Department of Bioengineering, Imperial College of Science, Technology, and Medicine, London SW7 2AZ, United Kingdom.
Int J Cardiol. 2012 Mar 22;155(3):394-9. doi: 10.1016/j.ijcard.2010.10.048. Epub 2010 Nov 20.
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.
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".
The algorithm identified positions to measure Doppler velocities within 3.6 ± 2.2mm (mitral inflow), 3.2 ± 1.8mm (septal annulus) and 3.8 ± 1.5mm (lateral annulus) of the consensus of 3 specialists. This was less than the average 4mm 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%.
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.
二尖瓣血流多谱勒（PW）和环组织多谱勒速度测量提供了有价值的诊断和预后信息。然而，它们依赖于心超医师手动选择位置进行测量。这既耗时又容易产生变异性，尤其是对于经验不足的操作人员来说。我们提出了一种新的自动方法，用于选择一致的多谱勒速度位置来测量血流和肌肉功能。
我们的自动算法结合了斑点追踪和彩色血流图，以定位隔瓣和侧瓣二尖瓣环（测量早期舒张峰值速度 E'）和二尖瓣流入（测量峰值流入速度 E）。我们还自动测量 PW 多谱勒迹线的峰值速度。将算法选择的位置和识别这些位置所需的时间与一组超声专家进行了比较，这是目前的“黄金标准”。
该算法在 3.6±2.2mm（二尖瓣流入）、3.2±1.8mm（隔瓣环）和 3.8±1.5mm（侧瓣环）的范围内确定了测量多谱勒速度的位置，这比专家们自己能够识别这些点的平均 4mm 精度要小。该自动算法有可能将完成这些测量的时间减少 60±15%。
我们的自动算法识别出了测量二尖瓣血流、间隔和侧瓣组织速度的采样位置，与专家一样可靠。它为新专家和潜在的非专家提供了一种快速、简便的方法，用于自动测量关键的心脏生理指标。这有助于支持决策，而不会引入延迟，并使更多的患者能够获得超声心动图检查。
