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PubMed1998

Planning of beam intensity modulation using an advanced 3D dose calculation algorithm and a simulated annealing method.

PURPOSE: The aim of this work was to develop a fast inverse planning algorithm that will calculate optimum beam intensity distributions and beam shapes, and to incorporate the algorithm into a three-dimensional CT planning system. METHOD: The algorithm is based on the technique of simulated annealing and produces beam intensity distributions that could in principle be implemented clinically, either by the use of compensators or dynamic multileaf collimation. Dose distributions are calculated using a voxel beam model based on a spherical co-ordinate system, and transformations are given allowing the dose to be determined at any point within the patient. The dose calculation algorithm calculates primary and scattered dose separately from a knowledge of tissue/air ratios and differential scatter/air ratios, and both are corrected for the presence of heterogeneities in three dimensions. Specific attention is given to the execution time of the algorithm, and the methods developed allow satisfactory results to be achieved in calculation times which are sufficiently fast to be used interactively in the planning system. Several objective functions have been developed and can be selected in a simple manner by the user. In general, these attempt to achieve a uniform dose within the target while limiting the dose to organs at risk, either by upper dose limits or by specifying constraints on their dose volume histograms. RESULTS: The beam intensity distributions produced from the optimization have been used automatically by the forward planning system to produce three-dimensional dose distributions, and the results obtained in a number of clinical situations are presented. CONCLUSIONS: The inverse planning algorithm developed has been successfully incorporated into a three-dimensional planning system and is capable of producing beam intensity modulated distributions for clinical implementation. The execution time of the algorithm is sufficiently fast to be used as an optimization tool in an interactive forward planning system.

Algorithms↗

PubMed1997

A structure-based algorithm to predict potential binding peptides to MHC molecules with hydrophobic binding pockets.

Binding of peptides to MHC class I molecules is a prerequisite for their recognition by cytotoxic T cells. Consequently, identification of peptides that will bind to a given MHC molecule must constitute a central part of any algorithm for prediction of T-cell antigenic peptides based on the amino acid sequence of the protein. Binding motifs, defined by anchor positions only, have proven to be insufficient to ensure binding, suggesting that other positions along the peptide sequence also affect peptide-MHC interaction. The second phase of prediction schemes therefore take into account the effect of all positions along the peptide sequence, and are based on position-dependent-coefficients that are used in the calculation of a peptide score. These coefficients can be extracted from a large ensemble of binding sequences that were tested experimentally, or derived from structural considerations, as in the algorithm developed by us recently. This algorithm uses the coordinates of solved complexes to evaluate the interactions of peptide amino acids with MHC contact residues, and results in a peptide score that reflects its binding energy. Here we present our analysis for peptide binding to four MHC alleles (HLA-A2, HLA-A68, HLA-B27 and H-2Kb), and compare the predictions of the algorithm to experimental binding data. The algorithm performs successfully in predicting peptide binding to MHC molecules with hydrophobic binding pockets but not when MHC molecules with hydrophilic, charged pockets are considered. For MHC molecules with hydrophobic pockets it is demonstrated how the algorithm succeeds in distinguishing binding from non-binding peptides, and in high ranking of immunogenic peptides within all overlapping same-length peptides spanning their respective protein sequences. The latter property of the algorithm makes it a useful tool in the rational design of peptide vaccines aimed at T-cell immunity.

Algorithms↗

PubMed1998

Prospective evaluation of an anemia treatment algorithm in hemodialysis patients.

Current guidelines recommend maintaining the hematocrits of chronic hemodialysis patients in the low to mid-30s. Maintaining patients' hematocrits within a narrow range requires frequent monitoring of their hematocrits and iron studies and periodic adjustment of erythropoietin doses and administration of intravenous iron. We designed a simple anemia treatment algorithm to streamline the management of anemia in hemodialysis patients. The protocol required formal monthly decisions about the administration of intravenous iron or changes in erythropoietin dose. This algorithm was implemented by dialysis nurses and evaluated prospectively for 6 months in a single dialysis unit (30 patients). The proportion of patients whose hematocrits were within the desired target (31% to 35%) increased from 27% at baseline to 61% during months 4 through 6 of the algorithm. Conversely, the proportion of patients whose hematocrit values were below the target decreased from 46% at baseline to 18% during months 4 through 6 of the algorithm (P=0.004). The percentage of patients whose hematocrit values were above the target did not increase. The proportion of patients whose transferrin saturation was less than 18% decreased from 47% at baseline to 20% during months 4 through 6 of the algorithm (P=0.04). The weekly erythropoietin dose administered decreased from 11,200+/-1,400 units at baseline to 9,400+/-1,200 units in month 6 of the algorithm (P=0.06). We conclude that a simple anemia treatment algorithm implemented by dialysis nurses is feasible and efficacious and may increase the proportion of hemodialysis patients whose hematocrit values are within the target range, without increasing erythropoietin requirements.

Adult↗

PubMedDate not supplied

Growing-cube isosurface extraction algorithm for medical volume data.

In medical applications, three-dimensional volume data such as CT and MRI are gathered from medical-imaging devices. Marching cube (MC) algorithm is a common routine to extract isosurfaces from volume data. The MC algorithm generates the massive number of triangles to represent an isosurface. It is difficult to render this amount of triangles in real-time on general workstations. In this paper, we present a growing-cube algorithm to reduce the number of triangles generated by the MC algorithm. Growing-cube algorithm uses a surface tracker to avoid exhaustive searching isosurfaces cell-by-cell and, therefore, it saves computation time. During surface tracking, the growing-cube algorithm adaptively merges surfaces contained in the tracked cells to reduce the number of triangles. Surfaces are merged as long as the error is within user-specified error thresholds. Therefore, the proposed algorithm can generate a variable resolution of isosurfaces according to these error parameters.

Algorithms↗

PubMed2000

Fast iterative algorithm for metal artifact reduction in X-ray CT.

RATIONALE AND OBJECTIVES: The reduction of metal artifacts in x-ray computed tomography (CT) has important clinical applications. An iterative method adapted from the expectation maximization (EM) formula for emission CT was shown to be effective for metal artifact reduction, but its computational speed is slow. The goal of this project was to accelerate that iterative method for metal artifact reduction. MATERIALS AND METHODS: Using the row-action/ordered-subset (EM) formula for emission CT as a basis, the authors developed a fast iterative algorithm for metal artifact reduction. In each iteration of this algorithm, both reprojection from an intermediate image and backprojection from discrepancy data are performed. RESULTS: The feasibility of the fast iterative algorithm was demonstrated in numerical and phantom experiments. In comparison with the nonaccelerated iterative algorithm, the speed of iterative metal artifact reduction is improved by an order of magnitude given image quality in terms of visual inspection, I-divergence in the projection domain, and the euclidean distance in the image domain. CONCLUSION: The fast iterative algorithm corrects intermediate reconstruction according to subsets of projections and produces satisfactory image quality at a much faster speed than the previously published iterative algorithm. This algorithm has important potential in clinical applications, such as orthopedic, oncologic, and dental imaging.

Algorithms↗

PubMed1997

Clique-detection algorithms for matching three-dimensional molecular structures.

The representation of chemical and biological molecules by means of graphs permits the use of a maximum common subgraph (MCS) isomorphism algorithm to identify the structural relationships existing between pairs of such molecular graphs. Clique detection provides an efficient way of implementing MCS detection, and this article reports a comparison of several different clique-detection algorithms when used for this purpose. Experiments with both small molecules and proteins demonstrate that the most efficient of these particular applications, which typically involve correspondence graphs with low edge densities, is the algorithm described by Carraghan and Pardalos. This is shown to be two to three times faster than the Bron-Kerbosch algorithm that has been used previously for MCS applications in chemistry and biology. However, the latter algorithm enables all substructures common to a pair of molecules to be identified, and not just the largest ones, as with the other algorithms considered here. The two algorithms can usefully be combined to increase the efficiency of database-searching systems that use the MCS as a measure of structural similarity.

Algorithms↗

PubMed2001

Volume learning algorithm artificial neural networks for 3D QSAR studies.

The current study introduces a new method, the volume learning algorithm (VLA), for the investigation of three-dimensional quantitative structure-activity relationships (QSAR) of chemical compounds. This method incorporates the advantages of comparative molecular field analysis (CoMFA) and artificial neural network approaches. VLA is a combination of supervised and unsupervised neural networks applied to solve the same problem. The supervised algorithm is a feed-forward neural network trained with a back-propagation algorithm while the unsupervised network is a self-organizing map of Kohonen. The use of both of these algorithms makes it possible to cluster the input CoMFA field variables and to use only a small number of the most relevant parameters to correlate spatial properties of the molecules with their activity. The statistical coefficients calculated by the proposed algorithm for cannabimimetic aminoalkyl indoles were comparable to, or improved, in comparison to the original study using the partial least squares algorithm. The results of the algorithm can be visualized and easily interpreted. Thus, VLA is a new convenient tool for three-dimensional QSAR studies.

Algorithms↗

PubMed1997

A comparison of heuristic search algorithms for molecular docking.

This paper describes the implementation and comparison of four heuristic search algorithms (genetic algorithm, evolutionary programming, simulated annealing and tabu search) and a random search procedure for flexible molecular docking. To our knowledge, this is the first application of the tabu search algorithm in this area. The algorithms are compared using a recently described fast molecular recognition potential function and a diverse set of five protein-ligand systems. Statistical analysis of the results indicates that overall the genetic algorithm performs best in terms of the median energy of the solutions located. However, tabu search shows a better performance in terms of locating solutions close to the crystallographic ligand conformation. These results suggest that a hybrid search algorithm may give superior results to any of the algorithms alone.

Algorithms↗

PubMed2001

Clinical evaluation of morphology discrimination: an algorithm for rhythm discrimination in cardioverter defibrillators.

The aim of this study was to test the new morphology discrimination diagnostic algorithm for ICDs that differentiates supraventricular tachycardias (SVTs) from VTs by analysis of ventricular depolarization complexes morphology. Twenty-five patients implanted with a St. Jude Ventritex single chamber ICD were studied during electrophysiological evaluation at predischarge and were followed for 7 +/- 4 months. Sensitivity and specificity for VT detection and overall diagnostic accuracy of the morphology discrimination algorithm were calculated on 326 detected events. At electrophysiological evaluation, the algorithm was tested during 67 episodes of right atrial pacing, during 119 episodes of RV pacing (at basal interventricular septum and RV apex) and during 27 episodes of sustained AF: specificity was 98%, sensitivity was 66%, and diagnostic accuracy was 80%. All episodes of AF were correctly diagnosed as SVT. Exclusion of detections related to pacing at the basal interventricular septum, resulted in a specificity of 98%, a sensitivity of 85%, and a diagnostic accuracy of 93%. During follow-up, evaluation of the morphology discrimination algorithm on 113 spontaneous episodes (31 VTs, 31 AF, 7 SVTs, and 44 sinus tachycardias) exhibited a specificity of 89%, a sensitivity of 100%, and a diagnostic accuracy of 92%. In conclusion, the morphology discrimination algorithm exhibits a high specificity in discriminating VTs from SVTs, although with a corresponding reduction in sensitivity. The preliminary experience on spontaneous episodes is promising. To correct for the reduction in sensitivity, it is advisable to use this algorithm in parallel with other algorithms for rhythm discrimination (sudden onset, stability) coupled with extended high rate.

Adult↗

PubMed2000

Clinical experience of a new rate drop response algorithm in the treatment of vasovagal and carotid sinus syncope.

Dual chamber pacing has proven beneficial in patients with sudden drops in heart rate as seen in vasovagal syncope and carotid sinus syndrome. Newer algorithms for faster detection of an insidious drop in heart rate and short lasting intervention pacing at a high rate, as in the rate drop response algorithm in the Medtronic Kappa series of pacemakers, might improve the effect of pacing. Two case reports, that demonstrate the use of these rate drop response algorithms, are presented. A 24-year-old woman with recurrent episodes of syncope and repeated tilt-table tests with vasovagal cardioinhibitory outcomes had a Medtronic Kappa 400 pacemaker implanted. Syncope was abolished during repeat tilt-table testing following pacemaker implantation and proper functioning of the rate drop response algorithm. The patient has been free of syncope during follow-up apart from a single episode that occurred due to neglect of vasovagal warning symptoms. A 52-year-old man with coronary artery disease developed recurrent blackouts. Carotid sinus massage resulted in 5.5 s of asystole and presyncope. A Medtronic Kappa 700 pacemaker with a rate drop response algorithm was implanted and the patient became asymptomatic. The rate drop response algorithm is discussed in detail based upon the case reports, and recommendations are given for the use of this algorithm in patients with vasovagal syncope and carotid sinus syndrome.

Adult↗

PubMed2001

A real-time ST-segment monitoring algorithm for implantable devices.

Continuous ST-segment monitoring by implantable devices may lead to clarification of the substrate of arrhythmias, clarification of the origin of nonspecific chest pain, and titration or preventative application of established anti-ischemic therapies. Although ST-segment monitoring algorithms are available for surface electrocardiogram, the computational demand of algorithms for implantable devices must be minimized for considerations of device longevity. The new algorithm first locates a fiducial point (FPT) at the dominant peak of each QRS complex. The ST-segment deviation (measured at 2 rate-adaptive delays after FPT, eg, FPT + 96 ms and FPT + 152 ms at 60 BPM) with respect to the isoelectric level (measured at the minimum slope preceding the QRS) is then measured. The following features are also quantified by simple operations: R-R interval, R-wave slope, R-wave amplitude, ST-segment slope, and noise content during the isoelectric segment. Inconsistencies in these features relative to their adaptive normal ranges are used to reject noisy or ectopic beats and sudden morphology changes. Finally, the ST-segment deviation over time is filtered to reject rates of change that are not likely attributable to human ischemia. Performance of the algorithm was evaluated on the European Society of Cardiology ST-T Database, which contains 180 hours of ambulatory electrocardiogram with 250 expert-annotated ischemic episodes. The sensitivity was 79% [74% 84%] (mean [95% CI]) and positive predictivity was 81% [76% 86%]. This performance is statistically equivalent to that of published electrocardiogram algorithms that were validated on the same dataset. Estimates of computational burden suggest that the algorithm could process two channels of electrogram continuously for more than 5 years with current implanted device technology. In conclusion, we have developed an algorithm for ST-segment monitoring that can be implemented in current implantable devices with sensitivity and positive predictivity that are comparable with the state-of-the-art.

Algorithms↗

PubMed2002

Evaluation of gene-finding algorithms by a content-balancing accuracy index.

A content-balancing accuracy index, called q(9), to evaluate gene-finding algorithms has been proposed. Here the concept of content-balancing means that the evaluation by this index is independent of the coding and non-coding composition of the sequence being evaluated. Since the coding and non-coding compositions are severely unbalanced in eukaryotic genomes, the performance of gene-finding algorithms is either over- or under-evaluated by the widely used accuracy indices, e.g., the correlation coefficient, due to the lack of content-balancing ability. Using the new accuracy index q(9), seven gene-finding algorithms, FGENES; Gene-Mark.hmm; Genie; Genescan; HMMgene; Morgan and MZEF, were compared and evaluated. It is shown that Genescan is still the best one, but with q(9)= 89%, averaged over the prediction for 195 sequences. In addition to the content-balancing ability, q(9) has the merit of having definition in all possible cases. It is also shown that the traditional specificity s(p) carries important information on the performance of the algorithm being evaluated. The set of sensitivity s(n), specificity s(p) and the accuracy q(9) constitutes a complete kit to evaluate gene-finding algorithms at nucleotide level. In addition, a graphic method to compare and evaluate gene-finding algorithms has been proposed, too. Its major advantage is that the overall performance of algorithms can be grasped quickly in a perceivable form. Additionally, the new accuracy index q(9) may be applied to evaluate the performance of weather forecast, clinical diagnosis, psychological examination and protein secondary structure prediction etc.

Algorithms↗

PubMed1994

Evaluation of algorithms for tomographic reconstruction of chemical concentrations in indoor air.

Numerical studies were performed to evaluate and compare four different algorithms for tomographically reconstructing pollutant concentrations in indoor air measured with an optical remote sensing system. With a remote sensing/computed tomography system, two-dimensional maps of air concentrations can be created for an entire room with good spatial and temporal resolution. The success of such a system for characterizing the flow of contaminants in air, exposure assessment, and leak detection depends on the choice of tomographic reconstruction algorithm. A systematic method was developed to evaluate the performance of four algorithms: ART, ART3, SIRT, and SART. One hundred and twenty test maps were reconstructed by each algorithm under ideal and nonideal sampling conditions, and image quality was evaluated using four criteria. The nonideal sampling conditions included simulation of measurement noise and reduction in the number density of rays. Performance of the algorithms was found to be intimately related to the number of peaks in the test maps. The importance of using multiple measures of image quality was underscored by the fact that for some sampling conditions simulated, performance of the algorithms was judged differently depending on the evaluation criteria. Results indicated that using numerical studies is successful for evaluating such algorithms.

Air Pollutants, Occupational↗

PubMed2001

A sequence alignment algorithm with an arbitrary gap penalty function.

An algorithm for aligning biological sequences is presented that is an adaptation of the sequence generating function approach used in the statistical mechanics of biopolymers. This algorithm uses recursion relationships developed from a partition function formalism of alignment probabilities. It is implemented within a dynamic programming format that closely resembles the forward algorithm used in hidden Markov models (HMM). The algorithm aligns sequences or structures according to the statistically dominant alignment path and will be referred to as the SDP algorithm. An advantage of this method over previous ones is that it allows more complicated and physically realistic gap penalty functions to be incorporated into the algorithm in a facile manner. The performance of this algorithm in a case study of aligning the heavy and light chain from the variable region of an immunoglobulin is investigated.

Algorithms↗

PubMed2001

A linear-time algorithm for computing inversion distance between signed permutations with an experimental study.

Hannenhalli and Pevzner gave the first polynomial-time algorithm for computing the inversion distance between two signed permutations, as part of the larger task of determining the shortest sequence of inversions needed to transform one permutation into the other. Their algorithm (restricted to distance calculation) proceeds in two stages: in the first stage, the overlap graph induced by the permutation is decomposed into connected components; then, in the second stage, certain graph structures (hurdles and others) are identified. Berman and Hannenhalli avoided the explicit computation of the overlap graph and gave an O(nalpha(n)) algorithm, based on a Union-Find structure, to find its connected components, where alpha is the inverse Ackerman function. Since for all practical purposes alpha(n) is a constant no larger than four, this algorithm has been the fastest practical algorithm to date. In this paper, we present a new linear-time algorithm for computing the connected components, which is more efficient than that of Berman and Hannenhalli in both theory and practice. Our algorithm uses only a stack and is very easy to implement. We give the results of computational experiments over a large range of permutation pairs produced through simulated evolution; our experiments show a speed-up by a factor of 2 to 5 in the computation of the connected components and by a factor of 1.3 to 2 in the overall distance computation.

Algorithms↗

PubMed2002

A structural EM algorithm for phylogenetic inference.

A central task in the study of molecular evolution is the reconstruction of a phylogenetic tree from sequences of current-day taxa. The most established approach to tree reconstruction is maximum likelihood (ML) analysis. Unfortunately, searching for the maximum likelihood phylogenetic tree is computationally prohibitive for large data sets. In this paper, we describe a new algorithm that uses Structural Expectation Maximization (EM) for learning maximum likelihood phylogenetic trees. This algorithm is similar to the standard EM method for edge-length estimation, except that during iterations of the Structural EM algorithm the topology is improved as well as the edge length. Our algorithm performs iterations of two steps. In the E-step, we use the current tree topology and edge lengths to compute expected sufficient statistics, which summarize the data. In the M-Step, we search for a topology that maximizes the likelihood with respect to these expected sufficient statistics. We show that searching for better topologies inside the M-step can be done efficiently, as opposed to standard methods for topology search. We prove that each iteration of this procedure increases the likelihood of the topology, and thus the procedure must converge. This convergence point, however, can be a suboptimal one. To escape from such "local optima," we further enhance our basic EM procedure by incorporating moves in the flavor of simulated annealing. We evaluate these new algorithms on both synthetic and real sequence data and show that for protein sequences even our basic algorithm finds more plausible trees than existing methods for searching maximum likelihood phylogenies. Furthermore, our algorithms are dramatically faster than such methods, enabling, for the first time, phylogenetic analysis of large protein data sets in the maximum likelihood framework.

Algorithms↗

PubMed1998

Algorithms and software for support of gene identification experiments.

MOTIVATION: Gene annotation is the final goal of gene prediction algorithms. However, these algorithms frequently make mistakes and therefore the use of gene predictions for sequence annotation is hardly possible. As a result, biologists are forced to conduct time-consuming gene identification experiments by designing appropriate PCR primers to test cDNA libraries or applying RT-PCR, exon trapping/amplification, or other techniques. This process frequently amounts to 'guessing' PCR primers on top of unreliable gene predictions and frequently leads to wasting of experimental efforts. RESULTS: The present paper proposes a simple and reliable algorithm for experimental gene identification which bypasses the unreliable gene prediction step. Studies of the performance of the algorithm on a sample of human genes indicate that an experimental protocol based on the algorithm's predictions achieves an accurate gene identification with relatively few PCR primers. Predictions of PCR primers may be used for exon amplification in preliminary mutation analysis during an attempt to identify a gene responsible for a disease. We propose a simple approach to find a short region from a genomic sequence that with high probability overlaps with some exon of the gene. The algorithm is enhanced to find one or more segments that are probably contained in the translated region of the gene and can be used as PCR primers to select appropriate clones in cDNA libraries by selective amplification. The algorithm is further extended to locate a set of PCR primers that uniformly cover all translated regions and can be used for RT-PCR and further sequencing of (unknown) mRNA.

Algorithms↗

PubMed1999

A RAPID algorithm for sequence database comparisons: application to the identification of vector contamination in the EMBL databases.

MOTIVATION: Word-matching algorithms such as BLAST are routinely used for sequence comparison. These algorithms typically use areas of matching words to seed alignments which are then used to assess the degree of sequence similarity. In this paper, we show that by formally separating the word-matching and sequence-alignment process, and using information about word frequencies to generate alignments and similarity scores, we can create a new sequence-comparison algorithm which is both fast and sensitive. The formal split between word searching and alignment allows users to select an appropriate alignment method without affecting the underlying similarity search. The algorithm has been used to develop software for identifying entries in DNA sequence databases which are contaminated with vector sequence. RESULTS: We present three algorithms, RAPID, PHAT and SPLAT, which together allow vector contaminations to be found and assessed extremely rapidly. RAPID is a word search algorithm which uses probabilities to modify the significance attached to different words; PHAT and SPLAT are alignment algorithms. An initial implementation has been shown to be approximately an order of magnitude faster than BLAST. The formal split between word searching and alignment not only offers considerable gains in performance, but also allows alignment generation to be viewed as a user interface problem, allowing the most useful output method to be selected without affecting the underlying similarity search. Receiver Operator Characteristic (ROC) analysis of an artificial test set allows the optimal score threshold for identifying vector contamination to be determined. ROC curves were also used to determine the optimum word size (nine) for finding vector contamination. An analysis of the entire expressed sequence tag (EST) subset of EMBL found a contamination rate of 0.27%. A more detailed analysis of the 50 000 ESTs in est10.dat (an EST subset of EMBL) finds an error rate of 0.86%, principally due to two large-scale projects. AVAILABILITY: A Web page for the software exists at http://bioinf.man.ac.uk/rapid, or it can be downloaded from ftp://ftp.bioinf.man.ac.uk/RAPID CONTACT: crispin@cs.man.ac.uk

Algorithms↗