Practical considerations for a method of rapid cardiac function analysis based on three-dimensional speckle tracking in a three-dimensional diagnostic ultrasound system

• Published in: Journal of medical ultrasonics (2001) Vol. 37; no. 2; pp. 41 - 49
• Main Authors: Takeguchi, Tomoyuki, Nishiura, Masahide, Abe, Yasuhiko, Ohuchi, Hiroyuki, Kawagishi, Tetsuya
• Format: Journal Article
• Language: English
• Published: Japan Springer Japan 01.04.2010; Springer; Springer Nature B.V
• Subjects: Algorithms; Cardiac function; Errors; Function analysis; Heart; Imaging; Information management; Mathematical models; Medicine; Medicine & Public Health; Methods; Numerical models; Original Article; Radiology; Software; Three dimensional analysis; Three dimensional imaging; Time series; Tracking; Ultrasonic imaging; Ultrasound; Speckle tracking; 3D echocardiography; Strain
• ISSN: 1346-4523; 1613-2254
• DOI: 10.1007/s10396-009-0249-8

Purpose The purpose of this study was to validate the accuracy of our novel 3D speckle tracking method by using numerical data, and to demonstrate the rapid processing of this method by using data obtained from human subjects. Methods In order to create a method that can rapidly assess cardiac function in regional heart wall segments, a 3D speckle tracking algorithm was created that focuses on data quality and performance. Prototype application software based on this algorithm was written to evaluate cardiac wall motion and to calculate indices such as strain. Time series 3D image data were generated for artificial numerical models that simulate the shape of the left ventricle and exhibit various types of motion. We compared observed values returned by the algorithm with expected values yielded by the models. This software was also applied to volume data of the human heart acquired by a 3D ultrasound system. Results Measurement of the indices was evaluated by using an error ratio that was a residual between an expected value and estimated one divided by the expected value. The average error ratio of the time series volumes was less than 5% for all indices, and no individual error ratio was more than 10% for numerical models. The process was complete within 0.5 s per frame for human heart volumes. Conclusion This application software can provide good estimates of various wall motion indices. The results are similar to data from numerical models, and are provided quickly enough for routine clinical usage.