Quantification of the intrinsic neural plexus of the heart – The missing link in histological tissue analysis

• The histological quantification of large transmural biopsies in its entirety remains a bottleneck in the image analysis stage and usually relies on analysis of selected regions of interest only. • A structured protocol including coding scripts is provided with all key steps of histological quantification of cardiac innervation in large transmural biopsies. • The workflow, using freely available software, can be easily adjusted, performed and holds potential to be applied in many fields of histological research. The heart is under strict regulation of the autonomic nervous system, during which, in a healthy state, the effects of sympathetic and parasympathetic branches are balanced. In recent years, there has been increasing interest in pathological remodeling and outgrowth of cardiac autonomic nerves in relation to arrhythmogenesis. However, the small size of the cardiac nerves in relatively large tissues renders research using histological quantification of these nerves extremely challenging and usually relies on quantification of the nerve density in selected regions of interest only. Our aim was to develop a method to be able to quantify the histological nerve density in transmural tissue sections. Here we describe a novel workflow that enables visualization and quantification of variable innervation types and their heterogeneity within transmural myocardial tissue sections. A custom semiautomatic workflow for the quantification of cardiac nerves involving Python, MATLAB and ImageJ is provided and described in this protocol in a stepwise and detailed manner. The results of two example tissue sections are represented in this paper. An example tissue section taken from the infarction core with a high heterogeneity value of 0.20, 63.3% normal innervation, 12.2% hyperinnervation, 3.6% hypoinnervation and 21.0% denervation. The second example tissue section taken from an area of the left ventricle remote from the infarction showed a low heterogeneity value of 0.02, 95.3% normal innervation, 3.8% hyperinnervation, 0.5% hypoinnervation and 0.5% denervation. : This approach has the potential to be broadly applied to any research involving high-resolution imaging of nerves in large tissues.