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Sympathetic activity and the underlying action potentials in sympathetic nerves: a simulation.

Understanding the relationship between activity recorded in sympathetic nerves and the action potentials of the axons that contribute to that activity is important for understanding the processing of sympathetic activity by the central nervous system. Because this relationship cannot be determined experimentally and is difficult to predict analytically, we simulated the summed action potentials of 300 axons. This simulation closely resembled actual sympathetic activity and permitted us to know how many action potentials contributed to each burst of simulated sympathetic activity and the durations and amplitudes of each burst. We used these simulated data to examine a statistical method (cluster analysis) that has been used to identify and quantify bursts of sympathetic activity. Simulation indicated that the integrals of bursts, whether determined directly from the simulation or by integrating bursts detected by cluster analysis, were linearly correlated to the number of action potentials contributing to bursts. The variances of samples of the simulated signal were also linearly correlated to the number of action potentials. The amplitudes of bursts of sympathetic activity were less well correlated to the number of underlying action potentials. A linear relationship existed between the average number of action potentials contributing to simulated bursts and the integral of the amplitude spectra obtained by Fourier transform of the simulated activity. Finally, simulated experiments indicated that relatively brief recordings might be sufficient to detect statistically significant changes in sympathetic activity.

Action Potentials↗

SUP: an extension to SLINK to allow a larger number of marker loci to be simulated in pedigrees conditional on trait values.

BACKGROUND: With the recent advances in high-throughput genotyping technologies that allow for large-scale association mapping of human complex traits, promising statistical designs and methods have been emerging. Efficient simulation software are key elements for the evaluation of the properties of new statistical tests. SLINK is a flexible simulation tool that has been widely used to generate the segregation and recombination processes of markers linked to, and possibly associated with, a trait locus, conditional on trait values in arbitrary pedigrees. In practice, its most serious limitation is the small number of loci that can be simulated, since the complexity of the algorithm scales exponentially with this number. RESULTS: I describe the implementation of a two-step algorithm to be used in conjunction with SLINK to enable the simulation of a large number of marker loci linked to a trait locus and conditional on trait values in families, with the possibility for the loci to be in linkage disequilibrium. SLINK is used in the first step to simulate genotypes at the trait locus conditional on the observed trait values, and also to generate an indicator of the descent path of the simulated alleles. In the second step, marker alleles or haplotypes are generated in the founders, conditional on the trait locus genotypes simulated in the first step. Then the recombination process between the marker loci takes place conditionally on the descent path and on the trait locus genotypes. This two-step implementation is often computationally faster than other software that are designed to generate marker data linked to, and possibly associated with, a trait locus. CONCLUSION: Because the proposed method uses SLINK to simulate the segregation process, it benefits from its flexibility: the trait may be qualitative with the possibility of defining different liability classes (which allows for the simulation of gene-environment interactions or even the simulation of multi-locus effects between unlinked susceptibility regions) or it may be quantitative and normally distributed. In particular, this implementation is the only one available that can generate a large number of marker loci conditional on the set of observed quantitative trait values in pedigrees.

Algorithms↗

Computerized patient model and simulated clinical experiences: evaluation with baccalaureate nursing students.

This study evaluated student and faculty member perceptions regarding the use of a computerized universal patient simulator (Laerdal SimMan Universal Patient Simulator) in a simulated clinical scenario. Students who used SimMan in clinical simulation activities in this baccalaureate program during two consecutive semesters were surveyed using a 20-item tool scored on a 4-point Likert scale. Four faculty members were surveyed using a 17-item tool with the same response scale. The majority of the student sample consisted of Anglo women between ages 22 and 36. Survey items related to the reality of the simulations, the pace and flow of the clinical simulation, the ability to transfer skills learned to actual clinical settings, and the value of the simulated clinical experiences. Faculty members were also surveyed related to resource issues. Descriptive statistics were used to analyze survey responses. The majority of the students and faculty members identified the simulations as realistic and valuable. However, only approximately half of the students agreed that the skills learned in the clinical simulation would transfer to a real clinical setting, compared to 100% of the faculty. Faculty members reported that implementing the simulated clinical scenario required additional time and resources.

Adult↗

Can simulators evaluate systematic differences between oscillometric non-invasive blood-pressure monitors?

BACKGROUND: Oscillometric non-invasive blood-pressure (NIBP) monitors estimate the arterial pressure using model-specific signal processing and algorithms. Hence each model's accuracy must be clinically evaluated. Simulators may assist the evaluation, but their ability to do so has not been verified. OBJECTIVE: To investigate whether simulators can detect systematic differences between NIBP monitors. METHODS: We tested whether a simulator can distinguish between the two different algorithms available in a particular monitor, detect calibration errors and detect systematic differences between monitors that are observed clinically. RESULTS: Simulator evaluation correctly detected 1.8 and 4.2 mmHg systolic and diastolic differences between the two Nellcor N-3100 algorithms (with specified 2 and 5 mmHg differences) but found no difference between their mean arterial pressures (as expected from the specification). Simulator evaluations detected calibration adjustments at 80/50, 120/80 and 200/150 mmHg. Simulator and clinical comparisons of two devices of the same type recording slightly different blood pressures were in close agreement, but simulator and clinical comparisons of three different models (Propaq, Critikon DINAMAP and Datex Cardiocap) were not consistently in agreement. The simulators generated oscillometric pulse shapes different from physiological recordings. CONCLUSION: The results suggest that, although simulators can reveal systematic differences between devices of the same model, they cannot be used to detect systematic differences between different NIBP models. This could be at least partly because the oscillometric pulses generated by the simulators are dissimilar to physiologically recorded pulses.

Algorithms↗

A virtual laboratory notebook for simulation models.

In this paper we describe how we have adopted the laboratory notebook as a metaphor for interacting with computer simulation models. This 'virtual' notebook stores the simulation output and meta-data (which is used to record the scientist's interactions with the simulation). The meta-data stored consists of annotations (equivalent to marginal notes in a laboratory notebook), a history tree and a log of user interactions. The history tree structure records when in 'simulation' time, and from what starting point in the tree changes are made to the parameters by the user. Typically these changes define a new run of the simulation model (which is represented as a new branch of the history tree). The tree shows the structure of the changes made to the simulation and the log is required to keep the order in which the changes occurred. Together they form a record which you would normally find in a laboratory notebook. The history tree is plotted in simulation parameter space. This shows the scientist's interactions with the simulation visually and allows direct manipulation of the parameter information presented, which in turn is used to control directly the state of the simulation. The interactions with the system are graphical and usually involve directly selecting or dragging data markers and other graphical control devices around in parameter space. If the graphical manipulators do not provide precise enough control then textual manipulation is still available which allows numerical values to be entered by hand. The Virtual Laboratory Notebook, by providing interesting interactions with the visual view of the history tree, provides a mechanism for giving the user complex and novel ways of interacting with biological computer simulation models.

Computational Biology↗

Mouse acetylcholinesterase unliganded and in complex with huperzine A: a comparison of molecular dynamics simulations.

A 1 ns molecular dynamics simulation of unliganded mouse acetylcholinesterase (AChE) is compared to a previous simulation of mouse AChE complexed with huperzine A (HupA). Several common features are observed. In both simulations, the active site gorge fluctuates in size during the 1 ns trajectory and is completely pinched off several times. Many of the residues in the gorge that formed hydrogen bonds with HupA in the simulation of the complex now form hydrogen bonds with other protein residues and water molecules in the gorge. The opening of a "backdoor" entrance to the active site that was found in the simulation of the complex is also observed in the unliganded simulation. Differences between the two simulations include overall lower structural rms deviations for residues in the gorge in the unliganded simulation, a smaller diameter of the gorge in the absence of HupA, and the disappearance of a side channel that was frequently present in the liganded simulation. The differences between the two simulations can be attributed, in part, to the interaction of AChE with HupA.

Acetylcholinesterase↗

A comparison of 15N NMR relaxation measurements with a molecular dynamics simulation: backbone dynamics of the glucocorticoid receptor DNA-binding domain.

The rapid motions of the backbone of the DNA-binding domain of the glucocorticoid receptor (GR DBD) have been investigated using proton-detected heteronuclear NMR experiments on 15N-labeled protein at pH 6.0 and with a 200 psec molecular dynamics simulation of hydrated GR DBD. The experimental data were interpreted in terms of a generalized order parameter (S2) and an effective correlation time (tau e) for the internal motion of each amide bond. A back calculation, using the same model, yielded the [1H]-14N nuclear Overhauser effects (NOEs) and the 15N spin-lattice relaxation times (T1) from the simulated data. The rapid motions of the backbone turned out to be rather limited and uniform throughout the protein, with a somewhat reduced mobility in the two major alpha-helical regions and a slightly enhanced flexibility for some residues in the first zinc coordinating region. The agreement between the experimental and simulated S2-values was as good as quantitative for most of the residues, except for some residues that were subject to a more large-scale, and in the simulation thus poorly sampled, motion. Examples of such motions that were found in the simulation include jumps of the amide bond of Ile-487 between the charged oxygens of the side chain of Asp-485 and less distinct large scale motions for some of the residues in the extended regions, that were shown to give rise to noisy and/or fast decaying internal reorientational correlation functions. For these residues large differences in the simulated and experimental tau e-values were found, indicating that motions on different time scales were dominating in the experimental and simulated values. The lower (< 0.7) experimental NOEs for these residues could not be reproduced in the simulation and were shown to be a consequence of the lower tau e-values estimated in the simulation. By combining information from the simulation and the experiment a more complete picture of the motions for these residues can be obtained as is illustrated with an estimation of the jump angle and jump frequency for the amide bond of Ile-487.

Amino Acid Sequence↗

Virtual simulation: initial clinical results.

We have developed a graphics-based three-dimensional treatment design system that permits the physician to easily understand which anatomy will be treated for any arbitrary beam orientation. Our implementation of this system differs from others in that the software (the Virtual Simulator) simulates the full functionality of a (physical) radiation therapy simulator allowing it to be easily used by physicians. The details of the of our initial clinical experience with virtual simulation are presented in this paper. Virtual simulation was attempted in 71 patients and completed in 65. In 41/71 patients (58%), the beam orientations chosen differed significantly from those traditionally used in our department. Although virtual simulation lead to traditional radiation portals in the remaining patients, in 23/71 (32%) secondary blocking was designed which was different from that which would have been conventionally employed. Thus, overall, virtual simulation lead to treatment changes in 64/71 (90%) of the patients in whom it was attempted. In 78% of evaluable patients the treatment designed with virtual simulation could be implemented on the physical simulator with a precision of +/- 5 mm (+/- 3 mm for brain and head and neck). Thus virtual simulation allowed both accurate planning and execution of treatment plans that would be difficult to achieve with conventional methods.

Brain Neoplasms↗

Virtual reality simulators in orthopedic surgery: what do the surgeons think?

BACKGROUND: There is increasing pressure to develop virtual reality surgical simulation that can be used in surgical training. However, little is known of the attitudes of the surgical community toward such simulation, and which aspects of simulation are most important. MATERIALS AND METHODS: A postal survey on attitudes to surgical simulation was sent to all New Zealand orthopedic surgeons and advanced trainees. This comprised of 44 questions in 10 sections, using either a visual analogue scale (0 to 10) or free text box replies. Results were analyzed for two sub-groups; surgeons qualified before 1990 and those qualified in or after 1990 or still in training. RESULTS: Of the 208 possible responses, 142 were received, a response rate of 68%. Only four respondents had tried a surgical based simulator. Earlier qualified surgeons were more likely to agree that simulation was an effective way to practice surgical procedures, median score 7.7 versus 5.6 (P = 0.03). Both groups thought the most important task for simulation was practicing angulation/spatial orientation (median score 8.4/10), while a realistic view of the operation was the most important requirement (median score 9/10). Both groups were unconvinced that simulation would impact on their practice in the next 5 years, with this statement being scored lower by later qualified surgeons, median score 2.4 versus 4.1 (P = 0.04). CONCLUSIONS: Orthopedic surgeons in New Zealand are supportive of surgical simulation but do not expect simulation to have an impact in the near future. Intriguingly, later qualified surgeons and trainees are more skeptical than their earlier qualified colleagues.

Adult↗

The effects of previously acquired skills on sinus surgery simulator performance.

OBJECTIVE: The Endoscopic Sinus Surgery Simulator is currently being studied as a tool for otolaryngology resident training. While examining performance patterns on the simulator, we sought to define any relationships that may exist between students' previously acquired skills and their performance on the simulator. METHODS: Twenty-six medical students were enrolled in our study. After completing their trials, they were asked to complete a 28-item questionnaire. This questionnaire included yes/no questions as well as 10-point Likert scale instruments. RESULTS: Only 4 students did not respond to the questionnaire. Significant contributions to simulator performance were elucidated for a number of previously learned skills, but most were short-lived. For example, experienced video gamers were significantly better at hazard avoidance in the simulator's novice mode (P = .03), but their advantage dissipated as they advanced to intermediate mode trials. In addition, students' handedness contributed to simulator performance for only the first 3 trials (P = .04), but this relationship, too, was no longer statistically significant in later trials. CONCLUSIONS: Some study students had skills and characteristics that significantly aided them in their ability to perform surgery on the simulator. However, these benefits were short-lived, and these results suggest that practicing plays a more important and long-standing role than other factors in surgical simulator performance. It follows that surgical simulation should play a more prominent role in surgical education because residents who practice on simulators such as this are, in turn, practicing for the reality of the operating room.

Adult↗

Monte Carlo simulations of supercoiling free energies for unknotted and trefoil knotted DNAs.

A new Monte Carlo (MC) algorithm is proposed for simulating inextensible circular chains with finite twisting and bending rigidity. This new algorithm samples the relevant Riemann volume elements in a uniform manner, when the constraining potential vanishes. Simulations are performed for filaments comprising 170 subunits, each containing approximately 28 bp, which corresponds to a DNA length of 4770 bp. The bending rigidity is chosen to yield a persistence length, P = 500 A, and the intersubunit potential is taken to be a hard-cylinder potential with diameter d = 50 A. This value of d yields the same second virial coefficient as the electrostatic potential obtained by numerical solution of the Poisson-Boltzmann equation for 150 mM salt. Simulations are performed for unknotted circles and also for trefoil knotted circles using two different values of the torsional rigidity, C = (2.0 and 3.0) x 10(-19) dyne cm2. In the case of unknotted circles, the simulated supercoiling free energy varies practically quadratically with linking difference delta l. The simulated twist energy parameter ET, its slope dET/dT, and the mean reduced writhe /delta l for C = 3 x 10(-19) dyne cm2 all agree well with recent simulations for unknotted circles using the polygon-folding algorithm with identical P, d, and C. The simulated ET vs. delta l data for C = 2.0 x 10(-19) dyne cm2 agree rather well with recent experimental data for p30 delta DNA (4752 bp), for which the torsional rigidity, C = 2.07 x 10(-19) dyne cm2, was independently measured. The experimental data for p30 delta are enormously more likely to have arisen from C = 2.0 x 10(-19) than from C = 3.0 x 10(-19) dyne cm2. Serious problems with the reported experimental assessments of ET for pBR322 and their comparison with simulated data are noted. In the case of a trefoil knotted DNA, the simulated value, (ET)tre, exceeds that of the unknotted DNA, (ET)unk, by approximately equal to 1.40-fold at magnitude of delta l = 1.0, but declines to a plateau about 1.09-fold larger than (ET)unk when magnitude of delta l > or = 15. Although the predicted ratio, (ET)tre/(ET)unk approximately equal to 1.40, agrees fairly well with recent experimental measurements on a 5600-bp DNA, the individual measured ET values, like some of those reported for pBR322, are so large that they cannot be simulated using P = 500 A, d = 50 A, and any previous experimental estimate of C.

Algorithms↗

Simulated and NMR-derived backbone dynamics of a protein with significant flexibility: a comparison of spectral densities for the betaARK1 PH domain.

A 7.6 ns molecular dynamics trajectory of the betaARK1 PH domain in explicit water with appropriate ions was calculated at 300 K. Spectral densities at omega = 0, omega(N), and 0.87omega(H) and the model-free parameters were evaluated from the experimental as well as the simulated data, taking the anisotropic overall motion of the protein into account. Experimental and simulated spectral densities are in reasonable general agreement for NH bond vectors, where the corresponding motions have converged within the simulation time. A sufficient sampling of the motions for NH bonds within flexible parts of the protein requires a longer simulation time. The simulated spectral densities J(0) and J(omega(N)) are, on average, 4.5% and 16% lower than the experimental data; the corresponding numbers for the core residues are about 6%; the high-frequency spectral densities J(0.87omega(H)) are lower by, on average, 16% (21% for the core). The simulated order parameters, S(2), are also lower, although the overall disagreement between the simulation and experiment is less pronounced: 1% for all residues and 6% for the core. The observed systematic decrease of simulated spectral density and the order parameters compared to the experimental data can be partially attributed to the ultrafast librational motion of the NH bonds with respect to their peptide plane, which was analyzed in detail. This systematic difference is most pronounced for J(0.87omega(H)), which appears to be most sensitive to the slow, subnanosecond time scale of internal motion, whereas J(0) and J(omega(N)) are dominated by the overall rotational tumbling of the protein. Similar discrepancies are observed between the experimentally measured (15)N relaxation parameters (R(1), R(2), NOE) and their values calculated from the simulated spectral densities. The analysis of spectral densities provides additional information regarding the comparison of the simulated and experimental data, not available from the model-free analysis.

Blood Proteins↗

Evaluation of medical students' performance using the anaesthesia simulator.

OBJECTIVES: A pilot project assessing clinical performance was undertaken using the Anaesthesia Simulation Centre at the University of Toronto. The purpose of this study was to determine the reliability of assessments of medical students' performance using the simulator as an evaluation tool, to compare these assessments to written and clinical evaluations and to elicit student opinion. Simulator assessments were performed at the completion of the anaesthesia rotation. DESIGN: Twenty-four of 177 University of Toronto medical students participated in a videotaped simulator session with an attending faculty. These 24 students were based at Sunnybrook Health Science Centre. During the session, each student worked through one of six predetermined cases involving discrete patient problems based on the list of core objectives. Five evaluators independently assessed each student's videotaped performance using standardized performance evaluation criteria and data were examined for inter-rater reliability. Clinical and written examination marks were compared to simulator assessments. A student questionnaire was administered and descriptive data obtained. SETTING: The University of Toronto. SUBJECTS: Medical students. RESULTS: The intraclass correlation coefficient (ICC) of inter-rater reliability was 0.87. There was poor correlation between the simulator and written examination marks (r=0.19, P=0.38) and between the simulator and clinical marks (r=0.04, P=0.87). The simulator experience was highly rated by students: learning experience 4.6 +/- 0.51, appropriate content 4.4 +/- 0.74, use as evaluation tool, 4.1 +/- 0.92 (1=poor, 5=excellent). CONCLUSIONS: Our pilot data suggest that the simulator is a reliable assessment method for medical students' performance. Further work may justify the inclusion of the simulator as an evaluation and education tool and expanded to incorporate learning objectives of other medical disciplines.

Anesthesiology↗

Stability testing of selected plastics additives for food contact in EU aqueous, fatty and alternative simulants.

Within the framework of the AIR3-CT94-2360 EU-project, the stability of three plastics additives in three EU aqueous and fatty food simulants and in two alternative simulants was studied under various time-temperature conditions. The additives tested were bis(2-ethylhexyl) adipate (DEHA), bis(2-ethylhexyl) phthalate (DEHP) and octadecyl 3-(3,5-di-tert-butyl-4-hydroxyphenyl) propionate (Irganox 1076). The various test conditions included exposures of 10 days at 40 degrees C, 1 h at reflux temperature for all aqueous simulants, 10 days at 40 degrees C and 1 h 175 degrees C for the olive oil and 2 days at 20 degrees C and 3 h at 60 degrees C for the isooctane simulant. Following the exposure, the additive samples were extracted from aqueous simulants with hexane. A sonication step was necessary to ensure maximum extraction of control samples. In the case of the isooctane simulant, the samples were analyzed directly from the simulant. The oil samples were extracted by acetonitrile. The extracts of samples exposed to various heat conditions as well as unexposed spiked controls and blanks were analysed by gas chromatography (GC) on a non-polar (5%--phenyl)-methylpolysiloxane capillary column with high temperature capabilities. The results showed that DEHA, DEHP and Irganox 1076 were stable at 40 degrees C and at reflux temperature in ethanolic or acidic aqueous simulants. The various additives were also stable in the organic isooctane simulant as well as in the fatty simulant olive oil. Studies on the stability of such additives used in food packaging are designed for regulatory purposes as an aid to decide whether the legislation should regulate limits for plasticizers based on a quantity in the food packaging itself or based on an ingested dose by the consumer.

Chromatography, Gas↗

Full modelling of the MOSAIC animal PET system based on the GATE Monte Carlo simulation code.

Positron emission tomography (PET) systems dedicated to animal imaging are now widely used for biological studies. The scanner performance strongly depends on the design and the characteristics of the system. Many parameters must be optimized like the dimensions and type of crystals, geometry and field-of-view (FOV), sampling, electronics, lightguide, shielding, etc. Monte Carlo modelling is a powerful tool to study the effect of each of these parameters on the basis of realistic simulated data. Performance assessment in terms of spatial resolution, count rates, scatter fraction and sensitivity is an important prerequisite before the model can be used instead of real data for a reliable description of the system response function or for optimization of reconstruction algorithms. The aim of this study is to model the performance of the Philips Mosaic animal PET system using a comprehensive PET simulation code in order to understand and describe the origin of important factors that influence image quality. We use GATE, a Monte Carlo simulation toolkit for a realistic description of the ring PET model, the detectors, shielding, cap, electronic processing and dead times. We incorporate new features to adjust signal processing to the Anger logic underlying the Mosaic system. Special attention was paid to dead time and energy spectra descriptions. Sorting of simulated events in a list mode format similar to the system outputs was developed to compare experimental and simulated sensitivity and scatter fractions for different energy thresholds using various models of phantoms describing rat and mouse geometries. Count rates were compared for both cylindrical homogeneous phantoms. Simulated spatial resolution was fitted to experimental data for (18)F point sources at different locations within the FOV with an analytical blurring function for electronic processing effects. Simulated and measured sensitivities differed by less than 3%, while scatter fractions agreed within 9%. For a 410-665 keV energy window, the measured sensitivity for a centred point source was 1.53% and mouse and rat scatter fractions were respectively 12.0% and 18.3%. The scattered photons produced outside the rat and mouse phantoms contributed to 24% and 36% of total simulated scattered coincidences. Simulated and measured single and prompt count rates agreed well for activities up to the electronic saturation at 110 MBq for the mouse and rat phantoms. Volumetric spatial resolution was 17.6 microL at the centre of the FOV with differences less than 6% between experimental and simulated spatial resolution values. The comprehensive evaluation of the Monte Carlo modelling of the Mosaic system demonstrates that the GATE package is adequately versatile and appropriate to accurately describe the response of an Anger logic based animal PET system.

Animals↗

A new performance-curve method for the detection of simulated cognitive impairment.

OBJECTIVE: To evaluate a new performance-curve method for detecting simulated cognitive impairment. DESIGN: The method was based on quantitative analysis of choice reaction times in a series of eight matching-to-sample tasks of graded complexity, in which participants were required to identify which of two comparison stimuli was identical to a simultaneously presented sample stimulus. The stimuli consisted of arrays of letters, the number of letters ranging from 1 to 10 in the eight tasks. METHODS: Mean reaction times of a standardization group of 20 healthy young adults were used to construct regression equations to describe the behaviour of three test groups: 20 healthy individuals instructed to perform to the best of their ability (non-simulators), 20 healthy individuals instructed to simulate cognitive impairment incurred as a result of a head injury (simulators), and 25 patients with a history of closed head injury (patients). RESULTS: There was a linear relationship between individual participants' latencies and the mean latencies of the standardization sample; the patient group showed steeper slopes, and the simulators higher intercepts, than the non-simulator group. A univariate measure of performance, based on the proportionate increase in latency corresponding to a standard increase in the standardization group's latency was able to identify 14/20 simulators while misclassifying 2/20 non-simulators and 2/25 patients. Other measures, including the number of errors made in the choice reaction time task and in recognition memory tasks, and a performance-curve measure based on Raven's Standard Progressive Matrices, were less successful in identifying simulators. CONCLUSIONS: This new performance-curve method may prove to be a useful addition to tests currently used to diagnose simulated cognitive impairment in clinical and medicolegal settings.

Adolescent↗

Validation of GATE Monte Carlo simulations of the GE Advance/Discovery LS PET scanners.

The recently developed GATE (GEANT4 application for tomographic emission) Monte Carlo package, designed to simulate positron emission tomography (PET) and single photon emission computed tomography (SPECT) scanners, provides the ability to model and account for the effects of photon noncollinearity, off-axis detector penetration, detector size and response, positron range, photon scatter, and patient motion on the resolution and quality of PET images. The objective of this study is to validate a model within GATE of the General Electric (GE) Advance/Discovery Light Speed (LS) PET scanner. Our three-dimensional PET simulation model of the scanner consists of 12 096 detectors grouped into blocks, which are grouped into modules as per the vendor's specifications. The GATE results are compared to experimental data obtained in accordance with the National Electrical Manufactures Association/Society of Nuclear Medicine (NEMA/SNM), NEMA NU 2-1994, and NEMA NU 2-2001 protocols. The respective phantoms are also accurately modeled thus allowing us to simulate the sensitivity, scatter fraction, count rate performance, and spatial resolution. In-house software was developed to produce and analyze sinograms from the simulated data. With our model of the GE Advance/Discovery LS PET scanner, the ratio of the sensitivities with sources radially offset 0 and 10 cm from the scanner's main axis are reproduced to within 1% of measurements. Similarly, the simulated scatter fraction for the NEMA NU 2-2001 phantom agrees to within less than 3% of measured values (the measured scatter fractions are 44.8% and 40.9 +/- 1.4% and the simulated scatter fraction is 43.5 +/- 0.3%). The simulated count rate curves were made to match the experimental curves by using deadtimes as fit parameters. This resulted in deadtime values of 625 and 332 ns at the Block and Coincidence levels, respectively. The experimental peak true count rate of 139.0 kcps and the peak activity concentration of 21.5 kBq/cc were matched by the simulated results to within 0.5% and 0.1% respectively. The simulated count rate curves also resulted in a peak NECR of 35.2 kcps at 10.8 kBq/cc compared to 37.6 kcps at 10.0 kBq/cc from averaged experimental values. The spatial resolution of the simulated scanner matched the experimental results to within 0.2 mm.

Algorithms↗

The future vision of simulation in health care.

Simulation is a technique-not a technology-to replace or amplify real experiences with guided experiences that evoke or replicate substantial aspects of the real world in a fully interactive manner. The diverse applications of simulation in health care can be categorised by 11 dimensions: aims and purposes of the simulation activity; unit of participation; experience level of participants; health care domain; professional discipline of participants; type of knowledge, skill, attitudes, or behaviours addressed; the simulated patient's age; technology applicable or required; site of simulation; extent of direct participation; and method of feedback used. Using simulation to improve safety will require full integration of its applications into the routine structures and practices of health care. The costs and benefits of simulation are difficult to determine, especially for the most challenging applications, where long term use may be required. Various driving forces and implementation mechanisms can be expected to propel simulation forward, including professional societies, liability insurers, health care payers, and ultimately the public. The future of simulation in health care depends on the commitment and ingenuity of the health care simulation community to see that improved patient safety using this tool becomes a reality.

Health Knowledge, Attitudes, Practice↗