We evaluated the performance of an optical camera based prospective motion correction (PMC) system in improving the quality of 3D echo-planar imaging functional MRI data. An optical camera and external marker were used to dynamically track the head movement of subjects during fMRI scanning. PMC was performed by using the motion information to dynamically update the sequence's RF excitation and gradient waveforms such that the field-of-view was realigned to match the subject's head movement. Task-free fMRI experiments on five healthy volunteers followed a 2 × 2 × 3 factorial design with the following factors: PMC on or off; 3.0 mm or 1.5 mm isotropic resolution; and no, slow, or fast head movements. Visual and motor fMRI experiments were additionally performed on one of the volunteers at 1.5 mm resolution comparing PMC on vs PMC off for no and slow head movements. Metrics were developed to quantify the amount of motion as it occurred relative to k-space data acquisition. The motion quantification metric collapsed the very rich camera tracking data into one scalar value for each image volume that was strongly predictive of motion-induced artifacts. The PMC system did not introduce extraneous artifacts for the no motion conditions and improved the time series temporal signal-to-noise by 30% to 40% for all combinations of low/high resolution and slow/fast head movement relative to the standard acquisition with no prospective correction. The numbers of activated voxels  in both task-based experiments were comparable for the no motion cases and increased by 78% and 330%, respectively, for PMC on versus PMC off in the slow motion cases. The PMC system is a robust solution to decrease the motion sensitivity of multi-shot 3D EPI sequences and thereby overcome one of the main roadblocks to their widespread use in fMRI studies. •Data quality was assessed in terms of tSNR, RMSE, and task fMRI t-statistics.•Correction improved tSNR by 30% to 40%.•Percent reduction in RMSE as a function of motion level was characterized.•Number of active voxels for motor and visual tasks increased significantly. Subject motion in functional magnetic resonance imaging (fMRI) is the most important cause of temporal instability in the data. Typically, fMRI studies attempt to detect changes from the mean MR signal on the order of 1% and therefore even minor degradation of the data due to motion can mask effects of interest. When motion occurs during an fMRI time series, it is most commonly handled with post-processing methods that assume rigid body motion and attempt to co-register and align all image volumes within the time series . These mslices, which leads to a theoretical SNR improvement proportional to √Nslices compared to the same volume acquired with a multi-slice 2D excitation and readout , assumptions about the type of motion (affine vs deformable), and when the correction is done (retrospective vs prospective). Approaches that use internal data to estimate motion, such as k-space-based or image-based navigators, need additional sequence time to acquire that information, but the demanding requirements in fMRI studies of high spatiotemporal resolution and whole brain volume coverage necessitate that the data sampling be as efficient as possible. The assumption that head movements can be characterized as rigid body translations and rotations is a very good approximation for all areas above the intercommissural (AC–PC) line, and therefore more complicated approaches to motion correction that can account for deformations  are not Here we present an approach to correct motion during 3D EPI scanning for fMRI applications. In light of the constraints noted above, we have chosen a method that uses an external sensor, assumes rigid body motion, and is applied prospectively. The prospective motion correction (PMC) system uses an optical camera to track a marker that is rigidly attached to the subject's head. The motion information is used to realign the imaging field-of-view (FOV) with the subject's measured head position and orientation immediately before each radio-frequency (RF) pulse. The performance of the approach was tested on five healthy volunteers during task-free fMRI scanning, with the following conditions in a 2 × 2 × 3 factorial design: PMC on vs off; 3.0 mm isotropic vs 1.5 mm isotropic spatial resolution; no head movement, intentional slow head movement, and intentional fast head movement. Further testing was done on one of the volunteers during visual and motor task fMRI using a 2 × 2 factorial design of PMC on vs PMC off and no head movement vs head movement. The objective of the study was to evaluate the extent to which the PMC system can improve the quality of the 3D EPI data under these various conditions.The PMC system uses an optical camera  mounted on the inside of the scanner bore to track the motion of a passive Moire phase marker at 80 Hz frame rate . Gratingx–ky plane of data in one echo train using Cartesian sampling and applied linearly ascending phase encoding along the partition dimension, where partition refers to the slow phase encoding direction . Motion data were recorded for use in analysis in all conditions. This information was used to prospectively correct the FOV alignment for the PMC on condition.The type of motion that the volunteers were instructed to carry out was designed to sample as well as possible the full range of motions seen in fMRI studies, from compliant healthy volunteers to more difficult patient populations . Before For the task-based imaging experiments, the fMRI time series data were acquired with the 3D-EPI sequence at 1.5 mm isotropic resolution. The 2 × 2 factorial designed consisted of conditions of PMC on vs PMC off and no head movement vs slow head movement. The visual paradigm used a 10-Hz flickering black/white checkerboard alternately stimulating the left and right visual hemifields. The motor paradigm was a standard finger-to-thumb tapping task where the volunteer alternated blocks of tapping with the left and right hands. For both tasks, block designs of 15-second left stimulation, 15-second rest, 15-second right stimulation, 15-second rest were repeated 5 times for a total scan time of 5 min.The goal of the study was to evaluate the performance of the PMC system as a function of head movement. In order to accomplish this, several metrics were established to quantify both the amount of motion occurring during data acquisition and the image quality resulting from the acquired data.total speed, combined the high temporal resolution camera-measured translations (in mm), x, y, z, and rotations (in degrees), P, R, Y, into a single scalar quantity, S, designed to measure the rate of the motion:The first motion metric, S has the temporal resolution of the camera data. To remove noise due to mechanical scanner vibration and other sources, a low pass filter was applied to the translation and rotation data to remove information above 10 Hz . Note that weighting the rotations by the same amount as the translations is equivalent to assuming a rotational radius of 5.7 cm, which is reasonable considering the typical head size.integrated motion and partition-weighted integrated motion, were designed to create a single estimate of the total amount of motion that occurred throughout the acquisition of one image volume. The integrated motion metric is a simple numerical integration of the total speed metric over the time of each image volume.The next two motion metrics, iS refers to the ith data point of the total speed variable, Δt is the time step between camera samples, and the sum is over all data points within one image volume acquisition. M has the temporal resolution of the image volume acquisition rate and the total speed values are all weighted equally. The next metric, partition-weighted integrated motion, is designed to reflect the fact that the k-space energy is distributed non-uniformly along the partition encoding dimension, and therefore motion occurring during different partition encoding steps will affect the image quality differently. The partition weightings are determined by converting the reference image of the time series into k-space using a Fourier transform and integrating the squared modulus of the k-space values, c, over the jth kx–ky plane:jth partition are then used to create the partition-weighted integrated motion metric:These weightings for the i data points of the total speed variable that are within a single partition and over the j partitions that make up the image volume. Note that because the Fourier transform of the reference image was done on the magnitude of the image, an artificial symmetry is imposed on the k-space that may not have existed in the original complex multi-channel data. This will affect the jk values by a few percent, but was deemed preferable to calculating the weights from the large raw k-space data sets.Here the sums are now over the M and PWM are related to the translation and rotation measurements. The grid lines indicate the timing of the MR data acquisition per image volume and the dot markers on the motion metrics indicate the timing of the central k-space partition.PWM metric. PWM metric being a better predictor of the artifact level than the simple integrated motion metric.PWM value that was at or below the PWM values of the baseline images (before motion commenced). A 3D mask was created to cover the entire brain and exclude signal from the skin surface and background noise. The entire 4D data set was scaled by the mean signal of all voxels within this mask. An RMSE value was calculated for each image volume using the reference image and all voxels within the mask. While the tSNR values gave an indication of the quality of the image data over the entire time series, the RMSE metric reflected the image quality of individual image volumes as a function of the amount of motion that occurred during data acquisition.Two measures of image quality were calculated to quantify the effect that motion had on the acquired data, the tSNR of the time series and the root mean square error (RMSE) of all individual image volumes. Before calculation of the metrics, all 4D image data sets were registered to their respective first image in the 100-volume time series using the Estimate & Reslice algorithm in SPM 8 , and theThe FOV coverage in the head–feet direction was different for the 3.0 mm and 1.5 mm cases. To facilitate comparison between the two types of scans, a common volume was chosen for the analysis that started several millimeters above the top of the brain and covered 48 mm towards the feet (16 slices for the 3.0 mm data and 32 slices for the 1.5 mm data).The data sets from the task fMRI experiments were processed in a standard pipeline using SPM8 . The firThe tSNR results over all twelve experimental conditions are summarized in Similar results are shown in The effects seen in the tSNR distributions are quantified in PWM) values. The data were pooled over all subjects, with each dot representing one image volume. The blue dashed lines represent the fit to the function:A and R are the fitted parameters. Several observations emerge from the scatter plots. The first is that RMSE increased with increasing values of PWM, as would be expected. However, the RMSE values did not increase linearly, but plateaued at some maximum level as PWM continued to increase. The fits to the data indicate that the RMSE values were, on average, lower for PMC on compared to PMC off for comparable values of PWM.While the tSNR values gave an indication of the quality of the image data over the entire time series of each run, the RMSE metric was intended to evaluate the image quality of individual image volumes as a function of the amount of motion that occurred during data acquisition. PWM metric compared to the simpler M metric for predicting motion-related artifacts. The function defined in Eq. PWM and M values for the PMC off motion cases, and r2 values were calculated in all instances. The r2 values were higher for all four cases when PWM was used as the input. The range of r2 values was from 0.61 to 0.77 when using PWM compared to 0.51 to 0.68 when using M.Goodness of fit tests were performed to evaluate the usefulness of the PWM. The plots were generated by averaging the data shown in PWM dimension that were 2.5 mm wide. Only bins that had 5 or more data points were kept. The percent reduction in RMSE was calculated as (RMSEPMC_Off − RMSEPMC_On) / RMSEPMC_Off, and the error bars show the standard errors of the binned RMSE values propagated through the percent difference calculation. The trend over the data sets showed small percent decreases in RMSE at low levels of motion (PWM < 5 mm), and then greater percent decreases in RMSE as the level of motion rises until a plateau was reached. This plateau in percent decrease of RMSE was larger for the slow motion cases (50%–60%) than for the fast motion cases (~ 40%).The results from the two task fMRI experiments are shown in The task fMRI t-score and tSNR values are summarized in histograms in The results presented here demonstrate that a PMC system using an external camera and marker with real-time feed-forward control to the imaging pulse sequence can significantly improve the data quality of 3D EPI images when motion occurs during data acquisition. For all conditions tested at different spatial resolutions and with differing amounts of deliberate head movement, the PMC system was able to improve the time series tSNR by 30% to 40% compared to uncorrected data. The tSNR increases translated into higher functional sensitivity in two separate fMRI test experiments. For the tested cases with no motion present, the PMC system was sufficiently precise and stable that its updates did not degrade the tSNR compared to the no correction cases. Multi-shot 3D EPI sequences are particularly susceptible to data degradation due to motion because of their relatively long acquisition time. Successfully integrating a PMC system to alleviate this problem represents a large step towards making 3D EPI sequences an attractive option for conducting fMRI studies.The metrics developed for analyzing motion were designed to compress the very rich camera motion tracking data down into a lower dimensionality while maintaining enough information to make useful predictions about the effect of motion on the image quality. They have several advantages over previous motion assessment strategies that use the image data to retrospectively estimate the movement between scans . The higPWM, is a good predictor of the level of artifact introduced into individual image volumes by motion when PMC is off. The scatter plots are noisy due to the complicated relationship between motion and image artifact, but a clear trend of increasing RMSE with increasing PWM can be seen. The functional form of Eq. The results shown in PWM metric. This approach has two advantages. First, it does not require that volunteers execute the exact same motion trajectory between “correction on” and “correction off” runs, which is a difficult task in practice. The level of motion present during “correction on” and “correction off” runs can be assessed with the PWM metric to determine if significant differences exist. Second, the performance of the motion correction scheme can be evaluated as a function of motion level. As PWM metric, the entire curve is described.One problem faced by any study attempting to evaluate a motion correction scheme is how to best sample the infinite parameter space of possible motion trajectories. Subject motion seen during fMRI studies can vary according to factors such as the task being performed, whether the subjects are healthy or patients, which particular patient population the subjects are from, how securely the head is immobilized within the RF coil, if the subject is falling asleep during scanning, if the subject is coughing or swallowing in the scanner, and so on. This study design took the approach of instructing volunteers to perform a wide range of motion types that fell within constraints of what has been reported in the literature , and theThe present study only evaluated the PMC system for the case of 3D EPI scanning. A direct extrapolation of these tSNR and t-score results to the more common approach of 2D EPI scanning for fMRI is not trivial given the different imaging parameters that would be used (e.g. longer TR and larger flip angles) and the fundamentally different data acquisition strategy. However, the implementation of the PMC system for 2D EPI scanning or 2D multiband EPI scanning  would beSeveral other groups have implemented and evaluated similar fast prospective motion correction approaches for 2D EPI scanning for fMRI studies. Schulz et al. used a system consisting of three cameras tracking three passive optical markers for prospective motion correction during a leg movement task known to induce correlated head movements . Their eWhile the PMC system shows great promise for reducing motion artifacts, practical limitations exist that may make the method unsuitable for certain fMRI studies. Perhaps the biggest practical issue is securely attaching the tracking marker to the subject's head. A number of approaches to fixating the marker to the subject's skin were tested, for example using an adhesive to attach it to the bridge of the nose or to the forehead, or attaching it to non-prescription eye glasses that the subject was wearing. However, each of these methods showed some degree of uncorrelated motion between the marker and the brain due to the malleability of the skin. Individually molded mini bite bars were therefore chosen for this study, but this may not be a feasible solution for all studies. For example, not all patient populations may tolerate the mini bite bars, it may be impractical to create many individual bite bars for a study involving a large number of subjects, or the mini bite bar set up may hinder certain speech related tasks.The results in Other known contributors to motion-induced errors are related to the fact that the head is moving through inhomogeneous B0 and B1-receive fields, neither of which the PMC system controls. B0 field distortions due to susceptibility changes at tissue boundaries cause well known artifacts of geometric distortions and signal drop out in EPI . Head moFinally, remaining sources of motion-induced error that pose a challenge for the PMC system include non-rigid body motion that can occur, for example, near the lower brainstem or cervical spinal cord ; signal Motion during fMRI studies is a persistent problem that is only partially addressed by standard retrospective image-based correction methods. The PMC system used here represents a further step forward due to its ability to pre-emptively suppress motion artifacts and more accurately characterize head motion. For a 3D EPI implementation, we have demonstrated temporal SNR improvements in the range of 30% to 40% and improvements in the numbers of significantly activated voxels during task fMRI in the range of 70% to 330%. We developed motion quantification metrics that reliably predict image artifact levels due to motion during data acquisition. The methods presented here can be directly extended to all types of fMRI studies, resting state or task-based with 2D EPI or 3D EPI scanning.


Do the complex processes of angiogenesis during organism development ultimately lead to a near optimal coronary vasculature in the organs of adult mammals? We examine this hypothesis using a powerful and universal method, built on physical and physiological principles, for the determination of globally energetically optimal arterial trees. The method is based on simulated annealing, and can be used to examine arteries in hollow organs with arbitrary tissue geometries. We demonstrate that the approach can generate in silico vasculatures which closely match porcine anatomical data for the coronary arteries on all length scales, and that the optimized arterial trees improve systematically as computational time increases. The method presented here is general, and could in principle be used to examine the arteries of other organs. Potential applications include improvement of medical imaging analysis and the design of vascular trees for artificial organs. Their anatomy has been studied for many centuries through the dissection of cadavers, inspection of corrosion casts, medical imaging techniques and computational models. It has been determined that individual arterial bifurcations follow optimality principles that lower metabolic demand locally –6, as derp is the radius of the parent artery, rd1,2 those of the daughter arteries and γ is the bifurcation exponent [in silico growth of vascular trees into a simulated tissue substrate aim to optimize the local properties of individual bifurcations [in silico arterial trees for arbitrary tissue structures, a different approach is needed.The relationship between the radii of vessels in individual bifurcations is well categorized by the equation: exponent ,17,18, wexponent . Severalrcations ,19. A prrcations  and signrcations . The varrcations , so whilAnother method for the generation of large scale arterial trees uses extensive morphological databases ,23. Thesin silico simulation of sprouting angiogenesis to obtain the vascular structure in a fully grown organ would be extremely difficult, as full details of the distribution of tissue and oxygen demands would be needed for all stages of embryonic and childhood development. As organs such as the heart have very small levels of variation in vascular structure over the population, the structure itself is likely to be caused by a process different from that of tumour vascularization. We suggest that this process is an optimum seeking one, and that as such an optimization procedure is required to accurately model it. We examine if, regardless of the complex processes that guide angiogenesis during growth, the final structure of the coronary vasculature in adult mammals is near optimal.A separate class of models exist for use in modelling the growth of tumourous vasculature and the process of vascular remodelling, which involve the direct simulation of sprouting angiogenesis –28. ThesDevelopment of a method which reaches a morphologically accurate solution based solely upon optimization criteria would be useful in vascular research, allowing for the modelling of realistic vascular trees in organs lacking extensive morphological databases. The inability of CCO and extensions to find the global energy minimum, and the subsequent lack of consistent structure (particularly of the larger arteries), is problematic if organ specific vasculature is required. An approach capable of producing an arterial tree, which minimizes pumping power and blood volume, while providing adequate blood flow to critical regions would be invaluable in this regard. This paper goes beyond previous work by introducing a far more flexible and universal method for generation of ‘whole organ’ arterial trees, in any arbitrarily shaped tissue substrate, that obeys both local and global optimization criteria. To identify globally optimized arterial trees, we use a powerful computational technique known as simulated annealing (SA) . Althoug2.The main purpose of any arterial tree is to maintain adequate blood perfusion with minimal total metabolic expense. The suitability of an arterial tree for this purpose is governed by two considerations: (i) as blood is viscous, the power required to pump blood through the vasculature should be minimized and (ii) as energy is required to generate and maintain blood, the volume of blood required should be minimized. Murray's law achieves this for individual bifurcations, but the optimal organization of large numbers of connected bifurcations is far from obvious. The interplay between these competing concerns for thousands of arterial segments leads to a complex optimization problem. Note that in the following, bifurcations will be referred to as nodes, arteries will be referred to as ‘segments between nodes’, and terminal arterioles are referred to as ‘end nodes’.2.1i of the tree must be known to calculate the volume. By assuming a fixed bifurcation exponent, the radii are determined by the topology and only vessel lengths rely on the geometrical arrangement. To calculate the cost, volume must be multiplied by a constant, mb, corresponding to a physiologically reasonable metabolic demand of the same quantity of blood and vascular tissue [mb is taken to be 641.3 J s−1 mm−3 and Vtree is the volume of the entire tree.The first component of the approach involves calculating the power needed to maintain the entire tree, which will be used as a value in the cost function. The power consumption of the tree can be split into two separate parts: the first is the metabolic cost of maintaining the blood volume and tissue associated with the tree, and the second is the power required to pump blood through the tree. The length and radius of each segment (vessel) r tissue . Thus, t2.2p=QR, is followed inside the segments, where Δp is the pressure drop over the vessel, and Q is the flow. The assumption that flow is laminar inside the vessels is justified provided that the typical length of a vessel is much larger than the radius, and that pulsatile flow effects are negligible. Vessels within the simulated trees have a typical length radius ratio of 10, and while in the largest arteries of the tree pulsatile effects may still be present, these rapidly decay so that the vast majority lie within a non-pulsatile regime. We assume both Murray's law and that terminal node flows are constant to simplify calculation of the relevant fluid dynamical quantities: the only quantity which relies on the structure of the tree is the pressure. In a sense, the segments can be considered as connected set of resistors, with the resistance given byr is the radius of the vessel, L its length and μ=3.6×10−3 Pa s the viscosity of blood. The pressures (and hence flows) for every node in the tree can then be found recursively. Wi, the power consumed by each segment i, is then calculated usingTo calculate the power needed to pump blood through the entire tree, we must know the pressure and volumetric flows inside each segment (vessel) of the tree, which can be found by first assuming that Poiseuille's law, Δ2.3ρ=1.06×103 kg m−3 [qrequired=2×10−2 s−1. The total flow into the heart is Q0=4.16×10−6 m3 s−1 [QN=Q0/N, where N is the total number of arterioles (end nodes). The radius of the supply sphere is then calculated via 4πR3supply/3=QN/qrequired. The sphere can be thought of as a microcirculatory ‘black box’ [b). While blood demand is not constant within the myocardium at any single instance of time, the majority of fluctuations are high frequency oscillations which are assumed to be averaged out in the present model [b) is used as a value in the cost function of the SA algorithm. In addition, all voxels not being supplied are given a cost, so that the overall penalty associated with having both unsupplied and oversupplied voxels is chosen to beb is the value of the supply at the voxel and the sum is performed over all the voxels comprising the tissue. In practice, this cost is set to be much larger than all other costs, as any unsupplied tissue would die. Therefore, the terminal nodes spread evenly through the tissue early in the optimization. Other functions may be used, provided that the minimum in the function for each voxel occurs at b=1. The value Cs then defines the fitness of the tree to supply blood, and the penalty for over supplying voxels forms a sort of self-avoidance algorithm, where terminal nodes are encouraged to pack the tissue as densely as possible without overlapping. A benefit of this method is that it allows easy integration of medical imaging into the model, as well as providing an easy method for differentiating tissue with different blood supply demands.The primary purpose of the vascular tree is to supply blood; thus it is important that terminal nodes are correctly dispersed inside the tissue. Initially, terminal nodes are randomly distributed inside the tissue, with each node having associated with it a sphere of influence for blood supply. The radius of this sphere is calculated using physiological values for the blood demand of the tissue. The density of myocardium is 3 kg m−3 , and thein−1 g−1  leading 6 m3 s−1 , which cack box’ , where tnt model . The ter2.4Rcutoff, whereby segments with radius larger than Rcutoff may not penetrate the tissue. In the calculations performed in this article, Rcutoff=0.01 mm. To determine which segments with radius greater than Rcutoff have penetrated the tissue we first take a distance transform of the tissue surface for each tissue voxel (a). This provides a second voxel map of the tissue, distinct from the blood supply map, giving a measure of the distance of a point from the surface when it is inside the tissue . For each segment satisfying the radius criteria, a list of voxels that its centre-line penetrates is generated [i, j and k are the Cartesian voxel coordinates taken from the centre-line of the segment. Dijk is the value of the distance transform at that voxel coordinate. In order to create a realistic vascular tree, it must be possible to exclude some segments from penetrating the tissue. For instance, in the case of the heart, it would be unlikely to find a very large artery within the myocardium, and vessels may not penetrate the ventricles; rather, the larger arteries and arterioles lie on the surface of the heart, with only the smaller arterioles and capillaries being found inside the tissue. To mimic this structure, the approach makes use of a cut-off radius ue voxel a. This penerated , along w2.5Pterm to function correctly. A new cost can be devised to ensure this. A suitable candidate isPi is the actual terminal node pressure. In practice, for trees which can be optimized on feasible time scales (i.e. of a few thousand nodes), the pressure drop from root to end node is less than 1% of the total pressure drop of a real arterial tree, with most of the pressure drop occurring over smaller arterioles than those considered here, so it is unnecessary to perform this calculation. When it becomes possible to grow larger trees, the pressure at the capillaries will need to be taken into consideration. This will add a significant computational cost.In physiologically realistic trees, capillary networks should receive a constant pressure 2.6Ai indicates a weighting value which scales each relevant cost. There is no way to analytically determine what weights to use, and the selection of appropriate weights must be found experimentally; however, a few basic principles such as having a very high weight for the blood supply cost and a low weight for the end node pressure cost can guide the process. In principle, As should be infinite, as tissue without supply dies. In this work, we use Aw,v=1×104, Ap=0, As=1×1030 and Ao=100. In this way, As and Ao force the exclusion of vessels and uniform supply of tissue to act like constraints. While the exclusion cost should technically be infinite, as no arteries are found in the ventricles of living humans, it is advantageous to give it a large but finite value. This allows the optimization procedure to identify gradients, giving it extra information and speeding up convergence. This size of the constant for Ao may seem small in this regard; however, its value Co is already raised to the power 6 in equation . The small probability to accept a higher cost tree during update allows the tree to climb out of local valleys in the cost function. The algorithm proceeds by making changes to the tree structure, calculating the change in cost function, and then either accepting or rejecting the change by comparing T starts large and is reduced slowly. If T has been reduced sufficiently slowly, then the global minimum of the cost function is guaranteed to be reached. In practice, the problem space is too large to achieve this in reasonable time, and slightly different trees with very similar cost are found if the algorithm is run with several random number seeds. The most important consideration is the lowest achieved cost. As such, if the structure of trees generated varies between different runs, we always display data from the run with the lowest cost function. As computational power increases, longer runs will be achievable leading to progressively better optimizations. The highest T used here is 1×1010, dropping during the algorithm to 10−5. Typically, a tree containing 1000 nodes will need 109 updates, with a doubling of nodes taking roughly quadruple the number of updates (up to approx. 6000 nodes with one month of CPU time). The large value of As means that the supply of tissue is determined by downhill search, while all other costs are minimized by SA.The total cost 2.8a) and (ii) swapping the parent vessels of bifurcations between different parts of the tree (b). For all nodes but the root node, this move is valid, and performed consecutively it allows all possible tree topologies to be explored. If one of the two nodes is a direct parent of the other  the move is rejected to avoid forming a closed loop. With these two updates, the entire parameter space of the tree can be explored, allowing the algorithm the opportunity to reach a globally optimal solution.The SA algorithm must have access to set of updates which allow it to alter the configuration of the tree. It is necessary to find changes that can be made to the topological and geometrical structure of the tree such that all possible solutions between perfectly symmetric structures and a single trunk vessel can be explored . This is achieved by allowing: (i) repositioning of bifurcations, which is achieved by translating a node in space a and  ordering method was first introduced to classify river systems, but can be applied to any bifurcating system. In standard Strahler ordering, nodes at the end of a tree (in this case the arterioles) are assigned a number 1. At a bifurcation, if two vessels (segments) of the same order meet, then the order of the parent vessel is 1 higher. However, if two vessels of different orders meet, the artery supplying these vessels has the largest order of the two. For example, if two arteries of order 1 meet, then the vessel supplying these arteries has order 2. If an artery of order 3 meets an artery of order 2, then the vessel supplying these arteries has order 3  in the generated tree. This is likely to be due to the combination of integer order numbers and the condition that terminal sites are of constant radius. The result of this constraint is that the terminal radii will only match the anatomical data for a correct choice of the number of arterioles. Figure 5c shows the effects on diameter of increasing the number of arterioles from 500 to 2000. Agreement is generally good, regardless of the number of terminal arteries, and there is a clear trend towards matching the experimental data as simulated tree size increases. Figure 5b compares average vessel length in the model and porcine morphological data as a function of order number. For the largest arteries (high order numbers), the agreement is excellent. Although the lengths of the smaller arteries (Strahler orders <7) in the computer-generated tree tended to be overestimated, this can be easily explained by the fact that the smallest vessels are required to bridge a gap that would normally be filled by inclusion of lower order vessels in a larger simulation. As the number of generated vessels is increased, the agreement with morphological data improves (figure 5d).The mean vessel diameters are shown as a function of order number for a tree comprising 6000 arterioles (12000 vessel segments) in figure 5Previously, the best methods available for the computer generation of arterial trees struggled to recreate realistic branching asymmetry. mb. The largest morphological change is found in the lengths of the larger arteries  there is a huge penalty associated with larger arteries, and so their lengths are contracted. In order to accommodate the reduction in length, the larger arteries must bifurcate more frequently and symmetrically. Additionally, the high volume cost causes the trunk artery to minimize its total length, resulting in a much straighter path across the tissue. Less extreme examples of this behaviour can been seen in mb and straight arteries for large mb.Our final figures show the effect of altering the metabolic energy cost of blood per unit volume arteries . As mb ithe tree . The expmb can also be interpreted as a change in length scale as follows: once the large vessels have been excluded from the tissue and all tissue is supplied, the remaining cost function that is optimized has the formA3 into the cost function to obtainmb is equivalent to changing the length scale, these results suggest that there are likely to be structural differences between species of different sizes, as the power required to pump blood becomes relatively more important than the metabolic demand to maintain blood volume in small vessels. In the absence of morphological data, visual comparison of the coronary arteries tentatively indicates that vessels meander around in smaller species [The change in  species  and that species .4.in silico, which is capable of identifying the near globally optimal configuration of arteries for arbitrarily shaped tissues with heterogeneous blood supply demands. As input, the method only needs information about the tissue structure and the entry point positions of the largest arteries. From this information, the approach generates morphologically and structurally accurate coronary arterial trees at almost every length scale. This is a significant improvement on previous optimization methods, which failed to reproduce the consistent structure found in the coronary arteries. We have shown that the method improves with the number of vessels modelled, so that, as computing power increases, there is a systematic improvement in the accuracy of the generated trees. To our knowledge, no other method can generate realistic arterial trees that closely match morphological data by taking only the shape of the tissue as input, and claim systematic improvement in the generated trees with increased computational power.We have developed a powerful and universal method for growing arterial trees We expect that our method could have several useful applications. Our first application is to use cardiac and partial cerebral vasculature structures (e.g. MCA territory) computed using this method as input to models of embolic stroke and other infarctions, as these models require detailed vasculature structure over a range of length scales which are not available to imaging techniques –52. ThisThere are several other potential applications. Models of arterial trees generated by our method may help to improve the interpretation of medical images though advanced image segmentation techniques. Vessels identified through automatic segmentation techniques can be connected via algorithms such as the one presented . In addiWe also speculate that the algorithm could be of use in designing the structures of vasculature for artificial tissues. Once the very difficult and intricate process of making networks of vessels in artificial tissue has been achieved –58, the


Two types of ultra high energy resolution neutron scattering instruments, the backscattering spectrometer and the spin echo spectrometer, are described. Examples of the types of research which can be done with these instruments are given and plans for a cold neutron backscattering spectrometer which will be built in the NIST Cold Neutron Research Facility (CNRF) are discussed. It is hoped that this information will be of use to researchers considering neutron scattering experiments at NIST. The first neutron scattering instrument to operate in this range was a backscattering spectrometer built at the Munich reactor around 1970 which had an energy resolution of 0.425 µeV  λ3HL. In order to scan time, the magnetic field H is varied.The NSE technique  uses the S :I=H/H ~ 10−5) and other conventional neutron scattering components . Flippers are used to prepare the neutron spin direction before, and after the two precession coils by rotating its direction.The main components of an NSE instrument ,11 see  are the Sinc measured by the backscattering spectrometer is the space and time Fourier transform of the self-correlation function sG which represents the probability that a particle which was at the origin at time t =0 is at position r at time t. Thus when devising a model of a diffusional process, it is only necessary to con-sider the motion of a single atom and not how the motion of that atom is correlated with the motions of other atoms in the system. Another important way of expressing Sinc is in terms of the intermediate scattering function II is the space Fourier transform of sG and is the quantity measured by the spin-echo technique.In this section we first outline basic features of quasielastic neutron scattering and then proceed to illustrate these points with various experimental applications. To date, most quasielastic neutron scattering experiments have been performed using incoherent scattering , due to p is the particle density at position r at time t and D is the diffusion constant. A solution of this equation is given by a self-correlation function of the formIn order to understand qualitatively how diffusion is manifested in a neutron scattering experiment, we will consider some simple models which display all of the basic features of more complex models. (For a more detailed discussion of the models presented here and for a far wider assortment of models see ). First ω = 0 and has an energy width (FWHM) T which is given bySince this represents an exponential decay in time, the time Fourier transform yields a Lorentzian lineshapeρ is the probability of finding the particle at position r at time, t, τ is the time between jumps and the sum is taken over the nearest neighbor sites at distances iℓ. Using the boundary condition ρ = δ(r) makes ρ and sG equivalent, and then the Fourier transform of the previous equation yieldsChudley and Elliott  generaliΓ oscillates in Q with the periodicity determined by the inverse of the jump vectors iℓ. Thus it is possible to determine the microscopic diffusion mechanism via the dependence of the width of the quasielastic scattering on the scattering vector. Another interesting feature is that for small values of Q, Γ ∝ Q2/τ. One can then connect this expression to the macroscopic diffusion constant since D ∝ 1/τ and Γ = 2DQ2 for Fickian diffusion. Γ(Q) for a powder averaged Chudley-Elliott model assuming l Å jumps with that of Fickian diffusion for identical values of the diffusion constant. The possibility of extracting the macroscopic diffusion constant from the small Q region makes it possible to compare quasielastic neutron scattering results with those obtained using other methods and to discern the activation energy 0E via the Arrhenius lawThe most important thing to note is that R. Consider functions if(t) which represent the probability that a particular atom is at site i at time t. These functions may be obtained using a rate equation similar to i. For simplicity we will consider the case of two possible equivalent molecular orientations corresponding, for example, to a water molecule undergoing twofold jumps about its C2 symmetry axis. Then f1(0) = 1, f2(0) = 0 and f1+f2 = 1. The intermediate scattering function is then given byR is the vector between positions 0 and 1. Note that this equation has been divided into two parts. The first decays exponentially in time and thus leads to a Lorentzian component in the quasielastic scattering while the second is independent of time and, therefore, gives a δ-function in energy. This lineshape is displayed in Q, but that the intensity oscillates with the inverse periodicity of the jump length. The intensity of the δ-function component, termed the elastic incoherent structure factor or EISF, oscillates with the same period but out of phase with respect to the intensity of the Lorentzian component. Thus, characteristic differences exist in the scattering from rotational jump diffusion compared to translational jump diffusion where the lineshape is a single Lorentzian. It is worth pointing out that the δ-function component arises from the fact that at infinite time, the particle has a finite probability of being in its original position. Thus this δ-function component is a characteristic feature of any diffusion process which is confined to a specific region of space.For rotational motions, one is typically concerned with molecules or ions which contain more than one hydrogen atom. Thus it should be reiterated that to describe the motion, only a single atom need be considered for an incoherent scatterer, since the motions of other atoms are irrelevant even if they are coupled to that of the first . The forR is the diameter of circle on which the diffusion is occurring, θ is the angle between the axis of rotation and Q and i =i2DRΓ with DRrepresenting the rotational diffusion constant. Thus, the scattering function can still be divided into a completely elastic component and a broadened component. However, in this case, the broadened component is a sum of many different Lorentzians of varying widths. Therefore, the total width of this component may vary somewhat in Q due to the trade-off in intensity between the various Lorentzians. The EISF’s of the two models discussed here are displayed in Q. This is simply a manifestation of the fact that the EISF represents the Fourier transform of the self-correlation function for infinite times. For a two-site model the probability is 0.5 that the particle has its original orientation, therefore the EISF only drops to 1/2, but for the rotational diffusion model the EISF eventually drops to zero since there are infinitely many possible sites on a circle. In principle it is possible to tell if a particle is undergoing rotational jumps or continuous rotational diffusion on this basis alone. In practice one usually cannot reach Q’s which are high enough to distinguish continuous diffusion from discrete many-fold jumps.The microscopic rotational mechanism need not be as well-characterized as it was for this simple example. For instance, if the static potential fluctuates due to phonons, the idea of a single jump frequency needs to be replaced by a distribution of residence times. This situation is called rotational diffusion since the self-correlation function obeys the diffusion equation if the residence time is short. Then for uniaxial rotational diffusion, it can be shown thatI is often expressed as the density-density correlation between monomers:βjr(t) is the position of monomer j in polymer β at time t, pN and N are the total number of polymers and the number of monomers per polymer chain respectively. Its initial value is the elastic  structure factor: S=I. I increases with Q2 which is also observed in In polymer research the intermediate scattering function I is called the first cumulant:S and which can readily be modelled for various polymer systems. Many approaches are used: the Kirkwood-Riseman (KR) equation for polymer solutions, the dynamic Random Phase Approximation NN jumps. In a model of this type only the jump vector between the original and final sites is relevant. The details of what happens in between are forgotten. The dashed lines in β-Ti is dominated by 1/2[111] jumps into nearest neighbor vacancies, however a small additional fraction of jumps into second nearest neighbor positions is also consistent with the data.When plotted as a function of l et al. ,20 have Q can be attributed to multiple scattering effects. Attempts were also made to fit the data to a model which allowed for 120° and 180° jumps in addition to 60° jumps with equal probabilities. However, the EISF determined using this model was consistently larger than expected for sixfold rotations. Thus, these data show that benzene rotates principally by 60° jumps with a correlation time of approximately 30 ns at 210 K. In addition the temperature dependence of the correlation time was found to be consistent with an activation energy of 182 meV determined using NMR.The previous two examples described systems in which the diffusing atoms (Li or Ti) undergo long-range translational motion so that the scattering law consists of a single Lorentzian component. As shown earlier, if the quasielastic scattering is due to rotational jumps, the scattering law is the sum of a δ-function and one or more Lorentzians. An interesting example of this type of system is crystalline benzene which has recently been studied using cold neutron backscatter-ing methods by Fujara et al. . The EISQ limit (QELS), Γ(Q) shows a characteristic Q2 dependence seen in D. At intermediate values of Q , a Q3 dependence of Γ(Q) characterizes the Zimm  Brownian diffusive modes [kBT is the solution temperature in energy units, ηυ is the solvent viscosity and C is a numerical constant that depends on solvent quality and preaveraging of the hydrodynamic interaction . The Q2 to Q3 transition has been observed [Q, diffusion of a single monomer dominates and the Q2 law is recovered again. This last transition (Q3 to Q2) involves scattering vectors that can be reached only with NSE [In dilute (monodisperse) polymer solutions, and at the small ve modes ,22:Γ(Q)with NSE ,24 as shIn semidilute solutions  hydrodynamic interactions between monomers start being screened so that a Rouse description  of polymQ3 power law dependence of Γ(Q) in the intermediate Q region becomes a Q4 dependence [Q. In crosslinked gels, for example, this slow mode disappears so that only fast modes describing local monomer motions remain. Tests of the reptation idea have brought about a better understanding of the viscoelastic behavior of polymer systems.In contrast to the case of dilute solutions, concentrated polymer solutions and polymer melt dynamics are dominated by interchain correlations. At a length scale smaller than the average distance between two entanglement points, the Rouse model (which neglects hydrodynamic interactions) describes chain dynamics well. The pendence . Howeverpendence ,31 whereI and its initial slope Γ(Q) can be related to their bare  counterparts. This approach has permitted the sorting out of the various diffusion coefficients  that are measured by various techniques in various experimental  conditions. Self and mutual diffusion coefficients are measured in dilute polymer solutions and correspond to the diffusion of a single chain and to that of many chains respectively. Inter-diffusion and cooperative diffusion characterize ternary polymer systems comprising, for example, concentrated solutions of two polymers A and B and correspond to the fast and slow modes when taken at the proper limits. The interdiffusion coefficient represents the diffusion of A relative to B while the cooperative diffusion coefficient describes the diffusion of the polymers (both of A and B) in the solvent. Interdiffusion for instance is the dominant mode in phase decomposing blends. It is interesting to note [Q→0 limit (contrary to the definition of a diffusive mode). This is reminiscent of the “optical mode” in multilayer crystalline solids keeping in mind, of course, that the interdiffusion mode is nonpropa-gating.A dynamic Random Phase Approximation (RPA) approach ,33 has b to note  that forN−1/2 with hydrodynamic interactions (dilute solutions) io N−1 in concentrated solutions of short chains in long chains (Rouse dynamics) to N−2 for melts of long chains (where reptation dominates). Recall that N is the number of monomers per polymer chain. The NSE technique is also particularly useful in observing polymer chain stiffness [Q values.Effects of temperature, concentration, molecular weight and chain stiffness on the dynamics of polymer solutions have been investigated. The molecular weight dependence of the mutual diffusion coefficient changes from tiffness ,34 and iThe previous sections described the dynamics of polymer systems that are in thermal equilibrium. The observed  modes are due to Brow-nian diffusion in solutions and in melts. This section, however, briefly describes “real time” dynamics of polymer systems following gradients in temperature   described in the previous sections involves time correlations of the fluctuating density ρ (in Fourier space):ρ:R(Q) of the time dependent structure factor:υS(Q) and ∞S(Q) are the initial and final  values of the structure factor tS(Q). When the concentration fluctuations are small, R(Q) can be simply expressed in terms of the mobility M, the interfacial free energy coefficient K and the inter-diffusion coefficient Dint:Dint. Two main theories describe the molecular weight dependence of Dint: a “slow mode” theory [The intermediate scattering function k theory ,38 descreriments  are actu” theory ,40 based” theory  assumingmV(θ) given byV0 is the height of the barrier and θ is the rotational angle. The Schrödinger equation is then given byB =ħ/2I (I is the moment of inertia), nψ is the wavefunction, and nE are the energy levels. V0 assuming a threefold potential and that the rotating species is a methyl (CH3) group. Here the solid lines represent singly degenerate levels having A symmetry while the dashed lines correspond to doubly degenerate solutions of E symmetry. Basically there are three regimes. The first is where the barrier is zero which corresponds to free quantum rotors characterized by doubly degenerate levels having energies jE ∝ j2 where j is the rotational quantum number. The second is the limit of large barriers where the molecule or ion undergoes harmonic librations which are characterized by triply degenerate levels with nE ∝ (n + 1/2). Here n is the librational quantum number. Perhaps the most interesting region is that between these two extremes which is characterized by the tunnel splitting of the librational ground state and of the excited states resulting from the overlap of the wavefunctions shown schematically in V0 since the overlap of the wave-functions depends exponentially on the barrier. This approximate exponential dependence of the ground state tunnel splitting is shown for both CH3 and CD3 in Perhaps the phenomena most studied using cold neutron backscattering is the rotational tunneling of small molecules and polyatomic ions in solids. In order to understand the origin of this effect consider a molecule in an m-fold potential 3NO2). Nitromethane is an ideal candidate for such studies for several reasons. First the internal barrier to rotation is very small. Thus in the solid phase, intermolecular interactions will dominate the rotational potential. In addition, the molecule is a simple one and will display only one-dimensional rotation. Finally, diffraction studies have shown that the space group of the crystalline material is P212121 which has only one molecule in the asymmetric unit [One of the most interesting applications of tunneling spectroscopy is the determination of the rotational potential felt by the methyl group in solid nitromethane  when neutrons are being counted in the detector.The cold neutron backscattering spectrometer (CNBS) which will be located in the CNRF is shown schematically in 2 to 3 × 3 cm2. It is not presently possible to quantify the length or the angle of convergence of the guide because of uncertainties in supermirror development; however it is hoped that an increase in flux of at least a factor of three will be possible. The neutrons will then impinge on a phase space transformer [Q resolution of the primary spectrometer to that of the secondary spectrometer with current supermirror technology. To overcome this difficulty Schelten and Alefeld [The remaining neutrons will then pass through a converging supermirror guide which will compress the beam cross section from 6 ×15 cmnsformer . This ca Alefeld  have prohη = 2cθ). For the purposes of this simulation, the phase space crystal was chosen to be pyrolytic graphite (d = 3.354 Å and θ0=69.181°) with a thickness of 5 mm. The incident distribution of neutrons was taken to be a 65 K Maxwell-Boltzmann distribution (in accord with measurements of the flux from the cold source) truncated at 4 Å to simulate a Be filter in the incident beam and at 10 Å because wavelengths longer than this have essentially no probability of being diffracted by the moving crystal. This distribution was then multiplied by the square of the incident wavelength in order to account for the fact that θc is proportional to the wavelength. The horizontal and vertical mosaics and the velocity of the graphite crystals were included as input parameters. The reflectivity of graphite was accounted for with the Bacon-Lowde equation for diffraction from ideally imperfect crystals [We have performed Monte Carlo simulations of this device in order to determine the gain expected for parameters relevant to the CNBS at NIST. The beam which emerges from the converging supermirror guide will have a divergence η approximately twice the critical angle of Ni in the horizontal plane  crystal. Note that this does not violate Liouville’s theorem because the orientation, not the volume, of the final phase space element has been changed.Two-dimensional projections of simulated Bragg reflections from a crystal having an isotropic 10° mosaic are shown in The most important information from the standpoint of increasing the flux of backscattering instruments is displayed in Δd/d (see Sec. 2) and therefore increased intensity. A similar result could be achieved by bowing the individual Si crystals, however this results in a more Lorentzian resolution function while the doped crystals result in a more Gaussian lineshape [0.1 Si0.9 monochromator which displaces the elastic peak by ~ 15 μeV will also be available.After deflecting from the phase space transformer, the neutrons will travel approximately 2 m to the focussing monochromator crystals which will be mounted on a Doppler drive. The Doppler motion is necessary to vary the energy of the neutrons which impinge on the sample. The total range of energies available is determined by the maximum velocity of the Doppler drive. The NIST instrument will have a variable energy range (up to a maximum of ~100 μeV). In order to obtain the maximum flux, the neutrons will be focussed by the monochromator onto the sample. However, ineshape . Note thAfter reflecting from the monochromator, the neutrons will pass back through the phase space transformer. This is possible because only half of the chopper is covered with graphite while the other half is transparent to neutrons. Furthermore, the frequency of the chopper is chosen so that time required for the neutrons to travel from the transformer to the monochromator and return is the same as that for the crystals to move out of the beam.2) bank of boron-doped Si analyzer crystals, which focus the neutrons back to the detectors. The focussing and boron doping will be chosen so that the energy resolution of the secondary spectrometer matches that of the primary spectrometer. The detectors are electronically gated so that they are off when neutrons are striking the sample thereby avoiding direct scattering of neutrons from the sample to the detector. The energy transfer is ascertained by measuring the time of arrival of the neutrons at the detector. Since the total distance between the monochromator and sample and the energy of the scattered neutrons are known, the initial energy and therefore the energy transferred by the scattering from the sample can be determined.The neutrons are then scattered from the sample to the large  more suitable for use in the first precession coil (solenoid) where the neutron magnetic moment precesses in a vertical plane. After the sample position, another precession coil makes the neutron spin precess in the other direction. In order to flip the spin direction, a π flipper is used between the two coils (just before the sample). Next, another π/2 flipper is required to rotate the magnetic moment from the radial direction to an axial one before reaching a spin analyzer (array of supermirrors). Finally, neutrons are detected in a position sensitive area detector.The main components of the CNRF-NSE instrument which is still at a preliminary design stage  are descI/I ~10−5 have to be achieved.In order for the NSE technique to work, the “field integral”  must remain constant before and after the sample (therefore creating an “echo”). In practice, it is difficult to make exactly identical main coils to be used before and after the sample, so that besides the main coils, other smaller “correcting” coils are also used. Correction coils are added before the sample to optimize the echo and around the sample to correct for the earth magnetic field. No steel or magnetic materials can be used in making the coils or close to the instrument. Moreover, because very stable DC current supplies are required, current stabilities of the order of dThe CNRF-NSE spectrometer is in the preliminary design stage; detailed designs are planned to start soon.We have presented the operating principles of two ultrahigh energy resolution neutron scattering spectrometers, the backscattering spectrometer and the spin echo spectrometer and have described types of measurements which can be done with these instruments at the Cold Neutron Research Facility at NIST. We have also discussed the basic design of the cold neutron backscattering spectrometer to be built in the CNRF. This information will assist researchers who are considering ultrahigh energy resolution neutron scattering experiments at NIST.


A number of qualifications can lead to employment in Clinical Engineering. A Clinical Engineer (CE) can be an Engineer who has completed an accredited Engineering degree with three years of relevant experience, an Engineering Associate who holds an Advanced Diploma in technical or nursing fields, or an Engineering Technologist who has completed a recognised Science/Technology degree that can work within clinics and/or provide specialised services for clinics –4. One g(i)in instrumentation, the calibration of a parameter is acceptable within a narrow 99 % confidence interval (CI);(ii)in Biology and Physiology, the acceptable range is nominally the 95 % CI; and(iii)all measurements should be within the range of biological and physiological expectations. Uncertainties are physical limitations of the accuracy of measuring devices. Accuracy is the proximity of the measurement to the true value or the reliability of the measurement within an uncertainty. Each device has the precision listed in the specification and precision, the repeatability, or reproducibility of the measurement? The precision of a device should be seen in the number of significant digits the device displays. It would be expected that the more significant digits that a device displays, the more precise the instrument. However, this cannot automatically be assumed to be true and should be tested.The CE is trained to consider both instrumentation  variance and biological  variance in measurements. Some aspects to consider are:A critical consideration of the uncertainty in measurement is that the biological or physiological quantity being measured has an uncertainty that is not dependent on the device’s measurement limitation. This uncertainty depends upon the distribution of the repeated measurements of the subject being monitored. The accuracy is the device’s ability to measure the TRUE value of the physical entity it is measuring. In this editorial we consider three frequently monitored physiological measurements: the Electrocardiogram (ECG); the Blood Pressure; and Pulse Oximetery. Examine their uncertainty in measurement and conclude with a general application of uncertainty to clinical measurements.An ECG monitor can measure body surface potentials down to 0.2 mV with a time resolution of 1 ms, but only displays the waveform to 1 cm = 1 mV resolution; it records the derived and averaged Heart Rate (HR) to ±1 beat per minute (bpm) with a running average computed . The accWith the advent of Heart Rate Variability (HRV), one can use the accuracy of the ECG monitor to determine HRV with a clinical acceptable mean of 141 ± 39 ms (mean and standard deviation) for a healthy subject. This equates to the 95 % confidence of short term variance of time between two consecutive heart beats in healthy adults being 104 ms –8. ThereAnother common and essential clinical measurement is the assessment of blood pressure. A bedside, physiological, non-invasive monitoring device measuring the cuff blood pressure may be a purely mechanical (pneumatic) device or an automated electromechanical device. The basic mechanical device has variances purely based on the physical size of the instrument, where a small dial that measures the pressure has a direct influence on the resolution of the measurement. This measurement is not only affected by instrumentation uncertainty but is also dependent on subjective uncertainty. There are spurious errors of the observer hearing the onset and decay of the Korotkoff sounds or observing the start and end of oscillations on the needle of the aneroid dial. There is also variance in the design control of the device. The instrumentation uncertainty is governed by AS ES 1060.3:2004  and AS/ANS3200.2.30:2001 (automated), where the accuracy of data is stated as a maximum of ±5 mmHg, with a standard deviation of 8 mmHg over 20 repeated measurements , 10. ThiThe more accurate method of measuring blood pressure is the invasive or direct blood pressure device. According to AS/NZS 3200.2.34:1996, the approval and test specification of Medical electrical equipment, the particular requirements for safety of direct blood-pressure monitoring equipment requires an operating range for the pressure transducer to be within a static pressure of 4,000 and −400 mmHg. This standard states that the dynamic pressure at 1 Hz that is reflected in manufacturer specification that the uncertainty of the pressure measurement, be within 4 mmHg, . This mePulse Oxymetery has become the standard, most commonly used, clinical performance indicator of both the circulatory and respiratory systems. The Oxymeter detects the deflected/observed light and analyses the wavelengths of oxygenated and de-oxygenated blood to derive a saturation percentage. This saturation is then mapped to partial pressure of Oxygen in the peripheral arteries. At arterial oxygen saturations above 90 %, the variability between true and recorded saturation is 5 % and, therefore, the 95 % CI for a saturation reading of 95 % is 90–100 %. Below 90 % saturation, when the attention of the clinician is required, the 95 % CI goes up by 10 % . This raThe above examples of ECG, the Blood Pressure and the Pulse Oxymetery are the basic and commonly used clinical measured parameters, These parameters are time variable and the technique for measurement, as illustrated, introduces variability and bias, and all devices have their calibration issues. So we expect a measurement to be of the form.Then we re-consider the above equation as time variant.m errors .The accuracy of a device is its ability to measure the true level of the physiological parameter. The repeatability of accuracy is a measure of its ability to indicate the same value of the measured quantity with repeated measurements. With scientific instruments, poor repeatability can be a sign of poor accuracy, but with medical devices, as illustrated above, poor repeatability is also a sign of wide variance that is inherent in biological systems. Here, the two terms of accuracy and uncertainty are independent and one cannot be replaced by the other. To achieve better measurement, we aim to be more accurate with less uncertainty. Here, the CE ensures, with the annual preventative maintenance schedule, that the measurements of the device are well within the specifications of the manufacturer. The manufacturer’s design control processes produce the precision within the device that has the instrumentation uncertainty of the measurement well within the physiological variance. Accuracy is measured against a gold standard of measurement and the accuracy of a particular instrument is how close the instrument indicates the true value of the quantity. Medical devices have a high accuracy and repeatability but also have a high physiological variance that is dependent on the physiological state of the individual patient. This variance should be indicated by the measuring devices so that it can be properly interpreted and understood by the clinicians.The CE faces a number of uncertainties in clinical measurement. The CE has the skill, along with the clinicians, to understand those variances and uncertainties. The CE can also respond appropriately to the variance in measurement and technically maintain the certainty in the measurements of all devices. This skill is just one of the many skills that the CE professional must develop, and a vital service that is offered to the Health Care Industry that is not offered by third party services on a day-to-day basis.


Errors in power output ranging from −100% to +210% have been reported in a multitude of physiotherapy transducers. Simpler In the phantom, differences in lesion size due to differences in ambient temperature are revealed by visual inspection. A simple temperature scale will correspond to concentric circles of varying radii printed on the phantom. The generated lesion size matches the radius of the corresponding circle at each ambient temperature, giving a visual check as to whether or not the transducer’s power output has changed. A Matlab code has been developed to numerically solve the bio-heat equation in finite differences time domain with a generation term dependent on the induced pressure field. The code generates plots with a color map corresponding to the thermochromic material’s color changing properties, and the acoustic absorber’s acoustic attenuation and thermal diffusivity properties. The attenuation coefficient of the material, provided by Precision Acoustics Ltd, was 28.8 ±2.6 dB∙cm-1∙MHz-1. The thermal diffusivity was tested by Decagon Devices, Inc. using the transient line heat source method, and was determined to be 0.09 ±0.01 mm2/s. The peak positive pressure is adjusted in the simulation so that the lesion size generated by the simulation corresponds to the actual lesion size measured after sonication, giving an estimate of the pressure at focus.A method for creating a simple DQA phantom has been devised. The main goal of the phantom is to verify that the output power of the transducer does not change compared to initial calibration. The end user places the phantom in their transducer system, and sonicates for a set power and time. The power output of the transducer is then checked visually using a system of concentric circles printed on the phantom. This system is a cheap and effective way to produce DQA phantoms, both because of the ease of use, and because the use of TLC makes visual changes in the phantom reversible and reproducible over a long period of time.


Maintenance time is a critical quantitative index in maintainability prediction. An efficient maintenance time measurement methodology plays an important role in early stage of the maintainability design. While traditional way to measure the maintenance time ignores the differences between line production and maintenance action. This paper proposes a corrective MOD method considering several important ergonomics factors to predict the maintenance time. With the help of the DELMIA analysis tools, the influence coefficient of several factors are discussed to correct the MOD value and the designers can measure maintenance time by calculating the sum of the corrective MOD time of each maintenance therbligs. Finally a case study is introduced, by maintaining the virtual prototype of APU motor starter in DELMIA, designer obtains the actual maintenance time by the proposed method, and the result verifies the effectiveness and accuracy of the proposed method. Maintainability, as an intrinsic property that shows how well a product can be maintained, should be strictly controlled in the design stage. Maintenance time is a critical quantitative index in maintainability design, which affects the combat mission success rate and cost of the equipment directly. For example, in military fields, short maintenance time will reduce the downtime caused by maintenance, improve the executing ability of equipment to increase combat efficiency, and also in the field of manufacturing, downtime of product line will cause great loss. But there isn’t a way to verify if the maintenance time can meet maintenance requirements in the design stage. Traditional way to measure the maintenance time by the physical prototypes has many drawbacks.One is that measuring maintenance time by the actual maintenance work relies on physical prototype which is lagged and modifying the design is very difficult in the in the later stage. The other one is that the data used in the cumulative model are usually obtained by the statistical experiment of skilled workers. Convening experienced maintenance personnel is troublesome in the actual work. The development of virtual reality technology provides an effective way to overcome the problem. The application of virtual reality (VR) in maintenance simulation to do analysis and forecasting in the early design phase has been investigated for years. “Virtual maintenance (VM)” is a computer and virtual reality-based application technology that can simulate the maintenance process.Since the 1990s, many studies have tested VM and proposed a number of solutions. Caudell and Mizell proved the effectiveness of using a VR system to provide instructions for wiring harness assembly  .According to Table So the bare-hand operation minimum workspace calculation expression is:Assuming maintenance personnel use standard tools to operate the failed units. The size data of the standard tools can be got through relative industry standard. The with tool operation minimum workspace expression is . We can analyze its basic MOD value and fill the basic MOD value in the third blank space in the property dialogue box, as shown in Fig. Based on this method, the basic MOD value of each MTP can be filled in the property dialogue box. Then, we choose one human task open its Gantt figure, and we can acquire the under ProcessList in P.P.R environment, consumption MOD value of this human task in Fig. After we get the basic MOD value, the next step is correcting MOD value considering the influence coefficients of visibility, workspace and human posture. Taking a screw MTP as an example, the one of the maintenance therbligs is shown in Fig. In the figure, maintenance tool is ratchet wrench, its length is 200 mm, width is 30 mm and thickness is 15 mm. According to the content in “workspace factor analysis”, the minimum workspace is:And the workspace is:So the workspace ratio is:2 = 1.3.And the workspace influence coefficient is k1 = 1.3. We open the human ergonomics tool and choose the RULA analysis tool; the result can be seen in Fig. 3 = 1.5.Opening the tool eye vision, the visibility condition under this MTP can be gained by Fig. As the basic MOD value of this maintenance therbligs is belongs to M2, so the basic consumption time is 2 MOD. The corrective MOD time is 2 MOD. And the value is:The rest can be done in the same manner. Then we can measure all maintenance therbligs MOD values.We can measure the basic maintenance work some therbligs. Therefore through cumulating the maintenance therbligs time, the total time can be gained. The procedure of disassembling APU motor starter can be divided into 8 parts: going up the operation platform, opening seven cap locks, opening the left side cabin door, opening the right side cabin door, screwing 8 hexagon bolts, screwing APU, moving cables and putting APU to the operation platform.With the help of Gantt figures of the 8 basic maintenance works, the basic maintenance work measurement time and corrective time is presented in Table Maintainability is product’s ability to maintain and restore condition according to prescribed procedures and methods to repair under the stated conditions for a given period of time. The prescribed time limit to complete maintenance work is metric to measure good degree of product’s maintainability, which influences the availability of the product directly and influences the combat readiness. For example, in military fields, good maintainability will reduce the downtime caused by maintenance, improve the executing ability of equipment to increase combat efficiency, and also in the field of manufacturing, downtime of product line caused by maintenance will cause great loss, but now there isn’t a useful method to measure the maintenance time in the design stage to verify if the maintenance time can meet maintainability requirement, while traditional way rely on statistic data in the physical prototypes in the later stage, which is lagged, and modifies the design is very difficult. To predict actual maintenance time in the design phase, this paper presents a method for measuring the actual maintenance time through virtual maintenance process simulation for complex product system. Considering unique features of the maintenance, this paper proposes a corrective MOD method to measure time, because VR still exist difference from the reality, it is difficult to simulate the adjustment process of the maintenance personnel, considering the some influence factors such as workspace, visibility and human posture that influence the maintenance operation, this paper modifies the initial maintenance time of each therbligs got from the virtual simulation. Finally a case verifies the effectiveness of the proposed method.


Urinary Incontinence (UI) is a common problem in women. The management of UI in primary care is time consuming and suboptimal. Shift of incontinence-care from General Practitioners (GP’s) to a nurse practitioner maybe improves the quality of care. The purpose of this observational (pre/post) study is to determine the effectiveness of introducing a nurse practitioner in UI care and to explore women’s reasons for not completing treatment.Sixteen trained nurse practitioners treated female patients with UI. All patients were examined and referred by the GP to the nurse practitioner working in the same practice. At baseline the severity of the UI (Sandvik-score), the impact on the quality of life (IIQ) and the impressed severity (PGIS) was measured and repeated after three months Differences were tested by the paired t and the NcNemar test.Reasons for not completing treatment were documented by the nurse practitioner and differences between the group that completed treatment and the drop-out group were tested.(P < 0.001), as did the impact on daily life . Among the IIQ score the impact on daily activities increased 0.73 points (P = 0.032), on social functioning 0.60 points (P = 0.030) and on emotional well-being 0.63 points (P = 0.031). The PGIS-score improved in 41.3 % of the patients.We included 103 women, mean age 55 years (SD 12.6). The Sandvik severity categories improved significantly (P = 0.036), in particular on the scores for social functioning (P = 0.015) and emotional well-being (P = 0.015).The most important reasons for not completing the treatment were lack of improvement of the UI and difficulties in performing the exercises. Women who withdraw from guidance by the nurse practitioner perceived more impact on daily life Treatment by a trained nurse practitioner seems positively affects the severity of the UI and the impact on the quality of life. Women who did not complete treatment suffer from more impact on quality of life, experience not enough improvement and mention difficulties in performing exercises. Urinary Incontinence (UI) is a common problem in women with a prevalence varying from 25 % to 50 % , 2. The According to the guideline ‘Urinary incontinence’ of the The Dutch College of General Practitioners the prevalent treatment for stress- and urge-incontinence is pelvic floor exercises and bladder training respectively . In mixeAdequate UI management according to the guideline is time-consuming. General practitioners (GP’s) may experience a lack of time and knowledge to provide adequate care . AnotherThe last few decades there is a shift going on in care from GP’s to nurse practitioners to meet the rising demands for primary care. It appears that the nurse practitioners can produce the same quality of care and achieve comparable health outcomes as GP’s . At the In a review about the role of a nurse in the care of patients with incontinence, nine of the twelve included studies reported a significant greater reduction of incontinence episode in the intervention group and patients were very satisfied. The nurses in the studies came from different countries and differed from a nurse with a bachelor of science in nursing degree to a nurse practitioner and the education differed from a full 6 weeks course till a short training by a local physiotherapist or behavioral psychologist , 15.Recently also a Dutch study is conducted with nurse involved in the treatment of patients with UI . Local Ndoes the introduction of a nurse practitioner in the treatment of UI in women in primary care lead to an improvement of the UI severity and the quality of life after three months therapy?what are reasons for women not to complete the treatment program given by a trained nurse practitioner and are their differences in patient characteristics between the group that completed treatment and the drop-out group?Nevertheless the effectiveness of nurse practitioner in primary care trained in UI is not clear. Because of this we firstly set up a training program for nurse practitioners to enable them to take care of patients with UI. Secondly we conducted a clinical observational study to establish the effectiveness of both incontinence severity and quality of life. We also study characteristics and reasons of patients not completing the treatment program. Consequently, we formulated the following research questions:We preformed an observational study.In this study a total of 16 nurse practitioners, already working with the GP in GP’s offices, in the eastern part of the Netherlands, undertook a training program in which they learned how to manage female patients with UI. The training program included 1.5 days course, several home assignments and refresher courses after three weeks, three and six months. The nurse practitioners were trained in tasks related to diagnostics, intervention and monitoring of incontinence based on the guideline ‘urinary incontinence’ of the The Dutch College of General Practitioners [Women who asked for help in primary care for symptoms of stress-, urge- or mixed UI were included between June 2009 and December 2010. Patients who underwent an incontinence operation in de past, patients with a pelvic organ prolapse grade IV , a gynecologic malignancy, a neurological disease or unstable mental disorder were excluded from the study.The GP diagnosed prior to the referral to the nurse practitioner, the type of incontinence and excluded other causes of urinary incontinence like urinary tract infections or malignancies. After explanation about the study and informed consent of the patient to participate in the study the GP gave the patients information about the type of incontinence but did not explain treatment option. Because co-morbidities and use of medication can influence UI we also registered them. We compared these data with the prevalence of the same co-morbidities in a standard primary care population according to the Continuous Morbidity Registration Nijmegen (CMR) to known if our study population is a presentation of a general population. The CMR is a very reliable registration system which determines epidemiological numbers according to the incidence and prevalence of diseases in primary care for scientific research and education . BecauseA view days after the consultation with the GP the patients had an appointment with the nurse practitioner. Prior to the first meeting with the nurse practitioner (T0), patients filled out questionnaires to assess the severity of the UI  , 20 and The primary outcome measure was the severity of involuntary urine loss. . The severity of involuntary loss of urine was measured by the total Sandvik-score (i.e. quantity of urine loss multiplied by the frequency) . The SanThe secondary outcome measures were the impact of quality of life and patients appraisal of the severity of incontinence.The impact on the quality of life was measured by the Incontinence Impact Questionnaire (IIQ), a questionnaire highly recommended by the International Consultation on Incontinence (= ICI) and is rated as Grade A  The IIQ To evaluate women’s overall appraisal of the severity of their UI we asked the patients to rate their experience of the severity of their incontinence problem with the Patient Global Impression of Severity (PGIS) into one of four categories  .Improvement in the severity of the incontinence was estimated to occur in 40 % of those in the treatment group compared to 5 % in the group without intervention. Giving a significance level of 3 % and a power of 80 %, 40 participants were needed. We expected a drop out during the trial of 30 % and therefore we set our target at 60 patients.To test for the changes on the total IIQ-scores between T0 and T1 we used paired t-tests. To assess the effect of the treatment on the Sandvik subgroups- and PGIS-scores we used the McNemar test.  In orderTo investigate differences between the drop-out (patients who started the treatment but dropped out during the follow up of three months) and the group patients who completed treatment we used a General Linear Model  with the dependent variables age, the total Sandvik- and IIQ-scores and Chi-square tests for variables type of incontinence, co-morbidity, use of medication and PGIS-scores.Upon consultation, the Medical Ethics Committee (CMO region Nijmegen Arnhem) stated that ethical approval was not necessary because of the non-invasive character of the study (CMO-nr 2010/460).One hundred and three women entered the treatment program. Thirty-three of them dropped out before the 3 months appointment. Additionally, three patients stopped treatment before the three month appointment because the UI sufficiently improved or they didn’t fill out the T1 questionnaires  patients regularly postponed micturition. In addition, seven (6.8 %) patients had mobility constraints. The average number of caffeine intake was 3.6 cups a day (SD 2.6) and the average number of alcohol intake was 0.8 units a day (SD 1.5), which is quite common in the Netherlands.Not all patients completed all questionnaires. Fifty-seven (85.1 %) patients completed the Sandvik-score at intake and 3 months. Forty-eight (71.6 %) and 46 (68.7 %) patients completed the IIQ and PGIS at both measurements.(P = 0.005): 23 patients (40.4 %) improved, 3 patients (5.3 %) deteriorated and 31 patients (54.4 %) stayed in the same sub group  (Table (P = 0.032), on social functioning 0.60 points (P = 0.030) and on emotional well-being 0.63 points (P = 0.031). Although the impact on travelling and mobility improved, this difference was not significant (P = 0.082). Also the PGIS-score improved significantly (P = 0.029): there was an improvement for 19 patients (41.3 %), a deteriorated in 4 patients (8.7 %) and in 23 patients (50.0 %) the PGIS did not change . The total IIQ-score was significantly higher in the drop-out group (P = 0.036) compared to the group that completed treatment. The same applied for the IIQ-scores for social functioning (P = 0.015) and emotional well-being  is high but comparable with other studies in which the drop-out rates vary from 11 % to 50 % , 15, 23.A limitation of the current study is that there is no control group involved as in a randomized controlled trial which received usual care from the GP. Several published randomized controlled trial conclude that a control-group without treatment shows no or a slightly improvement of the incontinence . FurtherFurthermore as our study focused on the short term effect of the nurse practitioner guidance, more research needs to be done to determine the long term effects.A trained nurse practitioner involved in the guidance of women with UI seems to have a positive effect on the severity of the UI and the impact of the UI on the quality of life after three months therapy. A major advantage of the Dutch nurse practitioners is that they are working in the GP’s office. Therefore they are familiar to cooperate with the GP. This facilitates nurse practitioners to consult a GP easier when necessary, probably lowers thresholds for patients to seek for help and possibly increases patient’s motivation. Former research shows that patient’s motivation is one of the most important factors for a successful treatment of UI . Nurse POne of the biggest problems of conservative treatment in case of UI is the high withdrawal of the patients. There are several options to improve the approach of UI by involving a trained nurse practitioner. First of all, exercises should be discussed with patients in a comprehensive way. Nurse practitioners should check several times whether patients still know how to perform the exercises and feel comfortable about it. It is also important that nurse practitioners keep in mind that the training program for patients with UI is time-consuming, not always easy to sustain and difficult to implement in daily life. This applies particularly patients with other health related problems.Secondly, it is also important to discuss patient’s expectations about the aim of the guidance by the nurse practitioner. This provides an opportunity to prevent patients for having unrealistic expectations, thereby avoiding possible disappointments and referrals to specialists before the treatment is finished.In conclusion a trained nurse practitioner involved in the guidance of women with UI seems to have a small positive effect on the severity of the UI and the impact of the UI on the quality of life after three months of therapy, especially in patients with little complains. Patients who do not complete treatment experience more impact of the UI on social function and emotional well being. We have to keep in mind the high rate of drop-out. Most important reasons for drop out are lake of improvement and difficulties in performing exercises. Also it is not clear if the improvement is due the nurse practitioner or the ‘treatment’ itself. More research needs to be done in order to determine the long term effects of the nurse practitioner guidance and to determine whether the guidance is superior to a control group with for example usual care.