# Multiphoton Microscopy to Visualize Live Renal Nerves in Reanimated Kidney Blocks

## TL;DR

This study uses multiphoton microscopy to visualize live renal nerves in reanimated pig kidney blocks, offering a new way to evaluate renal denervation techniques.

## Contribution

The paper introduces a novel method for visualizing live renal nerves using multiphoton microscopy in a reanimated kidney model.

## Key findings

- Peri-arterial nerves and arteriolar elastin fibers were successfully imaged at 25× magnification using 780 nm excitation.
- Autofluorescence was insufficient for nerve identification at 4× magnification.
- The model showed a high but variable signal-to-noise ratio of 52.3 (median, IQR 159).

## Abstract

Renal denervation to treat arterial hypertension is growing in adoption but still shows inconsistent results. Device improvement is difficult, as there is currently no way to study the immediate success of renal denervation devices in living tissue. In an effort to visualize live renal nerves surrounding their arteries using multiphoton microscopy, kidney pairs were explanted from Yorkshire pigs. They were maintained viable with a pulsatile perfusion apparatus using Visible Kidney™ methodologies, in which blood is replaced by a modified, oxygenated, and warmed (37 °C) Krebs–Henseleit buffer. The block resection allows catheter placement for nerve ablation treatment. Subsequently, the kidney block was disconnected from the perfusion system and underwent multiphoton microscopy (Nikon A1R 1024 MP). A total of three renal blocks were imaged using this model. Using 780 nm excitation for autofluorescence, we were able to selectively image peri-arterial nerves (2.5–23 μm diameter) alongside arteriolar elastin fibers (1.96 ± 0.87 μm; range: 0.3–4.27) at 25× magnification at a pixel size of 1.02 µm). Autofluoresecence was not strong enough to identify nerves at 4× magnification. There was a high but variable signal-to-noise ratio of 52.3 (median, IQR 159). This model may be useful for improving future physician training and innovations in renal denervation technologies.