Left atrial volumes evaluation by cardiac magnetic resonance - time to revise the grading severity cut off values

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): This work was supported by a grant of Ministery of Research and Innovation, CNCS-UEFISCDI, project number grant 5/2018 and 83/2018 and PN-III-P1-1-TE-2016-0669, within PNCDI III Background Left atrial maximal volume (LAVmax) assessed by 2D echocardiography (2DE) is incorporated in new scoring system (2019) of heart failure with preserved ejection fraction (HFpEF), using well established cut-off values for grading severity. These values have strong evidence for diagnosis and prognosis. Moreover, cardiac magnetic resonance (CMR) is also included in the structural evaluation of HFpEF. However, cut-off values for LAVmax evaluated by CMR are higher. This might generate a different classification for LA dilation by CMR, potentially including patients in another risk class. We aimed to evaluate LAVi by 2DE and CMR in a group of HFpEF patients, in order to test the agreement between these two methods, regarding severity grading. Methods.  We prospectively enrolled 74 HFpEF patients (68 ± 9 yrs), and evaluate them by 2DE and CMR. Conventional 2DE was used to define anatomy and function of the left ventricle (LV). NTproBNP was done in all patients. We assessed biplane LAVmax index (LAVimax) and LA minimal volume index (LAVimin), from 4C and 2C views, and reported as a mean value, by eco and CMR (area–length method). Cohen"s k of agreement was evaluated to determine if there was an agreement between eco and CMR, using the cut off values for LAVimax by CMR and eco, provided by the guidelines (Figure) Results. Feasibility of the complete analysis was 95% (70 pts). LVEF was 60 ± 5.7%. LAVimax and LAVimin by eco and CMR were highly correlated (all R &amp;gt; 0.7, p &amp;lt; 0.001) (Table). However, CMR diagnosed a high percent of patients as having normal LAVimax values, by comparison with echo (59 vs. 5.7 %, p &amp;lt; 0.001) (Figure). There was no agreement between these two evaluation methods (Cohen"s k of agreement = 0.000), suggesting that CMR evaluation provides completely  different severity grading. NTproBNP significantly correlated only with LAVimin by CMR (R = 0.4, p = 0.04). Conclusions. We suggest that there is need for a future update of the grading cut-offs for LAV by CMR with larger reference range studies, and also with prognosis studies, as 2DE already provided. The present CMR grading severity might generate misclassification in certain pathological condition, such as HFpEF. We also suggest that LAVi min, instead of LAVi max should be used in the future study for assessment of prognosis. LA volumes evaluation by CMR and 2D echo LAVimax LAVimin ECO (ml/m2) 47 ± 11 23 ± 9 CMR (ml/m2) 51 ± 15 26 ± 12 R coefficient 0.7 0.74 P value &amp;lt;0.001 &amp;lt;0.001 Abstract Figure. </jats:sec

Multimodality approach by cardiac magnetic resonance and biological markers in left ventricular non-compaction with heart failure with preserved ejection fraction - revealing the unknown

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): PN-III-P1-1-TE-2016-0669, within PNCDI III Background Left ventricular non-compaction (LVNC) is associated with an increased risk of heart failure (HF). The presence of a real LVNC with HF with preserved ejection fraction (HFpEF), is still controverted. Methods We evaluated prospectively 42 patients with HFpEF, 21 with LVNC (61 ± 9 years) and 21 without LVNC (LVC), aged and risk factor matched, by cardiac magnetic resonance (CMR) 1.5T. LVNC diagnosis was confirmed by Petersen and Jacquier criteria (NC/C ratio and the percentage of NC myocardium). We performed myocardial T1 mapping (normal value of 950 ± 21ms). We calculated a mean value of all native T1 (T1mean), and also for apical (apicalT1) and basal segments (basalT1). We also calculated ECV mean, basal and apical. All patients had NTproBNP and biomarkers for systemic inflammation (hsCRP, IL6, cystatin C and sST2), endothelial dysfunction: VCAM, von Willebrand factor (vWf), vWF metalloproteinase-ADAMTS13, and myocardial fibrosis: vascular peroxidase (VPO), and Galectin-3. Results In the LVNC, mean NC/C ratio was 2.9 ± 0.5 mm and the percentage of NC myocardium was 24.41 ± 8.8%. LVNC patients had significantly higher T1apical, higher ECVmean, ECV basal and apical (Table) by comparison with LVC group, suggesting an extensive fibrosis in LVNC group with significantly higher apical fibrosis.  Inflammatory markers were similar between groups, LVNC patients had lower values of ADAMTS13, suggesting endothelial dysfunction, and higher values of Galectin-3, suggesting increased myocardial fibrosis (Table). Galectin-3 correlated positively only with apicalT1 (R = 0.49, p = 0.04). NTproBNP significantly correlated with VPO, a promotor of fibrosis (r = 0.61, p = 0.009) in LVNC group, whereas in LVC group correlated with cystatin C (r = 0.62, p = 0003) and VCAM (r = 0.4, p = 0.05). Native apical T1 cut off &amp;gt;1021 ms provided the highest sensibility and specificity to differentiate segments with and without NC in HFpEF (p = 0.002) (Figure). Conclusion  HFpEF patients with LVNC have significant higher NTproBNP, higher fibrosis than patients without LVNC, more extensive in non-compacted apical segments. Galectin-3 level correlates only with apical fibrosis on CMR, expressed by apicalT1 time. Moreover, endothelial dysfunction seems to play an important role in HFpEF generation in LVNC. All findings suggests that LVNC is a stand alone condition, not an adaptive hyper-trabeculation in HFpEF. Table.Comparison between groups NTproBNP (pg/ml) Galectin3 (ng/ml) ADAMTS13 (ng/ml) T1mean (ms) basalT1 (ms) apicalT1 (ms) ECV mean (%) ECV basal (%) ECV apical (%) LVNC 294 ± 282 8.44 ± 3.45 767.35 ± 335.56 1013.8 ± 31.8 1002.8 ± 27.2 1059 ± 73 27.2 ± 2.9 26.2 ± 2.9 29.6 ± 3.9 LVC 163 ± 71 6.67 ± 2.88 962.33 ± 253.78 1003.2 ± 28.1 1004.3 ± 29.5 1007 ± 40 24.3 ± 2.5 24.2 ± 2.7 25.2 ± 2.8 P value 0.031 0.048 0.049 0.26 0.865 0.007 0.002 0.033 &amp;lt;0.001 Abstract Figure </jats:sec

Time to solve the puzzle of heart failure with preserved ejection fraction by biomarkers, echocardiography and cardiac magnetic resonance

Abstract Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): HEART PRESERVED onbehalf HEART PRESERVED Background Heart failure with preserved ejection fraction (HFpEF) is now recognized as a major and growing public health problem worldwide. Clinical trials investigating different treatment strategies had disappointing results. Several biomarkers of inflammation, endothelial dysfunction, and myocardial fibrosis appeared to be promising in understanding HFpEF pathophysiology. Methods. We enrolled prospectively 94 patients with HFpEF in sinus rhythm  (according to 2019 scoring system) (67 ± 9 yrs, 33 men). We evaluated them by 2D and speckle tracking echocardiography (STE). 80 patients had also a cardiac magnetic resonance (CMR) 1.5T evaluation. We measured LV ejection fraction (LVEF), mean E’ (E’m), E/E’ ratio, sPAP, left atrial volume indexed (LAVi), and global longitudinal stain by STE (GLS).  By CMR we evaluated LVEFcmr, LV mass, T1 mapping with mean extracellular volume (ECVm), and pre-gadolinium mean times quantification (preGDT1m) as markers of myocardial fibrosis. All patients had NTproBNP and biomarkers for systemic inflammation (IL6, cystatin C, pentraxin-3, GDF15), endothelial dysfunction: soluble E -selectin, VCAM, von Willebrand factor (vWf), and myocardial fibrosis: Galectin-3. Results. LVEF was 60.5 ± 6 % and LVEFcmr 61 ± 6.6%. All parameters from the scoring system were as we expected: E’m = 7.6 ± 1.8 cm/s, E/E’ ratio = 11 ± 3.4, sPAP = 34 ± 8 mmHg, LAVi = 47 ± 11 ml/m2, GLS=-18.3 ± 2.9, and NTproBNP of 282 ± 294 pg/ml. NTproBNP significantly correlated with sPAP, LAVi, preGDT1m, ECVm, galectin-3, GDF15, and pentraxin-3 (all r &amp;gt; 0.4, p &amp;lt; 0.05). The best predictor for NTproBNP level was GDF15 (r = 0.4, r2 = 0.25, p = 0.001). LAVi significantly corelated with E/E’ ratio, sPAP, NTproBNP, galectin-3 (r &amp;gt; 0.4, p &amp;lt; 0.05). GLS correlated with LVEFcmr, LV mass, ECVm, preGDT1m, LAVi, E/E’ ratio, NTproBNP, GDF15, vWf, Eselectin, VCAM (all r = 0.4, p &amp;lt; 0.05). The best predictor model for GLS was LV mass, NTproBNP, E-selectine, and vWf (r = 0.67, r2 = 0.45, P &amp;lt; 0.001). sPAP was best predicted by a model composed by IL6, VCAM, LAVi (r = 0.5, r2 = 0.25, p &amp;lt; 0.001). E’m significantly correlated with vWf, GHD15, VCAM, LV mass, and preGDT1 (all r &amp;gt; 0.4, p &amp;lt; 0.05), but the best predictor model included only LV mass and GDF15 (r = 0.57, r2 = 0.32, P &amp;lt; 0.001). Galectin-3 significantly correlated with LAVi, preGDT1m, and NTproBNP, but the only predictor for galectin-3 level was preGDT1 (r = 0.4, r2 = 0.2, p = 0.007). Conclusions In HFpEF NTproBNP is significantly correlated with markers of inflammatory status, endothelial dysfunction, and fibrosis, but the level is mainly determined by inflammation (GDF15). Diastolic dysfunction parameters are mainly correlated with inflammatory and endothelial dysfunction biomarkers . Only LAVi was correlated with myocardial fibrosis. Sub-clinical systolic dysfunction is mainly determined by proinflamatory status and endothelial dysfunction, but not by fibrosis. </jats:sec

Left atrial function by speckle tracking echocardography in HFpEF v1

AIMS. None of the conventional echocardiographic parameters alone predict increased NTproBNP level and symptoms, making diagnosis of heart failure with preserved ejection fraction (HFpEF) very difficult in some cases, in resting condition. We will evaluate LA functions by 2D speckle tracking echocardiography (STE) on top of conventional parameters in HFpEF and preHF patients with diastolic dysfunction (DD), in order to establish the added value of the LA deformation parameters in the diagnosis of HFpEF. METHODS. We will enroll patients with HFpEF and compare them with asymptomatic patients with similar risk factors with DD (preHF). We will evaluate them by NTproBNP, conventional DD parameters, and STE. Global longitudinal strain (GS) was added. LA reservoir (R), conduit (C), and pump function (CT) were assessed both by volumetric and STE. 2 reservoir strain (S) derived indices were also measured, stiffness (SI) and distensibility index (DI). </p