Light chain amyloidosis (AL) is a rare multiorgan disease with extracellular deposition of fibrillar amyloid proteins derived from immunoglobulin light chains 1, 2. Amyloid deposits in the heart, kidneys, liver and nervous system cause organ failure. There is poor prognosis with median survival of 4 months with heart failure 3, 4. It is associated with diastolic dysfunction but often preserved left ventricular (LV) ejection fraction, especially in the early stages 5-9. Left ventricular dyssynchrony is common in heart failure patients and may contribute to its pathophysiology10. Intraventricular dyssynchrony reduces ventricular efficiency and cardiac performance 11 while cardiac resynchronization therapy improves symptoms and prolongs life 12, 13. Amyloid deposition can potentially alter regional cardiac mechanics. In a recent paper, Bellavia, et al. reported that patients with less advanced AL cardiac amyloidosis had increased segmental dyssynchrony compared to controls, but more advanced amyloidosis was associated with hypersynchronization using Doppler tissue velocity imaging 14. Three dimensional (3D) assessment of regional dyssynchrony has potential advantage over 2-dimensional based tissue Doppler studies as the temporal relationships of all 16 segments can be related with ease. Recently, 3D echocardiography has been utilized to study the temporal pattern of the dispersion in segmental ventricular volumes during the cardiac cycle in the novel assessment of ventricular dyssynchrony 11, 15. The dispersion (expressed as standard deviation) of the duration/timing from beginning of systole to the minimal systolic volume in the 16 different regions of the left ventricle (16-SD%, normalized to cycle length) has been shown to be a marker of dyssynchrony that was associated with ventricular dysfunction 11, 15. We hypothesize that AL subjects have left ventricular dyssynchrony compared to healthy controls. The aim of the study was to compare 16-SD% in AL subjects versus healthy controls.
Ten consecutive biopsy-proven AL subjects undergoing workup at 1 institution and 10 healthy controls underwent 3D echocardiography (60├é┬▒3 versus 52├é┬▒1 years, p=NS; 5 females in each group). The diagnosis was initially confirmed by biopsy for light chain amyloid in kidneys (n=4), cardiac (n=3), bone marrow (n=2), gastrointestinal tract (1), fat pad, axillary mass (n=1 each). Among AL subjects, 7 had cardiac involvement as defined by cardiac biopsy or subendocardial late gadolinium enhancement on routine magnetic resonance imaging 16, 17. Three AL subjects without cardiac biopsy or late gadolinium enhancement on MRI had thickened anteroseptum or increased left ventricular mass index on echocardiography.
The study was approved by the local Institutional Review Boards (IRB) and is in compliance with the Helsinki Declaration. All healthy controls gave informed consent. 9 AL subjects signed informed consent as part of a prospective observational study of biopsy-proven AL subjects. 1 AL subject who had tissue biopsy confirmation of the disease at post-mortem did not provide informed consent and waiver of consent authorization was obtained from the IRB.
3D Echocardiography Imaging and Analysis
In all subjects, cardiac 3D full-volume datasets were acquired from the apical window using either an IE33 or Sonos 7500 echocardiograph and X3-1 and X4-2 full matrix-array transducer (Philips Medical Systems, Bothell WA). The full volume data sets consisted of 4 real-time subvolumes acquired during 4 cardiac cycles that are subsequently combined to create a full 3D pyramidal data set. The data sets all had evaluable endocardial borders.
The 3D volume dataset were analyzed by software (QLAB version 4.2, 3DQ Avanced, Philips Medical Systems, Bothell WA) similar to previously published procedure 11. In brief, 2-dimensional orthogonal planes representing the standard apical 4-chamber, apical 2-chamber and LV short axis were oriented to bisect the LV and incorporate the true LV apex. Five anatomic landmarks were set that included septal, lateral, anterior, inferior mitral annulus and the apical endocardium in both beginning and end of systole. The software then recreated a 3D model of the endocardial border at beginning and end of systole using automated border detection algorithm. Manual correction of endocardial border was done if necessary. The software then performed volumetric analysis creating a cast of the LV cavity throughout the cardiac cycle.
The LV was divided into 16 segments (excluding the apex) as per American Society of Echocardiography recommendations 18. The volume of each segment was plotted as a function of time throughout the cardiac cycle, with time normalized to the cycle length and expressed as % R-R interval to account for differences in heart rate. The time from end of diastole (beginning of systole) and minimal systolic volume was quantified for each segment and the standard deviation of these times for the 16 segments (16-SD%) was calculated. The 16-SD% has been previously shown to be a reliable measure of dyssynchrony 11, 15, 19.
Two investigators (RQM and LH) trained in 3D volume analyses independently measured the 3D dataset blinded to disease condition and measured the subjects in random order. The first investigator repeated the measurement greater than a week after the first measurement in random order and still blinded to subject condition . Left ventricular mass index (LVMI) was calculated by Devereux™s formula using the diastolic left ventricular internal diameter, anteroseptal thickness and inferolateral thickness 20. Left atrial volume index was calculated using area-length method as per American Society of Echocardiography standards 21. In AL subjects, the lateral mitral annular velocity (E™), mitral inflow velocity (E) and ratio (E/E™) were obtained using standard pulsed spectral Doppler echocardiography 22.
Data Analyses and Statistics
Data are expressed as mean ├é┬▒standard deviation. Continuous variables were compared by unpaired Student™s t- test for normally distributed data or Mann-Whitney rank-sum test for non-normally distributed data. Correlation analysis was performed using Pearson™s correlation. Intraobserver and interobserver agreement was assessed using intraclass correlation coefficient (ICC) analyses and method of differences by Bland-Altman. For the ICC, a two-way mixed model absolute agreement type was used 23. In this analysis, ICC values less than 0.4 indicate poor reproducibility, values between 0.4 to 0.75 indicate good reproducibility and greater than 0.75 shows excellent reproducibility 23, 24. Limits of agreement were assessed by plotting the differences in the measurement of 16-SD% against the average values of the measurement as described by Bland-Altman 25, 26. Analyses were performed using SPSS 16.0.1 (SPSS Inc. Chicago IL). A two-sided p-value less than 0.05 was used to denote statistical significance.
Eight AL patients had New York Heart Association functional classification I, with 1 each presenting in Class III and IV heart failure. Left ventricular ejection fraction was 62.4├é┬▒0.6% in control subjects and 58.6├é┬▒2.8% for AL (p=NS) (Table 1). AL subjects had thicker anteroseptum, increased left atrial volume index and tendency towards increased left ventricular mass index. The lateral mitral annular velocity (E™) was 15.4├é┬▒9.2 cm/s and ratio of mitral inflow velocity to E™ (E/E™) was 7.2├é┬▒3.3 in AL subjects. Although E and E/E™ data were not available in control subjects, the mean values of E™ and E/E™ in AL subjects in addition to increased left atrial volume index are consistent with diastolic dysfunction and increased left ventricular filling pressures based on prior validation studies 27-30. Based on conventional evaluation of degree of diastolic dysfunction using mitral inflow and mitral annular velocity 31, 1 AL patient had normal diastolic function, 3 had mild (impaired relaxation pattern), 4 had moderate (pseudonormalization) and 2 had severe (restrictive) diastolic dysfunction.
There was higher 16-SD% in AL subjects compared to controls (Table 1, Figures 1-2, see Additional files 1-2). There was shorter cycle length in AL subjects compared to controls. There was no correlation between cycle length and 16-SD% (R=-0.2, p=NS). 16-SD% was weakly correlated with left ventricular mass index (R=0.45, p=0.04). There was no correlation between 16-SD% and left ventricular ejection fraction (R=-0.3, p=0.14).
Intraclass correlation coefficient was 0.625 (p=0.001) for intraobserver and 0.606 (p=0.002) for interobserver differences in 16-SD%. The ICC together with the Bland-Altman analysis (Figure 3) show good reproducibility of 16-SD% measurements. The Bland-Altman plot further shows better agreement in the measurement at lower 16-SD% values.
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