Editorials |
, MD and
From The Cleveland Clinic Foundation, Cleveland, Ohio.
Correspondence to James D. Thomas, MD, FAHA, Department of Cardiology, Desk F-15, The Cleveland Clinic Foundation, 9500 Euclid Ave, Cleveland, OH 44195. E-mail thomasj{at}ccf.org
Key Words: Editorials echocardiography cardiac resynchronization therapy heart failure pacing pacemakers
"It came out of nowhere and captured the cardiology community by storm." The cliché seems very appropriate when describing the impact of cardiac resynchronization therapy (CRT) on the treatment of heart failure. CRT improves survival rate in symptomatic patients 1 and is the only nonsurgical technique that provides substantial and stable reverse remodeling in both symptomatic and asymptomatic patients.2,3 The most surprising fact is that this is accomplished through mechanisms that are still unclear and that are not fully elucidated in experimental models. CRT is the only heart failure therapy with a potential to improve survival rate that is not based on neurohormonal modulation. Finally, it represents a challenge to the imaging community, as it establishes a need to measure something that was previously overlooked—dyssynchrony.
Article see p 14
Unfortunately, CRT is not universally successful. One third of CRT patients do not feel better,4 and close to 40% of patients do not experience reverse remodeling, which is important because it predicts survival rate.5 This should not be a surprise—treatment of chronic diseases is rarely homogenously beneficial to all the patients. Nevertheless, in the case of CRT, some extra precautions are necessary. CRT is expensive; placement of electrodes may be difficult; and, even in experienced centers, a significant number of patients may require surgical placement. Finally, it is an expensive, healthcare-intensive therapy with extensive follow-up and occasional complications. Thus, there is an ongoing search for practical methods to predict the outcome of CRT and guide its use. Current guidelines use QRS duration (and symptoms) as the principal determinants for implantation, and as noted, this is fairly successful, with two thirds of such patients demonstrating improvement. The real challenge for clinicians comes in two situations: identifying those patients with narrow QRS who are likely to benefit and identifying those with wide QRS who will not benefit. Mechanical dyssynchrony has been proposed as the key predictor in both of these situations.
The contraction of ventricular segments can be quantified by myocardial velocities, strains, or strain rates. Whereas myocardial velocities simply represent a movement of a segment relative to some reference point, strains measure relative local deformation along 3 major cardiac axes. Plotting the changes of myocardial velocities, strains, or strain rates of individual segments through time can give us insight into ventricular function synchrony. Intraventricular dyssynchrony can then be quantified by how much peak values of these segmental tracings vary in their timing or in their maximal values (amplitudes).
Early on, magnetic resonance imaging strain studies showed that left bundle-branch block leads to uncoordinated contraction of ventricular segments and results in intraventricular mechanical dyssynchrony.6 Magnetic resonance imaging studies have also shown that earliest contracting segments show mid-systolic blunting of contraction (because of late forceful contraction of lateral segments), often with late- (or even post-) systolic peak.7 In contrast, late contracting segments contract forcefully because of early stretch and activation of the Starling mechanism.7 Indeed, this interplay of early and late segments is the basis for using preexcitation of ischemic segments to prevent postinfarct remodeling.8 Magnetic resonance imaging studies also have shown that CRT decreases both time- and amplitude-based measures of intraventricular dyssynchrony.6,9 In addition to this intraventricular dyssynchrony, interventricular dyssynchrony also exists (as is well known to anybody who has auscultated a patient with bundle-branch block), although its importance is less well established.10
Analysis of 3-dimensional segmental strains by magnetic resonance imaging is complex and not widely available. Therefore, the echocardiographic community has worked hard to develop predictive methods that are simple, robust, and efficient. Three major questions have emerged from nearly a decade of research: Should one measure dispersion in timings, or in the amplitude, of segmental signals? Should one use velocity- or strain-based measures? Should one measure timing of the onset of contraction or its peak?
The first methods to gain wide acceptance were velocity-based measures of dispersion in timing derived from tissue Doppler imaging. Several single-center studies have shown them to be accurate in predicting the outcome of CRT and to be superior to time-domain strain-based measures of dyssynchrony. Two recent studies that used time-based velocity dyssynchrony measures were not very encouraging, however. The multicenter Cardiac Resynchronization Therapy in Patients with Heart Failure and Narrow QRS (RethinQ) trial did not show that CRT was beneficial to patients with significant dyssynchrony but narrow QRS complexes,11 whereas the large Predictors of Response to CRT (PROSPECT) trial showed that similar velocity-based temporal measures have little prognostic value,12 challenging their widely believed applicability.
Hence the study of Miyazaki et al13 and the search for something better. The investigators studied 45 patients before and after biventricular pacing, examining several proposed indices of dyssynchrony. They demonstrated that many of the most popular indices (using time to peak tissue velocity in a variety of segments) did not predict response to resynchronization, whereas time to peak strain showed much better correlation. This was somewhat surprising because several larger previous trials that compared strain and velocity dyssynchrony showed the opposite result.14,15 The reasons for this are unclear, though perhaps improvements in both instrumentation and technique (such as narrowing the acquisition sector width) may have allowed strain to overcome its prior problems of excessively noisy signals. On the other hand, failure of velocity data should not be entirely unexpected. Segmental velocities are affected by a number of factors, such as local tethering and apico-basal position. For example, it is fairly common that patients with nonischemic dilated cardiomyopathy and prominent left-to-right rocking during systole (ie, with "longitudinal rotation"16) have depressed, double-peaked velocities of the basal lateral wall (Figure). This kind of velocity tracing is almost impossible to interpret by standard time-to-peak measures.
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An even greater issue to consider is the persistent focus of the echocardiography community on time-based measures of dyssynchrony. Indeed, we have shown in a small study that an amplitude-based measure of dyssynchrony carries some prognostic weight.20 One could also speculate that methods that incorporate both time and amplitude information would be even more predictive.19 What is desperately needed, however, are ways to perform and interpret these studies more simply, allowing them to move out of the expert hands of just a few laboratories. One helpful tool would be a dynamic, bulls-eye representation of the way strains change over time to provide an intuitive summary of the timing and magnitude of contraction. This type of display could help us define typical patterns of strain development during systole that underlie patient response to CRT. Ideally, in that situation, one could determine the necessity of CRT and the ideal location of the pacing electrode with the same certainty we have currently in determining the severity and pathoanatomic substrate of mitral regurgitation in patients with myxomatous mitral valve disease. Until that time, for clinical indications for CRT, we are left only with the crudest of tools: QRS complex duration and shape.
| Acknowledgments |
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Dr Thomas is supported in part by the National Space Biomedical Research Institute through NASA Grant NCC9–58 (Houston, Tex) and the Department of Defense (Fort Dietrich, Md, USAMRMC Grant No. 02360007).
Disclosures
None.
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