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22 May 2017 : Clinical Research  

Visualization of Penile Suspensory Ligamentous System Based on Visible Human Data Sets

Xianzhuo Chen1BCEF, Yi Wu2BCD, Ling Tao1AG, Yan Yan3BCD, Jun Pang4CD, Shaoxiang Zhang2BCD, Shirong Li1A*

DOI: 10.12659/MSM.901926

Med Sci Monit 2017; 23:2436-2444

Abstract

BACKGROUND: The aim of this study was to use a three-dimensional (3D) visualization technology to illustrate and describe the anatomical features of the penile suspensory ligamentous system based on the Visible Human data sets and to explore the suspensory mechanism of the penis for the further improvement of the penis-lengthening surgery.

MATERIAL AND METHODS: Cross-sectional images retrieved from the first Chinese Visible Human (CVH-1), third Chinese Visible Human (CVH-3), and Visible Human Male (VHM) data sets were used to segment the suspensory ligamentous system and its adjacent structures. The magnetic resonance imaging (MRI) images of this system were studied and compared with those from the Visible Human data sets. The 3D models reconstructed from the Visible Human data sets were used to provide morphological features of the penile suspensory ligamentous system and its related structures.

RESULTS: The fundiform ligament was a superficial, loose, fibro-fatty tissue which originated from Scarpa’s fascia superiorly and continued to the scrotal septum inferiorly. The suspensory ligament and arcuate pubic ligament were dense fibrous connective tissues which started from the pubic symphysis and terminated by attaching to the tunica albuginea of the corpora cavernosa. Furthermore, the arcuate pubic ligament attached to the inferior rami of the pubis laterally.

CONCLUSIONS: The 3D model based on Visible Human data sets can be used to clarify the anatomical features of the suspensory ligamentous system, thereby contributing to the improvement of penis-lengthening surgery.

Keywords: Imaging, Three-Dimensional, Ligaments, Penis, Visible Human Projects

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Medical Science Monitor eISSN: 1643-3750
Medical Science Monitor eISSN: 1643-3750