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Background/Aim. In the past two decades, we have witnessed the emergence of new radiation therapy techniques, radiotherapy treatment planning system (TPS) with calculating algorithms for the dosage calculation in a patient, units for multislice computed tomography (CT) and image-guided treatment delivery. The aim of the study was investigating the significant difference in dosimetric calculation of radiotherapy TPS in relation to the values obtained by measuring on the linear accelerator (LINAC), and the accuracy of dosimetric calculation between calculating algorithms Analytical Anisotropic Algorithm (AAA) and Acuros XB in various tissues and photon beam energies. Methods. For End-to-End test we used the hetero-geneous phantom CIRS Thorax002LFC, which anatomically represents human torso with a set of inserts known as relative electron densities (RED) for obtaining a CT calibration curve, comparable to the ?reference? CIRS 062M phantom. For the AAA and Acuros XB algorithms and for 6 MV and 16 MV photon beams in the TPS Varian Eclipse 13.6, four 3D conformal (3DCRT), and one intensity modulated (IMRT) and volumetric modulated arc (VMAT) radiotherapy plans were made. Measurements of the absolute dose in Thorax phantom, by PTW-Semiflex ionization chamber, were carried out on three Varian-DHX LINACs. Results. The difference between ?reference? and measured CT conversion curves in the bone area was 3%. For 476 phantom measurements, the difference between measured and TPS calculated dose of 3?6%, was found in 30 (6.3%) cases. According to regression analysis, the standardized Beta coefficient for relative errors, 6 MV vs. 16 MV, was 0.337 (33.7%, p < 0.001). Mean relative errors for AAA and Acuros XB, using Mann-Whitney test, for bones were 1.56% and 2.64%, respectively (p = 0.004). Conclusion. End-to-End test on Thorax002LFC phantom proved the accuracy of TPS dose calculation in relation to the one delivered to a patient by LINAC. There was a significant difference for photon energies relative errors (higher values are obtained for 16 MV vs. 6 MV). A statistically significant minor relative error in AAA vs. Acuros XB was found for the bone.

PURPOSE Access to knowledge-based treatment plan quality control has been hindered by the complexity of developing models and integration with different treatment planning systems (TPS). Online Real-time Benchmarking Information Technology for RadioTherapy (ORBIT-RT) provides a free, web-based platform for knowledge-based dose estimation that can be used by clinicians worldwide to benchmark the quality of their radiotherapy plans. MATERIALS AND METHODS The ORBIT-RT platform was developed to satisfy four primary design criteria: web-based access, TPS independence, Health Insurance Portability and Accountability Act compliance, and autonomous operation. ORBIT-RT uses a cloud-based server to automatically anonymize a user's Digital Imaging and Communications in Medicine for RadioTherapy (DICOM-RT) file before upload and processing of the case. From there, ORBIT-RT uses established knowledge-based dose-volume histogram (DVH) estimation methods to autonomously create DVH estimations for the uploaded DICOM-RT. ORBIT-RT performance was evaluated with an independent validation set of 45 volumetric modulated arc therapy prostate plans with two key metrics: (i) accuracy of the DVH estimations, as quantified by their error, DVHclinical − DVHprediction and (ii) time to process and display the DVH estimations on the ORBIT-RT platform. RESULTS ORBIT-RT organ DVH predictions show < 1% bias and 3% error uncertainty at doses > 80% of prescription for the prostate validation set. The ORBIT-RT extensions require 3.0 seconds per organ to analyze. The DICOM upload, data transfer, and DVH output display extend the entire system workflow to 2.5-3 minutes. CONCLUSION ORBIT-RT demonstrated fast and fully autonomous knowledge-based feedback on a web-based platform that takes only anonymized DICOM-RT as input. The ORBIT-RT system can be used for real-time quality control feedback that provides users with objective comparisons for final plan DVHs.

Introduction: Limited evidence exists showing the benefit of magnetic resonance (MR)-only radiotherapy treatment planning for anal and rectal cancers. This study aims to assess the impact of MR-only planning on target volumes (TVs) and treatment plan doses to organs at risks (OARs) for anal and rectal cancers versus a computed tomography (CT)-only pathway. Materials and methods: Forty-six patients (29 rectum and 17 anus) undergoing preoperative or radical external beam radiotherapy received CT and T2 MR simulation. TV and OARs were delineated on CT and MR, and volumetric arc therapy treatment plans were optimized independently (53.2 Gy/28 fractions for anus, 45 Gy/25 fractions for rectum). Further treatment plans assessed gross tumor volume (GTV) dose escalation. Differences in TV volumes and OAR doses, in terms of Vx Gy (organ volume (%) receiving x dose (Gy)), were assessed. Results: MR GTV and primary planning TV (PTV) volumes systematically reduced by 13 cc and 98 cc (anus) and 44 cc and 109 cc (rectum) respectively compared to CT volumes. Statistically significant OAR dose reductions versus CT were found for bladder and uterus (rectum) and bladder, penile bulb, and genitalia (anus). With GTV boosting, statistically significant dose reductions were found for sigmoid, small bowel, vagina, and penile bulb (rectum) and vagina (anus). Conclusion: Our findings provide evidence that the introduction of MR (whether through MR-only or CT-MR pathways) to radiotherapy treatment planning for anal and rectal cancers has the potential to improve treatments. MR-related OAR dose reductions may translate into less treatment-related toxicity for patients or greater ability to dose escalate.

Dual-energy computed tomography (CT) can be used in radiotherapy treatment planning for the calculation of absorbed dose distributions. The aim of this work is to evaluate whether there is room for improvement in the accuracy of the Monoenergetic Plus algorithm by Siemens Healthineers. A Siemens SOMATOM Force scanner was used to scan a cylindrical polymethyl methacrylate phantom with four rod-inserts made of different materials. Images were reconstructed using ADMIRE and processed with Monoenergetic Plus. The resulting CT numbers were compared with tabulated values and values simulated by the proof-of-a-concept algorithm DIRA developed by the authors. Both the Monoenergetic Plus and DIRA algorithms performed well; the accuracy of attenuation coefficients was better than about ±1% at the energy of 70 keV. Compared with DIRA, the worse performance of Monoenergetic Plus was caused by its (i) two-material decomposition to iodine and water and (ii) imperfect suppression of the beam hardening artifact in ADMIRE. Funding: CancerfondenSwedish Cancer Society [CAN 2017/1029, CAN 2018/622]; Swedish state government [LiO-602731]; Swedish county councils, the ALF-agreement [LiO-602731]; Patientsakerhetsforskning Region Ostergotland [LiO-724181]; VetenskapsradetSwedish Research Council [VR-NT 2016-05033]

Introduction. Medical physicists planning radiation treatment are increasingly confronted with situations that require special attention. Undoubtedly, one such situation is the postoperative irradiation of a patient with breast cancer in which there is a prosthesis or an expander. In recent years, expanders have appeared in this location, which, due to the density of the device’s valve makes it difficult to prepare an acceptable treatment plan. The study aims to present treatment planning in these situation in various Polish cancer centres and to compare overall patient preparation for the treatment. Material and methods. A questionnaire was prepared and sent to more than 20 radiotherapy departments, which included basic questions regarding the preparation of an irradiation plan for patients treated for breast cancer after a subcutaneous mastectomy with immediate reconstruction with a prosthesis or expander. The survey encompassed eight radiotherapy departments. Results. Not all radiotherapy departments require a manufacturer’s certificate, which shows that the manufacturer does not prohibit the use of a prosthesis/expander during treatment with ionizing radiation. The X 6MV photons and the supine position, total and fraction doses: from 40 to 60 Gy and from 2 to 2.67 Gy, respectively, are the most commonly used. The way of defining them also depends on the oncological centre. The most commonly used irradiation technique is VMAT. Conclusion. The conclusion from the questionnaire – no standardisation of treatment planning – should encourage the community, at least medical physicists, to develop rules of conduct in this case. Irradiation techniques are mainly dynamic ones. The expander or prosthesis does not significantly affect the dose distributions.

Highlights • Deep learning accelerates 4D-MRI recon for online adaptive MR-guided radiotherapy. • First reconstruction of high resolution whole thorax 4D-MRI for 16 phases in 28 s. • First use of dCNNs for midposition reconstruction from undersampled 4D-MRI in 28 s. • Excellent agreement between deep learning-based tumour midposition and reference., Background and Purpose 4D and midposition MRI could inform plan adaptation in lung and abdominal MR-guided radiotherapy. We present deep learning-based solutions to overcome long 4D-MRI reconstruction times while maintaining high image quality and short scan times. Methods Two 3D U-net deep convolutional neural networks were trained to accelerate the 4D joint MoCo-HDTV reconstruction. For the first network, gridded and joint MoCo-HDTV-reconstructed 4D-MRI were used as input and target data, respectively, whereas the second network was trained to directly calculate the midposition image. For both networks, input and target data had dimensions of 256 × 256 voxels (2D) and 16 respiratory phases. Deep learning-based MRI were verified against joint MoCo-HDTV-reconstructed MRI using the structural similarity index (SSIM) and the naturalness image quality evaluator (NIQE). Moreover, two experienced observers contoured the gross tumour volume and scored the images in a blinded study. Results For 12 subjects, previously unseen by the networks, high-quality 4D and midposition MRI (1.25 × 1.25 × 3.3 mm3) were each reconstructed from gridded images in only 28 seconds per subject. Excellent agreement was found between deep-learning-based and joint MoCo-HDTV-reconstructed MRI (average SSIM ≥ 0.96, NIQE scores 7.94 and 5.66). Deep-learning-based 4D-MRI were clinically acceptable for target and organ-at-risk delineation. Tumour positions agreed within 0.7 mm on midposition images. Conclusion Our results suggest that the joint MoCo-HDTV and midposition algorithms can each be approximated by a deep convolutional neural network. This rapid reconstruction of 4D and midposition MRI facilitates online treatment adaptation in thoracic or abdominal MR-guided radiotherapy.

PURPOSE: Recently, it has been shown that automated treatment planning can be executed by direct fluence prediction from patient anatomy using convolutional neural networks. Proof of principle publications utilise a fixed dose prescription and fixed collimator (0°) and gantry angles. The goal of this work is to further develop these principles for the challenging lung cancer indication with variable dose prescriptions, collimator and gantry angles. First we investigate the impact of clinical applicable collimator angles and various input parameters. Then, the model is tested in a complete user independent planning workflow. METHODS: The dataset consists of 152 lung cancer patients, previously treated with IMRT. The patients are treated with either a left or a right beam setup and collimator angles and dose prescriptions adjusted to their tumour shape and stage. First we compare two CNNs with standard vs. personalised, clinical collimator angles. Next, four CNNs are trained with various combinations of CT and contour inputs. Finally, a complete user free treatment planning workflow is evaluated. RESULTS: The difference between the predicted and ground truth fluence maps for the fluence prediction CNN with all anatomical inputs in terms of the mean mean absolute error (MAE) is 4.17 × 10-4 for a fixed collimator angle and 5.46 × 10-4 for variable collimator angles. These differences vanish in terms of DVH metrics. Furthermore, the impact of anatomical inputs is small. The mean MAE is 5.88 × 10-4 if no anatomical information is given to the network. The DVH differences increase when a total user free planning workflow is examined. CONCLUSIONS: Fluence prediction with personalised collimator angles performs as good as fluence prediction with a standard collimator angle of zero degrees. The impact of anatomical inputs is small. The combination of a dose prediction and fluence prediction CNN deteriorates the fluence predictions. More investigation is required. ispartof: PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS vol:99 pages:44-54 ispartof: location:Italy status: published

Aim:The patient experience of radiotherapy magnetic resonance (MR) simulation is unknown. This study aims to evaluate the patient experience of MR simulation in comparison to computed tomography (CT) simulation, identifying the quality of patient experience and pathway changes which could improve patient experience outcomes.Materials and Methods:MR simulation was acquired for 46 anal and rectal cancer patients. Patient experience questionnaires were provided directly after MR simulation. Questionnaire responses were assessed after 33 patients (cohort one). Changes to the scanning pathway were identified and implemented. The impact of changes was assessed by cohort two (13 patients).Results:Response rates were 85% (cohort one) and 54% (cohort two). 75% of cohort one respondents found the magnetic resonance imaging (MRI) experience to be better or similar to their CT experience. Implemented changes included routine use of blankets, earplugs and headphones, music and feet-first positioning and further MRI protocol optimisation. All cohort two respondents found the MRI experience to be better or similar to the CT experience.Findings:MR simulation can be a comfortable and positive experience that is comparable to that of standard radiotherapy CT simulation. Special attention is required due to the fundamental differences between CT and MRI scanning.

Purpose To evaluate the accuracy of surface‐guided radiotherapy (SGRT) in cranial patient setup by direct comparison between optical surface imaging (OSI) and cone‐beam computed tomography (CBCT), before applying SGRT‐only setup for conventional radiotherapy of brain and nasopharynx cancer. Methods and Materials Using CBCT as reference, SGRT setup accuracy was examined based on 269 patients (415 treatments) treated with frameless cranial stereotactic radiosurgery (SRS) during 2018‐2019. Patients were immobilized in customized head molds and open‐face masks and monitored using OSI during treatment. The facial skin area in planning CT was used as OSI region of interest (ROI) for automatic surface alignment and the skull was used as the landmark for automatic CBCT/CT registration. A 6 degrees of freedom (6DOF) couch was used. Immediately after CBCT setup, an OSI verification image was captured, recording the SGRT setup differences. These differences were analyzed in 6DOFs and as a function of isocenter positions away from the anterior surface to assess OSI‐ROI bias. The SGRT in‐room setup time was estimated and compared with CBCT and orthogonal 2D kilovoltage (2DkV) setups. Results The SGRT setup difference (magnitude) is found to be 1.0 ± 2.5 mm and 0.1˚±1.4˚ on average among 415 treatments and within 5 mm/3˚ with greater than 95% confidence level (P 5.0mm and 9 (2.2%) are >3.0˚. The setup differences show minor correlations (|r| < 0.45) between translational and rotational DOFs and a minor increasing trend (

Advancements in Radiation Oncology from conventional to 3D conformal radiotherapy treatment demands expertise in many steps of radiation planning, the horizon of radiologist is now expanded by many folds and made radiologist as a integral part of the Radiation Oncology Department. A critical aspect of radiotherapy treatment planning (RTP) is determining how to deliver the required radiation dosage to cancer cells while minimising the exposure to normal tissue for which the prerequisite is identification and accurate delineation of tumour volume as well as normal structure resulted in an increase in the therapeutic ratio by reducing complication associated with normal tissue and allowing for higher target dosage and better local control. In modern radiotherapy CT images are the standard set of imaging modality required for the radiotherapy planning along with it many other modalities like MRI, PET or DSA are used by superimposing on original CT images in order to contour or delineate the structures defined by International Commission on Radiation Units and Measurements in Reports 50, 62 and 71 (ICRU) for radiotherapy planning which comprise of Gross tumour volume, clinical target volume, planning target volume, irradiated volume, Internal target volume and the normal structures as Organ at risk. It is self-evident that the contribution of a radiologist with a thorough knowledge of the development of these new modalities is critical for optimising the potential of these novel modes of radiation treatment delivery.

The purpose of this work was to evaluate computed tomography simulators used in radiotherapy treatment planning in Serbia, Croatia, and Bosnia and Herzegovina. A survey of quality assurance programmes of 24 computed tomography simulators in 16 facilities was conducted. A dedicated CT-to-ED phantoms was scanned at 120 kV and 140 kV, to obtain CT-to-ED con version curves as well as CTDI vol. Thoracal phantoms were scanned in the standard and extended field of view to evaluate the dosimetric effect on treatment planning and delivery. The mean age of the measured scanners was 5.5 years. The mean water HU value was –6.5 (all scanners, all voltages) and air HU value was –997. Extended field of view computed tomography data differ from the standard field of view and differences between conversion curves have significant dosimetric impact. The CTDI data showed a large range of values between centers. Better quality assurance of computed tomography simulators in all countries is recommended. The CT-to-ED curve could be used as default at one voltage and per manufacturer. Extended field of view imaging can be used, but treatment planning should be avoided in the regions out of the standard field of view.

Aim:Studying the use of Aperture Shape Controller (ASC) and Convergence Mode (CM) in Eclipse (Varian Medical System) in terms of plan quality and complexity of volumetric modulated arc therapy (VMAT).Materials and methods:Forty VMAT plans were re-optimised for the prostate, prostate + lymph nodes, breast and head & neck patients retrospectively, changing the ASC settings (off, moderate, very high) and CM settings (off, on and extended).Results:Using ‘on’ or ‘extended’ CM increased plan quality in terms of planning target volume homogeneity and low-dose spread to the organs at risk (OAR). ‘Extended’ CM increased the optimisation time 4·3-fold compared to ‘on’, and deteriorated the plan quality in several simple planning cases. ‘Moderate’ ASC decreased plan complexity with minor effect on plan quality compared to ‘off’, but ‘very high’ ASC had larger adverse dosimetric effects. However, the ASC decreased the plan complexity only if the CM was turned ‘on’.Findings:Using ‘on’ CM increases the plan quality but using ‘extended’ CM is not recommended. The ‘moderate’ ASC decreased complexity without significant adverse effects on plan quality, and even ‘very high’ ASC may be used when plan simplicity is prioritised. However, if CM is not used, the ASC should also be turned off.

The musculoskeletal (MSK) system provides support, stability and movement to the body. Disorders to the MSK system cause pain and stiffness, and can debilitate anatomical regions, hinder movement, or result in disability. As such, they are among the leading cause of activity limitation and absence from work and result in a major medical burden and economic cost. Treatment and recommendations for diseases affecting the MSK system are very dependent on the type of disorder, the involvement of the affected soft tissues and bones, and the progression of the disease. In this context, medical imaging is crucial to localize a disorder, assess the stage of disease progression, support a diagnosis, or plan a treatment. For a comprehensive assessment and treatment planning of MSK pathologies, acquisition of both magnetic resonance imaging (MRI) and computed tomography (CT) is warranted, which is logistically complex and constitutes a high patient burden. This work discusses the use of synthetic CT (sCT), a deep learning-enabled CT-like image generated from MR images, as a CT surrogate. Synthetic CT has been thoroughly investigated, from the acquisition and processing of the original MRI data to its clinical application, with a focus on orthopaedic care. Synthetic CT has been found acceptable for bone visualization, simultaneously providing valuable information on soft tissues via the original MR acquisition. This paves the way to a purely MRI-based workflow with simplified logistics and radiation-free acquisition, and opens up new perspectives for diagnosis, treatment planning and disease understanding.

The musculoskeletal (MSK) system provides support, stability and movement to the body. Disorders to the MSK system cause pain and stiffness, and can debilitate anatomical regions, hinder movement, or result in disability. As such, they are among the leading cause of activity limitation and absence from work and result in a major medical burden and economic cost. Treatment and recommendations for diseases affecting the MSK system are very dependent on the type of disorder, the involvement of the affected soft tissues and bones, and the progression of the disease. In this context, medical imaging is crucial to localize a disorder, assess the stage of disease progression, support a diagnosis, or plan a treatment. For a comprehensive assessment and treatment planning of MSK pathologies, acquisition of both magnetic resonance imaging (MRI) and computed tomography (CT) is warranted, which is logistically complex and constitutes a high patient burden. This work discusses the use of synthetic CT (sCT), a deep learning-enabled CT-like image generated from MR images, as a CT surrogate. Synthetic CT has been thoroughly investigated, from the acquisition and processing of the original MRI data to its clinical application, with a focus on orthopaedic care. Synthetic CT has been found acceptable for bone visualization, simultaneously providing valuable information on soft tissues via the original MR acquisition. This paves the way to a purely MRI-based workflow with simplified logistics and radiation-free acquisition, and opens up new perspectives for diagnosis, treatment planning and disease understanding.

Purpose Treatment planning system (TPS) dose calculations have previously been shown to be sensitive to modeling errors, especially when treating with complex strategies like intensity‐modulated radiation therapy (IMRT). This work investigates the dosimetric impact of several dosimetric and nondosimetric beam modeling parameters, based on their distribution in the radiotherapy community, in two commercial TPSs in order to understand the realistic potential for dose deviations and their clinical effects. Methods and materials Beam models representing standard 120‐leaf Varian Clinac‐type machines were developed in Eclipse 13.5 (AAA algorithm) and RayStation 9A (v8.99, collapsed‐cone algorithm) based upon median values of dosimetric measurements from Imaging and Radiation Oncology Core (IROC) Houston site visit data and community beam modeling parameter survey data in order to represent a baseline linear accelerator. Five clinically acceptable treatment plans (three IMRT, two VMAT) were developed for the IROC head and neck phantom. Dose distributions for each plan were recalculated after individually modifying parameters of interest (e.g., MLC transmission, percent depth doses [PDDs], and output factors) according to the 2.5th to 97.5th percentiles of community survey and machine performance data to encompass the realistic extent of variance in the radiotherapy community. The resultant dose distributions were evaluated by examining relative changes in average dose for thermoluminescent dosimeter (TLD) locations across the two target volumes and organ at risk (OAR). Interplay was also examined for parameters generating changes in target dose greater than 1%. Results For Eclipse, dose calculations were sensitive to changes in the dosimetric leaf gap (DLG), which resulted in differences from −5% to +3% to the targets relative to the baseline beam model. Modifying the MLC transmission factor introduced differences up to ± 1%. For RayStation, parameters determining MLC behaviors likewise contributed substantially; the MLC offset introduced changes in dose from −4% to +7%, and the MLC transmission caused changes of −4% to +2%. Among the dosimetric qualities examined, changes in PDD implementation resulted in the most substantial changes, but these were only up to ±1%. Other dosimetric factors had

Purpose To assess the performance and optimize the MR image quality when using a custom-built flexible radiofrequency (RF) spine coil array fitted between the immobilization device and the patient for spine radiotherapy treatment planning. Methods A 32 channel flexible custom-designed receive-only coil array has been developed for spine radiotherapy simulation for a 3 T Philips MR scanner. Coil signal-to-noise performance and interactions with standard vendor hardware were assessed. In four volunteers, immobilization molds were created with a dummy version of the array within the mold, and subjects were scanned using the custom array in the mold. Phantoms and normal volunteers were scanned with both the custom spine coil array and the vendor's FDA-approved in-table posterior coil array to compare performance. Results The superior-inferior field of view for the custom spine array was ~30 cm encompassing at least 10 vertebrae. A noise correlation matrix showed at least 25 dB isolation between all coil elements. Signal-to-noise ratio (SNR) calculated on a phantom scan at the depth of the spinal cord was a factor of 3 higher with the form-fit spine array as compared to the vendor's posterior coil array. The body coil B1 transmit map was equivalent with and without the spine array in place demonstrating that the elements are decoupled from the body coil. Volunteer imaging showed improved SNR as compared to the vendor's posterior coil array. The custom array permitted a high degree of acceleration making possible the acquisition of isotropic high-resolution 1.1 × 1.1 × 1.1 mm3 three-dimensional data set over a 30-cm section of the spine in less than 5 min. Conclusion The custom-designed form-fitting flexible spine coil array provided enhanced SNR and increased acceleration compared to the vendor's posterior array. Future studies will assess MR-based spinal cord imaging with the custom coil in comparison to CT myelogram.

Introduction Radiotherapy treatment planning is a multi-criteria problem. Any optimization of the process produces a set of mathematically optimal solutions. These optimal plans are considered mathematically equal, but they differ in terms of the trade-offs involved. Since the various objectives are conflicting, the choice of the best plan for treatment is dependent on the preferences of the radiation oncologists or the medical physicists (decision makers). We defined a clinically relevant area on a prostate Pareto front which better represented clinical preferences and determined if there were differences among radiation oncologists and medical physicists. Methods and materials Pareto fronts of five localized prostate cancer patients were used to analyze and visualize the trade-off between the rectum sparing and the PTV under-dosage. Clinical preferences were evaluated with Clinical Grading Analysis by asking nine radiation oncologists and ten medical physicists to rate pairs of plans presented side by side. A choice of the optimal plan on the Pareto front was made by all decision makers. Results The plans in the central region of the Pareto front (1–4% PTV under-dosage) received the best evaluations. Radiation oncologists preferred the organ at risk (OAR) sparing region (2.5–4% PTV under-dosage) while medical physicists preferred better PTV coverage (1–2.5% PTV under-dosage). When the Pareto fronts were additionally presented to the decisions makers they systematically chose the plan in the trade-off region (0.5–1% PTV under-dosage). Conclusion We determined a specific region on the Pareto front preferred by the radiation oncologists and medical physicists and found a difference between them.

Introduction: The objective of this pilot study was to obtain preliminary data on the efficacy and feasibility of incorporating geriatric assessment (GA) into radiation oncology (RO) with regard to patient outcomes and treatment decisions. Materials and Methods: Feasibility was assessed via the percentage of patients able to complete certain aspects of the assessment on their own, or with the assistance of a carer before appointments, was recorded. Consultation times and referrals were also documented. All participants (n=30) underwent GA at baseline, before randomisation to the intervention/control arm and commencement of radiotherapy treatment planning procedures. The results of GA were relayed to the Radiation Oncologist (RO) for the intervention arm only. GA was repeated for each participant three months after the completion of radiotherapy. Results: There was some evidence of increasing dependence, at three month follow-up, in ADLs and IADLs, less mobility (TUG score), higher GDS scores and increased vulnerability. However, these were not statistically significant. All patients underwent their predefined radiotherapy treatment plan, without modification. A number of deficits on GA were identified that may be considered significant for older patients. Conclusion: The impact on decision making may reflect a lack of experience and familiarity with GA and how to interpret it, as well as an obvious gap in the literature as to how it affects radiotherapy patient outcomes.

Computed tomography (CT) plays key roles in radiotherapy treatment planning and PET attenuation correction (AC). Magnetic resonance (MR) imaging has better soft tissue contrast than CT and has no ionizing radiation but cannot directly provide information about photon interactions with tissue that is needed for radiation treatment planning and AC. Therefore, estimating synthetic CT (sCT) images from corresponding MR images and obviating CT scanning is of great interest, but can be particularly challenging in the abdomen owing to a range of tissue types and physiologic motion. For this purpose, inspired by deep learning, we design a novel generative adversarial network (GAN) model that organically combines ResNet, U-net, and auxiliary classifier-augmented GAN (RU-ACGAN for short). The significance of our effort is three-fold: 1) The combination of ResNet and U-net, instead of only the U-net which was commonly used in existing conditional GAN, is enlisted to constitute the generative network in RU-ACGAN. This has the potential to generate more accurate CT than existing methods. 2) Adding the classifier to the discriminant network makes the training process of the proposed model more stable, and thereby benefits the robustness of sCT estimation. 3) Owing to the delicate architecture, RU-ACGAN is capable of estimating superior sCT using only a limited quantity of training data. The experimental studies on ten subjects’ MR-CT pair images indicate that the proposed RU-ACGAN model can capture the potential, non-linear matching between the MR and CT images, and thus achieves the better performance for sCT estimation for the abdomen than many other existing methods.

Circular discs of diameter 5 mm were made from three indigenously developed optically stimulated luminescent (OSL) phosphors for medical dosimetry. Dosimetric characteristics of these discs were evaluated for their use in machine and patient-specific dosimetry in radiotherapy. Uncertainty in dosimetric measurements using these discs was also estimated, and combined standard uncertainty in measurement of absorbed dose was found to be 3.34%. Characterisation studies indicate that OSL discs are suitable for dosimetric application in radiotherapy. These discs were also used for patient-specific dosimetry in conventional and conformal radiotherapy treatments (five different cases) vis-à-vis ionisation chamber and Gafchromic EBT3 film. Doses measured by OSL discs were found comparable to ionisation chamber and Gafchromic EBT3 film measured values and radiotherapy treatment planning system (TPS) calculated dose values in all the cases. The variation between TPS calculated dose values and OSL discs measured dose values was found within the measurement uncertainty.

Purpose To demonstrate a specific skin dose limiting technique in radiotherapy treatment planning for esophageal cancer and carry out a comparative analysis combining with clinical cases. Material and methods Thirty patients with cervical and upper thoracic esophageal carcinoma previously treated in our institution were selected. A treatment plan had been finished previously according to the planning parameters directives from physician and delivered for each patient. In this study, we copied the previously delivered plans in radiotherapy treatment planning system and converted a low dose level (usually 5Gy) to a skin dose limiting structure (SDLS), then we set the objective functions of the SDLS in the Pinnacle Inverse Planning module and re‐optimize the plans to reduce the skin doses. Finally, we compared the dose distribution and other parameters of target volume and organs at risk (OARs) between the old plans and the new plans. Results There was no significant difference in most of OARs sparing. However, for all plans, the maximum dose to the SDLS decreased from 6145.90 ± 416.96 cGy to 5562.09 ± 616.69 cGy with maximum difference of 1361.30 cGy (P

Cervical cancer has a high incidence and mortality rate in low- and middle-income countries (LMICs) largely due to limited resources and insufficient staffing. Knowledge-based planning (KBP) could alleviate understaffing issues by streamlining the radiotherapy treatment planning process. Varian's KBP system (RapidPlan) was used to develop a model capable of producing volumetric modulated arc therapy (VMAT) plans for cervical cancer patients. Plan data from 46 patients previously treated at MD Anderson Cancer Center (MDACC) were used to create and train the model which was then applied to 32 patients excluded from the training process. Dose volume histogram (DVH) values for the planning target volume (PTV_High), bladder, rectum, and bowel were evaluated for the validation plans and found to have satisfied the required PTV coverage and organ-at-risk (OAR) dose constraints. The average value for PTV_High D95.0% was 48.0 Gy (sd = 3.0 Gy) for existing clinical plans and 48.4 Gy (sd = 2.6 Gy) for the validation plans. The mean dose for the bladder, rectum, and bowel was 39.8 Gy (sd = 3.9 Gy), 41.6 Gy (sd = 5.2 Gy), and 21.6 Gy (sd = 5.0 Gy) for existing clinical plans and 38.9 Gy (sd = 4.0 Gy), 40.3 Gy (sd = 4.8 Gy), and 21.5 Gy (sd = 4.6 Gy) for validation plans, respectively. A TOST test showed that the p values for the PTV_High D95.0% (p

Purpose: To compare the robustness of three dose-volume-histogram (DVH) prediction models for knowledge-based treatment planning (KBP) for radiation therapy.Methods: Three models proposed by Zhu et...

One of the primary treatment options for head and neck cancer is (chemo)radiation. Accurate delineation of the contour of the tumors is of great importance in the successful treatment of the tumor and in the prediction of patient outcomes. With this paper we take part in the HECKTOR 2021 challenge and we propose our methods for automatic tumor segmentation on PET and CT images of oropharyngeal cancer patients. To achieve this goal, we investigated different deep learning methods with the purpose of highlighting relevant image and modality related features, to refine the contour of the primary tumor. More specifically, we tested a Co-learning method [1] and a 3D Skip Spatial and Channel Squeeze and Excitation Multi-Scale Attention method (Skip-scSE-M), on the challenge dataset. The best results achieved on the test set were 0.762 mean Dice Similarity Score and 3.143 median of the Hausdorf Distance at 95 %.

Background:Prostate cancer is one of the most common solid malignancies and has a high morbidity rate. The uncertainty of the prostate location compromises the overall treatment plan optimisation. To account for the location uncertainty, the radiation oncologist needs to expand the margin of the planning target volume (PTV), which may increase the radiation toxicity to organs in proximity.Materials and methods:In this study, we investigated the quality of treatment plans for a patient with different ring sizes (2 and 3 cm). A small ring-shaped structure circumferentially around the PTV helps in defining the location of PTV. Prostate and pelvic node plans were analysed with dose prescription to 99% of PTV.Results:Additional ring-shaped structures led to more conformal dose coverage for target with reduced radiation side effects to nearby organ at risk (OAR). Expected treatment time was slightly higher for 2 cm ring compared to 3 cm ring. In case of prostate, expected duration was 4% higher, while for node plan, expected duration for 2 cm ring was 16% higher compared to 3 cm ring plan.Conclusions:It was observed that using a smaller size ring can lead to improved dose sparing to OAR with same target coverage as with larger dimension ring. The composite plans do not show any clinically significant difference in dose to OARs.

The use of magnetic resonance imaging (MRI) for radiotherapy treatment planning (RTP) is increasing due to excellent tissue contrast and high-resolution images compared to other modalities. However, the issue of image inhomogeneity which affects tissue delineation and contrast during treatment planning needs to be resolved. This study is aimed to qualitatively observe image inhomogeneity in T2-weighted images and T2 measurement using head phantom. Agar hydrogel phantom of various concentrations were used to form inhomogeneous phantom for mimicking tissue variation in the brain in addition to American College of Radiology accredited phantom. T2 images from both phantoms were obtained using fast spin echo sequence with variation of echo time (TE) and repetition time. Image processing was processed to obtain signal intensity and image mapping and the effect of inhomogeneity was observed qualitatively. T2 values were obtained by fitting signal intensity against TE and T2-mapping images were obtained. T2-weighted and T2-mapping images from the experiment provided qualitative description on image inhomogeneity and contrast. The result showed that T2-mapping images offered more information on phantom properties and described image inhomogeneity and contrast better than T2-weighted images. T2 measurement provided an alternative method for better description of image contrast which could enhance localization and tissue delineation in MRI-based RTP.

Background: In general, radiotherapy treatment planning is performed using the virtual bolus. It is necessary to investigate physical bolus in comparison to virtual one. Objectives: In the present study, first, radiological properties of superflab Gel bolus and Paraffin wax bolus was investigated in terms of their relative electron density. Then, dosimetric performance of both the bolus (i.e. Gel and Parafin wax) was compared with Virtual bolus.Material and Methods: In This experimental study, the radiological property of Wax and Gel boluses was investigated using two methods. In one, the relative electron density of both the Gel and Wax boluses was calculated by measuring their linear attenuation coefficient where in another method relative electron density was calculated by recording their CT No directly from their CT scan. Later CT scan of solid water slab phantom (dimension 30x30x15 cm3), with physical boluses (i.e. Gel and Wax bolus) of appropriate thicknesses required to deliver a dose of 200 cGy at Dmax using 4 MV, 6 MV and 15 MV photon beams, was taken. These CT data sets were retrieved to TPS. A plan was done to deliver a dose of 200 cGy at Dmax using Single 4 MV, 6 MV and 15 MV photon beams. Dose at depths Dmax, 1 cm, 2 cm, 3 cm, 4 cm and 5 cm was recorded. Using this similar method, doses at depths viz Dmax, 1 cm, 2 cm, 3 cm, 4 cm and 5 cm was recorded for the Gel and Wax boluses. The differences in dose of gel and wax bolus from virtual bolus were recorded for comparison of their dosimetric performance. Results: The measured (calculated) relative electron density of wax and Gel bolus was found to be 0.958 (0.926) and 0.923 (0.907), respectively. Variation in dosimetric performance of Gel and Wax with reference to Virtual bolus was studied. However, on average, Gel bolus was more consistent with virtual bolus. Conclusion: To avoid any dose difference between, delivered (using physical bolus) and planned (using virtual bolus), the physical boluses should be investigated for their dosimetric performance in comparison to virtual bolus. The results obtained and methodology used in this study can be applied in routine radiotherapy practices.

BackgroundAgreement between planners and treating radiation oncologists (ROs) on plan quality criteria is essential for consistent planning. Differences between ROs and planning medical physicists (MPs) in perceived quality of head and neck cancer plans were assessed.Materials and MethodsFive ROs and four MPs scored 65 plans for in total 15 patients. For each patient, the clinical (CLIN) plan and two or four alternative plans, generated with automated multi-criteria optimization (MCO), were included. There was always one MCO plan aiming at maximally adhering to clinical plan requirements, while the other MCO plans had a lower aimed quality. Scores were given as follows: 1–7 and 1–2, not acceptable; 3–5, acceptable if further planning would not resolve perceived weaknesses; and 6–7, straightway acceptable. One MP and one RO repeated plan scoring for intra-observer variation assessment.ResultsFor the 36 unique observer pairs, the median percentage of plans for which the two observers agreed on a plan score (100% = 65 plans) was 27.7% [6.2, 40.0]. In the repeat scoring, agreements between first and second scoring were 52.3% and 40.0%, respectively. With a binary division between unacceptable (scores 1 and 2) and acceptable (3–7) plans, the median inter-observer agreement percentage was 78.5% [63.1, 86.2], while intra-observer agreements were 96.9% and 86.2%. There were no differences in observed agreements between RO–RO, MP–MP, and RO–MP pairs. Agreements for the highest-quality, automatically generated MCO plans were higher than for the CLIN plans.ConclusionsInter-observer differences in plan quality scores were substantial and could result in inconsistencies in generated treatment plans. Agreements among ROs were not better than between ROs and MPs, despite large differences in training and clinical role. High-quality automatically generated plans showed the best score agreements.

We investigated the potential of respiratory gating to mitigate the motion-caused misdosage in lung stereotactic body radiotherapy (SBRT). For fourteen patients with lung tumors, we investigated treatment plans for a gating window (GW) including three breathing phases around the maximum exhalation phase, GW40–60. For a subset of six patients, we also assessed a preceding three-phase GW20–40 and six-phase GW20–70. We analyzed the target volume, lung, esophagus, and heart doses. Using normal tissue complication probability (NTCP) models, we estimated radiation pneumonitis and esophagitis risks. Compared to plans without gating, GW40–60 significantly reduced doses to organs at risk without impairing the tumor doses. On average, the mean lung dose decreased by 0.6 Gy (p &lt, 0.001), treated lung V20Gy by 2.4% (p = 0.003), esophageal dose to 5cc by 2.0 Gy (p = 0.003), and maximum heart dose by 3.2 Gy (p = 0.009). The model-estimated mean risks of 11% for pneumonitis and 12% for esophagitis without gating decreased upon GW40–60 to 7% and 9%, respectively. For the highest-risk patient, gating reduced the pneumonitis risk from 43% to 32%. Gating is most beneficial for patients with high-toxicity risks. Pre-treatment toxicity risk assessment may help optimize patient selection for gating, as well as GW selection for individual patients.

Aim: The aim of the present study was to evaluate the impact of magnetic resonance imaging (MRI) on radiotherapy target volume changes in prostate cancer. Materials and Methods: Ten patients with localized prostate cancer receiving radical radiotherapy were included in the study. Computerized tomography (CT) simulation was done with adequate immobilization, and pelvic MRI was also done at the same time. The two were then registered on eclipse planning system and fused. Target delineation (gross tumor volume [GTV] and clinical target volume [CTV]) was done on both the image sets separately and their volumes were compared. Results: In the current study, it has been found that the CT image-based contouring overestimated the GTV and CTV with 35.4% and 21.7%, respectively, as compared to that by MRI images. The difference observed was statistically significant in the case of GTV, whereas it was not statistically significant for CTV. Conclusions: It can be concluded that MRI is found to be a better modality for GTV delineation, as it gives superior soft-tissue contrast.

Atlas-based automatic segmentation is used in radiotherapy planning to accelerate the delineation of organs at risk (OARs). Atlas selection has been proposed as a way to improve the accuracy and execution time of segmentation, assuming that, the more similar the atlas is to the patient, the better the results will be. This paper presents an analysis of atlas selection methods in the context of radiotherapy treatment planning. For a range of commonly contoured OARs, a thorough comparison of a large class of typical atlas selection methods has been performed. For this evaluation, clinically contoured CT images of the head and neck ( ${N}={316}$ ) and thorax ( ${N}={280}$ ) were used. The state-of-the-art intensity and deformation similarity-based atlas selection methods were found to compare poorly to perfect atlas selection. Counter-intuitively, atlas selection methods based on a fixed set of representative atlases outperformed atlas selection methods based on the patient image. This study suggests that atlas-based segmentation with currently available selection methods compares poorly to the potential best performance, hampering the clinical utility of atlas-based segmentation. Effective atlas selection remains an open challenge in atlas-based segmentation for radiotherapy planning.

Aims The CHHiP trial investigated the use of moderate hypofractionation for the treatment of localised prostate cancer using intensity-modulated radiotherapy (IMRT). A radiotherapy quality assurance programme was developed to assess compliance with treatment protocol and to audit treatment planning and dosimetry of IMRT. This paper considers the outcome and effectiveness of the programme. Materials and methods Quality assurance exercises included a pre-trial process document and planning benchmark cases, prospective case reviews and a dosimetry site visit on-trial and a post-trial feedback questionnaire. Results In total, 41 centres completed the quality assurance programme (37 UK, four international) between 2005 and 2010. Centres used either forward-planned (field-in-field single phase) or inverse-planned IMRT (25 versus 17). For pre-trial quality assurance exercises, 7/41 (17%) centres had minor deviations in their radiotherapy processes; 45/82 (55%) benchmark plans had minor variations and 17/82 (21%) had major variations. One hundred prospective case reviews were completed for 38 centres. Seventy-one per cent required changes to clinical outlining pre-treatment (primarily prostate apex and base, seminal vesicles and penile bulb). Errors in treatment planning were reduced relative to pre-trial quality assurance results (49% minor and 6% major variations). Dosimetry audits were conducted for 32 centres. Ion chamber dose point measurements were within ±2.5% in the planning target volume and ±8% in the rectum. 28/36 films for combined fields passed gamma criterion 3%/3 mm and 11/15 of IMRT fluence film sets passed gamma criterion 4%/4 mm using a 98% tolerance. Post-trial feedback showed that trial participation was beneficial in evolving clinical practice and that the quality assurance programme helped some centres to implement and audit prostate IMRT. Conclusion Overall, quality assurance results were satisfactory and the CHHiP quality assurance programme contributed to the success of the trial by auditing radiotherapy treatment planning and protocol compliance. Quality assurance supported the introduction of IMRT in UK centres, giving additional confidence and external review of IMRT where it was a newly adopted technique.

Purpose Magnetic resonance imaging (MRI) is the primary modality for targeting brain tumors in radiotherapy treatment planning (RTP). MRI is not directly used for dose calculation since image voxel intensities of MRI are not associated with EDs of tissues as those of computed tomography (CT). The purpose of the present study is to develop and evaluate a tissue segmentation‐based method to generate a synthetic‐CT (sCT) by mapping EDs to corresponding tissues using only T1‐weighted MR images for MR‐only RTP. Methods Air regions were contoured in several slices. Then, air, bone, brain, cerebrospinal fluid (CSF), and other soft tissues were automatically segmented with an in‐house algorithm based on edge detection and anatomical information and relative intensity distribution. The intensities of voxels in each segmented tissue were mapped into their CT number range to generate a sCT. Twenty‐five stereotactic radiosurgery and stereotactic ablative radiotherapy patients’ T1‐weighted MRI and coregistered CT images from two centers were retrospectively evaluated. The CT was used as ground truth. Distances between bone contours of the external skull of sCT and CT were measured. The mean error (ME) and mean absolute error (MAE) of electron density represented by standardized CT number was calculated in HU. Results The average distance between the contour of the external skull in sCT and the contour in coregistered CT is 1.0 ± 0.2 mm (mean ± 1SD). The ME and MAE differences for air, soft tissue and whole body voxels within external body contours are −4 HU/24 HU, 2 HU/26 HU, and −2 HU/125 HU, respectively. Conclusions A MR‐sCT generation technique was developed based on tissue segmentation and voxel‐based tissue ED mapping. The generated sCT is comparable to real CT in terms of anatomical position of tissues and similarity to the ED assignment. This method provides a feasible method to generate sCT for MR‐only radiotherapy treatment planning.

Computed tomography (CT) data are required to calculate the dose distribution in a patient’s body. Generally, there are two CT number calibration methods for commercial radiotherapy treatment planning system (RTPS), namely CT number‐relative electron density calibration (CT‐RED calibration) and CT number‐mass density calibration (CT‐MD calibration). In a previous study, the tolerance levels of CT‐RED calibration were established for each tissue type. The tolerance levels were established when the relative dose error to local dose reached 2%. However, the tolerance levels of CT‐MD calibration are not established yet. We established the tolerance levels of CT‐MD calibration based on the tolerance levels of CT‐RED calibration. In order to convert mass density (MD) to relative electron density (RED), the conversion factors were determined with adult reference computational phantom data available in the International Commission on Radiological Protection publication 110 (ICRP‐110). In order to validate the practicability of the conversion factor, the relative dose error and the dose linearity were validated with multiple RTPSes and dose calculation algorithms for two groups, namely, CT‐RED calibration and CT‐MD calibration. The tolerance levels of CT‐MD calibration were determined from the tolerance levels of CT‐RED calibration with conversion factors. The converted RED from MD was compared with actual RED calculated from ICRP‐110. The conversion error was within ±0.01 for most standard organs. It was assumed that the conversion error was sufficiently small. The relative dose error difference for two groups was less than 0.3% for each tissue type. Therefore, the tolerance levels for CT‐MD calibration were determined from the tolerance levels of CT‐RED calibration with the conversion factors. The MD tolerance levels for lung, adipose/muscle, and cartilage/spongy‐bone corresponded to ±0.044, ±0.022, and ±0.045 g/cm3, respectively. The tolerance levels were useful in terms of approving the CT‐MD calibration table for clinical use.

Purpose Methods have been recently developed to generate pseudo–computed tomography (pCT) for dose calculation in magnetic resonance imaging (MRI)–only radiation therapy. This study aimed to propose an original nonlocal mean patch-based method (PBM) and to compare this PBM to an atlas-based method (ABM) and to a bulk density method (BDM) for prostate MRI-only radiation therapy. Materials and Methods Thirty-nine patients received a volumetric modulated arc therapy for prostate cancer. In addition to the planning computed tomography (CT) scans, T2-weighted MRI scans were acquired. pCTs were generated from MRIs using 3 methods: an original nonlocal mean PBM, ABM, and BDM. The PBM was performed using feature extraction and approximate nearest neighbor search in a training cohort. The PBM accuracy was evaluated in a validation cohort by using imaging and dosimetric endpoints. Imaging endpoints included mean absolute error and mean error between Hounsfield units of the pCT and the reference CT (CTref). Dosimetric endpoints were based on dose-volume histograms calculated from the CTref and the pCTs for various volumes of interest and on 3-dimensional gamma analyses. The PBM uncertainties were compared with those of the ABM and BDM. Results The mean absolute error and mean error obtained from the PBM were 41.1 and –1.1 Hounsfield units. The PBM dose-volume histogram differences were 0.7% for prostate planning target volume V95%, 0.5% for rectum V70Gy, and 0.2% for bladder V50Gy. Compared with ABM and BDM, PBM provided significantly lower dose uncertainties for the prostate planning target volume (70-78 Gy), the rectum (8.5-29 Gy, 40-48 Gy, and 61-73 Gy), and the bladder (12-78 Gy). The PBM mean gamma pass rate (99.5%) was significantly higher than that of ABM (94.9%) or BDM (96.1%). Conclusions The proposed PBM provides low uncertainties with dose planned on CTref. These uncertainties were smaller than those of ABM and BDM and are unlikely to be clinically significant.

Highlights • Average VMAT planning time using RTIP guidance was, Background and purpose Planning complex radiotherapy treatments can be inefficient, with large variation in plan quality. In this study we evaluated plan quality and planning efficiency using real-time interactive planning (RTIP) for head and neck (HN) volumetric modulated arc therapy (VMAT). Materials and methods RTIP allows manipulation of dose volume histograms (DVHs) in real-time to assess achievable planning target volume (PTV) coverage and organ at risk (OAR) sparing. For 20 HN patients previously treated with VMAT, RTIP was used to minimize OAR dose while maintaining PTV coverage. RTIP DVHs were used to guide VMAT optimization. Dosimetric differences between RTIP-assisted plans and original clinical plans were assessed. Five blinded radiation oncologists indicated their preference for each PTV, OAR and overall plan. To assess efficiency, ten patients were planned de novo by experienced and novice planners and a RTIP user. Results The average planning time with RTIP was

Purpose Assess the accuracy for quantitative measurements of electron density relative to water (ρe/ρe,w), effective atomic number (Zeff) and stopping power ratio relative to water (SPRw) using a dual-layer computed tomography (DLCT) system. Methods and Materials A tissue characterization phantom was scanned using DLCT with varying scanning parameters (i.e., tube voltage, rotation time, CTDIvol, and scanning mode) and different reference materials. Then, electron density ρe/ρe,w and atomic number Zeff images were reconstructed, and their values were determined for each reference materials. Based on these two values, SPRw was calculated. Finally, the percent error (PE) against the theoretical values was calculated for reference materials. Results Significant linear relationships (p 0.85). Conclusions DLCT provides a reasonable accuracy in the measurements of ρe/ρe,w, Zeff and SPRw, and could enhance radiotherapy treatment planning and the subsequent outcomes.

Modern radiotherapy treatment planning is a complex and time-consuming process that requires the skills of experienced users to obtain quality plans. Since the early 2000s, the automation of this planning process has become an important research topic in radiotherapy. Today, the first commercial automated treatment planning solutions are available and implemented in a growing number of clinical radiotherapy departments. It should be noted that these various commercial solutions are based on very different methods, implying a daily practice that varies from one center to another. It is likely that this change in planning practices is still in its infancy. Indeed, the rise of artificial intelligence methods, based in particular on deep learning, has recently revived research interest in this subject. The numerous articles currently being published announce a lasting and profound transformation of radiotherapy planning practices in the years to come. From this perspective, an evolution of initial training for clinical teams and the drafting of new quality assurance recommendations is desirable.

Metal Artefact Reduction (MAR) is very important in terms of dose calculation in radiotherapy. It was aimed to develop an in-house MAR software as an alternative to commercial software programs and to examine its effectiveness by comparing it with the SMART-MAR software which was available commercially. A phantom containing metal with high atomic number was designed and computed tomography (CT) images of this phantom were taken (Without-MAR images). The obtained CT images were processed with the SMART-MAR software and the developed In-House MAR software. Processed images were compared in terms of Hounsfield unit (HU), absolute dose values ​​in the Accuray and CMS XiO treatment planning systems, and gamma evaluation. The best HU improvement was observed in the developed In-House MAR. The maximum mean percentage differences in absorbed doses at the determined points in Accuray was found 33.3% and 32.5% between Without MAR - SMART MAR and Without MAR- In-House MAR, respectively. The In-House MAR software developed by using MATLAB was shown similar results with the SMART MAR software. Although in-house MAR software needs to be investigated clinically, it is more advantageous than commercially available software in terms of being cost-free, applicability in a shorter time and without reconstruction.

Purpose: To evaluate the target volume (TV) and critical organ doses with priority of testes with the comparison of conformal radiotherapy (CRT), dynamic intensity-modulated radiotherapy (DIMRT), and volumetric modulated arc therapy (VMAT) techniques. Materials and Methods: CRT, DIMRT, and VMAT techniques were generated on computed tomography images in prone position of 10 male patients with distal rectal cancer. Conformity index (CI), heterogeneity index (HI), treatment time, and monitor units were examined; dose-volume-histograms (DVHs) for the TV and the organs at risk (OARs) were evaluated. Results: Target dose coverage of all treatment plans was similar. HI and CI values for DIMRT and VMAT were closer to “1” compared to CRT. DVH parameters for OARs were decreased with DIMRT and VMAT compared to CRT. The percent volume (Vx) of 3 Gy dose of testes was 62.01% (±25.45%), 42.68% (±16.42%), and 35.89% (±14.97%) in the CRT, DIMRT, and VMAT techniques, respectively. V3 of testes decreased with VMAT compared to CRT and DIMRT (P = 0.008 and P = 0.051, respectively). Conclusion: Modern radiotherapy techniques are superior to conformal techniques in planning quality parameters and sparing OARs. DIMRT and VMAT could be considered instead of CRT in the desire to preserve fertility of patients with rectal cancer.

Purpose The current study aimed to compare contouring of glandular tissue only (gCTV) with the clinical target volume (CTV) as defined according to European Society for Radiotherapy and Oncology (ESTRO) guidelines (eCTV) and historically treated volumes (marked by wire and determined by palpation and anatomic landmarks) in breast cancer radiotherapy. Methods A total of 56 consecutive breast cancer patients underwent treatment planning based solely on anatomic landmarks/wire markings (“wire based”). From these treatment plans, the 50% and 95% isodoses were transferred as structures and compared to the following CT-based volumes: eCTV; a Hounsfield unit (HU)-based automatic contouring of the gCTV; and standardized planning target volumes (PTVs) generated with 1‑cm safety margins (resulting in the ePTVs and gPTVs, respectively). Results The 95% isodose volume of the wire-based plan was larger than the eCTV by 352.39 ± 176.06 cm3 but smaller than the ePTV by 157.58 ± 189.32 cm3. The 95% isodose was larger than the gCTV by 921.20 ± 419.78 cm3 and larger than the gPTV by 190.91 ± 233.49 cm3. Patients with larger breasts had significantly less glandular tissue than those with small breasts. There was a trend toward a lower percentage of glandular tissue in older patients. Conclusion Historical wire and anatomic landmarks-based treatment planning sufficiently covers the glandular tissue and the theoretical gPTV generated for the glandular tissue. Modern CT-based CTV and PTV definition according to ESTRO results in a larger treated volume than the historical wire-based techniques. HU-standardized glandular tissue contouring results in a significantly smaller CTV and might be an option for reducing the treatment volume and improving reproducibility of contouring between institutions.

Automatic segmentation of tumours and organs at risk can function as a useful support tool in radiotherapy treatment planning as well as for validating radiomics studies on larger cohorts. In this paper, we developed robust automatic segmentation methods for the delineation of gross tumour volumes (GTVs) from planning Computed Tomography (CT) and FDG-Positron Emission Tomography (PET) images of head and neck cancer patients. The data was supplied as part of the MICCAI 2020 HECKTOR challenge. We developed two main volumetric approaches: A) an end-to-end volumetric approach and B) a slice-by-slice prediction approach that integrates 3D context around the slice of interest. We exploited differences in the representations provided by these two approaches by ensembling them, obtaining a Dice score of 66.9% on the held out validation set. On an external and independent test set, a final Dice score of 58.7% was achieved.

Target dose homogeneity has historically been a priority in radiotherapy treatment planning. However, in an era of more advanced modulated techniques, there is now greater flexibility in shaping dose distributions suggesting that allowing controlled target dose heterogeneity may consequently improve organ at risk (OAR) sparing. This study sought to determine the feasibility of allowing an increase in target dose heterogeneity in oropharyngeal VMAT plans, and to examine the dosimetric impact this has on target coverage and OARs such as the parotid glands, spinal cord, brainstem and mandible. Nineteen oropharyngeal patients’ plans were created with homogeneous dose distributions specified in the London Cancer Head and Neck Radiotherapy Protocol. The upper dose constraint (UDC) objective of the primary planning target volumes (PTV) for each plan were increased in increments of 10% until a maximum of 150% of the prescribed dose was reached. These plans were dosimetrically compared to plans with a uniform dose distribution in terms of OAR sparing and target coverage. Minimal coverage was not compromised, with the largest median changes being a 0.81% decrease [98.6 to 97.8%] to the PTV_70Gy D98% and a 2.86% decrease [99.81 to 96.96%] to the PTV_54Gy D98% at a UDC of 150% of the prescription dose. An OAR sparing effect was observed for the parotid glands, spinal cord and oral cavity sub PTV. Mandible and brainstem Dmax values increased as the PTV UDC increased. Changes in brainstem dose were not statistically significant. All other differences were statistically significant for UDC's above 130%. Target coverage was not compromised as a result of increased target dose heterogeneity. The OAR sparing effect was promising for most organs, however further research with a larger dataset is necessary surrounding the effect on organs that overlap with the PTV.

For the commissioning of a treatment planning system (TPS) is substantial that the parameters of the radiation beam are adequately modeled and verified [1, 2]. In this work, we verified that Eclipse™ TPS V.11.031 reproduced the dose distributions of the Varian Clinac iX n/s 1227, in Medica Sur. For this, we use a PTW MP3 system and different models of dosimetry phantoms, ionization chambers and electrometers. The calculation algorithms to which quality assurance were applied were the Analytical Anisotropic Algorithm (AAA) and electron Monte Carlo (eMC). The basic photon and electron beams dose validation tests described in IAEA and AAPM guidelines [2, 3] were completed for each configured beam. For both algorithms, we have that the comparison between the measured and simulated data in the TPS is within the tolerance range specified in each validation test, being the measurements in the low dose regions and the measurements at larger depths the ones that present the greatest disagreement.

Upright radiotherapy is not new. It has been practiced for specialized treatments such as boron neutron capture therapy, light ion therapy, and even photon therapy before isocentric C-arm gantries became standardized more than 60 years ago. Today, radiotherapy treatment planning relies on CT and/or MRI systems which were typically designed only for recumbent positioning, however, lately CT and MRI scanners that can scan patients in the upright position have been developed. In recent years there is growing evidence that there are some medical benefits for treating some sites with the patient in the upright position. The existing literature describing the medical appropriateness is reviewed. Original work examining the impact to prostate radiotherapy in the upright direction is reported as is the effectiveness of repurposing conventional patient immobilization for upright radiotherapy. The financial benefits for treating with a fixed horizontal beam direction for external beam particle and photon therapy is also examined. So, is upright radiotherapy medically and financially better? The hypothesis is reasonable but it will require regulatory approval and early adopters to confirm the medical and cost effectiveness of the approach.

Background: Manual delineation of gross tumor volume (GTV) is essential for radiotherapy treatment planning, but it is time-consuming and suffers inter-observer variability (IOV). In clinics, CT, PET, and MRI are used to inform delineation accuracy due to their different complementary characteristics. This study aimed to investigate deep learning to assist GTV delineation in head and neck squamous cell carcinoma (HNSCC) by comparing various modality combinations. Materials and methods: This retrospective study had 153 patients with multiple sites of HNSCC including their planning CT, PET, and MRI (T1-weighted and T2-weighted). Clinical delineations of gross tumor volume (GTV-T) and involved lymph nodes (GTV-N) were collected as the ground truth. The dataset was randomly divided into 92 patients for training, 31 for validation, and 30 for testing. We applied a residual 3 D UNet as the deep learning architecture. We independently trained the UNet with four different modality combinations (CT-PET-MRI, CT-MRI, CT-PET, and PET-MRI). Additionally, analogical to post-processing, an average fusion of three bi-modality combinations (CT-PET, CT-MRI, and PET-MRI) was produced as an ensemble. Segmentation accuracy was evaluated on the test set, using Dice similarity coefficient (Dice), Hausdorff Distance 95 percentile (HD95), and Mean Surface Distance (MSD). Results: All imaging combinations including PET provided similar average scores in range of Dice: 0.72-0.74, HD95: 8.8-9.5 mm, MSD: 2.6-2.8 mm. Only CT-MRI had a lower score with Dice: 0.58, HD95: 12.9 mm, MSD: 3.7 mm. The average of three bi-modality combinations reached Dice: 0.74, HD95: 7.9 mm, MSD: 2.4 mm. Conclusion: Multimodal deep learning-based auto segmentation of HNSCC GTV was demonstrated and inclusion of the PET image was shown to be crucial. Training on combined MRI, PET, and CT data provided limited improvements over CT-PET and PET-MRI. However, when combining three bimodal trained networks into an ensemble, promising improvements were shown.

PurposeWhile artificial intelligence has shown great promise in organs-at-risk (OARs) auto segmentation for head and neck cancer (HNC) radiotherapy, to reach the level of clinical acceptance of this technology in real-world routine practice is still a challenge. The purpose of this study was to validate a U-net-based full convolutional neural network (CNN) for the automatic delineation of OARs of HNC, focusing on clinical implementation and evaluation.MethodsIn the first phase, the CNN was trained on 364 clinical HNC patients’ CT images with annotated contouring from routine clinical cases by different oncologists. The automated delineation accuracy was quantified using the Dice similarity coefficient (DSC) and 95% Hausdorff distance (HD). To assess efficiency, the time required to edit the auto-contours to a clinically acceptable standard was evaluated by a questionnaire. For subjective evaluation, expert oncologists (more than 10 years’ experience) were randomly presented with automated delineations or manual contours of 15 OARs for 30 patient cases. In the second phase, the network was retrained with an additional 300 patients, which were generated by pre-trained CNN and edited by oncologists until to meet clinical acceptance.ResultsBased on DSC, the CNN performed best for the spinal cord, brainstem, temporal lobe, eyes, optic nerve, parotid glands and larynx (DSC >0.7). Higher conformity for the OARs delineation was achieved by retraining our architecture, largest DSC improvement on oral cavity (0.53 to 0.93). Compared with the manual delineation time, after using auto-contouring, this duration was significantly shortened from hours to minutes. In the subjective evaluation, two observes showed an apparent inclination on automatic OARs contouring, even for relatively low DSC values. Most of the automated OARs segmentation can reach the clinical acceptance level compared to manual delineations.ConclusionsAfter retraining, the CNN developed for OARs automated delineation in HNC was proved to be more robust, efficiency and consistency in clinical practice. Deep learning-based auto-segmentation shows great potential to alleviate the labor-intensive contouring of OAR for radiotherapy treatment planning.