Using a mechanistic classification scheme to identify the causes of anterior vaginal wall prolapse and develop a validated surgical planning system

使用机械分类方案来确定阴道前壁脱垂的原因并开发经过验证的手术计划系统

• 批准号: 9922982
• 负责人: Luyun Chen
• 金额: $ 31.13万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-05-04 至 2023-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9922982
• 关键词: 3-Dimensional; American; Anterior; Anterior vaginal wall prolapse; Apical; Biomechanics; Classification; Classification Scheme; Cluster Analysis; Comb animal structure; Complication; Consensus; Cystocele; Defect; Diagnosis; Dimensions; Distress; Failure; Fascia; Future; Geometry; Goals; Guidelines; Gynecologist; Hysterectomy; Impairment; Intervention; Knowledge; Lead; Link; Location; Magnetic Resonance Imaging; Measurement; Measures; Mechanics; Methods; Modeling; Muscle; Operative Surgical Procedures; Organ; Patients; Pelvic floor structure; Pelvis; Physical Examination; Postoperative Period; Ptosis; Randomized Controlled Trials; Reconstructive Surgical Procedures; Site; Statistical Data Interpretation; Stress; Structural defect; Structure; Subgroup; Support System; Surgeon; Surgical Models; Suspensions; System; Testing; Unnecessary Surgery; Vagina; Woman; base; biomechanical model; design; in silico; in vivo; individualized medicine; insight; levator ani muscle; models and simulation; operation; pathomechanics; pelvic organ prolapse; precision medicine; predictive modeling; repaired; simulation; surgery outcome; treatment planning; virtual

ABSTRACT Cystocele, or anterior vaginal wall prolapse (AVP), is the most common form of pelvic organ prolapse, a distressing condition requiring surgery in over 200,000 women each year. It is also the most frequent site of operative failure with a failure rate up to 30%. The successful, complication-free and durable treatment of this problem is one of the biggest challenges facing a gynecologist today. Our overarching hypothesis is that the pathomechanism of AVP involves mechanical interaction between three support systems: the vaginal wall itself (SV), fascia attachment factors (SF) (e.g., fascial attachments to the vaginal walls and the support of the upper vagina), and the muscular support provided by the levator ani (SM). We anticipate that primary structural impairment in one or more of these systems can lead to recoverable deformations in other systems (i.e., secondary deformations). However, one presently lacks the ability to identify for each woman the primary impairment sites and secondary recoverable deformation that lead to either insufficient repair or unnecessary surgery. Given this knowledge gap, we will develop a personalized structural-based prolapse diagnosis and surgical planning platform. As a first step, we propose to combine MR imaging and biomechanical modeling approaches to develop a validated virtual pelvic floor “testbed” that allow surgeons to systematically test pathomechanics hypotheses, develop patient-specific treatment plans and evaluate surgical outcomes. AIM 1. Establish classification criteria for AVP subtypes based on MRI and biomechanical measurements of 120 women with AVP and 30 women with normal support. AIM 2. Understand the pathomechanics of at least two different AIM 1 subtypes by comparing biomechanical model simulations with systematically implemented structural impairments to the AIM 1 MRI measurements. AIM 3. Develop and validate surgical prediction models to predict the biomechanical consequence of the surgical interventions on any of the support systems (SV, SF and SM) in a subset of 40 AIM 1 women with AVP who undergo prolapse surgery. Upon completion of this proposal, we can classify women with AVP into different mechanistic subtypes on which mechanistically-based surgery can be planned. We will identify the most critical parameters that determine which operation will be successful and use these to form the rational basis for the future randomize controlled trials to test these surgical approaches.

抽象的 膀胱膨出或阴道前壁脱垂 (AVP) 是盆腔最常见的形式 器官脱垂是一种令人痛苦的疾病，每年有超过 200,000 名女性需要接受手术。这是 也是手术失败最常见的部位，失败率高达30%。成功者， 无并发症且持久地治疗这一问题是面临的最大挑战之一 今天是一名妇科医生。我们的首要假设是 AVP 的病理机制涉及 三个支撑系统之间的机械相互作用：阴道壁本身（SV）、筋膜 附着因素（SF）（例如，阴道壁的筋膜附着和阴道壁的支撑） 上阴道），以及提肛肌（SM）提供的肌肉支撑。我们预计 这些系统中的一个或多个的主要结构损伤可能导致可恢复的 其他系统中的变形（即二次变形）。然而，目前缺乏 能够识别每位女性的主要损伤部位和次要可恢复部位 导致修复不充分或不必要的手术的变形。鉴于这些知识 差距，我们将开发基于结构的个性化脱垂诊断和手术计划 平台。作为第一步，我们建议将 MR 成像和生物力学建模结合起来 开发经过验证的虚拟盆底“测试台”的方法，使外科医生能够 系统地测试病理力学假设，制定针对患者的治疗计划 评估手术结果。 目的 1. 基于MRI和生物力学建立AVP亚型分类标准 对 120 名接受 AVP 的女性和 30 名接受正常支持的女性进行的测量。 AIM 2. 了解至少两种不同 AIM 1 亚型的病理机制 将生物力学模型模拟与系统实施的结构进行比较 AIM 1 MRI 测量的损伤。 目标 3. 开发并验证手术预测模型以预测生物力学 手术干预对任何支持系统（SV、SF 和 SM）的影响 40 名患有 AVP 且接受脱垂手术的 AIM 1 女性的子集​​。 完成此提案后，我们可以将患有 AVP 的女性分为不同的机制 可以计划基于机械的手术的亚型。我们将确定最 决定哪个操作将成功的关键参数，并使用这些参数来形成 未来测试这些手术方法的随机对照试验的合理基础。