Search Results (11)

Background: To validate the automated quantification of cardiac chamber volumes and myocardial mass on non-contrast chest CT using cardiac MR (CMR) as a reference. Methods: We retrospectively included 53 consecutive patients who received non-contrast chest CT and CMR within three weeks. A deep learning model created cardiac segmentations on axial soft-tissue reconstructions from CT, covering all four cardiac chambers and the left ventricular myocardium. Segmentations on CMR cine short-axis and long-axis images served as a reference. Standard estimates of diagnostic accuracy were calculated for ventricular volumes at end-diastole and end-systole (LVEDV, LVESV, RVEDV, RVESV), left ventricular mass (LVM), and atrial volumes (LA, RA) at ventricular end-diastole. A qualitative assessment noted segmentation issues. Results: The deep learning model generated CT measurements for 52 of the 53 patients (98%). Based on CMR measurements, the average LVEDV was 166 ± 64 mL, RVEDV was 144 ± 51 mL, and LVM was 115 ± 39 g. The CT measurements correlated well with CMR measurements for LVEDV, LVESV, and LVM (ICC = 0.85, ICC = 0.84, and ICC = 0.91; all p < 0.001) and RVEDV and RVESV (ICC = 0.79 and ICC= 0.78; both p < 0.001), and moderately well with LA and RA (ICC = 0.74 and ICC = 0.61; both p < 0.001). Absolute agreements likewise favored LVEDV, LVM, and RVEDV. ECG-gating did not relevantly influence the results. The CT results correctly identified 7/15 LV and 1/1 RV as dilated (one and six false positives, respectively). Major qualitative issues were found in three cases (6%). Conclusions: Automated cardiac chamber volume and myocardial mass quantification on non-contrast chest CT produced viable measurements in this retrospective sample. Relevance Statement: An automated cardiac assessment on non-contrast chest CT provides quantitative morphological data on the heart, enabling a preliminary organ evaluation that aids in incidentally identifying at-risk patients who may benefit from a more targeted diagnostic workup. Full article

Background and Objectives: Left atrial (LA) remodelling and dilatation predicts atrial fibrillation (AF) recurrences after catheter ablation. However, whether right atrial (RA) remodelling and dilatation predicts AF recurrences after ablation has not been fully evaluated. Materials and Methods: This is an observational study of 85 consecutive patients (aged 57 ± 9 years; 70 [82%] men) who underwent cardiac magnetic resonance before first catheter ablation for AF (40 [47.1%] persistent AF). Four-chamber cine-sequence was selected to measure LA and RA area, and ventricular end-systolic image phase to obtain atrial 3D volumes. The effect of different variables on event-free survival was investigated using the Cox proportional hazards model. Results: In patients with persistent AF, combined LA and RA area indexed to body surface area (AILA + RA) predicted AF recurrences (HR = 1.08, 95% CI 1.00–1.17, p = 0.048). An AILA + RA cut-off value of 26.7 cm²/m² had 72% sensitivity and 73% specificity for predicting recurrences in patients with persistent AF. In this group, 65% of patients with AILA + RA > 26.7 cm²/m² experienced AF recurrence within 2 years of follow-up (median follow-up 11 months), compared to 25% of patients with AILA + RA ≤ 26.7 cm²/m² (HR 4.28, 95% CI 1.50–12.22; p = 0.007). Indices of LA and RA dilatation did not predict AF recurrences in patients with paroxysmal AF. Atrial 3D volumes did not predict AF recurrences after ablation. Conclusions: In this pilot study, the simple measurement of AILA + RA may predict recurrences after ablation of persistent AF, and may outperform measurements of atrial volumes. In paroxysmal AF, atrial dilatation did not predict recurrences. Further studies on the role of RA and LA remodelling are needed. Full article

Automated Cardiac Magnetic Resonance segmentation serves as a crucial tool for the evaluation of cardiac function, facilitating faster clinical assessments that prove advantageous for both practitioners and patients alike. Recent studies have predominantly concentrated on delineating structures on short-axis orientation, placing less emphasis on long-axis representations due to the intricate nature of structures in the latter. Taking these consideration into account, we present a robust hierarchy-based augmentation strategy coupled with the compact and fast Efficient-Net (ENet) architecture for the automated segmentation of two-chamber and four-chamber Cine-MRI images. We observed an average Dice improvement of 0.99% on the two-chamber images and of 2.15% on the four-chamber images, and an average Hausdorff distance improvement of 21.3% on the two-chamber images and of 29.6% on the four-chamber images. The practical viability of our approach was validated by computing clinical metrics such as the Left Ventricular Ejection Fraction (LVEF) and left ventricular volume (LVC). We observed acceptable biases, with a +2.81% deviation on the LVEF for the two-chamber images and a +0.11% deviation for the four-chamber images. Full article

This study aimed to evaluate cardiac function in a young mouse model of Duchenne muscular dystrophy (mdx) using cardiac magnetic resonance imaging (MRI) with feature tracking and self-gated magnetic resonance cine imaging. Cardiac function was evaluated in mdx and control mice (C57BL/6JJmsSlc mice) at 8 and 12 weeks of age. Preclinical 7-T MRI was used to capture short-axis, longitudinal two-chamber view and longitudinal four-chamber view cine images of mdx and control mice. Strain values were measured and evaluated from cine images acquired using the feature tracking method. The left ventricular ejection fraction was significantly less (p < 0.01 each) in the mdx group at both 8 (control, 56.6 ± 2.3% mdx, 47.2 ± 7.4%) and 12 weeks (control, 53.9 ± 3.3% mdx, 44.1 ± 2.7%). In the strain analysis, all strain value peaks were significantly less in mdx mice, except for the longitudinal strain of the four-chamber view at both 8 and 12 weeks of age. Strain analysis with feature tracking and self-gated magnetic resonance cine imaging is useful for assessing cardiac function in young mdx mice. Full article

This study validates the usefulness of myocardial strain analysis with cardiac cine magnetic resonance imaging (MRI) by evaluating the changes in the cardiac function and myocardial strain values longitudinally in a myocardial disease model. Six eight-week-old male Wistar rats were used as a model of myocardial infarction (MI). Cine images were taken in the short axis, two-chamber view longitudinal axis, and four-chamber view longitudinal axis directions in rats 3 and 9 days after MI and in control rats, with preclinical 7-T MRI. The control images and the images on days 3 and 9 were evaluated by measuring the ventricular ejection fraction (EF) and the strain values in the circumferential (CS), radial (RS), and longitudinal directions (LS). The CS decreased significantly 3 days after MI, but there was no difference between the images on days 3 and 9. The two-chamber view LS was −9.7 ± 2.1% at 3 days and −13.9 ± 1.4% at 9 days after MI. The four-chamber view LS was −9.9 ± 1.5% at 3 days and −11.9 ± 1.3% at 9 days after MI. Both the two- and four-chamber LS values were significantly decreased 3 days after MI. Myocardial strain analysis is, therefore, useful for assessing the pathophysiology of MI. Full article

Background: The complete left bundle branch block (CLBBB) results in ventricular dyssynchrony and a reduction in systolic and diastolic efficiency. We noticed a distinct clockwise rotation of the left ventricle (LV) in patients with CLBBB (“longitudinal rotation”). Aim: The aim of this study was to quantify the “longitudinal rotation” of the LV in patients with CLBBB in comparison to patients with normal conduction or complete right bundle branch block (CRBBB). Methods: Sixty consecutive patients with normal QRS, CRBBB, or CLBBB were included. Stored raw data DICOM 2D apical-4 chambers view images cine clips were analyzed using EchoPac plugin version 203 (GE Vingmed Ultrasound AS, Horten, Norway). In EchoPac–Q-Analysis, 2D strain application was selected. Instead of apical view algorithms, the SAX-MV (short axis—mitral valve level) algorithm was selected for analysis. A closed loop endocardial contour was drawn to initiate the analysis. The “posterior” segment (representing the mitral valve) was excluded before finalizing the analysis. Longitudinal rotation direction, peak angle, and time-to-peak rotation were recorded. Results: All patients with CLBBB (n = 21) had clockwise longitudinal rotation with mean four chamber peak rotation angle of −3.9 ± 2.4°. This rotation is significantly larger than in patients with normal QRS (−1.4 ± 3°, p = 0.005) and CRBBB (0.1 ± 2.2°, p = 0.00001). Clockwise rotation was found to be correlated to QRS duration in patients with the non-RBBB pattern. The angle of rotation was not associated with a lower ejection fraction or the presence of regional wall abnormalities. Conclusions: Significant clockwise longitudinal rotation was found in CLBBB patients compared to normal QRS or CRBBB patients using speckle-tracking echocardiography. Full article

Background: In magnetic resonance imaging (MRI), the comparability of gated and non-gated measurements of the left atrial (LA) area and function and their association with cardiovascular risk factors have not been firmly established. Methods: 3-Tesla MRIs were performed on 400 subjects enrolled in the KORA (Cooperative Health Research in the Augsburg Region) MRI study. The LA maximum and minimum sizes were segmented in gated CINE four-chamber sequences (LA_max and LA_min) and non-gated T1 VIBE-Dixon (NGLA). The area-based LA function was defined as LAaf = (LA_max − LA_min)/LA_max. Inter-and intra-reader reliability tests were performed (n = 31). Linear regression analyses were conducted to link LA size and function with cardiovascular risk factors. Results: Data from 378 subjects were included in the analysis (mean age: 56.3 years, 57.7 % male). The measurements were highly reproducible (all intraclass correlation coefficients ≥ 0.98). The average LA_max was 19.6 ± 4.5 cm², LA_min 11.9 ± 3.5 cm², NGLA 16.8 ± 4 cm² and LAaf 40 ± 9%. In regression analysis, hypertension was significantly associated with larger gated LA_max (β = 1.30), LA_min (β = 1.07), and non-gated NGLA (β = 0.94, all p ≤ 0.037). Increasing age was inversely associated with LAaf (β = −1.93, p < 0.001). Conclusion: LA enlargement, as measured in gated and non-gated CMR is associated with hypertension, while the area-based LA function decreases with age. Full article

Four-chamber (4CH) cine cardiovascular magnetic resonance imaging (CMR) facilitates simultaneous evaluation of cardiac chambers; however, manual segmentation is time-consuming and subjective in practice. We evaluated deep learning based on a U-Net convolutional neural network (CNN) for fully automated segmentation of the four cardiac chambers using 4CH cine CMR. Cine CMR datasets from patients were randomly assigned for training (1400 images from 70 patients), validation (600 images from 30 patients), and testing (1000 images from 50 patients). We validated manual and automated segmentation based on the U-Net CNN using the dice similarity coefficient (DSC) and Spearman’s rank correlation coefficient (ρ); p < 0.05 was statistically significant. The overall median DSC showed high similarity (0.89). Automated segmentation correlated strongly with manual segmentation in all chambers—the left and right ventricles, and the left and right atria (end-diastolic area: ρ = 0.88, 0.76, 0.92, and 0.87; end-systolic area: ρ = 0.81, 0.81, 0.92, and 0.83, respectively; p < 0.01). The area under the curve for the left ventricle, left atrium, right ventricle, and right atrium showed high scores (0.96, 0.99, 0.88, and 0.96, respectively). Fully automated segmentation could facilitate simultaneous evaluation and detection of enlargement of the four cardiac chambers without any time-consuming analysis. Full article

In magnetic resonance imaging (MRI), epicardial adipose tissue (EAT) overload remains often overlooked due to tedious manual contouring in images. Automated four-chamber EAT area quantification was proposed, leveraging deep-learning segmentation using multi-frame fully convolutional networks (FCN). The investigation involved 100 subjects—comprising healthy, obese, and diabetic patients—who underwent 3T cardiac cine MRI, optimized U-Net and FCN (noted FCNB) were trained on three consecutive cine frames for segmentation of central frame using dice loss. Networks were trained using 4-fold cross-validation (n = 80) and evaluated on an independent dataset (n = 20). Segmentation performances were compared to inter-intra observer bias with dice (DSC) and relative surface error (RSE). Both systole and diastole four-chamber area were correlated with total EAT volume (r = 0.77 and 0.74 respectively). Networks’ performances were equivalent to inter-observers’ bias (EAT: DSC_Inter = 0.76, DSC_U-Net = 0.77, DSC_FCNB = 0.76). U-net outperformed (p < 0.0001) FCNB on all metrics. Eventually, proposed multi-frame U-Net provided automated EAT area quantification with a 14.2% precision for the clinically relevant upper three quarters of EAT area range, scaling patients’ risk of EAT overload with 70% accuracy. Exploiting multi-frame U-Net in standard cine provided automated EAT quantification over a wide range of EAT quantities. The method is made available to the community through a FSLeyes plugin. Full article

Background and objective: Cardiac magnetic resonance (CMR) is a key tool for cardiac work-up. However, arrhythmia can be responsible for arrhythmia-related artifacts (ARA) and increased scan time using segmented sequences. The aim of this study is to evaluate the effect of cardiac arrhythmia on image quality in a comparison of a compressed sensing real-time (CS_rt) cine sequence with the reference prospectively gated segmented balanced steady-state free precession (Cine_ref) technique regarding ARA. Methods: A total of 71 consecutive adult patients (41 males; mean age = 59.5 ± 20.1 years (95% CI: 54.7–64.2 years)) referred for CMR examination with concomitant irregular heart rate (defined by an RR interval coefficient of variation >10%) during scanning were prospectively enrolled. For each patient, two cine sequences were systematically acquired: first, the reference prospectively triggered multi-breath-hold Cine_ref sequence including a short-axis stack, one four-chamber slice, and a couple of two-chamber slices; second, an additional single breath-hold CS_rt sequence providing the same slices as the reference technique. Two radiologists independently assessed ARA and image quality (overall, acquisition, and edge sharpness) for both techniques. Results: The mean heart rate was 71.8 ± 19.0 (SD) beat per minute (bpm) (95% CI: 67.4–76.3 bpm) and its coefficient of variation was 25.0 ± 9.4 (SD) % (95% CI: 22.8–27.2%). Acquisition was significantly faster with CS_rt than with Cine_ref (Cine_ref: 556.7 ± 145.4 (SD) s (95% CI: 496.7–616.7 s); CS_rt: 23.9 ± 7.9 (SD) s (95% CI: 20.6–27.1 s); p < 0.0001). A total of 599 pairs of cine slices were evaluated (median: 8 (range: 6–14) slices per patient). The mean proportion of ARA-impaired slices per patient was 85.9 ± 22.7 (SD) % using Cine_ref, but this was figure was zero using CS_rt (p < 0.0001). The European CMR registry artifact score was lower with CS_rt (median: 1 (range: 0–5)) than with Cine_ref (median: 3 (range: 0–3); p < 0.0001). Subjective image quality was higher in CS_rt than in Cine_ref (median: 3 (range: 1–3) versus 2 (range: 1–4), respectively; p < 0.0001). In line, edge sharpness was higher on CS_rt cine than on Cine_ref images (0.054 ± 0.016 pixel⁻¹ (95% CI: 0.050–0.057 pixel⁻¹) versus 0.042 ± 0.022 pixel⁻¹ (95% CI: 0.037–0.047 pixel⁻¹), respectively; p = 0.0001). Conclusion: Compressed sensing real-time cine drastically reduces arrhythmia-related artifacts and thus improves cine image quality in patients with arrhythmia. Full article

Background and objective: To evaluate the reliability of compressed-sensing (CS) real-time single-breath-hold cine imaging for quantification of right ventricular (RV) function and volumes in congenital heart disease (CHD) patients in comparison with the standard multi-breath-hold technique. Methods: Sixty-one consecutive CHD patients (mean age = 22.2 ± 9.0 (SD) years) were prospectively evaluated during either the initial work-up or after repair. For each patient, two series of cine images were acquired: first, the reference segmented multi-breath-hold steady-state free-precession sequence (SSFP_ref), including a short-axis stack, one four-chamber slice, and one long-axis slice; then, an additional real-time compressed-sensing single-breath-hold sequence (CS_rt) providing the same slices. Two radiologists independently assessed the image quality and RV volumes for both techniques, which were compared using the Wilcoxon test and paired Student’s t test, Bland–Altman, and linear regression analyses. The visualization of wall-motion disorders and tricuspid-regurgitation-related signal voids were also analyzed. Results: The mean acquisition time for CS_rt was 22.4 ± 6.2 (SD) s (95% CI: 20.8–23.9 s) versus 442.2 ± 89.9 (SD) s (95% CI: 419.2–465.2 s) for SSFP_ref (p < 0.001). The image quality of CS_rt was diagnostic in all examinations and was mostly rated as good (n = 49/61; 80.3%). There was a high correlation between SSFP_ref and CS_rt images regarding RV ejection fraction (49.8 ± 7.8 (SD)% (95% CI: 47.8–51.8%) versus 48.7 ± 8.6 (SD)% (95% CI: 46.5–50.9%), respectively; r = 0.94) and RV end-diastolic volume (192.9 ± 60.1 (SD) mL (95% CI: 177.5–208.3 mL) versus 194.9 ± 62.1 (SD) mL (95% CI: 179.0–210.8 mL), respectively; r = 0.98). In CS_rt images, tricuspid-regurgitation and wall-motion disorder visualization was good (area under receiver operating characteristic curve (AUC) = 0.87) and excellent (AUC = 1), respectively. Conclusions: Compressed-sensing real-time cine imaging enables, in one breath hold, an accurate assessment of RV function and volumes in CHD patients in comparison with standard SSFP_ref, allowing a substantial improvement in time efficiency. Full article