Archivio Italiano di Urologia e Andrologia (Apr 2013)
Animal experimental model of Peyronie’s disease: A pilot study
Abstract
Objective: The Peyronie's disease (PD) is an idiopathic disorder of connective tissue of the penis, that involves the tunica albuginea of the corpora cavernosa and the adjacent areolar space. It is a growing clinical evidence to support the therapeutic potential of mesenchymal stem cells and histological findings has assumed a possible application of lipofilling technique in patients with PD. The objective of this experimental study is the creation of a murine experimental model of PD, evaluating with MRI the penis of the rats (feasibility study), in order to plane the application of lipofilling technique in an animal model. Methods: Four male Wistar rats were anesthetized, fixed in prone position and subjected to MRI. The animals underwent, subsequently, an injection of thrombin in the tunica albuginea and MRI images were acquired at 7 and 21 days after injection with incision of the dartos. Results: The MRI acquisitions, both in coronal and axial projection, showed an adequate visibility of the anatomical structures. At 7 days after thrombin injection with the dartos incision it was evident an oedematous portion, visible as a hyperintense area, located at the injection area. At 21 days after injection, oedema was partially resolved: the injection part of the hyperintense area remains unchanged, while the remaining area appears to be part of a re-absorption and re-organization process. Conclusions: Since none of the various treatment modalities currently available for the management of PD is able to bring healing, the researchers’ attention is increasingly directed towards innovative treatment programs, such as the use of stem cells of mesenchymal origin. At the present time, the research in PD is hampered by the lack of universally accepted animal model and this is likely attributed to the limited insight into PD mechanisms and the difficulties faced by current animal models to truly represent the complexity.
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