Computer-Assisted Histologic Evaluation of Cardiac Allograft Rejection
心脏同种异体移植排斥反应的计算机辅助组织学评估
基本信息
- 批准号:10246527
- 负责人:
- 金额:$ 79万
- 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
- 起止时间:2020-09-01 至 2024-08-31
- 项目状态:已结题
- 来源:
- 关键词:AcuteAddressAllograftingAntibodiesArchivesAreaBenignBiological MarkersBiopsyBiopsy SpecimenCardiacCellsClassificationClinicalClinical Trials DesignComplicationComputer AssistedComputer Vision SystemsCustomDataDerivation procedureDevelopmentDiagnosisDiagnosticDisabled PersonsDiseaseEvaluationEventFlow CytometryFunctional disorderGene Expression ProfilingGraft RejectionGuidelinesHeartHeart TransplantationHeart-Lung TransplantationHistologicHistopathologic GradeHistopathologyHumanImageImage AnalysisImmuneImmune System DiseasesImmunofluorescence ImmunologicImmunologic MarkersImmunologicsIn SituInjuryInternationalInterobserver VariabilityInterventionJournalsLegal patentLymphocyteMachine LearningMalignant neoplasm of lungMediatingMedicalMethodsMolecularMonitorMorphologyOrgan TransplantationOutcomePaperPathologistPatient-Focused OutcomesPatientsPatternPerformancePopulationPreventionPrognosisProspective cohortProtocols documentationROC CurveRecurrenceReference StandardsResearchRetrospective cohortRiskSamplingSchemeServicesSeveritiesSlideSocietiesStainsSyndromeTechnologyTestingTherapeuticTissue imagingTissuesTrainingTransplant RecipientsTransplantationallograft rejectionantibody-mediated rejectionbasebiomarker discoverybiomarker validationclinical predictorsclinically significantcohortdiagnostic accuracyfeature detectiongraft failureheart allograftheart imagingimprovedinnovationmolecular markernovelovertreatmentpathology imagingphenotypic datapopulation basedpost-transplantprospectivescreeningsuccesstooltransplant centerstreatment as usualtreatment choice
项目摘要
Project Summary
Though cardiac transplantation is a lifesaving intervention, cardiac allograft rejection (CAR) remains a relatively
common and serious complication that confers an increased risk of acute graft failure and adverse patient
outcomes. For three decades, endomyocardial biopsy (EMB) with histological grading, as recommended by the
International Society of Heart and Lung Transplantation (ISHLT) has been the broadly applied standard for CAR
diagnosis. However, it is widely appreciated that the ISHLT rejection grading standard lacks diagnostic accuracy
and has limited ability to discern the mechanism of rejection. These limitations expose patients to risks of both
over-treatment and under-treatment, and highlight the unmet need for more accurate and informative
approaches to histopathologic analysis of EMB samples. Our team is a leader in computational pathology image
analysis with over 200 papers and >30 issued patents in this area. We have already developed and evaluated a
computer assisted histopathology grading evaluation (CACHE) scheme which (1) in N=205 patients, had an area
under the receiver operating characteristic curve (AUC)=0.95 compared to two cardiac pathologists (mean
AUC=0.74) in distinguishing normal from failing hearts and (2) could distinguish low and high ISHLT rejection
grades in N=1109 patients with a performance that exceeds that of trained cardiac pathologists. Recognizing the
frequent discordance between ISHLT rejection grade and the clinical trajectory of a rejection event, we will further
develop and optimize CACHE to identify new “grade agnostic” morphologic biomarkers of clinically serious CAR.
Our scientific premise is that morphologic biomarkers prioritized based on their correlation to patients’ clinical
trajectories and underlying immunological disease mechanisms will generate an accurate, consistent and
informative classifier for diagnosing allograft rejection. In service of this hypothesis, the proposed research will
address three specific aims. In Aim 1, we will utilize computational image analysis to discover the morphologic
biomarkers of rejection-related injury which are needed to develop a classifier capable of assessing the clinical
trajectory of CAR. In Aim 2, we will provide mechanistic annotation of biomarkers identified in Aim 1 through
correlation with in-situ immunologic markers using custom multi-parameter immunofluorescence panels. In Aim
3, we employ a multicenter, prospective cohort to validate the diagnostic and mechanistic accuracy of the new
rejection classifier developed in Aims 1 and 2. Ultimately, development of a more accurate and mechanistically
informative tool for morphologic diagnosis of CAR will improve patient outcomes by reducing over- and under-
treatment and inspire applications in other organ transplants. Interestingly, development of a superior histologic
diagnostic tool will empower development of alternative, biopsy-free diagnostic approaches that have been
handicapped by the necessity of comparison with the flawed ISHLT rejection grade as a reference standard.
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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Anant Madabhushi其他文献
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