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Evaluation of left ventricular mechanical dyssynchrony as determined by phase analysis of ECG-gated SPECT myocardial perfusion imaging in patients with left ventricular dysfunction and conduction disturbances
ORIGINAL ARTICLES Evaluation of left ventricular mechanical dyssynchrony as determined by phase analysis of ECG-gated SPECT myocardial perfusion imaging in patients with left ventricular dysfunction and conduction disturbances Mark A. Trimble, MD,a,c Salvador Borges-Neto, MD,a,b,c Stuart Smallheiser, MD,e Ji Chen, PhD,f Emily F. Honeycutt,c Linda K. Shaw,c Jaekyeong Heo, MD,d Robert A. Pagnanelli, CNMT, NCT,b E. Lindsey Tauxe, MEd,d Ernest V. Garcia, PhD,f Fabio Esteves, MD,f Frank Seghatol-Eslami, MD,d G. Neal Kay, MD,e and Ami E. Iskandrian, MDe Background. Cardiac resynchronization therapy (CRT) is approved for the treatment of patients with advanced systolic heart failure and evidence of dyssynchrony on electrocardiograms. However, a significant percentage of patients do not demonstrate improvement with CRT. Echocardiographic techniques have been used for more accurate determination of dyssynchrony. Single photon emission computed tomography (SPECT) myocardial perfusion imaging has not previously been used to evaluate cardiac dyssynchrony. The objective of this study is to evaluate mechanical dyssynchrony as described by phase analysis of gated SPECT images in patients with left ventricular dysfunction, conduction delays, and ventricular paced rhythms. Methods and Results. A novel count-based method is used to extract regional systolic wall thickening amplitude and phase from gated SPECT images. Five indices describing the phase dispersion of the onset of mechanical contraction are determined: peak phase, phase SD, bandwidth, skewness, and kurtosis. These indices were determined in consecutive patients with left ventricular dysfunction (n ⴝ 120), left bundle branch block (n ⴝ 33), right bundle branch block (n ⴝ 19), and ventricular paced rhythms (n ⴝ 23) and were compared with normal control subjects (n ⴝ 157). Phase SD, bandwidth, skewness, and kurtosis were significantly different between patients with left ventricular dysfunction, left bundle branch block, right bundle branch block, and ventricular paced rhythms and normal control subjects (all P < .001) Peak phase was significantly different between patients with right ventricular paced rhythms and normal control subjects (P ⴝ .001). Conclusions. A novel SPECT technique for describing left ventricular mechanical dyssynchrony has been developed and may prove useful in the evaluation of patients for CRT. (J Nucl Cardiol 2007;14:298-307.) Key Words: Myocardial perfusion imaging • heart failure • gated single photon emission computed tomography
From the Division of Cardiovascular Disease, Department of Medicine,a Department of Radiology,b and Duke Clinical Research Institute,c Duke University Medical Center, Durham, NC; Department of Radiology,d Division of Cardiology,e at University of Alabama at Birmingham, Birmingham, Ala; and Department of Radiology,f Emory University, Atlanta, Ga. This study was funded in part by a research grant from the Medtronic-Duke Strategic Alliance, of which Dr Borges-Neto is the primary investigator. 298
Received for publication Oct 31, 2006; final revision accepted Jan 24, 2007. Reprint requests: Salvador Borges-Neto, MD, DUMC, PO Box 3949, Durham, NC 27710; [email protected]. 1071-3581/$32.00 Copyright © 2007 by the American Society of Nuclear Cardiology. doi:10.1016/j.nuclcard.2007.01.041
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Congestive heart failure affects more than 5 million persons in the United States. Approximately 550,000 new cases are diagnosed annually and acute decompensated heart failure accounts for over 1 million hospital admissions per year.1-3 Cardiac resynchronization therapy (CRT) is approved for the treatment of patients with advanced heart failure symptoms, ejection fraction of 35% or less, and prolonged QRS duration. Several studies have shown improvements in quality of life, functional class, exercise capacity, and ejection fraction for patients who received CRT in addition to optimal medical therapy.4-7 Two recent studies have gone beyond showing symptomatic benefit to show a mortality benefit for patients undergoing CRT.8,9 In previous trials a significant percentage of patients (20%-30%) who met the entry criteria did not benefit from CRT. It has been suggested that electrical dyssynchrony as determined by QRS duration may not represent mechanical dyssynchrony, and it might not represent the best predictor of response to CRT.10-12 Therefore efforts have been made to more precisely define cardiac mechanical dyssynchrony in the hopes of selecting patients who would more consistently benefit from CRT. These efforts have focused on the use of advanced echocardiographic techniques to determine the degree of mechanical dyssynchrony.13 Nuclear cardiology imaging methods have also been evaluated for the diagnosis of mechanical dyssynchrony. Gated cardiac images provide count variations over time for each pixel or voxel. First-harmonic Fourier phase analysis calculates the phases of these count variations and has been used for gated cardiac imaging since its proposal in 1979.14 In gated blood pool ventriculography, phase analysis has been used to assess conduction abnormalities as well as ventricular dyssynchrony.15-18 To overcome the inherent limitations of planar imaging including the overlap of adjacent cardiac structures and the inaccurate localization of left ventricular and right ventricular abnormalities, phase analysis has been adapted to gated blood pool single photon emission computed tomography (SPECT).19-23 Recently, phase analysis has been applied to electrocardiography (ECG)– gated SPECT myocardial perfusion imaging to describe the timing of the regional left ventricular onset of mechanical contraction (OMC). This technique is fully automated and processes data obtained during routine gated SPECT imaging. This method has been used to create normal databases of 5 quantitative indices used to describe the left ventricular OMC.24 Our study evaluates these 5 indices in subjects with left ventricular dysfunction, baseline conduction delays, or right ventricular paced rhythms.
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METHODS OMC Determination and Phase Analysis Each subject enrolled in this study underwent a standard ECG-gated SPECT myocardial perfusion scan for clinical indications at 1 of 3 participating medical centers. Data were acquired at 8 frames per cardiac cycle. The R-R window used for gating was averaged from the prescan electrocardiogram. The short-axis data sets were generated by Butterworth filtering, followed by filtered backprojection reconstruction and oblique reorientation. Three-dimensional count distributions were then extracted from each of the 8 left ventricular shortaxis data sets and submitted to Fourier phase analysis. The analysis applied 1-dimensional fast Fourier transform to the count variation over time of each voxel to calculate the phase of the first Fourier harmonics. Then, the analysis generated a 3-dimensional phase distribution that described the timing of the left ventricular regional OMC as a function of degrees, with the 360° range representing the entire length of the R-R interval. Once the phase distribution was generated, it was displayed on the polar map as well as in histogram format. An example of the phase histogram is shown in Figure 1. The x-axis represents the timing of 1 cardiac cycle (R-R interval) in degrees. The y-axis represents the percent of myocardium that demonstrated the OMC during any particular time of the cardiac cycle. Five quantitative indices were calculated from the phase distribution to describe the phase dispersion of the left ventricular regional OMC. Peak phase is the most frequent phase and represents the time in the cardiac cycle during which the largest extent of myocardium is initiating contraction. Phase SD is the SD of the phase distribution. Phase histogram bandwidth represents the range of degrees of the cardiac cycle during which 95% of the myocardium is initiating contraction. Phase histogram skewness describes the symmetry of the histogram. A positive skewness indicates that the phase histogram is skewed to the right with a longer tail to the right of the peak phase. Phase histogram kurtosis describes the degree to which the histogram is peaked. A histogram with a higher peak and a narrower band has higher kurtosis.25 A comprehensive description of the method has recently been published.24 The software has been implemented in the Emory Cardiac Toolbox (Emory University/Syntermed, Inc, Atlanta, GA) for analysis of gated SPECT myocardial perfusion studies.
Subject Selection Our study retrospectively examined cohorts of consecutive subjects for phase analysis using the novel SPECT technique. All gated SPECT myocardial perfusion images were previously obtained for clinical indications via standard protocols. The cohorts included subjects with left ventricular dysfunction (n ⫽ 120), left bundle branch block (LBBB) (n ⫽ 33), right bundle branch block (RBBB) (n ⫽ 19), or right ventricular paced rhythms (n ⫽ 23). Subjects with left ventricular dysfunction were defined as those with ejection fractions of less than 40% on stress gated myocardial perfusion imaging.
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Figure 1. Representative phase histogram. The x-axis represents the timing of 1 cardiac cycle (R-R interval) in degrees. The y-axis represents the percent of myocardium demonstrating the OMC during any particular phase of the cardiac cycle. The color maps have 256 levels, with the minimum level corresponding to black and the maximum level corresponding to white. The raw phase polar map and histogram are displayed with 0° as black (minimum level) and 360° as white (maximum level). The normalized phase polar map and histogram are displayed with 0° as black and the maximum phase as white.
RESULTS
Table 1. Baseline characteristics
RV LV paced dysfunction LBBB RBBB rhythm No. Mean age (y) Male (%) Mean ejection fraction (%)
120 60 73 31
33 64 39 61
19 68 47 64
23 68 57 57
RV, Right ventricular.
Subjects with LBBB and RBBB had QRS durations of greater than 120 milliseconds. Baseline characteristics of these cohorts are shown in Table 1. The normal control subjects (n ⫽ 157) were defined as those who had no history of cardiac disease, ejection fractions of greater than 50%, and a less than 5% likelihood of coronary artery disease based on rest/stress myocardial perfusion imaging. They did not have evidence of LBBB or RBBB on surface electrocardiograms. The normal control subjects had a mean age of 55 years, and 52% were men.
Statistical Analysis Baseline characteristics and SPECT imaging phase indices were examined. The Wilcoxon rank sum test was used to determine if there was any difference in the distributions of the 5 quantitative indices describing the timing of the regional left ventricular OMC between the normal subjects and the distributions in each of the cohorts of subjects studied. Results presented include mean values ⫾ SD, median values, and 25th and 75th percentiles for each cohort of subjects studied.
Table 2 shows the 5 quantitative indices describing the left ventricular regional OMC in subjects with left ventricular dysfunction and normal control subjects. Peak phase did not differ significantly between subjects with left ventricular dysfunction and normal control subjects (130.8° ⫾ 28.3° vs 134.8° ⫾ 18.7°, P ⫽ .15). However, phase SD (47.8° ⫾ 19.4° vs 15.7° ⫾ 11.8°, P ⬍ .001), bandwidth (147.0° ⫾ 70.9° vs 42.0° ⫾ 28.4°, P ⬍ .001), skewness (2.7 ⫾ 0.8 vs 4.6 ⫾ 2.4, P ⬍ .001), and kurtosis (8.8 ⫾ 5.8 vs 22.4 ⫾ 11.7, P ⬍ .001) were all significantly different between subjects with left ventricular dysfunction and normal control subjects. Table 3 provides the 5 quantitative indices describing the left ventricular regional OMC in subjects with LBBB, RBBB, right ventricular paced rhythms, and normal control subjects. Peak phase was not significantly different between subjects with LBBB (138.6° ⫾ 21.5° vs 134.8° ⫾ 18.7°, P ⫽ .58) or RBBB (128.4° ⫾ 24.8° vs 134.8° ⫾ 18.7°, P ⫽ .18) and normal control subjects, but peak phase was significantly different between subjects with right ventricular paced rhythms and normal control subjects (118.6° ⫾ 33.9° vs 134.8° ⫾ 18.7°, P ⫽ .01). Phase SD was significantly different between subjects with LBBB (28.7° ⫾ 15.5° vs 15.7° ⫾ 11.8°, P ⬍ .001), RBBB (28.1° ⫾ 12.7° vs 15.7° ⫾ 11.8°, P ⬍ .001), and right ventricular paced rhythms (30.8° ⫾ 19.4° vs 15.7° ⫾ 11.8°, P ⬍ .001) and normal control subjects. Bandwidth was significantly different between subjects with LBBB (87.6° ⫾ 52.4° vs 42.0° ⫾ 28.4°, P ⬍ .001), RBBB (79.1° ⫾ 38.2° vs 42.0° ⫾ 28.4°, P ⬍ .001), and right ventricular paced rhythms (94.1° ⫾ 62.7° vs 42.0° ⫾ 28.4°, P ⬍ .001) and normal control
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Table 2. Phase analysis indices in normal subjects and patients with LV dysfunction
Peak phase (°) Mean ⫾ SD Median (Q1, Phase SD (°) Mean ⫾ SD Median (Q1, Bandwidth (°) Mean ⫾ SD Median (Q1, Skewness Mean ⫾ SD Median (Q1, Kurtosis Mean ⫾ SD Median (Q1,
Q3)
Normal (n ⴝ 157)
LV dysfunction (n ⴝ 120)
P value
134.8 ⫾ 18.7 136.0 (122.0, 147.0)
130.8 ⫾ 28.3 134.0 (116.0, 149.0)
.15
15.7 ⫾ 11.8 10.9 (8.1, 18.7)
47.8 ⫾ 19.4 47.2 (33.5, 59.7)
⬍.001(NP)
Q3)
42.0 ⫾ 28.4 33.0 (25.0, 48.0)
147.0 ⫾ 70.9 137.5 (87.5, 203.5)
⬍.001(NP)
Q3)
4.6 ⫾ 2.4 4.3 (2.8, 5.0)
2.7 ⫾ 0.8 2.6 (2.1, 3.2)
⬍.001(NP)
Q3)
22.4 ⫾ 11.7 20.1 (14.5, 28.3)
8.8 ⫾ 5.8 7.3 (4.9, 12.4)
⬍.001(NP)
Q3)
Q1, Twenty-fifth percentile; Q3, seventy-fifth percentile; NP, Nonparametric test.
subjects. Histogram skewness was significantly different between subjects with LBBB (2.9 ⫾ 0.9 vs 4.6 ⫾ 2.4, P ⬍ .001), RBBB (3.3 ⫾ 0.7 vs 4.6 ⫾ 2.4, P ⬍ .001), and right ventricular paced rhythms (2.9 ⫾ 1.0 vs 4.6 ⫾ 2.4, P ⬍ .001) and normal control subjects. Histogram kurtosis was significantly different between subjects with LBBB (9.9 ⫾ 5.8 vs 22.4 ⫾ 11.7, P ⬍ .001), RBBB (12.5 ⫾ 5.6 vs 22.4 ⫾ 11.7, P ⬍ .001), and right ventricular paced rhythms (10.2 ⫾ 8.7 vs 22.4 ⫾ 11.7, P ⬍ .001) and normal control subjects. Figure 2 shows a representative phase histogram calculated from a normal subject and one from a subject with left ventricular dysfunction demonstrating left ventricular mechanical dyssynchrony. The phase histogram of the normal subject demonstrates synchronous contraction over a relatively narrow phase range during the cardiac cycle. The phase histogram of the subject with left ventricular dysfunction demonstrates the OMC over a large phase range during the cardiac cycle. DISCUSSION CRT is approved for the treatment of patients with New York Heart Association class III/IV heart failure symptoms who have ejection fractions of 35% or less and a QRS duration of greater than 120 milliseconds on a surface electrocardiogram. Several studies have shown benefits with CRT when added to optimal medical therapy for groups of patients who meet these selection criteria. These benefits include improved functional status, exercise tolerance, quality of life, and left ventricular reverse remodeling.4-7 Two studies, the COMPANION
(Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure) trial and the CARE-HF (Cardiac Resynchronization–Heart Failure) trial, showed an additional mortality benefit from CRT of 24% and 33%, respectively, when added to optimal medical therapy.8,9 Difficulty occurs when attempting to select individual patients who would benefit from CRT. A significant percentage of patients (20%-30%) do not respond to CRT. Efforts have been made to more precisely define cardiac dyssynchrony in the hopes of more accurately identifying patients who would benefit from resynchronization. These efforts have primarily focused on the use of advanced echocardiographic techniques to determine left ventricular mechanical dyssynchrony. These include M-mode echocardiography,26-28 pulsed-wave tissue Doppler imaging,29-32 color-coded tissue Doppler imaging,33-40 strain and strain rate imaging,41-44 tissue synchronization imaging,45,46 and real-time 3-dimensional echocardiography.47 Although some techniques have been shown to predict clinical, hemodynamic, or echocardiographic response to CRT in small series of patients, none has been fully validated in large prospective trials. Furthermore, the techniques used are generally not automated, are time-intensive, and have varying degrees of reproducibility.13 Our study evaluated a recently developed tool, phase analysis of ECG-gated SPECT myocardial perfusion imaging, for the evaluation of left ventricular mechanical dyssynchrony. This tool uses the gated short-axis images to calculate the phase of the regional count changes (wall thickening) during the cardiac cycle. The phase information describes the time interval when the regions in the
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3-dimensional left ventricular wall start to contract, and it provides information as to how uniform the distribution of these time intervals is for the entire left ventricle. Our study first compared the 5 quantitative phase analysis indices in subjects with left ventricular dysfunction with normal control subjects. These results demonstrate that phase SD, bandwidth, skewness, and kurtosis were all significantly different between these cohorts of subjects. These results were expected. We compared phase analyses in 2 groups of subjects expected to have, on average, different degrees of mechanical dyssynchrony. If, on the other hand, our study demonstrated that the phase analyses did not differ significantly between subjects with left ventricular dysfunction and normal control subjects, then our hypothesis that phase analysis of ECG-gated SPECT myocardial perfusion imaging can determine mechanical dyssynchrony would have been rejected. In our study peak phase does not adequately discriminate subjects with left ventricular dysfunction from normal control subjects. Two potential explanations exist for this observation. It could relate to the fact that the phase histogram algorithm normalizes the location of the peak phase to a region of the histogram and thus the peak phase does not differ significantly between groups of subjects. Alternatively, this could indicate that ventricular dyssynchrony is a regional phenomenon, and even in subjects with mechanical dyssynchrony, significant portions of the left ventricular myocardium are behaving in a synchronous fashion. This would produce little change in the peak phase demonstrated on the phase histogram. Our study next compared indices describing mechanical dyssynchrony as determined by the novel SPECT technique in subjects with LBBB, RBBB, and right ventricular paced rhythms with indices in normal control subjects. These results show that phase SD, bandwidth, skewness, and kurtosis were all significantly different between these cohorts of subjects as well. All of these subjects have evidence of electrical dyssynchrony on their surface electrocardiograms and are expected, on average, to have more dyssynchronous contraction than normal subjects. Therefore these results further support our primary hypothesis that phase analysis of ECG-gated SPECT myocardial perfusion images can describe mechanical dyssynchrony. Although our study evaluates a novel tool to evaluate left ventricular mechanical dyssynchrony by use of gated SPECT imaging, gated blood pool imaging has also been used to evaluate ventricular dyssynchrony. Blood pool imaging has the potential advantage of improved temporal resolution, the ability to quantitate interventricular dyssynchrony, and the ability to quantitate intraventricular dyssynchrony of both the left and right ventricles. Fauchier et al48 reported that intraventricular dyssynchrony as determined by phase analysis of equilibrium radionuclide angioscintigraphy was an inde-
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pendent predictor of cardiac events in subjects with dilated cardiomyopathy. In addition, they found that intraventricular dyssynchrony demonstrated a stronger correlation with hemodynamic and functional parameters than did interventricular dyssynchrony. Several smaller series have studied the use of equilibrium radionuclide angioscintigraphy to evaluate dyssynchrony. These have found that the degree of interventricular dyssynchrony at baseline correlated with the degree of improvement after CRT, that improvements in synchrony correlated with improvements in left ventricular function, and that intraventricular dyssynchrony as measured by a left ventricular phase SD of greater than 50°, which improved with pacing, correlated with clinical improvement with CRT.49-51 The currently available outcome data are limited for equilibrium radionuclide angioscintigraphy, and outcome data predicting response to CRT are not available for use of phase analysis of gated SPECT imaging presented in this article. After further validation of both techniques, a comparative study to define the merits and potential advantages of each technique would prove beneficial. Our study represents the first step in the validation process of a novel technique for the evaluation of left ventricular mechanical dyssynchrony by demonstrating that the phase analysis of gated SPECT perfusion imaging appropriately discriminates between groups of patients who are expected, on average, to have different degrees of mechanical dyssynchrony. Future steps in the validation process will need to include a comparison to currently accepted imaging methods for the evaluation of dyssynchrony, the determination of the response of the phase analysis variables to CRT, the comparison of the performance characteristics of the phase analysis in well-defined cohorts of patients with nonischemic and ischemic cardiomyopathy, and the evaluation of phase analysis variables with respect to the prediction of clinical response to CRT. These studies would need to be completed before the use of phase analysis of gated SPECT perfusion imaging could be recommended for clinical application. There are several potential advantages to using SPECT myocardial perfusion imaging in the evaluation of dyssynchrony. First, the method is entirely automated and takes less than 1 minute to perform. Second, data are acquired from the entire left ventricle. Current echocardiographic techniques analyze data obtained from relatively small regions of interest in the base and mid portions of the 6 standard left ventricular walls. This allows for the SPECT method to potentially determine dyssynchronous contraction in regions not evaluated by echocardiography. Third, perfusion data may increase the ability of the SPECT method to predict response to
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Table 3. Phase analysis indices in normal subjects and patients with conduction abnormalities
Peak phase (°) Mean ⫾ SD Median (Q1, Phase SD (°) Mean ⫾ SD Median (Q1, Bandwidth (°) Mean ⫾ SD Median (Q1, Skewness Mean ⫾ SD Median (Q1, Kurtosis Mean ⫾ SD Median (Q1,
Normal (n ⴝ 157)
LBBB (n ⴝ 33)
RBBB (n ⴝ 19)
Q3)
134.8 ⫾ 18.7 136 (122.0, 147.0)
138.6 ⫾ 21.5 137.0 (126.0, 157.0)
128.4 ⫾ 24.8 126 (114.0, 145.0)
Q3)
15.7 ⫾ 11.8 10.9 (8.1, 18.7)
28.7 ⫾ 15.5 24.1 (15.2, 38.3)
28.1 ⫾ 12.7 28.1 (15.4, 37.8)
Q3)
42.0 ⫾ 28.4 33.0 (25.0, 48.0)
87.6 ⫾ 52.4 74.0 (49.0, 118.0)
79.1 ⫾ 38.2 67.0 (48.0, 119.0)
Q3)
4.6 ⫾ 2.4 4.3 (3.8, 5.0)
2.9 ⫾ 0.9 2.8 (2.4, 3.6)
3.3 ⫾ 0.7 3.2 (2.9, 3.7)
Q3)
22.4 ⫾ 11.7 20.1 (14.5, 28.3)
9.9 ⫾ 5.8 8.2 (5.3, 14.1)
12.5 ⫾ 5.6 10.6 (9.0, 17.3)
RV, Right ventricular; Q1, twenty-fifth percentile; Q3, seventy-fifth percentile; NP, nonparametric test.
CRT. It has recently been shown that patients with posterior-lateral scar on cardiac magnetic resonance imaging do not respond to CRT.52 Lastly, the addition of dyssynchrony determination to data obtained during routine SPECT imaging presents a cost-effective way to determine dyssynchrony and may obviate the need for additional diagnostic testing. The use of gated SPECT myocardial perfusion imaging for the determination of dyssynchrony does have potential limitations. These include the perceived low temporal resolution it provides. In our study all of the data were acquired at 8 frames per cardiac cycle. Higher temporal resolution may theoretically be obtained by use of data obtained at 16 frames per cardiac cycle. It must be noted that the first-harmonic Fourier transformation can enhance the phase analysis when applied to the data with lower temporal resolution. This transforms the 8 discreet data points into a continuous curve. Only the systolic portion of the data is used to determine the OMC. By having this curve fit closely with the systolic data points, the artifactual phase difference resulting from low temporal resolution is greatly reduced. Figure 3 shows the small difference of the phases obtained from a subject when data are acquired at 8 frames per cardiac cycle as compared with when data are acquired at 16 frames per cardiac cycle. This is consistent with previous work showing the value of Fourier temporal interpolation of data acquired at 8 frames per
cycle by improving image quality without detrimental effects on quantitative parameters such as ejection fraction and left ventricular volumes.53 A second potential limitation of our study is the fact that all of the gated SPECT myocardial perfusion data were processed via filtered backprojection reconstruction and Butterworth filtering. It must be noted that other processing methods such as iterative reconstruction, attenuation correction, scatter compensation, resolution recovery, and different filtering schemes can impact the counts of the gated SPECT myocardial perfusion images. The magnitude of impact these methods may have on the phase analysis results, as well as whether they would improve the processing techniques, remains to be investigated. A third potential limitation of our study is that criteria to define abnormality by use of the 5 quantitative indices have not been developed. Only mean values of normal patients have been determined for comparisons. We have chosen not to propose an arbitrary, nonvalidated definition of dyssynchrony by use of phase analysis of SPECT imaging at this time. Abnormal cardiac dyssynchrony should be defined in the context of how likely a patient with a known amount and location of dyssynchronous myocardium is to benefit from CRT. Defining the cutoff values for mechanical dyssynchrony should be done within the confines of a prospective clinical trial with important outcome data such as response to CRT, development of reverse left ventricular
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Table 3. Continued
P value RV paced rhythm (n ⴝ 19)
Normal vs RV paced rhythm
Normal vs LBBB
Normal vs LBBB
.31
.18
30.8 ⫾ 19.4 22.9 (16.1, 43.8)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
94.1 ⫾ 62.7 75.0 (46.0, 144.0)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
2.9 ⫾ 1.0 2.7 (2.0, 3.7)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
10.2 ⫾ 8.7 7.4 (4.0, 14.3)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
118.6 ⫾ 33.9 117 (82.0, 144.0)
Figure 2. Comparison of phase dispersion histogram in a patient demonstrating normal left ventricular synchrony (A) and one demonstrating left ventricular mechanical dyssynchrony (B). The normal histogram has a narrower and more peaked phase histogram, which is verified by the calculated quantitative indices of phase SD, bandwidth, skewness, and kurtosis.
.001
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Figure 3. Comparison of difference in phases obtained with data acquisition at 8 frames per cycle (left) or at 16 frames per cycle (right). The points in the right panel are the counts of a pixel arbitrarily chosen from the anterior region of the polar maps given by a set of gated (16 frames per cycle) short-axis images. The points in the left panel are down-sampled from the points in the right panel. The blue curve and red curve are the first harmonics that approximate the count changes during the cardiac cycle. With first-harmonic approximation, the phase difference between 8 frames per cycle and 16 frames per cycle is very small, at ⫺0.3°.
remodeling, improved functional status, and improved quality of life. As such, our study did not determine which patients would benefit from CRT. Rather, our study describes a novel technique to quantify dyssynchronous left ventricular contraction. Although additional validation studies need to be done before phase analysis of ECG-gated myocardial perfusion imaging is used in clinical practice, this study represents the first step in that process and is a proof-ofconcept study that will lay the foundations for future investigation. The goal of subsequent investigations is to develop a dyssynchrony score potentially using all or some of the 5 quantitative indices with various degrees of weighting in conjunction with myocardial perfusion data, which will more accurately predict patient response to CRT. Acknowledgment Dr. Garcia reports an ownership interest in and serves as a consultant/advisor board member to Syntermed Inc. Dr. Garcia also receives royalties from the sale of clinical software that was used as part of this research. Mr. Pagnanelli is a member of the speaker’s bureau for GE Healthcare.
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12. Brecker SJ, Xiao HB, Sparrow J, Gibson DG. Effects of dual chamber pacing with short atrioventricular delay in dilated cardiomyopathy. Lancet 1992;340:1308-12. 13. Bax JJ, Abraham T, Barold SS, Breithardt OA, Fung JW, Garrigue S, et al. Cardiac resynchronization therapy: part 1—issues before device implantation. J Am Coll Cardiol 2005;46:2153-67. 14. Adam WE, Tarkowska A, Bitter F, Stauch M, Geffers H. Equilibrium (gated) radionuclide ventriculography. Cardiovasc Radiol 1979;2:161-3. 15. Links JM, Douglass KH, Wagner HN Jr. Patterns of ventricular emptying by Fourier analysis of gated blood-pool studies. J Nucl Med 1980;21:978-82. 16. Botvinick EH, Frais MA, Shosa DW, O’Connell JW, PachecAlvarez JA, Scheinman M, et al. An accurate means of detecting and characterizing abnormal patterns of ventricular activation by phase image analysis. Am J Cardiol 1982;50:289-98. 17. Links JM, Raichlen JS, Wagner HN Jr, Reid PR. Assessment of the site of ventricular activation by Fourier analysis of gated bloodpool studies. J Nucl Med 1985;26:27-32. 18. Somsen GA, Verberne HJ, Burri H, Ratib O, Righetti A. Ventricular mechanical dyssynchrony and resynchronization therapy in heart failure: a new indication for Fourier analysis of gated blood-pool radionuclide ventriculography. Nucl Med Commun 2006;27:105-12. 19. Casset-Senon D, Philippe L, Babuty D, Eder V, Fauchier L, Fauchier JP, et al. Diagnosis of arrythmogenic right ventricular cardiomyopathy by Fourier analysis of gated blood pool singlephoton emission tomography. Am J Cardiol 1998;82:1399-404. 20. Neumann DR, Go RT, Myers BA, Macintyre WJ, Chen EQ, Cook SA. Parametric phase display for biventricular function from gated cardiac blood pool single-photon emission tomography. Eur J Nucl Med 1993;20:1108-11. 21. Graf G, Mester J, Clausen M, Henze E, Bitter F, Heidenreich P, et al. Reconstruction of Fourier coefficients: a fast method to get polar amplitude and phase images of gated SPECT. J Nucl Med 1990;31:1856-61. 22. Mate E, Mester J, Csermay L, Kuba A, Madani S, Makay A. Three-dimensional presentation of the Fourier amplitude and phase: a fast display method for gated cardiac blood-pool SPECT. J Nucl Med 1992;33:458-62. 23. Botvinick EH, O’Connell WO, Kadkade PP, Glickman SL, Dae MW, Cohen TJ, et al. Potential added value of three-dimensional reconstruction and display of single photon emission computed tomographic gated blood pool images. J Nucl Cardiol 1998;5: 245-55. 24. Chen J, Garcia EV, Folks RD, Cooke CD, Faber TL, Tauxe EL, et al. Onset of left ventricular contraction determined by phase analysis of ECG-gated myocardial perfusion SPECT imaging: development of a diagnostic tool for assessment of cardiac mechanical dyssynchrony. J Nucl Cardiol 2005;6:687-95. 25. Abramowitz M, Stegun IA, editors. Handbook of mathematical functions with formulas, graphs, and mathematical tables. 9th ed. New York: Dover; 1972. p. 928. 26. Pitzalis MV, Iacoviello M, Romito R, Massari F, Rizzon B, Luzzi G, et al. Cardiac resynchronization therapy tailored by echocardiographic evaluation of ventricular asynchrony. J Am Coll Cardiol 2002;40:1615-22. 27. Pitzalis MV, Iacoviello M, Romito R, Guida P, De Tommasi E, Luzzi G, et al. Ventricular asynchrony predicts a better outcome in patients with chronic heart failure receiving cardiac resynchronization therapy. J Am Coll Cardiol 2005;45:65-9. 28. Marcus GM, Rose E, Viloria EM, Shafer J, De Marco T, Saxon LA, et al; VENTAK CHF/CONTAK-CD Biventricular Pacing Study Investigators. Septal to posterior wall motion delay fails to
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predict reverse remodeling or clinical improvement in patients undergoing cardiac resynchronization therapy. J Am Coll Cardiol 2005;46:2208-14. Penicka M, Bartunek J, De Bruyne B, Vanderheyden M, Goethals M, De Zutter M, et al. Improvement of left ventricular function after cardiac resynchronization therapy is predicted by tissue Doppler imaging echocardiography. Circulation 2004;109:978-83. Ansalone G, Giannantoni P, Ricci R, Trambaiolo P, Laurenti A, Fedele F, et al. Doppler myocardial imaging in patients with heart failure receiving biventricular pacing treatment. Am Heart J 2001;142:881-96. Garrigue S, Reuter S, Labeque JN, Jais P, Hocini M, Shah DC, et al. Usefulness of biventricular pacing in patients with congestive heart failure and right bundle branch block. Am J Cardiol 2001; 88:1436-41. Bordachar P, Lafitte S, Reuter S, Sanders P, Jais P, Haissaguerre M, et al. Echocardiographic parameters of ventricular dyssynchrony validation in patients with heart failure using sequential biventricular pacing. J Am Coll Cardiol 2004;44:2157-65. Yu CM, Chau E, Sanderson JE, Fan K, Tang MO, Fung WH, et al. Tissue Doppler echocardiographic evidence of reverse remodeling and improved synchronicity by simultaneously delaying regional contraction after biventricular pacing therapy in heart failure. Circulation 2002;105:438-45. Bax JJ, Marwick TH, Molhoek SG, Bleeker GB, Van Erven L, Boersma E, et al. Left ventricular dyssynchrony predicts benefit of cardiac resynchronization therapy in patients with end-stage heart failure before pacemaker implantation. Am J Cardiol 2003; 92:1238-40. Yu CM, Fung WH, Lin H, Zhang Q, Sanderson JE, Lau CP. Predictors of left ventricular reverse remodeling after cardiac resynchronization therapy for heart failure secondary to idiopathic dilated or ischemic cardiomyopathy. Am J Cardiol 2003;91:684-8. Bax JJ, Bleeker GB, Marwick TH, Molhoek SG, Boersma E, Steendijk P, et al. Left ventricular dyssynchrony predicts response and prognosis after cardiac resynchronization therapy. J Am Coll Cardiol 2004;44:1834-40. Notabartolo D, Merlino JD, Smith AL, De Lurgio DB, Vera FV, Easley KA, et al. Usefulness of the peak velocity difference by tissue Doppler imaging technique as an effective predictor of response to cardiac resynchronization therapy. Am J Cardiol 2004;94:817-20. Yu CM, Fung JW, Zhang Q, Chan CK, Chan YS, Lin H, et al. Tissue Doppler imaging is superior to strain rate imaging and post systolic shortening on the prediction of reverse remodeling in both ischemic and nonischemic heart failure after cardiac resynchronization therapy. Circulation 2004;110:66-73. Sogaard P, Egeblad H, Kim WY, Jensen HK, Pedersen AK, Kristensen BO, et al. Tissue Doppler imaging predicts improved systolic performance and reversed left ventricular remodeling during long-term cardiac resynchronization therapy. J Am Coll Cardiol 2002;40:723-30. Sogaard P, Egeblad H, Pedersen AK, Kim WY, Kristensen BO, Hansen PS, et al. Sequential versus simultaneous biventricular resynchronization for severe heart failure: evaluation by tissue Doppler imaging. Circulation 2002;106:2078-84. Breithardt OA, Stellbrink C, Herbots L, Claus P, Sinha AM, Bijnens B, et al. Cardiac resynchronization therapy can reverse abnormal myocardial strain distribution in patients with heart failure and left bundle branch block. J Am Coll Cardiol 2003;42:486-94. Sun JP, Chinchoy E, Donal E, Popovic ZB, Perlic G, Asher CR, et al. Evaluation of ventricular synchrony using novel Doppler echocardiographic indices in patients with heart failure receiving
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43.
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cardiac resynchronization therapy. J Am Soc Echocardiogr 2004;17:845-50. Popovic ZB, Grimm RA, Perlic G, Chinchoy E, Geraci M, Sun JP, et al. Noninvasive assessment of cardiac resynchronization therapy for congestive heart failure using myocardial strain and left ventricular peak power as parameters of myocardial synchrony and function. J Cardiovasc Electrophysiol 2002;13:1203-8. Dohi K, Suffoletto MS, Schwartzman D, Ganz L, Pinsky MR, Gorcsan J III. Utility of echocardiographic radial strain imaging to quantify left ventricular dyssynchrony and predict acute response to cardiac resynchronization therapy. Am J Cardiol 2005;96:112-6. Gorcsan J III, Kanzaki H, Bazaz R, Dohi K, Schwartzman D. Usefulness of echocardiographic tissue synchronization imaging to predict acute response to cardiac resynchronization therapy. Am J Cardiol 2004;93:1178-81. Yu CM, Zhang Q, Fung JW, Chan HC, Chan YS, Yip GW, et al. A novel tool to assess systolic asynchrony and identify responders of cardiac resynchronization therapy by tissue synchronization imaging. J Am Coll Cardiol 2005;45:677-84. Kapetanakis S, Kearney MT, Siva A, Gall N, Cooklin M, Monaghan MJ. Real-time three-dimensional echocardiography: a novel technique to quantify global left ventricular mechanical dyssynchrony. Circulation 2005;112:992-1000.
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48. Fauchier L, Marie O, Casset-Senon D, Babuty D, Cosnay P, Fauchier JP. Interventricular and intraventricular dyssynchrony in idiopathic dilated cardiomyopathy: a prognostic study with Fourier phase analysis of radionuclide angioscintigraphy. J Am Coll Cardiol 2002;40:2022-30. 49. Toussaint JF, Lavergne T, Ollitraut J, Hignette C, Darondel JM, De Dieuleveult B, et al. Biventricular pacing in severe heart failure patients reverses electromechanical dyssynchronization from apex to base. Pacing Clin Electrophysiol 2000;23:1731-4. 50. Kerwin WF, Botvinick EH, O’Connell JW, Merrick SH, DeMarco T, Chatterjee K, et al. Ventricular contraction abnormalities in dilated cardiomyopathy: effect of biventricular pacing to correct interventricular dyssynchrony. J Am Coll Cardiol 2000;35:1221-7. 51. Le Rest C, Couturier O, Turzo A, Guillo P, Bizais Y, Etienne Y, et al. Use of left ventricular pacing in heart failure: evaluation by gated blood pool imaging. J Nucl Cardiol 1999;6:651-6. 52. Bleeker GB, Kaandorp TA, Lamb HJ, Boersma E, Steendijk P, De Roos A, et al. Effect of posterolateral scar tissue on clinical and echocardiographic improvement after cardiac resynchronization therapy. Circulation 2006;113:969-76. 53. Gremillet E, Champailler A, Soler C. Fourier temporal interpolation improves electrocardiograph-gated myocardial perfusion SPECT. J Nucl Med 2005;46:1769-74.
From the Division of Cardiovascular Disease, Department of Medicine,a Department of Radiology,b and Duke Clinical Research Institute,c Duke University Medical Center, Durham, NC; Department of Radiology,d Division of Cardiology,e at University of Alabama at Birmingham, Birmingham, Ala; and Department of Radiology,f Emory University, Atlanta, Ga. This study was funded in part by a research grant from the Medtronic-Duke Strategic Alliance, of which Dr Borges-Neto is the primary investigator. 298
Received for publication Oct 31, 2006; final revision accepted Jan 24, 2007. Reprint requests: Salvador Borges-Neto, MD, DUMC, PO Box 3949, Durham, NC 27710; [email protected]. 1071-3581/$32.00 Copyright © 2007 by the American Society of Nuclear Cardiology. doi:10.1016/j.nuclcard.2007.01.041
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Congestive heart failure affects more than 5 million persons in the United States. Approximately 550,000 new cases are diagnosed annually and acute decompensated heart failure accounts for over 1 million hospital admissions per year.1-3 Cardiac resynchronization therapy (CRT) is approved for the treatment of patients with advanced heart failure symptoms, ejection fraction of 35% or less, and prolonged QRS duration. Several studies have shown improvements in quality of life, functional class, exercise capacity, and ejection fraction for patients who received CRT in addition to optimal medical therapy.4-7 Two recent studies have gone beyond showing symptomatic benefit to show a mortality benefit for patients undergoing CRT.8,9 In previous trials a significant percentage of patients (20%-30%) who met the entry criteria did not benefit from CRT. It has been suggested that electrical dyssynchrony as determined by QRS duration may not represent mechanical dyssynchrony, and it might not represent the best predictor of response to CRT.10-12 Therefore efforts have been made to more precisely define cardiac mechanical dyssynchrony in the hopes of selecting patients who would more consistently benefit from CRT. These efforts have focused on the use of advanced echocardiographic techniques to determine the degree of mechanical dyssynchrony.13 Nuclear cardiology imaging methods have also been evaluated for the diagnosis of mechanical dyssynchrony. Gated cardiac images provide count variations over time for each pixel or voxel. First-harmonic Fourier phase analysis calculates the phases of these count variations and has been used for gated cardiac imaging since its proposal in 1979.14 In gated blood pool ventriculography, phase analysis has been used to assess conduction abnormalities as well as ventricular dyssynchrony.15-18 To overcome the inherent limitations of planar imaging including the overlap of adjacent cardiac structures and the inaccurate localization of left ventricular and right ventricular abnormalities, phase analysis has been adapted to gated blood pool single photon emission computed tomography (SPECT).19-23 Recently, phase analysis has been applied to electrocardiography (ECG)– gated SPECT myocardial perfusion imaging to describe the timing of the regional left ventricular onset of mechanical contraction (OMC). This technique is fully automated and processes data obtained during routine gated SPECT imaging. This method has been used to create normal databases of 5 quantitative indices used to describe the left ventricular OMC.24 Our study evaluates these 5 indices in subjects with left ventricular dysfunction, baseline conduction delays, or right ventricular paced rhythms.
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METHODS OMC Determination and Phase Analysis Each subject enrolled in this study underwent a standard ECG-gated SPECT myocardial perfusion scan for clinical indications at 1 of 3 participating medical centers. Data were acquired at 8 frames per cardiac cycle. The R-R window used for gating was averaged from the prescan electrocardiogram. The short-axis data sets were generated by Butterworth filtering, followed by filtered backprojection reconstruction and oblique reorientation. Three-dimensional count distributions were then extracted from each of the 8 left ventricular shortaxis data sets and submitted to Fourier phase analysis. The analysis applied 1-dimensional fast Fourier transform to the count variation over time of each voxel to calculate the phase of the first Fourier harmonics. Then, the analysis generated a 3-dimensional phase distribution that described the timing of the left ventricular regional OMC as a function of degrees, with the 360° range representing the entire length of the R-R interval. Once the phase distribution was generated, it was displayed on the polar map as well as in histogram format. An example of the phase histogram is shown in Figure 1. The x-axis represents the timing of 1 cardiac cycle (R-R interval) in degrees. The y-axis represents the percent of myocardium that demonstrated the OMC during any particular time of the cardiac cycle. Five quantitative indices were calculated from the phase distribution to describe the phase dispersion of the left ventricular regional OMC. Peak phase is the most frequent phase and represents the time in the cardiac cycle during which the largest extent of myocardium is initiating contraction. Phase SD is the SD of the phase distribution. Phase histogram bandwidth represents the range of degrees of the cardiac cycle during which 95% of the myocardium is initiating contraction. Phase histogram skewness describes the symmetry of the histogram. A positive skewness indicates that the phase histogram is skewed to the right with a longer tail to the right of the peak phase. Phase histogram kurtosis describes the degree to which the histogram is peaked. A histogram with a higher peak and a narrower band has higher kurtosis.25 A comprehensive description of the method has recently been published.24 The software has been implemented in the Emory Cardiac Toolbox (Emory University/Syntermed, Inc, Atlanta, GA) for analysis of gated SPECT myocardial perfusion studies.
Subject Selection Our study retrospectively examined cohorts of consecutive subjects for phase analysis using the novel SPECT technique. All gated SPECT myocardial perfusion images were previously obtained for clinical indications via standard protocols. The cohorts included subjects with left ventricular dysfunction (n ⫽ 120), left bundle branch block (LBBB) (n ⫽ 33), right bundle branch block (RBBB) (n ⫽ 19), or right ventricular paced rhythms (n ⫽ 23). Subjects with left ventricular dysfunction were defined as those with ejection fractions of less than 40% on stress gated myocardial perfusion imaging.
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Figure 1. Representative phase histogram. The x-axis represents the timing of 1 cardiac cycle (R-R interval) in degrees. The y-axis represents the percent of myocardium demonstrating the OMC during any particular phase of the cardiac cycle. The color maps have 256 levels, with the minimum level corresponding to black and the maximum level corresponding to white. The raw phase polar map and histogram are displayed with 0° as black (minimum level) and 360° as white (maximum level). The normalized phase polar map and histogram are displayed with 0° as black and the maximum phase as white.
RESULTS
Table 1. Baseline characteristics
RV LV paced dysfunction LBBB RBBB rhythm No. Mean age (y) Male (%) Mean ejection fraction (%)
120 60 73 31
33 64 39 61
19 68 47 64
23 68 57 57
RV, Right ventricular.
Subjects with LBBB and RBBB had QRS durations of greater than 120 milliseconds. Baseline characteristics of these cohorts are shown in Table 1. The normal control subjects (n ⫽ 157) were defined as those who had no history of cardiac disease, ejection fractions of greater than 50%, and a less than 5% likelihood of coronary artery disease based on rest/stress myocardial perfusion imaging. They did not have evidence of LBBB or RBBB on surface electrocardiograms. The normal control subjects had a mean age of 55 years, and 52% were men.
Statistical Analysis Baseline characteristics and SPECT imaging phase indices were examined. The Wilcoxon rank sum test was used to determine if there was any difference in the distributions of the 5 quantitative indices describing the timing of the regional left ventricular OMC between the normal subjects and the distributions in each of the cohorts of subjects studied. Results presented include mean values ⫾ SD, median values, and 25th and 75th percentiles for each cohort of subjects studied.
Table 2 shows the 5 quantitative indices describing the left ventricular regional OMC in subjects with left ventricular dysfunction and normal control subjects. Peak phase did not differ significantly between subjects with left ventricular dysfunction and normal control subjects (130.8° ⫾ 28.3° vs 134.8° ⫾ 18.7°, P ⫽ .15). However, phase SD (47.8° ⫾ 19.4° vs 15.7° ⫾ 11.8°, P ⬍ .001), bandwidth (147.0° ⫾ 70.9° vs 42.0° ⫾ 28.4°, P ⬍ .001), skewness (2.7 ⫾ 0.8 vs 4.6 ⫾ 2.4, P ⬍ .001), and kurtosis (8.8 ⫾ 5.8 vs 22.4 ⫾ 11.7, P ⬍ .001) were all significantly different between subjects with left ventricular dysfunction and normal control subjects. Table 3 provides the 5 quantitative indices describing the left ventricular regional OMC in subjects with LBBB, RBBB, right ventricular paced rhythms, and normal control subjects. Peak phase was not significantly different between subjects with LBBB (138.6° ⫾ 21.5° vs 134.8° ⫾ 18.7°, P ⫽ .58) or RBBB (128.4° ⫾ 24.8° vs 134.8° ⫾ 18.7°, P ⫽ .18) and normal control subjects, but peak phase was significantly different between subjects with right ventricular paced rhythms and normal control subjects (118.6° ⫾ 33.9° vs 134.8° ⫾ 18.7°, P ⫽ .01). Phase SD was significantly different between subjects with LBBB (28.7° ⫾ 15.5° vs 15.7° ⫾ 11.8°, P ⬍ .001), RBBB (28.1° ⫾ 12.7° vs 15.7° ⫾ 11.8°, P ⬍ .001), and right ventricular paced rhythms (30.8° ⫾ 19.4° vs 15.7° ⫾ 11.8°, P ⬍ .001) and normal control subjects. Bandwidth was significantly different between subjects with LBBB (87.6° ⫾ 52.4° vs 42.0° ⫾ 28.4°, P ⬍ .001), RBBB (79.1° ⫾ 38.2° vs 42.0° ⫾ 28.4°, P ⬍ .001), and right ventricular paced rhythms (94.1° ⫾ 62.7° vs 42.0° ⫾ 28.4°, P ⬍ .001) and normal control
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Table 2. Phase analysis indices in normal subjects and patients with LV dysfunction
Peak phase (°) Mean ⫾ SD Median (Q1, Phase SD (°) Mean ⫾ SD Median (Q1, Bandwidth (°) Mean ⫾ SD Median (Q1, Skewness Mean ⫾ SD Median (Q1, Kurtosis Mean ⫾ SD Median (Q1,
Q3)
Normal (n ⴝ 157)
LV dysfunction (n ⴝ 120)
P value
134.8 ⫾ 18.7 136.0 (122.0, 147.0)
130.8 ⫾ 28.3 134.0 (116.0, 149.0)
.15
15.7 ⫾ 11.8 10.9 (8.1, 18.7)
47.8 ⫾ 19.4 47.2 (33.5, 59.7)
⬍.001(NP)
Q3)
42.0 ⫾ 28.4 33.0 (25.0, 48.0)
147.0 ⫾ 70.9 137.5 (87.5, 203.5)
⬍.001(NP)
Q3)
4.6 ⫾ 2.4 4.3 (2.8, 5.0)
2.7 ⫾ 0.8 2.6 (2.1, 3.2)
⬍.001(NP)
Q3)
22.4 ⫾ 11.7 20.1 (14.5, 28.3)
8.8 ⫾ 5.8 7.3 (4.9, 12.4)
⬍.001(NP)
Q3)
Q1, Twenty-fifth percentile; Q3, seventy-fifth percentile; NP, Nonparametric test.
subjects. Histogram skewness was significantly different between subjects with LBBB (2.9 ⫾ 0.9 vs 4.6 ⫾ 2.4, P ⬍ .001), RBBB (3.3 ⫾ 0.7 vs 4.6 ⫾ 2.4, P ⬍ .001), and right ventricular paced rhythms (2.9 ⫾ 1.0 vs 4.6 ⫾ 2.4, P ⬍ .001) and normal control subjects. Histogram kurtosis was significantly different between subjects with LBBB (9.9 ⫾ 5.8 vs 22.4 ⫾ 11.7, P ⬍ .001), RBBB (12.5 ⫾ 5.6 vs 22.4 ⫾ 11.7, P ⬍ .001), and right ventricular paced rhythms (10.2 ⫾ 8.7 vs 22.4 ⫾ 11.7, P ⬍ .001) and normal control subjects. Figure 2 shows a representative phase histogram calculated from a normal subject and one from a subject with left ventricular dysfunction demonstrating left ventricular mechanical dyssynchrony. The phase histogram of the normal subject demonstrates synchronous contraction over a relatively narrow phase range during the cardiac cycle. The phase histogram of the subject with left ventricular dysfunction demonstrates the OMC over a large phase range during the cardiac cycle. DISCUSSION CRT is approved for the treatment of patients with New York Heart Association class III/IV heart failure symptoms who have ejection fractions of 35% or less and a QRS duration of greater than 120 milliseconds on a surface electrocardiogram. Several studies have shown benefits with CRT when added to optimal medical therapy for groups of patients who meet these selection criteria. These benefits include improved functional status, exercise tolerance, quality of life, and left ventricular reverse remodeling.4-7 Two studies, the COMPANION
(Comparison of Medical Therapy, Pacing, and Defibrillation in Heart Failure) trial and the CARE-HF (Cardiac Resynchronization–Heart Failure) trial, showed an additional mortality benefit from CRT of 24% and 33%, respectively, when added to optimal medical therapy.8,9 Difficulty occurs when attempting to select individual patients who would benefit from CRT. A significant percentage of patients (20%-30%) do not respond to CRT. Efforts have been made to more precisely define cardiac dyssynchrony in the hopes of more accurately identifying patients who would benefit from resynchronization. These efforts have primarily focused on the use of advanced echocardiographic techniques to determine left ventricular mechanical dyssynchrony. These include M-mode echocardiography,26-28 pulsed-wave tissue Doppler imaging,29-32 color-coded tissue Doppler imaging,33-40 strain and strain rate imaging,41-44 tissue synchronization imaging,45,46 and real-time 3-dimensional echocardiography.47 Although some techniques have been shown to predict clinical, hemodynamic, or echocardiographic response to CRT in small series of patients, none has been fully validated in large prospective trials. Furthermore, the techniques used are generally not automated, are time-intensive, and have varying degrees of reproducibility.13 Our study evaluated a recently developed tool, phase analysis of ECG-gated SPECT myocardial perfusion imaging, for the evaluation of left ventricular mechanical dyssynchrony. This tool uses the gated short-axis images to calculate the phase of the regional count changes (wall thickening) during the cardiac cycle. The phase information describes the time interval when the regions in the
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3-dimensional left ventricular wall start to contract, and it provides information as to how uniform the distribution of these time intervals is for the entire left ventricle. Our study first compared the 5 quantitative phase analysis indices in subjects with left ventricular dysfunction with normal control subjects. These results demonstrate that phase SD, bandwidth, skewness, and kurtosis were all significantly different between these cohorts of subjects. These results were expected. We compared phase analyses in 2 groups of subjects expected to have, on average, different degrees of mechanical dyssynchrony. If, on the other hand, our study demonstrated that the phase analyses did not differ significantly between subjects with left ventricular dysfunction and normal control subjects, then our hypothesis that phase analysis of ECG-gated SPECT myocardial perfusion imaging can determine mechanical dyssynchrony would have been rejected. In our study peak phase does not adequately discriminate subjects with left ventricular dysfunction from normal control subjects. Two potential explanations exist for this observation. It could relate to the fact that the phase histogram algorithm normalizes the location of the peak phase to a region of the histogram and thus the peak phase does not differ significantly between groups of subjects. Alternatively, this could indicate that ventricular dyssynchrony is a regional phenomenon, and even in subjects with mechanical dyssynchrony, significant portions of the left ventricular myocardium are behaving in a synchronous fashion. This would produce little change in the peak phase demonstrated on the phase histogram. Our study next compared indices describing mechanical dyssynchrony as determined by the novel SPECT technique in subjects with LBBB, RBBB, and right ventricular paced rhythms with indices in normal control subjects. These results show that phase SD, bandwidth, skewness, and kurtosis were all significantly different between these cohorts of subjects as well. All of these subjects have evidence of electrical dyssynchrony on their surface electrocardiograms and are expected, on average, to have more dyssynchronous contraction than normal subjects. Therefore these results further support our primary hypothesis that phase analysis of ECG-gated SPECT myocardial perfusion images can describe mechanical dyssynchrony. Although our study evaluates a novel tool to evaluate left ventricular mechanical dyssynchrony by use of gated SPECT imaging, gated blood pool imaging has also been used to evaluate ventricular dyssynchrony. Blood pool imaging has the potential advantage of improved temporal resolution, the ability to quantitate interventricular dyssynchrony, and the ability to quantitate intraventricular dyssynchrony of both the left and right ventricles. Fauchier et al48 reported that intraventricular dyssynchrony as determined by phase analysis of equilibrium radionuclide angioscintigraphy was an inde-
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pendent predictor of cardiac events in subjects with dilated cardiomyopathy. In addition, they found that intraventricular dyssynchrony demonstrated a stronger correlation with hemodynamic and functional parameters than did interventricular dyssynchrony. Several smaller series have studied the use of equilibrium radionuclide angioscintigraphy to evaluate dyssynchrony. These have found that the degree of interventricular dyssynchrony at baseline correlated with the degree of improvement after CRT, that improvements in synchrony correlated with improvements in left ventricular function, and that intraventricular dyssynchrony as measured by a left ventricular phase SD of greater than 50°, which improved with pacing, correlated with clinical improvement with CRT.49-51 The currently available outcome data are limited for equilibrium radionuclide angioscintigraphy, and outcome data predicting response to CRT are not available for use of phase analysis of gated SPECT imaging presented in this article. After further validation of both techniques, a comparative study to define the merits and potential advantages of each technique would prove beneficial. Our study represents the first step in the validation process of a novel technique for the evaluation of left ventricular mechanical dyssynchrony by demonstrating that the phase analysis of gated SPECT perfusion imaging appropriately discriminates between groups of patients who are expected, on average, to have different degrees of mechanical dyssynchrony. Future steps in the validation process will need to include a comparison to currently accepted imaging methods for the evaluation of dyssynchrony, the determination of the response of the phase analysis variables to CRT, the comparison of the performance characteristics of the phase analysis in well-defined cohorts of patients with nonischemic and ischemic cardiomyopathy, and the evaluation of phase analysis variables with respect to the prediction of clinical response to CRT. These studies would need to be completed before the use of phase analysis of gated SPECT perfusion imaging could be recommended for clinical application. There are several potential advantages to using SPECT myocardial perfusion imaging in the evaluation of dyssynchrony. First, the method is entirely automated and takes less than 1 minute to perform. Second, data are acquired from the entire left ventricle. Current echocardiographic techniques analyze data obtained from relatively small regions of interest in the base and mid portions of the 6 standard left ventricular walls. This allows for the SPECT method to potentially determine dyssynchronous contraction in regions not evaluated by echocardiography. Third, perfusion data may increase the ability of the SPECT method to predict response to
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Table 3. Phase analysis indices in normal subjects and patients with conduction abnormalities
Peak phase (°) Mean ⫾ SD Median (Q1, Phase SD (°) Mean ⫾ SD Median (Q1, Bandwidth (°) Mean ⫾ SD Median (Q1, Skewness Mean ⫾ SD Median (Q1, Kurtosis Mean ⫾ SD Median (Q1,
Normal (n ⴝ 157)
LBBB (n ⴝ 33)
RBBB (n ⴝ 19)
Q3)
134.8 ⫾ 18.7 136 (122.0, 147.0)
138.6 ⫾ 21.5 137.0 (126.0, 157.0)
128.4 ⫾ 24.8 126 (114.0, 145.0)
Q3)
15.7 ⫾ 11.8 10.9 (8.1, 18.7)
28.7 ⫾ 15.5 24.1 (15.2, 38.3)
28.1 ⫾ 12.7 28.1 (15.4, 37.8)
Q3)
42.0 ⫾ 28.4 33.0 (25.0, 48.0)
87.6 ⫾ 52.4 74.0 (49.0, 118.0)
79.1 ⫾ 38.2 67.0 (48.0, 119.0)
Q3)
4.6 ⫾ 2.4 4.3 (3.8, 5.0)
2.9 ⫾ 0.9 2.8 (2.4, 3.6)
3.3 ⫾ 0.7 3.2 (2.9, 3.7)
Q3)
22.4 ⫾ 11.7 20.1 (14.5, 28.3)
9.9 ⫾ 5.8 8.2 (5.3, 14.1)
12.5 ⫾ 5.6 10.6 (9.0, 17.3)
RV, Right ventricular; Q1, twenty-fifth percentile; Q3, seventy-fifth percentile; NP, nonparametric test.
CRT. It has recently been shown that patients with posterior-lateral scar on cardiac magnetic resonance imaging do not respond to CRT.52 Lastly, the addition of dyssynchrony determination to data obtained during routine SPECT imaging presents a cost-effective way to determine dyssynchrony and may obviate the need for additional diagnostic testing. The use of gated SPECT myocardial perfusion imaging for the determination of dyssynchrony does have potential limitations. These include the perceived low temporal resolution it provides. In our study all of the data were acquired at 8 frames per cardiac cycle. Higher temporal resolution may theoretically be obtained by use of data obtained at 16 frames per cardiac cycle. It must be noted that the first-harmonic Fourier transformation can enhance the phase analysis when applied to the data with lower temporal resolution. This transforms the 8 discreet data points into a continuous curve. Only the systolic portion of the data is used to determine the OMC. By having this curve fit closely with the systolic data points, the artifactual phase difference resulting from low temporal resolution is greatly reduced. Figure 3 shows the small difference of the phases obtained from a subject when data are acquired at 8 frames per cardiac cycle as compared with when data are acquired at 16 frames per cardiac cycle. This is consistent with previous work showing the value of Fourier temporal interpolation of data acquired at 8 frames per
cycle by improving image quality without detrimental effects on quantitative parameters such as ejection fraction and left ventricular volumes.53 A second potential limitation of our study is the fact that all of the gated SPECT myocardial perfusion data were processed via filtered backprojection reconstruction and Butterworth filtering. It must be noted that other processing methods such as iterative reconstruction, attenuation correction, scatter compensation, resolution recovery, and different filtering schemes can impact the counts of the gated SPECT myocardial perfusion images. The magnitude of impact these methods may have on the phase analysis results, as well as whether they would improve the processing techniques, remains to be investigated. A third potential limitation of our study is that criteria to define abnormality by use of the 5 quantitative indices have not been developed. Only mean values of normal patients have been determined for comparisons. We have chosen not to propose an arbitrary, nonvalidated definition of dyssynchrony by use of phase analysis of SPECT imaging at this time. Abnormal cardiac dyssynchrony should be defined in the context of how likely a patient with a known amount and location of dyssynchronous myocardium is to benefit from CRT. Defining the cutoff values for mechanical dyssynchrony should be done within the confines of a prospective clinical trial with important outcome data such as response to CRT, development of reverse left ventricular
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Table 3. Continued
P value RV paced rhythm (n ⴝ 19)
Normal vs RV paced rhythm
Normal vs LBBB
Normal vs LBBB
.31
.18
30.8 ⫾ 19.4 22.9 (16.1, 43.8)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
94.1 ⫾ 62.7 75.0 (46.0, 144.0)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
2.9 ⫾ 1.0 2.7 (2.0, 3.7)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
10.2 ⫾ 8.7 7.4 (4.0, 14.3)
⬍.001 (NP)
⬍.001 (NP)
⬍.001 (NP)
118.6 ⫾ 33.9 117 (82.0, 144.0)
Figure 2. Comparison of phase dispersion histogram in a patient demonstrating normal left ventricular synchrony (A) and one demonstrating left ventricular mechanical dyssynchrony (B). The normal histogram has a narrower and more peaked phase histogram, which is verified by the calculated quantitative indices of phase SD, bandwidth, skewness, and kurtosis.
.001
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Figure 3. Comparison of difference in phases obtained with data acquisition at 8 frames per cycle (left) or at 16 frames per cycle (right). The points in the right panel are the counts of a pixel arbitrarily chosen from the anterior region of the polar maps given by a set of gated (16 frames per cycle) short-axis images. The points in the left panel are down-sampled from the points in the right panel. The blue curve and red curve are the first harmonics that approximate the count changes during the cardiac cycle. With first-harmonic approximation, the phase difference between 8 frames per cycle and 16 frames per cycle is very small, at ⫺0.3°.
remodeling, improved functional status, and improved quality of life. As such, our study did not determine which patients would benefit from CRT. Rather, our study describes a novel technique to quantify dyssynchronous left ventricular contraction. Although additional validation studies need to be done before phase analysis of ECG-gated myocardial perfusion imaging is used in clinical practice, this study represents the first step in that process and is a proof-ofconcept study that will lay the foundations for future investigation. The goal of subsequent investigations is to develop a dyssynchrony score potentially using all or some of the 5 quantitative indices with various degrees of weighting in conjunction with myocardial perfusion data, which will more accurately predict patient response to CRT. Acknowledgment Dr. Garcia reports an ownership interest in and serves as a consultant/advisor board member to Syntermed Inc. Dr. Garcia also receives royalties from the sale of clinical software that was used as part of this research. Mr. Pagnanelli is a member of the speaker’s bureau for GE Healthcare.
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