Differentiation between gaseous and formed embolic materials in vivo. Application in prosthetic heart valve patients.

Abstract

Background and Purpose Doppler emboli detection is an established technique, but the nature of the underlying embolic material remains unclear. The intensity and spectral distribution of emboli signals could help to distinguish between signals arising from formed and gaseous emboli. We undertook this study to develop and evaluate a differentiation algorithm based on the spectral characteristics of emboli signals. Subsequently the algorithm was applied to patients with mechanical prosthetic cardiac valves.Methods Emboli signals detected in patients with carotid disease, acute stroke, and atrial fibrillation were used as formed emboli data, and signals detected in patients undergoing cardiac catheterization studies were used as gaseous emboli data. For each embolus signal, the maximal amplitude, the sum of amplitudes, and the spectral intensity distribution were calculated. Two hundred emboli signals from each category were used to develop a differentiation algorithm, which was subsequently evaluated on 501 additional solid and 995 gaseous emboli signals. The same algorithm was used to

Automatic Classification of HITS Into Artifacts or Solid or Gaseous Emboli by a Wavelet Representation Combined With Dual-Gate TCD

“…The emboli originating from ICA stenoses are all particulate by default, because no air is able to enter the arterial system. 17,19,21,[31][32][33] Two hundred solid emboli were recorded in 24 patients (67Ϯ9 years old) admitted to the 5 neurology departments for stroke attributed to a severe ICA stenosis (Ͼ70% lumen narrowing) diagnosed by both CDFI and MR angiography, in whom no coexisting cause of stroke was found after a complete diagnostic examination, including transesophageal echocardiography. At the time of TCD embolus detection, they were taking aspirin.…”

A Comparison of Four Methods for Distinguishing Doppler Signals From Gaseous and Particulate Emboli

“…It was also noted that the embolic signals with higher MEP values had significantly longer embolic signal durations. Georgiadis et al 8 injected various compositions and sizes of emboli into an in vitro flow model and found a positive correlation between MEP and embolic size, with MEP values being comparable to those seen in vivo. Droste et al 9 found a distinct inverse relationship between embolic velocity and embolic signal duration in both in vivo and in vitro studies for all sizes and compositions of emboli.…”

Relative Energy Index of Microembolic Signal Can Predict Malignant Microemboli

“…All therapeutic studies to date have measured treatment effect by the reduction in MES counts with a variety of therapies. 24 -27 The number of MES likely has some importance in predicting risk of stroke, as best demonstrated by Levi et al 28 in the dextran study of carotid endarterectomy candidates, which reported a 77% chance of stroke if Ͼ50 MES occurred per hour. Subsequent work suggested detection rate Ͼ10 MES per 30 minutes was associated with high postoperative stroke rate.…”

“…31 Measured embolus-to-blood ratio can be converted into MaxI on PMD display, which represents maximal power of MES. 18 Powerbased methods using measured embolus-to-blood ratio (MaxI on PMD display) are most promising 28 ; however, sound intensity for solid emboli (for example, red cell aggregate) does not increase monotonically with power; therefore, any 1 value of MaxI on PMD display could correspond to 2 or 3 different embolus sizes. 15 For this reason, the MaxI is not considered sufficient to characterize size of emboli unless other information is simultaneously provided.…”