Glickman Urological and Kidney Institute, Cleveland Clinic, Cleveland, OH, USA.
Cleveland Clinic Lerner College of Medicine, Cleveland Clinic, Cleveland, OH, USA.
Curr Urol Rep. 2024 Sep 20;26(1):2. doi: 10.1007/s11934-024-01232-6.
The estimation of penile curvature is an essential component in the assessment of both Peyronie's disease and hypospadias-associated congenital penile curvature, as the degree of curvature can significantly impact treatment decision-making. However, there is a lack of standardization in curvature assessment and current methodologies are prone to inaccuracies. With the rise of artificial intelligence (AI) in urology, new research has explored its applications in penile curvature assessment. This review aims to evaluate the current uses of AI and other automated platforms for assessing penile curvature.
Several novel and promising tools have been developed to estimate penile curvature, some utilizing AI-driven models and others employing automated computational models. These platforms aim to improve curvature assessment in various settings, including at-home evaluation of Peyronie's disease, in-office assessments using three-dimensional (3D) methodologies, and preoperative evaluations for hypospadias repair. In general, these new platforms produce highly accurate and reproducible angle estimates in non-clinical studies, however their effectiveness and relation to patient outcomes has had limited evaluation in clinical settings. Significant advancements have been made in the assessment and estimation of penile curvature in both Peyronie's and pediatric patients, largely driven by AI and other automated platforms. Continued research is needed to validate these findings in clinical studies, confirm their efficacy, and assess their feasibility for real-world applications.
阴茎弯曲的评估是评估 Peyronie 病和尿道下裂相关先天性阴茎弯曲的重要组成部分,因为弯曲的程度会显著影响治疗决策。然而,目前在弯曲评估方面缺乏标准化,而且当前的方法容易出现不准确的情况。随着人工智能(AI)在泌尿科的兴起,新的研究已经探索了其在阴茎弯曲评估中的应用。本综述旨在评估 AI 和其他自动化平台在评估阴茎弯曲方面的当前用途。
已经开发了几种新颖且有前途的工具来估计阴茎弯曲,其中一些利用 AI 驱动的模型,另一些则采用自动化计算模型。这些平台旨在改善各种情况下的弯曲评估,包括在家中评估 Peyronie 病、使用三维(3D)方法在办公室评估以及在尿道下裂修复的术前评估。通常情况下,这些新平台在非临床研究中产生了高度准确和可重复的角度估计值,但是它们在临床环境中的有效性和与患者结局的关系尚未得到充分评估。在 Peyronie 病和儿科患者的阴茎弯曲评估和估计方面取得了重大进展,这主要得益于 AI 和其他自动化平台。需要进一步的研究来在临床研究中验证这些发现,确认其疗效,并评估其在实际应用中的可行性。