Efficacy, safety, and dose-dependence of the analgesic effects of opioid therapy for people with osteoarthritis: systematic review and meta-analysis.

OBJECTIVE: To evaluate the efficacy and safety of opioids for analgesic therapy for people with osteoarthritis. STUDY DESIGN: Systematic review and meta-analysis of randomised, placebo-controlled trials of opioid therapies for treating the pain of osteoarthritis. The primary outcome was medium term pain relief (six weeks to less than 12 months). Quality of evidence was assessed with GRADE criteria. DATA SOURCES: MEDLINE, EMBASE, the Cochrane Database of Systematic Reviews and Central Register of Controlled Trials, CINAHL, PsycINFO, AMED, and the WHO International Clinical Trials Registry; trials published to 31 October 2020. DATA SYNTHESIS: We extracted pain, disability, health-related quality of life, and adverse events data for 36 eligible trials (overall dose range: 10-210 oral morphine milligram equivalents [MME] per day). Continuous pain and disability outcomes were converted to common 0-100-point scales; changes of less than ten points were deemed to be very small effects. Differences in dichotomous outcomes were expressed as risk ratios. Data were pooled for meta-analysis in random effects models. The evidence from 19 trials (8965 participants; dose range, 10-126 MME/day) for very small medium term pain relief (mean difference [MD], -4.59 points; 95% CI, -7.17 to -2.02 points) was low quality, as was that from 16 trials (6882 participants; dose range, 10-126 MME/day) for a very small effect on disability (MD, -4.15 points; 95% CI, -6.94 to -1.35 points). Opioid dose was not statistically significantly associated with either degree of pain relief or incidence of adverse events in a meta-regression analysis. Evidence that opioid therapy increased the risk of adverse events (risk ratio, 1.43; 95% CI, 1.29-1.59) was of very low quality. CONCLUSIONS: Opioid medications may provide very small pain and disability benefits for people with osteoarthritis, but may also increase the risk of adverse events. PROSPERO REGISTRATION: CRD42019142813 (prospective).

Unlocking a closed system: dosimetric commissioning of a ring gantry linear accelerator in a multivendor environment.

The Halcyon™ platform is self-contained, combining a treatment planning (Eclipse) system TPS) with information management and radiation delivery components. The standard TPS beam model is configured and locked down by the vendor. A portal dosimetry-based system for patient-specific QA (PSQA) is also included. While ensuring consistency across the user base, this closed model may not be optimal for every department. We set out to commission independent TPS (RayStation 9B, RaySearch Laboratories) and PSQA (PerFraction, Sun Nuclear Corp.) systems for use with the Halcyon linac. The output factors and PDDs for very small fields (0.5 × 0.5 cm2 ) were collected to augment the standard Varian dataset. The MLC leaf-end parameters were estimated based on the various static and dynamic tests with simple model fields and honed by minimizing the mean and standard deviation of dose difference between the ion chamber measurements and RayStation Monte Carlo calculations for 15 VMAT and IMRT test plans. Two chamber measurements were taken per plan, in the high (isocenter) and lower dose regions. The ratio of low to high doses ranged from 0.4 to 0.8. All percent dose differences were expressed relative to the local dose. The mean error was 0.0 ± 1.1% (TG119-style confidence limit ± 2%). Gamma analysis with the helical diode array using the standard 3%Global/2mm criteria resulted in the average passing rate of 99.3 ± 0.5% (confidence limit 98.3%-100%). The average local dose error for all detectors across all plans was 0.2% ± 5.3%. The ion chamber results compared favorably with our recalculation with Eclipse and PerFraction, as well as with several published Eclipse reports. Dose distribution gamma analysis comparisons between RayStation and PerFraction with 2%Local/2mm criteria yielded an average passing rate of 98.5% ± 0.8% (confidence limit 96.9%-100%). It is feasible to use the Halcyon accelerator with independent planning and verification systems without sacrificing dosimetric accuracy.

Pretreatment CT and PET radiomics predicting rectal cancer patients in response to neoadjuvant chemoradiotherapy.

BACKGROUND: The purpose of this study was to characterize pre-treatment non-contrast computed tomography (CT) and 18F-fluorodeoxyglucose positron emission tomography (PET) based radiomics signatures predictive of pathological response and clinical outcomes in rectal cancer patients treated with neoadjuvant chemoradiotherapy (NACR T). MATERIALS AND METHODS: An exploratory analysis was performed using pre-treatment non-contrast CT and PET imaging dataset. The association of tumor regression grade (TRG) and neoadjuvant rectal (NAR) score with pre-treatment CT and PET features was assessed using machine learning algorithms. Three separate predictive models were built for composite features from CT + PET. RESULTS: The patterns of pathological response were TRG 0 (n = 13; 19.7%), 1 (n = 34; 51.5%), 2 (n = 16; 24.2%), and 3 (n = 3; 4.5%). There were 20 (30.3%) patients with low, 22 (33.3%) with intermediate and 24 (36.4%) with high NAR scores. Three separate predictive models were built for composite features from CT + PET and analyzed separately for clinical endpoints. Composite features with α = 0.2 resulted in the best predictive power using logistic regression. For pathological response prediction, the signature resulted in 88.1% accuracy in predicting TRG 0 vs. TRG 1-3; 91% accuracy in predicting TRG 0-1 vs. TRG 2-3. For the surrogate of DFS and OS, it resulted in 67.7% accuracy in predicting low vs. intermediate vs. high NAR scores. CONCLUSION: The pre-treatment composite radiomics signatures were highly predictive of pathological response in rectal cancer treated with NACR T. A larger cohort is warranted for further validation.

Comprehensive evaluation of the high-resolution diode array for SRS dosimetry.

A high-resolution diode array has been comprehensively evaluated. It consists of 1013 point diode detectors arranged on the two 7.7 × 7.7 cm2 printed circuit boards (PCBs). The PCBs are aligned face to face in such a way that the active volumes of all diodes are in the same plane. All individual correction factors required for accurate dosimetry have been validated for conventional and flattening filter free (FFF) 6MV beams. That included diode response equalization, linearity, repetition rate dependence, field size dependence, angular dependence at the central axis and off-axis in the transverse, sagittal, and multiple arbitrary planes. In the end-to-end tests the array and radiochromic film dose distributions for SRS-type multiple-target plans were compared. In the equalization test (180° rotation), the average percent dose error between the normal and rotated positions for all diodes was 0.01% ± 0.1% (range -0.3 to 0.4%) and -0.01% ± 0.2% (range -0.9 to 0.9%) for 6 MV and 6MV FFF beams, respectively. For the axial angular response, corrected dose stayed within 2% from the ion chamber for all gantry angles, until the beam direction approached the detector plane. In azimuthal direction, the device agreed with the scintillator within 1% for both energies. For multiple combinations of couch and gantry angles, the average percent errors were -0.00% ± 0.6% (range: -2.1% to 1.6%) and -0.1% ± 0.5% (range -1.6% to 2.1%) for the 6MV and 6MV FFF beams, respectively. The measured output factors were largely within 2% of the scintillator, except for the 5 mm 6MV beam showing a 3.2% deviation. The 2%/1 mm gamma analysis of composite SRS measurements produced the 97.2 ± 1.3% (range 95.8-98.5%) average passing rate against film. Submillimeter (≤0.5 mm) dose profile alignment with film was demonstrated in all cases.

A hybrid volumetric dose verification method for single-isocenter multiple-target cranial SRS.

A commercial semi-empirical volumetric dose verification system (PerFraction [PF], Sun Nuclear Corp.) extracts multi-leaf collimator positions from the electronic portal imaging device movies collected during a pre-treatment run, while the rest of the delivered control point information is harvested from the accelerator log files. This combination is used to reconstruct dose on a patient CT dataset with a fast superposition/convolution algorithm. The method was validated for single-isocenter multi-target SRS VMAT treatments against absolute radiochromic film measurements in a cylindrical phantom. The targets ranged in size from 0.8 to 3.6 cm and in number from 3 to 10 per plan. A total of 17 films rotated at different angles around the cylinder axis were analyzed. Each of 27 total targets was intercepted by at least one film, and 2-4 different films were analyzed per plan. Film dose was always scaled to the ion chamber measurement in a high-dose, low-gradient area deliberately created at the isocenter. The planar dose agreement between PF and film using 3%(Global dose-difference normalization)/1 mm gamma analysis was on average 99.2 ± 1.1%. The point dose difference in the low-gradient area in the middle of every target was below 3%, while PF-reconstructed and film dose centroids for individual targets showed submillimeter agreement when measured on a well aligned accelerator. Volumetrically, all voxels in all plans agreed between PF and the primary treatment planning system at the 3%/1 mm level. With proper understanding of its advantages and shortcomings, the tool can be applied to patient-specific QA in routine radiosurgical clinical practice.

Practical quantification of image registration accuracy following the AAPM TG-132 report framework.

The AAPM TG 132 Report enumerates important steps for validation of the medical image registration process. While the Report outlines the general goals and criteria for the tests, specific implementation may be obscure to the wider clinical audience. We endeavored to provide a detailed step-by-step description of the quantitative tests' execution, applied as an example to a commercial software package (Mirada Medical, Oxford, UK), while striving for simplicity and utilization of readily available software. We demonstrated how the rigid registration data could be easily extracted from the DICOM registration object and used, following some simple matrix math, to quantify accuracy of rigid translations and rotations. The options for validating deformable image registration (DIR) were enumerated, and it was shown that the most practically viable ones are comparison of propagated internal landmark points on the published datasets, or of segmented contours that can be generated locally. The multimodal rigid registration in our example did not always result in the desired registration error below ½ voxel size, but was considered acceptable with the maximum errors under 1.3 mm and 1°. The DIR target registration errors in the thorax based on internal landmarks were far in excess of the Report recommendations of 2 mm average and 5 mm maximum. On the other hand, evaluation of the DIR major organs' contours propagation demonstrated good agreement for lung and abdomen (Dice Similarity Coefficients, DSC, averaged over all cases and structures of 0.92 ± 0.05 and 0.91 ± 0.06, respectively), and fair agreement for Head and Neck (average DSC = 0.73 ± 0.14). The average for head and neck is reduced by small volume structures such as pharyngeal constrictor muscles. Even these relatively simple tests show that commercial registration algorithms cannot be automatically assumed sufficiently accurate for all applications. Formalized task-specific accuracy quantification should be expected from the vendors.

Superficial and peripheral dose in compensator-based FFF beam IMRT.

Flattening filter-free (FFF) beams produce higher dose rates. Combined with compensator-based intensity modulated radiotherapy (IMRT) techniques, the dose delivery for each beam can be much shorter compared to the flattened beam MLC-based or flattened beam compensator-based IMRT. This 'snap shot' IMRT delivery is beneficial to patients for tumor motion management. Due to softer energy, superficial doses in FFF beam treatment are usually higher than those from flattened beams. Due to no flattening filter, thus less photon scattering, peripheral doses are usually lower in FFF beam treatment. However, in compensator-based IMRT using FFF beams, the compensator is in the beam pathway. Does it introduce beam hardening effects and scattering such that the superficial dose is lower and peripheral dose is higher compared to FFF beam MLC-based IMRT? This study applied Monte Carlo techniques to investigate the superficial and peripheral doses in compensator-based IMRT using FFF beams and compared it to the MLC-based IMRT using FFF beams and flattened beams. Besides varying thicknesses of brass slabs to simulate varying thicknesses of compensators, a simple cone-shaped compensator was simulated to mimic a clinical application. The dose distribution in water phantom by the cone-shaped compensator was then simulated by multiple MLC-defined FFF and flattened beams with varying apertures. After normalization to the maximum dose, Dmax, the superficial and peripheral doses were compared between the FFF beam compensator-based IMRT and FFF/flattened beam MLC-based IMRT. The superficial dose at the central 0.5 mm depth was about 1% (of Dmax) lower in the compensator-based 6 MV FFF (6FFF) IMRT compared to the MLC-based 6FFF IMRT, and about 8% higher than the flattened 6 MV MLC-based IMRT dose. At 8 cm off-axis at depth of central maximum dose, dmax, the peripheral dose between the 6FFF and flattened 6 MV MLC demonstrated similar doses, while the compensator dose was about 1% (of Dmax) higher. Compensators reduce the superficial doses slightly compared to open FFF beams, but increases the peripheral doses due to scatter in the compensator.

Validation of a GPU-Based 3D dose calculator for modulated beams.

A superposition/convolution GPU-accelerated dose computation algorithm (the Calculator) has been recently incorporated into commercial software. The algorithm requires validation prior to clinical use. Three photon energies were examined: conventional 6 MV and 15 MV, and 10 MV flattening filter free (10 MVFFF). For a set of IMRT and VMAT plans based on four of the five AAPM Practice Guideline 5a downloadable datasets, ion chamber (IC) measurements were performed on the water-equivalent phantoms. The average difference between the Calculator and IC was -0.3 ± 0.8% (1SD). The same plans were projected on a phantom containing a biplanar diode array. We used the forthcoming criteria for routine gamma analysis, 3% dose-error (global (G) normalization, 2 mm distance to agreement, and 10% low dose cutoff). The γ (3%G/2 mm) average passing rate was 98.9 ± 2.1%. Measurement-guided three-dimensional dose reconstruction on the patient CT dataset (excluding the Lung) resulted in a similar average agreement rate with the Calculator: 98.2 ± 2.0%. The mean γ (3%G/2 mm) passing rate comparing the Calculator to the TPS (again excluding the Lung) was 99.0 ± 1.0%. Because of the significant inhomogeneity, the Lung case was investigated separately. The calculator has an alternate heterogeneity correction mode that can change the results in the thorax for higher-energy beams (15 MV). As this correction is nonphysical and was optimized for simple slab geometries, its application leads to mixed results when compared to the TPS and independent Monte Carlo calculations, depending on the CT dataset and the plan. The Calculator vs. TPS 15 MV Guideline 5a IMRT and VMAT plans demonstrate 96.3% and 93.4% γ (3%G/2 mm) passing rates respectively. For the lower energies, which should be predominantly used in the thoracic region, the passing rates for the same plans and criteria range from 98.6 to 100%. Overall, the Calculator accuracy is sufficient for the intended use.

Reproducibility of F18-FDG PET radiomic features for different cervical tumor segmentation methods, gray-level discretization, and reconstruction algorithms.

Site-specific investigations of the role of radiomics in cancer diagnosis and therapy are emerging. We evaluated the reproducibility of radiomic features extracted from 18 Flourine-fluorodeoxyglucose (18 F-FDG) PET images for three parameters: manual versus computer-aided segmentation methods, gray-level discretization, and PET image reconstruction algorithms. Our cohort consisted of pretreatment PET/CT scans from 88 cervical cancer patients. Two board-certified radiation oncologists manually segmented the metabolic tumor volume (MTV1 and MTV2 ) for each patient. For comparison, we used a graphical-based method to generate semiautomated segmented volumes (GBSV). To address any perturbations in radiomic feature values, we down-sampled the tumor volumes into three gray-levels: 32, 64, and 128 from the original gray-level of 256. Finally, we analyzed the effect on radiomic features on PET images of eight patients due to four PET 3D-reconstruction algorithms: maximum likelihood-ordered subset expectation maximization (OSEM) iterative reconstruction (IR) method, fourier rebinning-ML-OSEM (FOREIR), FORE-filtered back projection (FOREFBP), and 3D-Reprojection (3DRP) analytical method. We extracted 79 features from all segmentation method, gray-levels of down-sampled volumes, and PET reconstruction algorithms. The features were extracted using gray-level co-occurrence matrices (GLCM), gray-level size zone matrices (GLSZM), gray-level run-length matrices (GLRLM), neighborhood gray-tone difference matrices (NGTDM), shape-based features (SF), and intensity histogram features (IHF). We computed the Dice coefficient between each MTV and GBSV to measure segmentation accuracy. Coefficient values close to one indicate high agreement, and values close to zero indicate low agreement. We evaluated the effect on radiomic features by calculating the mean percentage differences (d¯) between feature values measured from each pair of parameter elements (i.e. segmentation methods: MTV1 -MTV2 , MTV1 -GBSV, MTV2 -GBSV; gray-levels: 64-32, 64-128, and 64-256; reconstruction algorithms: OSEM-FORE-OSEM, OSEM-FOREFBP, and OSEM-3DRP). We used |d¯| as a measure of radiomic feature reproducibility level, where any feature scored |d¯| ±SD ≤ |25|% ± 35% was considered reproducible. We used Bland-Altman analysis to evaluate the mean, standard deviation (SD), and upper/lower reproducibility limits (U/LRL) for radiomic features in response to variation in each testing parameter. Furthermore, we proposed U/LRL as a method to classify the level of reproducibility: High- ±1% ≤ U/LRL ≤ ±30%; Intermediate- ±30% < U/LRL ≤ ±45%; Low- ±45 < U/LRL ≤ ±50%. We considered any feature below the low level as nonreproducible (NR). Finally, we calculated the interclass correlation coefficient (ICC) to evaluate the reliability of radiomic feature measurements for each parameter. The segmented volumes of 65 patients (81.3%) scored Dice coefficient >0.75 for all three volumes. The result outcomes revealed a tendency of higher radiomic feature reproducibility among segmentation pair MTV1 -GBSV than MTV2 -GBSV, gray-level pairs of 64-32 and 64-128 than 64-256, and reconstruction algorithm pairs of OSEM-FOREIR and OSEM-FOREFBP than OSEM-3DRP. Although the choice of cervical tumor segmentation method, gray-level value, and reconstruction algorithm may affect radiomic features, some features were characterized by high reproducibility through all testing parameters. The number of radiomic features that showed insensitivity to variations in segmentation methods, gray-level discretization, and reconstruction algorithms was 10 (13%), 4 (5%), and 1 (1%), respectively. These results suggest that a careful analysis of the effects of these parameters is essential prior to any radiomics clinical application.

Validation of an improved helical diode array and dose reconstruction software using TG-244 datasets and stringent dose comparison criteria.

The original helical ArcCHECK (AC) diode array and associated software for 3D measurement-guided dose reconstruction were characterized and validated; however, recent design changes to the AC required that the subject be revisited. The most important AC change starting in 2014 was a significant reduction in the overresponse of diodes to scattered radiation outside of the direct beam, accom-plished by reducing the amount of high-Z materials adjacent to the diodes. This change improved the diode measurement accuracy, but in the process invalidated the dose reconstruction models that were assembled based on measured data acquired with the older version of the AC. A correction mechanism was intro-duced in the reconstruction software (3DVH) to accommodate this and potential future design changes without requiring updating model parameters. For each permutation of AC serial number and beam model, the user can define in 3DVH a single correction factor which will be used to compensate for the difference in the out-of-field response between the new and original AC designs. The exact value can be determined by minimizing the dose-difference with an ionization chamber or another independent dosimeter. A single value of 1.17, corresponding to the maximum measured out-of-field response difference between the new and old AC, provided satisfactory results for all studied energies (6X, 15X, and flatten-ing filter-free 10XFFF). A library of standard cases recommended by the AAPM TG-244 Report was used for reconstructed dose verification. The overall difference between reconstructed dose and an ion chamber in a water-equivalent phantom in the targets was 0.0% ± 1.4% (1 SD). The reconstructed dose on a homogeneous phantom was also compared to a biplanar diode dosimeter (Delta4) using gamma analysis with 2% (local dose-error normalization) / 2 mm / 10% cutoff criteria. The mean agreement rate was 96.7% ± 3.7%. For the plans common with the previous comparison, the mean agreement rate was 98.3% ± 0.8%, essentially unchanged. We conclude that the proposed software modification adequately addresses the change in the dosimeter response.

Initial evaluation of automated treatment planning software.

Even with advanced inverse-planning techniques, radiation treatment plan opti-mization remains a very time-consuming task with great output variability, which prompted the development of more automated approaches. One commercially available technique mimics the actions of experienced human operators to pro-gressively guide the traditional optimization process with automatically created regions of interest and associated dose-volume objectives. We report on the initial evaluation of this algorithm on 10 challenging cases of locoreginally advanced head and neck cancer. All patients were treated with VMAT to 70 Gy to the gross disease and 56 Gy to the elective bilateral nodes. The results of post-treatment autoplanning (AP) were compared to the original human-driven plans (HDP). We used an objective scoring system based on defining a collection of specific dosimetric metrics and corresponding numeric score functions for each. Five AP techniques with different input dose goals were applied to all patients. The best of them averaged the composite score 8% lower than the HDP, across the patient population. The difference in median values was statistically significant at the 95% confidence level (Wilcoxon paired signed-rank test p = 0.027). This result reflects the premium the institution places on dose homogeneity, which was consistently higher with the HDPs. The OAR sparing was consistently better with the APs, the differences reaching statistical significance for the mean doses to the parotid glands (p < 0.001) and the inferior pharyngeal constrictor (p = 0.016), as well as for the maximum doses to the spinal cord (p = 0.018) and brainstem (p = 0.040). If one is prepared to accept less stringent dose homogeneity criteria from the RTOG 1016 protocol, nine APs would comply with the protocol, while providing lower OAR doses than the HDPs. Overall, AP is a promising clinical tool, but it could benefit from a better process for shifting the balance between the target dose coverage/homogeneity and OAR sparing.

Evaluation of the ΔV 4D CT ventilation calculation method using in vivo xenon CT ventilation data and comparison to other methods.

Ventilation distribution calculation using 4D CT has shown promising potential in several clinical applications. This study evaluated the direct geometric ventilation calculation method, namely the ΔV method, with xenon-enhanced CT (XeCT) ventilation data from four sheep, and compared it with two other published meth-ods, the Jacobian and the Hounsfield unit (HU) methods. Spearman correlation coefficient (SCC) and Dice similarity coefficient (DSC) were used for the evaluation and comparison. The average SCC with one standard deviation was 0.44 ± 0.13 with a range between 0.29 and 0.61 between the XeCT and ΔV ventilation distributions. The average DSC value for lower 30% ventilation volumes between the XeCT and ΔV ventilation distributions was 0.55 ± 0.07 with a range between 0.48 and 0.63. Ventilation difference introduced by deformable image registration errors improved with smoothing. In conclusion, ventilation distributions generated using ΔV-4D CT and deformable image registration are in reasonably agreement with the in vivo XeCT measured ventilation distribution.

Left ventricular ejection fraction estimation using mutual information on technetium-99m multiple-gated SPECT scans.

BACKGROUND: A new non-linear approach was applied to calculate the left ventricular ejection fraction (LVEF) using multigated acquisition (MUGA) images. METHODS: In this study, 50 patients originally for the estimation of the percentage of LVEF to monitor the effects of various cardiotoxic drugs in chemotherapy were retrospectively selected. All patients had both MUGA and echocardiography examinations (ECHO LVEF) at the same time. Mutual information (MI) theory was utilized to calculate the LVEF using MUGA imaging (MUGA MI). RESULTS: MUGA MI estimation was significantly different from MUGA LVEF and ECHO LVEF, respectively (p < 0.005). The higher repeatability for MUGA MI can be observed in the figure by the higher correlation coefficient for MUGA MI (r = 0.95) compared with that of MUGA LVEF (r = 0.80). Again, the reproducibility was better for MUGA MI (r = 0.90, 0.92) than MUGA LVEF (r = 0.77, 0.83). The higher correlation coefficients were obtained between proposed MUGA MI and ECHO LVEF compared to that between the conventional MUGA LVEF and ECHO LVEF. CONCLUSIONS: MUGA image with the aid of MI is promising to be more interchangeable LVEF to ECHO LVEF measurement as compared with the conventional approach on MUGA image.

Measurement-guided volumetric dose reconstruction for helical tomotherapy.

It was previously demonstrated that dose delivered by a conventional linear accelerator using IMRT or VMAT can be reconstructed - on patient or phantom datasets - using helical diode array measurements and a technique called planned dose perturbation (PDP). This allows meaningful and intuitive analysis of the agreement between the planned and delivered dose, including direct comparison of the dose-volume histograms. While conceptually similar to modulated arc techniques, helical tomotherapy introduces significant challenges to the PDP formalism, arising primarily from TomoTherapy delivery dynamics. The temporal characteristics of the delivery are of the same order or shorter than the dosimeter's update interval (50 ms). Additionally, the prevalence of often small and complex segments, particularly with the 1 cm Y jaw setting, lead to challenges related to detector spacing. Here, we present and test a novel method of tomotherapy-PDP (TPDP) designed to meet these challenges. One of the novel techniques introduced for TPDP is organization of the subbeams into larger subunits called sectors, which assures more robust synchronization of the measurement and delivery dynamics. Another important change is the optional application of a correction based on ion chamber (IC) measurements in the phantom. The TPDP method was validated by direct comparisons to the IC and an independent, biplanar diode array dosimeter previously evaluated for tomotherapy delivery quality assurance. Nineteen plans with varying complexity were analyzed for the 2.5 cm tomotherapy jaw setting and 18 for the 1 cm opening. The dose differences between the TPDP and IC were 1.0% ± 1.1% and 1.1% ± 1.1%, for 2.5 and 1.0 cm jaw plans, respectively. Gamma analysis agreement rates between TPDP and the independent array were: 99.1%± 1.8% (using 3% global normalization/3 mm criteria) and 93.4% ± 7.1% (using 2% global/2 mm) for the 2.5 cm jaw plans; for 1 cm plans, they were 95.2% ± 6.7% (3% G/3) and 83.8% ± 12% (2% G/2). We conclude that TPDP is capable of volumetric dose reconstruction with acceptable accuracy. However, the challenges of fast tomotherapy delivery dynamics make TPDP less precise than the IMRT/VMAT PDP version, particularly for the 1 cm jaw setting.

Evaluation of semiempirical VMAT dose reconstruction on a patient dataset based on biplanar diode array measurements.

We report the results of a preclinical evaluation of recently introduced commercial tools for 3D patient IMRT/VMAT dose reconstruction, the Delta4 Anatomy calculation algorithm. Based on the same initial measurement, volumetric dose can be reconstructed in two ways. Three-dimensional dose on the Delta4 phantom can be obtained by renormalizing the planned dose distribution by the measurement values (D4 Interpolation). Alternatively, incident fluence can be approximated from the phantom measurement and used for volumetric dose calculation on an arbitrary (patient) dataset with a pencil beam algorithm (Delta4 PB). The primary basis for comparison was 3D dose obtained by previously validated measurement-guided planned dose perturbation method (ACPDP), based on the ArcCHECK dosimeter with 3DVH software. For five clinical VMAT plans, D4 Interpolation agreed well with ACPDP on a homogeneous cylindrical phantom according to gamma analysis with local dose-error normalization. The average agreement rates were 98.2% ± 1.3% (1 SD), (range 97.0%-100%) and 92.8% ± 3.9% (89.5%-99.2%), for the 3%/3 mm and 2%/2 mm criteria, respectively. On a similar geometric phantom, D4 PB demonstrated substantially lower agreement rates with ACPDP: 88.6% ± 6.8% (81.2%-96.1%) and 72.4% ± 8.4% (62.1%-81.1%), for 3%/3 mm and 2%/2 mm, respectively. The average agreement rates on the heterogeneous patients' CT datasets are lower yet: 81.2% ± 8.6% (70.4%-90.4%) and 64.6% ± 8.4% (56.5%-74.7%), respectively, for the same two criteria sets. For both threshold combinations, matched analysis of variance (ANOVA) multiple comparisons showed statistically significant differences in mean agreement rates (p < 0.05) for D4 Interpolation versus ACPDP on one hand, and D4 PB versus ACPDP on either cylindrical or patient dataset on the other hand. Based on the favorable D4 Interpolation results for VMAT plans, the resolution of the reconstruction method rather than hardware design is likely to be responsible for D4 PB limitations.

Evaluation of inhomogeneity correction factors for 6 MV flattening filter-free beams with brass compensators.

The 6 MV flattening filter-free (FFF) beam has been commissioned for use with compensators at our institution. This novel combination promises advantages in mitigating tumor motion due to the reduced treatment time made possible by the greatly increased dose rate of the FFF beam. Given the different energy spectrum of the FFF beam and the beam hardening effect of the compensator, the accuracy of the treatment planning system (TPS) model in the presence of low-density heterogeneities cannot be assumed. Therefore, inhomogeneity correction factors (ICF) for an FFF beam attenuated by brass slabs were measured and compared to the TPS calculations in this work. The ICF is the ratio of the point dose in the presence of inhomogeneity to the dose in the same point in a homogeneous medium. The ICFs were measured with an ion chamber at a number of points in a flat water-equivalent slab phantom containing a 7.5 cm deep heterogeneity (air or 0.27 g/cm3 wood). Comparisons for the FFF beam were carried out for the field sizes from 5× 5 to 20 × 20 cm2 with the brass slabs ranging from 0 to 5 cm in thickness. For a low-density wood heterogeneity in a slab phantom, with the exception of the point 1cm beyond the proximal buildup interface, the TPS handles the inhomogeneity correction with the brass-filtered 6 MV FFF beam at the requisite 2% error level. The combinations of field sizes and compensator thicknesses when the error exceeds 2% (2.6% maximum) are not likely to be experienced in clinical practice. In terms of heterogeneity corrections, the beam model is adequate for clinical use.

Validation of measurement-guided 3D VMAT dose reconstruction on a heterogeneous anthropomorphic phantom.

3DVH software (Sun Nuclear Corp., Melbourne, FL) is capable of generating a volumetric patient VMAT dose by applying a volumetric perturbation algorithm based on comparing measurement-guided dose reconstruction and TPS-calculated dose to a cylindrical phantom. The primary purpose of this paper is to validate this dose reconstruction on an anthropomorphic heterogeneous thoracic phantom by direct comparison to independent measurements. The dosimetric insert to the phantom is novel, and thus the secondary goal is to demonstrate how it can be used for the hidden target end-to-end testing of VMAT treatments in lung. A dosimetric insert contains a 4 cm diameter unit-density spherical target located inside the right lung (0.21 g/cm(3) density). It has 26 slots arranged in two orthogonal directions, milled to hold optically stimulated luminescent dosimeters (OSLDs). Dose profiles in three cardinal orthogonal directions were obtained for five VMAT plans with varying degrees of modulation. After appropriate OSLD corrections were applied, 3DVH measurement-guided VMAT dose reconstruction agreed 100% with the measurements in the unit density target sphere at 3%/3 mm level (composite analysis) for all profile points for the four less-modulated VMAT plans, and for 96% of the points in the highly modulated C-shape plan (from TG-119). For this latter plan, while 3DVH shows acceptable agreement with independent measurements in the unit density target, in the lung disagreement with experiment is relatively high for both the TPS calculation and 3DVH reconstruction. For the four plans excluding the C-shape, 3%/3 mm overall composite analysis passing rates for 3DVH against independent measurement ranged from 93% to 100%. The C-shape plan was deliberately chosen as a stress test of the algorithm. The dosimetric spatial alignment hidden target test demonstrated the average distance to agreement between the measured and TPS profiles in the steep dose gradient area at the edge of the 2 cm target to be 1.0 ± 0.7, 0.3 ± 0.3, and 0.3 ± 0.3 mm for the IEC X, Y, and Z directions, respectively.

Validation of three deformable image registration algorithms for the thorax.

Deformable image registration (DIR) has been proposed for lung ventilation calculation using 4D CT. Spatial accuracy of DIR can be evaluated using expert landmark correspondences. Additionally, image differences between the deformed and the target images give a degree of accuracy of DIR algorithms for the same image modality registration. DIR of the normal end-expiration (50%), end-inspiration (0%), midexpiration (30%), and midinspiration image (70%) phases of the 4D CT images was used to correlate the voxels between the respiratory phases. Three DIR algorithms, optical flow (OF), diffeomorphic morphons (DM), and diffeomorphic demons (DD) were validated using a 4D thorax model, consisting of a 4D CT image dataset, along with associated landmarks delineated by a radiologist. Image differences between the deformed and the target images were used to evaluate the degree of registration accuracy of the three DIR algorithms. In the validation of the DIR algorithms, the average target registration error (TRE) for normal end-expiration-to-end-inspiration registration with one standard deviation (SD) for the DIR algorithms was 1.6 ± 0.9 mm (maximum 3.1 mm) for OF, 1.4 ± 0.6 mm (maximum 3.3 mm) for DM, and 1.4 ± 0.7 mm (maximum 3.3 mm) for DD, indicating registration errors were within two voxels. As a reference, the median value of TRE between 0 and 50% phases with rigid registration only was 5.0 mm with one SD of 2.5 mm and the maximum value of 12.0 mm. For the OF algorithm, 81% of voxels were within a difference of 50 HU, and 93% of the voxels were within 100 HU. For the DM algorithm, 69% of voxels were within 50 HU, and 87% within 100 HU. For the DD algorithm, 71% of the voxels were within 50 HU, and 87% within a difference of 100 HU. These data suggest that the three DIR methods perform accurate registrations in the thorax region. The mean TRE for all three DIR methods was less than two voxels suggesting that the registration performed by all methods are equally accurate in the thorax.

Is wax equivalent to tissue in electron conformal therapy planning? A Monte Carlo study of material approximation introduced dose difference.

With CT-based Monte Carlo (MC) dose calculations, material composition is often assigned based on the standard Hounsfield unit ranges. This is known as the density threshold method. In bolus electron conformal therapy (BolusECT), the bolus material, machineable wax, would be assigned as soft tissue and the electron density is assumed equivalent to soft tissue based on its Hounsfield unit. This study investigates the dose errors introduced by this material assignment. BEAMnrc was used to simulate electron beams from a Trilogy accelerator. SPRRZnrc was used to calculate stopping power ratios (SPR) of tissue to wax, SPR (tissue) (wax), and tissue to water, SPR(tissue) (water), for 6, 9, 12, 15, and 18 MeV electron beams, of which 12 and 15MeV beams are the most commonly used energies in BolusECT. DOSXYZnrc was applied in dose distribution calculations in a tissue phantom with either flat wax slabs of various thicknesses or a wedge-shaped bolus on top. Dose distribution for two clinical cases, a chest wall and a head and neck, were compared with the bolus material treated as wax or tissue. The SPR(tissue) (wax) values for 12 and 15MeV beams are between 0.935 and 0.945, while the SPR(tissue) (water) values are between 0.990 and 0.991. For a 12 MeV beam, the dose in tissue immediately under the bolus is overestimated by 2.5% for a 3 cm bolus thickness if the wax bolus is treated as tissue. For 15 MeV beams, the error is 1.4%. However, in both clinical cases the differences in the PTV DVH is negligible. Due to stopping power differences, dose differences of up to 2.5% are observed in MC simulations if the bolus material is misassigned as tissue in BolusECT dose calculations. However, for boluses thinner than 2 cm that are more likely encountered in practice, the error is within clinical tolerance.

Dependence of ventilation image derived from 4D CT on deformable image registration and ventilation algorithms.

Ventilation imaging using 4D CT is a convenient and low-cost functional imaging methodology which might be of value in radiotherapy treatment planning to spare functional lung volumes. Deformable image registration (DIR) is needed to calculate ventilation imaging from 4D CT. This study investigates the dependence of calculated ventilation on DIR methods and ventilation algorithms. DIR of the normal end expiration and normal end inspiration phases of the 4D CT images was used to correlate the voxels between the two respiratory phases. Three different DIR algorithms, optical flow (OF), diffeomorphic demons (DD), and diffeomorphic morphons (DM) were retrospectively applied to ten esophagus and ten lung cancer cases with 4D CT image sets that encompassed the entire lung volume. The three ventilation extraction methods were used based on either the Jacobian, the change in volume of the voxel, or directly calculated from Hounsfield units. The ventilation calculation algorithms used are the Jacobian, ΔV, and HU method. They were compared using the Dice similarity coefficient (DSC) index and Bland-Altman plots. Dependence of ventilation images on the DIR was greater for the ΔV and the Jacobian methods than for the HU method. The DSC index for 20% of low-ventilation volume for ΔV was 0.33 ± 0.03 (1 SD) between OF and DM, 0.44 ± 0.05 between OF and DD, and 0.51 ± 0.04 between DM and DD. The similarity comparisons for Jacobian were 0.32 ± 0.03, 0.44 ± 0.05, and 0.51 ± 0.04, respectively, and for HU they were 0.53 ± 0.03, 0.56 ± 0.03, and 0.76 ± 0.04, respectively. Dependence of extracted ventilation on the ventilation algorithm used showed good agreement between the ΔV and Jacobian methods, but differed significantly for the HU method. DSC index for using OF as DIR was 0.86 ± 0.01 between ΔV and Jacobian, 0.28 ± 0.04 between ΔV and HU, and 0.28 ± 0.04 between Jacobian and HU, respectively. When using DM or DD as DIR, similar values were obtained when comparing the different ventilation calculation methods. The similarity values for the 20% high-ventilation volume were close to those found for the 20% low-ventilation volume. The results obtained with DSC index were confirmed when using the Bland-Altman plots for comparing the ventilation images. Our data suggest that ventilation calculated from 4D CT depends on the DIR algorithm employed. Similarities between ΔV and Jacobian are higher than between ΔV and HU, and Jacobian and HU.