Rapid and accurate left ventricular chamber quantification using a novel CMR segmentation algorithm: a clinical validation study

Estimation of Left and Right Ventricular Ejection Fractions from cine-MRI Using 3D-CNN

Cardiac function indices must be calculated using tracing from short-axis images in cine-MRI. A 3D-CNN (convolutional neural network) that adds time series information to images can estimate cardiac function indices without tracing using images with known values and cardiac cycles as the input. Since the short-axis image depicts the left and right ventricles, it is unclear which motion feature is captured. This study aims to estimate the indices by learning the short-axis images and the known left and right ventricular ejection fractions and to confirm the accuracy and whether each index is captured as a feature. A total of 100 patients with publicly available short-axis cine images were used. The dataset was divided into training:test = 8:2, and a regression model was built by training with the 3D-ResNet50. Accuracy was assessed using a five-fold cross-validation. The correlation coefficient, MAE (mean absolute error), and RMSE (root mean squared error) were determined as indices of accuracy evaluation. The mean correlation coefficient of the left ventricular ejection fraction was 0.80, MAE was 9.41, and RMSE was 12.26. The mean correlation coefficient of the right ventricular ejection fraction was 0.56, MAE was 11.35, and RMSE was 14.95. The correlation coefficient was considerably higher for the left ventricular ejection fraction. Regression modeling using the 3D-CNN indicated that the left ventricular ejection fraction was estimated more accurately, and left ventricular systolic function was captured as a feature.

Ultrafast Computation of Left Ventricular Ejection Fraction by Using Temporal Intensity Variation in Cine Cardiac Magnetic Resonance

Cardiac magnetic resonance enables comprehensive cardiac evaluation; however, intense time and labor requirements for data acquisition and processing have discouraged many clinicians from using it. We have developed an alternative image-processing algorithm that requires minimal user interaction: an ultrafast algorithm that computes left ventricular ejection fraction (LVEF) by using temporal intensity variation in cine balanced steady-state free precession (bSSFP) short-axis images, with or without contrast medium. We evaluated the algorithm's performance against an expert observer's analysis for segmenting the LV cavity in 65 study participants (LVEF range, 12%-70%). In 12 instances, contrast medium was administered before cine imaging. Bland-Altman analysis revealed quantitative effects of LV basal, midcavity, and apical morphologic variation on the algorithm's accuracy. Total computation time for the LV stack was <2.5 seconds. The algorithm accurately delineated endocardial boundaries in 1,132 of 1,216 slices (93%). When contours in the extreme basal and apical slices were not adequate, they were replaced with manually drawn contours. The Bland-Altman mean differences were <1.2 mL (0.8%) for end-diastolic volume, <5 mL (6%) for end-systolic volume, and <3% for LVEF. Standard deviation of the difference was ≤4.1% of LV volume for all sections except the midcavity in end-systole (8.3% of end-systolic volume). We conclude that temporal intensity variation-based ultrafast LVEF computation is clinically accurate across a range of LV shapes and wall motions and is suitable for postcontrast cine SSFP imaging. Our algorithm enables real-time processing of cine bSSFP images on a commercial scanner console within 3 seconds in an unobtrusive automated process.

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification

BACKGROUND

Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning have markedly improved automated processing, but have yet to be applied to PC-CMR. This study tested a novel machine learning model for fully automated analysis of PC-CMR aortic flow.

METHODS

A machine learning model was designed to track aortic valve borders based on neural network approaches. The model was trained in a derivation cohort encompassing 150 patients who underwent clinical PC-CMR then compared to manual and commercially-available automated segmentation in a prospective validation cohort. Further validation testing was performed in an external cohort acquired from a different site/CMR vendor.

RESULTS

Among 190 coronary artery disease patients prospectively undergoing CMR on commercial scanners (84% 1.5T, 16% 3T), machine learning segmentation was uniformly successful, requiring no human intervention: Segmentation time was < 0.01 min/case (1.2 min for entire dataset); manual segmentation required 3.96 ± 0.36 min/case (12.5 h for entire dataset). Correlations between machine learning and manual segmentation-derived flow approached unity (r = 0.99, p < 0.001). Machine learning yielded smaller absolute differences with manual segmentation than did commercial automation (1.85 ± 1.80 vs. 3.33 ± 3.18 mL, p < 0.01): Nearly all (98%) of cases differed by ≤5 mL between machine learning and manual methods. Among patients without advanced mitral regurgitation, machine learning correlated well (r = 0.63, p < 0.001) and yielded small differences with cine-CMR stroke volume (∆ 1.3 ± 17.7 mL, p = 0.36). Among advanced mitral regurgitation patients, machine learning yielded lower stroke volume than did volumetric cine-CMR (∆ 12.6 ± 20.9 mL, p = 0.005), further supporting validity of this method. Among the external validation cohort (n = 80) acquired using a different CMR vendor, the algorithm yielded equivalently small differences (∆ 1.39 ± 1.77 mL, p = 0.4) and high correlations (r = 0.99, p < 0.001) with manual segmentation, including similar results in 20 patients with bicuspid or stenotic aortic valve pathology (∆ 1.71 ± 2.25 mL, p = 0.25).

CONCLUSION

Fully automated machine learning PC-CMR segmentation performs robustly for aortic flow quantification - yielding rapid segmentation, small differences with manual segmentation, and identification of differential forward/left ventricular volumetric stroke volume in context of concomitant mitral regurgitation. Findings support use of machine learning for analysis of large scale CMR datasets.

Blood-threshold CMR volume analysis of functional univentricular heart

PURPOSE

To validate a blood-threshold (BT) segmentation software for cardiac magnetic resonance (CMR) cine images in patients with functional univentricular heart (FUH).

MATERIALS AND METHODS

We evaluated retrospectively 44 FUH patients aged 25 ± 8 years (mean ± standard deviation). For each patient, the epicardial contour of the single ventricle was manually segmented on cine images by two readers and an automated BT algorithm was independently applied to calculate end-diastolic volume (EDV), end-systolic volume (ESV), stroke volume (SV), ejection fraction (EF), and cardiac mass (CM). Aortic flow analysis (AFA) was performed on through-plane images to obtain forward volumes and used as a benchmark. Reproducibility was tested in a subgroup of 24 randomly selected patients. Wilcoxon, Spearman, and Bland-Altman statistics were used.

RESULTS

No significant difference was found between SV (median 57.7 ml; interquartile range 47.9-75.6) and aortic forward flow (57.4 ml; 48.9-80.4) (p = 0.123), with a high correlation (r = 0.789, p < 0.001). Intra-reader reproducibility was 86% for SV segmentation, and 96% for AFA. Inter-reader reproducibility was 85 and 96%, respectively.

CONCLUSION

The BT segmentation provided an accurate and reproducible assessment of heart function in FUH patients.

Multiplanar strain quantification for assessment of right ventricular dysfunction and non-ischemic fibrosis among patients with ischemic mitral regurgitation

Background

Ischemic mitral regurgitation (iMR) predisposes to right ventricular (RV) pressure and volume overload, providing a nidus for RV dysfunction (RV_DYS) and non-ischemic fibrosis (NIF). Echocardiography (echo) is widely used to assess iMR, but performance of different indices as markers of RV_DYS and NIF is unknown.

Methods

iMR patients prospectively underwent echo and cardiac magnetic resonance (CMR) within 72 hours. Echo quantified iMR, assessed conventional RV indices (TAPSE, RV-S’, fractional area change [FAC]), and strain via speckle tracking in apical 4-chamber (global longitudinal strain [RV-GLS]) and parasternal long axis orientation (transverse strain). CMR volumetrically quantified RVEF, and assessed ischemic pattern myocardial infarction (MI) and septal NIF.

Results

73 iMR patients were studied; 36% had RV_DYS (EF<50%) on CMR among whom LVEF was lower, PA systolic pressure higher, and MI size larger (all p<0.05). CMR RVEF was paralleled by echo results; correlations were highest for RV-GLS (r = 0.73) and lowest for RV-S’ (r = 0.43; all p<0.001). RV_DYS patients more often had CMR-evidenced NIF (54% vs. 7%; p<0.001). Whereas all RV indices were lower among NIF-affected patients (all p≤0.006), percent change was largest for transverse strain (48.3%). CMR RVEF was independently associated with RV-GLS (partial r = 0.57, p<0.001) and transverse strain (r = 0.38, p = 0.002) (R = 0.78, p<0.001). Overall diagnostic performance of RV-GLS and transverse strain were similar (AUC = 0.93[0.87–0.99]|0.91[0.84–0.99], both p<0.001), and yielded near equivalent sensitivity and specificity (85%|83% and 80%|79% respectively).

Conclusion

Compared to conventional echo indices, RV strain parameters yield stronger correlation with CMR-defined RVEF and potentially constitute better markers of CMR-evidenced NIF in iMR.

Echocardiography-quantified myocardial strain-a marker of global and regional infarct size that stratifies likelihood of left ventricular thrombus

BACKGROUND

Myocardial strain provides a novel means of quantifying subtle alterations in contractile function; incremental utility post-MI is unknown.

OBJECTIVES

To test longitudinal-quantified by postprocessing routine echo-for assessment of MI size measured by cardiac magnetic resonance (CMR) and conventional methods, and assess regional and global strain (GLS) as markers of LV thrombus.

METHODS

The population comprised of patients with anterior ST-segment MI who underwent echo and CMR prospectively. Preexisting echoes were retrieved, re-analyzed for strain, and compared to conventional MI markers as well as CMR-evidenced MI, function, and thrombus.

RESULTS

Seventy-four patients underwent echo and CMR 4 ± 1 weeks post-MI; 72% had abnormal GLS. CMR-quantified MI size was 2.5-fold larger and EF lower among patients with abnormal GLS, paralleling 2.6-3.1 fold differences in Q-wave size and CPK (all P ≤ .002). GLS correlated with CMR-quantified MI (r = .66), CPK (r = .52) and Q-wave area (r = .44; all P ≤ .001): Regional strain was lower in the base, mid, and apical LV among patients with CMR-defined transmural MI in each territory (P < .05) and correlated with cine-CMR regional EF (r = .53-.71; P < .001) and echo wall motion (r = .45-.71; P < .001). GLS and apical strain were ~2-fold lower among patients with LV thrombus (P ≤ .002): Apical strain yielded higher diagnostic performance for thrombus (AUC: 0.83 [0.72-0.93], P = .001) than wall motion (0.73 [0.58-0.88], P = .02), as did global strain (0.78 [0.65-0.90], P = .005) compared to LVEF (0.58 [0.45-0.72], P = .41).

CONCLUSIONS

Echo-quantified longitudinal strain provides a marker of MI size and improves stratification for post-MI LV thrombus beyond conventional indices.

Cine-CMR partial voxel segmentation demonstrates increased aortic stiffness among patients with Marfan syndrome

BACKGROUND

Standard cine-cardiac magnetic resonance (CMR) imaging is commonly used to evaluate cardiac structure, geometry and function. Prior studies have shown that automated segmentation via partial voxel interpolation (PVI) accurately quantifies phantom-based cardiac chamber volumes and necropsy left ventricular myocardial mass. Despite this, the applicability and usefulness of PVI in the determination of physiologic parameters of the aorta such as aortic stiffness has yet to be investigated.

METHODS

Routine CMR was conducted with a 1.5T (GE) scanner with pulse sequences similar to that of standard CMR (parameters: TR 3.4 msec, TE 1.14 msec, flip angle 60°, temporal resolution ~30-40 msec). Views were obtained in standard cardiac-oriented longitudinal or axial views (2, 3 and 4 chambers). Within non-dilated regions of the descending thoracic aorta, aortic area was quantified via a novel PVI automated process (LV-METRIC), which discerns relative amounts of blood pool in each voxel. Aortic stiffness, as calculated from brachial artery pulse pressure and aortic area at maximal and minimal dimensions, was evaluated in 60 total segments (one segment per patient). All segments were in the descending aorta and were not aneurysmal.

RESULTS

Sixty patients in total were studied, including 50 that had genetically-related aortic disorder [35 bicuspid aortic valve (BAV), 15 Marfan syndrome (MFS)]. Ten normal controls without aortic disease were included for comparison purposes. All patients (n=60) had evaluable CMR images for assessment of the descending aorta with use of automated segmentation. Patients with BAV and MFS were similar to controls in age, systolic blood pressure, brachial artery pulse pressure, smoking status or hypercholesterolemia (all P=NS). There were more women (P<0.001), lower body mass index (P=0.008), and greater height (P<0.001) in the MFS cohort compared to BAV and controls. Descending aortic area in either systole (maximal) or diastole (minimal) was similar among all three cohorts. However, change in aortic area (ΔArea) throughout the cardiac cycle was substantially lower in MFS than control subjects (P<0.001). In contrast, change in aortic area throughout the cardiac cycle was not significantly different between BAV vs. controls (P=0.62). Aortic stiffness was increased among MFS patients versus control subjects (P=0.014). When comparing MFS to BAV subjects, a comparable trend was observed (P=0.09). No statistical difference was evident in aortic stiffness in patients with BAV versus control subjects (P=0.29).

CONCLUSIONS

The application of PVI to standard CMR imaging can assess abnormal descending aorta functional indices in normal caliber segments in MFS subjects. Future prospective studies with larger subject populations are warranted to further determine the overall utility of automated aortic segmentation as a possible early biomarker of aortic dysfunction before overt dilatation.

Echocardiographic Linear Dimensions for Assessment of Right Ventricular Chamber Volume as Demonstrated by Cardiac Magnetic Resonance

BACKGROUND

Echocardiography-derived linear dimensions offer straightforward indices of right ventricular (RV) structure but have not been systematically compared with RV volumes on cardiac magnetic resonance (CMR).

METHODS

Echocardiography and CMR were interpreted among patients with coronary artery disease imaged via prospective (90%) and retrospective (10%) registries. For echocardiography, American Society of Echocardiography-recommended RV dimensions were measured in apical four-chamber (basal RV width, mid RV width, and RV length), parasternal long-axis (proximal RV outflow tract [RVOT]), and short-axis (distal RVOT) views. For CMR, RV end-diastolic volume and RV end-systolic volume were quantified using border planimetry.

RESULTS

Two hundred seventy-two patients underwent echocardiography and CMR within a narrow interval (0.4 ± 1.0 days); complete acquisition of all American Society of Echocardiography-recommended dimensions was feasible in 98%. All echocardiographic dimensions differed between patients with and those without RV dilation on CMR (P < .05). Basal RV width (r = 0.70), proximal RVOT width (r = 0.68), and RV length (r = 0.61) yielded the highest correlations with RV end-diastolic volume on CMR; end-systolic dimensions yielded similar correlations (r = 0.68, r = 0.66, and r = 0.65, respectively). In multivariate regression, basal RV width (regression coefficient = 1.96 per mm; 95% CI, 1.22-2.70; P < .001), RV length (regression coefficient = 0.97; 95% CI, 0.56-1.37; P < .001), and proximal RVOT width (regression coefficient = 2.62; 95% CI, 1.79-3.44; P < .001) were independently associated with CMR RV end-diastolic volume (r = 0.80). RV end-systolic volume was similarly associated with echocardiographic dimensions (basal RV width: 1.59 per mm [95% CI, 1.06-2.13], P < .001; RV length: 1.00 [95% CI, 0.66-1.34], P < .001; proximal RVOT width: 1.80 [95% CI, 1.22-2.39], P < .001) (r = 0.79).

CONCLUSIONS

RV linear dimensions provide readily obtainable markers of RV chamber size. Proximal RVOT and basal width are independently associated with CMR volumes, supporting the use of multiple linear dimensions when assessing RV size on echocardiography.

Echocardiographic Algorithm for Post-Myocardial Infarction LV Thrombus: A Gatekeeper for Thrombus Evaluation by Delayed Enhancement CMR

OBJECTIVES

The goal of this study was to determine the prevalence of post-myocardial infarction (MI) left ventricular (LV) thrombus in the current era and to develop an effective algorithm (predicated on echocardiography [echo]) to discern patients warranting further testing for thrombus via delayed enhancement (DE) cardiac magnetic resonance (CMR).

BACKGROUND

LV thrombus affects post-MI management. DE-CMR provides thrombus tissue characterization and is a well-validated but an impractical screening modality for all patients after an MI.

METHODS

A same-day echo and CMR were performed according to a tailored protocol, which entailed uniform echo contrast (irrespective of image quality) and dedicated DE-CMR for thrombus tissue characterization.

RESULTS

A total of 201 patients were studied; 8% had thrombus according to DE-CMR. All thrombi were apically located; 94% of thrombi occurred in the context of a left anterior descending (LAD) infarct-related artery. Although patients with thrombus had more prolonged chest pain and larger MI (p ≤ 0.01), only 18% had aneurysm on echo (cine-CMR 24%). Noncontrast (35%) and contrast (64%) echo yielded limited sensitivity for thrombus on DE-CMR. Thrombus was associated with stepwise increments in basal → apical contractile dysfunction on echo and quantitative cine-CMR; the echo-measured apical wall motion score was higher among patients with thrombus (p < 0.001) and paralleled cine-CMR decrements in apical ejection fraction and peak ejection rates (both p < 0.005). Thrombus-associated decrements in apical contractile dysfunction were significant even among patients with LAD infarction (p < 0.05). The echo-based apical wall motion score improved overall performance (area under the curve 0.89 ± 0.44) for thrombus compared with ejection fraction (area under the curve 0.80 ± 0.61; p = 0.01). Apical wall motion partitions would have enabled all patients with LV thrombus to be appropriately referred for DE-CMR testing (100% sensitivity and negative predictive value), while avoiding further testing in more than one-half (56% to 63%) of patients.

CONCLUSIONS

LV thrombus remains common, especially after LAD MI, and can occur even in the absence of aneurysm. Although DE-CMR yielded improved overall thrombus detection, apical wall motion on a noncontrast echocardiogram can be an effective stratification tool to identify patients in whom DE-CMR thrombus assessment is most warranted. (Diagnostic Utility of Contrast Echocardiography for Detection of LV Thrombi Post ST Elevation Myocardial Infarction; NCT00539045).

Clinical feasibility of a myocardial signal intensity threshold-based semi-automated cardiac magnetic resonance segmentation method

OBJECTIVES

To assess the accuracy and efficiency of a threshold-based, semi-automated cardiac MRI segmentation algorithm in comparison with conventional contour-based segmentation and aortic flow measurements.

METHODS

Short-axis cine images of 148 patients (55 ± 18 years, 81 men) were used to evaluate left ventricular (LV) volumes and mass (LVM) using conventional and threshold-based segmentations. Phase-contrast images were used to independently measure stroke volume (SV). LV parameters were evaluated by two independent readers.

RESULTS

Evaluation times using the conventional and threshold-based methods were 8.4 ± 1.9 and 4.2 ± 1.3 min, respectively (P < 0.0001). LV parameters measured by the conventional and threshold-based methods, respectively, were end-diastolic volume (EDV) 146 ± 59 and 134 ± 53 ml; end-systolic volume (ESV) 64 ± 47 and 59 ± 46 ml; SV 82 ± 29 and 74 ± 28 ml (flow-based 74 ± 30 ml); ejection fraction (EF) 59 ± 16 and 58 ± 17%; and LVM 141 ± 55 and 159 ± 58 g. Significant differences between the conventional and threshold-based methods were observed in EDV, ESV, and LVM mesurements; SV from threshold-based and flow-based measurements were in agreement (P > 0.05) but were significantly different from conventional analysis (P < 0.05). Excellent inter-observer agreement was observed.

CONCLUSIONS

Threshold-based LV segmentation provides improved accuracy and faster assessment compared to conventional contour-based methods.

KEY POINTS

• Threshold-based left ventricular segmentation provides time-efficient assessment of left ventricular parameters • The threshold-based method can discriminate between blood and papillary muscles • This method provides improved accuracy compared to aortic flow measurements as a reference.

Validation and Development of a New Automatic Algorithm for Time-Resolved Segmentation of the Left Ventricle in Magnetic Resonance Imaging

Introduction. Manual delineation of the left ventricle is clinical standard for quantification of cardiovascular magnetic resonance images despite being time consuming and observer dependent. Previous automatic methods generally do not account for one major contributor to stroke volume, the long-axis motion. Therefore, the aim of this study was to develop and validate an automatic algorithm for time-resolved segmentation covering the whole left ventricle, including basal slices affected by long-axis motion. Methods. Ninety subjects imaged with a cine balanced steady state free precession sequence were included in the study (training set n = 40, test set n = 50). Manual delineation was reference standard and second observer analysis was performed in a subset (n = 25). The automatic algorithm uses deformable model with expectation-maximization, followed by automatic removal of papillary muscles and detection of the outflow tract. Results. The mean differences between automatic segmentation and manual delineation were EDV −11 mL, ESV 1 mL, EF −3%, and LVM 4 g in the test set. Conclusions. The automatic LV segmentation algorithm reached accuracy comparable to interobserver for manual delineation, thereby bringing automatic segmentation one step closer to clinical routine. The algorithm and all images with manual delineations are available for benchmarking.

Left ventricle: fully automated segmentation based on spatiotemporal continuity and myocardium information in cine cardiac magnetic resonance imaging (LV-FAST)

CMR quantification of LV chamber volumes typically and manually defines the basal-most LV, which adds processing time and user-dependence. This study developed an LV segmentation method that is fully automated based on the spatiotemporal continuity of the LV (LV-FAST). An iteratively decreasing threshold region growing approach was used first from the midventricle to the apex, until the LV area and shape discontinued, and then from midventricle to the base, until less than 50% of the myocardium circumference was observable. Region growth was constrained by LV spatiotemporal continuity to improve robustness of apical and basal segmentations. The LV-FAST method was compared with manual tracing on cardiac cine MRI data of 45 consecutive patients. Of the 45 patients, LV-FAST and manual selection identified the same apical slices at both ED and ES and the same basal slices at both ED and ES in 38, 38, 38, and 41 cases, respectively, and their measurements agreed within −1.6 ± 8.7 mL, −1.4 ± 7.8 mL, and 1.0 ± 5.8% for EDV, ESV, and EF, respectively. LV-FAST allowed LV volume-time course quantitatively measured within 3 seconds on a standard desktop computer, which is fast and accurate for processing the cine volumetric cardiac MRI data, and enables LV filling course quantification over the cardiac cycle.

Left ventricular geometric remodeling in relation to non-ischemic scar pattern on cardiac magnetic resonance imaging

Left ventricular (LV) remodeling and myocardial fibrosis have been linked to adverse heart failure outcomes. Mid wall late gadolinium enhancement (MW-LGE) on cardiac magnetic resonance (CMR) imaging is well-associated with non-ischemic cardiomyopathy (NICM), but prevalence in ischemic cardiomyopathy (ICM) and association with remodeling are unknown. The population comprised patients with systolic dysfunction [LV ejection fraction (LVEF ≤ 40 %)]. CMR was used to identify MW-LGE, conventionally defined as fibrosis of the mid-myocardial or epicardial aspect of the LV septum. 285 patients were studied. MW-LGE was present in 12 %, and was tenfold more common with NICM (32 %) versus ICM (3 %, p < 0.001). However, owing to higher prevalence of ICM, 15 % of patients with MW-LGE had ICM. LV wall stress was higher (p = 0.02) among patients with, versus those without, MW-LGE despite similar systolic blood pressure (p = 0.24). In multivariate analysis, MW-LGE was associated with CMR-quantified LV end-diastolic volume (p = 0.03) independent of LVEF and mass. Incorporation of clinical and imaging variables demonstrated MW-LGE to be associated with higher LV end-diastolic volume (OR 1.13, CI 1.004-1.27 per 10 ml/m(2), p = 0.04) after controlling for presence of NICM (OR 16.0, CI 5.8-44.1, p < 0.001). While more common in NICM, MW-LGE can occur in ICM and is a marker of LV chamber dilation irrespective of cardiomyopathic etiology.

Q wave area for stratification of global left ventricular infarct size: comparison to conventional ECG assessment using Selvester QRS-score

OBJECTIVES

Left ventricular (LV) infarct size is a prognostic determinant after acute myocardial infarction (AMI). ECG data have been used to measure infarct size, but conventional approaches use multiparametric algorithms that have limited clinical applicability. This study tested a novel ECG approach - based solely on Q wave area - for calculation of LV infarct size.

METHODS

Serial 12-lead ECGs were performed in AMI patients. Computerized software was used to quantify Q wave area (summed across surface ECG leads) and Selvester QRS-score components. ECG analysis was compared to the reference of myocardial infarct size quantified by delayed enhancement cardiac magnetic resonance.

RESULTS

Overall, 158 patients underwent ECG during early (4±0.4) and follow-up (29±5 days) post-AMI time points. Selvester QRS-score and Q wave area increased stepwise with LV infarct size (P<0.001). Whereas both methods manifested marked increases at a threshold of 10% LV infarction, magnitude was greater for Q wave area (>2.5-fold) than Selvester QRS-score (<two-fold). In receiver operating characteristic analysis, Q wave area (area under the curve=0.83-0.86) and Selvester QRS-score (0.82-0.87) manifested similar performance in relation to a 10% infarct cutoff. When Selvester QRS-score and Q wave area thresholds were selected to optimize sensitivity, both methods yielded similar negative predictive value (Q wave area: 89-91%, Selvester QRS-score: 92-94%) although specificity was higher for Q wave area (44-45 vs. 17-25%; P≤0.01).

CONCLUSION

Q wave area provides an index for stratification of LV infarct size that performs similarly to conventional ECG assessment via the Selvester QRS-score for exclusion of large infarction.

CMR reference values for left ventricular volumes, mass, and ejection fraction using computer-aided analysis: the Framingham Heart Study

PURPOSE

To determine sex-specific reference values for left ventricular (LV) volumes, mass, and ejection fraction (EF) in healthy adults using computer-aided analysis and to examine the effect of age on LV parameters.

MATERIALS AND METHODS

We examined data from 1494 members of the Framingham Heart Study Offspring cohort, obtained using short-axis stack cine SSFP CMR, identified a healthy reference group (without cardiovascular disease, hypertension, or LV wall motion abnormality) and determined sex-specific upper 95th percentile thresholds for LV volumes and mass, and lower 5th percentile thresholds for EF using computer-assisted border detection. In secondary analyses, we stratified participants by age-decade and tested for linear trend across age groups.

RESULTS

The reference group comprised 685 adults (423F; 61 ± 9 years). Men had greater LV volumes and mass, before and after indexation to common measures of body size (all P = 0.001). Women had greater EF (73 ± 6 versus 71 ± 6%; P = 0.0002). LV volumes decreased with greater age in both sexes, even after indexation. Indexed LV mass did not vary with age. LV EF and concentricity increased with greater age in both sexes.

CONCLUSION

We present CMR-derived LV reference values. There are significant age and sex differences in LV volumes, EF, and geometry, whereas mass differs between sexes but not age groups.

Longitudinal monitoring of cardiac siderosis using cardiovascular magnetic resonance T2* in patients with thalassemia major on various chelation regimens: a 6-year study

Cardiovascular magnetic resonance (CMR) and hepatic magnetic resonance imaging (MRI) have become reliable noninvasive tools to monitor iron excess in thalassemia major (TM) patients. However, long-term studies are lacking. We reviewed CMR and hepatic MRI T2* imaging on 54 TM patients who had three or more annual measurements. They were managed on various chelation regimens. Patients were grouped according to their degree of cardiac siderosis: severe (T2*, <10 msec), mild to moderate (T2* = 10-20 msec), and no cardiac siderosis (T2*, >20 msec). We looked at the change in cardiac T2*, liver iron concentration (LIC) and left ventricular ejection fraction (LVEF) at years 3 and 5. In patients with severe cardiac siderosis, cardiac T2* (mean ± SD) improved from 6.9 ± 1.6 at baseline to 13.6 ± 10.0 by year 5, mean ΔT2* = 6.7 (P = 0.04). Change in cardiac T2* at year 3 was not significant in the severe group. Patients with mild to moderate cardiac siderosis had mean cardiac T2* of 14.6 ± 2.9 at baseline which improved to 26.3 ± 9.5 by year 3, mean ΔT2* =  1.7 (P = 0.01). At baseline, median LICs (mg/g dry weight) in patients with severe, mild-moderate, and no cardiac siderosis were 3.6, 2.8, and 3.3, whereas LVEFs (mean ± SD) (%) were 56.3 ± 10.1, 60 ± 5, and 66 ± 7.6, respectively. No significant correlation was noted between Δ cardiac T2* and Δ LIC, Δ cardiac T2*, and Δ LVEF at years 3 and 5. Throughout the observation period, patients with no cardiac siderosis maintained their cardiac T2* above 20 msec. The majority of patients with cardiac siderosis improve cardiac T2* over time with optimal chelation.

Left ventricular stroke volume quantification by contrast echocardiography - comparison of linear and flow-based methods to cardiac magnetic resonance

BACKGROUND

Echocardiography (echo)-quantified LV stroke volume (SV) is widely used to assess systolic performance after acute myocardial infarction (AMI). This study compared 2 common echo approaches - predicated on flow (Doppler) and linear chamber dimensions (Teichholz) - to volumetric SV and global infarct parameters quantified by cardiac magnetic resonance (CMR).

METHODS

Multimodality imaging was performed as part of a post-AMI registry. For echo, SV was measured by Doppler and Teichholz methods. Cine-CMR was used for volumetric SV and LVEF quantification, and delayed-enhancement (DE) CMR for infarct size.

RESULTS

Overall, 142 patients underwent same day echo and CMR. On echo, mean SV by Teichholz (78 ± 17 mL) was slightly higher than Doppler (75 ± 16 mL; Δ = 3 ± 13 mL; P = 0.02). Compared to SV on CMR (78 ± 18 mL), mean difference by Teichholz (Δ = -0.2 ± 14; P = 0.89) was slightly smaller than Doppler (Δ = -3 ± 14; P = 0.02), but limits of agreement were similar between CMR and echo methods (Teichholz: -28, 27 mL, Doppler: -31, 24 mL). For Teichholz, differences with CMR SV were greatest among patients with anteroseptal or lateral wall hypokinesis (P < 0.05). For Doppler, differences were associated with aortic valve abnormalities or root dilation (P = 0.01). SV by both echo methods decreased stepwise in relation to global LV injury as assessed by CMR-quantified LVEF and infarct size (P < 0.01).

CONCLUSIONS

Teichholz and Doppler calculated SV yield similar magnitude of agreement with CMR. Teichholz differences with CMR increase with septal or lateral wall contractile dysfunction, whereas Doppler yields increased offsets in patients with aortic remodeling.

Cardiac MR perfusion image processing techniques: a survey

First-pass cardiac MR perfusion (CMRP) imaging has undergone rapid technical advancements in recent years. Although the efficacy of CMRP imaging in the assessment of coronary artery diseases (CAD) has been proven, its clinical use is still limited. This limitation stems, in part, from manual interaction required to quantitatively analyze the large amount of data. This process is tedious, time-consuming, and prone to operator bias. Furthermore, acquisition and patient related image artifacts reduce the accuracy of quantitative perfusion assessment. With the advent of semi- and fully automatic image processing methods, not only the challenges posed by these artifacts have been overcome to a large extent, but a significant reduction has also been achieved in analysis time and operator bias. Despite an extensive literature on such image processing methods, to date, no survey has been performed to discuss this dynamic field. The purpose of this article is to provide an overview of the current state of the field with a categorical study, along with a future perspective on the clinical acceptance of image processing methods in the diagnosis of CAD.

Novel techniques for assessment of left ventricular systolic function

The evaluation of left ventricular systolic function is one of the most common reasons for referral for a non-invasive cardiac imaging study. In addition to its diagnostic and prognostic value, an assessment of ejection fraction can also be used to guide medical and device therapy. Thus, obtaining an accurate and reproducible assessment of LVEF is essential for patient management. This review will focus on novel multi-modality techniques used for the quantification of left ventricular systolic function. Emerging echocardiography techniques such as three-dimensional echocardiography and strain imaging and their incremental role over traditional 2D imaging will be discussed. In addition, new developments expanding nuclear imaging techniques' evaluation of left ventricular systolic function will be reviewed. Finally, an overview of advances in imaging techniques such as cardiac magnetic resonance and cardiac computed tomography, which now allow for an accurate and highly reproducible assessment of LVEF, will be presented.

Improved left ventricular mass quantification with partial voxel interpolation: in vivo and necropsy validation of a novel cardiac MRI segmentation algorithm

BACKGROUND

Cardiac magnetic resonance (CMR) typically quantifies LV mass (LVM) by means of manual planimetry (MP), but this approach is time-consuming and does not account for partial voxel components--myocardium admixed with blood in a single voxel. Automated segmentation (AS) can account for partial voxels, but this has not been used for LVM quantification. This study used automated CMR segmentation to test the influence of partial voxels on quantification of LVM.

METHODS AND RESULTS

LVM was quantified by AS and MP in 126 consecutive patients and 10 laboratory animals undergoing CMR. AS yielded both partial voxel (AS(PV)) and full voxel (AS(FV)) measurements. Methods were independently compared with LVM quantified on echocardiography (echo) and an ex vivo standard of LVM at necropsy. AS quantified LVM in all patients, yielding a 12-fold decrease in processing time versus MP (0:21±0:04 versus 4:18±1:02 minutes; P<0.001). AS(FV) mass (136±35 g) was slightly lower than MP (139±35; Δ=3±9 g, P<0.001). Both methods yielded similar proportions of patients with LV remodeling (P=0.73) and hypertrophy (P=1.00). Regarding partial voxel segmentation, AS(PV) yielded higher LVM (159±38 g) than MP (Δ=20±10 g) and AS(FV) (Δ=23±6 g, both P<0.001), corresponding to relative increases of 14% and 17%. In multivariable analysis, magnitude of difference between AS(PV) and AS(FV) correlated with larger voxel size (partial r=0.37, P<0.001) even after controlling for LV chamber volume (r=0.28, P=0.002) and total LVM (r=0.19, P=0.03). Among patients, AS(PV) yielded better agreement with echo (Δ=20±25 g) than did AS(FV) (Δ=43±24 g) or MP (Δ=40±22 g, both P<0.001). Among laboratory animals, AS(PV) and ex vivo results were similar (Δ=1±3 g, P=0.3), whereas AS(FV) (6±3 g, P<0.001) and MP (4±5 g, P=0.02) yielded small but significant differences with LVM at necropsy.

CONCLUSIONS

Automated segmentation of myocardial partial voxels yields a 14-17% increase in LVM versus full voxel segmentation, with increased differences correlated with lower spatial resolution. Partial voxel segmentation yields improved CMR agreement with echo and necropsy-verified LVM.

Impact of diastolic dysfunction severity on global left ventricular volumetric filling - assessment by automated segmentation of routine cine cardiovascular magnetic resonance

OBJECTIVES

To examine relationships between severity of echocardiography (echo) -evidenced diastolic dysfunction (DD) and volumetric filling by automated processing of routine cine cardiovascular magnetic resonance (CMR).

BACKGROUND

Cine-CMR provides high-resolution assessment of left ventricular (LV) chamber volumes. Automated segmentation (LV-METRIC) yields LV filling curves by segmenting all short-axis images across all temporal phases. This study used cine-CMR to assess filling changes that occur with progressive DD.

METHODS

115 post-MI patients underwent CMR and echo within 1 day. LV-METRIC yielded multiple diastolic indices - E:A ratio, peak filling rate (PFR), time to peak filling rate (TPFR), and diastolic volume recovery (DVR80 - proportion of diastole required to recover 80% stroke volume). Echo was the reference for DD.

RESULTS

LV-METRIC successfully generated LV filling curves in all patients. CMR indices were reproducible (< or = 1% inter-reader differences) and required minimal processing time (175 +/- 34 images/exam, 2:09 +/- 0:51 minutes). CMR E:A ratio decreased with grade 1 and increased with grades 2-3 DD. Diastolic filling intervals, measured by DVR80 or TPFR, prolonged with grade 1 and shortened with grade 3 DD, paralleling echo deceleration time (p < 0.001). PFR by CMR increased with DD grade, similar to E/e' (p < 0.001). Prolonged DVR80 identified 71% of patients with echo-evidenced grade 1 but no patients with grade 3 DD, and stroke-volume adjusted PFR identified 67% with grade 3 but none with grade 1 DD (matched specificity = 83%). The combination of DVR80 and PFR identified 53% of patients with grade 2 DD. Prolonged DVR80 was associated with grade 1 (OR 2.79, CI 1.65-4.05, p = 0.001) with a similar trend for grade 2 (OR 1.35, CI 0.98-1.74, p = 0.06), whereas high PFR was associated with grade 3 (OR 1.14, CI 1.02-1.25, p = 0.02) DD.

CONCLUSIONS

Automated cine-CMR segmentation can discern LV filling changes that occur with increasing severity of echo-evidenced DD. Impaired relaxation is associated with prolonged filling intervals whereas restrictive filling is characterized by increased filling rates.