Macro-vasculature: A Novel Image Biomarker of Lung Cancer
Macro-vasculature: A Novel Image Biomarker of Lung Cancer
批准号:
10292493
负责人:
Jiantao Pu
金额:
$23.15万
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:
已结题
起止时间:
2020-01-13 至 2023-01-01
关键词:
AchievementAdenocarcinomaAdultAgeAppearanceBenignBiopsyBlood VesselsBody CompositionCancer EtiologyCancer ModelCancer PatientCessation of lifeCharacteristicsChestChinese PeopleClinicalClinical ManagementCollaborationsComputersData SetDatabasesDetectionDevelopmentDiagnostic ProcedureDiseaseEarly DiagnosisEnsureExcisionFunding OpportunitiesGenderGoalsGrowthHealthcareHigh Resolution Computed TomographyImageIncidenceInstitutionInterventionInvestigationLeadLobarLungLung AdenocarcinomaLung NeoplasmsLung noduleMachine LearningMalignant - descriptorMalignant NeoplasmsMalignant neoplasm of lungMetastatic Neoplasm to Lymph NodesMetastatic Neoplasm to the LungMorbidity - disease rateMorphologyNoduleNutrientOperative Surgical ProceduresOutcomeOxygenPathologicPathologyPatientsPositron-Emission TomographyProceduresProcessQuality of lifeRadiation exposureRadiation therapyRecording of previous eventsReportingResearchRiskScanningSelection for TreatmentsSmokerTechnologyTestingTextureThoracic RadiographyTimeTobacco smoking behaviorTreatment outcomeUnited StatesUnited States National Institutes of HealthVisualWithholding TreatmentX-Ray Computed Tomographyaccurate diagnosisalgorithm developmentbasecancer diagnosiscancer invasivenesscancer therapycare burdenclinical practiceclinical translationcomputerizedexperiencefollow-upimaging biomarkerimprovedinterestlow dose computed tomographylung basal segmentlung cancer screeningmortalitymultidisciplinarynovelprogramsracial differenceradiomicsscreeningside effectsmoking cessationsuccesstooltranslational clinical trialtreatment planningtumor
中文摘要
摘要
英文摘要
ABSTRACT
Lung cancer remains the leading cause of cancer related deaths in the United States and worldwide despite
advances in early detection, treatment, and smoking cessation programs. It was reported by the National Lung
Screening Trial (NLST) that screening with low dose computed tomography (LDCT) scans may reduce lung
cancer mortality by 20% compared to chest x-ray. This conclusion ultimately led to the approval and
reimbursement for lung cancer screening using LDCT among asymptomatic adults with a history of tobacco
smoking. However, LDCT-based screening often results in a large number of indeterminate nodules that later
turn out to be non-cancerous. With increasing implementation of LDCT-based lung cancer screening in the U.S.,
the detection of indeterminate lung nodules during lung cancer screening is likely to increase. To reduce
unnecessary diagnostic procedures, such as follow-up CT scan, positron emission tomography (PET)/CT exam,
and invasive biopsies, a tool that can easily and accurately assess the malignancy and invasiveness of the
indeterminate findings will be a welcomed addition to clinical practice. Different levels of invasiveness typically
indicate different treatment plans and can often predict the treatment outcome. Compared to the investigative
efforts dedicated to discriminating benign from malignant nodules, very limited effort has been focused on
assessing the invasiveness of the suspicious nodules and explore the underlying factors associated with
invasiveness. We proposed to develop and validate a novel computer tool to non-invasively assess the
invasiveness of adenocarcinomas using LDCT scans from a large and diverse lung cancer database with
pathology outcome. We will investigate and identify how image-based features contribute to invasiveness. Our
exciting preliminary results demonstrate the feasibility of developing and implementing such a tool and its highly
translational potential. We believe that our computer tool will be a tremendously useful addition to the clinical
practice of lung cancer diagnosis and treatment. Its availability will: (1) enable a timely and accurate diagnosis
of lung cancer, (2) limit the need for further imaging, biopsies, and possible surgery, and (3) facilitate an optimal
selection of the treatment approach (e.g., surgical resection or radiotherapy). Ultimately, we want to improve
survival and the quality of life of lung cancer patients.
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Macro-vasculature: A Novel Image Biomarker of Lung Cance
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批准号:10311064
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项目类别:
-
资助金额:$63.21万
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财政年份:2020
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负责人:Jiantao Pu
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依托单位:
Macro-vasculature: A Novel Image Biomarker of Lung Cance
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批准号:9883874
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项目类别:
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资助金额:$41.56万
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财政年份:2020
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负责人:Jiantao Pu
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依托单位:
Macro-vasculature: A Novel Image Biomarker of Lung Cance
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批准号:10536597
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项目类别:
-
资助金额:$67.17万
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财政年份:2020
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负责人:Jiantao Pu
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依托单位:
CT Assessment of Lung Fissures: Anatomy and Correlated Function
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批准号:7881830
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项目类别:
-
资助金额:$18.94万
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财政年份:2010
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负责人:Jiantao Pu
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依托单位:
CT Assessment of Lung Fissures: Anatomy and Correlated Function
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批准号:8456152
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项目类别:
-
资助金额:$21.42万
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财政年份:2010
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负责人:Jiantao Pu
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依托单位:
CT Assessment of Lung Fissures: Anatomy and Correlated Function
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批准号:8066017
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项目类别:
-
资助金额:$22.73万
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财政年份:2010
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负责人:Jiantao Pu
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依托单位:
CT Assessment of Lung Fissures: Anatomy and Correlated Function
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批准号:9204412
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项目类别:
-
资助金额:$26.95万
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财政年份:2010
-
负责人:Jiantao Pu
-
依托单位:
CT Assessment of Lung Fissures: Anatomy and Correlated Function
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批准号:8257535
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项目类别:
-
资助金额:$22.5万
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财政年份:2010
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负责人:Jiantao Pu
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依托单位:
国内基金
海外基金
大肠癌发生机制的adenoma-adenocarcinoma pathway同serrated pathway的关系的研究
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批准号:30840003
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项目类别:专项基金项目
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资助金额:12.0万元
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批准年份:2008
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负责人:焦宇飞
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依托单位: