Transcript COPDGene - National Alliance for Medical Image Computing

COPDGene® : Genetic Epidemiology of COPD
NA-MIC: All Hand Meeting
Raúl San José & James Ross
BWH
Overview
COPDGene
Data Analysis
Future Directions
COPD: Chronic Obstructive Pulmonary Disease
Definition: “Airflow limitation that is not fully
reversible. The airflow limitation is usually
progressive and associated with an abnormal
inflammatory response of the lung to noxious
particles or gases.”
Causes:
Overview
COPDGene
Data Analysis
Future Directions
COPD: a growing disease
Projected to be the third-leading cause of death by
2020
24 million people affected by COPD in US
Overview
COPDGene
Data Analysis
Future Directions
COPD: The Diseases
What is the underlying process?
Slowly progressive irreversible destruction of the lung tissue
Emphysema: air sacs that exchange gases
Airway disease (Chronic Bronchitis): airways that conduct
these gases
End Result:
Progressive shortness of breath
Cough
Sputum production
Overview
COPDGene
Data Analysis
Future Directions
Disease in Images
Airway Diseases
Emphysema Diseases
Overview
COPDGene
Data Analysis
Future Directions
COPDGene
Only 20% of smokers develop COPD
Genetic factors
Multi-center study funded by the National
Heart, Lung and Blood Institute (NHLBI).
Co-PIs: Drs. James Crapo, Edwin Silverman.
21 clinical sites
3 Image analysis
centers:
• Denver
• Iowa
• BWH
Overview
COPDGene
Data Analysis
Future Directions
COPDGene: Hypothesis
1)
Precise phenotypic characterization of COPD
subjects using computed tomography, as well as
clinical and physiological measures, will provide
data that will enable the broad COPD syndrome to
be segregated into clinically significant subtypes.
2)
Genome-wide association studies will identify
genetic determinants for COPD susceptibility that will
provide insight into clinically relevant COPD
subtypes.
3)
Distinct genetic determinants influence the
development of emphysema and airway disease.
Overview
COPDGene
Data Analysis
Future Directions
COPDGene: Goals
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Collect a large population of COPD subjects and
smokers without COPD: 10,000
Two racial/ethnic groups: Non-Hispanic whites and
Non-Hispanic African Americans
Extensive Characterization (Chest CT scans)
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Inspiratory, Expiratory
High resolution CT (0.7mm isotropic with 50% overlap)
2 reconstructions kernels (smooth and sharp)
Use genome-wide association analysis to find
inherited causes of COPD and COPD subtypes
Overview
COPDGene
Data Analysis
Future Directions
COPDGene: Study Design
Figure 7. Genome Wide Association of COPD: Study Design
Phase 1
Genome Wide Screen
Case/Control
Non-Hispanic White
n=1000/1000
Case/Control
African American
n=500/500
~6000 SNP Candidates
~6000 SNP Candidates
Fast track
panel*
Phase 2
Confirmation of SNP Signals
Case/Control
Non-Hispanic White
n=1000/1000
Case/Control
African American
n=500/500
50 regions (flanking SNPs)
50 regions (flanking SNPs)
Phase 3
Region Mapping
Case/Control
Non-Hispanic White
n=1000/1000
Case/Control
African American
n=500/500
~3-5 Gene Candidates
~3-5 Gene Candidates
Phase 4
Case/Control
Cohorts
Non-Hispanic White
n=3000/3000
African American
n=1500/1500
Candidate Gene Analysis
GOLD 1 Cohort
Non-Hispanic White
n=1000
African American
n=500
Boston Early
Onset COPD
Family Study
n=160 families,
1100 individuals
International
COPD Genetics
Network
n=1150 probands
+ 1950 sibs
Overview
COPDGene
Data Analysis
Future Directions
COPDGene: Current status
• Since Sept 2007 over 6500 subjects have been
recruited.
• First 2500 have been fully analyzed.
Overview
COPDGene
Data Analysis
Future Directions
Challenges
• Data management
– Storage: 40,000 scans, 20 TB expected to archive full cohort
– Quality control: Initial and processing
– Querying and retrieval
• Image analysis: inspiration and expiration
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Lung area and lobes
Airway segmentation
Robust: outlier detection
Minimal user input
• High-throughput analysis
– Batch analysis
– Grid deployment
Overview
COPDGene
Data Analysis
Future Directions
Analysis Centers
• National Jewish (Denver): Drs. Lynch and Schroeder
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Q&A
Emphysema and Airway analysis using VIDA
Primary archiving center
Result integration
• BWH (Boston): Dr. Washko
– High-throughput emphysema analysis
– New phenotypes
– Data replication
• University of Iowa: Dr. Hoffman
– COPDGene Phantom Analysis (Q&A)
– VIDA customization
Overview
COPDGene
Data Analysis
Future Directions
BWH Pipeline
• Lung Imaging Platform
– ITK-based filters for lung extraction, lobe
segmentation and parenchymal texture analysis
– Emphysema quantification
– Air trapping quantification
– Tracheal air correction
– VTK-based filters for airway measurements
– Command Line Tools
• Grid Wizard Enterprise for pipeline deployment
• Iterative Lobe segmentation in Slicer 3
Overview
COPDGene
Data Analysis
Future Directions
BWH Pipeline
• Filters
• Tools
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itkLungConventions
itkExtractLungLabelMapImageFilter
itkPartialLungLabelMapImageFilter
itkMergeLungLabelMapsImageFilter
itkAutoThresholdAirwaySegmentationI
mageFilter
itkWholeLungVesselAndAirwaySegme
ntationImageFilter
itkSplitLeftAndRightLungsImageFilter
itkLabelLungRegionsImageFilter
itkAirwayGraphTraits
itkImageToAirwayGraphFilter
itkImageToAirwayGraphFunctor
itkMinCostPathAirwaySegmentationIm
ageToGraphFilter
ConvertDicom
GeneratePartialLungLabelMap
GenerateEmphysemaMeasures
QualityControl
ExtractLungLabelMap
MergeLungLabelMaps
GenerateHUStatistics
SegmentationAssistant
GenerateMedianFilteredImage
SplitLeftAndRightLungs
LabelLungRegions
GenerateAirwayPhantom
Overview
COPDGene
Data Analysis
Future Directions
BWH Pipeline
Overview
COPDGene
Data Analysis
Future Directions
Data Quality: Dashboard
Overview
COPDGene
Data Analysis
Future Directions
Future Directions
• Airway Analysis
– User-driven path extraction
– Fully automatic approach based on Scale-space
particles
• Development of new airway phenotypes
– Role of airway density in disease
– New approaches for emphysema
• Multi scanner brand correction
• Automatic pipeline supervision and reporting
• Insp.-Exp. registration for lobar ventilation
assessment