Computers and biomedical research, an international journal最新文献

Event Graphs, conditional representations of stochastic relationships between discrete events, simulate disease dynamics. In this paper, we demonstrate how Event Graphs, at an appropriate abstraction level, also extend and organize scientific knowledge about diseases. They can identify promising treatment strategies and directions for further research and provide enough detail for testing combinations of new medicines and interventions. Event Graphs can be enriched to incorporate and validate data and test new theories to reflect an expanding dynamic scientific knowledge base and establish performance criteria for the economic viability of new treatments. To illustrate, an Event Graph is developed for mastitis, a costly dairy cattle disease, for which extensive scientific literature exists. With only a modest amount of imagination, the methodology presented here can be seen to apply modeling to any disease, human, plant, or animal. The Event Graph simulation presented here is currently being used in research and in a new veterinary epidemiology course.

This paper introduces a number of reliability criteria for computer-aided diagnostic systems for breast cancer. These criteria are then used to analyze some published neural network systems. It is also shown that the property of monotonicity for the data is rather natural in this medical domain, and it has the potential to significantly improve the reliability of breast cancer diagnosis while maintaining a general representation power. A central part of this paper is devoted to the representation/narrow vicinity hypothesis, upon which existing computer-aided diagnostic methods heavily rely. The paper also develops a framework for determining the validity of this hypothesis. The same framework can be used to construct a diagnostic procedure with improved reliability.

Multichannel algorithms have been developed for more accurate analysis of electrocardiograms (ECGs). Their benefit is the ability to use the information contained in all simultaneously acquired channels. In this paper we present a multichannel version of a nonsyntactic algorithm, based on length transformation. The proposed algorithm uses a decentralized schema for combining the results derived from each individual lead, instead of a global/centralized one (a spatial vector approach). Its performance was evaluated using the CSE database and real ECGs acquired by a 12-lead cardiograph. The results are also compared with previous—single-channel and multichannel—versions of the algorithm, showing a better performance. Since a multichannel algorithm is always a time-consuming task, it is rarely used in real-time monitoring systems. Motivated by this observation, we designed a parallel implementation of the proposed algorithm and tested its ability to be used in such systems.

A closed-loop model of cardiopulmonary circulation has been developed for the study of right–left ventricular interaction under physiologically normal and altered conditions. The core model provides insight into the effects of ventricular interaction and pericardial mechanics on hemodynamics. The complete model contains realistic descriptions of (a) the interacting ventricular free walls and septum, (b) the atria, (c) the pericardium, and (d) the systemic and pulmonary vascular loads. The current analysis extends previous work on ventricular interaction and pericardial influence under isolated heart conditions to loading conditions imposed by a closed-loop model of the circulation. A nonlinear least-squares parameter identification method (Levenberg–Marquardt algorithm) is used, together with parameter sensitivity analysis, to estimate the values of key parameters associated with the ventricular and circulation models. Pressure measurements taken at several anatomical locations in the circulation during open-chest experiments on dogs are used as data in the identification process. The complete circulatory model, including septal and pericardial coupling, serves as a virtual testbed for assessing the global affects of localized mechanical or hemodynamic alterations. Studies of both direct and series ventricular interaction, as well as the effect of the pericardium on cardiac performance, are accomplished with this model. Alterations in model parameter values are used to predict the impact of disease and/or clinical interventions on steady-state hemodynamic performance. Additionally, a software package titled CardioPV has been developed to integrate the complete model with data acquisition tools and a sophisticated graphical user interface. The complete software package enables users to collect experimental data, use the data to estimate model parameters, and view the model outputs in an online setting.

Two inverse algorithms were applied for solving the EEG inverse problem assuming a single dipole as a source model. For increasing the efficiency of the forward computations the lead field approach based on the reciprocity theorem was applied. This method provides a procedure to calculate the computationally heavy forward problem by a single solution for each EEG lead. A realistically shaped volume conductor model with five major tissue compartments was employed to obtain the lead fields of the standard 10–20 EEG electrode system and the scalp potentials generated by simulated dipole sources. A least-squares method and a probability-based method were compared in their performance to reproduce the dipole source based on the reciprocal forward solution. The dipole localization errors were 0 to 9 mm and 2 to 22 mm without and with added noise in the simulated data, respectively. The two different inverse algorithms operated mainly very similarly. The lead field method appeared applicable for the solution of the inverse problem and especially useful when a number of sources, e.g., multiple EEG time instances, must be solved.

The purpose of this study is to investigate if fractal texture analysis can assist in the diagnostic interpretation of perfusion lung scans. Forty-five perfusion scans were acquired from patients with clinical suspicion of acute pulmonary embolism (PE) who underwent pulmonary angiography for final diagnosis. Fractal texture analysis was performed on 270 regions of interest (ROIs) extracted from the posterior view of the lung scans. Specifically, there were 94 normally perfused ROIs and 176 abnormal ROIs representing various lung diseases including PE and obstructive pulmonary disease (OPD). The average fractal dimension (FD) of normal ROIs was statistically significantly higher than that of abnormal ROIs. Furthermore, the FDs of abnormal ROIs with PE were significantly lower than the FDs of ROIs with OPD present.

In cancer chemotherapy, it is important to design treatment strategies that ensure a desired rate of tumor cell kill without unacceptable toxicity. To optimize treatment, we used a mathematical model describing the pharmacokinetics of anticancer drugs, antitumor efficacy, and drug toxicity. This model was associated with constraints on the allowed plasma concentrations, drug exposure, and leukopenia. Given a schedule of drug administrations, the mathematical model optimized the drug doses that can minimize the tumor burden while limiting toxicity at the level of the white blood cells. The main result is that the optimal drug administration is an initial high-dose chemotherapy up to saturation of constraints associated with normal cell toxicity and a maintenance continuous infusion at a moderate rate. Data related to etoposide investigations were used in a feasibility study. Simulations with the optimized protocol showed better performances than usual clinical protocols. Model-based optimal drug doses provide for greater cytoreduction, while limiting the risk of unacceptable toxicity.

Reconstructing three-dimensional (3-D) shapes of structures like internal organs from tomographic data is an important problem in medical imaging. Various forms of the deformable surface model have been proposed to tackle it, but they are either computationally expensive or limited to tubular shapes. In this paper a 3-D reconstruction mechanism that requires only 2-D deformations is proposed. Advantages of the proposed model include that it is conformable to any 3-D shape, efficient, and highly parallelizable. Most importantly, it requires from the user an initial 2-D contour on only one of the tomograph slices to start with. Experimental results are shown to illustrate the performance of the model.

We present the polysomnogram assay (PSGA), a new representation format for the polysomnogram (PSG), designed to assist in the interpretation of overnight PSG studies. The technique condenses the PSG record by a factor of 30 while preserving the ability to portray PSG features of diagnostic relevance, including sleep architecture, arousals, movement, leg jerks, cyclic alternating pattern, and increased breathing effort. The PSGA patterns associated with these events are described and illustrated by examples. The new format considerably reduces the effort required to evaluate sleep quality and continuity, making it more practicable for the polysomnographer to interpret the entire overnight PSG study. The compressed time scale also facilitates analysis of relatively long PSG episodes and allows assessment of signal activity surrounding critical PSG events. The PSGA appears capable of improving identification of arousals, leg jerks, and upper airway resistance, and may be especially amenable for automatic analysis of PSG data.

IMM/Scrub is a pilot tool developed to assist in the deduplication of vaccination history records in childhood immunization registries. This problem is complicated by a number of factors including that fact that: (1) some doses are numbered and some are not, (2) doses may have different dose numbers, (3) doses may specify different preparations within a vaccine series, (4) one dose may indicate a combination vaccine and the other dose may specify one component of that combination, (5) two doses may have slightly different dates, and (6) combinations of any of these problems may occur together. IMM/Scrub is designed to help detect 10 different types of vaccination dose duplicates and also allows the user to specify flexibly the conditions in which a duplicate dose might be automatically eliminated. In addition, IMM/Scrub is linked to the IMM/Serve immunization forecasting program, which can provide additional assistance in the data cleaning process. The paper describes (1) the design of the current pilot implementation of IMM/Scrub, (2) the lessons learned during its implementation, and (3) our preliminary experience applying it to data from three immunization databases, from a state, a metropolitan area, and an academic medical center.