A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.

Influence of reconstruction parameters during filtered backprojection and ordered-subset expectation maximization in the measurement of the left-ventricular volumes and function during gated SPECT

A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). Methods: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. Results: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. Conclusion: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.

Influence of reconstruction parameters during filtered backprojection and ordered-subset expectation maximization in the measurement of the left-ventricular volumes and function during gated SPECT.

A crucial method for investigating patients with coronary artery disease (CAD) is the calculation of the left ventricular ejection fraction (LVEF). It is, consequently, imperative to precisely estimate the value of LVEF--a process that can be done with myocardial perfusion scintigraphy. Therefore, the present study aimed to establish and compare the estimation performance of the quantitative parameters of the reconstruction methods filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM). METHODS: A beating-heart phantom with known values of end-diastolic volume, end-systolic volume, and LVEF was used. Quantitative gated SPECT/quantitative perfusion SPECT software was used to obtain these quantitative parameters in a semiautomatic mode. The Butterworth filter was used in FBP, with the cutoff frequencies between 0.2 and 0.8 cycles per pixel combined with the orders of 5, 10, 15, and 20. Sixty-three reconstructions were performed using 2, 4, 6, 8, 10, 12, and 16 OSEM subsets, combined with several iterations: 2, 4, 6, 8, 10, 12, 16, 32, and 64. RESULTS: With FBP, the values of end-diastolic, end-systolic, and the stroke volumes rise as the cutoff frequency increases, whereas the value of LVEF diminishes. This same pattern is verified with the OSEM reconstruction. However, with OSEM there is a more precise estimation of the quantitative parameters, especially with the combinations 2 iterations × 10 subsets and 2 iterations × 12 subsets. CONCLUSION: The OSEM reconstruction presents better estimations of the quantitative parameters than does FBP. This study recommends the use of 2 iterations with 10 or 12 subsets for OSEM and a cutoff frequency of 0.5 cycles per pixel with the orders 5, 10, or 15 for FBP as the best estimations for the left ventricular volumes and ejection fraction quantification in myocardial perfusion scintigraphy.

Three-dimensional ordered-subset expectation maximization iterative protocol for evaluation of left ventricular volumes and function by quantitative gated SPECT: a dynamic phantom study.

The purposes of this study were to characterize the performance of a 3-dimensional (3D) ordered-subset expectation maximization (OSEM) algorithm in the quantification of left ventricular (LV) function with (99m)Tc-labeled agent gated SPECT (G-SPECT), the QGS program, and a beating-heart phantom and to optimize the reconstruction parameters for clinical applications. METHODS: A G-SPECT image of a dynamic heart phantom simulating the beating left ventricle was acquired. The exact volumes of the phantom were known and were as follows: end-diastolic volume (EDV) of 112 mL, end-systolic volume (ESV) of 37 mL, and stroke volume (SV) of 75 mL; these volumes produced an LV ejection fraction (LVEF) of 67%. Tomographic reconstructions were obtained after 10-20 iterations (I) with 4, 8, and 16 subsets (S) at full width at half maximum (FWHM) gaussian postprocessing filter cutoff values of 8-15 mm. The QGS program was used for quantitative measurements. RESULTS: Measured values ranged from 72 to 92 mL for EDV, from 18 to 32 mL for ESV, and from 54 to 63 mL for SV, and the calculated LVEF ranged from 65% to 76%. Overall, the combination of 10 I, 8 S, and a cutoff filter value of 10 mm produced the most accurate results. The plot of the measures with respect to the expectation maximization-equivalent iterations (I x S product) revealed a bell-shaped curve for the LV volumes and a reverse distribution for the LVEF, with the best results in the intermediate range. In particular, FWHM cutoff values exceeding 10 mm affected the estimation of the LV volumes. CONCLUSION: The QGS program is able to correctly calculate the LVEF when used in association with an optimized 3D OSEM algorithm (8 S, 10 I, and FWHM of 10 mm) but underestimates the LV volumes. However, various combinations of technical parameters, including a limited range of I and S (80-160 expectation maximization-equivalent iterations) and low cutoff values (< or =10 mm) for the gaussian postprocessing filter, produced results with similar accuracies and without clinically relevant differences in the LV volumes and the estimated LVEF.

Comparison between real-time three-dimensional echocardiography, T1-201 single photon emission computed tomography and cardiac magnetic resonance imaging in the quantitative assessment of left ventricular volumes

Left ventricular (LV) volumes have important prognostic implications in patients with chronic ischemic heart disease. We sought to examine the accuracy and reproducibility of real-time 3D echo (RT-3DE) compared to TI-201 single photon emission computed tomography (SPECT) and cardiac magnetic resonance imaging (MRI). Thirty (n = 30) patients (age 62±9 years, 23 men) with chronic ischemic heart disease underwent LV volume assessment with RT-3DE, SPECT, and MRI. Ano vel semi-automated border detection algorithmwas used by RT-3DE. End diastolic volumes (EDV) and end systolic volumes (ESV) measured by RT3DE and SPECT were compared to MRI as the standard of reference. RT-3DE and SPECT volumes showed excellent correlation with MRI (Table). Both RT- 3DE and SPECT underestimated LV volumes compared to MRI (ESV, SPECT 74±58 ml versus RT-3DE 95±48 ml versus MRI 96±54 ml); (EDV, SPECT 121±61 ml versus RT-3DE 169±61 ml versus MRI 179±56 ml). The degree of ESV underestimation with RT-3DE was not significant.

Coronary revascularization can improve regional left ventricular volumes in non-transmural scars without contractile reserve

Revascularization (RVS) of scar segts does not lead to recovery of left ventricular (LV) function, but its effect on post-infarct remodeling is unclear. We examined the impact of RVS on regional remodeling in different transmural extents of scar (TME). Dobutamine echo (DbE) and contrast enhanced magnetic resonance imaging (ce- MRI) were performed in 72 pts post MI (age 63±10, EF 49±12%). Pts were selected for RVS (n = 31) or medical treatment (n = 41). Segts were classified as scar if there were no contractile reserve during lowdose DbE.TMEwas measured by ce-MRI; a cutoff of 75% was used to differentiate transmural (TM) from non-transmural (NT) scars. Regional end systolic (ESV) and end diastolic volumes (EDV) were measured at baseline and 12 months follow up.Of 218 segts identified as scar on DbE, 164wereNTand 54 were TM on ce-MRI. Revascularization was performed to 62 NT and 11 TM segts. In the RVS group, there was reverse remodeling with significant reduction in LV volumes in NT (ESV, 6.8±3.2 ml versus 5.8±3.7 ml, p = 0.002; EDV, 10.9±4.9 ml versus 9.8±5.6 ml, p = 0.02), but no significant change in volumes in TM (ESV, 6.9±3.7 ml versus 5.4±2.1 ml, p = 0.09; EDV, 10.2±4.4 ml versus 9.4±4.3 ml, p = 0.5). In the medically treated group, there were no changes in LV volumes in both NT (ESV, 12.0±11.9 ml versus 12.7±13.8 ml, p = 0.3; EDV, 12.5±7.8 ml versus 12.6±9.7 ml, p = 0.8) and TM (ESV, 8.0±3.8 ml versus 7.9±4.6 ml, p = 0.8; EDV, 10.3±4.8 ml versus 10.4±5.4 ml, p = 0.9). Despite absence of contractile reserve on DbE, NT benefit from coronary revascularization with regional reverse LV remodeling.

Reduction in scar thickness post myocardial infarction is secondary to increase in regional left ventricular volumes

We sought to determine the relative impact of myocardial scar and viability on post-infarct left ventricular (LV) remodeling in medically-treated patients with LV dysfunction. Forty patients with chronic ischemic heart disease (age 64±9, EF 40±11%) underwent rest-redistribution Tl201 SPECT (scar = 50% transmural extent), A global index of scarring for each patient (CMR scar score) was calculated as the sum of transmural extent scores in all segts. LV end diastolic volumes (LVEDV) and LV end systolic volumes (LVESV) were measured by real-time threedimensional echo at baseline and median of 12 months follow-up. There was a significant positive correlation between change in LVEDV with number of scar segts by all three imaging techniques (LVEDV: SPECT scar, r = 0.62, p < 0.001; DbE scar, r = 0.57, p < 0.001; CMR scar, r = 0.52, p < 0.001) but change in LV volumes did not the correlate with number of viable segments. ROC curve analysis showed that remodeling (LVEDV> 15%) was predicted bySPECTscars(AUC= 0.79),DbEscars(AUC= 0.76),CMR scars (AUC= 0.70), and CMR scar score (AUC 0.72). There were no significant differences between any of the ROC curves (Z score

Influence of left ventricular size and hemodynamics on the systolic longitudinal myocardial Doppler velocity response to stress

Background Systolic myocardial Doppler velocity accurately identifies coronary artery disease. However, these velocities may be affected by age, hemodynamic responses to stress, and left ventricular cavity size. We sought to examine the influences of these variables on myocardial velocity during dobutamine stress in patients with normal wall motion. Methods One hundred seventy-nine consecutive patients with normal dobutamine echocardiograms were studied. Color myocardial tissue Doppler data were obtained at rest and peak stress, and peak systolic myocardial velocity (PSV) was measured in all basal and midventricular segments. Velocities at rest and peak stress were compared with left ventricular diastolic and systolic volumes, blood pressure, heart rate, and age by Pearson correlation and interdecile analysis by use of analysis of variance. Results The only clinical variable correlating with velocity was age; PSV showed only mild correlation with age at rest (r(2) = 0.01, P = .001) and peak stress (r(2) = 0.02, P = .001), but the normal peak velocity was significantly different between the extremes of age (<44 years and >74 years). There was very weak correlation of PSV with systolic and diastolic blood pressure (r(2) < 0.01), heart rate (r(2) < 0.01), systemic vascular resistance (r(2) = 0.08), and left ventricular volumes (r(2) < 0.01). Conclusions Peak systolic velocity during dobutamine stress is relatively independent of hemodynamic factors and left ventricular cavity size. The extremes of age may influence peak systolic Doppler velocities. These results suggest that peak systolic velocity may be a robust quantitative measure during dobutamine echocardiography across most patient subgroups.