Pathophysiology and Management of Long-term Complications After Transvaginal Urethral Diverticulectomy

Experience in conversion of symptomatic urethral diverticulum to asymptomatic status through surgery

Symptomatic urethral diverticulum (UD) is a rare disease typically treated with complete surgical resection, which often involves significant trauma and higher postoperative complication rates. This study introduces a surgical concept to convert "Symptomatic" UD into "Asymptomatic" UD. In our study, we retrospectively analyzed 21 symptomatic female UD patients treated at our center between January 2018 and May 2023, collecting baseline demographic and clinical data. All patients underwent diverticulectomy or partial resection and were followed postoperatively. Mean surgery time was 75.67 ± 28.85 min, with an average blood loss of 25.52 ± 10.69 ml. The median hospital stay was 6 days (interquartile range 3.5-7 days), and the median catheterization time was 15 days (interquartile range 14-21 days). According to the Clavien-Dindo classification, most complications were minor (Grade 1 = 2 patients, Grade 2 = 1 patient, above Grade 3a = 1 patient). Pre- and post-operation UDI-6 and QoL questionnaires showed that symptoms involved in Q1-4 all improved after surgery (P < 0.05) and quality of life score also increased (P < 0.05). The "symptom cure rate" reached 76.2%, suggesting that our surgical approach may offer a minimally invasive and effective option for managing UD.

Female urethral diverticulum complicated with urethral calculi

Female urethral diverticulum is a rare phenomenon, which is often discovered due to its associated complications. Delayed diagnosis is not uncommon due to the varied non-specific symptoms and clinical features. We are highlighting a case of female urethral diverticulum complicated with urethral calculi. She had recurrent lower urinary tract symptoms for the past 3 years and presented with recent dyspareunia. Transvaginal diverticulectomy and local extraction of the calculi successfully treated the condition. A high index of suspicion is required to successfully diagnose this condition early, not only for symptom relief but also to prevent complications.

Surgical management of bladder outlet obstruction due to functional and anatomical etiologies in women

INTRODUCTION

Bladder outlet obstruction (BOO) in women includes functional and anatomic etiologies. Primary bladder neck obstruction (PBNO), Fowler's syndrome (FS), and dysfunctional voiding (DV) are some examples of functional obstructions, whereas pelvic organ prolapse (POP), periurethral masses, and intragenic causes are some of the anatomic causes.

METHODS

This literature review describes the etiologies of female BOO, unique aspects of the workup and diagnosis, and the data for the standard surgical treatments and newer surgical techniques to treat women. Urethral stenosis and sling-related obstruction are treated in the other articles of this series. Where possible the focus is the efficacy and outcomes.

RESULTS

Treatment of PBNO using a transurethral incision of the bladder neck and injection of botulinum toxin in the bladder neck decreases the BOO. After the failure of conservative approaches, sacral neuromodulation (SNM) is effective for FS, while DV may benefit from SNM or botulinum toxin injections. Concerning POP, most surgeries have been reported to significantly improve a pre-existent BOO but the level of evidence is low. Benign urethral and periurethral masses may provoke BOO, and surgical excision usually resolves this condition.

CONCLUSION

Although most surgical treatments of BOO for functional and benign anatomical etiologies in women seem to be effective, data are scarce even for more common conditions like POP. Further studies are required to give better advice on the choice of surgical technique for these patients.

Evaluation and management of urethral and periurethral masses in women

PURPOSE OF REVIEW

Female periurethral masses are an uncommon occurrence. The purpose of this review is to describe etiologies of female urethral and periurethral masses and to provide an update on diagnosis and management.

RECENT FINDINGS

The most common causes of periurethral and urethral masses in women are urethral caruncles, urethral diverticula, and Skene's gland cysts. Urethral meatal lesions such as urethral caruncles and prolapse can be managed conservatively with topical estrogen therapy and close follow-up or should be excised in the setting of thrombosis, significant or recurrent bleeding, acute urinary retention, or persistent pain. Benign periurethral gland masses, such as Skene's gland cysts, Gartner's duct cysts, and Mullerian duct cysts, remain rare. Recent case series reveal a high rate of surgical management of these lesions with few complications. Urethral malignancy or malignant transformation of benign etiologies are even rarer but can be aggressive in nature and should be treated promptly.

SUMMARY

Nonspecific urinary and vaginal symptoms as well as similar physical presentations make diagnosis of urethral and periurethral lesions in females difficult. Magnetic resonance imaging is useful for differentiation of periurethral masses. The decision for conservative or surgical management is typically guided by patient symptom bother, as well as concern for urethral malignancy.

The Current State of Artificial Intelligence Application in Urology

Artificial intelligence (AI) is being used in many areas of healthcare, including disease diagnosis and personalized treatment and rehabilitation management. Medical AI research and development has primarily focused on diagnosis, prediction, treatment, and management as an aid to patient care. AI is being utilized primarily in the areas of personal healthcare and diagnostic imaging. In the field of urology, significant investments are being made in the development of urination monitoring systems in the field of personal healthcare and ureteral stricture and urinary stone diagnosis solutions in the field of diagnostic imaging. In addition, AI technology is also being applied in the field of neurogenic bladder to develop risk monitoring systems based on video and audio data. This paper examines the application of AI to urological diseases and discusses the current trends and future prospects of AI research.

Laparoscopic surgery for female posterior urethral bladder diverticulum with bladder outlet obstruction: A case report

INTRODUCTION

Bladder diverticula (BD) can be classified into congenital and acquired forms, with the latter accounting for approximately 90% of all cases, primarily among male patients. Although BD-associated anatomical bladder outlet obstruction (BOO) is uncommon, existing literature suggests that congenital BD are more frequently observed in male children and rarely in female children. While around 70% of acquired BD are linked to BOO secondary to benign prostatic hyperplasia in male patients, clinical reports of female BD are less common. Furthermore, cases of female BD located posterior to the urethra, which lead to voiding difficulties, are exceedingly rare.

CASE PRESENTATION

Herein, we present a case of laparoscopic treatment in a 53-year-old female patient diagnosed with congenital bladder diverticulum causing progressively worsening dysuria. Voiding cystourethrography revealed a soft cystic protrusion of the posterior urethral wall during voiding, which reinforced the patient's symptoms. Urodynamic examination showed elevated detrusor muscle contraction during voiding, a reduced urinary flow rate, and P/Q values indicative of significant BOO. Considering the patient's clinical condition, we performed laparoscopic bladder diverticulectomy, partial urethral croppingplasty, and cystoplasty.

RESULTS

The laparoscopic bladder diverticulectomy, partial urethral croppingplasty, and cystoplasty procedures were completed thoroughly and with great success. However, complete removal of the diverticular epithelium proved challenging, resulting in an overall operative time of approximately 3 hours and 32 minutes. At the postoperative follow-up, the patient presented with symptoms of a lower urinary tract infection for a week, which were effectively resolved with oral antibiotics. At the 8-month follow-up, the patient reported normal urination and the absence of any discomfort during urination.

CONCLUSION

Female bladder outlet obstruction resulting from posterior urethral BD can be challenging to visualize during transurethral cystoscopy, especially with limited angulation, and may even be overlooked. Furthermore, conventional transvaginal diverticulectomy is often difficult to perform effectively. Therefore, laparoscopic bladder diverticulectomy, partial urethral croppingplasty, and cystoplasty are considered appropriate treatment options for such cases.

Development and Evaluation of Urolithiasis Detection Technology Based on a Multimethod Algorithm

Purpose: In this paper, we propose an optimal ureter stone detection model utilizing multiple artificial intelligence technologies. Specifically, the proposed model of urinary tract stone detection merges an artificial intelligence model and an image processing model, resulting in a multimethod approach.Methods: We propose an optimal urinary tract stone detection algorithm based on artificial intelligence technology. This method was intended to increase the accuracy of urinary tract stone detection by combining deep learning technology (Fast R-CNN) and image processing technology (Watershed).Results: As a result of deriving the confusion matrix, the sensitivity and specificity of urinary tract stone detection were calculated to be 0.90 and 0.91, and the accuracy for their position was 0.84. This value was higher than 0.8, which is the standard for accuracy. This finding confirmed that accurate guidance to the stones area was possible when the developed platform was used to support actual surgery.Conclusions: The performance evaluation of the method proposed herein indicated that it can effectively play an auxiliary role in diagnostic decision-making with a clinically acceptable range of safety. In particular, in the case of ambush stones or urinary stones accompanying ureter polyps, the value that could be obtained through combination therapy based on diagnostic assistance could be evaluated.

New Trends in Innovative Technologies Applying Artificial Intelligence to Urinary Diseases

Artificial intelligence (AI) is used in various fields of medicine, with applications encompassing all areas of medical services, such as the development of medical robots, the diagnosis and personalized treatment of diseases, and personalized healthcare. Medical AI research and development have been largely focused on diagnosis, prediction, treatment, and management as an auxiliary means of patient care. AI is mainly used in the fields of personal healthcare and diagnostic imaging. In urology, substantial investments are being made in the development of urination monitoring systems in the personal healthcare field and diagnostic solutions for ureteral stricture and urolithiasis in the diagnostic imaging field. This paper describes AI applications for urinary diseases and discusses current trends and future perspectives in AI research.

A Study on the Optimal Artificial Intelligence Model for Determination of Urolithiasis

Purpose

This paper aims to develop a clinical decision support system (CDSS) that can help detect the stone that is most important to the diagnosis of urolithiasis. Among them, especially for the development of artificial intelligence (AI) models that support a final judgment in CDSS, we would like to study the optimal AI model by comparing and evaluating them.

Methods

This paper proposes the optimal ureter stone detection model using various AI technologies. The use of AI technology compares and evaluates methods such as machine learning (support vector machine), deep learning (ResNet-50, Fast R-CNN), and image processing (watershed) to find a more effective method for detecting ureter stones.

Results

The final value of sensitivity, which is calculated using true positive (TP) and false negative and is a measure of the probability of TP results, showed high recognition accuracy, with an average value of 0.93 for ResNet-50. This finding confirmed that accurate guidance to the stones area was possible when the developed platform was used to support actual surgery.

Conclusions

The general situation in the most effective way to the detection stone can be found. But a variety of variables may be slightly different the difference through the term could tell. Future works, on urological diseases, are diverse and the research will be expanded by customizing AI models specialized for those diseases.

Development of an Artificial Intelligence-Based Support Technology for Urethral and Ureteral Stricture Surgery

Purpose

This paper proposes a technological system that uses artificial intelligence to recognize and guide the operator to the exact stenosis area during endoscopic surgery in patients with urethral or ureteral strictures. The aim of this technological solution was to increase surgical efficiency.

Methods

The proposed system utilizes the ResNet-50 algorithm, an artificial intelligence technology, and analyzes images entering the endoscope during surgery to detect the stenosis location accurately and provide intraoperative clinical assistance. The ResNet-50 algorithm was chosen to facilitate accurate detection of the stenosis site.

Results

The high recognition accuracy of the system was confirmed by an average final sensitivity value of 0.96. Since sensitivity is a measure of the probability of a true-positive test, this finding confirms that the system provided accurate guidance to the stenosis area when used for support in actual surgery.

Conclusions

The proposed method supports surgery for patients with urethral or ureteral strictures by applying the ResNet-50 algorithm. The system analyzes images entering the endoscope during surgery and accurately detects stenosis, thereby assisting in surgery. In future research, we intend to provide both conservative and flexible boundaries of the strictures.