The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers
The Duke Preclinical Research Resources for Quantitative Imaging Biomarkers
批准号:
9387149
负责人:
CRISTIAN T BADEA
金额:
$59.27万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-09-30 至 2022-08-31
关键词:
AddressAdjuvantAmerican Society of Clinical OncologyAmputationAnimalsAppearanceArchivesAutopsyBehaviorBiological MarkersCessation of lifeChestClinicalClinical DataClinical MedicineClinical TreatmentClinical TrialsCodeCommunitiesComputer softwareCorrelative StudyDataData ScienceData SetDatabasesDepositionDevelopmentDiseaseDisease-Free SurvivalDistantDocumentationEffectivenessExcisionFutureGene ExpressionGenetic EngineeringGenetically Engineered MouseGoalsHistologicHumanImageImmune checkpoint inhibitorImmune responseImmune systemImmunotherapyLimb structureMagnetic Resonance ImagingMeasurementMetastatic Neoplasm to the LungMethodologyMethodsMicroscopyModelingMonitorMotionMusNecrosisNeoadjuvant TherapyNeoplasm MetastasisOperative Surgical ProceduresOutcomePathologyPatientsPhasePhase II Clinical TrialsPhysiologyPrimary NeoplasmProgression-Free SurvivalsProtocols documentationPublicationsRadiation therapyRandomizedReaderRecurrenceResearchResearch ProposalsResolutionResourcesScienceSoft tissue sarcomaStandardizationTechnologyTestingTreatment outcomeUndifferentiatedX-Ray Computed Tomographyanimal imaginganticancer researcharmburden of illnesscancer imagingcancer therapychest computed tomographydata sharingdesignexperimental studyfollow-uphigh riskhuman imagingimaging approachimaging biomarkerimaging modalityimaging studyimprovedin vivoin vivo imaginginhibitor/antagonistliposarcomamouse modelnovel strategiesnovel therapeutic interventiononcologyopen datapartial responsepre-clinicalpre-clinical researchpre-clinical trialpreclinical studypredict clinical outcomepreventpublic health relevancequantitative imagingreconstructionrepositoryresponsesarcomatreatment responsetumorweb-accessible
中文摘要
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英文摘要
Abstract
Quantitative imaging approaches are currently being standardized for clinical medicine by the Quantitative
Imaging Biomarkers Alliance (QIBA). However, similar efforts for preclinical imaging do not exist although the
need for standardization is even more pressing because of the high degree of diversity that exists in preclinical
imaging hardware and software. Compared to clinical (human) imaging, the technical challenges are
significantly more difficult for the optimization of mouse model quantitative imaging. The goal of this proposal is
to design, optimize and apply preclinical quantitative imaging with micro-magnetic resonance imaging (MRI)
and micro- computed tomography (CT). Specifically, we will apply our quantitative imaging methods in a co-
clinical trial which mirrors an on-going, multi-institutional, randomized phase II clinical trial that has a primary
objective to investigate whether neoadjuvant radiotherapy combined with pembrolizumab followed by surgical
resection and adjuvant pembrolizumab improves disease-free survival for patients with high-risk soft-tissue
sarcoma of the extremity (undifferentiated pleomorphic sarcoma or dedifferentiated/pleomorphic liposarcoma)
compared to radiotherapy alone followed by surgical resection. The trial aims to evaluate the 2- and 5-year
recurrence-free survival and overall survival. MRI is used to assess the radiation treatment response and to
plan for surgery. Chest CT is used during follow up to evaluate for distant tumor recurrence (lung metastases).
For preclinical studies, we will use the Cre-loxP technology to generate primary sarcomas in the hind limb of
mice. Our autochthonous tumor models closely mimic human soft tissue sarcomas in histologic appearance,
gene expression, and clinical behavior, including lung metastasis development. For the metastatic tumor
model, the primary tumor-bearing limb will be amputated and mice will be monitored for metastases. In our first
specific aim, we will develop and optimize quantitative imaging with micro-MRI for primary soft tissue sarcoma
tumors and micro-CT for lung metastases. We will follow similar methodologies proposed in the QIBA
framework but adapted for small animal imaging. During the second aim, we will implement our optimized
quantitative imaging methods in the co-clinical trial using our genetically engineered mouse models of
sarcoma. We anticipate that radiotherapy with PD-1 inhibitors will improve metastasis-free survival. The
preclinical experiments will provide greater understanding of mechanisms involved in these combined
therapies and will inform future clinical trials. Finally, the last specific aim will focus on creating a web-
accessible research resource for archiving and disseminating small animal imaging protocols and data.
Imaging and biologic data, including pathology, will be robustly integrated for correlative studies. The expected
outcome of this project is the standardization of micro-MRI and micro-CT preclinical imaging for cancer studies.
This standardization will facilitate and guide the incorporation of small animal imaging into future pre- and co-
clinical trials involving new therapeutic approaches to cancer treatment. Ultimately, reduced variability in
preclinical imaging studies will improve the value of quantitative correlations established between
pathophysiological biomarkers and imaging biomarkers.
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会议论文
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海外基金