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Published on: September 28, 2022
Computer-assisted three-dimensional tracking of sensory innervation in the murine bladder mucosa with two-photon
Anna Schueth1, Bart Spronck2, Marc A M J van Zandvoort3
1Department of Urology, Maastricht University Medical Center, P.O. Box 5800, 6202 AZ, Maastricht, The Netherlands; Department of Cognitive Neuroscience, Maastricht Brain Imaging Center (MBIC), Maastricht University, Oxfordlaan 55, 6200 MD, Maastricht, The Netherlands.
Abstract:
A strong association between functional bladder disorders and bladder sensation is well-known, with a relationship between malfunctioning detrusor muscle and abnormal sensation arising from the sub-urothelium and the lamina propria (LP), has been suggested. However, the exact underlying pathophysiology of these bladder disorders is not completely understood. Therefore, it is important to gain knowledge on sensory innervation of the urinary bladder in order to understand the neural network function in healthy and diseased bladder. In the present study we aim at the development of a computer-assisted method for 3D-tracking of sensory innervation in the murine bladder mucosa using two-photon laser scanning microscopy (TPLSM). TPLSM was performed on 10 fixed, stained (CGRP) bladder samples in both the trigone and dome. Nerve tracking was performed in subvolumes (6.3±2.9106μm3; median±IQR) of 22 stacks with determining total nerve length, nerve segment lengths, curviness, straightness, and locations of branching and ending points in the lamina propria (LP). The results show that the highest concentration of afferent fibres was found at the urothelium-LP interface. Nerve curviness, a presumed indicator of nerve activity, showed an equal value throughout the complete LP. We found a significantly higher median nerve segment length in the LP of the trigone and significantly more curved nerves in the dome of the bladder. This indicates an adaptation to, or an involvement in the detection of, bladder volume changes. Conclusively, we successfully developed a computer-assisted method for 3D tracking of sensory nerve fibres in the LP of the murine bladder wall.

