Category: Urinary Incontinence: Outcomes & Complications

MP15-16 - Impact of pelvic MRI parameters to predict urinary incontinence after robot-assisted laparoscopic prostatectomy.

Sat, Sep 22
10:00 AM - 12:00 PM

Introduction & Objective :

Urinary incontinence (UI) is one of the major prostate cancer (PCa) treatment-related morbidities. To date, it has been reported that the post-prostatectomy UI was related to width of pelvic floor muscles (PFM) and length of urethra. However, the detail of anatomical parameters has been unknown. This study aimed to investigate whether the preoperative pelvic parameters has a correlation with UI in addition to anatomical parameters of the urethra measured by magnetic resonance imaging (MRI).


Methods :

Five hundred and seventy-one patients with localized PCa underwent robot-assisted laparoscopic (RALP) in our institution from 2010 to 2017. The patients treated with single-surgeon were included. Those with follow-up less than 1-year and those who could not measure MRI parameters correctly were excluded. Preoperative prostate volume (PV), obturator internal muscle (OIM), anal sphincter muscle (ASM), levator ani muscle (LAM), urethra wall thickness (UWT), and membranous urethral length (MUL) were measured by MRI. The patients were divided in two groups depending on degree of the pad/day status 1-yr after RALP; pad free (pad 0) and non-pad free (pad ≧ 1 including security pad). 


Results :

Seventy patients were included in this retrospective study. Thirty-seven patients were classified pad free group and 33 patients were non-pad free group. There was significant difference between two groups in age (65 vs 70: p=0.03), MUL (12.1 vs 10.3: p<0.001), UWT (9.3 vs 9.8; p=0.03) and LAM (11.3 vs 9.2: p=0.001). However, PV, PSA and nerve-sparing (NS) had no significant difference in two groups. Multivariate logistic regression analyses revealed that MUL and LAM were predicting factors of UI 1-yr after RALP.


Conclusions :

The pelvic parameters measured by MRI before RALP is a useful tool to predict UI. The MUL in addition to LAM can predict postop UI.

Takuya Sadahira

Clinical Fellow
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Takuya Sadahira M.D.
2011-2013 Resident, Okayama University Hospital, Japan
2013-2016 Resident, Department of Urology, Okayama University Hospital, Japan
2016-present Clinical Fellow, Department of Urology, Okayama Medical Hospital, Japan

Yosuke Mitsui

Medical staff
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Yuki Maruyama

graduate student
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

I am a urologist at Okayama university in Japan. Thank you for your kindness.

Koichiro Wada

assistant professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Ryuta Tanimoto

assistant professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Yasuyuki Kobayashi

asisstant professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Motoo Araki

Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Masami Watanabe

Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Toyohiko Watanabe

associate professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan

Yasutomo Nasu

professor
Department of Urology; Okayama University Graduate School of Medicine; Okayama, Japan
Okayama, Okayama, Japan