Estimating the accuracy of the random walk simulation of mass transport processes

The mass transport processes always accompany the flow phenomena and have attracted many researchers. A lot of numerical methods have been developed to study them. These numerical methods can be classified into the Eulerian and the Lagrangian approaches. The Lagrangian approach has advantages in high stability and simplicity over the Eulerian approach, but suffers from heavy computational cost. In this paper, we are mainly concerned with the trade-offs between the accuracy and computational cost when applying the random walk method, which is a Lagrangian approach for examining the mass transport scenario. We introduce a linear model to assess the accuracy of the random walk method in several computational configurations. Studies on computational parameters, i.e. the size of time step and number of particles, are conducted with the focus on estimation of the longitudinal dispersion coefficient D_L in steady flows. The results show that the proposed linear model can satisfactorily explain the computational accuracy, both in sample and out-of-sample. Furthermore, we find a constant dimensionless parameter, which quantifies a generic relationship between the accuracy and the number of particles regardless of the flow and diffusion conditions. This dimensionless parameter is of theoretic value and offers guidelines for choosing the correct computational parameters to achieve the required numerical accuracy.

Probing the early phase of rapid instructed rule encoding

Humans can rapidly convert instructions about a rule into functional neural structures used to apply the rule. The early stages of this encoding process are poorly understood. We designed a stimulus-response (SR) task in which participants were first shown a SR rule on a screen for 200 ms, and then had to apply it to a test stimulus T, which either matched the S in the rule (SR trial) or not (catch trial). To investigate the early stages of rule encoding, the delay between the end of rule display and the onset of the test stimulus was manipulated and chosen between values of 50 ms to 1300 ms. Participants conducted three sessions of 288 trials each, separated by a median of 9 h. Random sequences of 20 rules were used. We then analysed the reaction times and the types of errors made by participants in the different conditions. The analysis of practice effects in session 1 suggests that the neural networks that process SR and catch trials are at least partially distinct, and improve separately during the practice of respectively SR and catch trials. The rule-encoding process, however, is common to both tasks and improves with the number of trials, irrespective of the trial type. Rule encoding shows interesting dynamic properties that last for 500 ms after the end of the stimulus presentation. The encoding process increases the response time in a non-stochastic way, simply adding a reaction time cost to all responses. The rule-retrieval system is functional before the encoding has stabilized, as early as 50 ms after the end of SR rule presentation, with low response errors. It is sensitive to masking however, producing errors with brief (100 ms) test stimulus presentations. Once encoding has stabilized, the sensitivity to masking disappears. It is suggested that participants do encode rules as a parametrized function, using the same neural encoding structure for each trial, rather than reconfiguring their brain anew for each new SR rule. This structure would have been implemented from instructions received prior to the experiment, by using a library of neural functions available in the brain. The observed errors are consistent with this view.

Evaluation and correction on quinones' quantification errors: Derived from the coexistence of different quinone species and pH-sensitive feature

Quinones are becoming an essential tool for refractory organics treatment, while their quantification may be not well-considered. In this paper, two kinds of potential errors in quantification were evaluated in multiple pH conditions. They were derived from the coexistence of oxidized/reduced quinone species (Type I) and pH-sensitive feature (Type II), respectively. These errors would remarkably influence the accuracy of quantification while they haven't been emphasized. Thus, to elaborate the relationship between the two types of errors and the absorbance or pH conditions, three typical quinones [Anthraquinone-1-sulfonate (α-AQS), anthraquinone-2,6-disulfonate (AQDS) and lawsone] were selected and their acid dissociation coefficients (pKa) as well as UV-Vis spectra were determined. Results revealed that, for Type I, the relative error (RE) of α-AQS concentration would exceed the limit (5%) when reduced α-AQS was below 48% of total α-AQS. Similar results were found for lawsone. However, the RE can be eliminated by the equation established in this paper. For Type II, the pH-sensitive feature was related to the pKa values of quinones. Absorbances of α-AQS and lawsone would change remarkably with pH variation. Therefore, a model for correction was established. Analog data showed high consistency with experimental data [r = 0.995 (n = 25, p < 0.01) and r = 0.997 (n = 36, p < 0.01), for lawsone and α-AQS respectively]. Especially, the determination of AQDS concentrations was noticed to be pH-independent at 437 nm under pH 4.00 to 9.18 conditions. Based on these features, a comprehensive data solution was proposed for handling these errors.

Simulations and error analysis of the CNC milling of a face gear tooth with given tool paths

This data article gives the validation files to the article “CNC milling of face gears with a novel geometric analysis” [1]. The data is about the simulation and machining error analysis of the CNC milling of a face gear tooth with given tool paths. It includes four files. Three of them are simulation videos of the CNC milling process in VERICUT with a general view, partial view and enlarged view, respectively. The other one is the source file of the machining error analysis, and it has the design model of the face gear, the simulated machined model of the face gear, and machining error analysis according to the comparison of the design model and simulated machined model.

Treatment of soil washing wastewater via adsorption of lead and zinc using graphene oxide

In the present work, graphene oxide (GO) was synthesized via the modified Hummers method and utilized in treating real soil washing wastewater via adsorptive removal of lead (Pb) and zinc (Zn). Characterization analysis of GO was performed using X-ray diffraction, Brunauer-Emmett-Teller method, Fourier transform infrared spectroscopy, scanning electron microscopy, transmission electron microscopy, and zeta potential analysis. The Van't Hoff, Eyring, and Arrhenius equations were applied to determine the activation and thermodynamic parameters namely activation energy (E_a), standard Gibbs energy change (ΔG°), standard enthalpy change (ΔH°), standard entropy change (ΔS°), change in activation Gibbs energy (ΔG^#), change in activation enthalpy (ΔH^#), and change in activation entropy (ΔS^#). Based on the high coefficient of determination values (0.8882 ≥ R² ≥ 0.9094) and low values of SSE (0.0292 ≤ SSE ≤ 0.0511) and ARE (0.8014 ≤ ARE ≤ 0.8822), equilibrium data agreed well with the Freundlich isotherm. The maximum adsorption capacity for Pb(II) and Zn(II) was determined to be 11.57 and 4.65 mg/g, respectively. Kinetic studies revealed that pseudo-second-order equation fitted well with the experimental data, which indicates that chemisorption is the rate-determining step of the adsorption system. Results have shown the possibility of GO as a potential adsorbent material in the treatment of soil washing wastewater.

An error analysis for image-based multi-modal neural machine translation

In this article, we conduct an extensive quantitative error analysis of different multi-modal neural machine translation (MNMT) models which integrate visual features into different parts of both the encoder and the decoder. We investigate the scenario where models are trained on an in-domain training data set of parallel sentence pairs with images. We analyse two different types of MNMT models, that use global and local image features: the latter encode an image globally, i.e. there is one feature vector representing an entire image, whereas the former encode spatial information, i.e. there are multiple feature vectors, each encoding different portions of the image. We conduct an error analysis of translations generated by different MNMT models as well as text-only baselines, where we study how multi-modal models compare when translating both visual and non-visual terms. In general, we find that the additional multi-modal signals consistently improve translations, even more so when using simpler MNMT models that use global visual features. We also find that not only translations of terms with a strong visual connotation are improved, but almost all kinds of errors decreased when using multi-modal models.

Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks

PURPOSE

Optical imaging is evolving as a key technique for advanced sensing in the operating room. Recent research has shown that machine learning algorithms can be used to address the inverse problem of converting pixel-wise multispectral reflectance measurements to underlying tissue parameters, such as oxygenation. Assessment of the specific hardware used in conjunction with such algorithms, however, has not properly addressed the possibility that the problem may be ill-posed.

METHODS

We present a novel approach to the assessment of optical imaging modalities, which is sensitive to the different types of uncertainties that may occur when inferring tissue parameters. Based on the concept of invertible neural networks, our framework goes beyond point estimates and maps each multispectral measurement to a full posterior probability distribution which is capable of representing ambiguity in the solution via multiple modes. Performance metrics for a hardware setup can then be computed from the characteristics of the posteriors.

RESULTS

Application of the assessment framework to the specific use case of camera selection for physiological parameter estimation yields the following insights: (1) estimation of tissue oxygenation from multispectral images is a well-posed problem, while (2) blood volume fraction may not be recovered without ambiguity. (3) In general, ambiguity may be reduced by increasing the number of spectral bands in the camera.

CONCLUSION

Our method could help to optimize optical camera design in an application-specific manner.

Investigating health information systems-induced errors

PURPOSE

The purpose of this paper is to present a review of health information system (HIS)-induced errors and its management. This paper concludes that the occurrence of errors is inevitable but it can be minimised with preventive measures. The review of classifications can be used to evaluate medical errors related to HISs using a socio-technical approach. The evaluation could provide an understanding of errors as a learning process in managing medical errors.

DESIGN/METHODOLOGY/APPROACH

A literature review was performed on issues, sources, management and approaches to HISs-induced errors. A critical review of selected models was performed in order to identify medical error dimensions and elements based on human, process, technology and organisation factors.

FINDINGS

Various error classifications have resulted in the difficulty to understand the overall error incidents. Most classifications are based on clinical processes and settings. Medical errors are attributed to human, process, technology and organisation factors that influenced and need to be aligned with each other. Although most medical errors are caused by humans, they also originate from other latent factors such as poor system design and training. Existing evaluation models emphasise different aspects of medical errors and could be combined into a comprehensive evaluation model.

RESEARCH LIMITATIONS/IMPLICATIONS

Overview of the issues and discourses in HIS-induced errors could divulge its complexity and enable its causal analysis.

PRACTICAL IMPLICATIONS

This paper helps in understanding various types of HIS-induced errors and promising prevention and management approaches that call for further studies and improvement leading to good practices that help prevent medical errors.

ORIGINALITY/VALUE

Classification of HIS-induced errors and its management, which incorporates a socio-technical and multi-disciplinary approach, could guide researchers and practitioners to conduct a holistic and systematic evaluation.

Determination of isotopes activity ratio using gamma ray spectroscopy based on neural network model

The uranium isotopes activity-ratio was determined using in-situ γ-ray spectroscopic measurements and an artificial neural network model. The method was developed to use forward-learn multilayer algorithm. Each layer consists of a perceptron, that controls the forward-learn process, and a mean-square-error mapping for the spectral data from the set of fired perceptrons. The set of output parameters should represent a vector of coefficients for double logarithmic polynomial that distinguish the instrumental efficiency. The forward-learn is controlled by a rejection function which is based on an input set Ψ of parameters that tells the neural layer to accept or reject data points. Each layer maps to the next layer by reducing chi-square-difference with the experimental uncertainty as weight. There are two supervised controls to the network, the maximum deviation from interpolated curve and the assumed initial set of rejection parameters (Ψ₀). The model was tested on spectra of known enrichments and gave an excellent agreement with low enriched uranium samples ((1.38 ± 0.14)% and (20 ± 1.55)%). The use of the algorithm on natural uranium ore and association with radium-226 daughters causes increase of uncertainty and deviation of the results from the certified value. The current algorithm provides a practical solution to a wide range of gamma-ray measurement problems encountered for in-situ characterization of uranium-containing materials. These include security, safeguards, fuel assessment, decontamination and decommissioning operations with no collimation or special setup. It is also applicable for large-scale installations.

Position and Orientation Errors in a Neuronavigation Procedure: A Stepwise Protocol Using a Cranial Phantom

OBJECTIVE

Neuronavigation procedures demand high precision and accuracy. Despite this need, there are still few studies analyzing errors in such procedures. The aim of this study was to use a custom-built cranial phantom to measure target position and orientation errors in different phases of a simulated neuronavigation procedure.

METHODS

A cranial phantom with 10 target sites was designed and imaged with computed tomography and magnetic resonance. A segmentation of a cloud of points of the phantom (ground truth) was obtained using an optical tracking system and compared with the images (imaging phase). Targets and trajectories were then planned with neuronavigation software and compared with the ground truth (planning phase). The same plan was used to identify the points in real space after image-to-phantom registration and calculate the final error of the procedure by comparison with the ground truth (registration and execution phase).

RESULTS

The mean errors after the imaging phase were 1.11 ± 0.42 mm and 3.23° ± 1.69° for position and orientation, respectively. After planning the mean errors were 1.10 ± 0.39 mm and 5.55° ± 2.91°. The global errors after the registration and mechanical execution were 3.93 ± 1.70 mm and 3.65° ± 1.29°.

CONCLUSIONS

After a stepwise analysis, registration and mechanical execution were the main contributors to the global position error.

European follow-up of incorrect biomarker results for colorectal cancer demonstrates the importance of quality improvement projects

Biomarker analysis for colorectal cancer has been shown to be reliable in Europe with 97% of samples tested by EQA participants to be correctly classified. This study focuses on errors during the annual EQA assessment. The aim was to explore the causes and actions related to the observed errors and to provide feedback and assess any improvement between 2016 and 2017. An electronic survey was sent to all laboratories with minimum one genotyping error or technical failure on ten tumor samples. A workshop was organized based on 2016 survey responses. Improvement of performance in 2017 was assessed for returning participants (n = 76), survey respondents (n = 13) and workshop participants (n = 4). Survey respondents and workshop participants improved in terms of (maximum) analysis score, successful participation, and genotyping errors compared to all returning participants. In 2016, mostly pre- and post-analytical errors (both 25%) were observed caused by unsuitability of the tumor tissue for molecular analysis. In 2017, most errors were due to analytical problems (50.0%) caused by methodological problems. The most common actions taken (n = 58) were protocol revisions (34.5%) and staff training (15.5%). In 24.1% of issues identified no action was performed. Corrective actions were linked to an improved performance, especially if performed by the pathologist. Although biomarker testing has improved over time, error occurrence at different phases stresses the need for quality improvement throughout the test process. Participation to quality improvement projects and a close collaboration with the pathologist can have a positive influence on performance.

Reducing wrong intraocular lens implants in cataract surgery

Purpose Wrong lens implants have been associated with the highest frequency of medical errors in cataract surgery. The purpose of this paper is to explore the use of the Systems Engineering Initiative for Patient Safety (SEIPS) framework to sustainably reduce wrong intraocular lens (IOL) implants in cataract surgery. Design/methodology/approach In this mixed-methods study, the SEIPS framework was used to analyse a series of (near) misses of IOL implants in a national tertiary specialty hospital in Singapore. A series of interventions was developed and applied in the case hospital. Risk assessment audits were done before the interventions (2012; n=6,111 surgeries), during its implementation ( n=7,475) and in the two years post-interventions (2013-2015; n=39,390) to compare the wrong IOL-rates. Findings Although the absolute number of incidents was low, the incident rate decreased from 4.91 before to 2.54 per 10,000 cases after. Near miss IOL error decreased from 5.89 before to 3.55 per 1,000 cases after. The number of days between two IOL incidents increased from 35 to an initial peak of 385 before stabilizing on 56. The large variety of available IOL types and vendors was found as the main root cause of wrong implants that required reoperation. Practical implications The SEIPS framework seems to be helpful to assess components involved and develop sustainable quality and safety interventions that intervene at different levels of the system. Originality/value The SEIPS model is supportive to address differences between person and system root causes comprehensively and thereby foster quality and patient safety culture.

Quantification of the limitation of Langmuir model used in adsorption research on sediments via site energy heterogeneity

The Langmuir model has been extensively introduced into the field of environmental adsorption, while some studies showed that it was difficult for the model to describe the adsorption of sediments. The purpose of this paper is to recognize the applicability of the Langmuir model used in the adsorption of contaminants onto sediments quantitatively through the relationship between the error of Langmuir (δ) and site energy heterogeneity (σ). The formula for calculating δ in sediments was developed based on the heterogeneity parameters (m, n). The data was extracted from papers discussing about the adsorption of pollutants on natural sediments. It was further used to investigate the error of Langmuir and the effect on the error from the site energy heterogeneity. The results indicate that the Langmuir model can be applied in sediments when each one of the conditions below is satisfied, (1) m and n lie in the area which signifies that the relative error is less than 10%, (2) the site energy heterogeneity of sediment is under 5.668. These findings are vital for the proper choice of models fitting the adsorption process of sediments.

Experimental validation of predicted application accuracies for computer-assisted (CAS) intraoperative navigation with paired-point registration

PURPOSE

The target registration error (TRE) is a crucial parameter to estimate the potential usefulness of computer-assisted navigation intraoperatively. Both image-to-patient registration on base of rigid-body registration and TRE prediction methods are available for spatially isotropic and anisotropic data. This study presents a thorough validation of data obtained in an experimental operating room setting with CT images.

METHODS

Optical tracking was used to register a plastic skull, an anatomic specimen, and a volunteer to their respective CT images. Plastic skull and anatomic specimen had implanted bone fiducials for registration; the volunteer was registered with anatomic landmarks. Fiducial localization error, fiducial registration error, and total target error (TTE) were measured; the TTE was compared to isotropic and anisotropic error prediction models. Numerical simulations of the experiment were done additionally.

RESULTS

The user localization error and the TTE were measured and calculated using predictions, both leading to results as expected for anatomic landmarks and screws used as fiducials. TRE/TTE is submillimetric for the plastic skull and the anatomic specimen. In the experimental data a medium correlation was found between TRE and target localization error (TLE). Most of the predictions of the application accuracy (TRE) fall in the 68% confidence interval of the measured TTE. For the numerically simulated data, a prediction of TTE was not possible; TRE and TTE show a negligible correlation.

CONCLUSION

Experimental application accuracy of computer-assisted navigation could be predicted satisfactorily with adequate models in an experimental setup with paired-point registration of CT images to a patient. The experimental findings suggest that it is possible to run navigation and prediction of navigation application accuracy basically defined by the spatial resolution/precision of the 3D tracker used.

Xanthium strumarium L. seed hull as a zero cost alternative for Rhodamine B dye removal

Treatment of polluted water has been considered as one of the most important aspects in environmental sciences. Present study explores the decolorization potential of a low cost natural adsorbent Xanthium strumarium L. seed hull for the adsorption of a toxic xanthene dye, Rhodamine B (RHB). The characterization of the adsorbent revealed the presence of high amount of carbon, when exposed to Electron Dispersive Spectroscopy (EDS). Further appreciable decolorization took place which was confirmed by Fourier Transform Infrared Spectroscopy (FTIR) analysis noticing shift in peaks. Isothermal studies indicated multilayer adsorption following Freundlich isotherm. The rate of adsorption was supported by second order kinetics directing a chemical phenomenon during the process with dominance of film diffusion as the rate governing step. Moreover paper aims at correlating the chemical arena to the mathematical aspect providing an in-depth information of the studied treatment process. For proper assessment and validation of the observed data, experimental data has been statistically treated by applying different error functions namely, Chi-square test (χ²), Sum of absolute errors (EABS) and Normalized standard deviation (NSD). Further practical applicability of the low cost adsorbent was evaluated by continuous column mode studies with 72.2% of dye recovery. Xanthium strumarium L. proved to be environment friendly low cost natural adsorbent for decolorizing RHB from aquatic system.

Development of model for prediction of Leachate Pollution Index (LPI) in absence of leachate parameters

Leachate pollution index (LPI) is an environmental index which quantifies the pollution potential of leachate generated in landfill site. Calculation of Leachate pollution index (LPI) is based on concentration of 18 parameters present in leachate. However, in case of non-availability of all 18 parameters evaluation of actual values of LPI becomes difficult. In this study, a model has been developed to predict the actual values of LPI in case of partial availability of parameters. This model generates eleven equations that helps in determination of upper and lower limit of LPI. The geometric mean of these two values results in LPI value. Application of this model to three landfill site results in LPI value with an error of ±20% for ∑_iⁿw_i⩾0.6.

Optimization of isotherm models for pesticide sorption on biopolymer-nanoclay composite by error analysis

A carboxy methyl cellulose-nano organoclay (nano montmorillonite modified with 35-45 wt % dimethyl dialkyl (C₁₄-C₁₈) amine (DMDA)) composite was prepared by solution intercalation method. The prepared composite was characterized by infrared spectroscopy (FTIR), X-Ray diffraction spectroscopy (XRD) and scanning electron microscopy (SEM). The composite was utilized for its pesticide sorption efficiency for atrazine, imidacloprid and thiamethoxam. The sorption data was fitted into Langmuir and Freundlich isotherms using linear and non linear methods. The linear regression method suggested best fitting of sorption data into Type II Langmuir and Freundlich isotherms. In order to avoid the bias resulting from linearization, seven different error parameters were also analyzed by non linear regression method. The non linear error analysis suggested that the sorption data fitted well into Langmuir model rather than in Freundlich model. The maximum sorption capacity, Q₀ (μg/g) was given by imidacloprid (2000) followed by thiamethoxam (1667) and atrazine (1429). The study suggests that the degree of determination of linear regression alone cannot be used for comparing the best fitting of Langmuir and Freundlich models and non-linear error analysis needs to be done to avoid inaccurate results.

Intact non-word repetition and similar error patterns in language-matched children with autism spectrum disorders: A pilot study

PURPOSE

We investigated whether enhanced auditory short-term memory may contribute to the learning of novel word forms in children with Autism Spectrum Disorder. We also evaluated whether delayed but qualitatively normal, versus atypical, cognitive processes underlie non-word repetition in this population via a detailed error analysis.

METHOD

English-speaking children with Autism Spectrum Disorder (who had significant language delay) and typically-developing children matched pairwise on language ability were compared on the Syllable Repetition Task (Shriberg et al., 2009).

RESULTS

All children exhibited better performance on stimuli of shorter vs. longer syllable length. In addition there was a significant interaction whereby children with Autism Spectrum Disorder performed better than typically-developing children at the longest syllable length. Repetition accuracy was significantly correlated with language level in both groups. In contrast, the relationship between Repetition accuracy and age was only marginally significant in the Autism Spectrum Disorder group and did not reach significance in the typically-developing group. This underscores the importance of language level to non-word repetition performance, and supports the practice of matching on language rather than age alone. An error analysis (Shriberg et al., 2012) showed many similarities between groups in terms of number of consonants deleted, encoding accuracy, and transcoding accuracy components of the task. However the Autism Spectrum Disorder group tended to display better auditory short-term memory with a medium effect size, though this did not reach significance given the small sample size.

CONCLUSION

These findings extend evidence of delayed but qualitatively normal non-word repetition previously described in preadolescents with Autism Spectrum Disorder (Williams et al., 2013) to younger kindergarten-age children with Autism Spectrum Disorder and language delay, indicating that non-word repetition is not an area of specific difficulty for this population. With respect to enhanced auditory short-term memory, we found preliminary evidence of better memory for longer nonwords in children with Autism Spectrum Disorder compared to younger typically developing children who were matched on language.

Robust learning in SpikeProp

Training a Spiking Neural Network using SpikeProp and its derivatives faces stability issues. Surges, marked by a sudden rise in learning cost, are a common occurrence during the learning process. They disrupt the learning process and often destabilize the process resulting in failure. A proper learning rate, which is neither too small nor too big, is important to minimize surges. Furthermore, external disturbances due to imperfection in sample data as well as internal disturbances are additional destabilizing source during the learning process. In this paper, we perform error system analysis incorporating external disturbance, followed by weight convergence analysis along with detailed robust stability analysis of SpikeProp learning process to ensure error bound of the learning process. Based on these results, we propose a robust adaptive learning rate scheme that aligns with the results of theoretical analysis. The performance of the proposed method has been compared with other prevalent methods based on different benchmark datasets and the results demonstrate that our method indeed has better performance in terms of convergence and learning speed as well.

Homotopy perturbation method: a versatile tool to evaluate linear and nonlinear fuzzy Volterra integral equations of the second kind

In this article, we focus on linear and nonlinear fuzzy Volterra integral equations of the second kind and we propose a numerical scheme using homotopy perturbation method (HPM) to obtain fuzzy approximate solutions to them. To facilitate the benefits of this proposal, an algorithmic form of the HPM is also designed to handle the same. In order to illustrate the potentiality of the approach, two test problems are offered and the obtained numerical results are compared with the existing exact solutions and are depicted in terms of plots to reveal its precision and reliability.

Synchronization Design and Error Analysis of Near-Infrared Cameras in Surgical Navigation

The accuracy of optical tracking systems is important to scientists. With the improvements reported in this regard, such systems have been applied to an increasing number of operations. To enhance the accuracy of these systems further and to reduce the effect of synchronization and visual field errors, this study introduces a field-programmable gate array (FPGA)-based synchronization control method, a method for measuring synchronous errors, and an error distribution map in field of view. Synchronization control maximizes the parallel processing capability of FPGA, and synchronous error measurement can effectively detect the errors caused by synchronization in an optical tracking system. The distribution of positioning errors can be detected in field of view through the aforementioned error distribution map. Therefore, doctors can perform surgeries in areas with few positioning errors, and the accuracy of optical tracking systems is considerably improved. The system is analyzed and validated in this study through experiments that involve the proposed methods, which can eliminate positioning errors attributed to asynchronous cameras and different fields of view.

Poster - Thur Eve - 53: Analysis of the distribution of dose delivery during respiratory-gated step-and-shoot IMRT for lung cancer radiotherapy

Respiratory motion is a large source of dosimetric error when treating lung cancer with Intensity Modulated Radiation Therapy (IMRT). The asynchronicity of the tumour motion and the multileaf collimator (MLC) used to modulate the radiation beam intensity, leads to the interplay effect. One method to account for this effect is respiratory gating. Treatment planning optimization for gated IMRT is performed on a subset average 4D-CT which includes the phases surrounding end exhalation. However, this assumes that the beam delivery will be evenly distributed amongst those phases. This study investigates the distribution of beam delivery during gated step-and-shoot IMRT (SS-IMRT) for both early and late stage non-small cell lung cancer (NSCLC). Four Stage I NSCLC patients, prescribed a dose of 54 Gy in 3 fractions, and five Stage III NSCLC patients, prescribed a dose of 60 Gy in 30 fractions, were retrospectively planned with high and low modulation beams-IMRT, and delivered using the QUASAR™ Programmable Respiratory Motion Platform with 15 mm and 20 mm peak-to-peak sinusoidal motion and real patient breathing motion. The percent monitor units delivered at each phase were compared. For Stage I patients, the monitor units delivered were evenly distributed over the gating window due to a high number of monitor units delivered per control point. For Stage III patients, as the complexity of SS-IMRT increases, there were more monitor units delivered in the initial gating phase. This dose discrepancy could potentially lead to geographic miss of the tumour and should be taken into account during treatment planning.

Sci-Fri PM: Delivery - 04: Quantitative air communication testing of ion chambers for megavoltage dosimetry

The valid application of the standard correction for air density (P_TP in the TG-51 protocol) requires that for a vented ion chamber (basically all reference-class ion chambers) the air cavity does indeed communicate directly with the external environment. However, this assumption is not tested by users, and not universally verified by calibration laboratories. A system has therefore been developed at the National Research Council to test air communication of cylindrical and parallel-plate ion chambers. The systems is based on measurements in a vacuum vessel with a Sr-90 check source; the procedure is simple and quick and can measure ionization currents over the pressure range 0 kPa (atmospheric) to -20kPa (0.8 atm) with an uncertainty better than 0.2%. Investigation of a wide range of chamber types shows that for a coarse check on chamber performance (i.e., that the chamber is vented to atmosphere) measurement at a single polarity is sufficient (total test time less than 15 minutes) but for accurate characterization of the chamber performance, data at both polarities must be acquired. The accuracy of the system means that it can potentially be used to investigate: i) the validity of the pressure correction, and ii) the source of the polarity correction in cylindrical and parallel-plate chambers. The air communication test will be implemented as part of the standard calibration services provided by NRC for external beam radiotherapy.

Sci-Fri PM: Delivery - 07: Cyberknife relative output factor measurements using fiber-coupled luminescence, MOSFETS and RADPOS dosimetry system

Novel dosimetry systems based on Al₂ O₃ :C radioluminescence (RL) and a 4D dosimetry system (RADPOS) from Best Medical Canada were used to measure the relative output factor (ROF) on Cyberknife. Measurements were performed in a solid water phantom at the depth of 1.5 cm and SSD = 78.5 cm for cones from 5 to 60 mm. ROFs were also measured using a mobileMOSFET system (Best Medical Canada) and EBT1 and EBT2 GAFCHROMIC® (ISP, Ashland) radiochromic films. For cone sizes 12.5-60 mm all detector results were in agreement within the measurement uncertainty. The microMOSFET/RADPOS measurements (published corrections applied) yielded ROFs of 0.650 ± 1.9%, 0.811 ± 0.9% and 0.843 ± 1.7% for the 5, 7.5 and 10 mm cones, respectively, and were in excellent agreement with radiochromic film values (averaged for EBT1 and EBT2) of 0.645 ± 1.4%, 0.806 ± 1.1% and 0.859 ± 1.1%. Monte-Carlo calculated correction factors were applied to the RL readings to correct for excessive scatter due to the relatively high effective atomic number of Al₂ O₃ (Z=10.2) compared to water for the 5, 7.5 and 10 mm cones. When these corrections are applied to our RL detector measurements, we obtain ROFs of 0.656 ± 0.3% and 0.815 ± 0.3% and 0.865 ± 0.3% for 5, 7.5 and 10 mm cones. Our study shows that the microMOSFET/RADPOS and optical fiber-coupled RL dosimetry system are well suited for Cyberknife cone output factors measurements over the entire range of field sizes, provided that appropriate correction factors are applied for the smallest cone sizes (5, 7.5 and 10 mm).

WE-G-217A-06: Spatial Accuracy Quantification of an MR System

PURPOSE

To develop a phantom and measurement protocol for quantifying spatial accuracy of an MR imaging system over its entire imaging volume.

METHODS

The measurement protocol is comprised of a phantom, a set of MR sequence parameters for imaging the phantom, and analysis software for calculating spatial errors in the acquired phantom images. The phantom covers the entire imaging volume of the scanner above the patient table. It consists of layers of tooling foam which does not produce any detectable signal on conventional MR images, embedded with a matrix of oil capsules to serve as markers. To account for possible spatial errors in the construction of the phantom, the phantom was imaged with CT to create a gold standard data set. On MR scanners, the phantom is acquired with a 3D FGRE sequence that covers an extended FOV of 61.44 mm and with bandwidth = ±62.5 kHz. Error measurements are performed by detecting markers in the image sets and identifying them based on their known locations on the phantom. The spatial error of a marker is defined as the difference between its locations on the MR and CT image sets.

RESULTS

The phantom was constructed and the measurement protocol was executed on two different MR scanners. Some markers were located in areas of severe field inhomogeneity or gradient nonlinearity, and could not be adequately detected for analysis. Maximum errors over concentric spherical regions were observed by plotting the error of each marker as a function of their distance from isocenter.

CONCLUSION

The proposed phantom and protocol can be an effective tool for verifying the spatial accuracy of an MR system, which in turn can improve the accuracy and confidence of MR guided therapies. Data from this protocol may also be used in the development of advanced distortion correction algorithms. Employed by General Electric Healthcare.