Dysphagia in Head and Neck Radiotherapy: The Influence of Pharyngeal Constrictor Anatomy and Dosimetry.

The goal of this study was to identify which anatomical and dosimetric changes correlated with late patient-reported dysphagia throughout the course of head and neck chemo-radiotherapy treatment. The patient cohort (n = 64) considered oropharyngeal and nasopharyngeal patients treated with curative intent, exhibiting no baseline dysphagia with a follow-up time greater than one year. Patients completed the MD Anderson Dysphagia Inventory during a follow-up visit. A composite score was measured ranging from 20 to 100, with a low score indicating a high symptom burden; a score ≤60 indicated patient-reported dysphagia. The pharyngeal (PCM) and cricopharyngeal constrictor muscles (CPM) were contoured on a planning CT image and adapted to weekly cone-beam CT anatomy using deformable image registration and dose was accumulated using weighted dose-volume histogram curves. The PCM and CPM were examined for volume, thickness, and dosimetric changes across treatment with the results correlated to symptom group. Anatomical evaluation indicated the PCM thickness increased more during treatment for patients with dysphagia, with base of C2 vertebrae (p = 0.04) and superior-inferior middle PCM (p = 0.01) thicknesses indicating a 1.0-1.5 mm increase. The planned and delivered mean dose and DVH metrics to PCM and CPM were found to be within random error measured for the dose accumulation, indicating delivered and planned dose are equivalent. The PCM and CPM organs were found to lie approximately 5 mm closer to high dose gradients in patients exhibiting dysphagia. The volume, thickness, and high dose gradient metrics may be useful metrics to identify patients at risk of late patient-reported dysphagia.

Developing and validating multi-omics prediction models for late patient-reported dysphagia in head and neck radiotherapy.

Background and purpose. To investigate models developed using radiomic and dosiomic (multi-omics) features from planning and treatment imaging for late patient-reported dysphagia in head and neck radiotherapy.Materials and methods. Training (n = 64) and testing (n = 23) cohorts of head and neck cancer patients treated with curative intent chemo-radiotherapy with a follow-up time greater than 12 months were retrospectively examined. Patients completed the MD Anderson Dysphagia Inventory and a composite score ≤60 was interpreted as patient-reported dysphagia. A chart review collected baseline dysphagia and clinical factors. Multi-omic features were extracted from planning and last synthetic CT images using the pharyngeal constrictor muscle contours as a region of interest. Late patient-reported dysphagia models were developed using a random forest backbone, with feature selection and up-sampling methods to account for the imbalanced data. Models were developed and validated for multi-omic feature combinations for both timepoints.Results. A clinical and radiomic feature model developed using the planning CT achieved good performance (validation: sensitivity = 80 ± 27% / balanced accuracy = 71 ± 23%, testing: sensitivity = 80 ± 10% / balanced accuracy = 73 ± 11%). The synthetic CT models did not show improvement over the plan CT multi-omics models, with poor reliability of the radiomic features on these images. Dosiomic features extracted from the synthetic CT showed promise in predicting late patient-reported dysphagia.Conclusion. Multi-omics models can predict late patient-reported dysphagia in head and neck radiotherapy patients. Synthetic CT dosiomic features show promise in developing successful models to account for changes in delivered dose distribution. Multi-center or prospective studies are required prior to clinical implementation of these models.

Do Dosiomic Features Extracted From Planned 3-Dimensional Dose Distribution Improve Biochemical Failure-Free Survival Prediction: an Analysis Based on a Large Multi-Institutional Data Set.

Purpose: The objective of this work was to investigate whether including additional dosiomic features can improve biochemical failure-free survival prediction compared with models with clinical features only or with clinical features as well as equivalent uniform dose and tumor control probability. Methods and Materials: This retrospective study included 1852 patients who received diagnoses of localized prostate cancer between 2010 and 2016 and were treated with curative external beam radiation therapy in Albert, Canada. A total of 1562 patients from 2 centers were used for developing 3 random survival forest models: Model A included only 5 clinical features; Model B included 5 clinical features, equivalent uniform dose, and tumor control probability; and Model C considered 5 clinical features and 2074 dosiomic features derived from the planned dose distribution of the clinical target volume and planning target volume with further feature selection to determine prognostic features. No feature selection was performed for models A and B. Two hundred ninety patients from another 2 centers were used for independent validation. Individual model-based risk stratification was examined, and the log-rank tests were performed to test statistically significant differences between the risk groups. The 3 models' performances were evaluated using Harrell's concordance index (C-index) and compared using one-way repeated-measures analysis of variance with post hoc paired t test. Results: Model C selected 6 dosiomic features and 4 clinical features to be prognostic. There were statistically significant differences between the 4 risk groups for both training and validation data sets. The C-index for the out-of-bag samples of the training data set was 0.650, 0.648, and 0.669 for models A, B, and C, respectively. The C-index for the validation data set for models A, B, and C was 0.653, 0.648, and 0.662, respectively. Although gains were modest, Model C was statistically significantly better than models A and B. Conclusions: Dosiomics contain information beyond common dose-volume histogram metrics from planned dose distributions. Incorporation of prognostic dosiomic features in biochemical failure-free survival outcome models can lead to statistically significant although modest improvement in performance.

Stability of dosiomic features against variations in dose calculation: An analysis based on a cohort of prostate external beam radiotherapy patients.

INTRODUCTION: Interest in using higher order features of the planned 3D dose distributions (i.e., dosiomics) to predict radiotherapy outcomes is growing. This is driving many retrospective studies where historical data are mined to train machine learning models; however, recent decades have seen considerable advances in dose calculation that could have a direct impact on the dosiomic features such studies seek to extract. Is it necessary to recalculate planned dose distributions using a common algorithm if retrospective datasets from different institutions are included? Does a change in dose calculation grid size part way through a retrospective cohort, introduce bias in the extracted dosiomic features? The purpose of this study is to assess the stability of dosiomic features against variations in three factors: the dose calculation algorithm type, version, and dose grid size. METHODS: Dose distributions for 27 prostate patients who received EBRT were recalculated in the Eclipse Treatment Planning System (Varian Medical Systems, Palo Alto, California, USA) using two algorithms (AAA and Acuros XB), two versions (version 13.6 and 15.6), and three dose grids (2, 2.5 s, and 3 mm) - 12 dose distributions for each patient. Ninety-three dosiomic features were extracted from each dose distribution and each of the following regions-of-interest: high dose PTV (PTV_High), 1 cm rind around PTV_High (PTV_Ring), low dose PTV (PTV_Low), rectum, and bladder using PyRadiomics. The coefficient of variation (CV) was calculated for each dosiomic feature. Hierarchical clustering was used to group features with high and low variability. Three-way repeated measures ANOVA was performed to investigate the effect of the three different factors on dosiomic features that were classified with high variation. Additionally, CVs were calculated for cumulative dose volume histograms (DVHs) to test their ability to detect the variations in dose distributions. RESULTS: For PTV_Ring, PTV_Low, and rectum, all the dosiomic features had low CV (average CV ≤ 0.26) across the varying dose calculation conditions. For PTV_High, six dosiomic features showed CV > 0.26, and dose calculation algorithm type and grid size were the major sources of within-patient variation. For bladder, one dosiomic feature had average CV > 0.26, but none of the three dose calculation-related factors led to a statistically significant variation. The CVs for all the DVHs were very small (CV < 0.05). CONCLUSION: For all the regions-of-interest examined in this study, the majority of the dosiomic features were stable against variations in dose calculation; however, some of the dosiomic features for PTV_High and bladder had significant variations due to differences in dose calculation details. DVHs were detecting less variation than dosiomic features.

External beam radiation therapy treatment factors prognostic of biochemical failure free survival: A multi-institutional retrospective study for prostate cancer.

BACKGROUND AND PURPOSE: The goal of this work is to identify specific treatment planning and delivery features that are prognostic of biochemical failure-free survival (BFFS) for prostate cancer patients treated with external beam radiotherapy (EBRT). MATERIALS AND METHODS: This study reviewed patients diagnosed with localized prostate adenocarcinoma between 2005 and 2016, and treated with EBRT on a Varian linear accelerator at one of the four cancer centers in Alberta, Canada. BFFS was calculated using the Kaplan-Meier estimator. Patient demographics, tumor characteristics, and EBRT treatment planning and delivery factors, were collected for each patient. The patient cohort was split into a training dataset with patients from two centers and a validation dataset with patients from another two centers. A random survival forest was used to identify features associated with BFFS. RESULTS: This study included 2827 patients with a median follow-up of 6.4 years. The BFFS for this cohort collectively was 84.9% at 5 years and 69.3% at 10 years. 2519 patients from two centers were used for model training and 308 patients from two different centers were used for model validation. The prognostic features were Gleason score, prostate-specific antigen (PSA) at diagnosis, clinical T stage, CTV D99, pelvic irradiation, IGRT frequency, and PTV V98. Variables including bladder volume, dose calculation algorithm, PTV D99, age at diagnosis, hip prosthesis, number of malignancies, fiducial marker usage, PTV volume, RT modality, PTV HI, rectal volume, hormone treatment, PTV D1cc, equivalent PTV margin, IGRT type, and EQD2_1.5 were unlikely to be prognostic. A random survival forest using only the seven prognostic variables was built. The Harrell's concordance index for the model was 0.65 for the whole training dataset, 0.62 for out-of-bag samples of the training dataset, and 0.62 for the validation dataset. CONCLUSION: EBRT features prognostic of BFFS were identified and a random survival forest was developed for predicting prostate cancer patients' BFFS after EBRT.

Complex housing partially mitigates low dose radiation-induced changes in brain and behavior in rats.

PURPOSE: In recent years, much effort has been focused on developing new strategies for the prevention and mitigation of adverse radiation effects on healthy tissues and organs, including the brain. The brain is very sensitive to radiation effects, albeit as it is highly plastic. Hence, deleterious radiation effects may be potentially reversible. Because radiation exposure affects dendritic space, reduces the brain's ability to produce new neurons, and alters behavior, mitigation efforts should focus on restoring these parameters. To that effect, environmental enrichment through complex housing (CH) and exercise may provide a plausible avenue for exploration of protection from brain irradiation. CH is a much broader concept than exercise alone, and constitutes exposure of animals to positive physical and social stimulation that is superior to their routine housing and care conditions. We hypothesized that CHs may lessen harmful neuroanatomical and behavioural effects of low dose radiation exposure. METHODS: We analyzed and compared cerebral morphology in animals exposed to low dose head, bystander (liver), and scatter irradiation on rats housed in either the environmental enrichment condos or standard housing. RESULTS: Enriched condo conditions ameliorated radiation-induced neuroanatomical changes. Moreover, irradiated animals that were kept in enriched CH condos displayed fewer radiation-induced behavioural deficits than those housed in standard conditions. CONCLUSIONS: Animal model-based environmental enrichment strategies, such as CH, are excellent surrogate models for occupational and exercise therapy in humans, and consequently have significant translational possibility. Our study may thus serve as a roadmap for the development of new, easy, safe and cost-effective methods to prevent and mitigate low-dose radiation effects on the brain.

A model of infection and immune response to low dose radiation.

PURPOSE: Low dose radiation therapy (LDRT) using doses in the range of 30-150 cGy has been proposed as a means of mitigating the pneumonia associated with COVID-19. However, preliminary results from ongoing clinical trials have been mixed. The aim of this work is to develop a mathematical model of the viral infection and associated systemic inflammation in a patient based on the time evolution of the viral load. The model further proposes an immunomodulatory response to LDRT based on available data. Inflammation kinetics are then explored and compared to clinical results. METHODS: The time evolution of a viral infection, inflammatory signaling factors, and inflammatory response are modeled by a set of coupled differential equations. Adjustable parameters are taken from the literature where available and otherwise iteratively adjusted to fit relevant data. Simple functions modeling both the suppression of pro-inflammatory signal factors and the enhancement of anti-inflammatory factors in response to low doses of radiation are developed. The inflammation response is benchmarked against C-reactive protein (CRP) levels measured for cohorts of patients with severe COVID-19. RESULTS: The model fit the time-evolution of viral load data, cytokine data, and inflammation (CRP) data. When LDRT was applied early, the model predicted a reduction in peak inflammation consistent with the difference between the non-surviving and surviving cohorts. This reduction of peak inflammation diminished as the application of LDRT was delayed. CONCLUSION: The model tracks the available data on viral load, cytokine levels, and inflammatory biomarkers well. An LDRT effect is large enough in principle to provide a life-saving immunomodulatory effect, though patients treated with LDRT already near the peak of their inflammation trajectory are unlikely to see drastic reductions in that peak. This result potentially explains some discrepancies in the preliminary clinical trial data.

Assessment of IGRT variability for lung SBRT.

PURPOSE: The purpose of this project was to assess factors that may influence variability in the pre-treatment kilovoltage cone beam computed tomography (kV CBCT) image matching process for lung stereotactic body radiation therapy (SBRT). METHODS AND MATERIALS: Pre-treatment CBCT and planning CT data sets of previously-treated lung SBRT patients were gathered and anonymized from four radiotherapy centers in Alberta. Eight radiation therapists (RTTs) and four radiation oncologists (ROs) were recruited from the same four cancer centers for image matching. Identical data sets were provided to each user, but the order of image sets was randomized independently for each user to remove any learning bias. Inter-user variabilities were then investigated as functions of various factors, including image origin (source institution/machine), user's institution (local matching protocol), profession (RTT vs. RO), years of experience and image quality (presence/absence of added noise). RESULTS: Very little variation in image matching between different users was observed. The mean differences from the consensus means for different image sets were less than 1 mm in all directions, and cases that exceeded 3 mm (i.e. clinically significant differences) were extremely rare. Image origin, user's institution, and profession (RTT vs. RO) didn't lead to any meaningful clinical differences, while image quality didn't introduce any statistically significant differences. In addition, no discernible trend was seen between user's experience and deviation from the user mean. Overall, no meaningful differences in inter-user variabilities for the different factors investigated were found in this study. CONCLUSIONS: There appears to be an adequate standardization across the province of Alberta in terms of CBCT image matching process. No clinically significant differences were observed as functions of various factors investigated in this study. Consistency in matching between RTTs and ROs in this study suggests that RTTs do not need systematic RO approval of their lung CBCT match. It should be noted that RTTs at the centers in this study receive comprehensive training in CBCT-based image matching.

Low dose lung radiation therapy for pneumonia: an examination of historical dose distributions.

The novel coronavirus, SARS-CoV-2, that causes the COVID-19 disease currently has healthcare systems around the world dealing with unprecedented numbers of critically ill patients. One of the primary concerns associated with this illness is acute respiratory distress syndrome (ARDS) and the pneumonia that accompanies it. Historical literature dating back to the 1940s and earlier contains many reports of successful treatment of pneumonias with ionizing radiation. Although these were not randomized controlled trials, they do suggest a potential avenue for further investigation. Technical details in these reports however were limited. In this work we review the literature and identify details including nominal kilovoltage ranges, filtration, and focus-skin distances (FSDs). Using a freely available and benchmarked code, we generated spectra and used these as sources for Monte Carlo simulations using the EGSnrc software package. The approximate sources were projected through a radiologically anthropomorphic phantom to provide detailed dose distributions within a targeted lung volume (approximate right middle lobe). After accounting for the reported exposure levels, mean lung doses fell in a relatively narrow range: 30-80 cGy. Variation in patient dimensions and other details are expected to result in an uncertainty on the order of ± 20%. This result is consistent with the dose range expected to induce anti-inflammatory effects.

Lasso logistic regression to derive workflow-specific algorithm performance requirements as demonstrated for head and neck cancer deformable image registration in adaptive radiation therapy.

As automation in radiation oncology becomes more common, it is important to determine which algorithms are equivalent for a given workflow. Often, algorithm comparisons are performed in isolation; however, clinical context can provide valuable insight into the importance of algorithm features and error magnification in subsequent workflow steps. We propose a strategy for deriving workflow-specific algorithm performance requirements. We considered two independent workflows indicating the need for radiotherapy treatment replanning for 15 head and neck cancer patients (15 planning CTs, 105 on-unit CBCTs). Each workflow was based on a different deformable image registration (DIR) algorithm. Differences in DIR output were assessed using three sets of QA metrics: (1) conventional, (2) workflow-specific, (3) a combination of (1) and (2). For a given set of algorithm metrics, lasso logistic regression modeled the probability of discrepant replan indications. Varying the minimum probability needed to predict a workflow discrepancy produced receiver operating characteristic (ROC) curves. ROC curves were compared using sensitivity, specificity, and the area under the curve (AUC). A heuristic then derived simple algorithm performance requirements. Including workflow-specific QA metrics improved AUC from 0.70 to 0.85, compared to the use of conventional metrics alone. Algorithm performance requirements had high sensitivity of 0.80, beneficial for replan assessments, with specificity of 0.57. This was an improvement over a naïve application of conventional QA criteria, which had sensitivity of 0.57 and specificity of 0.68. In addition, the algorithm performance requirements indicated practical refinements of conventional QA tolerances, indicated where auxiliary workflow processes should be standardized, and may be used to prioritize structures for manual review. Our algorithm performance requirements outperformed current comparison recommendations and provided practical means for ensuring workflow equivalence. This strategy may aid in trial credentialing, algorithm development, and streamlining expert adjustment of workflow output.

Variation in Interinstitutional Plan Quality When Adopting a Hypofractionated Protocol for Prostate Cancer External Beam Radiation Therapy.

PURPOSE: This study quantified plan quality differences across the 4 cancer centers in Alberta, Canada for plans that followed the PROstate Fractionated Irradiation Trial protocol. METHODS AND MATERIALS: Prostate plans of 235 patients were retrospectively reviewed. Interinstitutional plan quality comparisons were made based on distributions of protocol-specified parameters using 1-way analysis of variance with Games-Howell post hoc analysis. Dosimetrically representative cases were selected from each center using k-medoid clustering, enabling side-by-side comparison of dose-volume histograms and dose distributions. Fourteen anatomic features were investigated to explore interinstitutional patient population differences. Anatomically representative cases were selected from each center to explore differences in planning practices. Tumor control probability (TCP), as well as rectal wall and bladder wall normal tissue complication probabilities (NTCPs), were calculated to quantify the clinical effect of the differences in plan quality. RESULTS: Comparing the mean value of each center to the other 3, statistically significant differences were observed for bladder wall D30% and D50%, left and right femoral heads D5%, planning target volume D99% and D1cc, and clinical target volume D99%. Dosimetrically representative cases demonstrated consistent results. Although anatomic differences were observed between the center-specific populations, an analysis using anatomically similar cases demonstrated consistent trends in the dosimetric differences, suggesting the dosimetric variation is not exclusively due to anatomic differences. Minimal differences (<1%) among the 4 centers were noted for TCP and NTCPs, suggesting the reported differences in plan quality may not have any clinical significance. CONCLUSIONS: Despite common guidelines, statistically significant differences in plan quality metrics occurred among the 4 investigated centers. The differences are due at least in part to variation in local planning practices. TCP and NTCP calculations suggest that the clinical significance of the differences is minimal. These results can serve as a reference for the degree of variation among centers that can be accepted when a common protocol is adopted.

Data clustering to select clinically-relevant test cases for algorithm benchmarking and characterization.

Algorithm benchmarking and characterization are an important part of algorithm development and validation prior to clinical implementation. However, benchmarking may be limited to a small collection of test cases due to the resource-intensive nature of establishing 'ground-truth' references. This study proposes a framework for selecting test cases to assess algorithm and workflow equivalence. Effective test case selection may minimize the number of ground-truth comparisons required to establish robust and clinically relevant benchmarking and characterization results. To demonstrate the proposed framework, we clustered differences between two independent workflows estimating during-treatment dose objective violations for 15 head and neck cancer patients (15 planning CTs, 105 on-unit CBCTs). Each workflow used a different deformable image registration algorithm to estimate inter-fractional anatomy and contour changes. The Hopkins statistic tested whether workflow output was inherently clustered and k-medoid clustering formalized cluster assignment. Further statistical analyses verified the relevance of clusters to algorithm output. Data at cluster centers ('medoids') were considered as candidate test cases representative of workflow-relevant algorithm differences. The framework indicated that differences in estimated dose objective violations were naturally grouped (Hopkins = 0.75, providing 90% confidence). K-medoid clustering identified five clusters which stratified workflow differences (MANOVA: p  < 0.001) in estimated parotid gland D50%, spinal cord/brainstem Dmax, and high dose CTV coverage dose violations (Kendall's tau: p  < 0.05). Systematic algorithm differences resulting in workflow discrepancies were: parotid gland volumes (ANOVA: p  < 0.001), external contour deformations (t-test: p  = 0.022), and CTV-to-PTV margins (t-test: 0.009), respectively. Five candidate test cases were verified as representative of the five clusters. The framework successfully clustered workflow outputs and identified five test cases representative of clinically relevant algorithm discrepancies. This approach may improve the allocation of resources during the benchmarking and characterization process and the applicability of results to clinical data.

Dosimetric effect of body contour changes for prostate and head and neck volumetric modulated arc therapy plans.

Body contour changes are commonly seen in prostate and head and neck (H&N) patients undergoing volumetric modulated arc therapy (VMAT) treatments, which may cause a discrepancy between the planned dose and the delivered dose. Dosimetrists, radiation oncologists or medical physicists sometimes are required to visually assess the dosimetric impact of body contour changes and make a judgment call on whether further re-assessment of the plan is needed. However, an intuitive judgment cannot always be made in a timely manner due to the complexity of VMAT plans as well as the complicated forms of body contour changes. This study evaluated the dosimetric effect of body contour changes for prostate and H&N patients to help with clinical decision-making. By analyzing the one-dimensional spatial dose profiles from the original body and the body with different body contour deformations, rules of thumb for dose percentage change and isodose line shift due to body contour changes were ascertained. Moreover, based on dose distribution comparison using three-dimensional gamma analysis, the response of the clinical prostate and H&N VMAT plans to body contour changes was assessed. Within center specific dose deviation tolerances, prostate patients who had less than 2 cm single side body contour change or less than 1 cm uniform body contour change were unlikely to need plan re-assessment; H&N VMAT plans with less than 1 cm uniform body contour change or less than 1 cm shoulder superior-inferior positional change were also unlikely to trigger further evaluation. Dose percentage change and isodose line shift were considered independently from the problem of volume changes in this study, but clinically, both aspects must be considered.

Monte Carlo study of the relationship between skin dose and optically stimulated luminescence dosimeter dose in Pd-103 permanent breast seed implant brachytherapy.

PURPOSE: To establish a method for estimating skin dose for patients with permanent breast seed implant based on in vivo optically stimulated luminescence dosimeters (OSLDs) measurements. METHODS AND MATERIALS: Monte Carlo simulations were performed in a simple breast phantom using the EGSnrc user code egs_brachy. Realistic models of the IsoAid Advantage Pd-103 brachytherapy source and Landauer nanoDot OSLD were created to model in vivo skin dose measurements where an OSLD would be placed on the skin of a patient with permanent breast seed implant following implantation. Doses to a 0.2 cm3 volume of skin beneath the OSLD and to the sensitive volume within the OSLD were calculated, and the ratio of these values was found for various seed positions inside the breast phantom. The maximum value of this ratio may be used as a conversion factor that would allow skin dose to be estimated from in vivo OSLD measurements. RESULTS: Conversion factors of 0.5 and 1.44 are recommended for OSLDs calibrated to dose to Al2O3 and water, respectively, at the point of measurement in the OSLD. These factors were not significantly affected by the addition of extra seeds in the dose calculations. CONCLUSIONS: A method for estimating skin dose from OSLD measurements was proposed. Individual institutions should calibrate OSLDs to Pd-103 seeds to apply the results of this work clinically.

The potential impact of ultrathin filter design on dosimetry and relative biological effectiveness in modern image-guided small animal irradiators.

OBJECTIVE:: Modern image-guided small animal irradiators like the Xstrahl Small Animal Radiation Research Platform (SARRP) are designed with ultrathin 0.15 mm Cu filters, which compared with more heavily filtrated traditional cabinet-style biological irradiators, produce X-ray spectra weighted toward lower energies, impacting the dosimetric properties and the relative biological effectiveness (RBE). This study quantifies the effect of ultrathin filter design on relative depth dose profiles, absolute dose output, and RBE using Monte Carlo techniques. METHODS:: The percent depth-dose and absolute dose output are calculated using kVDoseCalc and EGSnrc, respectively, while a tally based on the induction of double-strand breaks as a function of electron spectra invoked in PENELOPE is used to estimate the RBE. RESULTS:: The RBE increases by >2.4% in the ultrathin filter design compared to a traditional irradiator. Furthermore, minute variations in filter thickness have notable effects on the dosimetric properties of the X-ray beam, increasing the percent depth dose (at 2 cm in water) by + 0.4%/0.01 mm Cu and decreasing absolute dose (at 2 cm depth in water) by -1.8%/0.01 mm Cu for the SARRP. CONCLUSIONS:: These results show that modern image-guided irradiators are quite sensitive to small manufacturing variations in filter thickness, and show a small change in RBE compared to traditional X-ray irradiators. ADVANCES IN KNOWLEDGE:: We quantify the consequences of ultrathin filter design in modern image-guided biological irradiators on relative and absolute dose, and RBE. Our results show these to be small, but not insignificant, suggesting laboratories transitioning between irradiators should carefully design their radiobiological experiments.

A quantitative assessment of the consequences of allowing dose heterogeneity in prostate radiation therapy planning.

Target dose uniformity has been historically an aim of volumetric modulated arc therapy (VMAT) planning. However, for some sites, this may not be strictly necessary and removing this constraint could theoretically improve organ-at-risk (OAR) sparing and tumor control probability (TCP). This study systematically investigates the consequences of PTV dose uniformity that results from the application or removal of an upper dose constraint (UDC) in the inverse planning process for prostate VMAT treatments. OAR sparing, target coverage, hotspots, and plan complexity were compared between prostate VMAT plans with and without the PTV UDC optimized using the progressive resolution optimizer (PRO, Varian Medical Systems, Palo Alto, CA). Removing the PTV UDC, the median D1cc reached 144.6% for the CTV and the PTV, and an average increase of 3.2% TCP was demonstrated, while CTV and PTV coverage evaluated by D99% was decreased by less than 0.6% with statistical significance. Moreover, systematic improvement in the rectum dose volume histograms was shown (a 5-10% decrease in the volume receiving 50% to 75% prescribed dose), resulting in an average decrease of 1.3% (P < 0.01) in the rectum normal tissue complication probability. Additional consequences included potentially increased dose to the urethra as evaluated by PTV D0.035cc (median: 153.4%), delivering 283 extra monitor units (MUs), and slightly higher degrees of modulation. In general, the results were consistent when a different optimizer (Photon Optimizer, Varian Medical Systems) was used. In conclusion, removing the PTV UDC is acceptable for localized prostate cases given the systematic improvement of rectal dose and TCP. It can be particularly useful for cases that do not meet the rectum dose constraints with the PTV UDC on. This comes with the foreseeable consequences of increased dose heterogeneity in the PTV and an increase in MUs and plan complexity. It also has a higher requirement for reproducing the position and size of the target and OARs during treatment. Finally, with the PTV UDC completely removed, in some cases the maximum doses within the PTV did approach levels that may be of concern for urethral toxicity and therefore in clinical implementation it may still be necessary to include a PTV UDC, but one based on limiting toxicity rather than enforcing dose homogeneity.

COMP report: CPQR technical quality control guideline for medical linear accelerators and multileaf collimators.

The Canadian Organization of Medical Physicists (COMP), in close partnership with the Canadian Partnership for Quality Radiotherapy (CPQR) has developed a series of Technical Quality Control (TQC) guidelines for radiation treatment equipment. These guidelines outline the performance objectives that equipment should meet in order to ensure an acceptable level of radiation treatment quality. The TQC guidelines have been rigorously reviewed and field tested in a variety of Canadian radiation treatment facilities. The development process enables rapid review and update to keep the guidelines current with changes in technology (the most updated version of this guideline can be found on the CPQR website). This particular TQC details recommended quality control testing for medical linear accelerators and multileaf collimators.