By spatial modulation of the ASL process it is possible to uniquely label individual arteries over a series of measurements, allowing each to be separately identified in the resulting angiographic images. This separation requires appropriate analysis for which a general Bayesian framework has previously been proposed. Here this framework is adapted for clinical dynamic angiographic imaging. This specifically addresses the issues of computational speed of the algorithm and the robustness required to deal with real patient data. An algorithm is proposed that can incorporate planning information about the arteries being imaged whilst adapting for subsequent patient movement. A fast maximum a posteriori solution is adopted and shown to be only marginally less accurate than Monte Carlo sampling under simulation. The final algorithm is demonstrated on in vivo data with analysis on a time scale of the order of 10 min, from both a healthy control and a patient with a vertebro-basilar occlusion.Arterial spin labelling (ASL) MRI offers a non-invasive means to create blood-borne contrast  In ASL an endogenous ‘contrast agent’ is generated by radio-frequency inversion of the magnetization of flowing blood upstream from the organ being investigated, followed by subsequent imaging of this labelled blood once it has reached the organ. This image is subtracted from another taken in the absence of labelling to remove the static tissue signal and reveal the blood supply, from which quantitative measures of blood flow can be derived . The ASLSome organs, most notably the brain, are supplied with blood by a number of arteries, each artery supplying a different region; commonly referred to as vascular territories. It is of clinical relevance to be able to visualise the blood flow within individual arteries and the territories they supply. A notable example is collateral flow in the ‘Circle of Willis’ whereby blood may pass from one major artery via a communicating artery to feed a different vascular territory. For example, flow from an internal carotid artery may be diverted to a posterior territory normally supplied by the vertebral arteries in the case of vertebral occlusion or stenosis. A number of selective ASL labelling methods have been proposed that can target individual arteries . RecentlN-arteries per class was used to restrict the number of arteries that were assumed to contribute to the signal in a voxel, resulting in greater signal-to-noise ratio (SNR) efficiency and reductions in the number of encoding cycles required.We have previously proposed a general framework for the analysis of VE-ASL data employing a Bayesian solution . It offeThe general framework was demonstrated on VE-ASL imaging of the cerebral vascular territories . HoweverA Posteriori (MAP) solution for the ‘global’ parameters to address issues of computation time. Secondly, we introduce constraints into the inference of artery locations that match those that might be expected from subject movement. Finally, we offer a solution to the general framework that does not involve the computationally costly solution of the global parameters, yet retains many of the robust characteristics of the general framework. This latter option offers a routine alternative to matrix inversion analyses with very minimal increase in computational cost.In this work we present a number of modifications to the existing general framework for VE-ASL analysis that address the issues arising from its use in dynamic angiographic imaging. Firstly, we employ a Maximum 2The full theory for VE-ASL analysis is given in , but a s2.1f represents the sources of signal, s is the vector of (noise-less) measured values and E is the encoding matrix:N encoding cycles produce N images by spatially encoding the signal from M arteries. A conventional control-all image in cycle i would be generated by setting ij m= 1 for each vessel, j, and likewise for a tag-all image by setting ijm = −1. The final column must always be all unity values, since this dictates the contribution of the static magnetization of the tissues to the measured signal. Example encoding matrices for labelling arteries in the neck are shown in The tag-control differencing of VE-ASL can be represented in matrix form :(1)s=Efw2.2cth class using a matrix, cP, in the kth voxel:cL arteries in the cth class, then kcf will be (c L+ 1) × 1 in size. cP will be a matrix of zeros, (M + 1) × (c L+ 1) in size, with a single unity entry in each column that selects individual vessels included in this class . For example, for a 3-artery problem (M = 3), considering pairs of arteries (Lc = 2) the cP matrices for all classes (combination of arteries) are:P matrices mean that only a section of the encoding matrix is considered at a time.The full encoding matrix permits any voxel to receive contribution from all supply arteries. However, this is unlikely in practice since most tissue will be fed by only a subset of the labelled arteries. Analysis should ideally be performed only with a subsection of the encoding matrix representing the appropriate arteries, leading to a better-conditioned encoding matrix and more robust analysis. This can be achieved by including classification within the analysis, where each voxel is assigned a class, each class specifying a unique subset of the supply arteries. This can be described for the 2.3k refers to an individual voxel, tk is the measured data containing N measurements, q is the map of discrete class labels and κ is a specific configuration thereof, thus kκ is a specific class label assigned to voxel k, ϕ is the vector of noise precisions.The estimation of voxelwise class membership and flow contributions can be cast within a Bayesian framework. Assuming white noise the Likelihood, as in , is givec is set to be the proportion of voxels belonging to that class, cπ, as determined from the data. The prior specification includes the requirement that the class proportions must sum to unity. Additionally an automatic relevancy determination (ARD) prior is placed on each class proportion so that where data does not support that class it will be automatically removed from the model (a priori by the acquisition and from the planning angiographic image at the labelling region (see below), in which case Pr(E) = 1. The encoding matrix may be further parameterised, for example in terms of the locations of the arteries in the labelling plane. The encoding matrix parameters being inferred from the data and subject to prior information defined within the Pr(E) term.Application of Bayes’ theorem gives the posterior distribution:for both , making he model . Finallyk,c is the non-normalized class label posterior probability:Marginalization can be performed analytically over all the parameters that vary from voxel to voxel: flow, noise precision and class label in every voxel. This gives:2.4m, for each combination of artery and modulation phase, i.e. for the ith encoded image and jth vessel:g is the 1-dimensional modulation function, xj is the location and vj is the speed of flow in the jth artery, ic, iθ and iD are the centre, direction and scale of the ith encoding. The modulation function can be simulated by numerical evaluation of the Bloch equations for a range of mean flow speeds assuming a parabolic flow profile  where the artery locations from a planning angiographic acquisition are used to form the encoding matrix according to Eqs. MIt)Standard matrix inversion (•BI): Bayesian analysis using fixed global parameters. Estimation of flow contributions using Eq. ‘Bayesian inversion’ (•Bxy): MAP solution of Eq. Bayesian inference of artery locations  for comparison.•BT3). This represents a simple model of patient movement after planning. The transformation can be described by a rotation, θ, and a 2D translation [dxdy]T:Bayesian inference of rigid body transformation of artery locations assuming a 3 DOF transformation (where where the transformation was performed about the centre of the artery locations. Informative priors were applied to the transformation parameters:•BT3v): This is the same as BT3 but with the artery flow speeds, in Eq. Bayesian inference of rigid body transformation and artery flow speeds (Transformation parameters and class proportions were inferred using a MAP procedure via Eq. •BT6). Similar to BT3 but with the entries in the rotation matrix being inferred:Bayesian inference of rigid body transformation assuming a 6 DOF 2-dimensional affine transformation  using code written in-house and was executed as a complied run time on an Intel Xeon Quad core server running at 3.0 GHz . MAP estimation of ‘global’ parameters was made using the BFGS Quasi-Newton method  with a c3.2x and y). These were treated as the locations obtained from the planning acquisition. For data generation these were subject to a two dimensional 3 DOF rigid body transformation with two translations and one rotation drawn randomly from a zero mean normal distribution with a standard deviation of 1 mm for translation and 1° for rotation. Additionally the flow speed in each artery was drawn from a normal distribution with mean 30 cm/s and standard deviation 5 cm/s . An imaging region 25 × 25 × 1 voxels was populated with four arterial segments whose centre and orientation was randomly generated, an example is shown in To test the relative accuracy of the different analysis methods simulated data were generated that approximated a VE-ASL angiographic acquisition. The simulation included 4 arteries in the labelling plane placed at the corners of a square  under a technical development protocol agreed with local ethics and institutional committees. The first subject was a young healthy volunteer with no known neurologic deficit. The second subject was a patient with severe bilateral vertebral artery stenoses scanned according to a protocol approved by the local ethics review board.Prior to VE-ASL acquisition a standard time-of-flight (TOF) image was acquired of the head and neck. This image was used to estimate the locations of the arteries within the labelling plane and set up the modulations used within the VE-ASL acquisition itself. Acquisition was performed using the vessel-encoded pseudo-continuous ASL method of Wong , followeAnalysis was performed using the methods outlined above with the estimated artery locations from the TOF acquisition. The full complex magnitude and phase of the data was used for analysis, since substantial changes in the phase of signal from large vessels are possible, leading to artefacts in magnitude only data. For the methods where ‘global’ parameter estimation was required, the estimation was carried out on only the first time point image from within the dataset. This considerably reduced the size of the data to be processed and thus the computational cost. We used the first frame since it would contain the largest signal, as the ASL label still fills the major arteries at this stage. Flow parameter estimation was carried out using the full 20 time point data. The computation time for the parameter inference phase for each of the methods was recorded to give an indication of the relative speed of the different approaches.44.1MCMC), although the improvement over a MAP solution was relatively small. Bayesian inversion (BI), while resulting in larger errors than the ‘global’ parameter search methods, still offered a marked improvement over standard matrix inversion analysis. Even when matrix inversion was performed using the true artery locations (MIt) the Bayesian inversion  was comparable if not better.4.24.35In this work we have applied the general framework for VE-ASL analysis to dynamic angiographic images. This permits non-invasive visualisation of arteries in the brain allowing each artery’s signal contribution to be separately determined. To avoid the computationally costly MCMC evaluation of ‘global’ parameters in the original solution for VE-ASL perfusion imaging we have adopted MAP estimation. This coupled with only evaluating these parameters on a single frame of the dynamic sequence, leads to more acceptable processing time for high-resolution angiographic data. Typically processing times when performing MAP estimation of ‘global’ parameters up to 600 s were observed for the real data considered. For comparison a similar MCMC analysis would take of the order of 40,000 s on the same hardware. The actual time taken will vary in practice from dataset to dataset because an iterative optimization procedure is involved. An alternative that we have explored is calculating ‘global’ parameters within a mask defined from the tag-control difference signal, including only voxels containing substantial blood flow, across all time frames. Since this typically contains fewer voxels processing time is faster and by using all time frames it would be less sensitive to late arriving blood as might occur in stenotic or occlusive vascular diseases.To improve robustness in a clinical context we modified the original general framework, reducing the number of free parameters associated with the artery locations in the labelling plane. This was achieved by using the artery locations from the planning acquisition, and then modelling transformations that might be expected due to subject motion. In simulation and real data this was shown to confer some improvement in accuracy, although the overall effect was relatively small. However, in some clinical cases there may be an advantage to being able to more closely define the relative locations of the arteries as achieved using the transformations in the BT3 and BT6 solutions. For example, in the patient case there is complete occlusion of the vertebral arteries leading to no signal from these in the resulting images. There is a danger that the Bxy algorithm might shift the vertebral locations to the location of a peripheral vessel that has been unintentionally included in the labelling region. In such circumstances it becomes harder to determine unambiguously from the results that no signal arises from the missing vertebrals, since it may be simply that a stronger signal has been observed from the peripheral vessel. By fixing the relative locations of the arteries it is possible to interpret the zero signal from the vertebrals with greater confidence, but still allow for patient movement.We have shown that it is possible to avoid MAP parameter estimation altogether by calculating flow images from Eq. In this work we have adopted a MAP estimation of the ‘global’ parameters to obtain results within a clinically acceptable time frame. A possible disadvantage of this over the MCMC solution we have taken previously is that information about the uncertainty in the ‘global’ parameters is lost. However, the uncertainty associated with the ‘global’ parameters in this application is not critical. What is required is a point estimate that can be used to recover flow images from individual arteries. Another potential disadvantage is that a MAP method is more liable to find a local rather than the global minimum when compared with MCMC approaches. We might expect the posterior to possess multiple local minima because of the cyclic nature of the modulation functions. It is feasible that there would thus be multiple solutions for the vessel locations that result in very similar flow images. In practice the relatively informative priors used should avert this danger. Additionally the ‘global’ parameter values are not of direct interest (they can be considered nuisance parameters): it is the flow images that are desired. Thus as long as the flow image is correct, whether the estimated vessel locations match the true values or a cyclic equivalent is not an issue.In this work we have considered data that has been acquired with the aid of a planning angiographic image of the labelling region. This image being used to define the encoding cycles to achieve maximum labelling efficiency and allowing the artery locations to be estimated. It may be desirable to have a planning free acquisition, for example using randomly defined encoding cycles as proposed by


Previous nonlinear gradient research has focused on trajectories that reconstruct images with a minimum number of echoes. Here we describe sequences where the nonlinear gradients vary in time to acquire the image in a single readout. The readout is designed to be very smooth so that it can be compressed to minimal time without violating peripheral nerve stimulation limits, yielding an image from a single 4 ms echo.This sequence was inspired by considering the code of each voxel, i.e. the phase accumulation that a voxel follows through the readout, an approach connected to traditional encoding theory. We present simulations for the initial sequence, a low slew rate analog, and higher resolution reconstructions.Extremely fast acquisitions are achievable, though as one would expect, SNR is reduced relative to the slower Cartesian sampling schemes because of the high gradient strengths.The prospect that nonlinear gradients can acquire images in a single <10 ms echo makes this a novel and interesting approach to image encoding. Parallel imaging, the use of locally sensitive receivers to provide encoding, typically aims to reduce scan time by reconstructing images from a reduced number of timepoints.2 image feasible in 4 ms. The proposed trajectories impose a unique timecourse on each pixel in the image by applying rotating nonlinear fields. Pixels with redundant or similar timecourses have an azimuthal symmetry that can be distinguished via receiver coil encoding.To date, these nonlinear fields have primarily had constant amplitude over the readout. Here we present an image encoding strategy that can produce extremely short image acquisition times by using time varied waveforms that collect a single echo, making a 642 datapoints in a minimal amount of time. Rather than producing images from a reduced number of timepoints, the trajectory is designed to minimize the total slew of the acquisition, allowing for high bandwidths that acquire the Nl is the index for coil sensitivity lC. So long as the code of a pixel is unique and the noise is sufficiently low, the magnitude of signal coming from that pixel can be deduced.The shift in point of view that motivated this family of trajectories was to consider gradient encoding as a means of applying a unique phase/magnitude code or signature to each pixel in the image. We refer to this timecourse as the code of that pixel. The code of a pixel at  can be written as: x, that satisfies: Ax = b, where b is the measurement data, A is the encoding matrix, and x is the object or image. A as being assembled row by row. Each row describes the encoding iA being applied when we measured datapoint ib. Thus, each row captures the equation: ixA = ibWe can further justify this assertion by connecting it to the matrix methods that are increasingly used to reconstruct MR images. Typically, the reconstruction problem is defined as the solution, However, we can just as easily describe this same encoding matrix as being assembled column by column. Each column describes the code followed by a given pixel over the full course of the acquisition. From this perspective, the matrix equation can be understood as a decomposition of different timecourses, like those commonly used in fMRI. Requiring a unique code for each pixel is equivalent to requiring that the columns of the encoding matrix be linearly independent to resolve the image. If two pixels have identical codes due to gradient evolution , those pixels “fold” on top of each other. However, just as in SENSE, these pixels can be unfolded so long as the coil weightings on the folded pixels are not identical. In terms of the encoding matrix, the coil weightings create differently weighted versions of the timecourse code, so that previously identical columns become linearly independent.The purpose of such sequences is to impose a unique code on each voxel. Such a scheme should therefore be designed such that voxels with the same gradient code should be distant in space so that the receiver coil weightings may distinguish them. Furthermore, to achieve very fast acquisitions, we have focused on very smooth gradient waveforms that could be played out in a single acquisition window.l = 3, |m| = 3 spherical harmonic, as shown in G1 with a cosine amplitude modulation and G2 with a sine amplitude modulation, we rotate the field through π/3, which returns us to the initial orientation and spins anywhere in the FOV are dephased and rephased in this cycle.One field that produces an interesting code is that of a rotating t samples each dwell time of the acquisition and ω is 2π divided by the total acquisition time. Then the argument of the exponential in x,y), is: We can also solve for this phase code analytically. The gradient as a function of time is: Thus, over the entire rotation, the phase code of any pixel will look like a sine wave. The amplitude of the sine wave will be proportional to its distance from the center, and the starting phase is related to its azimuthal position. 2 + (y−y0)2, with x0 = −.45FOV and y0 = −.19FOV. This field was then played out with an amplitude modulation that was out of phase with field G1 and in phase with field G2. The spatial shape of this additional field, which in practice is created by a linear combination of the x, y, and z2- ½(x2+y2) gradients, is shown in z2, Gx, and Gy remain constant, which corresponds to a constant center placement of the Gz2 field, the changing proportion of G1 causes the saddle of the composite field to shift during the readout. Simultaneously, the changing proportions of nonlinear gradients also cause variations in the topology of the field, from a pure G1/G2 combination, like those shown in 2- ½(x2+y2) gradient. The z2- ½(x2+y2) term is offcenter and thus introduces a steep gradient across the center of the FOV where the G1/G2 gradients are flattest thus allowing us to resolve spins in the center of the FOV.To address this limitation, we added a field with the shape of  by considering the same shapes and number of points but with twice the dwell time, leading to a longer acquisition window 2) by considering the longer acquisition window, but maintaining the dwell time, leading to twice the number of points, and 3) by acquiring more than one echo. In the two echo simulations, the first echo uses linear and second order fields that create G =  (x−x0)2 + (y−y0)2, while the second echo uses the field G =  (x+x0)2 + (y+y0)2. The amplitude modulation and the higher order gradient shapes are otherwise the same.To study higher resolution reconstructions, we also simulated reconstructions with longer acquisition times and higher reconstruction matrix sizes. For 1282 resolution, with noise adjusted to produce an SNR of 150, and using experimental coil receiver sensitivity profiles which were windowed to the diameters of the bore of the coil before being included in the reconstruction matrix. For each single point image, we calculated a metric reflecting the localization of the PSF by calculating the signal intensity at the occupied voxel divided by the mean of signal intensity at all other voxels in the image.To study the point spread function (PSF) properties of the reconstruction, we also performed reconstructions of single point images for each position in the FOV using our simulation for the sinusoidal trajectory. These were also performed at 642, and 1400 Hz/cm3 for the 1st, 2nd, and 3rd order fields, respectively. Because fields are steepest at the edge of the field of view, imaging over larger areas would require lower bandwidth acquisitions and longer readouts, but our projections would apply to normal brain imaging using a head insert to generate the nonlinear fields.To test the limits of fast imaging with this sequence, we also studied a trajectory like that shown in Note that in both these pulse sequence diagrams, the sequences and signals are shown in an arrangement that produces codes like those shown in 2 images of 2 image. The next two columns show reconstructions of acquisition windows that would be twice as long. The longer acquisition window would either result from acquiring the same number of points, but doubling the dwell time, as we show in the second column. This is equivalent to doubling the gradient strength but, relative to the aforementioned acquisitions run at maximum slew, this could only be achieved by increasing dwell time. In the third column, the longer acquisition uses the original gradient strengths and dwell times but acquires twice the number of points. This shows a significant improvement in the reconstruction. Finally we consider acquiring twice the original data over two repetitions of the sequence. In the second repetition, we use a different  for the circularly symmetric field, but this shows little improvement over the longer readout and loses the advantages of acquiring the entire image in a single echo.To achieve higher resolution reconstructions, we studied various trajectory modifications, with those results shown in In addition, we have also calculated and mapped a metric reflecting our ability to localize signal in different parts of the field of view. 2 resolution, but the finer images could be reconstructed by doubling the number of sample points in a single echo. Still higher resolution reconstructions may also require only an extended readout, still acquiring data for the entire image in a single short echo.Dynamically changing the gradient amplitude in sequences that use nonlinear gradients can open a complex parameter space that makes sequence design challenging. Due to memory constraints and the structure of our simulation program, our simulations were only feasible to a 128By focusing on the code of each voxel, we can design sequences that encode the entire image in a single readout. Redundancies in the code are kept spatially separated such that the coil sensitivity profiles from parallel receiver arrays can resolve the resulting ambiguities. While the examples shown here used third order gradients combined with an off-center z2 gradient a wide-range of gradient shapes could potentially be explored to yield single echo images. The important feature is to design dynamic gradient trajectories that impose a unique phase and frequency history on each voxel in the FOV in order to spatially localize each voxel. This approach abandons the constraints that Fourier transform theory conventionally imposes in terms of the data required to reconstruct an image and yields a highly efficient encoding strategy.2 image in as little as 4 ms using only a single echo acquisition.The use of extremely smooth sinusoidally varying gradient amplitudes may make it possible to play these out on very short time scales without violating physiological peripheral nerve stimulation limits. Using these techniques, our simulations suggest that it may be feasible to acquire a 64


Prenatal screening for Down's syndrome is performed using biochemical and ultrasound markers measured in early pregnancy such as the Integrated test using first and second trimester markers. Recently, DNA sequencing methods have been introduced on free DNA in maternal plasma, yielding a high screening performance. These methods are expensive and there is a test failure rate. We determined the screening performance of merging the Integrated test with the newer DNA techniques in a protocol that substantially reduces the cost compared with universal DNA testing and still achieves high screening performance with no test failures.Published data were used to model screening performance of a protocol in which all women receive the first stage of the Integrated test at about 11 weeks of pregnancy. On the basis of this higher risk women have reflex DNA testing and lower risk women as well as those with a failed DNA test complete the Integrated test at about 15 weeks.The overall detection rate was 95% with a 0.1% false-positive rate if 20% of women were selected to receive DNA testing. If all women had DNA testing the detection rate would be 3 to 4 percentage points higher with a false-positive rate 30 times greater if women with failed tests were treated as positive and offered a diagnostic amniocentesis, or 3 times greater if they had a second trimester screening test (Quadruple test) and treated as positive only if this were positive. The cost per women screened would be about one-fifth, compared with universal DNA testing, if the DNA test were 20 times the cost of the Integrated test.The proposed screening protocol achieves a high screening performance without programme test failures and at a substantially lower cost than offering all women DNA testing. The testing of cell-free DNA circulating in maternal plasma offers an effective means of screening for Down's syndrome with detection rates (proportion of affected pregnancies with positive results) of 98% or more and false-positive rates (proportion of unaffected pregnancies with positive results) of about 0.2% or less We here propose a screening protocol arising from, and improving on, an idea previously reported 3] and inhibin-A. Typically the Integrated test uses an hCG  measurement in the second trimester, but in the proposed protocol it is measured in the first trimester instead.The proposed protocol, which is outlined in The proposal provides a practical solution to the problem that while DNA testing is an effective screening method it is expensive and can be done only at a small number of laboratories. We offer a solution to this by using the existing screening tests based on serum markers and an ultrasound marker used at a very low false-positive rate to identify a higher risk group, such that only the higher risk women need to have the DNA testing. Importantly, this entails little loss in screening performance.Screening performance of the protocol was estimated as follows. Multivariate Gaussian distribution parameters  of the screening markers from a large cohort study (the Serum Urine and Ultrasound Screening Study [SURUSS]) 3, hCG and inhibin-A; 85% detection rate for a 5% false-positive rate) For each simulated pregnancy, a risk of being affected with Down's syndrome based on the first stage of the Integrated test  was calculated by multiplying the maternal age-specific odds of having an affected live birth , the cost per woman screened is:-We estimated the cost of the screening protocol per woman as a multiple of the cost of an Integrated test. If a+b = 1, b = 1-a, and after dividing throughout by ITC and rearranging, the cost per woman screened as a multiple of the cost of the Integrated test is given by the following equationBecause a is 75%, P is 10% and the DNA test is 20 times more expensive than the Integrated test, the cost per woman screened as a multiple of the Integrated test cost is 1+[0.97×0.1×(0.75−1)]+20×0.1 = 3.0.So if A similar analysis was performed using the protocol applied to the Combined test.The cost per woman screened as a multiple of the Combined test is The reflex DNA testing protocol proposed here, in which the first part of an Integrated test is used to determine who should receive a DNA test, has a number of advantages. First, it has a high screening performance; while the detection rate may be about five percentage points lower than routine DNA testing, the false-positive rate is about 30 times lower if DNA test failures are considered positive and these women have a diagnostic amniocentesis, or about 3 times lower if these women have a second trimester Quadruple test. Second, all women receive a screening result; there are no failed tests and there is no need to tell some women that they had a failed DNA test and needlessly cause them anxiety. Third, the cost of DNA sequencing for the programme is reduced by 80 or 90%, depending on which of the options is adopted. The cost of continuing the Integrated test would remain, which in a public service context is available at the Wolfson Institute of Preventive Medicine, London, for £35 (about $50), but at present this is substantially less than all women having a DNA test. Fourth, the very low false positive rate means that only about 3 per 1000 women screened would need a diagnostic amniocentesis and in about 2 in 3 a Down's syndrome pregnancy would be diagnosed. Fifth, such a protocol allows for the screening of other pregnancy complications such as pre-eclampsia, identified using immunoassays or heart defects using ultrasound markers.In our analysis we used the results of Palomaki and colleagues  and the overall false-positive rate 0.12% (instead of 0.08%) if 20% of women were selected for a reflex DNA test. There is no advantage in measuring hCG in both the first and second trimesters. The measurement of additional markers such as serum placental growth factor, or ultrasound ductus venosus blood flow or nasal bone would improve the screening performance of the proposed protocol, but these are not routinely used, and therefore are not considered here.Most of the published studies on DNA sequencing as a screening test for Down's syndrome were performed on women who were, for one reason or another, at higher than average risk, but this is not a source of bias as the detection rate and false-positive rate of screening tests using markers that are the consequence of the disorder are independent of the prevalence of the disorder.As experience is gained with the screening protocol proposed in this paper, and if the cost of DNA testing falls, with a lower rate of failed tests, DNA testing could be offered to a larger proportion of pregnancies. At the same time the need for immunoassays and ultrasound measurements currently used to screen for Down's syndrome can be reviewed to assess their value in screening for other disorders such as pre-eclampsia.Reflex DNA testing with the Combined test rather than the Integrated test yields a similar screening performance see  with a sA feature of the proposed screening protocol is that it applies equitably to all pregnant women with the cost averaged over all women screened, regardless of who has a DNA test. This is a practical approach in the context of a screening programme, which is the appropriate way of delivering the service to a population.Our proposed protocol could usefully be linked to interpretive software that would automatically modify the proportion of women selected for reflex DNA testing and provide the appropriate risk cut-off to achieve this. Also, all women who have a DNA test could receive an estimate of the risk of having a Down's syndrome pregnancy, based on a combination of the DNA test result and the first stage of the Integrated test, so the results would be quantitative and not simply be based on a qualitative DNA result. In deriving this risk, the DNA result could be adjusted for relevant factors such as the fetal DNA fraction and maternal weight.In summary, the proposed protocol combines current screening methods with the newer DNA sequencing methods to provide a cost effective strategy for all pregnant women with a very high level of efficacy and safety.Figure S1Protocol for reflex DNA testing in conjunction with Combined test screening.(TIF)Click here for additional data file.Figure S2Protocol for reflex DNA testing in conjunction with Combined test screening in which 20% of women at highest risk using the Combined test receive a DNA sequencing test.(TIF)Click here for additional data file.Table S1Screening performance of reflex DNA tests with the Combined test according to percentage of women having reflex DNA test. (Combined test risk cut-off 1 in 50 for DNA test failures).(DOCX)Click here for additional data file.Table S2Illustration of the cost per woman screened according to the cost of the DNA test, expressed as a multiple of the cost of a Combined test, and the proportion of women who have a DNA test (i.e. positive based on the Combined test).(DOCX)Click here for additional data file.


The predicted value for the thermal degradation temperature for the cured polybenzoxazine based on the telechelic polyetherketone (PEK) monomer was ca. 400°C, in line with the experimental thermal degradation temperature range of 450°C to 500°C. Mechanical Properties of both the unmodified PEK and the telechelic benzoxazines are simulated and compared to experimental values (where available). The introduction of the benoxazine moieties are predicted to increase the elastic moduli in line with the increase of crosslinking in the system.Molecular simulation is becoming an important tool for both understanding polymeric structures and predicting their physical and mechanical properties. In this study, temperature ramped molecular dynamics simulations are used to predict two physical properties  of a previously synthesised and published telechelic benzoxazine. Plots of simulated density  From this series, a representative sample of 2200 Da  was selected, whose balance of properties (high degree of conversion coupled with impressive Tg) looked particularly interesting as a model to study  in the literature To model the precursor oligomer based on the low molecular weight poly(ether ketone) (PEK) , the tarn = 5. To form the cross-linked polymer network (the polybenzoxazine) to different selected degrees of conversion, a curing programme produced in house The Amorphous Cell module within Materials Studio was used to construct an amorphous cell with 12 telechelic precursors with the structural repeat unit shown in g then this ensemble serves this purpose quite well. We have carried out experiments using NVT for several polymeric systems and observed the change in pressure but this deserves fuller treatment in another publication. COMPASS was used with the atomic van der Waals summation, a cut-off at 10.0 Å, a spline width of 3.00 Å and a buffer width of 1.0 Å. The Tg is a second order phase change, which shows a change in thermal expansion coefficient when the temperature and volume of a polymer are plotted g. The process of indicating the best point of gradient change can be quite complex. Hall et al.The temperature ramped MD simulations were performed using the Temperature Cycle option in the Amorphous Cell Protocols. A collection of MD simulations was run over different temperatures, with decrements of 10 K from the starting temperature. The starting temperature was set at 600 K, and a total of 31 MD simulations were performed, ranging between 600 K and 300 K. At each temperature stage a 125 ps MD simulation was created. The first 25 ps of each simulation were used to equilibrate the system and the subsequent 100 ps simulation was used to record the results. In order to confirm that 100 ps was a sufficient timescale to equilibrate the volume of the cell, volume, energy and non-boned energy were plotted with respect to simulation time. This showed that all three parameters converged after 25 ps and remained stable for the duration of the simulation. This does not of course prove that there might be a transition to another stable minimum after this time period but for the purposes of this simulation it was sufficient. The NPT ensemble  with a time step of 1 fs was utilized with the Anderson thermostat in combination with the Parinello Barostat Mechanical properties were calculated using the full trajectory from the MD run in the Discover module, using Analysis, then Mechanical, then static mechanical properties calculation. Several determinations of moduli were taken starting from different initial configurations of the polymer model. Models were energy minimised with a default setting of 50000 steps and the majority of the models finished minimising at around 20000 steps. Mechanical properties were calculated as the average of three separate determinations.α,ω-dihydroxy terminated telechelic monomer by maintaining the stoichiometry of the reaction mixture . Prior to constructing the network, the foundations were laid by preparing in silico the same precursor oligomer    was undei.e. no benzoxazine rings and no crosslinks. The temperature ramped MD study was performed on the model shown in g then a drop in density is noted. This is because the volume of the system changes and as density is inversely related to volume, then an increase in volume relates to a decrease in density. As the Tg is a second order thermodynamic event, it does not have a defined experimental value and a range is often quoted. In the simulation we look to observe a change in density at the point where main chain motion takes place. In the past this was done by inspection of the data but this can be subject to interpretation, so a new method was developed that was less subject to interpretation. The axis on the right hand side of the graph is the transition mid-point certainty, which is calculated from fitting an ellipse to each point, thereby taking into account the uncertainty in both density and temperature and effectively finds the point of maximum deviation in the data. The red line on the graph represents these data. The dataset can be sub-divided to locate the deviations corresponding to the α transition, the Tg and the Td. The method employed is described in greater detail in reference 22.An initial study was performed on the PEK oligomer (the precursor) for which some literature is available to allow comparison to be made. In this paper, we have adopted the following convention: each model is designated by two numbers, the first denoting the % of the chains endcapped and the second denoting the % of those benzoxazine rings that have been reacted to form crosslinks. Thus, the model 53-21 comprises a 3-D network based on oligomers (n = 5) in which 53% of the chains bear benzoxazine rings (the remainder are hydroxyl terminated) of which 21% have been reacted to form crosslinks. The PEK precursor is thus 0-0, −3) at around 50–170°C where there is a marked change in the gradient of the plot, which may correspond to the glass transition temperature , which precedes a more marked drop in density, which appears to correspond to the degradation temperature of 0-0. Again there is a change in the slope in reference 5 at 260°C  using pyrolysis GC/MS and identified 1,4–diphenoxybenzene and 4-phenoxyphenol as products at 450°C Several distinct transitions, corresponding to reductions in density, are visible in the graph. There is a gradual drop in density  were noted and are displayed in d represents the onset of thermal degradation).Two examples of the crosslinked networks are shown  and 8 tod) conventional MD simulations use harmonic potentials for bond lengths and tend to operate well when bond lengths only vary between about 75% of their equilibrium values. This means that they cannot be used to model bond breaking scenarios. Reactive molecular dynamics e.g. in REAXFF When examining the thermal degradation behaviour  at room temperature (for the given configurations).(DOC)Click here for additional data file.


Using this prototype system, an early moisture detection system has been installed in the dome that supports the fresco. The result is encouraging and opens interesting prospects for future research.Non-destructive methods are of great interest for the analysis of cultural heritage. Among the different possible techniques, this paper presents a low cost prototype based on the emission and reception of airborne ultrasound without direct contact with the test specimen. We successfully performed a method test for the detection of brick joints under a XVth century Renaissance fresco of the Metropolitan Cathedral of the city of Valencia (Spain). Both laboratory and  This has been especially true for wall paintings because of their particular vulnerability, as they constitute an external layer which is itself the interface between the support and the environment .http://www.frescosdelacatedral.com) which had been hidden for more than 300 years. In the restoration process the presence of efflorescence was observed and certain parts with deterioration issues due to high humidity were also identified [In 2004, the metropolitan basilica cathedral of St. Mary in Valencia started the restoration of the main chapel and its Renaissance fresco paintings R=ρiϕ is the phase shift. Using simple trigonometric relations, one can obtain the phase shift ϕ as a function of the RMS amplitude of the real part of x (x̂=Re{x}) as:The basis of the proposed method consists in measuring the phase difference produced by the ultrasound reflection at different points of the test specimen under testing. As the signal which drives the emitter is a pure tone, the phase can be easily calculated. The sum of two waves having the same amplitude and frequency but different phase can be written as:iωte has been synthesized and represents the input signal of the emitter. The signal measured by the receiver is normalized in order to use In practice, this method has been implemented offline as part of the post processing. The reference signal 2.2.A 40 kHz Murata Manufactoring Co., Ltd  ultrasonic MA40B8S emitter and a MA40B8R receiver were used. The emitter was driven constantly by a 1.5 volt peak to peak sinusoidal wave. As already mentioned, each of them was mounted forming a 30° angle with the perpendicular axis of the test specimen under study . The traThe input signal is generated with an Agilent Technologies  33220A signal generator. The received signal was ×10 preamplified by a LM324 AC coupled inverting operational amplifier to obtain more than 200 mV Pk–Pk in the receiver and eventually acquired using a digital PC oscilloscope, Pico Technology  model PicoScope 3224. The data acquisition stage is coordinated with an automated positioning system, described below. In order to increase the signal-to-noise ratio, 50 signals have been averaged. Around five periods of long time domain signals have been post-processed to extract both the amplitude and the phase. Thus, disregarding the time needed to move the sensors along the surface, a single point measurement takes less than 50 ms, including averaging.2.3.X-Y-Z positioning was provided by an automated positioning system . Further2 in steps of 3 mm in both Cartesian axes X and Y. Thus, one measurement comprises 138 × 85 mesh points, which corresponds to 11,730 measurement positions. The same XY measure was performed at two different heights. The sensor reference line was established at two different heights, 1 and 2 mm, measured from the lower part of our system to the test specimen surface marked as “h” in The surface measured covers 25.5 × 41.4 cm2.4.The 3D visible light scanning consists in projecting a specific visible light pattern on the objects surface to extract geometrical information from the deformations of this pattern by triangulation –27. We u2.5.The test specimen  was builSome cuts were made on the surface of the test specimen to locate the corners of the bricks.2.6.In order to monitor the microclimate that affects the Renaissance frescoes of St. Mary’s Cathedral of Valencia, ceramic tubes were inserted in the joints between the bricks of the vault that supports these frescoes.Taking advantage of a section of wall where bricks were visible, a template on a transparent plastic sheet was drawn. This plastic was used as a guide of the size of bricks and joints since the arrangement of the bricks beneath the frescoes was known.In areas where we intended to locate the joint a manual scan was performed to mark the points where the phase changes were evident. These points were compared with the template to ensure certainty. Ten points were marked by this technique . Holes o3.3.1.An analysis of the phase shift was performed for two different scans at two different heights from the test specimen. The results of the scan are shown in As shown in The offset values observed in the two experiences are different. This is because the offset value of a position depends on the distance traveled by the wave between the emission and reception. The height variation produces different values of phase shift, although the pattern is identical.i.e., they might be placed at different depths with respect to the test specimen surface. On the other hand the surface of the test specimen is not completely flat, as discussed in the next section and this issue may affect the results.The bricks in the bottom row are not as well defined as those at the top. This may be due to different causes. First bricks have different thickness due to the handmade fabrication process, In addition, we tested another sensor configuration in terms of their orientation. The emission was perpendicular to the test specimen surface and two symmetrical receivers forming an angle to the test specimen were used. However, the results obtained with this configuration did not provide clear information about the position where the bricks are located.3.2.f = 40 kHz, the wavelength is 8.5 mm (using the speed of sound in air at laboratory constant conditions as oc = 340 m/s). This implies that a variation in height between two points produces a delay φ given by:ω= 2π f is the angular frequency, Δh is the height variation and α = 30°  were found meaning that a small part of a brick was perforated.4.Our results show that abrupt changes in the measured phase are well correlated with the limits of bricks allowing a good location of joints (interface zone). Furthermore, the analysis of the topography clearly indicates that the measurements are not just the phase difference due to the specular reflection of the incident beam on the test specimen surface.in situ non-invasive studies of bricks position supporting mural paintings and simple plasters, and could be extended to other antique artifacts such as mosaics, etc. In fact, its simplicity and the low data acquisition time could be put together to obtain real time measurements, which in addition to a position tracking system would enable a fast and versatile non-destructive system.The acoustical method presented here meets the requirements to perform Although this is a preliminary study and more tests and theoretical simulations must be performed to clearly understand the underlying physical phenomenon, the results are sufficiently promising for its application in other areas within the cultural heritage and even in industrial applications for the detection of defects in structures or surfaces.


Hyperthermia is considered one of the new therapeutic modalities for cancer treatment and is based on the difference in thermal sensitivity between healthy tissues and tumors. During hyperthermia treatment, the temperature of the tumor is raised to 40–45°C for a definite period resulting in the destruction of cancer cells. This paper investigates design, modeling and simulation of a new non-invasive hyperthermia applicator system capable of effectively heating deep seated as well as superficial brain tumors using inexpensive, simple, and easy to fabricate components without harming surrounding healthy brain tissues.The proposed hyperthermia applicator system is composed of an air filled partial half ellipsoidal chamber, a patch antenna, and a head model with an embedded tumor at an arbitrary location. The irradiating antenna is placed at one of the foci of the hyperthermia chamber while the center of the brain tumor is placed at the other focus. The finite difference time domain (FDTD) method is used to compute both the SAR patterns and the temperature distribution in three different head models due to two different patch antennas at a frequency of 915 MHz.The obtained results suggest that by using the proposed noninvasive hyperthermia system it is feasible to achieve sufficient and focused energy deposition and temperature rise to therapeutic values in deep seated as well as superficial brain tumors without harming surrounding healthy tissue.The proposed noninvasive hyperthermia system proved suitable for raising the temperature in tumors embedded in the brain to therapeutic values by carefully selecting the systems components. The operator of the system only needs to place the center of the brain tumor at a pre-specified location and excite the antenna at a single frequency of 915 MHz. Our study may provide a basis for a clinical applicator prototype capable of heating brain tumors. Hyperthermia or thermotherapy has often been used alone to induce cancer cell death by elevating the temperature in these cells or as an adjunctive cancer treatment modality to improve the clinical outcome of radiotherapy and chemotherapy ,2. DurinResearch interest in the applicability of clinical hyperthermia in cancer therapies is continuously growing. Local, regional, and whole-body hyperthermia treatment regimens have been under extensive investigation during the past decades and have provided promising results with several types of cancers -6. The qSeveral computational studies have proposed non-invasive hyperthermia applicators to heat superficial tumors ,14. SpecTheoretical studies  and laboIn addition, extensive theoretical and experimental research has been conducted to develop a noninvasive focused hyperthermia system based on the use of a complete ellipsoidal beamformer ,25. In tCareful selection, design and tuning of the antenna used as a source of tissue irradiation in noninvasive hyperthermia applicators is necessary since the presence of the head comprised of lossy soft tissues in the vicinity of the antenna has a considerable effect on the characteristics and the performance of the antenna.In addition, the hyperthermia applicator system should provide efficient power absorption distribution (SAR) and selective heating efficacy in deep seated brain tumors. The SAR is a measure of the rate at which electromagnetic energy is absorbed by brain tissues and is a vital quantity in assessing the effectiveness of hyperthermia. The temperature in brain tissues is usually computed by substituting the SAR values into the Pennes bioheat equation. Knowledge of the temperature distribution in brain tissues is essential since the goal of hyperthermia is to raise the temperature of the tumor without affecting healthy brain tissues.To our knowledge, adequate localization and focusing of energy patterns and the calculation of the temperature distribution in a realistic 3D head model containing a deeply seated as well as a superficial brain tumor due to irradiation by a simple easy to fabricate antenna excited at a single frequency placed in a partial half ellipsoidal noninvasive air filled hyperthermia applicator is still lacking. In this study, we numerically designed a noninvasive hyperthermia applicator system composed of a patch antenna, a partial half ellipsoidal chamber and a head model containing a tumor. The FDTD method was used to compute both the SAR patterns and the temperature distribution in three different head models. Several improvement steps were performed on all of the applicator system configurations to adequately ensure sufficient and focused energy deposition and temperature distribution in the brain tumor. The system is capable of heating deep seated as well as superficial brain tumors by placing the center of the tumor at a pre-specified location (one of the foci) controlled by the operator of the proposed hyperthermia system. The use of a partial half ellipsoidal chamber ensures better head positioning and patients comfort compared to whole ellipsoidals.The proposed focused deep brain hyperthermia model consists of a half ellipsoidal chamber with part of the bottom horizontal walls, coinciding with the major axis, partially covered (60 cm). A vertical cut is removed from the opposite side of the half ellipsoidal chamber leaving room for the head to be placed in the open uncovered part Figure A. The ra7 S/m. The system arrangement ensures better directivity, higher energy deposition and better focusing in the brain tumor.This chamber was based on the interesting focusing properties of ellipsoidal reflectors, where if a light source is placed at one focus of the ellipse; all light rays on the plane of the ellipse are reflected to the second focus with the same path length. The walls of the chamber are modeled as a thin shell of copper (5 mm in thickness) having a conductivity of σ = 5.8 × 10Different chamber model sizes were simulated to ensure better focusing properties in the brain tumor. The final chamber size was selected based on the design that ensures a better localization and maximum SAR deposition at the target region (tumor) in the head. The final model used in this study had a chamber major axis of 100 cm while the distance from the center of the major axis to the top of the chamber was 47.7 cm. Several vertical sections were deducted from the edge of the chamber close to the second focal point where the brain tumor is placed. A vertical section 20 cm to the right of the second focal point was selected where simulations have shown that the focusing properties into the tumor did not improve when sections were made at larger distances.Three head models were used in our computations. First, the average brain model consisted of a two layered sphere representing the simplest head configuration model . The inn1 = 0.595 S/m, ϵ1 = 38.836 and σ2 = 1.21 S/m, ϵ2 = 63.259 respectively. The cancer contrast was 1:1 in the electrical conductivity and relative permittivity compared to the surrounding tissue in the first case. In the second case, the cancer contrast was ~ 2:1 relative to the surrounding tissue in the electrical conductivity and ~ 1.6:1 in the relative permittivity. The 1:1 contrast case was adopted to eliminate any enhancement in the selectivity of microwave absorption in the brain tumor due to the contrast in the electrical properties and was considered a control case to test the focusing ability of the proposed hyperthermia system. This contrast case was tested in the optimized proposed hyperthermia system in the presence of the 3D realistic head model. The second contrast case was simulated based on actual measured electrical properties reported in the literature for brain cancer tissues [2K [The brain tumor conductivity and dielectric constant were assigned two different values of σ tissues ,30. The  tissues . The thesues [2K .r =11.9 (tangent loss tan δ =0.0437) and εr = 1.002 respectively, were designed, analyzed and optimized for use in the brain hyperthermia applicator. The first antenna design consisted of a conducting ground plane (13.5 × 13.5 cm2) and a conducting patch (4.8 × 4.8 cm2) at a distance h = 1 mm from the groundplane. The second antenna consisted of a conducting ground plane (60 × 40 cm2) and a conducting patch (16 × 8 cm2) at a distance h = 4 mm from the groundplane. The conducting patch and the ground plane of each antenna were assigned electrical properties of copper. The polarization of the antenna is along its length.Two patch antennas with two different substrates: a silicone substrate and a foam substrate assigned dielectric constants of ε11) for the two antennas was computed and several optimization steps were performed to fine tune the antenna to resonate at the desired frequency when placed in the hyperthermia applicator system model.Input power was set to 500 W and 50 W for the first and second antennas respectively. Simulations were carried out with harmonic excitation signals. The selected resonant frequency used in our computations was 915 MHz since it was found to be within the range of promising authorized frequency candidates for head and neck applicators . The retS11 — the ratio of power reflected to power input. S11 is typically measured on a decibel scale asThe efficiency of an antenna is mainly dependent on the antenna's return loss Pr is the reflected power and Pi is the input power. Since S11 is measured on a decibel scale, smaller S11 indicates greater power coupled to the brain tissue. The 3D radiation patterns of the foam substrate antenna inside the hyperthermia system model with and without the presence of the head model were also computed.where The SEMCAD X version 14 , a commercial finite-difference time-domain (FDTD) based program, was used to compute the electromagnetic energy SAR deposited in brain tissues and the tumor as well as the thermal profiles in these tissues. The SAR is defined as the power absorbed into the unit mass of tissue.i is the peak value of electric field component. The constants σ and ρ denote the conductivity and mass density of the tissue respectively. The computed SAR values were then substituted as the heat source into the Pennes bioheat equation to compute the temperature distribution in different head models as well as in the tumor. The bioheat equation is represented as follows:Where, Eρ is the density of tissue, c is the specific heat capacity, T is the temperature of tissue, k is the thermal conductivity, Qr is the regional heat delivered by the source (SAR), Qm is the power generated by metabolism, ρbl is the density of blood, cbl is the specific heat capacity of blood, wbl is the blood perfusion, and Tbl is the temperature of blood. B represents the term associated with blood flow and equals ρblcblwbl.where 11 parameters from iteration to iteration and when the difference in the maximum value of multiple subsequent periods has decreased to a few percent. The temperature increase in the human head was calculated for an exposure time of 30 minutes.The entire computational domain is divided into voxels, i.e., small cubical elements. SEMCAD provides the possibility of grid refinement since the grid lines do not have to be spaced homogeneously. A maximum of grid stepping between λ/15 and λ/20 is indicated for sufficient accuracy for a variable grid. The spatial discretization of the computational grid was < 1.5 mm. Grid refinements at small brain structures, antenna and half ellipsoidal chamber were used to increase the accuracy of the model while retaining acceptable computational times and satisfying the stability criterion. In our simulations, a twelve-layered UPML was adopted as the absorbing boundary to truncate the computational domain. Convergence was assessed by monitoring the convergence of the SVarious simulations were carried out at 915 MHz to test the applicability of the proposed hyperthermia system model. Two patch antennas having different substrate materials were used to irradiate three different head models and the field distribution inside the proposed chamber, with and without the presence of the human head model was computed. SAR and thermal profiles were also calculated in different brain tissues as well as in the tumor.S11 for both antennas was calculated and their dimensions were optimized to fine tune the antennas to resonate at the desired frequency.The return loss 11 at 915 MHz.Figure 11 of −11 dB was observed for the second antenna having a foam substrate when the antenna was placed at one of the foci of the hyperthermia chamber model at the desired frequency  which was placed at one of the foci of the hyperthermia chamber model Figure . The antThe focusing properties of the half ellipsoidal chamber were investigated in the presence of the realistic head model containing the tumor. The electric field distribution inside the proposed hyperthermia system is depicted in Figure The SAR was computed in the brain tissues when the deep seated tumor in the head was placed at one of the focal points of the hyperthermia chamber model system and the antenna was placed at the other focal point. In the first configuration, the antenna having a silicone substrate was used to irradiate the head Figure A, B. LocIn the second configuration, the antenna with a foam substrate was placed at the other focal point opposite to the head Figure A, B. In When the ~ 2:1 contrast between the tumor and the surrounding WM case was adopted, a similar SAR pattern was observed in the tumor in both the axial view and the sagittal view Figure A, B. HigIt is also worth noting that the SAR value in the tumor was less than those computed in the two simpler head models due to the complexity of the head geometry and the presence of more brain structures.The brain tumor was placed at a superficial location inside the realistic 3D head model instead of being deeply seated within the brain. This is analogous to a clinical situation where all the physician needs to do is to place the center of the brain tumor wherever it is located in the head at the other focal point of the hyperthermia system. The SAR was computed in the realistic 3D head model with its superficial tumor placed at one of the focal points of the hyperthermia chamber model and the antenna with a foam substrate placed at the other focal point Figure A, B. In It’s very important to calculate the temperature due to hyperthermia therapy process, because the SAR values alone are not sufficient to assess the effectiveness of the hyperthermia therapy process. The SAR values are substituted into the bioheat equation to compute the temperature in different brain tissues. The temperature values were calculated when the brain tumor within the head was placed at one of the focal points of the hyperthermia chamber model system and the antenna placed at the other focal point. In the first configuration, the antenna having a silicone substrate was used to irradiate the head Figure A, B. TheIn the second configuration, the antenna with a foam substrate was placed at the other focal point opposite to the head Figure A, B. In When the ~ 2:1 contrast between the tumor and the surrounding WM case was adopted, a localized temperature of 43.4°C was observed in the tumor while the temperature in the outer CSF layer and ventricles was less than 39°C Figure A, B.Again, another observation worth noting is that the temperature distribution does not coincide with the SAR distribution in brain tissues since the highest temperature exists in the tumor in the sagittal plane  deposited in brain tissues must be high enough to produce sufficient temperature rise in brain tumors. The hyperthermia chamber system should be capable of rising the temperature of brain tumors to values above 42°C without harming surrounding healthy tissues. Therefore, SAR patterns and temperature distribution were computed and compared using two different antenna designs to irradiate three different head models.Two improvement strategies were performed on all of the hyperthermia system configurations to adequately ensure sufficient and focused energy deposition (SAR) and temperature distribution in brain tumors. In the first approach, the head models varied from a very simple spherical head model to a layered concentric spherical model and finally to a more complicated and realistic 3D head model. Each of the head models contained a tumor. SAR distributions in the spherical head models, using any of the two patch antenna configurations, were observed to be different than those computed in the realistic 3D head model. A localized SAR pattern was observed in the tumor placed at the center of the simple spherical head model  only.The antenna design varied from an antenna with a silicone substrate configuration to an antenna design with a foam substrate. Two parameters of the antenna are affected by the substrate material, the size of the antenna and its efficiency . High diWhen a superficial tumor located in the head model was placed at the focal point of the chamber and irradiated by the foam substrate antenna, the proposed air filled hyperthermia chamber model was capable of heating the brain tumor using a single frequency Figure A, B. WhoOur results also revealed that the SAR patterns in brain tissues are not correlated in a simple manner to the temperature distribution in these tissues. Comparing Figures The proposed system is designed to achieve focused power deposition in the tumor through constructive reflections off the upper chamber walls, but selective absorption of the electromagnetic waves takes place and causes power deposition in the ventricles as well. There is not good spatial correlation between SAR and temperature, i.e., the peak temperature in certain brain tissues is not directly related to the peak SAR value and location. Similar observations were reported in other studies due to the exposure of the human head to microwave frequencies ,38,42. TThe proposed hyperthermia treatment system was shown to be effective in heating the target tumor while keeping the healthy brain tissue way below the thermal damage limit. Although hot spots were observed in the ventricles, these temperatures (< 39°C) were below those observed in another study using a time-multiplexed beamforming technique (< 41°C) . The cirThe focusing performance of the proposed hyperthermia system was tested by assigning different electrical properties to the tumor compared to the surrounding tissue due to uncertainties and the lack of precise values of these properties in the literature. Several studies have shown that malignant tissue has a higher electrical conductivity and permittivity than normal tissue in the breast and the human liver at microwave frequencies ,44,45. TThe proposed hyperthermia system caused localized SAR in the tumor for both cases of contrast between the tumor and the surrounding WM. Although the temperature rise in the tumor was less for the 1:1 contrast case as compared to the temperature rise for the ~ 2:1 contrast case Figure , increasIt is also worth noting that, calculating the temperature increase with the Pennes bioheat equation may have some limitations. In particular, the effect of vasculature which causes cooling of surrounding tissues was excluded in our study. However, in order to raise the temperature of the tumor to higher values using the proposed hyperthermia applicator, we only need to increase the input source power to the antenna which will result in higher SAR values and higher temperatures in the brain tumor.21. In future work, experimental SAR verification as well as temperature measurements in different tissues of a phantom head model would be conducted to test the effectiveness of the proposed hyperthermia chamber model.We have built the hyperthermia chamber system and the antenna with a foam substrate using simple inexpensive materials. Preliminary proof of concept was achieved by placing another antenna at the location of the brain tumor and measuring the SWe utilized the FDTD method to design, model and simulate a low cost and easy to fabricate noninvasive air filled hyperthermia applicator system capable of heating deep seated as well as superficial brain tumors. Accurate modeling of the head geometry  is of vital importance since simple models do not correctly predict SAR patterns. Careful design and selection of the antenna as well as the partial half ellipsoidal chamber proved suitable for raising the temperature to sufficient therapeutic values in the target tumor within the brain. Our results may form the basis for a clinical prototype. The operator of the proposed hyperthermia system only needs to place the center of the brain tumor at a pre-specified location (one of the foci) and excite the antenna at a single frequency of 915 MHz.The authors declare that they have no competing interests.All authors contributed equally to this work. All authors read and approved the final manuscript.


Buccaneer software are described: the use of a database of protein fragments in improving the model completeness and the assembly of disconnected chain fragments into complete molecules.Two developments in the process of automated protein model building in the  Buccaneer software are presented. A general-purpose library for protein fragments of arbitrary size is described, with a highly optimized search method allowing the use of a larger database than in previous work. The problem of assembling an autobuilt model into complete chains is discussed. This involves the assembly of disconnected chain fragments into complete molecules and the use of the database of protein fragments in improving the model completeness. Assembly of fragments into molecules is a standard step in existing model-building software, but the methods have not received detailed discussion in the literature.Two developments in the process of automated protein model building in the  The developments are the following.α trace to main-chain models, the building of missing loops and termini, and the correction of residue insertions and deletions. This library has been implemented for loop building in the Coot software  An efficiently searchable database of protein fragments which may be used for diverse purposes including the conversion of a C(ii) The automated ‘tidying’ of a fragmentary autobuilt protein model, with the aim of reducing the manual effort required to complete the model. Automated model building sometimes leads to models which may consist of multiple disconnected fragments, especially at low resolution or when disordered loop regions are not visible in the electron density. These fragments must be assembled into one or more molecules, which may involve the application of symmetry operators and cell translations to some of the fragments. In the case of noncrystallographic symmetry (NCS) it is also necessary to assign the fragments to different copies of the molecule.This paper outlines two developments of relevance to the problem of automated protein model building. The initial application of these techniques in the 1.1.The use of databases of protein fragments in the determination and validation of atomic models is well established in both manual and automated model building.OOPS for the validation of the protein backbone trace.Kleywegt & Jones 1996 describeα positions alone, although Payne . The database is optimized for very fast homology searches, allowing the use of a much larger database than in previous work. The use of a much larger database also provides the potential to perform searches restricted by residue-type filters without compromising coverage beyond usefulness.1.2.Automated model building typically produces as an intermediate result a set of protein-chain fragments, some of which may have been docked into the protein sequence. Ultimately, these will need to be assembled into molecules. A problem arises in determining how the fragments are connected to one another. When protein molecules are tightly packed together the molecule boundaries may not be obvious, and as a result it is possible to link fragments which belong not to the same chain but rather to symmetry-related chains. If the density for the link is obvious, this step may be performed by automatic or manual model completion; however, this is often not the case.The problem becomes more complex in the case of noncrystallographic symmetry (NCS). In this case, the fragments must also be assigned to the correct NCS copy of the molecule, as well as to the correct asymmetric unit. The problem may be further complicated in the case of hetero-oligomers (protein complexes consisting of heterogeneous sequences), although this is mainly a bookkeeping problem.ARP/wARP  Finding Cα atoms (or input chains) are grown by adding residues at either end, guided by the electron density and constrained by the allowed region of the Ramachandran plot.(ii) Growing fragments: the candidate C(iii) Joining fragments: overlapping fragments are joined to make longer chains.(iv) Linking fragments: nearby N- and C-termini are examined to see if they can be linked by inserting one or two additional residues.(v) Assigning sequence: likelihood comparison between the density of each residue in the work structure and the density from residues of a reference structure is used to identify the likelihood of each residue being of a particular type. Comparison with the known sequence allows longer fragments to be matched to the sequence.(vi) Correcting sequence: insertions and deletions in the model as identified in the sequence-assignment step are corrected by rebuilding to add or delete a residue where possible.(vii) Filtering fragments in poor density: residues which have not been docked into the sequence and are in poor density are removed.(viii) Building NCS: any NCS relationships found in the model are used to extend existing chains by combining all of the NCS-related chains.(ix) Pruning fragments: fragments which provide inconsistent interpretations of the same electron density are examined. The poorer fragment is removed.(x) Rebuilding: side-chain atoms and carbonyl O atoms are added to the model.This process is repeated over several cycles. In subsequent cycles, the finding step is modified to preferentially find Cα positions which are in regions where no model is present.The 2.A library of real protein fragments of arbitrary length is employed to interpret electron density and correct existing models. In order to support both interactive graphical model building (where users demand immediate feedback) and automated model building (where many possible model fragments may need to be tested to match a particular feature), it must be possible to perform a very rapid search for fragments containing some atoms matching a desired conformation.α trace the database will be searched for all six-peptide fragments matching the Cα atoms surrounding a particular peptide bond and the peptide atoms from the middle peptide of the best-fitting fragment will be used to provide the main-chain atoms for that peptide group. Similarly, to build a missing loop in a protein structure a search will be performed for all fragments for which the initial and final pairs of Cα atoms in the fragment may be superimposed on the last two Cα atoms before the break and the first two Cα atoms after the break.For example, to fit the main-chain atoms to a Cet al., 2003α atoms exceed 40 Å2. This provides a database of 106 295 amino acids in 1327 continuous fragments. For each amino acid, the residue type and the coordinates of the N, Cα and C atoms are stored (in turn providing sufficient information to locate the Cβ and O atoms). The entire database is stored as a single list of amino-acid records.A library has therefore been constructed using the 500 well refined protein structures of the Richardsons’ ‘Top 50’ database  set of CPerforming a least-squares superposition for every fragment in the database would be computationally demanding, so an initial pre-selection phase is performed to produce a subset of fragments which may be good matches to the search fragment. This pre-selection involves a computationally cheaper distance-matrix score.α to the remaining n − 1, the second row the distances from the second Cα to the remaining n − 2 and so on. The columns of this matrix correspond to the diagonals of the upper triangle of a conventional distance matrix  The various fragments built by the chain-tracing and sequence-docking algorithms are grouped into discontinuous chains using a scoring function that rewards compactness and penalizes sequence duplication. This removes a tedious manual step of assigning chain IDs and renaming the resulting chain fragments by hand.(ii) Where there are discontinuities (or breaks) in the resulting chains, an attempt is made to fix these discontinuities by pruning any overlap and placing a fragment from a stored database of protein fragments across the gap.The steps involved in the grouping of fragments into chains are described in detail in §§The steps employed in the completion of the atomic model in the current version of 3.1.The process of grouping fragments into chains involves assigning a chain identifier to each fragment such that the fragments which make up a single chain all have the same chain identifier. Furthermore, the resulting fragments may need to be transformed by the application of crystallographic symmetry elements to form a compact molecule.In the simplest case of a single sequence with no noncrystallographic symmetry (NCS), the process of allocating chain identifiers is simply a matter of separating a set of fragments which comprise a single complete chain from those which are incorrectly built or sequenced .The general case involves two additional layers of complexity. Firstly, there may be multiple copies of the molecule in the asymmetric unit. In this case, multiple chains with different chain identifiers must be built and each fragment must be allocated to one of the chains in such a way as to build several compact molecules. Secondly, in the case of a hetero-complex there may be multiple distinct sequences involved.(i) In the case where multiple sequences are present, those fragments which have been docked to one of the sequences are sorted according to which sequence was used. Each sequence is then considered in turn and the following steps are applied to all the fragments belonging to that sequence.(ii) A set of ‘seed’ fragments are identified by the method described in §(iii) The seed fragments are then grown by successively adding an additional fragment to a seed by the method described in §Steps (ii) and (iii) are repeated for each sequence until all sequences have been considered. The fragments are then assembled into chains by grouping all the fragments sharing a chain identifier in order of sequence number. In some cases, sequence numbers of grouped fragments may overlap; in this case, insertion codes are used to ensure that each residue is uniquely identified.The basic steps of the calculation are as follows.3.2.and the overlapped regions have similar conformations, the number of overlapped residues is stored in the matrix. The identification of ‘seed’ fragments is performed as follows. Firstly, a matrix is constructed whose order is the number of fragments under consideration. The matrix is used to store flags identifying which fragments overlap. For each pair of sequences, the number of residues of overlap is identified. If the overlap exceeds 12 residues A depth-first permutation search is then performed to identify the largest subset of fragments all of which overlap. There will usually be multiple equal solutions; in this case, the set is chosen for which the total number of residues in the overlapping fragments is the greatest.n sets must be considered, where n is the number of fragments. In practice, the number of overlapped sequences does not significantly exceed the number of NCS copies and depth searches may be terminated early if they cannot match the current best solution; thus, in practice the computational cost of this step is negligible.At first glance the algorithm is computationally expensive, since potentially 2The fragments thus selected contain the same sequence of residues in a similar conformation and thus can be assumed to be different NCS copies of one part of the structure. Each of the selected seed fragments is therefore allocated a different chain identifier and becomes the core of that chain.3.3.This step is performed iteratively. Every unallocated fragment is considered and the score is calculated for adding that fragment to each chain. The highest scoring chain/fragment combination is selected and the fragment is added to that chain. This will affect all subsequent scores for that chain and therefore the calculation is then repeated from the start.α atom within 5 Å of a Cα atom which has already been allocated to a given chain provides a score of +1 for adding the fragment to that chain. Each residue which has been docked into sequence with a sequence number clashing with a residue already allocated to a given chain provides a score of −2 for adding the fragment to that chain.The scoring function rewards geometrical compactness and penalizes sequence inconsistencies as follows. Each CIn this way, fragments which are intimate to an existing chain but which do not contain the same set of sequence are added to that chain. The process continues until no positive scores remain.3.4.(i) Flexible surface loops for which the electron density is poor.(ii) Mistracings where the chain trace has left the chain (often following a side chain or disulfide bridge) and the chain trace is then continued in a subsequent fragment.For the gap to be corrected, any wrongly traced residues (e.g. following a side chain or disulfide bridge) must first be removed by pruning back at least enough residues to remove any duplicated sequence numbers from the ends of the two fragments  and then selecting a fragment from a database of protein-chain fragments to bridge the gap.Often it will occur that there are gaps in the trace of the protein chain. These most commonly occur for one of two reasons.Buccaneer calculation an attempt is made to link spatially proximal N- and C-termini without regard to sequence. Sometimes these linkages are made incorrectly. However, this mistake is not serious, because when docking the resulting chain to the sequence the two parts of the joined chain will usually dock to different places in the sequence, at which point the error can be corrected by breaking the chain again. When linking chains on the basis of previously assigned sequences, the use of the sequence to validate the link is no longer available, so mistakes introduced at this stage will never be corrected. As a result, it was found to be necessary to limit the maximum length of the bridging fragment to six amino acids (i.e. two amino acids overlap with each chain and a maximum of two amino acids of gap). Longer missing loops must still be built manually. Since the errors arise from the presence of wrongly sequenced fragments which occur early in the model-building process when the fragments are short, this constraint should probably be relaxed to allow longer loops to be built once the model is approaching completion, at which point errors become less likely.Note that caution is required in this step. Earlier in the 3.5.Buccaneer calculation were also rewritten to make use of the fragment database. The ‘linking’ step (joining nearby N- and C-termini irrespective of sequence) and ‘correction’ step (correcting insertions and deletions by rebuilding one or three residues with two residues) both made use of a routine for building a loop of two residues by searching over allowed Ramachandran angles. Both of these steps have been replaced by an equivalent implementation using the fragment database.Two existing steps in the 4.Buccaneer software.Some preliminary results are presented here on the applicability of the fragment database and on the automated model-tidying features in the 4.1.To investigate the usefulness of the fragment database, an exhaustive search was performed to test for a given fragment length how well each fragment in the database can be represented by some other fragment from the database.α-atom positions and those of the search fragment, and the distance between the worst-matching Cα atom and the corresponding atom in the search fragment. This calculation was performed for fragments of six, nine and 12 residues .Each possible fragment of the chosen length was extracted from the database in turn and used as a search model to find other similar fragments. In every case the best-fitting fragment will be the original fragment, so the best fit is discarded and the second-best match is used. Two statistics are calculated for the matching fragment: the r.m.s. deviation between the CThe results are shown in Fig. 3The r.m.s. deviations are worse than 1.0 Å for 0.04% of six-residue fragments, 5% of nine-residue fragments and 38% of 12-residue fragments. Given that a significant proportion of the fragments in the database will be in very similar helical or strand conformations, this suggests that the library will be of limited use for 12-residue fragments except for common motifs.Similarly, the worst deviating atom has a displacement of worse than 1.5 Å for 0.05% of six-residue fragments, 5% of nine-residue fragments and 36% of 12-residue fragments. (Note the change in distance criterion compared with the previous data.) This again suggests that 12-residue fragments will be of less use, since automated refinement is likely to struggle to correct errors of this magnitude.As a result, the database provides effectively complete coverage for fragments of up to six residues or for loop fitting over only two missing residues. For missing loops of intermediate length (3–6 residues), the database will provide good loop conformations in a subset of cases where the loop happens to match one in the database and so will catch common turn motifs, for example. For longer loops, the database is likely to be useful only in less frequent cases. However, this approach has been shown to have good success by Choi & Deane 2010 for loop4.2.The model-tidying procedure was applied to the same 55 test structures used in Cowtan 2008 and is dEach of the 50 tidied chains was examined to determine the proportion of the chain corresponding to a single molecule in the final structure. As the model becomes more complete, the assignment becomes easier, so these proportions are tabulated along with the completeness of the chain in Table 1In every case where the chain is at least 60% complete, at least 80% is correctly assigned to a single molecule and in 44 of 48 such cases the assignment is entirely correct or correct apart from a few trailing residues. For the two cases where the completeness is less than 50%, the grouping of fragments into chains is rather less accurate.1vluA chain  is shown in Fig. 4Buccaneer model shows chain breaks in similar positions. The disconnected range of residues 331–391 has been placed at the wrong end of the molecule. It is probable that the error could have been corrected in this specific case by adding a term rewarding proximity of sequence number to the scoring function; however, this was not tested because in the experience of the author the incorrect linking of chains across protein contacts is a significant problem in the early stages of building and this problem is likely to be exacerbated by such a change.The case of the 4.3.Buccaneer calculation to make use of the database and by adding a new loop-building step using the database, as described in §The usefulness of the fragment database in automated building was tested by rewriting two existing steps of the The results of the model-building calculation are rather sensitive to changes in the algorithm or input data, so to determine whether each change made an improvement multiple model-building runs were used. For each of the 55 test structures used in Cowtan 2008 ten modeα within 1.9 Å of the correct position) was averaged over the 550 runs to obtain a score for this method.The percentage of the model built and correctly sequenced  is the correction of insertions and deletions during sequencing [step (v) in the Buccaneer calculation]. These steps were previously performed using an exhaustive search over allowed Ramachandran angles, in the first case to build a link of up to two residues and in the second to rebuild a stretch of either one or three residues with two residues. Finally, a new loop-building step was added, similar to the ‘link’ step but performed after the sequence has been assigned to the chains. Unlike the ‘link’ step, the loop-building step may prune an arbitrary number of residues from either chain to bring similarly numbered residues into proximity.The results of these calculations are shown in Table 2The updated link step makes minimal difference to the amount of model built, but does provide a speed benefit over the previous (Ramachandran search) implementation. The updated correct step gives a small improvement in the amount of model built, although the difference is comparable to the noise among different runs. The loop-building step shows no significant improvement in the proportion built. It is a recurring problem in the development of the model-building algorithm that the improvements are marginal and hard to distinguish from noise, even with the large number of test runs. However, in each of four cases where only the correct step is changed the results always improve, suggesting that this result is significant.However, the benefit of the loop-building step can be seen in the connectivity of the model, which is a benefit when it comes to finishing the model by hand. The number of fragments in the output model gives an indication of what is happening. For the original version, the average number of fragments over the 550 autobuilt models is 8.7; when the loop-building step is added, this reduces to 7.4 (similar changes are seen when combining the loop-building step with the other new steps and when the resolution is truncated). A reduction in the number of fragments without a reduction in the proportion built implies an improvement in connectivity. The implication is that the loop-building step is most commonly dealing with cases where chains are coming into close proximity but failing to meet (and possibly branching down side chains) rather than true loop-building problems when there are missing residues.To summarize, using the fragment database for the link step reduces the computational overhead, using the fragment database for the correct step provides a small improvement in completeness and using the fragment database for loop building provides a significant improvement in connectivity.4.4.Sloop, which is capable of building short missing loops in incomplete protein models. As noted above, the usefulness of this tool varies according to whether the loop concerned happens to conform to an existing motif.The fragment library has also been used in the implementation of a loop-building tool, α trace into a main-chain  trace has also been implemented. The results show similar high levels of accuracy to those of Esnouf  Use of the loop-building code to build longer loops when the model is nearly complete. This may be in a single step, or possibly using the stepwise approach of Joosten  al. 2008 where a (ii) Use of the fragment library to rebuild regions of the chain where residue type influences geometry, in particular in the vicinity of Gly and Pro residues.Buccaneer, in a manner similar to that of Terwilliger (2003(iii) Testing the use of a subset of the fragment library to replace the current Ramachandran search in the chain-growing step in iger 2003.Coot software.(iv) Use of the fragment library to provide validation scores in the manner of Jones & Thirup 1986 in the C(v) Extension of the fragment-database concept to handle nucleotides.The protein-fragment database is capable of reproducing the various functionalities implemented by previous authors, with the efficient search algorithm allowing the use of a larger database than in previous implementations. Some preliminary applications have been explored and a range of future applications are planned, including the following.