Quantitative Multiparametric MRI to Assess the Effect of Stem Cell Therapy on Chronic Low Back Pain
定量多参数 MRI 评估干细胞疗法对慢性腰痛的效果
基本信息
- 批准号:10454354
- 负责人:
- 金额:$ 71.58万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2014
- 资助国家:美国
- 起止时间:2014-08-01 至 2025-07-31
- 项目状态:未结题
- 来源:
- 关键词:AgingAmericanAnatomyBack PainBiologyChemicalsChronic low back painClinicalConsumptionDataDehydrationDetectionDevelopmentDiagnosisDiagnostic ProcedureDiffusionDimensionsFamily suidaeGoalsGrantHeightHumanImageImaging TechniquesImmobilizationIndividualInjectionsIntervertebral disc structureLongitudinal StudiesLow Back PainMagnetic Resonance ImagingMapsMeasuresMedicalMesenchymal Stem CellsMetabolismMethodsMiniature SwineModelingMolecularMonitorMorbidity - disease rateMotionNatural regenerationNatureOccupationsOperative Surgical ProceduresPainPathologicPatientsPhysiciansProcessPropertyProtonsPublishingReproducibilityScanningSourceSpinal FusionSystemT2 weighted imagingTechniquesTherapeutic EffectTimeTissuesUnited StatesVertebral columnWaterWorkaccurate diagnosisbasebone marrow mesenchymal stem cellcardiovascular imagingdata acquisitiondisabilityhealthy volunteerimaging modalityimprovedintervertebral disk degenerationmolecular markermultitasknew therapeutic targetnucleus pulposuspain patientpain reliefparametric imagingporcine modelreconstructionsolutestem cell therapystem cellstargeted treatmenttooltreatment response
项目摘要
PROJECT SUMMARY
The goal of the proposed project is to develop multiparametric mapping magnetic resonance imaging (MRI)
techniques to assess the effect of stem cell therapy on Intervertebral Disc (IVD) degeneration, a major source
of chronic low back pain (LBP). LBP is a common cause of morbidity and disability, and the most common
cause of job-related disability and a leading contributor to missed work in the United States. If a patient with
LBP has several degenerate discs, further examination is required to determine which disc is the source of
pain, prior to a decision of medical treatment or surgical intervention. However, there are no diagnostic
methods in clinical use that help to differentiate between a pathologically painful and an aging disc. On the
other hand, there are no good surgical solutions for patients suffering from chronic LBP as they failed to show
long term pain relief compared to conservative treatment. A potential alternative approach to surgical
procedures is the use of injected stem cells as a potential treatment to regenerate the discs, which have shown
promising therapeutic effects in several recent studies. In this proposal, we hypothesize that a combination of
multiple MR parameters T1, T2, T1ρ, ADC, and qCEST can detect painful discs and quantitatively measure the
effect of mesenchymal stem cells (MSCs) injection to degenerate discs on LBP better than any single MR
parameter. In Aim 1, we will develop a highly efficient and simultaneous multiparametric mapping approach for
T1, T2, T1ρ, ADC, and CEST quantification. The centerpiece of the technical development is our newly
developed Multitasking framework, published in Nature BME in 2018, which allows motion compensated,
highly efficient, simultaneous, multiparametric mapping using low rank tensor reconstruction, taking advantage
of the vast data redundancy among multiple time dimensions. We have applied the technique to quantitative
cardiovascular and body imaging with excellent results. In Aim 2, we will validate that multiparametric
mappings are better associated with molecular pain markers than any individual parameters alone and can
detect the therapeutic effect of MSC injection in a minipig model of disc degeneration. Successful completion
of this project has the potential to make major impact on the way we diagnose and treat chronic LBP.
Multiparametric quantification MRI will provide a reliable and noninvasive tool for LBP detection and guide
physicians which discs to treat. It could also be used to monitor the therapeutic effect of various stem cell
injections, or other disc-targeted therapies that are currently in development.
项目总结
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Debiao Li其他文献
Debiao Li的其他文献
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