Regional myocardial strain measurements from 4DCT in patients with normal LV function

Reference ranges of computed tomography-derived strains in four cardiac chambers

Research on cardiovascular diseases using CT-derived strain is gaining momentum, yet there is a paucity of information regarding reference standard values beyond echocardiography, particularly in cardiac chambers other than the left ventricle (LV). We aimed to compile CT-derived strain values from the four cardiac chambers in healthy adults and assess the impact of age and sex on myocardial strains. This study included 101 (mean age: 55.2 ± 9.0 years, 55.4% men) consecutive healthy individuals who underwent multiphase cardiac CT. CT-derived cardiac strains, including LV global and segmental longitudinal, circumferential, and transverse strains, left atrial (LA), right atrial (RA), and right ventricle (RV) strains were measured by the commercially available software. Strain values were classified and compared by their age and sex. The normal range of CT-derived LV global longitudinal strain (GLS), global circumferential strain (GCS), and global radial strain (GRS) were -20.2 ± 2.7%, -27.9 ± 4.1%, and 49.4 ± 12.1%, respectively. For LA, reservoir strain, pump strain, and conduit strain were 28.6 ± 8.5%, 13.2 ± 6.4%, and 15.5 ± 8.6%, respectively. The GLS of RA and RV were 27.9 ± 10.9% and -22.0 ± 5.7%, respectively. The absolute values of GLS of RA and RV of women were higher than that in men (32.4 ± 11.4 vs. 24.3 ± 9.1 and -25.2 ± 4.7 vs. -19.4 ± 5.0, respectively; p<0.001, both). Measurement of CT-derived strain in four cardiac chambers is feasible. The reference ranges of CT strains in four cardiac chambers can be used for future studies of various cardiac diseases using the cardiac strains.

Successful Cardiac Resynchronization Therapy Reduces Negative Septal Work in Patient-Specific Models of Dyssynchronous Heart Failure

In patients with dyssynchronous heart failure (DHF), cardiac conduction abnormalities cause the regional distribution of myocardial work to be non-homogeneous. Cardiac resynchronization therapy (CRT) using an implantable, programmed biventricular pacemaker/defibrillator, can improve the synchrony of contraction between the right and left ventricles in DHF, resulting in reduced morbidity and mortality and increased quality of life. Since regional work depends on wall stress, which cannot be measured in patients, we used computational methods to investigate regional work distributions and their changes after CRT. We used three-dimensional multi-scale patient-specific computational models parameterized by anatomic, functional, hemodynamic, and electrophysiological measurements in eight patients with heart failure and left bundle branch block (LBBB) who received CRT. To increase clinical translatability, we also explored whether streamlined computational methods provide accurate estimates of regional myocardial work. We found that CRT increased global myocardial work efficiency with significant improvements in non-responders. Reverse ventricular remodeling after CRT was greatest in patients with the highest heterogeneity of regional work at baseline, however the efficacy of CRT was not related to the decrease in overall work heterogeneity or to the reduction in late-activated regions of high myocardial work. Rather, decreases in early-activated regions of myocardium performing negative myocardial work following CRT best explained patient variations in reverse remodeling. These findings were also observed when regional myocardial work was estimated using ventricular pressure as a surrogate for myocardial stress and changes in endocardial surface area as a surrogate for strain. These new findings suggest that CRT promotes reverse ventricular remodeling in human dyssynchronous heart failure by increasing regional myocardial work in early-activated regions of the ventricles, where dyssynchrony is specifically associated with hypoperfusion, late systolic stretch, and altered metabolic activity and that measurement of these changes can be performed using streamlined approaches.

A three-dimensional left atrial motion estimation from retrospective gated computed tomography: application in heart failure patients with atrial fibrillation

Background

A reduced left atrial (LA) strain correlates with the presence of atrial fibrillation (AF). Conventional atrial strain analysis uses two-dimensional (2D) imaging, which is, however, limited by atrial foreshortening and an underestimation of through-plane motion. Retrospective gated computed tomography (RGCT) produces high-fidelity three-dimensional (3D) images of the cardiac anatomy throughout the cardiac cycle that can be used for estimating 3D mechanics. Its feasibility for LA strain measurement, however, is understudied.

Aim

The aim of this study is to develop and apply a novel workflow to estimate 3D LA motion and calculate the strain from RGCT imaging. The utility of global and regional strains to separate heart failure in patients with reduced ejection fraction (HFrEF) with and without AF is investigated.

Methods

A cohort of 30 HFrEF patients with (n = 9) and without (n = 21) AF underwent RGCT prior to cardiac resynchronisation therapy. The temporal sparse free form deformation image registration method was optimised for LA feature tracking in RGCT images and used to estimate 3D LA endocardial motion. The area and fibre reservoir strains were calculated over the LA body. Universal atrial coordinates and a human atrial fibre atlas enabled the regional strain calculation and the fibre strain calculation along the local myofibre orientation, respectively.

Results

It was found that global reservoir strains were significantly reduced in the HFrEF + AF group patients compared with the HFrEF-only group patients (area strain: 11.2 ± 4.8% vs. 25.3 ± 12.6%, P = 0.001; fibre strain: 4.5 ± 2.0% vs. 15.2 ± 8.8%, P = 0.001), with HFrEF + AF patients having a greater regional reservoir strain dyssynchrony. All regional reservoir strains were reduced in the HFrEF + AF patient group, in whom the inferior wall strains exhibited the most significant differences. The global reservoir fibre strain and LA volume + posterior wall reservoir fibre strain exceeded LA volume alone and 2D global longitudinal strain (GLS) for AF classification (area-under-the-curve: global reservoir fibre strain: 0.94 ± 0.02, LA volume + posterior wall reservoir fibre strain: 0.95 ± 0.02, LA volume: 0.89 ± 0.03, 2D GLS: 0.90 ± 0.03).

Conclusion

RGCT enables 3D LA motion estimation and strain calculation that outperforms 2D strain metrics and LA enlargement for AF classification. Differences in regional LA strain could reflect regional myocardial properties such as atrial fibrosis burden.

Motion correction of wide-detector 4DCT images for cardiac resynchronization therapy planning

BACKGROUND

Lead placement at the latest mechanically activated left ventricle (LV) segments is strongly correlated with response to cardiac resynchronization therapy (CRT). We demonstrate the feasibility of a cardiac 4DCT motion correction algorithm (ResyncCT) in estimating LV mechanical activation for guiding lead placement in CRT.

METHODS

Subjects with full cardiac cycle 4DCT images acquired using a wide-detector CT scanner for CRT planning/upgrade were included. 4DCT images exhibited motion artifact-induced false-dyssynchrony, hindering LV mechanical activation time estimation. Motion-corrupted images were processed with ResyncCT to yield motion-corrected images. Time to onset of shortening (TOS) was estimated in each of 72 endocardial segments. A false-dyssynchrony index (FDI) was used to quantify the extent of motion artifacts in the uncorrected and the ResyncCT images. After motion correction, the change in classification of LV free-wall segments as optimal target sites for lead placement was investigated.

RESULTS

Twenty subjects (70.7 ​± ​13.9 years, 6 female) were analyzed. Motion artifacts in the ResyncCT-processed images were significantly reduced (FDI: 28.9 ​± ​9.3 ​% vs 47.0 ​± ​6.0 ​%, p ​< ​0.001). In 10 (50 ​%) subjects, ResyncCT motion correction yielded statistically different TOS estimates (p ​< ​0.05). Additionally, 43 ​% of LV free-wall segments were reclassified as optimal target sites for lead placement after motion correction.

CONCLUSIONS

ResyncCT significantly reduced motion artifacts in wide-detector cardiac 4DCT images, yielded statistically different time to onset of shortening estimates, and changed the location of optimal target sites for lead placement. These results highlight the potential utility of ResyncCT motion correction in CRT planning when using wide-detector 4DCT imaging.

Myocardial Regional Shortening from 4D Cardiac CT Angiography for the Detection of Left Ventricular Segmental Wall Motion Abnormality

Purpose

To investigate whether endocardial regional shortening computed from four-dimensional (4D) CT angiography (RSCT) can be used as a decision classifier to detect the presence of left ventricular (LV) wall motion abnormalities (WMAs).

Materials and Methods

One hundred electrocardiographically gated cardiac 4D CT studies (mean age, 59 years ± 14 [SD]; 61 male patients) conducted between April 2018 and December 2020 were retrospectively evaluated. Three experts labeled LV wall motion in each of the 16 American Heart Association (AHA) segments as normal or abnormal; they also measured peak RSCT across one heartbeat in each segment. The data set was split evenly into training and validation groups. During training, interchangeability of RSCT thresholding with experts to detect WMA was assessed using the individual equivalence index (γ), and an optimal threshold of the peak RSCT (RSCT*) that achieved maximum agreement was identified. RSCT* was then validated using the validation group, and the effect of AHA segment-specific thresholds was evaluated. Agreement was assessed using κ statistics.

Results

The optimal threshold, RSCT* of -0.19, when applied to all AHA segments, led to high agreement (agreement rate = 92.17%, κ = 0.82) and interchangeability with experts (γ = -2.58%). The same RSCT* also achieved high agreement in the validation group (agreement rate = 90.29%, κ = 0.76, γ = -0.38%). The use of AHA segment-specific thresholds (range: 0.16 to -0.23 across AHA segments) slightly improved agreement (1.79% increase).

Conclusion

RSCT thresholding was interchangeable with expert visual analysis in detecting segmental WMA from 4D CT and may be used as an objective decision classifier.Keywords: CT, Left Ventricle, Regional Endocardial Shortening, Wall Motion Abnormality Supplemental material is available for this article. © RSNA, 2023.

Regional left ventricular endocardial strains estimated from low-dose 4DCT: Comparison with cardiac magnetic resonance feature tracking

BACKGROUND

Estimates of regional left ventricular (LV) strains provide additional information to global function parameters such as ejection fraction (EF) and global longitudinal strain (GLS) and are more sensitive in detecting abnormal regional cardiac function. The accurate and reproducible assessment of regional cardiac function has implications in the management of various cardiac diseases such as heart failure, myocardial ischemia, and dyssynchrony.

PURPOSE

To develop a method that yields highly reproducible, high-resolution estimates of regional endocardial strains from 4DCT images.

METHODS

A method for estimating regional LV endocardial circumferential( ε c c ) $( {{\epsilon }_{cc}} )$ and longitudinal (ε l l ${\epsilon }_{ll}$ ) strains from 4DCT was developed. Point clouds representing the LV endocardial surface were extracted for each time frame of the cardiac cycle from 4DCT images. 3D deformation fields across the cardiac cycle were obtained by registering the end diastolic point cloud to each subsequent point cloud in time across the cardiac cycle using a 3D point-set registration technique. From these deformation fields,ε c c and ε l l ${\epsilon }_{cc}\ {\rm{and\ }}{\epsilon }_{ll}$ were estimated over the entire LV endocardial surface by fitting an affine transformation with maximum likelihood estimation. The 4DCT-derived strains were compared with strains estimated in the same subjects by cardiac magnetic resonance (CMR); twenty-four subjects had CMR scans followed by 4DCT scans acquired within a few hours. Regional LV circumferential and longitudinal strains were estimated from the CMR images using a commercially available feature tracking software (cvi42). Global circumferential strain (GCS) and global longitudinal strain (GLS) were calculated as the mean of the regional strains across the entire LV for both modalities. Pearson correlation coefficients and Bland-Altman analyses were used for comparisons. Intraclass correlation coefficients (ICC) were used to assess the inter- and intraobserver reproducibility of the 4DCT-derived strains.

RESULTS

The 4DCT-derived regional strains correlated well with the CMR-derived regional strains (ε c c ${\epsilon }_{cc}$ : r = 0.76, p < 0.001;ε l l ${\epsilon }_{ll}$ : r = 0.64, p < 0.001). A very strong correlation was found between 4DCT-derived GCS and 4DCT-derived EF (r = -0.96; p < 0.001). The 4DCT-derived strains were also highly reproducible, with very low inter- and intraobserver variability (intraclass correlation coefficients in the range of [0.92, 0.99]).

CONCLUSIONS

We have developed a novel method to estimate high-resolution regional LV endocardial circumferential and longitudinal strains from 4DCT images. Except for the definition of the mitral valve and LV outflow tract planes, the method is completely user independent, thus yielding highly reproducible estimates of endocardial strain. The 4DCT-derived strains correlated well with those estimated using a commercial CMR feature tracking software. The promising results reported in this study highlight the potential utility of 4DCT in the precise assessment of regional cardiac function for the management of cardiac disease.

Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning

Background

The presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion abnormalities (WMA) from dynamic volume renderings (VR) of clinical 4D computed tomography (CT) angiograms using a deep learning (DL) framework.

Methods

Three hundred forty-three ECG-gated cardiac 4DCT studies (age: 61 ± 15, 60.1% male) were retrospectively evaluated. Volume-rendering videos of the LV blood pool were generated from 6 different perspectives (i.e., six views corresponding to every 60-degree rotation around the LV long axis); resulting in 2058 unique videos. Ground-truth WMA classification for each video was performed by evaluating the extent of impaired regional shortening visible (measured in the original 4DCT data). DL classification of each video for the presence of WMA was performed by first extracting image features frame-by-frame using a pre-trained Inception network and then evaluating the set of features using a long short-term memory network. Data were split into 60% for 5-fold cross-validation and 40% for testing.

Results

Volume rendering videos represent ~800-fold data compression of the 4DCT volumes. Per-video DL classification performance was high for both cross-validation (accuracy = 93.1%, sensitivity = 90.0% and specificity = 95.1%, κ: 0.86) and testing (90.9, 90.2, and 91.4% respectively, κ: 0.81). Per-study performance was also high (cross-validation: 93.7, 93.5, 93.8%, κ: 0.87; testing: 93.5, 91.9, 94.7%, κ: 0.87). By re-binning per-video results into the 6 regional views of the LV we showed DL was accurate (mean accuracy = 93.1 and 90.9% for cross-validation and testing cohort, respectively) for every region. DL classification strongly agreed (accuracy = 91.0%, κ: 0.81) with expert visual assessment.

Conclusions

Dynamic volume rendering of the LV blood pool combined with DL classification can accurately detect regional WMA from cardiac CT.

Right Ventricular and Pulmonary Computed Tomography Assessments in Paradoxical Low-Flow Low-Gradient Aortic Stenosis Undergoing Transcatheter Aortic Valve Replacement

Background

Patients with paradoxical low-flow low-gradient aortic stenosis (pLFLG-AS) have high mortality and high degree of TAVR futility. Computed tomography (CT) enables accurate simultaneous right ventricular (RV) and parenchymal lung disease evaluation which may provide useful objective markers of AS severity, concomitant pulmonary comorbidities, and transcatheter aortic valve replacement (TAVR) improvement. However, the prevalence of RV dysfunction and its association with pulmonary disease in pLFLG-AS is unknown. The study objective was to test the hypothesis that pLFLG-AS patients undergoing TAVR have decreased RV function without significant parenchymal lung disease.

Methods

Between August 2016 and March 2020, 194 consecutive AS patients completed high-resolution computed tomography (CT) imaging for TAVR evaluation. Subjects were stratified based on echocardiographic criteria as the study group, pLFLG (n=27), and two consecutive control groups: classic severe, normal-flow, high-gradient (n=27) and normal-flow, low-gradient (NFLG) (n=27) AS. Blinded biventricular function and lung parenchymal disease assessments were obtained by high-resolution CT imaging.

Results

Patient demographics were similar between groups. pLFLG-AS had lower RV ejection fraction (49±10%) compared to both classic severe (58±7%, p<0.001) and NFLG AS (55±65%, p=0.02). There were no significant differences on lung emphysema (p=0.19), air fraction (p=0.58), and pulmonary disease presence (p=0.94) and severity (p=0.67) between groups.

Conclusion

pLFLG-AS patients have lower RV ejection fraction, than classic severe and normal-flow low-gradient AS patients in the absence of significant parenchymal lung disease on CT imaging. These findings support the direct importance of RV function in the pathophysiology of aortic valve disease.

Octree Representation Improves Data Fidelity of Cardiac CT Images and Convolutional Neural Network Semantic Segmentation of Left Atrial and Ventricular Chambers

PURPOSE

To assess whether octree representation and octree-based convolutional neural networks (CNNs) improve segmentation accuracy of three-dimensional images.

MATERIALS AND METHODS

Cardiac CT angiographic examinations from 100 patients (mean age, 67 years ± 17 [standard deviation]; 60 men) performed between June 2012 and June 2018 with semantic segmentations of the left ventricular (LV) and left atrial (LA) blood pools at the end-diastolic and end-systolic cardiac phases were retrospectively evaluated. Image quality (root mean square error [RMSE]) and segmentation fidelity (global Dice and border Dice coefficients) metrics of the octree representation were compared with spatial downsampling for a range of memory footprints. Fivefold cross-validation was used to train an octree-based CNN and CNNs with spatial downsampling at four levels of image compression or spatial downsampling. The semantic segmentation performance of octree-based CNN (OctNet) was compared with the performance of U-Nets with spatial downsampling.

RESULTS

Octrees provided high image and segmentation fidelity (median RMSE, 1.34 HU; LV Dice coefficient, 0.970; LV border Dice coefficient, 0.843) with a reduced memory footprint (87.5% reduction). Spatial downsampling to the same memory footprint had lower data fidelity (median RMSE, 12.96 HU; LV Dice coefficient, 0.852; LV border Dice coefficient, 0.310). OctNet segmentation improved the border segmentation Dice coefficient (LV, 0.612; LA, 0.636) compared with the highest performance among U-Nets with spatial downsampling (Dice coefficients: LV, 0.579; LA, 0.592).

CONCLUSION

Octree-based representations can reduce the memory footprint and improve segmentation border accuracy.Keywords CT, Cardiac, Segmentation, Supervised Learning, Convolutional Neural Network (CNN), Deep Learning Algorithms, Machine Learning Algorithms© RSNA, 2021.

The Potential Role of Cardiac CT in the Evaluation of Patients With Known or Suspected Cardiomyopathy: From Traditional Indications to Novel Clinical Applications

After 15 years from its advent in the clinical field, coronary computed tomography (CCTA) is now widely considered as the best first-step test in patients with low-to-moderate pre-test probability of coronary artery disease. Technological innovation was of pivotal importance for the extensive clinical and scientific interest in CCTA. Recently, the advent of last generation wide-coverage CT scans paved the way for new clinical applications of this technique beyond coronary arteries anatomy evaluation. More precisely, both biventricular volume and systolic function quantification and myocardial fibrosis identification appeared to be feasible with last generation CT. In the present review we would focus on potential applications of cardiac computed tomography (CCT), beyond CCTA, for a comprehensive assessment patients with newly diagnosed cardiomyopathy, from technical requirements to novel clinical applications.

Novel 4DCT Method to Measure Regional Left Ventricular Endocardial Shortening Before and After Transcatheter Mitral Valve Implantation

BACKGROUND

Regional left ventricular (LV) mechanics in mitral regurgitation (MR) patients, and local changes in function after transcatheter mitral valve implantation (TMVI) have yet to be evaluated. Herein, we introduce a method for creating high resolution maps of endocardial function from 4DCT images, leading to detailed characterization of changes in local LV function. These changes are particularly interesting when evaluating the effect of the Tendyne™ TMVI device in the region of the epicardial pad.

METHODS

Regional endocardial shortening from CT (RSCT) was evaluated in Tendyne (Abbott Medical) TMVI patients with 4DCT exams pre- and post-implantation. Regional function was evaluated in 90 LV segments (5 longitudinal × 18 circumferential). LV volumes and ejection fraction (EF) were also computed. A reproducibility study was performed in a subset of patients to determine the precision of RSCT measurements in this population.

RESULTS

Baseline and local changes in RSCT post TMVI were highly variable and extremely spatially heterogeneous. Both inter- and intra-observer variability were low and demonstrated the high precision of RSCT for evaluating regional LV function.

CONCLUSION

RSCT is a reproducible metric which can be evaluated in patients with highly abnormal regional LV function and geometry. After TMVI, significant spatially heterogeneous changes in RSCT were observed in all subjects; therefore, it is unlikely that the functional state of TMVI patients can be fully described by changes in LV volume or EF. Measurement of RSCT provides precise characterization of the spatially heterogeneous effects of MR and TMVI on LV function and remodeling.

Automated cardiac volume assessment and cardiac long- and short-axis imaging plane prediction from electrocardiogram-gated computed tomography volumes enabled by deep learning

AIMS

To develop an automated method for bloodpool segmentation and imaging plane re-slicing of cardiac computed tomography (CT) via deep learning (DL) for clinical use in coronary artery disease (CAD) wall motion assessment and reproducible longitudinal imaging.

METHODS AND RESULTS

One hundred patients who underwent clinically indicated cardiac CT scans with manually segmented left ventricle (LV) and left atrial (LA) chambers were used for training. For each patient, long-axis (LAX) and short-axis planes were manually defined by an imaging expert. A DL model was trained to predict bloodpool segmentations and imaging planes. Deep learning bloodpool segmentations showed close agreement with manual LV [median Dice: 0.91, Hausdorff distance (HD): 6.18 mm] and LA (Dice: 0.93, HD: 7.35 mm) segmentations and a strong correlation with manual ejection fraction (Pearson r: 0.95 LV, 0.92 LA). Predicted planes had low median location (6.96 mm) and angular orientation (7.96 ° ) errors which were comparable to inter-reader differences (P > 0.71). 84-97% of DL-prescribed LAX planes correctly intersected American Heart Association segments, which was comparable (P > 0.05) to manual slicing. In a test cohort of 144 patients, we evaluated the ability of the DL approach to provide diagnostic imaging planes. Visual scoring by two blinded experts determined ≥94% of DL-predicted planes to be diagnostically adequate. Further, DL-enabled visualization of LV wall motion abnormalities due to CAD and provided reproducible planes upon repeat imaging.

CONCLUSION

A volumetric, DL approach provides multiple chamber segmentations and can re-slice the imaging volume along standardized cardiac imaging planes for reproducible wall motion abnormality and functional assessment.

Hyperparameter optimisation and validation of registration algorithms for measuring regional ventricular deformation using retrospective gated computed tomography images

Recent dose reduction techniques have made retrospective computed tomography (CT) scans more applicable and extracting myocardial function from cardiac computed tomography (CCT) images feasible. However, hyperparameters of generic image intensity-based registration techniques, which are used for tracking motion, have not been systematically optimised for this modality. There is limited work on their validation for measuring regional strains from retrospective gated CCT images and open-source software for motion analysis is not widely available. We calculated strain using our open-source platform by applying an image registration warping field to a triangulated mesh of the left ventricular endocardium. We optimised hyperparameters of two registration methods to track the wall motion. Both methods required a single semi-automated segmentation of the left ventricle cavity at end-diastolic phase. The motion was characterised by the circumferential and longitudinal strains, as well as local area change throughout the cardiac cycle from a dataset of 24 patients. The derived motion was validated against manually annotated anatomical landmarks and the calculation of strains were verified using idealised problems. Optimising hyperparameters of registration methods allowed tracking of anatomical measurements with a mean error of 6.63% across frames, landmarks, and patients, comparable to an intra-observer error of 7.98%. Both registration methods differentiated between normal and dyssynchronous contraction patterns based on circumferential strain (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p_1=0.0065$$\end{document}p1=0.0065, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p_2=0.0011$$\end{document}p2=0.0011). To test whether a typical 10 temporal frames sampling of retrospective gated CCT datasets affects measuring cardiac mechanics, we compared motion tracking results from 10 and 20 frames datasets and found a maximum error of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$8.51\pm 0.8\%$$\end{document}8.51±0.8%. Our findings show that intensity-based registration techniques with optimal hyperparameters are able to accurately measure regional strains from CCT in a very short amount of time. Furthermore, sufficient sensitivity can be achieved to identify heart failure patients and left ventricle mechanics can be quantified with 10 reconstructed temporal frames. Our open-source platform will support increased use of CCT for quantifying cardiac mechanics.

Quantitative analysis of three-dimensional left ventricular global strain using coronary computed tomography angiography in patients with heart failure: Comparison with 3T cardiac MR

PURPOSE

The objective of this study was to investigate whether three dimentional (3D)- Coronary CT angiography (CCTA)- feature tracking (FT) can measure global myocardial strain of the left ventricle (LV) in patients with heart failure using cardiac MR (CMR) as reference.

METHODS

Consecutive patients (n = 44) with variable degrees of heart failure who underwent an ECG-gated CCTA and CMR within 24 h were included. Both modalities were compared for 2D/3D LV global radial strain (2D/3D-GRS), circumferential strain (2D/3D-GCS), longitudinal strain (2D/3D-GLS) and conventional functional parameters.

RESULTS

Compared to CMR, CCTA-derived 3D-GLS and LVEF showed no significant difference (p > 0.05). Bland-Altman plots showed a small bias (0.3 %) between CCTA-derived 3D-GLS and CMR 3D-GLS. Close correlations were observed between the two modalities regarding LV global strain (3D-GRS, r = 0.89; 3D-GCS, r = 0.86; 3D-GLS, r = 0.79, respectively, p < 0.001 for all). However, CCTA-derived 3D-GRS and 3D-GCS were statistically different compared with CMR. CCTA-derived 3D-GLS had an inverse correlation with CCTA-LVEF(r=-0.75, p < 0.05). Intraobserver agreements for CCTA-derived 3D-global strain were good (ICC = 0.856 for 3D-GLS, ICC = 0.741 for 3D-GCS and ICC = 0.762 for 3D-GRS). 2D global strain showed statistical differences between the two modalities (p＜0.05 for all), but close correlations were observed regarding 2D LV global strain (2D-GRS, r = 0.80; 2D-GCS, r = 0.81; 2D-GLS, r = 0.81, respectively, p < 0.001 for all). The average radiation dose-long-product (DLP) of CCTA was 387.86 ± 89.3 mGy*cm.

CONCLUSION

CCTA-derived 3D-GLS can provide both reliable and interchangeable results for quantitative assessment of myocardial mechanical changes in HF patients compared to CMR with good intra-observer agreement.

Automatic estimation of aortic and mitral valve displacements in dynamic CTA with 4D graph-cuts

The location of the mitral and aortic valves in dynamic cardiac imaging is useful for extracting functional derived parameters such as ejection fraction, valve excursions, and global longitudinal strain, and when performing anatomical structures tracking using slice following or valve intervention's planning. Completely automatic segmentation methods are still challenging tasks because of their fast movements and the different positions that prevent good visibility of the leaflets along the full cardiac cycle. In this article, we propose a processing pipeline to track the displacement of the aortic and mitral valve annuli from high-resolution cardiac four-dimensional computed tomographic angiography (4D-CTA). The proposed method is based on the dynamic separation of left ventricle, left atrium and aorta using statistical shape modeling and an energy minimization algorithm based on graph-cuts and has been evaluated on a set of 15 electrocardiography-gated 4D-CTAs. We report a mean agreement distance between manual annotations and our proposed method of 2.52±1.06 mm for the mitral annulus and 2.00±0.69 mm for the aortic valve annulus based on valve locations detected from manual anatomical landmarks. In addition, we show the effect of detecting the valvular planes on derived functional parameters (ejection fraction, global longitudinal strain, and excursions of the mitral and aortic valves).

Characteristics of the left ventricular three-dimensional maximum principal strain using cardiac computed tomography: reference values from subjects with normal cardiac function

OBJECTIVES

This study evaluated the characteristics of left ventricular maximum principal strain (LV-MPS) using cardiac CT in subjects with normal LV function.

METHODS

Of 973 subjects who underwent retrospective electrocardiogram-gated cardiac CT using a third-generation dual-source CT without beta-blocker administration, 31 subjects with preserved LV ejection fraction ≥ 55% assessed by echocardiography without coronary artery stenosis and cardiac pathology were retrospectively identified. CT images were reconstructed every 5% (0-95%) of the RR interval. LV-MPS and the time to peak (TTP) were analyzed using the 16-segment model and compared among three levels (base, mid, and apex) and among four regions (anterior, septum, inferior, and lateral) using the Steel-Dwass test. The intra- and inter-observer reproducibilities for LV-MPS were calculated using intraclass correlation coefficients (ICCs).

RESULTS

The intra- and inter-observer ICCs (95% confidence interval) for peak LV-MPS were 0.96 (0.94-0.97) and 0.94 (0.92-0.96), respectively. The global peak LV-MPS (median, inter-quantile range) was 0.59 (0.55-0.72). The regional LV-MPS significantly increased in the order of the basal (0.54, 0.49-0.59), mid-LV (0.57, 0.53-0.65), and apex (0.68, 0.60-0.84) (p < 0.05, in each), and was significantly higher in the lateral wall (0.66, 0.60-0.77), while that in the septal region (0.47, 0.44-0.54) was the lowest among the four LV regions (all p < 0.05). No significant difference in TTP was seen among the myocardial levels and regions.

CONCLUSION

CT-derived LV-MPS is reproducible and quantitatively represents synchronized myocardial contraction with heterogeneous values in subjects with normal LV function.

KEY POINTS

• CT-derived left ventricular maximum principal strain analysis allows highly reproducible quantitative assessments of left ventricular myocardial contraction. • In subjects with normal cardiac function, the peak value of CT-derived left ventricular maximum principal strain is the highest in the apical level and in the lateral wall and the lowest in the septum. • The regional peak left ventricular maximum principal strain shows intra-ventricular heterogeneity on a per-patient basis, but myocardial contraction is globally synchronized in subjects with normal cardiac function seen on cardiac CT.

Anthropomorphic left ventricular mesh phantom: a framework to investigate the accuracy of SQUEEZ using Coherent Point Drift for the detection of regional wall motion abnormalities

We present an anthropomorphically accurate left ventricular (LV) phantom derived from human computed tomography (CT) data to serve as the ground truth for the optimization and the spatial resolution quantification of a CT-derived regional strain metric (SQUEEZ) for the detection of regional wall motion abnormalities. Displacements were applied to the mesh points of a clinically derived end-diastolic LV mesh to create analytical end-systolic poses with physiologically accurate endocardial strains. Normal function and regional dysfunction of four sizes [1, 2/3, 1/2, and 1/3 American Heart Association (AHA) segments as core diameter], each exhibiting hypokinesia (70% reduction in strain) and subtle hypokinesia (40% reduction in strain), were simulated. Regional shortening (RS CT ) estimates were obtained by registering the end-diastolic mesh to each simulated end-systolic mesh condition using a nonrigid registration algorithm. Ground-truth models of normal function and of hypokinesia were used to identify the optimal parameters in the registration algorithm and to measure the accuracy of detecting regional dysfunction of varying sizes and severities. For normal LV function,RS CT values in all 16 AHA segments were accurate to within ± 5 % . For cases with regional dysfunction, the errors inRS CT around the dysfunctional region increased with decreasing size of dysfunctional tissue.