Automated Threshold-Based 3D Segmentation Versus Short-Axis Planimetry for Assessment of Global Left Ventricular Function with Dual-Source MDCT

Identification of rapid progression of right ventricular functional measures using three-dimensional cardiac computed tomography after total surgical correction of tetralogy of Fallot

OBJECTIVE

To identify subsets of patients with tetralogy of Fallot (TOF) after total surgical correction demonstrating the rapid progression of right ventricle (RV) functional measures using cardiac computed tomography (CT) ventricular volumetry.

METHODS

Rapid or slow progression of RV functional measures was determined in 109 patients with TOF who underwent cardiac CT ventricular volumetry more than twice after total surgical correction. Patient age, body surface area, postoperative days, the time interval between the first and last cardiac CT examinations, and CT-based functional measures were evaluated using binary logistic regression to determine the predictors of the rapid progression. Receiver operating characteristic curve analysis was performed to evaluate diagnostic performance of the potential predictors.

RESULTS

The rapid progression of indexed RV end-systolic volume (ESV) (≥2.7 mL/m²/year) and indexed RV end-diastolic volume (≥0.9 mL/m²/year) could be predicted by RV ejection fraction (EF) at the last cardiac CT with an odds ratio of 1.340 (95 % confidence interval [CI], 1.122-1.600; p = 0.001) and age at the last cardiac CT with an odds ratio of 8.255 (95 % CI, 1.531-44.513; p = 0.014), respectively. RV EF at the last cardiac CT showed the highest diagnostic performance (area under the curve = 0.799; p < 0.002) for the rapid progression of indexed RV ESV.

CONCLUSION

Cardiac CT ventricular volumetry can be used to identify patients demonstrating the rapid progression of RV functional measures after total surgical correction of TOF and follow-up imaging protocols can be individually optimized based on initial progression rate.

The auto segmentation for cardiac structures using a dual-input deep learning network based on vision saliency and transformer

Purpose

Accurate segmentation of cardiac structures on coronary CT angiography (CCTA) images is crucial for the morphological analysis, measurement, and functional evaluation. In this study, we achieve accurate automatic segmentation of cardiac structures on CCTA image by adopting an innovative deep learning method based on visual attention mechanism and transformer network, and its practical application value is discussed.

Methods

We developed a dual‐input deep learning network based on visual saliency and transformer (VST), which consists of self‐attention mechanism for cardiac structures segmentation. Sixty patients’ CCTA subjects were randomly selected as a development set, which were manual marked by an experienced technician. The proposed vision attention and transformer mode was trained on the patients CCTA images, with a manual contour‐derived binary mask used as the learning‐based target. We also used the deep supervision strategy by adding auxiliary losses. The loss function of our model was the sum of the Dice loss and cross‐entropy loss. To quantitatively evaluate the segmentation results, we calculated the Dice similarity coefficient (DSC) and Hausdorff distance (HD). Meanwhile, we compare the volume of automatic segmentation and manual segmentation to analyze whether there is statistical difference.

Results

Fivefold cross‐validation was used to benchmark the segmentation method. The results showed the left ventricular myocardium (LVM, DSC = 0.87), the left ventricular (LV, DSC = 0.94), the left atrial (LA, DSC = 0.90), the right ventricular (RV, DSC = 0.92), the right atrial (RA, DSC = 0.91), and the aortic (AO, DSC = 0.96). The average DSC was 0.92, and HD was 7.2 ± 2.1 mm. In volume comparison, except LVM and LA (p < 0.05), there was no significant statistical difference in other structures. Proposed method for structural segmentation fit well with the true profile of the cardiac substructure, and the model prediction results closed to the manual annotation.

Conclusions

The adoption of the dual‐input and transformer architecture based on visual saliency has high sensitivity and specificity to cardiac structures segmentation, which can obviously improve the accuracy of automatic substructure segmentation. This is of gr

Automated Segmentation of Left Ventricular Myocardium on Cardiac Computed Tomography Using Deep Learning

OBJECTIVE

To evaluate the accuracy of a deep learning-based automated segmentation of the left ventricle (LV) myocardium using cardiac CT.

MATERIALS AND METHODS

To develop a fully automated algorithm, 100 subjects with coronary artery disease were randomly selected as a development set (50 training / 20 validation / 30 internal test). An experienced cardiac radiologist generated the manual segmentation of the development set. The trained model was evaluated using 1000 validation set generated by an experienced technician. Visual assessment was performed to compare the manual and automatic segmentations. In a quantitative analysis, sensitivity and specificity were calculated according to the number of pixels where two three-dimensional masks of the manual and deep learning segmentations overlapped. Similarity indices, such as the Dice similarity coefficient (DSC), were used to evaluate the margin of each segmented masks.

RESULTS

The sensitivity and specificity of automated segmentation for each segment (1-16 segments) were high (85.5-100.0%). The DSC was 88.3 ± 6.2%. Among randomly selected 100 cases, all manual segmentation and deep learning masks for visual analysis were classified as very accurate to mostly accurate and there were no inaccurate cases (manual vs. deep learning: very accurate, 31 vs. 53; accurate, 64 vs. 39; mostly accurate, 15 vs. 8). The number of very accurate cases for deep learning masks was greater than that for manually segmented masks.

CONCLUSION

We present deep learning-based automatic segmentation of the LV myocardium and the results are comparable to manual segmentation data with high sensitivity, specificity, and high similarity scores.

Semiautomatic Three-Dimensional Threshold-Based Cardiac Computed Tomography Ventricular Volumetry in Repaired Tetralogy of Fallot: Comparison with Cardiac Magnetic Resonance Imaging

Objective

To assess the accuracy and potential bias of computed tomography (CT) ventricular volumetry using semiautomatic three-dimensional (3D) threshold-based segmentation in repaired tetralogy of Fallot, and to compare them to those of two-dimensional (2D) magnetic resonance imaging (MRI).

Materials and Methods

This retrospective study evaluated 32 patients with repaired tetralogy of Fallot who had undergone both cardiac CT and MRI within 3 years. For ventricular volumetry, semiautomatic 3D threshold-based segmentation was used in CT, while a manual simplified contouring 2D method was used in MRI. The indexed ventricular volumes were compared between CT and MRI. The indexed ventricular stroke volumes were compared with the indexed arterial stroke volumes measured using phase-contrast MRI. The mean differences and degrees of agreement in the indexed ventricular and stroke volumes were evaluated using Bland-Altman analysis.

Results

The indexed end-systolic (ES) volumes showed no significant difference between CT and MRI (p > 0.05), while the indexed end-diastolic (ED) volumes were significantly larger on CT than on MRI (93.6 ± 17.5 mL/m² vs. 87.3 ± 15.5 mL/m² for the left ventricle [p < 0.001] and 177.2 ± 39.5 mL/m² vs. 161.7 ± 33.1 mL/m² for the right ventricle [p < 0.001], respectively). The mean differences between CT and MRI were smaller for the indexed ES volumes (2.0–2.5 mL/m²) than for the indexed ED volumes (6.3–15.5 mL/m²). CT overestimated the stroke volumes by 14–16%. With phase-contrast MRI as a reference, CT (7.2–14.3 mL/m²) showed greater mean differences in the indexed stroke volumes than did MRI (0.8–3.3 mL/m²; p < 0.005).

Conclusion

Compared to 2D MRI, CT ventricular volumetry using semiautomatic 3D threshold-based segmentation provides comparable ES volumes, but overestimates the ED and stroke volumes in patients with repaired tetralogy of Fallot.

Comparison between Three-Dimensional Navigator-Gated Whole-Heart MRI and Two-Dimensional Cine MRI in Quantifying Ventricular Volumes

Objective

To test whether the method utilizing three-dimensional (3D) whole-heart MRI has an additional benefit over that utilizing conventional two-dimensional (2D) cine MRI in quantifying ventricular volumes.

Materials and Methods

In 110 patients with congenital heart disease, a navigator-gated, 3D whole-heart MRI during end-systole (ES) and end-diastole (ED), 2D short-axis cine MRI, and phase contrast MRI of the great arteries were acquired. Ventricular volumes were measured by using a 3D threshold-based segmentation for 3D whole-heart MRI and by using a simplified contouring for 2D cine MRI. The cardiac trigger delays of 3D whole-heart MRI were compared with those of a 2D cine MRI. The stroke volumes calculated from the ventricular volumes were compared with the arterial flow volumes, measured by phase contrast MRI.

Results

The ES and ED trigger delays of whole-heart MRI were significantly less than cine MRI for both the left ventricle (−16.8 ± 35.9 ms for ES, −59.0 ± 90.4 ms for ED; p < 0.001) and the right ventricle (−58.8 ± 30.6 ms for ES, −104.9 ± 92.7 ms for ED; p < 0.001). Compared with the arterial flow volumes, 2D cine MRI significantly overestimated the left ventricular stroke volumes (8.7 ± 8.9 mL, p < 0.001) and the 3D whole-heart MRI significantly underestimated the right ventricular stroke volumes (−22.7 ± 22.9 mL, p < 0.001).

Conclusion

Three-dimensional whole-heart MRI is often subject to early timing of the ED phase, potentially leading to the underestimation of the right ventricular stroke volumes.

Comparison of Echocardiography, Cardiac Magnetic Resonance, and Computed Tomographic Imaging for the Evaluation of Left Ventricular Myocardial Function: Part 1 (Global Assessment)

Assessing left ventricular function is an essential part of the cardiovascular evaluation as it plays an important role in managing the patient and predicting prognosis. Recent advances in the imaging modalities currently allow a non-invasive comprehensive assessment of cardiac mechanics and precise estimation of cardiovascular hemodynamics. In this review, we will discuss and compare the currently available techniques and novel approaches utilized by echocardiography, cardiac magnetic resonance, and computed tomography for the assessment of global left ventricular performance.

QUANTITATIVE PLANAR AND VOLUMETRIC CARDIAC MEASUREMENTS USING 64 MDCT AND 3T MRI VS. STANDARD 2D AND M-MODE ECHOCARDIOGRAPHY: DOES ANESTHETIC PROTOCOL MATTER?

Cross-sectional imaging of the heart utilizing computed tomography and magnetic resonance imaging (MRI) has been shown to be superior for the evaluation of cardiac morphology and systolic function in humans compared to echocardiography. The purpose of this prospective study was to test the effects of two different anesthetic protocols on cardiac measurements in 10 healthy beagle dogs using 64-multidetector row computed tomographic angiography (64-MDCTA), 3T magnetic resonance (MRI) and standard awake echocardiography. Both anesthetic protocols used propofol for induction and isoflourane for anesthetic maintenance. In addition, protocol A used midazolam/fentanyl and protocol B used dexmedetomedine as premedication and constant rate infusion during the procedure. Significant elevations in systolic and mean blood pressure were present when using protocol B. There was overall good agreement between the variables of cardiac size and systolic function generated from the MDCTA and MRI exams and no significant difference was found when comparing the variables acquired using either anesthetic protocol within each modality. Systolic function variables generated using 64-MDCTA and 3T MRI were only able to predict the left ventricular end diastolic volume as measured during awake echocardiogram when using protocol B and 64-MDCTA. For all other systolic function variables, prediction of awake echocardiographic results was not possible (P = 1). Planar variables acquired using MDCTA or MRI did not allow prediction of the corresponding measurements generated using echocardiography in the awake patients (P = 1). Future studies are needed to validate this approach in a more varied population and clinically affected dogs.

Model-based automatic segmentation algorithm accurately assesses the whole cardiac volumetric parameters in patients with cardiac CT angiography: a validation study for evaluating the accuracy of the workstation software and establishing the reference values

RATIONALE AND OBJECTIVES

The cardiac chamber volumes and functions can be assessed manually and automatically using the current computed tomography (CT) workstation system. We aimed to evaluate the accuracy and precision and to establish the reference values for both segmentation methods using cardiac CT angiography (CTA).

MATERIALS AND METHODS

A total of 134 subjects (mean age 55.3 years, 72 women) without heart disease were enrolled in the study. The cardiac four-chamber volumes, left ventricular (LV) mass, and biventricular functions were measured with manual, semiautomatic, and model-based fully automatic approaches. The accuracies of the semiautomated and fully automated approaches were validated by comparing them with manual segmentation as a reference. The precision error was determined and compared for both manual and automatic measurements.

RESULTS

No significant difference was found between the manual and semiautomatic assessments for the assessment of all functional parameters (P > .05). Using the manual method as a reference, the automatic approach provided a similar value in LV ejection fraction and left atrial volumes in both genders and right ventricular (RV) stroke volume in women (P > .05), with some underestimation of RV volume (P < .001) and overestimation of all remaining parameters (P < .05) in both genders. In addition, a significantly higher precision with a considerable association in intermeasurement (reproducibility) was observed using the automated approach.

CONCLUSIONS

The model-based fully automatic segmentation algorithm can help with the assessment of the cardiac four-chamber volume and function. This may help in establishing reference values of functional parameters in patients who undergo cardiac CTA.

Impact of ventricular contrast medium attenuation on the accuracy of left and right ventricular function analysis at cardiac multi detector-row CT compared with cardiac MRI

RATIONALE AND OBJECTIVES

The aim of this study was to investigate the impact of ventricular contrast medium attenuation on the accuracy of left ventricular (LV) and right ventricular (RV) function analysis on coronary computed tomographic angiographic (CCTA) imaging compared to cardiac magnetic resonance imaging (CMR).

MATERIALS AND METHODS

Thirty patients (mean age, 61.9 ± 11.2 years; 14 men) underwent CCTA imaging and CMR. For both the right and left ventricles, end-diastolic volume (EDV), end-systolic volume (ESV), and stroke volume (SV) were computed using multiphase image reconstruction of CCTA data. The accuracy of CCTA imaging was determined by subtracting CCTA measurements from CMR measurements. The accuracy of CCTA imaging was then correlated with the level of LV and RV contrast medium attenuation using regression analysis.

RESULTS

In the right ventricle, there was strong correlation between the accuracy of CCTA functional assessment of EDV (R(2) = 0.78, P < .001), ESV (R(2) = 0.36, P < .001), and SV (R(2) = 0.75, P < .001) and the level of RV contrast medium attenuation. In studies with lower RV enhancement (<176 Hounsfield units; n = 15), the mean CCTA deviations of EDV, ESV, and SV from CMR measurements were 43.6 ± 17.4, 11.2 ± 9.64, and 35.1 ± 11.5 mL, respectively. In studies with higher RV attenuation (>176 Hounsfield units; n = 15), these values were 13.6 ± 10, 8.0 ± 5.28, and 13 ± 4.96 mL, respectively. In the left ventricle, there was weak correlation between functional CCTA accuracy and LV attenuation (mean, 358.31 ± 68.71 Hounsfield units), and there was excellent correlation with CMR for LV EDV (R(2) = 0.86, P < .001), ESV (R(2) = 0.85, P < .001), and SV (R(2) = 0.51, P < .001).

CONCLUSIONS

If computed tomographic evaluation of RV function is desired, attention should be paid to the contrast injection protocol, because the accuracy of RV function analysis depends on the level of contrast medium attenuation. The high contrast medium attenuation that is typically achieved in the left ventricle routinely enables highly accurate measurements compared to CMR.

Accuracy of different reconstruction intervals to quantify left ventricular function and mass in cardiac computed tomography examinations

PURPOSE

To compare the accuracy of cardiac dual-source CT (DSCT) reconstructions obtained at 5% and 10% of the cardiac cycle and MRI for quantifying global left ventricular (LV) function and mass in heart transplant recipients.

MATERIAL AND METHODS

We prospectively included 23 heart transplant recipients (21 male, mean age 60±11.7 years) who underwent cardiac DSCT and MRI examinations. We compared LV parameters on cardiac DSCT reconstructions obtained at 5% (0%-95%) and 10% (0%-90%) intervals of the cardiac cycle and on double-oblique short-axis MR images. We determined ejection fraction (EF), end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), and myocardial mass using commercially available semiautomated segmentation analysis software for DSCT datasets and conventional manual contour tracing for MR studies.

RESULTS

Using different reconstruction intervals to quantify LV parameters at DSCT resulted in non-significant differences (P>.05). Compared to MRI, DSCT slightly overestimated LV-EDV, ESV, and mass when both 5% (11.5±25.1ml, 6.8±10.9ml, and 28.3±21.6g, respectively) and 10% (mean difference 15.3±26.3ml, 7.4±11.5ml, and 29.3±18.7g, respectively) reconstruction intervals were used. DSCT and MRI estimates of EF and SV were not significantly different.

CONCLUSION

In heart transplant recipients, DSCT allows reliable quantification of LV function and mass compared with MRI, even using 10% interval reconstructions.

Left ventricular volume: an optimal parameter to detect systolic dysfunction on prospectively triggered 64-multidetector row computed tomography: another step towards reducing radiation exposure

In this study, we define the correlation between LV volumes (both LV end-diastolic volume [LVEDV] and LV end-systolic volume [LVESV]) and ejection fraction (EF) on 64 slice multi-detector computed tomography (MDCT). We also determine the accuracy of all the LV volume (LVV) parameters to detect LV systolic dysfunction (LVSD) and investigate the feasibility of using LVV as a surrogate of LVSD on prospectively gated imaging to prevent the radiation exposure of retrospective imaging. 568 patients undergoing 64-detector MDCT were divided into 2 groups: Group 1—subjects without any heart disease and LVEF ≥ 50%; and Group 2—patients with coronary artery disease and LVEF < 50% (defined as LVSD). The LVV (LV cavity only) and Total LV volume (cavity + LV mass) at end-systole and end-diastole (LVESV, Total LVESV, LVEDV and Total LVEDV) were measured. The upper limit values (mean + 2 SD) of all LVV parameters in Group 1 were used as the reference criterion to diagnose LVSD in Group 2. An exponential correlation was found between LVEF and all the LVV parameters. The specificity to detect LVSD in Group 2 was >90% and the sensitivity was 88.9, 83.3, 61.3 and 74.9% by using LVESV, Total LVESV, LVEDV and Total LVEDV, respectively. Systolic and diastolic LV volumes had a high correlation with LVEF and a high accuracy to detect LVSD. Thus, on prospectively triggered imaging, ventricular volumes can predict patients with reduced LVEF, and appropriate referrals can be made.

Cardiac CT for the differentiation of bicuspid and tricuspid aortic valves: comparison with echocardiography and surgery

OBJECTIVE

The purpose of this study is to evaluate the diagnostic performance of CT, compared with that of echocardiography and surgery, for differentiating between bicuspid and tricuspid aortic valves.

MATERIALS AND METHODS

Forty-seven patients with bicuspid valve and 47 patients with tricuspid aortic valve underwent retrospectively ECG-gated dual-source CT and echocardiography. Thirty-four (72%) of the 47 patients with bicuspid aortic valve underwent valve surgery. Two independent blinded observers assessed the CT image quality of the aortic valve during diastole and systole on a 4-point scale, determined which phase allowed the differentiation of valve type, distinguished between tricuspid and bicuspid aortic valves, and assessed for the presence of a raphe. Diagnostic performance of CT was determined using echocardiography and surgery as the reference standard.

RESULTS

According to echocardiography and surgery, seven (15%) of the 47 bicuspid aortic valves had no raphe, and 40 (85%) had a raphe. CT image quality was diagnostic (i.e., scores of 1-3) in all 94 patients in both diastole and systole. Among patients with bicuspid aortic valve and no raphe, differentiation between tricuspid and bicuspid aortic valves could be performed in diastole in 100% (7/7) of cases. Among patients with bicuspid aortic valve and raphe, differentiation was possible only in systole in 5% (2/40) of cases and when combining diastole and systole in 95% (38/40) of cases. In three bicuspid aortic valves with raphe, the valve was misclassified by CT as tricuspid aortic valve. Overall sensitivity and specificity of CT for the diagnosis of bicuspid aortic valve were 94% and 100%.

CONCLUSION

CT is highly accurate for differentiation between bicuspid and tricuspid aortic valves. For bicuspid aortic valves without raphe, diastolic reconstructions are sufficient, whereas in those with a raphe, additional reconstructions in systole are required.

Comparison of (semi-)automatic and manually adjusted measurements of left ventricular function in dual source computed tomography using three different software tools

To assess the accuracy of (semi-)automatic measurements of left ventricular (LV) functional parameters in cardiac dual-source computed tomography (DSCT) compared to manually adjusted measurements in three different workstations. Forty patients, who underwent cardiac DSCT, were included (31 men, mean age 58 ± 14 years). Multiphase reconstructions were made with ten series at every 10% of the RR-interval. LV function analysis was performed on three different, commercially available workstations. On all three workstations, end-systolic volume (ESV), end-diastolic volume (EDV), LV ejection fraction (LVEF) and myocardial mass (MM) were calculated as automatically as possible. With the same DSCT datasets, LV functional parameters were also calculated with as many manual adjustments as needed for accurate assessment for all three software tools. For both semi-automatic as well as manual methods, time needed for evaluation was recorded. Paired t-tests were employed to calculate differences in LV functional parameters. Repeated measurements were performed to determine intra-observer and inter-observer variability. (Semi-)automatic measurements revealed a good correlation with manually adjusted measurements for Vitrea (LVEF r = 0.93, EDV r = 0.94, ESV r = 0.98 and MM r = 0.94) and Aquarius (LVEF r = 0.96, EDV r = 0.94, ESV r = 0.98 and MM r = 0.96). Also, good correlation was obtained for Circulation, except for LVEF (LVEF r = 0.45, EDV r = 0.93, ESV r = 0.92 and MM r = 0.86). However, statistically significant differences were found between (semi-)automatically and manually adjusted measurements for LVEF (P < 0.05) and ESV (P < 0.001) in Vitrea, all LV functional parameters in Circulation (P < 0.001) and EDV, ESV and MM (<0.001) in Aquarius Workstation. (Semi-)automatic measurement of LV functional parameters is feasible, but significant differences were found for at least two different functional parameters in all three workstations. Therefore, expert manual correction is recommended at all times.

Assessment of Epicardial Fat Volume With Threshold-Based 3-Dimensional Segmentation in CT: Comparison With the 2-Dimensional Short Axis-Based Method

Background and Objectives

We aimed to assess the usefulness of a threshold-based, 3-dimensional (3D) segmentation in comparison with the traditional 2-dimensional (2D) short axis-based method for measurement of epicardial fat volume with 64-slice multidetector computed tomography (MDCT).

Subjects and Methods

One hundred patients (52 males; mean age, 58.36±11.0 years) who underwent coronary CT angiography were enrolled in this study. The epicardial fat volume was measured using the two methods. The existing method was the 2D short axis-based method and the new method was the threshold-based 3D segmentation. Pearson's correlation was used to compare the two measurement methods. We also assessed the relationship between the epicardial fat volume and coronary artery disease (CAD).

Results

There were a strong correlation between the epicardial fat volumes determined using the two methods (r=0.956, p<0.001). The mean overestimation of epicardial fat volume by the threshold-based 3D method was 59.89±12.00% compared to the 2D short-axis based method. Using the 3D method, the epicardial fat volume was significantly higher in the CAD group than in the controls (165.07±48.22 cm³ vs. 108.39±48.03 cm³, p<0.001).

Conclusion

Threshold-based 3D segmentation is another easy and useful tool for measuring the epicardial fat volume.

Region-based endocardium tracking on real-time three-dimensional ultrasound

Matrix-phased array transducers for real-time 3-D ultrasound enable fast, noninvasive visualization of cardiac ventricles. Typically, 3-D ultrasound images are semiautomatically segmented to extract the left ventricular endocardial surface at end-diastole and end-systole. Automatic segmentation and propagation of this surface throughout the entire cardiac cycle is a challenging and cumbersome task. If the position of the endocardial surface is provided at one or two time frames during the cardiac cycle, automated tracking of the surface over the remaining time frames could reduce the workload of cardiologists and optimize analysis of 3-D ultrasound data. In this paper, we applied a region-based tracking algorithm to track the endocardial surface between two reference frames that were manually segmented. To evaluate the tracking of the endocardium, the method was applied to 40 open-chest dog datasets with 484 frames in total. Ventricular geometry and volumes derived from region-based endocardial surfaces and manual tracing were quantitatively compared, showing strong correlation between the two approaches. Statistical analysis showed that the errors from tracking were within the range of interobserver variability of manual tracing. Moreover, our algorithm performed well on ischemia datasets, suggesting that the method is robust-to-abnormal wall motion. In conclusion, the proposed optical flow-based surface tracking method is very efficient and accurate, providing dynamic "interpolation" of segmented endocardial surfaces.

[Comparison of 2D and 3D techniques in the evaluation of global ventricular function on multidetector-row CT]

PURPOSE

To compare two methods of post processing cardiac CT data to measure global ventricular function. Materials and methods. Retrospective study where three readers measured the end-diastolic volume (EDV), end-systolic volume (ESV) and ejection fraction (EF) of the right (n=22) and left (n=44) ventricles, using a 2D method (extrapolated volumetric method, EVM) and a 3D method (direct volumetric method, DVM) after cardiac CT with retrospective ECG gating. Inter- and intraobserver agreement were calculated based on the intraclass correlation coefficient (ICC) with 95% confidence interval (CI95%), and results obtained with each method were compared using the student t test for paired samples.

RESULTS

Inter- and intraobserver reproducibility were very good for both methods, with ICC ranging between 0.694 and 0.992, without significant difference. For the left ventricle, EDV, ESV and EF were 16653 ml, 8351 ml and 5415% for DVM et de 20361 ml, 11558 ml and 4613% for EVM respectively. Right ventricular values were 15247 ml, 7534 ml, 5013% and 17253 ml, 9940 ml, 439% (p<0,0001).

CONCLUSION

The very good inter- and intraobserver reproducibility for both methods validate their use in clinical practice. Volume measurements with DVM are always inferior to volumes with EDM, with inverse relationship for EF measurements.