarding treatment and transfers of patients. Registered variables included demographics, stroke risk factors, AS treatment workflow time points, and clinical outcome measures. We analyzed data from 236 patients, 104 (44.3%) men with a median age of 71 years. Sixty percent of the patients were initially evaluated at the ESC, and 122 (85.9%) were transferred to the ASC. The median transfer time was 123 min. The most common risk factor was hypertension (73.6%). Stroke subtypes were ischemic (86.0%) and hemorrhagic (14.0%). Median times for onset-to-door, door-to-imaging, door-to-needle, and door-to-groin were: 135.5, 37.0, 76.0, and 151.5 min, respectively. The rate of intravenous thrombolysis was 35%. Large vessel occlusion was present in 63 patients, from whom 44% received endovascular therapy; 71.4% achieved early clinical improvement (median NIHSS reduction of 11 points). Treatment-associated morbimortality was 3.4%. With the implementation of a modified hub-and-spoke model, this study shows that delivery of AS care in low- and middle-income countries is feasible and achieves good clinical outcomes.

Implementation of superficial radiation therapy (SRT) using SRT-100 Vision™ for non-melanoma skin cancer in a Radiation Oncology clinic.

This article describes our experience in implementation of superficial radiation therapy (SRT) using SRT-100 Vision™ for non-melanoma skin cancer. Following the American Association of Physicists in Medicine Task Group-61 protocol, absolute output (absorbed dose to water at surface (cGy/min)) was measured for three energies (50, 70, and 100kV) and for six applicators (1.5-5.0cm in diameter). Percent depth dose (PDD) and profiles were also measured. Timer testing and ultrasound testing were performed. A treatment time calculation worksheet was created. Quality assurance (QA) of SRT-100 Vision was implemented. After treatment workflow for our clinic was developed, end-to-end (E2E) testing was performed using a Rando phantom. Considerations for treatment using SRT-100 Vision were made. Absolute output (cGy/min) decreases as energy increases and applicator size decreases. Due to scatter from the applicator, PDD at depths ≤5mm does not follow conventional trends but PDD at depths ≥15mm increases with increasing applicator size. Profiles for the 5cm applicator do not have strong dependence on depth except profiles at 5mm for 50kV. Timer/end errors are negligible for all three energies. Ultrasound images confirm allowed field of view and depth as well as no image artifacts and spatial integrity. Daily, monthly and annual QA of SRT-100 Vision implemented in our clinic is listed in a table format. E2E testing results (<1%) demonstrate the functionality and performance of our treatment workflow. Our considerations for SRT treatment include patient, applicator size and energy selections, patient setup, and shields. This article is expected to serve as guidance for Radiation Oncology and/or Dermatology clinics aspiring to initiate an SRT program in their clinics.

A Hybrid Embedded Discrete Fracture Model and Dual-Porosity, Dual-Permeability Workflow for Hierarchical Treatment of Fractures in Practical Field Studies

Summary Natural fracture systems comprise numerous small features and relatively few large ones. At field scale, it is impractical to treat all fractures explicitly. We represent the largest fractures using an embedded discrete fracture model (EDFM) and account for smaller ones using a dual-porosity, dual-permeability (DPDK) idealized representation of the fracture network. The hybrid EDFM + DPDK approach uses consistent discretization schemes and efficiently simulates realistic field cases. Further speedup can be obtained using aggregation-based upscaling. Capabilities to visualize and post-process simulation results facilitate understanding for effective management of fractured reservoirs. The proposed approach embeds large discrete fractures as EDFM within a DPDK grid (which contains both matrix and idealized fracture continua for smaller fractures) and captures all connections among the triple media. In contrast with existing EDFM formulations, we account for discrete fracture spacing within each matrix cell via a new matrix-fracture transfer term and use consistent assumptions for classical EDFM and DPDK calculations. In addition, the workflow enables coarse EDFM representations using flow-based cell-aggregation upscaling for computational efficiency. Using a synthetic case, we show that the proposed EDFM + DPDK approach provides a close match of simulation results from a reference model that represents all fractures explicitly, while providing runtime speedup. It is also more accurate than previous standard EDFM and DPDK models. We demonstrate that the matrix-fracture transfer function agrees with flow-based upscaling of high-resolution fracture models. Next, the automated workflow is applied to a waterflooding study for a giant carbonate reservoir, with an ensemble of stochastic fracture realizations. The overall workflow provides the computational efficiency needed for performance forecasts in practical field studies, and the 3D visualization allows for the derivation of insights into recovery mechanisms. Finally, we apply a finite-volume tracer-based flux post-processing scheme on simulation results to analyze production allocation and sweep for understanding expected waterflood performance.

Same-day adaptive palliative radiotherapy without prior CT simulation: Early outcomes in the FAST-METS study

Background and PurposeStandard palliative radiotherapy workflows involve waiting times or multiple clinic visits. We developed and implemented a rapid palliative workflow using diagnostic imaging (dCT) for pre-planning, with subsequent on-couch target and plan adaptation based on a synthetic computed tomography (CT) obtained from cone-beam CT imaging (CBCT). Materials and methodsPatients with painful bone metastases and recent diagnostic imaging were eligible for inclusion in this prospective, ethics-approved study. The workflow consisted of 1) telephone consultation with a radiation oncologist (RO); 2) pre-planning on the dCT using planning templates and mostly intensity-modulated radiotherapy; 3) RO consultation on the day of treatment; 4) CBCT scan with on-couch adaptation of the target and treatment plan; 5) delivery of either scheduled or adapted treatment plan. Primary outcomes were dosimetric data and treatment times; secondary outcome was patient satisfaction. Results47 patients were enrolled between December 2021 and October 2022. In all treatments, adapted treatment plans were chosen due to significant improvements in target coverage (PTV/CTV V95%, p-value < 0.005) compared to the original treatment plan calculated on daily anatomy. Most patients were satisfied with the workflow. The average treatment time, including consultation and on-couch adaptive treatment, was 85 minutes. On-couch adaptation took on average 30 min. but was longer in cases where the automated deformable image registration failed to correctly propagate the targets. ConclusionA fast treatment workflow for patients referred for painful bone metastases was implemented successfully using online adaptive radiotherapy, without a dedicated CT simulation. Patients were generally satisfied with the palliative radiotherapy workflow.

MR-linac daily semi-automated end-to-end quality control verification.

Adaptive radiation therapy (ART) on the integrated Elekta Unity magnetic resonance (MR)-linac requires routine quality assurance to verify delivery accuracy and system data transfer. In this work, our objective was to develop and validate a novel automated end-to-end test suite that verifies data transfer between multiple software platforms and quantifies the performance of multiple machine subcomponents critical to the ART process. We designed and implemented a software tool to quantify the MR and megavoltage (MV) isocenter coincidence, treatment couch positioning consistency, isocenter shift accuracy for the adapted plan as well as the MLC and jaw position accuracy following the beam aperture adaptation. Our tool employs a reference treatment plan with a simulated isocenter shift generated on an MR image of a readily available phantom with MR and MV visible fiducials. Execution of the test occurs within the standard adapt-to-position (ATP) clinical workflow with MV images collected of the delivered treatment fields. Using descriptive statistics, we quantified uncertainty in couch positioning, isocentre shift as well as the jaw and MLC positions of the adapted fields. We also executed sensitivity measurements to evaluate the detection algorithm's performance. We report the results of 301 daily testing instances. We demonstrated consistent tracking of the MR-to-MV alignment with respect to the established value and to detect small changes on the order of 0.2mm following machine service events. We found couch position consistency relative to the test baseline value was within 95% CI [-0.31, 0.26mm]. For phantom shifts that form the basis for the plan adaptation, we found agreement between MV-image-detected phantom shift and online image registration, within±1.5mm in all directions with a 95% CI difference of [-1.29, 0.79mm]. For beam aperture adaptation accuracy, we found differences between the planned and detected jaw positions had a mean value of 0.27mm and 95% CI of [-0.29, 0.82mm] and -0.17mm and 95% CI of [-0.37, 0.05mm] for the MLC positions. Automated fiducial detected accuracy was within 0.08±0.20mm of manual localization. Introduced jaw and MLC position errors (1-10mm) were detected within 0.55mm (within 1mm for 15/256 instances for the jaws). Phantom shifts (1.3 or 5mm in each cardinal direction) from a reference position were detected within 0.26mm. We have demonstrated the accuracy and sensitivity of a daily end-to-end test suite capable of detecting errors in multiple machine subcomponents including system data transfer. Our test suite evaluates the entire treatment workflow and has captured system communication issues prior to patient treatment. With automated processing and the use of a standard vendor-provided phantom, it is possible to expand to other Unity sites.

Synthetic cranial MRI from 3D optical surface scans using deep learning for radiation therapy treatment planning

BackgroundOptical scanning technologies are increasingly being utilised to supplement treatment workflows in radiation oncology, such as surface-guided radiotherapy or 3D printing custom bolus. One limitation of optical scanning devices is the absence of internal anatomical information of the patient being scanned. As a result, conventional radiation therapy treatment planning using this imaging modality is not feasible. Deep learning is useful for automating various manual tasks in radiation oncology, most notably, organ segmentation and treatment planning. Deep learning models have also been used to transform MRI datasets into synthetic CT datasets, facilitating the development of MRI-only radiation therapy planning.AimsTo train a pix2pix generative adversarial network to transform 3D optical scan data into estimated MRI datasets for a given patient to provide additional anatomical data for a select few radiation therapy treatment sites. The proposed network may provide useful anatomical information for treatment planning of surface mould brachytherapy, total body irradiation, and total skin electron therapy, for example, without delivering any imaging dose.MethodsA 2D pix2pix GAN was trained on 15,000 axial MRI slices of healthy adult brains paired with corresponding external mask slices. The model was validated on a further 5000 previously unseen external mask slices. The predictions were compared with the “ground-truth” MRI slices using the multi-scale structural similarity index (MSSI) metric. A certified neuro-radiologist was subsequently consulted to provide an independent review of the model’s performance in terms of anatomical accuracy and consistency. The network was then applied to a 3D photogrammetry scan of a test subject to demonstrate the feasibility of this novel technique.ResultsThe trained pix2pix network predicted MRI slices with a mean MSSI of 0.831 ± 0.057 for the 5000 validation images indicating that it is possible to estimate a significant proportion of a patient’s gross cranial anatomy from a patient’s exterior contour. When independently reviewed by a certified neuro-radiologist, the model’s performance was described as “quite amazing, but there are limitations in the regions where there is wide variation within the normal population.” When the trained network was applied to a 3D model of a human subject acquired using optical photogrammetry, the network could estimate the corresponding MRI volume for that subject with good qualitative accuracy. However, a ground-truth MRI baseline was not available for quantitative comparison.ConclusionsA deep learning model was developed, to transform 3D optical scan data of a patient into an estimated MRI volume, potentially increasing the usefulness of optical scanning in radiation therapy planning. This work has demonstrated that much of the human cranial anatomy can be predicted from the external shape of the head and may provide an additional source of valuable imaging data. Further research is required to investigate the feasibility of this approach for use in a clinical setting and further improve the model’s accuracy.

Operations research contribution to totally automated radiotherapy treatment planning: A noncoplanar beam angle and fluence map optimization engine based on optimization models and algorithms

The planning of radiotherapy treatments is based on the use of mathematical optimization models and algorithms. A treatment plan will correspond to an admissible solution to a problem that is defined by the medical prescription. The medical prescription defines the constraints that have to be satisfied, and that are patient dependent. To find a treatment plan complying with all the defined constraints, an objective function is built, having a set of parameters that can be tuned. In the clinical practice, the objective function parameters are tuned through a trial-and-error procedure. One common way of defining this objective function is to consider as parameters weights that are related with the importance of the corresponding structures of interest (volumes to treat and organs to spare), as well as upper and lower bounds that are related with the constraints defined by the medical prescription. Some treatment options, like the set of irradiation directions (beam angles), are usually defined beforehand by the planner, considering previous experiences with similar cases. This trial-and-error process is lengthy, since it can take up to several hours to calculate an admissible treatment plan for a single patient. There have been some research efforts to automate the treatment planning procedure, releasing the planner for other important tasks in the radiotherapy treatment workflow and guaranteeing the consistent calculation of high-quality plans. In this work derivative-free optimization algorithms are integrated with fuzzy inference systems that automatically tune the objective function parameters so that an admissible solution is found. This fully automated approach was tested and assessed considering six head-and-neck cancer cases already treated at the Portuguese Institute of Oncology at Coimbra (IPOC). For the clinical cases tested, comparisons between different treatment plans clearly favor the proposed approach. For a similar tumor coverage, it was possible to improve the sparing of the spinal cord, brainstem and parotids. Automating radiotherapy treatment planning can contribute to improved treatment plans in a consistent way.