3D Shearwave Elasticity Biomarker Development for Neuromuscular Disease

神经肌肉疾病的 3D 剪切波弹性生物标志物开发

基本信息

批准号：
10601107
负责人：
Kathryn Radabaugh Nightingale
金额：
$ 54.15万
依托单位：
DUKE UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-04-01 至 2025-12-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10601107
关键词：
3-Dimensional Acoustics Adoption Affect Age Algorithms Anisotropy Behavior Biological Markers Biomechanics Biopsy Breast Calibration Cessation of life Clinic Clinical Clinical Research Clinical Trials Complex Consumption Data Diagnosis Disease Disease Management Disease Progression Dual-Energy X-Ray Absorptiometry Duchenne muscular dystrophy Elastic Tissue Elasticity Exclusion Fiber Gender Geometry Glycogen storage disease type II Health Height Heterogeneity Image Imaging technology Isotropy Lesion Liver Fibrosis Magnetic Resonance Imaging Measurement Measures Medical Methods Modeling Modulus Monitor Muscle Muscle Fibers Muscle function Muscular Dystrophies Musculoskeletal Musculoskeletal System Myopathy Nature Neuromuscular Diseases Outcome Measure Pain Pathology Patient Participation Patients Performance Procedures Property Prostate Radiation Replacement Therapy Reporting Research Risk Sampling Scanning Skeletal Muscle Speed Staging System Testing Therapeutic Therapeutic Intervention Thyroid Gland Time Treatment Efficacy Ultrasonics Ultrasonography Viscosity Walking Weight X-Ray Computed Tomography biomarker development biomechanical test comorbidity compliance behavior cost data acquisition disability disease diagnosis efficacy evaluation elastography enzyme therapy gene therapy image reconstruction imaging approach imaging modality imaging system improved in vivo mechanical properties muscle strength novel novel therapeutics personalized medicine portability primary outcome prototype reconstruction screening sex side effect skeletal disorder soft tissue success tool treatment response ultrasound viscoelasticity

项目摘要

Neuromuscular disorders, including Duchenne's Muscular Dystrophy and Pompe disease, are progressive and often result in signiﬁcant disability and sometimes death. Encouragingly, novel enzyme replacement and ge- netic therapies are becoming available, but they are associated with detrimental side effects and assessing their efﬁcacy remains a challenge. Current methods used to assess muscle health are subjective, non-quantitative, and focus on muscle quantity and strength; however, measuring muscle quantity can over-estimate the amount of functional muscle, and muscle strength tests are affected by patient cooperation, pain, and co-morbidities. There is an urgent and unmet clinical need for a low-cost, non-invasive biomarker to accurately assess muscle health, monitor disease progression, and determine treatment response. Ultrasonic shear wave elasticity (SWE) imaging methods estimate the biomechanical properties of soft tissues, and these methods have demonstrated promise in the characterization of healthy and diseased muscle; however, commercially- available SWE methods are limited to estimating material parameters from a 2D imaging plane, and measure- ment variability and challenges with ﬁber alignment have limited clinical adoption. We have developed a 3D- SWE imaging system and advanced reconstruction algorithms with which we have obtained preliminary in vivo data that demonstrate, for the ﬁrst time, the complex 3D shearwave behaviors generated by SWE excitations in vivo in skeletal muscles, and have observed signiﬁcant differences between patients with myopathy that are consistent with clinical strength metrics. We have developed reconstruction algorithms that leverage the 3D-nature of these data to estimate multiple independent material properties, including: the longitudinal and transverse shear moduli, the shear anisotropy, the tensile anisotropy, and the viscosity along and across the muscle ﬁbers. We hypothesize that the more complete material characterization afforded by these measurements will provide improved biomarkers of muscle health. We now propose to optimize the se- quencing and minimize the 3D data acquisition time; to automate and validate our parameter reconstruction al- gorithms; and to quantify the parameter measurement accuracy and precision in calibrated elasticity phantoms. Finally, we propose a pilot clinical study in which we will quantify and compare 3D-SWE muscle parameters in vivo in patients with myopathy and muscular dystrophy and in healthy controls, evaluate the repeatability of these measurements, and assess their correlation with clinical measures of muscle health. Successful com- pletion of this project will provide non-invasive quantitative biomarkers of muscle health on a low-cost portable platform, enabling frequent measurement and longitudinal monitoring of disease progression and treatment response which will facilitate personalized and optimized neuromuscular disease man- agement.

神经肌肉疾病，包括Duchenne的肌肉营养不良和蓬松疾病，是进行性的，通常会导致显着的残疾，有时甚至导致死亡。令人鼓舞的是，新颖的酶替代和ge- 网络疗法已变得可用，但它们与有害的副作用有关，并评估其效率仍然是一个挑战。用于评估肌肉健康的当前方法是主观的，非定量的，专注于肌肉的数量和力量；但是，测量肌肉数量可以过度估计功能性肌肉和肌肉力量测试受患者的合作，疼痛和合并症的影响。对低成本，非侵入性生物标志物的紧急且未满足的临床需求可以准确评估肌肉健康，监测疾病进展并确定治疗反应。超声剪波弹性（SWE）成像方法估计软组织的生物力学特性，这些方法在表征健康和解剖的肌肉方面表现出了希望；但是，商业上 - 可用的SWE方法仅限于从2D成像平面估算材料参数，并测量 - 临床采用有限的临床采用有限的变异性和挑战。我们已经开发了一个3D- SWE成像系统和高级重建算法，我们已经获得了初步的在第一次证明SWE产生的复杂的3D剪力波行为的体内数据骨骼肌的体内激发，并观察到患者之间的显着差异与临床强度指标一致的肌病。我们开发了重建算法利用这些数据的3D天气来估计多个独立的材料属性，包括：纵向和横向剪切模量，剪切各向异性，拉伸各向异性以及沿着粘度并跨过肌肉纤维。我们假设，更完整的材料表征由这些测量将提供改进的肌肉健康生物标志物。我们现在建议优化SE- 淬灭和最小化3D数据采集时间；为了自动化和验证我们的参数重建al- gorithms;并量化校准弹性幻象的参数测量精度和精度。最后，我们提出了一项试验临床研究，其中我们将量化和比较3D-SWE肌肉参数体内肌病和肌肉营养不良症和健康对照中的体内，评估这些测量值，并评估它们与肌肉健康临床测量的相关性。成功com- 该项目的整体将在低成本上提供肌肉健康的非侵入性定量生物标志物便携式平台，实现疾病进展的经常测量和纵向监测和治疗反应，这将促进个性化和优化的神经肌肉疾病人分化。