Four-dimensional reconstruction and characterization of bladder deformations

• Published in: Computer methods and programs in biomedicine 2023-07, Vol.237, p.107569-107569, Article 107569
• Main Authors: Ogier, Augustin C., Rapacchi, Stanislas, Bellemare, Marc-Emmanuel
• Format: Article
• Language: English
• Subjects: 3D Dynamic MRI; Biomechanics; Bladder; Computer Science; Engineering Sciences; Human health and pathology; Life Sciences; Mechanics; Medical Imaging; Pelvic dynamics; Urology and Nephrology; Volume reconstruction
• ISSN: 0169-2607; 1872-7565
• DOI: 10.1016/j.cmpb.2023.107569

•A dynamic 3D real-time observation of the pelvic region has been proposed as well as a 3D representation of the organs deformations.•First real-time 3D deformation fields of the bladder under strain from in-bore forced breathing exercises.•The organ reconstruction process allowed a characterization of the 3D deformations undergone by the pelvic organs during loading exercises.•The complete methodology is directly transferable to clinics.•Our combined MR acquisition and image processing framework opens novel perspectives towards real-time 3D dynamic pelvic imaging and biomechanical pelvic organs. Pelvic floor disorders are prevalent diseases and patient care remains difficult as the dynamics of the pelvic floor remains poorly understood. So far, only 2D dynamic observations of straining exercises at excretion are available in the clinics and 3D mechanical defects of pelvic organs are not well studied. In this context, we propose a complete methodology for the 3D representation of non-reversible bladder deformations during exercises, combined with a 3D representation of the location of the highest strain areas on the organ surface. Novel image segmentation and registration approaches have been combined with three geometrical configurations of up-to-date rapid dynamic multi-slice MRI acquisitions for the reconstruction of real-time dynamic bladder volumes. For the first time, we proposed real-time 3D deformation fields of the bladder under strain from in-bore forced breathing exercises. The potential of our method was assessed on eight control subjects undergoing forced breathing exercises. We obtained average volume deviations of the reconstructed dynamic volume of bladders around 2.5% and high registration accuracy with mean distance values of 0.4 ± 0.3 mm and Hausdorff distance values of 2.2 ± 1.1 mm. The proposed framework provides proper 3D+t spatial tracking of non-reversible bladder deformations. This has immediate applicability in clinical settings for a better understanding of pelvic organ prolapse pathophysiology. This work can be extended to patients with cavity filling or excretion problems to better characterize the severity of pelvic floor pathologies or to be used for preoperative surgical planning.