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PubMed2000

Pitfalls of the concept of incremental specificity used in comparisons of dual chamber VT/VF detection algorithms.

The concepts of incremental specificity and incremental positive predictive accuracy (PPA) have been proposed to measure the success of dual chamber cardioverter defibrillator (ICD) algorithms for tachyarrhythmia detection in improving specificity while maintaining very high sensitivity to detection of episodes of ventricular tachycardia/fibrillation (VT/VF). While dual chamber VT/VF detection algorithms differ substantially among different ICD manufacturers, they all operate as "add-on" features to the single chamber elementary detection algorithms that are based on simple criteria of increased ventricular rate. The incremental specificity and PPA characterize the performance of the dual chamber detection operation in this "add-on" mode, that is within a database of rhythm episodes all meet the simple rate-based criteria. A statistical model of hypothetical devices has been used to demonstrate that the concepts of incremental specificity and PPA are very dependent on the composition of the database used to evaluate a particular dual chamber ICD. Because some sinus tachycardia and supraventricular tachyarrhythmias with regular atrioventricular conduction are more easily discriminated from true VT/VF than other supraventricular tachyarrhythmias, the model shows that rather than the performance of the dual chamber detection functions, the major contributor to the incremental specificity may be the proportion between the "easy" and "difficult" supraventricular episodes. The algorithms used by different ICD manufacturers to detect tachyarrhythmias based on ventricular rate are known to differ substantially in the ability to differentiate true VT/VF from other tachyarrhythmias. Consequently, the databases of rhythms against which the different dual camber ICDs are tested are also different in composition of different types of supraventricular tachyarrhythmias. Therefore, the values of incremental specificity and PPA reported by different manufacturers do not have an equivalent meaning and do not offer a valid comparison of the true performance of different dual chamber ICDs.

Algorithms↗

PubMed2000

Atrial pacing in the prevention of paroxysmal atrial fibrillation: first results of a new combined algorithm.

UNLABELLED: Pacing algorithms for prevention of atrial tachyarrhythmia (AT) are under clinical evaluation. The present study prospectively evaluated the efficacy of three simultaneously active algorithms for AT prevention and aimed at identifying patients in whom atrial preventive pacing (APP) may be particularly successful. METHODS: In 31 patients with conventional pacing indications and paroxysmal AT, a DDDRP pacing system was implanted, which stores 35 AT episodes with atrial electrograms and marker annotations. Counters and stored AT episodes were retrieved 30 days after implant. APP algorithms (atrial preference pacing, atrial rate stabilization, postmode switching overdrive) were activated. Counters and stored AT episodes were again retrieved 60 days later. The number and duration of AT episodes was measured. Several clinical variables were examined with respect to their ability to identify candidates for APP. RESULTS: During APP, the mean number of AT episodes/patient/day decreased from 7.67 to 1.68 (P = 0.04). However, time in AT was not significantly reduced (9.45% versus 10.41%). APP decreased the number of episodes/day in 11 patients and increased it in 9 patients. No clinical parameters predicting APP success was identified. CONCLUSIONS: APP using three algorithms significantly reduced the mean number of AT episodes/patient/day. However, the time during which patients were in AT was not reduced. No clinical variable predicted the success or failure of APP.

Aged↗

PubMed2005

Evaluation of fusion beat detection with a new ventricular automatic capture algorithm in ICDs.

This study evaluated a newly developed automatic capture verification scheme for implantable cardioverter defibrillators (ICDs) regarding discrimination of capture, fusion, and noncapture beats, with an emphasis on fusion detection. The algorithm uses evoked response detection based on a sensing vector from right ventricular shocking coil to Can. Patients undergoing ICD implant or replacement were enrolled in this study. An external system was used for pacing and data acquisition. To provoke ventricular fusion beats, VVI patients were paced close to the rate of their intrinsic rhythm and DDD patients were paced close at their intrinsic PR interval. Surface ECG and wideband filtered intracardiac electrograms were recorded for off-line analysis. Each paced beat was independently classified visually by surface ECG and by the automatic detection algorithm. The algorithm performance was then evaluated by comparing the classification results. Twenty-seven patients (22 males, 5 females; 63.8 +/- 12.5 years) were analyzed. Device and lead demographics were: 18 DDD/9 VVI; 16 dedicated bipolar, 11 integrated bipolar leads; 18 acute, 9 chronic (3.7 +/- 2.0 years) leads. In total, 2064 beats were analyzed, including 1,477 fusion beats and 587 capture beats. Fusion detection sensitivity and specificity were 99.5% and 99.0%, respectively. Seven true-fusion beats (0.5%) were classified as capture and 6 capture beats (1.0%) were identified as fusions. Capture or fusion beats were never detected as non-capture beats. It is concluded that the algorithm was effective in detecting fusion beats. It could potentially be used in ICD applications that need accurate fusion detection.

Algorithms↗

PubMed1998

A new classification algorithm for discrimination of ventricular from supraventricular tachycardia in a dual chamber implantable cardioverter defibrillator.

INTRODUCTION: The high incidence of inappropriate therapies due to supraventricular tachycardia remains a major unsolved problem of implantable cardioverter defibrillators. We report a new detection formula for discrimination of ventricular tachycardia from supraventricular tachycardia in a patient with a dual chamber implantable cardioverter defibrillator and a new atrioventricular classification algorithm. METHODS AND RESULTS: The enhanced detection algorithm performs a stepwise arrhythmia analysis. The rhythm is first classified on the basis of cycle length. Each episode is then classified as supraventricular or ventricular on the basis of atrioventricular association, stability of circle length, and origin of acceleration. Sophisticated diagnostic information is provided by atrioventricular markers and electrogram recordings. Successful discrimination of two spontaneous episodes of ventricular tachycardia and supraventricular tachycardia is demonstrated. CONCLUSION: This new dual chamber detection algorithm may significantly improve the specificity of tachyarrhythmia detection without sacrificing sensitivity, thereby reducing the number of spurious shocks in patients with recurrent supraventricular tachycardias. Further studies are needed to assess the sensitivity and specificity of this detection algorithm.

Algorithms↗

PubMed2006

The Rhythm ID Going Head to Head Trial (RIGHT): design of a randomized trial comparing competitive rhythm discrimination algorithms in implantable cardioverter defibrillators.

BACKGROUND: The implantable cardioverter defibrillator (ICD) has become primary therapy for the prevention of sudden death. One of the major morbidities of ICD use remains inappropriate therapy for supraventricular arrhythmias (SVA). Detection enhancements have increased therapy specificity, but their impact on inappropriate therapy is not well studied. Moreover, ICD manufacturers have developed unique algorithms to meet this goal, with no previous clinical direct comparisons. RIGHT is a randomized, prospective study that will assess the differential efficacy of ICDs from two different manufacturers. It is the first trial to compare directly competitive ICD rhythm discrimination algorithms on a large scale. OBJECTIVE: The primary objective of this study is to assess arrhythmia discrimination in Guidant versus Medtronic ICDs by comparing the time to first inappropriate therapy after the predischarge visit. METHODS: The study will enroll approximately 2,000 patients in 100 centers. Patients will be randomized to Guidant or Medtronic using a permuted block design, stratified by center and by single/dual chamber device types. Patients will receive a commercially available Guidant VITALITY 2 family ICD with Rhythm ID or a Medtronic ICD using the Enhanced PR Logic or Wavelet discrimination algorithms, and will be followed according to the schedule shown until a common closing date with a minimum follow-up of 12 months. All events will be reviewed by an independent committee to determine the appropriateness of rhythm classification and therapy delivery. CONCLUSION: RIGHT is the first randomized, large scale, head-to-head comparison of ICD discrimination algorithms.

Algorithms↗

PubMed2005

The full EM algorithm for the MLEs of QTL effects and positions and their estimated variances in multiple-interval mapping.

The advent of complete genetic linkage maps of DNA markers has made systematic studies of mapping quantitative trait loci (QTL) in experimental organisms feasible. The method of multiple-interval mapping provides an appropriate way for mapping QTL using genetic markers. However, efficient algorithms for the computation involved remain to be developed. In this article, a full EM algorithm for the simultaneous computation of the MLEs of QTL effects and positions is developed. EM-based formulas are derived for computing the observed Fisher information matrix. The full EM algorithm is compared with an ECM algorithm developed by Kao and Zeng (1997, Biometrics 53, 653-665). The validity of the inverted observed Fisher information matrix as an estimate of the variance matrix of the MLEs is demonstrated by a simulation study.

Algorithms↗

PubMedDate not supplied

Optimizing remediation of an unconfined aquifer using a hybrid algorithm.

We present a novel hybrid algorithm, integrating a genetic algorithm (GA) and constrained differential dynamic programming (CDDP), to achieve remediation planning for an unconfined aquifer. The objective function includes both fixed and dynamic operation costs. GA determines the primary structure of the proposed algorithm, and a chromosome therein implemented by a series of binary digits represents a potential network design. The time-varying optimal operation cost associated with the network design is computed by the CDDP, in which is embedded a numerical transport model. Several computational approaches, including a chromosome bookkeeping procedure, are implemented to alleviate computational loading. Additionally, case studies that involve fixed and time-varying operating costs for confined and unconfined aquifers, respectively, are discussed to elucidate the effectiveness of the proposed algorithm. Simulation results indicate that the fixed costs markedly affect the optimal design, including the number and locations of the wells. Furthermore, the solution obtained using the confined approximation for an unconfined aquifer may be infeasible, as determined by an unconfined simulation.

Algorithms↗

PubMed2001

A new algorithm for autoregression moving average model parameter estimation using group method of data handling.

A new algorithm for autoregresive moving average (ARMA) parameter estimation is introduced. The algorithm is based on the group method of data handling (GMDH) first introduced by the Russian cyberneticist, A. G. Ivakhnenko, for solving high-order regression polynomials. The GMDH is heuristic in nature and self-organizes into a model of optimal complexity without any a priori knowledge about the system's inner workings. We modified the GMDH algorithm to solve for ARMA model parameters. Computer simulations have been performed to examine the efficacy of the GMDH and comparison of the GMDH is made to one of the most accurate and one of the most widely used algorithms, the fast orthogonal search (FOS) and the least-squares methods, respectively. The results show that in some cases with noise contamination and incorrect model order assumptions, the GMDH performs better than either the FOS or the least-squares methods in providing only the parameters that are associated with the true model terms.

Algorithms↗

PubMed2002

A stochastic nonlinear autoregressive algorithm reflects nonlinear dynamics of heart-rate fluctuations.

Current methods for detecting nonlinear determinism in a time series require long and stationary data records, as most of them assume that the observed dynamics arise only from the internal, deterministic workings of the system, and the stochastic portion of the signal (the noise component) is assumed to be negligible. To explicitly account for the stochastic portion of the data we recently developed a method based on a stochastic nonlinear autoregressive (SNAR) algorithm. The method iteratively estimates nonlinear autoregressive models for both the deterministic and stochastic portions of the signal. Subsequently, the Lyapunov exponents (LE) are calculated for the estimated models in order to examine if nonlinear determinism is present in the deterministic portion of the fitted model. To determine if nonlinear dynamic analysis of heart-rate fluctuations can be used to assess arrhythmia susceptibility by predicting the outcome of invasive cardiac electrophysiologic study (EPS), we applied the SNAR algorithm to noninvasively measured resting sinus-rhythm heart-rate signals obtained from 16 patients. Our analysis revealed that a positive LE was highly correlated to a patient with a positive outcome of EPS. We found that the statistical accuracy of the SNAR algorithm in predicting the outcome of EPS was 88% (sensitivity=100%, specificity=75%, positive predictive value=80%, negative predictive value=100%, p=0.0019). Our results suggest that the SNAR algorithm may serve as a noninvasive probe for screening high-risk populations for malignant cardiac arrhythmias.

Adult↗

PubMedDate not supplied

A robust time-varying identification algorithm using basis functions.

We extend a recently developed time invariant (TIV) model order search criterion named the optimal parameter search algorithm (OPS) for identification of time varying (TV) autoregressive (AR) and autoregressive moving average (ARMA) models. Using the TV algorithm is facilitated by the fact that expanding each TV coefficient onto a finite set of basis sequences permits TV parameters to become TIV. Taking advantage of this TIV feature of expansion parameters exploits the features of the OPS, which has been shown to provide accurate model order selection as well as extraction of only the significant model terms. Another advantage of the new algorithm is its ability to discriminate insignificant basis sequences thereby reducing the number of expansion parameters to be estimated. Due to these features, the resulting algorithm can accurately estimate TV AR or ARMA models and determine their orders. Indeed, comparison via computer simulations of AR models between the proposed method and one of the well-known iterative methods, recursive least squares, shows the greater capability of the new method to track TV parameters. Furthermore, application of the new method to experimentally obtained renal blood flow signals shows that the new method provides higher-resolution time-varying spectral capability than does the short-time Fourier transform (STFT), concomitant with fewer spurious frequency peaks than obtained with the STFT spectrogram.

Algorithms↗

PubMed2004

An improved Morris Water Maze tracking algorithm for psychophysical studies.

An algorithm to track a rat swimming in a Morris Water Maze has been developed. The system is automatically configured to any pool and relative suitable light conditions. It tracks the rat's position and head pose 10 times per second. The output data is displayed in a bitmap and also in a text file. The system was tested with an X - Y plotter using a simulated rat swimming in the maze. Known signals were provided to a model rat and compared to the position and pose information provided by the tracking algorithm. The algorithm was able to track rat velocities up to 2.32 m/s, localize rat position to 4 mm within the maze, and provide head pose information. Early prototypes of the algorithm were also used to track actual rats in a water maze.

Algorithms↗

PubMed1999

Optimization algorithm performance in determining optimal controls in human movement analyses.

The objective of this study was to evaluate the performance of different multivariate optimization algorithms by solving a "tracking" problem using a forward dynamic model of pedaling. The tracking problem was defined as solving for the muscle controls (muscle stimulation onset, offset, and magnitude) that minimized the error between experimentally collected kinetic and kinematic data and the simulation results of pedaling at 90 rpm and 250 W. Three different algorithms were evaluated: a downhill simplex method, a gradient-based sequential quadratic programming algorithm, and a simulated annealing global optimization routine. The results showed that the simulated annealing algorithm performed for superior to the conventional routines by converging more rapidly and avoiding local minima.

Algorithms↗

PubMedDate not supplied

Novel algorithm of processing optical coherence tomography images for differentiation of biological tissue pathologies.

A numerical algorithm based on a small-angle approximation of the radiative transfer equation (RTE) is developed to reconstruct scattering characteristics of biological tissues from optical coherence tomography (OCT) images. According to the algorithm, biological tissue is considered to be a layered random medium with a set of scattering parameters in each layer: total scattering coefficient, variance of a small-angle scattering phase function, and probability of backscattering, which fully describe the OCT signal behavior versus probing depth. The reconstruction of the scattering parameters is performed by their variation to fit the experimental OCT signal by the theoretical one using a time-saving genetic algorithm. The proposed reconstruction procedure is tested on model media with known scattering parameters. The possibility to estimate scattering parameters from OCT images is studied for various regimes of OCT signal decay. The developed algorithm is applied to reconstruct optical characteristics of epithelium and stroma for normal cervical tissue and its pathologies, and the potential to distinguish between the types of pathological changes in epithelial tissue by its OCT images is demonstrated.

Algorithms↗

PubMed2000

An algorithm for automatic needle localization in ultrasound-guided breast biopsies.

An algorithm was developed in order to reduce operator dependence in ultrasound-guided breast biopsy, by automatically locating the needle in the ultrasound image, and displaying its location on the image for the user. Ultrasound images of a typical breast biopsy needle inserted in a tissue-mimicking agar were obtained to test the algorithm. The resulting images were examined by a group of observers who recorded the values of the angle, intercept and tip coordinates of the needle in the image, and inter- and intra-observer variability studies were performed on the results. The results of the algorithm segmentation were compared to the values recorded by the observers, and physical measurements recorded at the time the images were acquired. The algorithm segmentation was precise enough to successfully (when considering angle and tip segmentation) target 90% of tumors of 4.5 mm in diameter situated at the center of the image.

Algorithms↗

PubMed2000

A two-step algorithm for predicting portal dose images in arbitrary detectors.

Recently, portal imaging systems have been successfully demonstrated in dosimetric treatment verification applications, where measured and predicted images are quantitatively compared. To advance this approach to dosimetric verification, a two-step model which predicts dose deposition in arbitrary portal image detectors is presented. The algorithm requires patient CT data, source-detector distance, and knowledge of the incident beam fluence. The first step predicts the fluence entering a portal imaging detector located behind the patient. Primary fluence is obtained through ray-tracing techniques, while scatter fluence prediction requires a library of Monte Carlo-generated scatter fluence kernels. These kernels allow prediction of basic radiation transport parameters characterizing the scattered photons, including fluence and mean energy. The second step of the algorithm involves a superposition of Monte Carlo-generated pencil beam kernels, describing dose deposition in a specific detector, with the predicted incident fluence. This process is performed separately for primary and scatter fluence, and yields a predicted dose image. A small but noticeable improvement in prediction is obtained by explicitly modeling the off-axis energy spectrum softening due to the flattening filter. The algorithm is tested on a slab phantom and a simple lung phantom (6 MV). Furthermore, an anthropomorphic phantom is utilized for a simulated lung treatment (6 MV), and simulated pelvis treatment (23 MV). Data were collected over a range of air gaps (10-80 cm). Detectors incorporating both low and high atomic number buildup are used to measure portal image profiles. Agreement between predicted and measured portal dose is better than 3% in areas of low dose gradient (<30%/cm) for all phantoms, air gaps, beam energies, and detector configurations tested here. It is concluded that this portal dose prediction algorithm is fast, accurate, allows separation of primary and scatter dose, and can model arbitrary detectors.

Air↗

PubMed2002

Numerical algorithms for spatial registration of line fiducials from cross-sectional images.

We present several numerical algorithms for six-degree-of-freedom rigid-body registration of line fiducial objects to their marks in cross-sectional planar images, such as those obtained in CT and MRI, given the correspondence between the marks and line fiducials. The area of immediate application is frame-based stereotactic procedures, such as radiosurgery and functional neurosurgery. The algorithms are also suitable to problems where the fiducial pattern moves inside the imager, as is the case in robot-assisted image-guided surgical applications. We demonstrate the numerical methods on clinical CT images and computer-generated data and compare their performance in terms of robustness to missing data, robustness to noise, and speed. The methods show two unique strengths: (1) They provide reliable registration of incomplete fiducial patterns when up to two-thirds of the total fiducials are missing from the image; and (2) they are applicable to an arbitrary combination of line fiducials without algorithmic modification. The average speed of the fastest algorithm is 0.3236 s for six fiducial lines in real CT data in a Matlab implementation.

Algorithms↗

PubMed2003

Matched view weighting in tilted-plane-based reconstruction algorithms to suppress helical artifacts and optimize noise characteristics.

In multi-slice helical CT, the single-tilted-plane-based reconstruction algorithm has been proposed to combat helical and cone beam artifacts by tilting a reconstruction plane to fit a helical source trajectory optimally. Furthermore, to improve the noise characteristics or dose efficiency of the single-tilted-plane-based reconstruction algorithm, the multi-tilted-plane-based reconstruction algorithm has been proposed, in which the reconstruction plane deviates from the pose globally optimized due to an extra rotation along the 3rd axis. As a result, the capability of suppressing helical and cone beam artifacts in the multi-tilted-plane-based reconstruction algorithm is compromised. A matched view weighting approach is proposed here to optimize the capability of suppressing helical and cone beam artifacts and noise characteristics. A helical body phantom is employed to quantitatively evaluate the imaging performance of the matched view weighting approach, showing that the matched view weighting improves both the helical artifact suppression and noise characteristics or dose efficiency significantly in comparison to the case in which nonmatched view weighting is applied. The matched view weighting approach is of practical importance in the development of multi-slice helical CT, because it maintains the computational structure of fan beam filtered back-projection and demands no extra computational resources.

Algorithms↗

PubMed2004

The cone-beam algorithm of Feldkamp, Davis, and Kress preserves oblique line integrals.

The algorithm of Feldkamp, Davis, and Kress [J. Opt. Soc. Am. A 1, 612-619 (1984)] is a widely used filtered-backprojection algorithm for three-dimensional image reconstruction from cone-beam (CB) projections measured with a circular orbit of the x-ray source. A well-known property of this approximate algorithm is that the integral of the reconstructed image along any axial line orthogonal to the plane of the orbit is exact when the cone-beam projections are not truncated. We generalize this result to oblique line integrals, thus providing an efficient method to compute synthetic radiographs from cone-beam projections. Our generalized result is obtained by showing that the FDK algorithm is invariant under transformations that map oblique lines onto axial lines.

Algorithms↗