Prediction of Recurrent Anterior Shoulder Instability Using the On/Off Track Method and 3D MRI: A Clinical Outcomes and Cost-Effectiveness Study
Prediction of Recurrent Anterior Shoulder Instability Using the On/Off Track Method and 3D MRI: A Clinical Outcomes and Cost-Effectiveness Study
批准号:
10396027
负责人:
Soterios Gyftopoulos
金额:
$39.83万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-07-01 至 2024-04-30
关键词:
3-DimensionalAlgorithmsAnatomyAnteriorBone InjuryCaliberClinicalConflict (Psychology)DataEvaluationFailureFractureHeadImageImaging TechniquesIncidenceIndividualInjuryJoint CapsuleLeadLesionLiteratureLocationMagnetic Resonance ImagingMeasurementMeasuresMethodsModelingOperative Surgical ProceduresOutcomePatient-Focused OutcomesPatientsPersonsPlayPostoperative PeriodQuality of lifeRadiationRecording of previous eventsRecurrenceReference StandardsReportingRetrospective cohortRiskRisk FactorsRoleSelection for TreatmentsShoulderSoft Tissue InjuriesSymptomsTechniquesTimeUnited Statesbasebipolar bone lossbone lossclinical practicecostcost effectivecost effectivenesseffectiveness studyhumerusimage reconstructionimprovedmarkov modelminimal riskpatient populationrepairedsoft tissuesurgery outcomethree-dimensional modelingtissue repairtool
中文摘要
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英文摘要
PROJECT SUMMARY
Anterior shoulder instability (ASI) is one of the most common shoulder ailments in the United States.1 A large
proportion of ASI patients undergo surgical stabilization, typically arthroscopic soft tissue repair (i.e. repair of
the labrum and/or joint capsule), with approximately 260,000 surgeries of this type performed each year in the
United States.2,3 While the majority of these cases are successful, up to 35% are considered clinical failures
due to recurrent ASI and/or persistent limited shoulder function.4,5 One of the major reasons for failure of
arthroscopic repair in ASI patients is the inadequate evaluation and treatment of bone injuries that occur in this
clinical setting, humeral Hill Sachs lesions and anterior glenoid bone loss, (i.e. bipolar bone loss), reported to
be the cause of recurrent ASI after surgery in up to 67% of patients.6 MRI plays a crucial role in the
preoperative evaluation of patients with ASI, providing important information on the associated soft tissue and
bone injuries. Prior studies have defined imaging based thresholds of “significant” bone loss at the humerus
and glenoid that are used to guide the selection of treatment with the location of greatest bone injury typically
determining management. However, the utility of these thresholds and the consideration of only one bone
injury have come into question with several studies demonstrating conflicting treatment results and patient
outcomes using these techniques. More recently, greater emphasis has been put on the potential interaction
between these injuries rather than their sizes as the main risk factor for recurrent ASI. To improve the
preoperative evaluation of bipolar bone loss, we will develop and optimize a new imaging strategy that consists
of an imaging technique, 3D MRI, and imaging measurement tool, the On/Off Track method, that can be easily
implemented into clinical practice. 3D MRI reconstructions are created using standard imaging data and
minimal post processing time without the cost and radiation associated with other 3D models. The On/Off
Track method is a technique that uses simple measurements of bipolar bone loss to assess the potential for
interaction between these osseous injuries in order to predict recurrent ASI. We will examine the value of the
On/Off Track method on MRI with 3D MRI models in predicting which patients with a history of ASI will be
considered a failure within 24 months of surgery. We will also determine the most cost-effective pre-operative
imaging strategy for patients with a history of ASI. This study will establish a new cost-effective MRI strategy
for the assessment of bipolar bone loss in the patient with ASI, which can be used to select the most
appropriate initial treatment and improve patient outcomes.
期刊论文(1)
专著(0)
科研奖励(0)
会议论文
Three-dimensional MRI Bone Models of the Glenohumeral Joint Using Deep Learning: Evaluation of Normal Anatomy and Glenoid Bone Loss.
使用深度学习的盂肱关节三维 MRI 骨模型:正常解剖结构和关节盂骨丢失的评估。
DOI:
10.1148/ryai.2020190116
发表时间:
2020
期刊:
Radiology. Artificial intelligence
影响因子:
--
作者:
[CantarelliRodrigues,Tatiane, Deniz,CemM, Alaia,ErinF, Gorelik,Natalia, Babb,JamesS, Dublin,Jared, Gyftopoulos,Soterios]
通讯作者:
Gyftopoulos,Soterios
Prediction of Recurrent Anterior Shoulder Instability Using the On/Off Track Method and 3D MRI: A Clinical Outcomes and Cost-Effectiveness Study
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批准号:9902331
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项目类别:
-
资助金额:$42.13万
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财政年份:2018
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负责人:Soterios Gyftopoulos
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依托单位:
海外基金