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A multiple projection method for digital tomosynthesis.

A new method of optimized efficiency for the retrospective reconstruction of tomograms is presented. The method has been developed for use with isocentric fluoroscopic units and is capable of performing digital tomosynthesis of anatomical planes of user selected orientation and distance from the isocenter. Optimization of efficiency has been achieved by segmenting the reconstruction process into discrete transformations that are specific to groups of pixels, rather than performing pixel by pixel operations. These involve a number of projections of the acquired image matrices as well as parallel translations and summing. Application of this method has resulted in a significant reduction of computing time. The proposed algorithm has been experimentally tested on a radiotherapy simulator unit with the use of a phantom and the obtained results are reported and discussed.

Algorithms↗

Driving cerebral perfusion pressure with pressors: how, which, when?

In traumatic brain injury, cerebral hypoperfusion is associated with adverse outcome, particularly in the early phases of management. This has resulted in the increased use of drugs such as adrenaline, noradrenaline, dopamine and phenylephrine to augment or maintain systemic blood pressures at near normal levels. This is now part of standard practice and is endorsed by the Brain Trauma Foundation guidelines. It probably matters little which agent is used, provided appropriate monitoring is in place and those reversible causes of hypotension are promptly excluded and treated. However, blindly applying management guidelines to all patients may negate these early benefits. The time has come move away from artificially separated concepts of "intracranial pressure" versus "cerebral perfusion pressure" based strategies. These should be considered in parallel and applied to an individual patient, rather than making the patient fit into an all-encompassing treatment algorithm. . A paradigm shift from a "set and forget" philosophy to one of "titration against time" to achieve appropriate therapeutic targets is now required. In this context the rational use of vasoactive agents to optimise cerebral perfusion pressure may be employed. On the basis of limited animal and human evidence, noradrenaline appears to be the most appropriate catecholamine for traumatic brain injury, although definitive, targeted trials are required.

Journal Article↗

[Assessment of axonal degeneration on Alzheimer's disease with diffusion tensor MRI].

PURPOSE: Alzheimer disease (AD) causes cortical degeneration with subsequent degenerative changes of the white matter. The aim of this study was to investigate the extent of white matter tissue damage of patients with Alzheimer's disease in comparison with healthy subjects using diffusion tensor MRI (DTI). The value of integrated parallel imaging techniques (iPAT) for reduction of image distortion was assessed. MATERIAL AND METHODS: We studied 9 patients with mild AD and 10 age and gender matched healthy controls. DTI brain scans were obtained on a 1.5 tesla system (Siemens Magnetom Sonata) using parallel imaging (iPAT) and an EPI diffusion sequence with TE/TR 71 ms/6000 ms. We used an 8-element head coil and a GRAPPA reconstruction algorithm with an acceleration factor of 2. From the tensor, the mean diffusivity (D), the fractional anisotropy (FA), and the relative anisotropy (RA) of several white matter regions were determined. RESULTS: FA was significantly lower (p <0,05) in the white matter of the genu of corpus callosum from patients with AD than in the corresponding regions from healthy controls. There was a trend observed for slightly higher ADC values in the AD group (p=0,06). No significant changes were observed in the regions of the splenium, internal capsule, pericallosal areas, frontal, temporal, parietal, and occipital lobe. The images obtained with iPAT contained substantially less susceptibility artefacts and were less distorted than images acquired with non-parallel imaging technique. CONCLUSIONS: DTI is a method with potential to assess early stages of white matter damage in vivo. The altered FA and ADC values in the genu of corpus callosum of patients with AD presumably reflect the microscopic white matter degeneration. Acquisition time can be reduced by iPAT methods with less image distortion from susceptibility artefacts resulting in a more accurate calculation of the diffusion tensor.

Adult↗

Forward planar projection through layered media.

A planar forward projection algorithm is combined with ray theory to describe longitudinal propagation through an arbitrary number of randomly oriented isotropic layers. This method first measures the space-time pressure field in a plane, then uses wavevector frequency-domain methods to project the field through layered media and to an arbitrary new plane, not necessarily parallel to the initial plane. The approach is valid for longitudinal propagation through liquid layers and in solids, such as soft tissues, that can be approximated as viscous liquids. The algorithm is verified by propagating the field from a 0.5 MHz planar transducer through a combination of rubber, plastic, and water layers. Hydrophone measurements indicate correlation between measured and simulated fields for angles below the longitudinal critical angles of the layered materials.

Acoustics↗

A reflectance photometer with a square photodiode array detector for use on multilayer dry-film slides.

This semiautomated prototype reflectance photometer measures reflected light from multilayer dry-film slides. The instrument makes use of a square photodiode array detector, a Hewlett-Packard desktop computer, and a modified mechanical transport mechanism from an Ektachem DT60 analyzer. When 2 microL of serum is placed on a dry-film slide, a colored spot is formed. The slide is automatically transported to an incubation area and then to the photometer area. There the spot is illuminated with dual tungsten lamps, and the reflected light passes through an interference filter, where it is focused on a square photodiode array containing 10,000 individual detectors. The analog signal from each detector is digitized and transmitted to a computer for calculation of the percentage of reflectance. I used a series of algorithms to locate the spot, estimate spot area, correct for minor variations in sample volume, and compute the average reflectance from a central spot area. To evaluate the instrument's performance, I ran parallel glucose determinations in the Beckman Astra; results correlated well. The small sample size along with no dead sample volume makes the system useful for small sample volumes.

Algorithms↗

Efficient foldover suppression using SENSE.

Parallel imaging techniques, which in principle represent procedures of unfolding a reduced dataset, are well known and well established in MR imaging. This paper presents a further application of one particular reconstruction method, the SENSE algorithm, considered from a different point of view to remove potential foldover in conventional images acquired with multiple receive coils. Based on the coil sensitivity information, a body coverage map in the excited plane is calculated. This is used together with the measured raw data in a SENSE-type reconstruction to optimize the signal-to-noise ratio (SNR) as well as to remove foldover reliably by unfolding the image to a larger field of view. The reconstruction is performed automatically, without any user interaction, and does not affect data acquisition. Based on phantom and in vivo studies, which retain high image quality after the removal, the potential and limits of this approach are discussed, also taking into account future scanner hardware that will support a large number of parallel receiver channels.

Algorithms↗

Fully balanced steady-state 3D-spin-echo (bSSSE) imaging at 3 Tesla.

In this work a 3D fully balanced steady-state spin-echo sequence (bSSSE) was designed and implemented on a 3-Tesla whole-body MR scanner. In contrast to previously introduced nonbalanced SSSE (nbSSSE) sequences, bSSSE features fully rewound imaging gradients. Additionally, all phase encodings and the readout prephasing are performed after the refocusing pulse. Its performance was compared with previously used gradient-echo (GE) and nbSSSE sequences. The signal response of each sequence was simulated by numerical solution of the Bloch equation. All sequences were then optimized based on these simulations for high-resolution (HR) imaging of tissues with short relaxation times and applied to in vivo HR-MRI of trabecular bone. bSSSE outperformed nbSSSE sequences in terms of SNR and SNR efficiency. Measurements of structural bone parameters revealed thinner trabeculae and a lower bone/bone-marrow fraction for the bSSSE sequence compared to the nbSSSE sequence. By applying a parallel imaging technique based on generalized autocalibrating partially parallel acquisition (GRAPPA) with a reduction factor of 2, we were able to maintain a clinically feasible scan time using bSSSE. Comparisons of structural bone parameters revealed a difference of less than 3% for all structural parameters between parallel and conventional imaging.

Algorithms↗

Sequencing of megabase plus DNA by hybridization: theory of the method.

A mismatch-free hybridization of oligonucleotides containing from 11 to 20 monomers to unknown DNA represents, in essence, a sequencing of a complementary target. Realizing this, we have used probability calculations and, in part, computer simulations to estimate the types and numbers of oligonucleotides that would have to be synthesized in order to sequence a megabase plus segment of DNA. We estimate that 95,000 specific mixes of 11-mers, mainly of the 5'(A,T,C,G)(A,T,C,G)N8(A,T,C,G)3' type, hybridized consecutively to dot blots of cloned genomic DNA fragments would provide primary data for the sequence assembly. An optimal mixture of representative libraries in M13 vector, having inserts of (i) 7 kb, (ii) 0.5 kb genomic fragments randomly ligated in up to 10-kb inserts, and (iii) tandem "jumping" fragments 100 kb apart in the genome, will be needed. To sequence each million base pairs of DNA, one would need hybridization data from about 2100 separate hybridization sample dots. Inevitable gaps and uncertainties in alignment of sequenced fragments arising from nonrandom or repetitive sequence organization of complex genomes and difficulties in cloning "poisonous" sequences in Escherichia coli, inherent to large sequencing by any method, have been considered and minimized by choice of libraries and number of subclones used for hybridization. Because it is based on simpler biochemical procedures, our method is inherently easier to automate than existing sequencing methods. The sequence can be derived from simple primary data only by extensive computing. Phased experimental tests and computer simulations increasing in complexity are needed before accurate estimates can be made in terms of cost and speed of sequencing by the new approach. Nevertheless, sequencing by hybridization should show advantages over existing methods because of the inherent redundancy and parallelism in its data gathering.

Algorithms↗

MrBayes 3: Bayesian phylogenetic inference under mixed models.

MrBayes 3 performs Bayesian phylogenetic analysis combining information from different data partitions or subsets evolving under different stochastic evolutionary models. This allows the user to analyze heterogeneous data sets consisting of different data types-e.g. morphological, nucleotide, and protein-and to explore a wide variety of structured models mixing partition-unique and shared parameters. The program employs MPI to parallelize Metropolis coupling on Macintosh or UNIX clusters.

Algorithms↗

Promise and challenge of high-performance computing, with examples from molecular modelling.

Computational modelling is one of the most significant developments in the practice of scientific inquiry in the 20th century. During the past decade, advances in computing technologies have increased the speed of computers by a factor of 100; an increase of a factor of 1000 can be expected in the next decade. These advances have, however, come at a price, namely, radical change(s) in computer architecture. Will computational scientists and engineers be able to harness the power offered by these high-performance computers to solve the most critical problems in science and engineering? In this paper, we discuss the challenges that must be addressed if we are to realize the benefits offered by high-performance computing. The task will not be easy; it will require revision or replacement of much of the software developed for vector supercomputers as well as advances in a number of key theoretical areas. Because of the pace of computing advances, these challenges must be met by close collaboration between computational scientists, computer scientists and applied mathematicians. The effectiveness of such a multidisciplinary approach is illustrated in a brief review of NWCHEM, a general-purpose computational chemistry code designed for parallel supercomputers.

Algorithms↗

Finite-element neural networks for solving differential equations.

The solution of partial differential equations (PDE) arises in a wide variety of engineering problems. Solutions to most practical problems use numerical analysis techniques such as finite-element or finite-difference methods. The drawbacks of these approaches include computational costs associated with the modeling of complex geometries. This paper proposes a finite-element neural network (FENN) obtained by embedding a finite-element model in a neural network architecture that enables fast and accurate solution of the forward problem. Results of applying the FENN to several simple electromagnetic forward and inverse problems are presented. Initial results indicate that the FENN performance as a forward model is comparable to that of the conventional finite-element method (FEM). The FENN can also be used in an iterative approach to solve inverse problems associated with the PDE. Results showing the ability of the FENN to solve the inverse problem given the measured signal are also presented. The parallel nature of the FENN also makes it an attractive solution for parallel implementation in hardware and software.

Algorithms↗

Adaptive temporal resolution optimization in helical cardiac cone beam CT reconstruction.

Cone beam computed tomography scanners in combination with heart rate adaptive reconstruction schemes have the potential to enable cardiac volumetric computed tomography (CT) imaging for a larger number of patients and applications. In this publication, an adaptive scheme for the automatic and patient-specific reconstruction optimization is introduced to improve the temporal resolution and image quality. The optimization method permits the automatic determination of the required amount of gated helical cone beam projection data for the reconstruction volume. It furthermore allows one to optimize subvolume reconstruction yielding an increased temporal resolution. In addition, methods for the assessment of the temporal resolution are given which enable a quantitative documentation of the reconstruction improvements. Results are presented for patient data sets acquired in low pitch helical mode using a 16-slice cone beam CT system with parallel ECG recording.

Algorithms↗

Implementation of the DPM Monte Carlo code on a parallel architecture for treatment planning applications.

We have parallelized the Dose Planning Method (DPM), a Monte Carlo code optimized for radiotherapy class problems, on distributed-memory processor architectures using the Message Passing Interface (MPI). Parallelization has been investigated on a variety of parallel computing architectures at the University of Michigan-Center for Advanced Computing, with respect to efficiency and speedup as a function of the number of processors. We have integrated the parallel pseudo random number generator from the Scalable Parallel Pseudo-Random Number Generator (SPRNG) library to run with the parallel DPM. The Intel cluster consisting of 800 MHz Intel Pentium III processor shows an almost linear speedup up to 32 processors for simulating 1 x 10(8) or more particles. The speedup results are nearly linear on an Athlon cluster (up to 24 processors based on availability) which consists of 1.8 GHz+ Advanced Micro Devices (AMD) Athlon processors on increasing the problem size up to 8 x 10(8) histories. For a smaller number of histories (1 x 10(8)) the reduction of efficiency with the Athlon cluster (down to 83.9% with 24 processors) occurs because the processing time required to simulate 1 x 10(8) histories is less than the time associated with interprocessor communication. A similar trend was seen with the Opteron Cluster (consisting of 1400 MHz, 64-bit AMD Opteron processors) on increasing the problem size. Because of the 64-bit architecture Opteron processors are capable of storing and processing instructions at a faster rate and hence are faster as compared to the 32-bit Athlon processors. We have validated our implementation with an in-phantom dose calculation study using a parallel pencil monoenergetic electron beam of 20 MeV energy. The phantom consists of layers of water, lung, bone, aluminum, and titanium. The agreement in the central axis depth dose curves and profiles at different depths shows that the serial and parallel codes are equivalent in accuracy.

Algorithms↗

A software-controlled EKG simulator.

This design allows generation of a wide range of waveforms from subaudio to ultrasonic directly via software. Waveforms may be calculated on the fly by suitable algorithms or produced from previously created lookup tables. The heart of the design is a fast 16-bit processor which directly executes the Forth programming language. A simple R/2R digital-to-analog converter is coupled to a parallel output port to produce the desired waveforms. This device has been used to generate realistic-appearing normal and abnormal EKG tracings in the lab.

Algorithms↗

Using a neural network to identify potential HLA-DR1 binding sites within proteins.

The presentation by antigen-presenting cells of immunodominant peptide segments in association with major histocompatibility complex (MHC) encoded proteins is fundamental to the efficacy of a specific immune response. One approach used to identify immunodominant segments within proteins has involved the development of predictive algorithms which utilize amino acid sequence data to identify structural characteristics or motifs associated with in vivo antigenicity. The parallel-computing technique termed 'neural networking' has recently been shown to be remarkably efficient at addressing the problem of pattern recognition and can be applied to predict protein secondary structure attributes directly from amino acid sequence data. In order to examine the potential of a neural network to generalize peptide structural features related to binding within class II MHC-encoded proteins, we have trained a neural network to determine whether or not any given amino acid of a protein is part of a peptide segment capable of binding to HLA-DR1. We report that a neural network trained on a data base consisting of peptide segments known to bind to HLA-DR1 is able to generalize features relating to HLA-DR1-binding capacity (r = 0.17 and p = 0.0001).

Amino Acid Sequence↗

On the advantages of multi-input single-output parallel cascade classifiers.

Parallel Cascade Identification (PCI) has been successfully applied to build dynamic nonlinear systems that address diverse challenges in the field of bioinformatics. PCI may be used to identify either single-input single-output (SISO) or multi-input single-output (MISO) models. Although SISO PCI models have typically sufficed, it has been suggested that MISO PCI systems could also be used to form bioinformatics classifiers, and indeed they were successfully applied in one study. This paper reports on the first systematic comparison of MISO and SISO PCI classifiers. Motivation for using the MISO structure is given. The construction of MISO parallel cascade models is also briefly reviewed. In order to compare the accuracy of SISO and MISO PCI classifiers, genetic algorithms are applied to optimize the model architecture on a number of equivalent single-input and multi-input biological training datasets. Through evaluation of both model structures on independent test datasets, we establish that MISO PCI is capable of building classifiers of equal accuracy to those resulting from SISO PCI models. Moreover, we discuss and illustrate the benefits of the MISO approach, including significant reduction in training and testing times, and the ability to adjust automatically the weighting of individual inputs according to information content.

Algorithms↗

De novo backbone and sequence design of an idealized alpha/beta-barrel protein: evidence of stable tertiary structure.

We have designed, synthesized, and characterized a 216 amino acid residue sequence encoding a putative idealized alpha/beta-barrel protein. The design was elaborated in two steps. First, the idealized backbone was defined with geometric parameters representing our target fold: a central eight parallel-stranded beta-sheet surrounded by eight parallel alpha-helices, connected together with short structural turns on both sides of the barrel. An automated sequence selection algorithm, based on the dead-end elimination theorem, was used to find the optimal amino acid sequence fitting the target structure. A synthetic gene coding for the designed sequence was constructed and the recombinant artificial protein was expressed in bacteria, purified and characterized. Far-UV CD spectra with prominent bands at 222nm and 208nm revealed the presence of alpha-helix secondary structures (50%) in fairly good agreement with the model. A pronounced absorption band in the near-UV CD region, arising from immobilized aromatic side-chains, showed that the artificial protein is folded in solution. Chemical unfolding monitored by tryptophan fluorescence revealed a conformational stability (DeltaG(H2O)) of 35kJ/mol. Thermal unfolding monitored by near-UV CD revealed a cooperative transition with an apparent T(m) of 65 degrees C. Moreover, the artificial protein did not exhibit any affinity for the hydrophobic fluorescent probe 1-anilinonaphthalene-8-sulfonic acid (ANS), providing additional evidence that the artificial barrel is not in the molten globule state, contrary to previously designed artificial alpha/beta-barrels. Finally, 1H NMR spectra of the folded and unfolded proteins provided evidence for specific interactions in the folded protein. Taken together, the results indicate that the de novo designed alpha/beta-barrel protein adopts a stable three-dimensional structure in solution. These encouraging results show that de novo design of an idealized protein structure of more than 200 amino acid residues is now possible, from construction of a particular backbone conformation to determination of an amino acid sequence with an automated sequence selection algorithm.

Amino Acid Sequence↗

Differentiation of cysts from solid tumors in the breast with diffuse optical tomography.

RATIONALE AND OBJECTIVES: Near-infrared diffuse optical tomography (DOT) is an emerging imaging technology that has the potential to offer enhanced contrast resolution over the existing technologies for detection and diagnosis of breast cancer. Thus far, the clinical evaluation of DOT has been largely limited to solid tumors. A pilot clinical study focused on DOT imaging of breasts with cysts is presented. MATERIALS AND METHODS: Six cases were studied using the recently developed compact, parallel-detection DOT system. Images characterizing the tissue absorption and scattering were obtained with a finite element-based reconstruction algorithm. The optical images were compared with the mammograms and sonograms. In one case, in vitro measurements of optical properties were conducted for the fluid obtained from needle aspiration. RESULTS: Substantial contrast between cyst and adjacent parenchyma is observed. For the six cases evaluated, the locations and sizes of cysts imaged optically are accurate and consistent with the mammographic and sonographic findings. For the case that aspiration was performed, the absorption and scattering coefficients imaged in the cyst region are quantitatively accurate compared with that measured in vitro from the fluid aspirated. CONCLUSION: This pilot study shows that cysts ranging from 1-4 cm in diameter can be quantitatively imaged. They can be differentiated from solid breast tumors because cysts generally demonstrate lower absorption and scattering coefficients compared with the surrounding normal tissue, whereas solid tumors show concurrent higher absorption and scattering related to the normal tissue.

Adult↗