A new automated system to identify a consistent sampling position to make tissue Doppler and transmitral Doppler measurements of E, E′ and E/E′

INTERNATIONAL JOURNAL OF CARDIOLOGY

卷:155

Article

Dhutia, Niti M.^1,2  Cole, Graham D.²  Willson, Keith²  Rueckert, Daniel³  Parker, Kim H.^1,2  Hughes, Alun D.²  Francis, Darrel P.² 

[1] Univ London Imperial Coll Sci Technol & Med, Dept Bioengn, London SW7 2AZ, England

[2] Univ London Imperial Coll Sci Technol & Med, Natl Heart & Lung Inst, Int Ctr Circulatory Hlth, London, England

[3] Univ London Imperial Coll Sci Technol & Med, Dept Comp, London SW7 2AZ, England

关键词: Echocardiography;    Doppler;    Pulsed;    Heart failure;    Systolic;    Heart failure;    Diastolic;    Automated;   

DOI  :  10.1016/j.ijcard.2010.10.048

来源: Elsevier

【 摘 要 】

Background: Transmitral pulse wave (PW) Doppler and annular tissue Doppler velocity measurements provide valuable diagnostic and prognostic information. However, they depend on an echocardiographer manually selecting positions to make the measurements. This is time-consuming and open to variability, especially by less experienced operators. We present a new, automated method to select consistent Doppler velocity sites to measure blood flow and muscle function. Methods: Our automated algorithm combines speckle tracking and colour flow mapping to locate the septal and lateral mitral valve annuli (to measure peak early diastolic velocity, E') and the mitral valve inflow (to measure peak inflow velocity, E). We also automate peak velocity measurements from resulting PW Doppler traces. The algorithm-selected locations and time taken to identify them were compared against a panel of echo specialists - the current gold standard. Results: The algorithm identified positions to measure Doppler velocities within 3.6 +/- 2.2 mm (mitral inflow), 3.2 +/- 1.8 mm (septal annulus) and 3.8 +/- 1.5 mm (lateral annulus) of the consensus of 3 specialists. This was less than the average 4 mm fidelity with which the specialists could themselves identify the points. The automated algorithm could potentially reduce the time taken to make these measurements by 60 +/- 15%. Conclusions: Our automated algorithm identified sampling positions for measurement of mitral flow, septal and lateral tissue velocities as reliably as specialists. It provides a rapid, easy method for new specialists and potentially non-specialists to make automated measurements of key cardiac physiological indices. This could help support decision-making, without introducing delay and extend availability of echocardiography to more patients. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

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