Analysis of Cardiac Amyloidosis Progression Using Model-Based Markers

Abstract

Deposition of amyloid in the heart can lead to cardiac dilation and impair its pumping ability. This ultimately leads to heart failure with worsening symptoms of breathlessness and fatigue due to the progressive loss of elasticity of the myocardium. Biomarkers linked to the clinical deterioration can be crucial in developing effective treatments. However, to date the progression of cardiac amyloidosis is poorly characterized. There is an urgent need to identify key predictors for disease progression and cardiac tissue function. In this proof of concept study, we estimate a group of new markers based on mathematical models of the left ventricle derived from routine clinical magnetic resonance imaging and follow-up scans from the National Amyloidosis Center at the Royal Free in London. Using mechanical modeling and statistical classification, we show that it is possible to predict disease progression. Our predictions agree with clinical assessments in a double-blind test in six out of the seven sample cases studied. Importantly, we find that multiple factors need to be used in the classification, which includes mechanical, geometrical and shape features. No single marker can yield reliable prediction given the complexity of the growth and remodeling process of diseased hearts undergoing high-dimensional shape changes. Our approach is promising in terms of clinical translation but the results presented should be interpreted with caution due to the small sample size.

The Scope and Limitations of In Vivo and In Silico Models of Cardiac Amyloidosis

“…It is important to have an indicator of cardiac tissue function, which is important f treatment. Li et al used mathematical models of the left ventricle derived from routi clinical magnetic resonance imaging to find new markers and demonstrated the agre ments with clinical symptoms (double-blinded test in six out of the seven sample case The following factors were evaluated in a group of amyloidosis patients before and af treatment: the strains, stresses, p-V curve, LV shape and volume (Figure 3) [6].…”

“…Li et al used mathematical models of the left ventricle derived from routine clinical magnetic resonance imaging to find new markers and demonstrated the agreements with clinical symptoms (double-blinded test in six out of the seven sample cases). The following factors were evaluated in a group of amyloidosis patients before and after treatment: the strains, stresses, p-V curve, LV shape and volume (Figure 3) [6]. A model based on the evaluation of circulating retinol-binding protein 4 (RBP4) concentration was developed for the identification of ATTR V122I amyloidosis in elderly African American patients [9].…”

Apparent growth tensor of left ventricular post myocardial infarction – In human first natural history study

“…Validation 2: A template mesh with 50 (longitudinal)×60 (circumferential)× 10(transmural) elements is used for representing the LV geometry, the same mesh has been used for finite element modelling of LV dynamics [33]. To check whether this mesh is adequate for estimating g , the mesh of patient 9 is refined with 60 (longitudinal)×84 (circumferential)×14 (transmural) elements.…”