A fully automated method for late ventricular diastole frame selection in post-dive echocardiography without ECG gating.

Journal Article (Journal Article)

Venous gas emboli (VGE) are often quantified as a marker of decompression stress on echocardiograms. Bubble-counting has been proposed as an easy to learn method, but remains time-consuming, rendering large dataset analysis impractical. Computer automation of VGE counting following this method has therefore been suggested as a means to eliminate rater bias and save time. A necessary step for this automation relies on the selection of a frame during late ventricular diastole (LVD) for each cardiac cycle of the recording. Since electrocardiograms (ECG) are not always recorded in field experiments, here we propose a fully automated method for LVD frame selection based on regional intensity minimization. The algorithm is tested on 20 previously acquired echocardiography recordings (from the original bubble-counting publication), half of which were acquired at rest (Rest) and the other half after leg flexions (Flex). From the 7,140 frames analyzed, sensitivity was found to be 0.913 [95% CI: 0.875-0.940] and specificity 0.997 [95% CI: 0.996-0.998]. The method's performance is also compared to that of random chance selection and found to perform significantly better (p≺0.0001). No trend in algorithm performance was found with respect to VGE counts, and no significant difference was found between Flex and Rest (p>0.05). In conclusion, full automation of LVD frame selection for the purpose of bubble counting in post-dive echocardiography has been established with excellent accuracy, although we caution that high quality acquisitions remain paramount in retaining high reliability.

Full Text

Duke Authors

Cited Authors

  • Markley, E; Le, DQ; Germonpré, P; Balestra, C; Tillmans, F; Denoble, P; Freiberger, JJ; Moon, RE; Dayton, PA; Papadopoulou, V

Published In

Volume / Issue

  • 48 / 1

Start / End Page

  • 73 - 80

PubMed ID

  • 33648036

International Standard Serial Number (ISSN)

  • 1066-2936

Language

  • eng

Conference Location

  • United States