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We present a fast, automatic method for mitral annulus excursion measurement using pocket-sized ultrasound (PSU). The motivation is to provide PSU users with a rapid measurement of cardiac systolic function. The algorithm combines low-frame-rate tolerance, computational efficiency and automation in a novel way. The method uses a speckle-tracking scheme, initialized and constrained by a deformable model. A feasibility study using 30 apical four-chamber PSU recordings from an unselected patient population revealed an error of (mean ± SD) -1.80 ± 1.96 mm, p < 0.001, when compared with manual anatomic m-mode analysis using laptop scanner data. When only septal side excursion was measured, the mean error was -0.27 ± 1.89 mm, p < 0.001. The accuracy is comparable with previously reported results using semiautomatic methods and full-size scanners. The computation time of 3.7 ms/frame on a laptop computer suggests that a real-time implementation on a PSU device is feasible., (Copyright © 2011 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.)

Aims: automatic detection of the QRS complex on electrocardiogram (ECG) is used on cardiac ultrasound scanners to separate ultrasound image series into cardiac cycles for playback and storage. On small hand-held scanners it is unpractical to connect ECG cables. We therefore aim to do automatic cardiac cycle separation using apical B-mode ultrasound images., Methods and Results: cardiac cycle length is estimated by cyclicity analysis of B-mode intensities. To determine a cycle start estimate near QRS, a deformable model is fitted to the left ventricle in real-time. The model is used to initialize and constrain a speckle tracker positioned near the mitral annulus. In the displacement curve generated by the speckle tracker, a time point near maximum distance from the probe is detected as a cardiac cycle start estimate. Validation against ECG was done on 233 recordings from normal subjects and 46 recordings from subjects with coronary pathology. Several test cases were run for each recording to emulate B-mode series starting at all time points in the cardiac cycle. Totally, 11 886 test cases were run. Cycle length estimation was feasible in 98% of normal subject cases and 91% of pathology cases. Median difference in cycle length by ECG was 0 and -3 ms, respectively. Cycle start estimation was feasible in 90% of normal subject cases and 77% of pathology cases. Median difference to cycle start by ECG was 62 and 76 ms, respectively., Conclusion: apical B-mode series can automatically be separated into cardiac cycles without using ECG.