Quantitative shoulder MRI for evaluating rotator cuff pathology

用于评估肩袖病理的定量肩部 MRI

• 批准号: 10673608
• 负责人: Misung Han
• 金额: $ 13.19万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10673608
• 关键词: 3-Dimensional; Acute; Affect; Age; American; Arthroscopic Surgical Procedures; Articular Range of Motion; Award; Biochemical; Biological Markers; Biology; Biopsy; Cells; Chemicals; Chronic; Clinical; Clinical Research; Collagen Fiber; Complication; Development; Diagnosis; Elbow; Elderly; Encapsulated; Evaluation; Exhibits; Failure; Fatty acid glycerol esters; Fibrosis; Goals; Grant; Harvest; Histologic; Histopathologic Grade; Image; Imaging Techniques; Infiltration; Information Systems; Injury; Intramuscular; Knowledge; Longitudinal Studies; Magnetic Resonance Imaging; Maps; Measurement; Measures; Methods; Morphology; Mus; Muscle; Muscular Atrophy; Musculoskeletal; Operative Surgical Procedures; Outcome; Pain; Pathology; Patient Outcomes Assessments; Patient Recruitments; Patient imaging; Patients; Physical Function; Physical therapy; Population; Process; Productivity; Quality of life; Recurrence; Relaxation; Reporting; Research; Research Design; Research Methodology; Research Project Grants; Rotator Cuff; Sampling; Shoulder; Shoulder Pain; Site; Source; Statistical Data Interpretation; Structure; Surgeon; Technical Expertise; Techniques; Tendon structure; Thick; Time; Tissues; Training; Upper Extremity; Visual Analogue Pain Scale; Water; design; disability; functional outcomes; healing; human old age (65+); imaging modality; imaging scientist; improved; mitochondrial uncoupling protein; muscle degeneration; muscle regeneration; older patient; optimal treatments; pain score; quantitative imaging; repaired; rotator cuff tear; statistics; surgery outcome; treatment strategy; uncoupling protein 1

PROJECT SUMMARY/ABSTRACT Rotator cuff tears are a common source of pain and disability in the upper extremity, occurring up to 50-80% in an elderly population. Surgical treatment is normally considered for patients who fail in non-operative management, have an acute tear, or are unable to participate in their normal daily activities despite a course of physical therapy. However, failure of tendon healing after rotator cuff surgery is a common complication. Multiple studies have demonstrated that preoperative tear size, patient age, and muscle quality are critical factors to determine surgical outcomes, but there is a need for improved non-invasive evaluation methods to assess tendon and muscle quality to determine optimal treatment strategy. The goals of this research project are to develop quantitative MRI methods for evaluating tendon and muscle quality, to assess the sensitivity of developed MRI methods to degeneration in comparison to histological analysis, and to evaluate tendon and muscle quality changes due to surgery. First, quantitative ultrashort echo- time methods will be developed to evaluate the rotator cuff tendons, which consist of highly-ordered collagen fiber structures resulting in a short T2 relaxation time. The quantified parameters will be compared between controls and patients having full-thickness rotator cuff tears, and MR quantification will be compared with semi- quantitative histologic grades of tendon samples acquired during surgery for the patient group. Second, muscle quantitative imaging techniques will be developed for two different purposes, to evaluate fibrosis and fat fractions simultaneously and to discriminate fat tissue as either beige or white fat. Muscle fibrosis has not been quantified much due to its short T2* relaxation time, but UTE multi-echo images will allow the quantification of muscle fibrosis as well. A potential of the presence of beige fat in the rotator cuff muscles after tendon tears has been shown, which is important because beige fat can promote muscle regeneration and healing. We will also develop accurate fat quantification technique to define beige fat. Third, a longitudinal study will be performed with patients having full-thickness rotator cuff tears before and after surgery using developed tendon and muscle evaluation techniques, and tendon and muscle quality changes due to surgery will be evaluated. Statistical analysis to determine important imaging metrics that affect clinical functional outcomes will be performed, too. This proposed approach includes comprehensive biomarkers of structural, micro-structural, and biochemical changes, and aims for fully quantitative imaging for more precise assessments. The proposed research and training plans are designed for the candidate to gain further knowledge in musculoskeletal biology and statistics, and expertise in clinical research design and methodologies while extending her MRI technical skills. The K01 grant award will help the candidate to be an independent imaging scientist in the musculoskeletal field.

项目总结/摘要 肩袖撕裂是上肢疼痛和残疾的常见原因， 老年人口。非手术治疗失败的患者通常考虑手术治疗。 管理，有急性撕裂，或无法参加他们的正常日常活动，尽管一个过程中， 物理治疗然而，肩袖手术后肌腱愈合失败是一种常见的并发症。多 研究表明，术前撕裂大小、患者年龄和肌肉质量是 确定手术结果，但需要改进的非侵入性评估方法来评估 肌腱和肌肉质量，以确定最佳治疗策略。 本研究计画的目标是发展量化的磁振造影方法来评估肌腱和肌肉 质量，以评估发达的MRI方法与组织学相比对变性的敏感性 分析，并评估肌腱和肌肉质量的变化，由于手术。首先，定量超短回波- 将开发时间方法来评估由高度有序的胶原蛋白组成的肩袖肌腱 纤维结构导致短的T2弛豫时间。将比较以下参数的量化参数： 对照组和肩袖全层撕裂患者，MR定量将与半定量进行比较。 患者组手术期间获得的肌腱样本的定量组织学分级。二、肌肉 定量成像技术将被开发用于两个不同的目的，以评估纤维化和脂肪分数 同时将脂肪组织区分为米色或白色脂肪。肌肉纤维化尚未量化 这主要是由于其短的T2* 弛豫时间，但UTE多回波图像将允许量化肌肉 纤维化也是。肌腱撕裂后肩袖肌肉中存在米色脂肪的可能性已经被证实， 这一点很重要，因为米色脂肪可以促进肌肉再生和愈合。我们还将开发 准确的脂肪定量技术来定义米色脂肪。第三，将对患者进行纵向研究 使用发达的肌腱和肌肉评估手术前后全层肩袖撕裂 技术，肌腱和肌肉质量的变化，由于手术将进行评估。统计分析来 确定影响临床功能结局的重要成像指标。这一拟议 方法包括结构、微观结构和生物化学变化的综合生物标志物， 进行全面的定量成像，以便进行更精确的评估。 拟议的研究和培训计划旨在让候选人获得更多的知识， 肌肉骨骼生物学和统计学，以及临床研究设计和方法的专业知识， 扩展她的核磁共振技术技能K 01补助金将帮助候选人成为一个独立的成像 肌肉骨骼领域的科学家

项目成果

Technology and Tool Development for BACPAC: Qualitative and Quantitative Analysis of Accelerated Lumbar Spine MRI with Deep-Learning Based Image Reconstruction at 3T.

• DOI: 10.1093/pm/pnad035
• 发表时间: 2023-08-04
• 期刊: PAIN MEDICINE
• 影响因子: 3.1
• 作者: Han, Misung;Bahroos, Emma;Hess, Madeline E.;Chin, Cynthia T.;Gao, Kenneth T.;Shin, David D.;Villanueva-Meyer, Javier E.;Link, Thomas M.;Pedoia, Valentina;Majumdar, Sharmila
• 通讯作者: Majumdar, Sharmila