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Rapid Low-Cost Quantitative 3D MRI and Gait Assessment of the Knee

Rapid Low-Cost Quantitative 3D MRI and Gait Assessment of the Knee
快速、低成本定量 3D MRI 和膝关节步态评估
批准号:
10671520
负责人:
Brian Andrew Hargreaves
金额:
$65.93万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2020
资助国家:
美国
项目状态:
未结题
起止时间:
2020-08-15 至 2025-06-30
关键词:
3-DimensionalAffectAmericanAnterior Cruciate LigamentArticulationBilateralBiochemicalBiomechanicsBone MarrowBone SpurCartilageChronicClinicalCluster AnalysisCollaborationsConnective TissueCost MeasuresCoupledDataData PoolingDegenerative polyarthritisDetectionDevelopmentDiagnosisDiagnosticDiffusionDiffusion Magnetic Resonance ImagingDiseaseEnrollmentEnvironmentEquipmentEtiologyEvaluationFemaleFemurFibrocartilagesFutureGaitGait abnormalityGoalsHealthHuman ResourcesImageInflammatoryInjectionsInjuryInterventionJointsKellgren-Lawrence gradeKneeKnee OsteoarthritisLeftLengthLesionLigamentsMagnetic Resonance ImagingManualsMapsMeasurementMeasuresMeniscus structure of jointMethodsMorphologyMotionMotivationOrthopedicsOutputPainPatient TriagePatientsPopulationProtocols documentationProtonsQuality of lifeQuantitative EvaluationsRadiationReaderReplacement ArthroplastyResearchResearch PersonnelRiskRisk FactorsRoentgen RaysSamplingScanningSex DifferencesSliceStructureSurfaceSynovitisTechniquesTendon structureTestingThickTimeTissuesTraumatic ArthropathyVisualizationanalysis pipelineanterior cruciate ligament injuryanterior cruciate ligament ruptureautomated analysisbiomechanical testbonecohortcostdeep learningdensitydisabilitydisease phenotypedisorder riskearly onseteffective therapygait examinationhigh body mass indeximage reconstructionimprovedkinematicslearning classifiermeniscus injuryminimally invasivenovelprimary outcomequantitative imagingradiological imagingreconstructionresearch studysensorskillssocietal coststherapy developmenttissue biomarkersultra high resolution

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中文摘要
翻译
项目摘要 动机:骨关节炎(OA)是一种痛苦的疾病,影响着数千万美国人,但情况并不乐观 了解,导致缺乏治疗。使广泛研究风险因素的低成本方法成为可能, 骨性关节炎的发病和早期进展将有助于更好地了解骨性关节炎的机制、治疗进展、 以及根据特定的fic疾病表型对患者进行不同治疗的分诊。 多种系统因素、生化因素和其他危险因素与骨性关节炎有关,但病因各不相同(fi)。 在缓慢的进程中隔离和研究邪教。目前,骨性关节炎的诊断为关节间隙狭窄。 放射学,在干预措施可以有效的阶段。磁共振成像(MRI)- FERS对形态和生化变化敏感,但大多数方法不适用于广泛的临床 或研究用途。通常核磁共振检查只研究一个膝盖,排除了比较膝盖的机会。SIM卡- 通常,生物力学评估通常需要使用先进的和很少获得的设备进行大量测试- 由技术人员进行数据和时间密集型分析,这对广泛使用来说是一项挑战。 我们已经用定量松弛测量法和扩散图显示了双膝快速、同时的3D扫描- 结缔组织的PING,结合在人群中验证的纵向变化的新可视化 伴有前十字韧带(ACL)撕裂。我们已经开发了全自动软骨和半月板切割机- 分割以简化后处理。(我们的自动软骨分割变异性接近于 读者之间的可变性。)我们现在建议将MRI采集、重建和分析技术结合起来- 将简单的运动学测量转化为广泛适用的低成本成像和生物力学测试, 我们将在前交叉韧带损伤的受试者和不同Kellgren-Lawrence骨性关节炎分级的受试者中进行验证。 方法:我们将首先开发一个健壮的5到8分钟的双侧膝关节核磁共振检查,使用EffiEncient 3D 各向同性获取和新的基于深度学习的图像重建。这之后将是自动的 3块膝盖板的软骨分割和定量分析(厚度、T2、弥散)并自动完成 滑膜炎、骨髓和软骨损伤的半定量评分方法。惯性测量 单位(IMU)将用于测量运动学和步态不对称性。我们将继续在acl pa学习- 目的:验证技术并开发成像和生物力学测量的不对称性分析。 最后,在具有不同的办公自动化等级的受试者中,我们将评估总体低成本方法的潜力 不对称性和纵向变化测量进展和骨关节炎分级。 SignifiCance:该项目将开发一个采集和分析管道,以量化膝关节变化和 在骨性关节炎之前的左/右不对称。我们将描述特发性骨关节炎受试者和前交叉韧带的治疗方法。 受伤的受试者有创伤后骨性关节炎的风险。非常低的目标成本,低于120美元/受试者,最终将实现 对不同类型的骨性关节炎的早期发病和进展的广泛研究,导致更早和更好的治疗。
英文摘要
Project Abstract Motivation: Osteoarthritis (OA) is a painful disease that affects tens of millions of Americans, but is poorly understood, resulting in a lack of treatments. Enabling low-cost approaches for widespread study of risk factors, onset and early progression of OA will enable better understanding of OA mechanisms, treatment development, and triage of patients to different treatments based on specific disease phenotypes. Multiple systemic factors, biochemical factors, and other risk factors are associated with OA, but causes are diffi- cult to isolate and study during slow progression. Currently OA is diagnosed as joint-space narrowing using X-ray radiography, at a stage well beyond when interventions can be effective. Magnetic resonance imaging (MRI) of- fers sensitivity to morphologic and biochemical changes, but most methods are impractical for widespread clinical or research use. Usually MRI exams study only one knee, precluding the opportunity to compare knees. Sim- ilarly, biomechanics assessment typically requires numerous tests using advanced and rarely-available equip- ment and time-intensive analysis by skilled personnel, making this a challenge for widespread use. We have shown rapid, simultaneous 3D scanning of both knees with quantitative relaxometry and diffusion map- ping of connective tissues, combined with novel visualization of longitudinal change validated in a population with anterior cruciate ligament (ACL) tears. We have developed fully-automated cartilage and meniscus seg- mentation to simplify post-processing. (Our automated cartilage segmentation variability approaches that of reader-to-reader variability.) We now propose to combine MRI acquisition, reconstruction and analysis tech- niques with simple measures of kinematics into a widely applicable low-cost imaging and biomechanical test, which we will validate in subjects with ACL-injury and subjects with varying Kellgren-Lawrence grades of OA. Approach: We will begin by developing a robust 5-to-8-minute bilateral knee MRI exam, using an efficient 3D isotropic acquisition and novel deep-learning based image reconstructions. This will be followed with automated cartilage segmentation and quantitative analysis (thickness, T2, diffusion) of all 3 knee plates and automated semiquantitative scoring approaches for synovitis, bone marrow and cartilage lesions. Inertial measurement units (IMUs) will be used to measure kinematics, and gait asymmetries. We will continue our studies in ACL pa- tients to validate techniques and to develop asymmetry analyses for both imaging and biomechanical measures. Finally, in subjects with varying OA grade, we will evaluate the potential of the overall low-cost approach to relate asymmetry and longitudinal change measures to progression and OA grade. Significance: This project will develop an acquisition and analysis pipeline to quantify knee changes and left/right asymmetries that precede OA. We will characterize methods in idiopathic OA subjects and ACL- injured subjects at risk of post-traumatic OA. The very low target cost, under $120/subject, will ultimately enable widespread study of early onset and progression of different OA types, leading to earlier and better treatments.
期刊论文(26)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1186/s13075-021-02436-8
发表时间: 2021-02-13
期刊: Arthritis research & therapy
影响因子: 4.9
作者: [de Vries BA, Breda SJ, Sveinsson B, McWalter EJ, Meuffels DE, Krestin GP, Hargreaves BA, Gold GE, Oei EHG]
通讯作者: Oei EHG
Improving Data-Efficiency and Robustness of Medical Imaging Segmentation Using Inpainting-Based Self-Supervised Learning.
使用基于介入的自我监督学习来改善医学成像分割的数据效率和鲁棒性。
DOI: 10.3390/bioengineering10020207
发表时间: 2023-02-04
期刊: Bioengineering (Basel, Switzerland)
影响因子: --
作者: []
通讯作者:
DOI: 10.1038/s41591-024-02855-5
发表时间: 2023-09
期刊: Nature medicine
影响因子: 82.9
作者: [Dave Van Veen;Cara Van Uden;Louis Blankemeier;Jean-Benoit Delbrouck;Asad Aali;Christian Blüthgen;A. Pareek;Malgorzata Polacin;William Collins;Neera Ahuja;C. Langlotz;Jason Hom;S. Gatidis;John M. Pauly;Akshay S. Chaudhari]
通讯作者: Dave Van Veen;Cara Van Uden;Louis Blankemeier;Jean-Benoit Delbrouck;Asad Aali;Christian Blüthgen;A. Pareek;Malgorzata Polacin;William Collins;Neera Ahuja;C. Langlotz;Jason Hom;S. Gatidis;John M. Pauly;Akshay S. Chaudhari
DOI: 10.1002/jmri.27331
发表时间: 2021-08
期刊: Journal of magnetic resonance imaging : JMRI
影响因子: --
作者: [Chaudhari AS, Sandino CM, Cole EK, Larson DB, Gold GE, Vasanawala SS, Lungren MP, Hargreaves BA, Langlotz CP]
通讯作者: Langlotz CP
18
    Improved Diagnostic MRI around Metallic Implants
    • 批准号:
      10367211
    • 项目类别:
    • 资助金额:
      $66.24万
    • 财政年份:
      2022
    • 负责人:
      Brian Andrew Hargreaves
    • 依托单位:
    Improved Diagnostic MRI around Metallic Implants
    • 批准号:
      10558660
    • 项目类别:
    • 资助金额:
      $59.68万
    • 财政年份:
      2022
    • 负责人:
      Brian Andrew Hargreaves
    • 依托单位:
    Rapid Low-Cost Quantitative 3D MRI and Gait Assessment of the Knee
    • 批准号:
      10032904
    • 项目类别:
    • 资助金额:
      $65.83万
    • 财政年份:
      2020
    • 负责人:
      Brian Andrew Hargreaves
    • 依托单位:
    Rapid Low-Cost Quantitative 3D MRI and Gait Assessment of the Knee
    • 批准号:
      10441342
    • 项目类别:
    • 资助金额:
      $66.45万
    • 财政年份:
      2020
    • 负责人:
      Brian Andrew Hargreaves
    • 依托单位:
    海外基金