366 The use of dedicated long-axis views focused on the left atrium improves the accuracy of left atrial volumes and function measured by cardiovascular magnetic resonance

Aims The use of apical views focused on the left atrium (LA) has improved the accuracy of LA volume evaluation by two-dimensional echocardiography. However, routine cardiac magnetic resonance (CMR) evaluation of LA volumes still uses standard 2- and 4-chamber cine images focused on the left ventricle. To investigate the potential of LA-focused CMR cine images, we compared LA maximal (LAVmax) and minimal (LAVmin) volumes, and emptying fraction (LA-EF) calculated on both standard and LA-focused long-axis cine images with LA volumes obtained by short-axis cine stacks covering the LA. Methods and results LA volumes and LA-EF were obtained from 108 consecutive patients by applying the biplane area-length algorithm to both standard and LA-focused 2- and 4-chamber cine images. Manual segmentation of a short-axis cine stack covering the LA was used as the reference method. Compared to the reference method, the standard approach significantly underestimated LA volumes (LAVmax: bias −13 ml; LOA = +11 ml, −37 ml; LAVmin; bias −10 ml, LOA: +9 ml, −28ml), and overestimated LA-EF (bias= 5%, LOA: +23%, −14%). Conversely, LA volumes (LAVmax bias −0.03 ml; LOA: +10 ml, −10 ml. LAVmin bias = −1.5 ml; LOA: +7 ml, −10 ml), and LA-EF (bias 2%, LOA: +11%, −7%) by LA-focused cine images were similar to those measured using the reference method. Moreover, LA volumes by LA-focused images were obtained faster than using the reference method (1.2 vs. 4.5 min, P < 0.001). Conclusions LA volumes and LA-EF measured using dedicated LA-focused long-axis cine imaging are more accurate than using standard (LV-focused) cine images.

Unchanged right ventricular strain in repaired tetralogy of Fallot after pulmonary valve replacement with radial long-axis cine magnetic resonance images

We measured right ventricular (RV) strain by applying a novel postprocessing technique to conventional short-axis cine magnetic resonance imaging in the repaired tetralogy of Fallot (TOF) and investigated whether pulmonary valve replacement (PVR) changes the RV strain. Twenty-four patients with repaired TOF who underwent PVR and 16 healthy controls were enrolled. Global maximum and minimum principal strains (GPSmax, GPSmin) and global circumferential and longitudinal strains (GCS, GLS) were measured from short-axis cine images reconstructed radially along the long axis. Strain parameters before and after PVR were compared using paired t-tests. One-way ANOVA with Tukey post-hoc analysis was used for comparisons between the before and after PVR groups and the control group. There were no differences in strain parameters before and after PVR. The GPSmax before PVR was lower than that in the control group (P = 0.002). Before and after PVR, GCSs were higher and GLSs were lower than those in the control group (before and after GCSs: P = 0.002 for both, before and after GLSs: P < 0.0001 and P = 0.0003). RV strains from radially reconstructed short-axis cine images revealed unchanged myocardial motion after PVR. When compared to the control group, changes in GCS and GLS in TOF patients before and after PVR might be due to RV remodeling.

Right Ventricular Strain in Repaired Tetralogy of Fallot After Pulmonary Valve Replacement With Reconstructed Radial Long-axis Cine Magnetic Resonance Images

Objectives: To investigate changes in right ventricular (RV) strain after pulmonary valve replacement (PVR) in repaired tetralogy of Fallot (TOF) by applying a novel postprocessing technique to conventional short-axis cine MRI to measure RV strains before and after PVR.Methods: Twenty-four patients with repaired TOF who underwent PVR and 16 healthy controls were enrolled. Global maximum and minimum principal strains (GPSmax, GPSmin) and global circumferential and longitudinal strains (GCS, GLS) were measured from short-axis cine images reconstructed radially along the long axis. Strain parameters before and after PVR were compared using paired t-tests. One-way ANOVA with Tukey post-hoc analysis was used for comparisons between the before and after PVR groups and the control group. Results: There were no differences in strain parameters before and after PVR. The GPSmax before PVR was lower than that in the control group (P=0.002). Before and after PVR, GCSs were higher and GLSs were lower than those in the control group (before and after GCSs: P=0.002 for both, before and after GLSs: P<0.0001 and P=0.0003). Conclusions: RV strains from radially reconstructed short-axis cine images revealed impaired myocardial motion after PVR. When compared to the control group, changes in GCS and GLS in TOF patients before and after PVR might be due to RV remodeling.

Segmental Strain for Myocardial Scar Detection in Acute Infarcts and Follow-Up CMR Using Non-Contrast Cine Images

Aims Scar tissue from myocardial infarction is best visualized with cardiac magnetic resonance (CMR) late gadolinium enhancement (LGE). Gadolinium-free alternatives for detection of myocardial scars are limited. This study investigated the feasibility of myocardial scar detection in acute infarcts and follow-up CMR using non-contrast cine images. Methods Fifty-seven patients with acute infarcts (15 female, mean age 61 ± 12 years, CMR 2.8 ± 2 days after infarction) were retrospectively evaluated with follow-up CMR exams available in thirty-two patients (9 female, 35 ± 14 days after infarction). Twenty-eight patients with normal CMR scans (2 female, mean age 47 ± 8 years) served as controls. Global and segmental strain parameters (global peak circumferential [GPCS], global peak longitudinal [GPLS], global peak radial strain [GPRS], segmental peak circumferential [SPCS], segmental peak longitudinal [SPLS], and segmental peak radial strain [SPRS]) were calculated from standard non-contrast balanced SSFP cine sequences using commercially available software (Segment CMR, Medviso, Sweden). Visual assessment of wall motion abnormalities on short axis cine images, as well as segmental circumferential strain calculations (endo-/epicardially contoured short axis cine and resulting polar plot strain map) of every patient (acute imaging and follow-up CMR) and control were presented for two blinded readers in random order, who were advised to localize potentially infarcted segments, blinded to LGE images and clinical information.Results While global strain values were impaired in patients with acute infarcts compared to controls (GPCS p= 0.01; GPLS p= 0.04; GPRS p= 0.01), global strain was similar between first CMR and follow-up imaging in the subgroup of 32 patients (GPCS p= 0.7; GPLS p=0.8; GPRS p=0.2). In acute infarcts and in follow-up CMR, patients had reduced mean SPCS in infarcted segments compared to remote myocardium (acute p= 0.03, follow-up exams p= 0.02). SPCS values in infarcted areas were similar in acute infarcts and in follow-up exams (p=0.8). In acute infarcts 74.6% of all in LGE infarcted segments (141/189) were correctly localized in polar plot strain maps compared to 44.4% (84/189) of infarcted segments detected by visual wall motion assessment only (p < 0.01). In follow-up exams, 81.5% of all in LGE infarcted segments (93/114 segments) were correctly localized in polar plot strain maps compared to 51.8% (59/114) of infarcted segments detected by visual wall motion assessment (p < 0.01).Conclusion Segmental circumferential strain derived from routinely acquired cine sequences detects nearly 75% acute infarcts and about 80% of infarcts in follow-up CMR and can potentially be used for scar identification based on non-contrast cine images, when gadolinium cant not be applied or LGE images are not available.

Segmental strain analysis for the detection of chronic ischemic scars in non-contrast cardiac MRI cine images

Cardiac magnetic resonance imaging (MRI) with late gadolinium enhancement (LGE) is considered the gold standard for scar detection after myocardial infarction. In times of increasing skepticism about gadolinium depositions in brain tissue and contraindications of gadolinium administration in some patient groups, tissue strain-based techniques for detecting ischemic scars should be further developed as part of clinical protocols. Therefore, the objective of the present work was to investigate whether segmental strain is noticeably affected in chronic infarcts and thus can be potentially used for infarct detection based on routinely acquired non-contrast cine images in patients with known coronary artery disease (CAD). Forty-six patients with known CAD and chronic scars in LGE images (5 female, mean age 52 ± 19 years) and 24 gender- and age-matched controls with normal cardiac MRI (2 female, mean age 47 ± 13 years) were retrospectively enrolled. Global (global peak circumferential [GPCS], global peak longitudinal [GPLS], global peak radial strain [GPRS]) and segmental (segmental peak circumferential [SPCS], segmental peak longitudinal [SPLS], segmental peak radial strain [SPRS]) strain parameters were calculated from standard non-contrast balanced SSFP cine sequences using commercially available software (Segment CMR, Medviso, Sweden). Visual wall motion assessment of short axis cine images as well as segmental circumferential strain calculations (endo-/epicardially contoured short axis cine and resulting polar plot strain map) of every patient and control were presented in random order to two independent blinded readers, which should localize potentially infarcted segments in those datasets blinded to LGE images and patient information. Global strain values were impaired in patients compared to controls (GPCS p = 0.02; GPLS p = 0.04; GPRS p = 0.01). Patients with preserved ejection fraction showed also impeded GPCS compared to healthy individuals (p = 0.04). In patients, mean SPCS was significantly impaired in subendocardially (− 5.4% ± 2) and in transmurally infarcted segments (− 1.2% ± 3) compared to remote myocardium (− 12.9% ± 3, p = 0.02 and 0.03, respectively). ROC analysis revealed an optimal cut-off value for SPCS for discriminating infarcted from remote myocardium of − 7.2% with a sensitivity of 89.4% and specificity of 85.7%. Mean SPRS was impeded in transmurally infarcted segments (15.9% ± 6) compared to SPRS of remote myocardium (31.4% ± 5; p = 0.02). The optimal cut-off value for SPRS for discriminating scar tissue from remote myocardium was 16.6% with a sensitivity of 83.3% and specificity of 76.5%. 80.3% of all in LGE infarcted segments (118/147) were correctly localized in segmental circumferential strain calculations based on non-contrast cine images compared to 53.7% (79/147) of infarcted segments detected by visual wall motion assessment (p > 0.01). Global strain parameters are impaired in patients with chronic infarcts compared to controls. Mean SPCS and SPRS in scar tissue is impeded compared to remote myocardium in infarcts patients. Blinded to LGE images, two readers correctly localized 80% of infarcted segments in segmental circumferential strain calculations based on non-contrast cine images, in contrast to only 54% of infarcted segments detected due to wall motion abnormalities in visual wall motion assessment. Analysis of segmental circumferential strain shows a promising method for detection of chronic scars in routinely acquired, non-contrast cine images for patients who cannot receive or decline gadolinium.

Automatic estimation of left atrial function from short axis CINE-MRI using machine learning

Introduction The importance of atrial mechanical dysfunction in atrial and ventricular pathologies is becoming increasingly recognised. Although machine learning (ML) tools have the ability to automatically estimate atrial function, to date ML techniques have not been used to automatically estimate atrial volumes and functional parameters directly from short axis CINE MRI. Purpose We introduce a convolutional neural network (CNN) to automatically segment the left atria (LA) in CINE-MRI. As a demonstration of the clinical utility of this technique, we calculated LA and left ventricular (LV) ejection fractions automatically from CINE images. Methods Short axis CINE MRI stacks, covering both ventricles and atria, were obtained in a 1.5T Philips Ingenia scanner. A 2D bSSFP ECG-gated protocol was used (FA=60°, TE/TR=1.5/2.9 ms), typical FOV =385 x 310 x 150 mm3, acquisition matrix = 172 x 140, slice thickness = 10 mm, reconstructed with resolution 1.25 x 1.25 x 10 mm3, 30–50 cardiac phases. Images were collected from 37 AF patients in sinus rythm at the time of scan (31–72 years old, 75% male, 18 with paroxysmal AF (PAF), 19 with persistent AF (persAF)). To automatically segment the LA, we used a dedicated CNN that follows a U-Net architecture and was trained in 715 images of the LA, manually segmented by an expert. Data augmentation techniques that included noise addition and linear and non-linear image transforms were also used to increase the training dataset. Ventricular structures, including the LV blood pool, were automatically segmented in these images using a CNN previously trained for this task. Volumetric time plots of LA and LV volume were produced and used to automatically compute maximal and minimal volumes, from which LA and LV ejection fractions (EFs) were assessed. A Bland-Altman analysis compared these automatically computed LA volumes and LA EFs with clinical manual estimates from the same scanning session. Results The CNN achieved very good quality LA segmentations when compared to manual ones (Fig a,b): Dice coefficients (0.90±0.07), median contour distances (0.50±1.12mm) and Hausdorff distances (6.70±6.16mm). Bland-Altman analyses show very good agreement between automatic and manual LA volumes and EFs (Fig e). A moderate linear correlation between LA and LV EFs in AF patients was found (Fig d). The measured LA EF was higher for PAF (29±8%) than PersAF patients (21±11%), although non-significantly (t-test p-value: 0.10). Conclusions We present a reliable automatic method to perform LA segmentations from CINE MRI across the entire cardiac cycle. This approachs opens up the possibility of automatically calculating more sophisticated biomarkers of LA function which take into account information about LA volumes across the entire cardiac cycle, including biomarkers of LA booster pump function. Figure 1 Funding Acknowledgement Type of funding source: Foundation. Main funding source(s): British Heart Foundation; EPSRC/Wellcome Centre for Medical Engineering