To study the diffusion tensor-based fiber tracking feasibility to access the male urethral sphincter complex of patients with prostate cancer undergoing Retzius-sparing robot-assisted laparoscopic radical prostatectomy (RS-RARP).
Twenty-eight patients (median age of 64.5 years old) underwent 3 T multiparametric-MRI of the prostate, including an additional echo-planar diffusion tensor imaging (DTI) sequence, using 15 diffusion-encoding directions and a b value = 600 s/mm2. Acquisition parameters, together with patient motion and eddy currents corrections, were evaluated. The proximal and distal sphincters, and membranous urethra were reconstructed using the deterministic fiber assignment by continuous tracking (FACT) algorithm, optimizing fiber tracking parameters. Tract length and density, fractional anisotropy (FA), axial diffusivity (AD), mean diffusivity (MD), and radial diffusivity (RD) were computed. Regional differences between structures were accessed by ANOVA, or nonparametric Kruskal-Wallis test, and post-hoc tests were employed, respectively, TukeyHSD or Dunn's.
The structures of the male urethral sphincter complex were clearly depicted by fiber tractography using optimized acquisition and fiber tracking parameters. The use of eddy currents and subject motion corrections did not yield statistically significant differences on the reported DTI metrics. Regional differences were found between all structures studied among patients, suggesting a quantitative differentiation on the structures based on DTI metrics.
The current study demonstrates the technical feasibility of the proposed methodology, to study in a preoperative setting the male urethral sphincter complex of prostate cancer patients candidates for surgical treatment. These findings may play a role on a more accurate prediction of the RS-RARP post-surgical urinary continence recovery rate.
Insights into imaging. 2020 Nov 27*** epublish ***
Ana S C Verde, Joao Santinha, Eunice Carrasquinha, Nuno Loucao, Ana Gaivao, Jorge Fonseca, Celso Matos, Nikolaos Papanikolaou
Head of Computational Clinical Imaging Group, Centre for the Unknown, Champalimaud Foundation, Av. Brasilia, 1400-038, Lisbon, Portugal., Philips Healthcare, Lisbon, Portugal., Radiology Department, Champalimaud Foundation, Lisbon, Portugal., Urology Unit, Champalimaud Foundation, Lisbon, Portugal., Head of Computational Clinical Imaging Group, Centre for the Unknown, Champalimaud Foundation, Av. Brasilia, 1400-038, Lisbon, Portugal. .