Background
Although 3D echocardiography (3DE) allows accurate and reproducible quantification of cardiac chambers, it has not been integrated into clinical practice because it relies on manual input, which interferes with workflow. A recently developed automated adaptive analytics algorithm for simultaneous quantification of left ventricular and atrial (LV, LA) volumes was found to be accurate and reproducible in patients with good images. We sought to prospectively test its feasibility and accuracy in consecutive patients in relationship with image quality and reader experience.
Methods
Three hundred consecutive patients underwent 3DE. Image quality was graded as poor, adequate, or good. Images were analyzed by an expert echocardiographer to obtain LV volumes and ejection fraction (EF) and LA volume using the automated analysis (HeartModel, Philips, Andover, MA) with and without editing the endocardial boundaries and using conventional manual tracing (QLAB, Philips, Andover, MA) blinded to the automated measurements as a reference. In a subgroup of 100 patients, automated analysis was repeated by two readers without 3DE experience.
Results
Automated analysis failed in 31/300 patients (10%). Patients with poor image quality ( n = 72, 24%) showed suboptimal agreement with the reference technique, especially for LVEF. Importantly, patients with adequate ( n = 89, 30%) and good ( n = 108, 36%) images showed small biases and excellent correlations without border corrections, which were further improved with editing. In contrast, border corrections by inexperienced readers did not improve the agreement with reference values.
Conclusions
Automated 3DE analysis allows accurate quantification of left-heart size and function in 66% of consecutive patients, while in the remaining patients, its performance is limited/unreliable due to image quality. Border corrections require 3DE experience to improve the accuracy of the automated measurements. In patients with sufficient image quality, this automated approach has the potential to overcome the workflow limitations of the 3D analysis in clinical practice.
Highlights
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We tested the feasibility and accuracy of the automated adaptive analytics algorithm for simultaneous quantification of left ventricular and atrial volumes in consecutive patients in relation to image quality and reader’s experience.
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Automated 3DE analysis allows accurate quantification of left-heart size and function in 66% of consecutive patients.
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In the remaining patients, its performance is limited/unreliable due to image quality.
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Border corrections require 3DE experience to improve the accuracy of the automated measurements.
Three-dimensional (3D) echocardiography (3DE) has been shown to have advantages over two-dimensional (2D) imaging in multiple areas and thus has been gradually incorporated into clinical routine in many echocardiography laboratories throughout the world. Improved accuracy and reproducibility of the quantification of cardiac chamber size and function is one of the major advantages of 3DE over 2D echocardiography (2DE). This is because the volumetric 3DE approach, which directly counts pixels inside the endocardial surface, does not rely on geometrical assumptions and thus avoids the risk of underestimating chamber volumes due to the use of foreshortened views, which are common with 2DE. The equipment and analysis software of 3DE is now widely available, and the rising numbers of publications have placed this technology as an evolving new standard for chamber quantification. The higher accuracy and reproducibility translate into improved clinical prognostic significance, which is the reason why 3DE is the recommended technique by the recently published guidelines for quantification of left-heart chambers. Nevertheless, currently available analysis techniques rely on extensive user input, which requires expertise and adversely affects the workflow and thus impedes the implementation in busy clinical laboratories. As a result, most clinical laboratories still use traditional, frequently qualitative, 2DE assessment of cardiac function.
To overcome these limitations, we recently tested a new automated approach for left-heart chamber quantification based on an adaptive analytics algorithm. In a single-center study, we reported good accuracy and reproducibility, and improved speed of analysis, compared with the conventional 3DE methodology and cardiac magnetic resonance. In a more recent multicenter study, we showed that it is an accurate and robust alternative to conventional manual methodology, which yields almost the same values across laboratories and is more reproducible. However, these studies included only patients with good-quality images.
Furthermore, current 3DE acquisition is based on combining multiple beats (usually 4 to 6) to generate a single full-volume data set, which is needed to obtain a high enough frame rate for accurate analysis of cardiac function. This multibeat acquisition is associated with “stich artifacts,” which are particularly common in patients with arrhythmias and those who cannot hold their breath, precluding accurate analysis. To circumvent this limitation, the new automated analysis utilizes a different, high frame rate, single-beat 3D acquisition mode. However, the impact of this new acquisition mode on the accuracy of chamber size and function measurements is unknown.
Accordingly, the main goal of this study was to assess the feasibility of this automated technique in consecutive nonselected patients and evaluate the effects of image quality on its accuracy. The additional goals were to evaluate the effects of reader experience with 3DE and the high frame rate, single-beat acquisition mode on the accuracy of the automated analysis.
Methods
Population and Study Design
We prospectively studied 300 consecutive nonselected patients (age, 63 ± 17; female, 54%; body surface area, 1.9 ± 0.2 m 2 ) referred for clinically indicated transthoracic echocardiograms for a wide range of suspected cardiovascular conditions ( Table 1 ) who underwent in addition 3DE imaging. Noncooperative patients or those who refused to participate were excluded; no other exclusion criteria were applied. The protocol was approved by the Institutional Review Board, and informed consent was obtained from each patient.
| Hypertension (0 = no, 1 = yes) | Coronary artery disease (0 = no, 1 = yes) | Cardiomyopathy (0 = no, 1 = ischemic, 2 = idiopathic) | Valvular heart disease (0 = no, 1 = yes) | Congenital heart disease (0 = no, 1 = yes) | Arrhythmia (0 = no, 1 = yes) | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| No. | % | No. | % | No. | % | No. | % | No. | % | No. | % | |
| 0 | 93 | 31 | 215 | 72 | 179 | 60 | 261 | 87 | 297 | 99 | 237 | 79 |
| 1 | 207 | 69 | 85 | 28 | 52 | 17 | 39 | 13 | 3 | 1 | 63 | 21 |
| 2 | 69 | 23 | ||||||||||
Images were analyzed by an experienced echocardiographer, who used the automated 3DE software to measure left heart chamber size and function indices, with and without endocardial boundary corrections. To generate a reference standard, the same reader used the conventional approach based on 3D-guided biplane measurements, while blinded to the results of the automated analysis. These comparisons were used to determine the accuracy of the automated analysis when images were classified by quality. In addition, to evaluate the effects of reader experience on the ability to effectively edit endocardial borders and thus potentially improve the accuracy of the automated analysis, measurements were repeated in a subset of randomly selected 100 patients by two readers without 3DE experience (third-year general cardiology fellows) and compared against the same reference standard.
To assess the effects of the high frame rate, single-beat acquisition on the accuracy of the 3DE measurements, 30 patients with good-quality images were imaged in addition using the conventional 4-beat full-volume mode. These 4-beat data sets were analyzed using conventional semiautomated volumetric analysis and used as the reference for comparisons.
Echocardiographic Imaging
Imaging was performed using the EPIQ system (version 7C, Philips Medical Systems, Andover, MA) and an X5-1 phased-array transducer with the patient in the left lateral decubitus position. Before each acquisition, images were optimized for endocardial visualization by modifying the gain, compress, and time-gain compensation controls. Image acquisition included wide-angled, single-beat, high frame rate 3DE data sets (HM ACQ key on the EPIQ system) from the apical position during a single breath hold. Care was taken to include the entire left ventricular (LV) and left atrial (LA) cavity within the 3DE images. Imaging depth and sector width were optimized to obtain the highest possible frame rate. In addition, in a subset of 30 patients, a conventional 4-beat full-volume acquisition was performed in the same setting using the same equipment.
Three-Dimensional Echocardiography Image Analysis
Images were reviewed and analyzed by an expert echocardiographer with extensive training in 3DE. First, the image quality of the 3DE images was graded by reviewing two-, three-, and four-chamber views extracted from the 3D data set as poor (more than two of six contiguous segments not visualized in any view or two of six contiguous segments in at least two different views), adequate (not more than two of six not well visualized contiguous segments in one view and one or fewer in the other views), and good (better than adequate).
Then the automated analysis was performed (HeartModel [HM], Philips) to obtain LV end-diastolic (ED) and end-systolic (ES) volumes (EDV, ESV) and LA volume (LAV) measurements, and LV ejection fraction (EF) was calculated. Analysis methodology was described in detail in our recent publications. Briefly, the software simultaneously detects LV and LA endocardial surfaces using an adaptive analytics algorithm, which uses knowledge-based identification to orient and locate cardiac chambers and patient-specific adaptation of endocardial borders. The algorithm automatically identifies the ED and ES phases of the cardiac cycle, and creates ED and ES 3D casts of the LV cavity and an ES cast of the LA cavity, from which LV and LA volumes are derived directly without geometrical assumptions. Manual corrections of the LV and LA endocardial surfaces are possible, when the operator judges the automatically detected surface as suboptimal. This is achieved by displaying the LA and LV contours on four-, three-, and two-chamber cut planes extracted from the 3DE data sets and allowing the user to edit the contours to optimize the match between the detected and the perceived endocardial boundaries ( Figure 1 ).
These measurements were compared to LV EDV, ESV, EF, and LAV values obtained with conventional 3DE software using the 3D-guided biplane approach (3DQ, QLAB, Philips) based on manual initialization of the endocardial boundaries in nonforeshortened views extracted from the 3DE data sets. These anatomically correct LV- and LA-focused apical two- and four-chamber views were identified as those in which the long-axis dimension of the relevant chamber was maximized. The ED and ES frames used for analysis were the same ones chosen by the automated technique. After mitral annular points were marked in each view, and an additional point was placed to mark either the LV apex for LV analysis, or the most distal point on the LA roof for the LA analysis, the endocardial border was automatically identified. After manually editing the borders as deemed necessary, LV EDV, ESV, and LAV were obtained and LVEF was calculated. The reader was blinded to the results of the automated measurements during this conventional analysis.
In addition, in a subset of randomly selected 100 patients, the automated analysis was repeated by two readers without 3DE experience who received minimal training with the HM software and were instructed to edit the automatically detected endocardial boundaries when deemed necessary to optimize border position. Their measurements were compared with the same reference values generated by the expert reader using the above 3D-guided biplane methodology, in order to assess the effects of 3DE experience.
Finally, in the subset of 30 patients with both single-beat and 4-beat images, the latter data sets were analyzed by the expert reader using the volumetric approach, which does not rely on geometrical assumptions (4D LV Analysis software, a module of Research Arena 2.0, TomTec Imaging Systems, Unterschleissheim, Germany). This methodology has been extensively used previously, including publications from our laboratory. Briefly, after the long axis of the relevant chamber is identified, the software creates a 3D cast, which is automatically tracked throughout the cardiac cycle using speckle-tracking. Fine-tuning of the endocardial surface was performed interactively to optimize boundary position as necessary. Finally, the actual chamber volume inside each cast was calculated throughout the cardiac cycle and used to determine EDV, ESV, EF, and LAV.
Statistics
For each parameter, the comparisons included linear regression with Pearson correlation coefficients and Bland-Altman analyses to assess the bias and limits of agreement (defined as 2 SD around the mean). Values of P < .05 by t tests were considered statistically significant.
Results
The average frame rate for the single-beat data sets was 19 ± 3 Hz. Semiautomated 3DE-derived maximal LV EDV ranged between 62 and 555 mL (median, 153 mL), ESV between 22 and 468 mL (median, 80 mL), EF between 5% and 79% (median, 47%), and LAV between 15 and 242 mL (median, 72 mL).
The automated software failed in 31 (10%) out of the 300 consecutive nonselected patients because of substandard image quality or complex congenital heart disease. Figure 2 shows an example of a failed analysis, both for the LV and LA (top and bottom panels, respectively). These 31 patients were not included in the evaluation of the accuracy of the automated analysis. The comparisons in the remaining 269 patients showed overall excellent agreement between the automated 3DE and 3D-guided biplane volume measurements, with minimal biases and correlation coefficients above 0.90 for volumes, but a lower value of 0.79 for LVEF ( Figure 3 ). However, there was a considerable number of patients in whom the agreement between the two techniques was suboptimal, as evidenced by the outlying data points ( Figure 3 , top) especially obvious for LVEF, and relatively wide limits of agreement ( Figure 3 , bottom). Figure 4 shows the same data without the 72 patients with poor-quality images (total of 197 patients) and depicts a considerably tighter distribution of data points, resulting in even better correlations across all measured parameters, including LVEF with r = 0.94 and narrower limits of agreement. Interestingly, the levels of intertechnique agreement were similar between patients with good and adequate images ( Table 2 ), indicating that the automated measurements were accurate in 197/300 (66%) of consecutive patients. On the other hand, as expected, the intertechnique agreement was worse in patients with poor image quality, with wide limits of agreement for all parameters and a correlation of only 0.49 for LVEF, despite higher correlations for volumes.
