Non-ischemic Primary and Secondary Cardiomyopathy
Karin Pola
PhD student
Lund University
Lund, Skane Lan, Sweden
Karin Pola
PhD student
Lund University
Lund, Skane Lan, Sweden
Zakariye Ashkir, MD
Clinical Research Fellow
University of Oxford
Oxford, England, United Kingdom
Håkan Arheden, MD, PhD
Professor
Lund University
Lund, Sweden
Hugh Watkins, MD, PhD
Professor of Cardiovascular Medicine
University of Oxford, England, United Kingdom
Stefan Neubauer, MD, FSCMR
Professor of Cardiovascular Medicine
University of Oxford
Oxford, England, United Kingdom
Per M. Arvidsson, MD, PhD
Researcher
University of Oxford, Sweden
Betty Raman, MD, PhD
Associate Professor
University of Oxford
Oxfordshire, England, United Kingdom
Patients with non-obstructive hypertrophic cardiomyopathy (nHCM) may exhibit a range of anatomical variations including septal, reverse septal, apical, mid-ventricular and concentric hypertrophy. Cardiovascular magnetic resonance imaging (CMR) with 4D flow permits assessment of intraventricular haemodynamics by computation of haemodynamic forces (HDF) and kinetic energy (KE) of the blood flow (1,2). These parameters may signify underlying left ventricular dysfunction (3,4). The aim of this study was therefore to investigate if left ventricular HDF and KE differ between nHCM and controls, and between subgroups of nHCM.
Methods:
Patients with nHCM (n=71) and age- and sex-matched controls (n=20) underwent CMR at 3T (Trio, Siemens) (Table 1). Patients were categorised as phenotype positive (P+) based on presence of hypertrophy (maximum wall thickness ≥15mm, or ≥13mm with a positive family history), and as phenotype negative (P-) referring to pre-hypertrophic sarcomeric variant carriers. Patients with P+ nHCM were classified into subgroups based on the pattern of hypertrophy. Left ventricular HDF and KE were computed over the cardiac cycle using validated modules in the software Segment v3.3R10057 (Medviso, Lund, Sweden) (Figure 1). Measurements of HDF were based on the Navier-Stokes equations (1), and analysed in three orthogonal directions as root mean square values for systole and diastole. Force ratio was calculated as the sum of the two transverse components divided by the longitudinal component. The Mann-Whitney U test was used for group comparisons, Pearson analysis for correlations, and Fisher’s exact test for binary categorical data.
Results:
Hemodynamic force ratio was increased in systole in P+ patients compared to P- and controls (Figure 2A, Table 1), mainly through increased HDF in the lateral wall-septum direction in P+ (Table 1). Diastolic force ratio did not differ between patients with nHCM and controls (Table 1).
Kinetic energy was increased in systole in patients with nHCM compared to controls (5.6mJ [3.3] vs 4.0mJ [2.4], p=0.001). Notably, P+ patients had increased systolic KE compared to P- patients and controls, despite being classified as non-obstructive by the treating physician (Table 1, Figure 2B). Patients with septal hypertrophy had greater systolic KE than patients with apical and concentric hypertrophy, and controls (p=0.005 and p=0.04 and p< 0.0001) (Figure 2B). Patients with reverse septal hypertrophy also had greater systolic KE than controls (p=0.0007). Diastolic KE did not differ between patients with nHCM and controls (5.0mJ [3.4] vs 4.1 [2.5], p=0.3). Systolic force ratio and KE correlated with maximum wall thickness (r=0.31, p=0.005; r=0.43, p< 0.0001).
Conclusion:
In hypertrophic cardiomyopathy, left ventricular hemodynamic forces and kinetic energy analysis from 4D flow CMR can detect abnormal intraventricular haemodynamics prior to establishment of left ventricular outflow tract obstruction, and between hypertrophy phenotype subgroups.