Population Characteristics

We retrospectively included 150 patients with severe AS who underwent TAVR, applying the following exclusion criteria: (1) lack of or inadequate preprocedural MDCT ( n = 23), (2) lack of intraprocedural 3D TEE or imaging performed using an ultrasound system from another vendor ( n = 134), and (3) valve-in-valve procedures ( n = 18). Selection criteria for TAVR were the presence of severe AS, defined by mean aortic valve gradient ≥ 40 mm Hg or aortic valve area ≤ 1 cm ² . Eligibility for TAVR was decided in a heart team discussion and mainly for those patients deemed too high risk or having contraindications for cardiac surgery. The need for patient written informed consent was waived by the institutional review board of the Leiden University Medical Center after approval of this retrospective analysis of clinically acquired data.

Transthoracic Echocardiography

Comprehensive two-dimensional transthoracic echocardiography was performed before TAVR using a commercially available ultrasound system (Vivid; GE Vingmed Ultrasound, Horten, Norway). Valve morphology, AS severity, stroke volume, and left ventricular (LV) function were measured according to the European Association of Cardiovascular Imaging and American Society of Echocardiography standards. Specifically, LV end-diastolic and end-systolic volumes and LV ejection fraction were calculated using the Simpson biplane method. Stroke volume was indexed to body surface area.

Three-Dimensional Transesophageal Echocardiography

Acquisition of 3D transesophageal echocardiographic images was performed intraprocedurally using a commercially available ultrasound system (iE33 and EPIQ7; Philips Medical Systems) and transesophageal probe (X7-2t). Using 3D zoom mode with adjustment of lateral and elevation width, 3D images of the whole aortic valve apparatus were obtained, including the LV outflow tract (LVOT), the aortic root, and the ascending aorta. Image quality was recorded in all patients and graded as follows: 1 = poor, 2 = fair, 3 = good, 4 = very good, and 5 = excellent.

The 3D transesophageal echocardiographic images of the aortic annulus and root were subsequently analyzed using a prototype of dedicated software that allows automated modeling of the aortic annulus and aortic root in a multistep, predefined work flow. The software provides several measurements of the aortic root (LVOT, aortic annulus, sinus of Valsalva [SV], and sinotubular junction [STJ]), which can be preselected before the analysis. The following measurements were collected for the purpose of this study: aortic annular area, aortic annular maximum and minimum diameter, aortic annular perimeter, SV mean diameter, and STJ mean diameter. The mean aortic annulus diameter was calculated as the average of the maximum and minimum diameters. Figure 1 highlights the key steps of the software work flow.

Overview of work flow of the 3D transesophageal echocardiographic automated software. A graphical illustration (A) and an example of a case with 3D TEE (B) demonstrate the automated orientation of different MPR planes ( green frame , long-axis view; blue frame , coronal view; red frame , short-axis view), including markers for the ascending aorta (AA) and LVOT. Automated tracings of different anatomic locations are shown in (C) (aortic annulus), (D) (SV), and (E) (STJ). (F) Obtained 3D model of the three different planes ( red , aortic annulus; yellow , SV; blue , STJ) with the possibility of overlaying a 3D model of various prostheses ( pink mesh ).

After selection of the 3D transesophageal echocardiographic Digital Imaging and Communications in Medicine file, an automated algorithm orients the multiplanar reconstruction (MPR) images as requested ( Figures 1 A and 1B). After manual frame selection (in an early systolic phase), the user can place two reference markers (“AA: Ascending Aorta” or “LVOT”) to facilitate interpretation of the images and eventually further adjust the MPRs. The software uses built-in algorithms to automatically define three virtual aortic valve annular points in each MPR, which can be confirmed by the user ( Figures 1 C–1E). The MPR in the transverse view automatically adjusts to the plane containing the three points, followed by an automated generation of the annulus contour. After approval of the annular contour, the software automatically initiates the LVOT contour at a plane parallel to the aortic annular plane and offset 5 mm into the left ventricle. The same steps are then followed to generate the SV and STJ contours in their respective planes.

If deemed necessary by the user, the software allows adjustment of the obtained contours using two different approaches ( Figure 2 ). The first approach comprises manual regional adjustment of the contour by altering the position of the automated points. The second approach comprises global contour scaling (“slider”) with a user-predetermined amount (or “offset”). Users can define this specific offset by determining the difference in measurements (or “bias”) between 3D echocardiography and MDCT in a group of their own patients. Both approaches can also be combined to further improve contour tracing. Finally, after generating an aortic root model with the four different contours (aortic annulus, LVOT, SV, and STJ), the software allows the user to select from a variety of TAVR devices, allowing a 3D overlay of the device superimposed on the generated aortic root model ( Figure 1 F). An instantaneously generated and detailed list of the performed measurements is provided by the software, which can be exported to an Excel file (Microsoft, Redmond, WA) at any moment of the analysis. Duration of the analysis (in seconds) with the novel software was recorded in all patients.

Regional and global adjustment of the generated contour. An example of a stenotic aortic valve with calcification of the right coronary cusp is shown ( asterisk , A ). The annular contour was automatically generated excluding the calcification (B) . Regional adjustment was performed by altering the position of one of the automated points ( B , blue arrow ) more eccentrically (C) . Global adjustment can further be performed by offsetting the global contour ( C , blue arrows ), resulting in improved contour tracing (D) .

Multi–Detector Row Computed Tomography

Aortic valve data acquisition was performed using either a 64–detector row or 320–detector row computed tomographic scanner (Aquilion 64 or Aquilion ONE, respectively; Toshiba Medical Systems, Otawara, Japan). The data acquisition protocol for the Aquilion 64 and Aquilion ONE has been previously described. Scanning was performed during midinspiratory breath hold, and the arrival of contrast media was detected using a real-time tracking technique with a threshold of +180 Hounsfield units (HU). The electrocardiogram was simultaneously recorded during image acquisition for retrospective gating. After reconstruction of the data sets, offline postprocessing was performed (Vitrea FX 6.5; Vital Images, Minnetonka, MN). From the systolic images (30%–35% of the R-R interval) using MPR planes, aortic annular dimensions (maximum annular diameter, minimum annular diameter, aortic annular perimeter, and aortic valve area) and aortic root dimensions (SV and STJ) were measured according to the standard protocol. The mean annular diameter (in millimeters) was calculated as the average of the maximum and minimum diameters. From the non-contrast-enhanced images, the aortic valve calcification (AVC) score (or Agatston score of the aortic valve) was assessed.

Statistical Analysis

All normally distributed continuous data are presented as mean ± SD unless otherwise stated. All categorical variables are presented as frequencies and percentages and were compared using the χ ² test.

To study the factors that may influence the duration of the automated 3D transesophageal echocardiographic analysis, patients were divided according to the median value of image quality on 3D TEE or of AVC score, and the differences in duration of the automated 3D echocardiographic analysis were compared using an independent-samples t test. Comparison of measurements between MDCT and 3D TEE was performed using a paired two-sided Student’s t test. Concordance between the techniques was evaluated with plots using the Bland-Altman method. To assess the correlation between measurements from echocardiography and MDCT, Pearson correlation coefficients were calculated. The first 100 patients were used as a calibration group whereby we sought to identify the average measurement bias between 3D TEE and MDCT. The last 50 patients were used as a validation cohort whereby we sought to explore whether the use of the “slider” feature, preset with the bias obtained by the calibration group as an offset, would improve the concordance between the techniques compared with the calibration cohort. To assess the agreement between the different imaging modalities regarding the choice of prosthesis size, a contingency analysis was performed, and agreement was expressed using the κ value (good agreement, κ = 0.61–0.80; very good agreement, κ = 0.81–1.00), which was also compared between the calibration and the validation groups. A receiver operating characteristic curve for AVC score was generated using bias > 1% as a classification variable.

To test interobserver variability between both methods, 10 random studies were analyzed by two cardiologists (N.A.M and E.A.P.) who independently reviewed the 3D images and performed the automatic measurements. One observer (E.A.P.) repeated the measurements in 10 randomly selected cases at two different time points to assess intraobserver variability. Interobserver and intraobserver agreements were calculated using intraclass correlation coefficients (ICCs), with excellent agreement defined as ICC > 0.75 and strong agreement defined as ICC = 0.60 to 0.74. Readers of one modality were blinded to the results of the other modality. Statistical analyses were performed using SPSS version 22.0 (IBM, Armonk, NY), and differences were considered significant at P < .05.

Patient Population

Clinical, echocardiographic, and computed tomographic characteristics of the study population are summarized in Table 1 . The study population consisted of 76 women and 74 men with mean age of 80.7 ± 7.2 years. All patients had native severe AS (mean aortic valve area, 0.8 ± 0.3 cm ² ; mean gradient, 43.5 ± 19.5 mm Hg). The mean logistic European System for Cardiac Operative Risk Evaluation score was 18.7 ± 13.1, and the majority of procedures were performed via transfemoral access. Forty-five patients received 23-mm prostheses, 62 patients received 26-mm prostheses, 42 patients received 29-mm prostheses, and one patient received a 31-mm prosthesis.

Duration of Analysis with Automated 3D Transesophageal Echocardiographic Software

The mean duration of analysis of aortic annular and root dimensions using the novel software was 4.2 ± 1.0 min. This duration was affected by the AVC score (mean duration, 3.6 ± 1.0 min for AVC < 3,500 HU [the median value of the population] vs 6.5 ± 1.8 min for AVC ≥ 3,500 HU; P < .001) and by 3D echocardiographic image quality (3.7 ± 1.0 min for patients with image quality 4 or 5 vs 5.5 ± 1.9 min for those with image quality 1–3, P < .001).

Comparison of Computed Tomographic versus Automated 3D Echocardiographic Measurements

Computed tomographic and automated 3D transesophageal echocardiographic measurements of aortic annular area and aortic annular minimum and maximum diameters were performed in all 150 patients, while measurements of SV and STJ diameter were possible in 133 patients (89%; Table 2 ). Including the entire patient population, automated 3D echocardiographic measurements were significantly smaller than measurements by MDCT ( P < .001) in all anatomic locations, although the absolute differences were relatively small.

An excellent correlation between automated 3D TEE and MDCT was observed for aortic annular area measurements ( r = 0.91). The correlations for aortic annular perimeter, annular maximum, minimum, and mean diameters, and SV and STJ mean diameters were good ( r = 0.83, r = 0.75, r = 0.71, r = 0.75, r = 0.87, and r = 0.73, respectively). Figure 3 and Supplemental Figure 1 (available at www.onlinejase.com ) show Bland-Altman plots for agreement between both methods and scatterplots to demonstrate degree of correlation. A receiver operating characteristic curve was constructed to determine a cutoff for AVC using an absolute bias > 1% as a classification variable ( Supplemental Figure 2; available at www.onlinejase.com ). Good discriminatory ability was found for MDCT-derived AVC score (area under the curve = 0.669) and yielded an AVC value of 3,366 HU as a threshold (sensitivity, 66.3%; specificity, 63.2%) in our cohort.

Bland-Altman plots and scatterplots of 3D transesophageal echocardiographic automated analysis versus multi–detector row computed tomographic measurements for aortic annular area and mean annular diameter and perimeter in the overall patient population. Aortic annular mean diameter = (aortic annular maximum diameter + aortic annular minimum diameter)/2.

“Slider” Feature for Global Scaling: Calibration versus Validation Cohort

After analyzing the first 100 patients (calibration cohort), an interim comparison of measurements of automated 3D TEE and MDCT showed an average bias for aortic annular area of −17.8 mm ² (underestimation) with 95% limits of agreement of −86.1 to 50.4 mm ² ( Figure 4 A). In the following 50 patients (validation cohort), the “slider” feature was used for automated global scaling with this bias used as an offset. Application of the “slider” resulted in improved agreement between the measurements of both modalities, with a slight overestimation of the automated 3D echocardiographic analysis software of +5.4 mm ² and narrower 95% limits of agreement (−53.2 to 64.1 mm ² ; Figure 4 B). Comparison of the different characteristics of the calibration and validation cohort is shown in Supplemental Table 1 (available at www.onlinejase.com ).

Only gold members can continue reading. Log In or Register to continue

Share this:

• Click to share on Twitter (Opens in new window)
• Click to share on Facebook (Opens in new window)

Related

Related posts:

1. ACC/AATS/AHA/ASE/ASNC/HRS/SCAI/SCCT/SCMR/STS 2017 Appropriate Use Criteria for Multimodality Imaging in Valvular Heart Disease
2. Role of Echocardiography in Transcatheter Mitral Valve Replacement in Native Mitral Valves and Mitral Rings
3. Transcatheter Tricuspid Valve-in-Valve Intervention for Degenerative Bioprosthetic Tricuspid Valve Disease
4. Nashville, Here We Come!

Stay updated, free articles. Join our Telegram channel

Join