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Biomedical subjects

D M Budgett

Publications and source records attributed to D M Budgett.

2 recordsLinked to original sources

Comparison of measured and computed epicardial potentials from a patient-specific inverse model.

This study reports the first direct comparison of measured and computed epicardial potentials in which the specific anatomy of a test subject has been used to calculate the inverse electrocardiographic model. It is now feasible to obtain low-noise body surface potential maps and to incorporate accurate anatomic data into inverse procedures for the purpose of computing epicardial potential distributions. The direct verification of computed human epicardial distributions remains an important goal. The experiment reported here obtained direct measurements from six transcutaneous pacing wires that were attached to points on the epicardial surface of the human heart in an intact subject. From the same subject, a magnetic resonance scan was used to produce a specific thoracic model consisting of 5-mm cubes. The forward model uses the finite difference method to compute a forward transfer matrix that relates each of 26 epicardial regions to body surface measurements. The inverse computation was performed by zero-order Tikhonov regularization. Body surface potentials were used in the inverse procedure to compute epicardial potentials, which were then compared with direct epicardial measurements. The computed epicardial potentials were compared to the measured ones by correlation, which gave an amplitude-independent measure of similarity. Amplitude differences and time delays in computed potentials were observed, but the morphologic trend was generally well recovered. The results obtained indicate the sensitivity of the inverse model to a number of factors. The robustness of computed epicardial distributions to errors in assumed lung conductivity is shown. Results from a nonpatient-specific, but realistic, torso model are presented.(ABSTRACT TRUNCATED AT 250 WORDS)

Cardiac Pacing, Artificial↗

Parallel computation of ECG fields.

A parallel implementation of a finite difference model for computing the electric field of cardiac sources is presented. On a relatively inexpensive SIMD parallel computer, a full-forward solution is obtained in minutes, using accurate thoracic detail including anisotropy if required. Because the computation is based on a volume grid with constant size voxels, it readily accepts anatomical data from classified magnetic resonance imaging scans. By using a variation of the colored successive over-relaxation iteration, our finite difference model takes full advantage of the performance of massively parallel computers. Evaluations of the accuracy and performance of the model show the practicality of using specific anatomical models to recover the electrocardiographic field distributions for individual subjects. A relatively modest parallel machine is capable of assembling and computing a specific direct inverse solution from body surface potentials within an hour of measurement, assuming the magnetic resonance imaging classification has been previously completed.

Electrocardiography↗