A novel method for visualization and quantification of nerve density in transmural biopsies after myocardial infarction

Abstract

Abstract Introduction Abnormal cardiac innervation plays an important role in arrhythmogenicity after myocardial infarction (MI). To study the innervation state after cardiac damage and ventricular arrhythmias, accurate quantification of nerve density is important. However, as cardiac nerves are very small structures, the histological quantification of nerves requires high resolution images, thus far proved extremely challenging and has never been performed transmurally. Aim To develop a method to analyze nerve density in large transmural biopsies after MI. Method Transmural myocardial biopsies from 4 swine, 3 months after MI, were stained with Picrosirius Red (fibrosis) and Beta-III-Tubulin (autonomic nerves). Fibrosis cut-offs were used to classify the biopsies into MI core (>59.8%), borderzone (BZ) (14.3–59.8%) or remote zone (RZ) (<14.3%). Each biopsy was quantified with a custom software pipeline, involving Python, Matlab and ImageJ. The biopsy was graphically divided into a 1x1mm grid. Using fixed values, nerve and myocardial tissue areas were thresholded and subjected to a quality check and artefact removal, followed by further division into 0.1x0.1mm squares. The nerve density per square was calculated and classified into denervation, hypoinnervation, normal innervation and hyperinnervation according to cut-offs (5th, 95th percentile) derived from 3 control swine. Finally, squares were located back to the original position within the biopsy allowing visualization and quantification of the different innervation types. Currently these steps are being integrated into an easy-to-use framework. Results In all 121 analyzed biopsies (experimental swine n=83, control n=38), areas with variable nerve densities were observed, although the areas with denervation, hypo- and hyperinnervation were largest in the MI core and BZ. Normal innervation was observed in 94.9% (93.8–96.0%) of the total biopsy area in the RZ, decreased in the BZ biopsies, 87.9% (85.1–92.4%, p<0.001), and even lower in the MI core, 72.8% (66.3–75.8%, p<0.001). The percentage of denervation and hypoinnervation per biopsy was highest in the core biopsies, 16.7% (13.5–23.5%) and 3.8% (2.9–5.0%) respectively, lower in the BZ, 2.6% (1.6–6.5%, p<0.008) and 1.2% (0.8–1.7%, p=0.015) and even lower in the RZ, 1.2% (0.7–1.8%, p<0.001), 0.6% (0.3–1.3, p<0.001). Hyperinnervation was observed mainly in the BZ, 5.3% (3.7–9.4%) and remarkably, also in the core, 5.3% (3.7–9.4%, p>0.999), whilst being low in the RZ 2.6% (1.7–4.3%, p=0.002 and p=0.038 respectively). Conclusion This novel method allows successful visualization and quantification of nerve density after cardiac damage in transmural biopsies. Strikingly, alternating areas of different innervation types could be identified within the same biopsy after MI, indicating a potentially heterogenous substrate for arrhythmias. This method has the potential to be broadly applied to any research involving high resolution imaging of nerves in large tissues. Funding Acknowledgement Type of funding sources: None.