Biomedical subjects

E A Geiser

Publications and source records attributed to E A Geiser.

39 records · Page 3Linked to original sources

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↗

PubMedDate not supplied

Inhaled gases affect the ultrasound contrast produced by Albunex in anesthetized dogs.

In anesthetized animals maintained with isoflurane using 100% oxygen as a carrier gas, Albunex (Molecular Biosystems, Inc., San Diego, Calif.) produced no ultrasound contrast in the left ventricle after intravenous administration. The current study tested the hypothesis that the inhalation of gas mixtures with increased concentrations of oxygen decreased the quality and duration of Albunex-induced contrast. Albunex (0.22 mL/kg) was injected intravenously into anesthetized dogs (n = 9) breathing compressed air, oxygen, mixtures of oxygen and nitrogen, or combinations of oxygen and nitrous oxide. Albunex produced ultrasound contrast of shorter duration and decreased quality during the inhalation of gas mixtures containing increased amounts of oxygen. In the presence of inhaled gas mixtures containing nitrous oxide, Albunex produced no contrast in the left ventricle, regardless of the oxygen content. These data indicate that the inhalation of gas mixtures containing smaller amounts of nitrogen, compared with air, decreased the ability of Albunex to cause ultrasound contrast in the heart after intravenous administration.

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