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.
Currently, cardiac computed tomography angiography (cardiac CTA) is widely used as an effective method to detect and rule out coronary artery disease (CAD) and for the simultaneous assessment of size and function of cardiac chamber. The cardiac chamber volumes, left ventricular (LV) mass, and the biventricular systolic functions are important parameters for the diagnosis, prognosis, risk stratification, and management of patients with heart disease .
Semiautomated threshold-based segmentation techniques have been used to segment the blood pool for the assessment of the LV function . However, the complexity of heart anatomy, with suboptimal contrast within the right chambers, and a variety of other structures with different characteristics in the cardiac region pose a challenge, thereby demonstrating a need for more robust approaches for segmenting all the four chambers. These challenges have led to the development of a fully automatic model-based segmentation algorithm that has been evaluated in clinical studies , with the technical aspects described in previous works . To achieve fully automatic segmentation, detection of the heart location and extraction of the cardiac structures play a key role. Some initial studies indicated that the generalized hough transform algorithm may have the potential to detect the heart in three-dimensional (3D) space despite variations in cardiac shape, pose, and imaging protocols as well as in the presence of noise . The successive algorithms combining parametric and deformable adaptations can be used for the exact extraction of the cardiac anatomic structures . It is possible to segment whole cardiac structures accurately by the combination of both techniques described previously. Clinical studies have shown that this automatic segmentation algorithm is robust to significant morphologic, contrast, and noise variations across patients and imaging phases of R-R interval and has the potential to accurately segment the great vessels and four chambers .
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Methods
Study Population
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Table 1
Clinical and Demographic Characteristics of Study Subjects
Characteristics Men ( n = 59) Women ( n = 72) Age (year) 54.0 ± 10.6 56.4 ± 11.1 Race Caucasian (%) 50.8 48.6 Hispanic (%) 15.2 18.1 African-American (%) 11.9 13.9 Asia (%) 13.6 9.7 Other (%) 8.5 9.7 Height (cm) 176.1 ± 11.9 159.6 ± 10.1 Weight (kg) 89.4 ± 21.4 71.1 ± 16.7 Body surface area (m 2 ) 2.1 ± 0.3 1.7 ± 0.2 Body mass index (kg/m 2 ) 28.8 ± 6.0 27.9 ± 6.1 Body mass index (BMI) BMI < 18.5 kg/m 2 (%) 0 1.4 BMI 18.5–24.9 kg/m 2 (%) 27.1 36.1 BMI 25–29.9 kg/m 2 (%) 40.7 34.7 BMI ≥ 30 kg/m 2 (%) 32.2 27.8 Chest pain 23.7 16.7 Family history of heart disease 35.6 38.9 Smoking (%) 5.0 1.4 Diabetes mellitus (%) 0 0 High cholesterol (%) 30.5 27.8 Hypertension (%) 0 0 Coronary Agatston Score 0 0 Lifestyle Sedentary (%) 8.4 8.3 Active (%) 69.2 68.1 Stress (%) 22.4 23.6 Heart rate during computed tomography angiography 56.4 ± 6.5 58.1 ± 8.1
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Multidetector Computed Tomography
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Cardiac CTA
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Data Acquisition
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Four-chamber Segmentations
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Statistical Analyses
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Results
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Table 2
Reference Values of Four-Chamber Volumes at End Systole, Mid Diastole, and End Diastole with Manual and Automatic Methods
Men ( n = 59) Women ( n = 72) End Systole Mid Diastole End Diastole End Systole Mid Diastole End Diastole LVV manual (mL) 55.1 ± 14.0 109.0 ± 20.8 130.0 ± 22.9 46.4 ± 13.6 97.0 ± 19.1 113.8 ± 18.7 LVV automatic (mL) 63.0 ± 16.1 124.3 ± 22.7 148.9 ± 25.3 57.9 ± 15.0 111.5 ± 20.6 133.1 ± 22.0 LVV manual (mL/m 2 ) 27.2 ± 7.1 53.7 ± 10.8 64.1 ± 12.1 26.9 ± 7.8 56.2 ± 9.9 66.0 ± 9.9 LVV automatic (mL/m 2 ) 31.1 ± 8.6 61.3 ± 12.1 73.4 ± 13.5 33.8 ± 8.8 64.8 ± 11.8 77.4 ± 12.6 RVV manual (mL) 111.1 ± 28.9 167.9 ± 36.0 186.8 ± 38.1 76.9 ± 17.1 127.0 ± 26.7 142.3 ± 26.4 RVV automatic (mL) 106.1 ± 26.5 165.2 ± 36.0 185.8 ± 37.8 73.3 ± 15.8 122.1 ± 24.8 138.0 ± 25.2 RVV manual (mL/m 2 ) 54.2 ± 12.3 81.1 ± 15.1 91.4 ± 16.0 44.4 ± 8.6 73.6 ± 13.5 82.3 ± 12.4 RVV automatic (mL/m 2 ) 51.7 ± 11.1 80.7 ± 14.7 90.9 ± 15.5 42.5 ± 8.2 70.7 ± 12.4 80.0 ± 12.7 RAV manual (mL) 99.5 ± 25.4 81.2 ± 19.7 58.3 ± 17.6 89.7 ± 20.4 70.7 ± 16.1 46.6 ± 13.4 RAV automatic (mL) 106.4 ± 25.5 88.9 ± 22.8 68.7 ± 19.8 94.1 ± 22.6 73.6 ± 18.6 52.5 ± 15.6 RAV manual (mL/m 2 ) 49.1 ± 13.1 40.1 ± 10.2 28.6 ± 8.3 52.3 ± 12.6 41.3 ± 10.2 27.2 ± 8.3 RAV automatic (mL/m 2 ) 52.5 ± 13.2 43.7 ± 10.9 33.6 ± 9.0 54.8 ± 13.3 42.8 ± 10.9 30.5 ± 9.2 LAV manual, automatic (mL) 87.5 ± 17.9 73.1 ± 15.3 53.5 ± 16.0 85.8 ± 20.9 70.4 ± 18.3 52.8 ± 17.6 LAV manual, automatic (mL/m 2 ) 43.3 ± 10.3 36.1 ± 8.4 26.4 ± 8.4 50.1 ± 12.9 41.1 ± 11.2 30.9 ± 10.7
LAV, left atrial volume; LVV, left ventricular volume; RAV, right atrial volume; RVV, right ventricular volume.
Table 3
The Reference Values of Left and Right Ventricular Stroke Volume, Functions and LV Mass Using Both Manual and Automatic Assessment, and the Biases of Automatic Assessment from Manual Segmentation
n Manual Automatic Bias 95% CI_P_ value (Manual–Automatic)r value (Manual–Automatic) LVEF in men and women (%) 131 57.9 ± 7.4 57.2 ± 7.3 −0.7 −11.1, 9.6 .111 0.74 LVSV in men (mL) 59 74.9 ± 15.3 86.1 ± 17.4 11.2 −9.0, 31.4 <.001 0.81 LVSV in women (mL) 72 67.2 ± 12.3 75.3 ± 13.5 8.1 −7.7, 23.6 <.001 0.81 RVEF in men (%) 59 41.0 ± 6.3 43.4 ± 7.3 2.4 −4.3, 9.2 <.001 0.88 RVEF in women (%) 72 45.9 ± 5.3 47.2 ± 4.8 1.3 −4.9, 7.2 <.002 0.81 RVSV in men (mL) 59 75.7 ± 15.6 80.2 ± 18.4 4.5 −12.3, 21.0 <.001 0.89 RVSV in women (mL) 72 65.5 ± 13.7 64.8 ± 13.7 −0.7 −14.8, 13.6 .888 0.86 LV mass at mid diastole in men (g) 59 137.8 ± 35.1 142.6 ± 32.6 4.8 −26.4, 36.1 <.001 0.89 LV mass at mid diastole in women (g) 72 93.1 ± 18.8 97.6 ± 17.2 4.5 −23.8, 32.7 .012 0.89 LVV at mid diastole in men and women (mL) 131 102.4 ± 20.7 117.3 ± 22.4 14.9 −5.7, 35.5 <.001 0.88 RVV at mid diastole in men and women (mL) 131 145.3 ± 37.0 141.4 ± 37.1 −3.9 −21.0, 13.1 <.001 0.97 RAV at end systole in men and women (mL) 131 94.1 ± 23.2 99.6 ± 24.6 5.5 −15.4, 26.4 <.001 0.90 LAV at end systole in men and women (mL) 131 86.6 ± 19.6 85.7 ± 18.9 −0.9 −12.2, 10.4 .068 0.96
LAV, left atrial volume; LVEF, left ventricular ejection fraction; LV mass, LV myocardium; LVV, left ventricular volume; RAV, right atrial volume; RVV, right ventricular volume; SV, stroke volume.
The indexed parameters can be calculated using the body surface area (men in 2.1 and women in 1.7 m 2 ).
Table 4
Comparison of Precision Error between Manual and Automatic Segmentation in all Patients (C.V and Kappa Coefficient)
Manual C.V (%) Kappa Coefficient (95% CI) Auto C.V (%) Kappa Coefficient (95% CI) LVEF (%) 5.2 ± 2.8 0.70 (0.65–0.75) 2.1 ± 1.2 0.90 (0.88–0.93) LVSV (mL) 6.8 ± 4.5 0.72 (0.68–0.78) 3.9 ± 3.2 0.86 (0.83–0.88) LVV at end systole (mL) 8.5 ± 4.4 0.75 (0.70–0.80) 1.8 ± 1.2 0.96 (0.95–0.97) LVV at mid diastole (mL) 3.8 ± 4.2 0.72 (0.67–0.78) 2.0 ± 2.5 0.92 (0.91–0.94) LVV at end diastole (mL) 3.5 ± 4.7 0.78 (0.74–0.81) 1.9 ± 2.8 0.94 (0.93–0.95) LV mass at mid diastole (mL) 7.9 ± 8.8 0.72 (0.67–0.78) 1.8 ± 2.7 0.97 (0.96–0.99) Total LVV at mid diastole (mL) 3.1 ± 6.2 0.82 (0.78–0.86) 1.3 ± 3.9 0.94 (0.93–0.95) RVV at mid diastole (mL) 4.1 ± 5.8 0.80 (0.76–0.84) 1.6 ± 2.1 0.94 (0.93–0.95) RAV at end systole (mL) 4.8 ± 4.7 0.79 (0.77–0.81) 1.2 ± 1.2 0.98 (0.97–0.99) LAV at end systole (mL) 5.2 ± 4.3 0.78 (0.76–0.81) 1.7 ± 1.9 0.94 (0.93–0.96)
CV, cardiovascular; LAV, left atrial volume; LVEF, left ventricular ejection fraction; LV mass, LV myocardium; LVV, left ventricular volume; RAV, right atrial volume; RVV, right ventricular volume; SV, stroke volume.
Total LVV = LVV + LV mass.
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Discussion
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Limitation
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Summary
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