A standardized method to measure the membranous urethral length (MUL) on MRI of the prostate with high inter- and intra-observer agreement

Recent developments in diagnostic ultrasound for lower urinary tract function

Ultrasonography (US) is an essential tool in the clinical management of lower urinary tract dysfunction (LUTD), including lower urinary tract symptoms, overactive bladder, and benign prostatic hyperplasia, in which prostatic volume and post-void residual volume are routinely used to evaluate the pathophysiological characteristics of afflicted patients. US can also be employed to diagnose hydronephrosis and bladder calculus as complications of severe LUTD. Moreover, US is essential for identifying pathophysiological characteristics and surgical indications, predicting disease development and drug efficacy, and monitoring bladder function improvement by means of such parameters as bladder wall thickness, prostatic urethral length, intravesical prostatic protrusion, and prostatic urethral angulation/angle. Herein, I narratively review the recent advances in US approaches for the management of LUTD, especially in adult males.

EAU-EANM-ESTRO-ESUR-ISUP-SIOG Guidelines on Prostate Cancer-2024 Update. Part I: Screening, Diagnosis, and Local Treatment with Curative Intent

BACKGROUND AND OBJECTIVE

The European Association of Urology (EAU)-European Association of Nuclear Medicine (EANM)-European Society for Radiotherapy and Oncology (ESTRO)-European Society of Urogenital Radiology (ESUR)-International Society of Urological Pathology (ISUP)-International Society of Geriatric Oncology (SIOG) guidelines provide recommendations for the management of clinically localised prostate cancer (PCa). This paper aims to present a summary of the 2024 version of the EAU-EANM-ESTRO-ESUR-ISUP-SIOG guidelines on the screening, diagnosis, and treatment of clinically localised PCa.

METHODS

The panel performed a literature review of all new data published in English, covering the time frame between May 2020 and 2023. The guidelines were updated, and a strength rating for each recommendation was added based on a systematic review of the evidence.

KEY FINDINGS AND LIMITATIONS

A risk-adapted strategy for identifying men who may develop PCa is advised, generally commencing at 50 yr of age and based on individualised life expectancy. The use of multiparametric magnetic resonance imaging in order to avoid unnecessary biopsies is recommended. When a biopsy is considered, a combination of targeted and regional biopsies should be performed. Prostate-specific membrane antigen positron emission tomography imaging is the most sensitive technique for identifying metastatic spread. Active surveillance is the appropriate management for men with low-risk PCa, as well as for selected favourable intermediate-risk patients with International Society of Urological Pathology grade group 2 lesions. Local therapies are addressed, as well as the management of persistent prostate-specific antigen after surgery. A recommendation to consider hypofractionation in intermediate-risk patients is provided. Patients with cN1 PCa should be offered a local treatment combined with long-term intensified hormonal treatment.

CONCLUSIONS AND CLINICAL IMPLICATIONS

The evidence in the field of diagnosis, staging, and treatment of localised PCa is evolving rapidly. These PCa guidelines reflect the multidisciplinary nature of PCa management.

PATIENT SUMMARY

This article is the summary of the guidelines for "curable" prostate cancer. Prostate cancer is "found" through a multistep risk-based screening process. The objective is to find as many men as possible with a curable cancer. Prostate cancer is curable if it resides in the prostate; it is then classified into low-, intermediary-, and high-risk localised and locally advanced prostate cancer. These risk classes are the basis of the treatments. Low-risk prostate cancer is treated with "active surveillance", a treatment with excellent prognosis. For low-intermediary-risk active surveillance should also be discussed as an option. In other cases, active treatments, surgery, or radiation treatment should be discussed along with the potential side effects to allow shared decision-making.

Membranous urethral length is the single independent predictor of urinary continence recovery at 12 months following Retzius-sparing robot-assisted radical prostatectomy

The influence of anatomical parameters on urinary continence (UC) after Retzius-sparing robot-assisted radical prostatectomy (RS-RARP) remains uncharted. Our objective was to evaluate their association with UC at 3, 6 and 12 months post-operatively. Data from patients who underwent RS-RARP were prospectively collected. Continence was defined as no pad use. Anatomic variables were measured on preoperative magnetic resonance imaging (MRI). Regression analyses were performed to identify predictors of UC at each time point. We included 158 patients with a median age of 60 years, most of whom had a localized tumor (≤ cT2). On multivariate analyses, at 3 months post-surgery, urinary incontinence (UI) rises with age, odds ratio (OR) 1.07 [95% confidence interval (CI) 1.004-1.142] and with prostate volume (PV), OR 1.029 (95% CI 1.006-1.052); it reduces with longer membranous urethral length (MUL), OR 0.875 (95% CI 0.780-0.983) and with higher membranous urethral volume (MUV), OR 0.299 (95% CI 0.121-0.737). At 6 months, UI rises with PV, OR 1.033 (95% CI 1.011-1.056) and decreases with MUV, OR 0.1504 (95% CI 0.050-0.444). Significantly, at 12 months post-surgery, the only predictor of UI is MUL, OR 0.830 (95% CI 0.706-0.975), establishing a threshold associated with a risk of UI of 5% (MUL > 15 mm) in opposition to a risk of 25% (MUL < 10 mm). This single institutional study requires external validation. To our knowledge, this is the first prospective cohort study supporting MUL as the single independent predictor of UC at 12 months post-surgery. By establishing MUL thresholds, we enable precise patient counseling.

Membranous urethral length measurement on preoperative MRI to predict incontinence after radical prostatectomy: a literature review towards a proposal for measurement standardization

OBJECTIVES

To investigate the membranous urethral length (MUL) measurement and its interobserver agreement, and propose literature-based recommendations to standardize MUL measurement for increasing interobserver agreement. MUL measurements based on prostate MRI scans, for urinary incontinence risk assessment before radical prostatectomy (RP), may influence treatment decision-making in men with localised prostate cancer. Before implementation in clinical practise, MRI-based MUL measurements need standardization to improve observer agreement.

METHODS

Online libraries were searched up to August 5, 2022, on MUL measurements. Two reviewers performed article selection and critical appraisal. Papers reporting on preoperative MUL measurements and urinary continence correlation were selected. Extracted information included measuring procedures, MRI sequences, population mean/median values, and observer agreement.

RESULTS

Fifty papers were included. Studies that specified the MRI sequence used T2-weighted images and used either coronal images (n = 13), sagittal images (n = 18), or both (n = 12) for MUL measurements. 'Prostatic apex' was the most common description of the proximal membranous urethra landmark and 'level/entry of the urethra into the penile bulb' was the most common description of the distal landmark. Population mean (median) MUL value range was 10.4-17.1 mm (7.3-17.3 mm), suggesting either population or measurement differences. Detailed measurement technique descriptions for reproducibility were lacking. Recommendations on MRI-based MUL measurement were formulated by using anatomical landmarks and detailed descriptions and illustrations.

CONCLUSIONS

In order to improve on measurement variability, a literature-based measuring method of the MUL was proposed, supported by several illustrative case studies, in an attempt to standardize MRI-based MUL measurements for appropriate urinary incontinence risk preoperatively.

CLINICAL RELEVANCE STATEMENT

Implementation of MUL measurements into clinical practise for personalized post-prostatectomy continence prediction is hampered by lack of standardization and suboptimal interobserver agreement. Our proposed standardized MUL measurement aims to facilitate standardization and to improve the interobserver agreement.

KEY POINTS

• Variable approaches for membranous urethral length measurement are being used, without detailed description and with substantial differences in length of the membranous urethra, hampering standardization. • Limited interobserver agreement for membranous urethral length measurement was observed in several studies, while preoperative incontinence risk assessment necessitates high interobserver agreement. • Literature-based recommendations are proposed to standardize MRI-based membranous urethral length measurement for increasing interobserver agreement and improving preoperative incontinence risk assessment, using anatomical landmarks on sagittal T2-weighted images.

Automated pelvic MRI measurements associated with urinary incontinence for prostate cancer patients undergoing radical prostatectomy

BACKGROUND

Pelvic morphological parameters on magnetic resonance imaging (MRI), such as the membranous urethral length (MUL), can predict urinary incontinence after radical prostatectomy but are prone to interobserver disagreement. Our objective was to improve interobserver agreement among radiologists in measuring pelvic parameters using deep learning (DL)-based segmentation of pelvic structures on MRI scans.

METHODS

Preoperative MRI was collected from 167 prostate cancer patients undergoing radical prostatectomy within our regional multicentric cohort. Two DL networks (nnU-Net) were trained on coronal and sagittal scans and evaluated on a test cohort using an 80/20% train-test split. Pelvic parameters were manually measured by three abdominal radiologists on raw MRI images and with the use of DL-generated segmentations. Automated measurements were also performed for the pelvic parameters. Interobserver agreement was evaluated using the intraclass correlation coefficient (ICC) and the Bland-Altman plot.

RESULTS

The DL models achieved median Dice similarity coefficient (DSC) values of 0.85-0.97 for coronal structures and 0.87-0.98 for sagittal structures. When radiologists used DL-generated segmentations of pelvic structures, the interobserver agreement for sagittal MUL improved from 0.64 (95% confidence interval 0.28-0.83) to 0.91 (95% CI 0.84-0.95). Furthermore, there was an increase in ICC values for the obturator internus muscle from 0.74 (95% CI 0.42-0.87) to 0.86 (95% CI 0.75-0.92) and for the levator ani muscle from 0.40 (95% CI 0.05-0.66) to 0.61 (95% CI 0.31-0.78).

CONCLUSIONS

DL-based automated segmentation of pelvic structures improved interobserver agreement in measuring pelvic parameters on preoperative MRI scans.

RELEVANCE STATEMENT

The implementation of deep learning segmentations allows for more consistent measurements of pelvic parameters by radiologists. Standardized measurements are crucial for incorporating these parameters into urinary continence prediction models.

KEY POINTS

• DL-generated segmentations improve interobserver agreement for pelvic measurements among radiologists. • Membranous urethral length measurement improved from substantial to almost perfect agreement. • Artificial intelligence enhances objective pelvic parameter assessment for continence prediction models.

An artificial intelligence method for predicting postoperative urinary incontinence based on multiple anatomic parameters of MRI

Background

Deep learning methods are increasingly applied in the medical field; however, their lack of interpretability remains a challenge. Captum is a tool that can be used to interpret neural network models by computing feature importance weights. Although Captum is an interpretable model, it is rarely used to study medical problems, and there is a scarcity of data regarding MRI anatomical measurements for patients with prostate cancer after undergoing Robotic-Assisted Radical Prostatectomy (RARP). Consequently, predictive models for continence that use multiple types of anatomical MRI measurements are limited.

Methods

We explored the energy efficiency of deep learning models for predicting continence by analyzing MRI measurements. We analyzed and compared various statistical models and provided reference examples for the clinical application of interpretable deep-learning models. Patients who underwent RARP at our institution between July 2019 and December 2020 were included in this study. A series of clinical MRI anatomical measurements from these patients was used to discover continence features, and their impact on continence was primarily evaluated using a series of statistical methods and computational models.

Results

Age and six other anatomical measurements were identified as the top seven features of continence by the proposed model UINet7 with an accuracy of 0.97, and the first four of these features were also found by primary statistical analysis.

Conclusions

This study fills the gaps in the in-depth investigation of continence features after RARP due to the limitations of clinical data and applicable models. We provide a pioneering example of the application of deep-learning models to clinical problems. The interpretability analysis of deep learning models has the potential for clinical applications.

Prostate MRI for Improving Personalized Risk Prediction of Incontinence and Surgical Planning: The Role of Membranous Urethral Length Measurements and the Use of 3D Models

Prostate MRI has an important role in prostate cancer diagnosis and treatment, including detection, the targeting of prostate biopsies, staging and guiding radiotherapy and active surveillance. However, there are other ''less well-known'' applications which are being studied and frequently used in our highly specialized medical center. In this review, we focus on two research topics that lie within the expertise of this study group: (1) anatomical parameters predicting the risk of urinary incontinence after radical prostatectomy, allowing more personalized shared decision-making, with special emphasis on the membranous urethral length (MUL); (2) the use of three-dimensional models to help the surgical planning. These models may be used for training, patient counselling, personalized estimation of nerve sparing and extracapsular extension and may help to achieve negative surgical margins and undetectable postoperative PSA values.