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Biomedical subjects

E A Geiser

Publications and source records attributed to E A Geiser.

9 recordsLinked to original sources
PubMed1992

Use of transesophageal echocardiography to visualize an anomalous right coronary artery arising from the left main coronary artery (single coronary artery).

This case report demonstrates a role for transesophageal echocardiography in defining the course of anomalous coronary arteries. Origin of the right coronary artery (RCA) from the left main (LM) (single coronary artery) is an exceedingly rare congenital anomaly. It is not always benign and may result in myocardial infarction. This may be due to compression between the aorta and the pulmonary artery. Transesophageal echocardiography offers a low-risk, noninvasive means of imaging the proximal coronary arteries. In the majority of patients, the proximal segments of the three major coronaries can be clearly visualized. With the addition of color flow, it is possible to visualize flow in most patients. Proximal obstructive lesions can be seen in some patients although sensitivity thus far seems low.

Blood Flow Velocity↗
PubMed1975

The left ventricle in anomalous pulmonary venous return. Morphometric analysis of 36 fatal cases in infancy.

The mass of the left ventricle is normal in infants with total anomalous pulmonary venous return, but the ventricular cavity is compromised by leftward displacement of the interventricular septum due to the combined pressure-volume overload of the right side of the heart. Severe septal displacement is associated with distorted myocardial architecture in the region of the septal attachments of the left ventricular free wall. Abnormalities of septal motion are frequently detected in echocardiograms. Left ventricular output is low, as judged by arrested development of the aortic valve circumference, and is probably compromised both by the left to right shunt and by septal displacement. Successful correction of the anomaly may depend on intervention before the changes in septal position, structure, and function have become irreversible.

Cardiac Output↗
PubMedDate not supplied

A method for evaluation of enhancement operations in two-dimensional echocardiographic images.

A means of estimating the degree of enhancement of structure and suppression of background noise in filtered two-dimensional echocardiographic images is described. The method is termed the peak-to-background ratio. To test the method, two-dimensional short-axis echocardiographic images were enhanced with Laplacian operations of increasing mask size. There was excellent correlation between the calculated peak-to-background ratio and the subjective opinion of trained echocardiographers. Furthermore, radial length measurements made from images that were thought to be optimally enhanced by the peak-to-background ratio calculation showed the lowest interobserver mean differences. We conclude that the peak-to-background ratio does reflect improvement in characteristics of the image that favor more precise measurement (amplification of peaks and suppression of background) and can be used to help guide a dynamic approach to image processing.

Analog-Digital Conversion↗
PubMedDate not supplied

Applications of cross-correlation techniques to the quantitation of wall motion in short-axis two-dimensional echocardiographic images.

Echocardiography is now a mainstay in the diagnosis of cardiovascular disease. Rapid methods for quantitation of the images would provide an effective tool for the diagnosis of change in left ventricular function. The purpose of this article is to show the feasibility of using the cross-correlation technique to quantify change in left ventricular function over time in two-dimensional short-axis echocardiographic images. Radial histograms of radial distance versus the number of probable specular targets are formed in eight sectors on each frame during the cardiac cycle. These histograms are then shifted to a position of best correlation. The number of radial bins through which the histograms at end systole are shifted to correlate with those of the frame at end diastole defines the regional motion. The methods are described and preliminary findings are presented.

Algorithms↗
PubMedDate not supplied

A second-generation computer-based edge detection algorithm for short-axis, two-dimensional echocardiographic images: accuracy and improvement in interobserver variability.

The present study tested the hypothesis that a second-generation endocardial edge detection algorithm that used a priori endocardial and epicardial information would improve accuracy and reduce the variability of border definition. Five nonexpert observers utilized the version 2 algorithm on 20 cycles of two-dimensional short-axis images (five excellent, seven good, and eight poor quality studies stored digitally from a previously reported project). Manually defined areas by five recognized experts on these 20 cardiac cycles were considered to be "true areas." Areas defined by the experts with version 1 of the algorithm were also used for comparison. Regression of the version 2 areas with mean, manually defined excellent quality areas yielded a similar correlation (r = 0.985) to that reported between the manual and the version 1 areas (r = 0.986). For all 20 cycles in the series, however, the correlation between version 2 and the manually defined areas was lower (r = 0.952) than that of the same correlation with version 1 areas (r = 0.980). For all studies the interobserver variability (percent area difference) was +/- 14.4% for manually defined borders, +/- 11.1% for version 1-defined borders, and +/- 7.7% for version 2-defined borders. No difference in variability was observed for excellent quality studies (+/- 5.3% versus 5.2%) between version 1 and version 2 areas. However, the version 2 algorithm significantly reduced interobserver variability for good and poor quality studies (+/- 8.4% to 7.6%, p less than 0.025, and 16.3% to 9.1%, p less than 0.05, respectively). We concluded that: the version 2 algorithm provided accuracy and significantly reduced the variability of area measurement in good and poor quality studies and that epicardial information was important to the improvement by providing wall thickness information to assist in filling areas of dropout and avoidance of intracavitary structures.

Algorithms↗
PubMedDate not supplied

Clinical validation of an edge detection algorithm for two-dimensional echocardiographic short-axis images.

The purpose of this study was to validate an edge detection algorithm for short-axis two-dimensional echocardiographic studies in a protocol that stimulated its implementation at multiple clinical laboratories. Six short-axis two-dimensional echocardiographic studies were solicited from each of five clinical laboratories. A single cardiac cycle from each of the resulting 30 studies was entered into the computer system. Five expert observers came to the laboratory on separate occasions and traced endocardial borders from the short-axis studies on 2 separate days. The computer algorithm generated borders on each frame of the cardiac cycles on the basis of regions of search defined by the observers. Of the 30 original studies, five were considered excellent, seven were good, nine were poor, and nine were technically inadequate by consensus of the five observers. The correlation coefficient for computer-defined borders with manually defined borders in the excellent quality studies was 0.985. Interobserver variability was expressed as the mean percent area difference for all possible pairings of observers. The mean percent area differences were decreased from +/- 9.8% to +/- 5.3%, +/- 12.5% to +/- 8.4%, and +/- 17.4% to +/- 15.6% when comparing observer with computer-generated borders in the excellent, good, and poor quality studies, respectively. Intraobserver variability was expressed as decrease in mean percent area difference on corresponding frames between days 1 and 2. Intraobserver variability was decreased from +/- 6.5% to +/- 4.5%, +/- 10.8% to +/- 7.0%, and +/- 14.0% to +/- 11.9%, respectively. All reductions in variability were statistically significant at p less than 0.01. Observer acceptance of computer-defined borders was estimated at 94%, 93%, and 97% for excellent, good, and poor quality studies, respectively. Once the observer defined a region of search, computer process time to generate all borders in the cardiac cycle was approximately 4 minutes. The conclusion is that the algorithm produces accurate, reliable, and acceptable borders.

Algorithms↗