update on lung cancer image processing rick avila karthik krishnan luis ibanez kitware, inc....
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Update on Lung Cancer Image Update on Lung Cancer Image ProcessingProcessing
Rick AvilaRick AvilaKarthik KrishnanKarthik Krishnan
Luis IbanezLuis Ibanez
Kitware, Inc.Kitware, Inc.
[email protected]@kitware.com
April 19, 2006
KitwareKitware
Therapy AssessmentTherapy Assessment
StartTherapy
TimeTimeTimeTime
AssessmentAssessment• Tumor responseTumor response• ID new lesionsID new lesions
??
Tu
mo
r S
ize
Tu
mo
r S
ize
Tu
mo
r S
ize
Tu
mo
r S
ize
tt
AssessResponse
4 cm lesion4 cm lesion
CharacteristicsCharacteristics• Late stageLate stage• Thick CTThick CT
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KitwareKitware
RECISTRECIST
TimeTimeTimeTime
Baseline& Treat
AssessResponse
D = -30%D = -30%
D = +20%D = +20%
Sta
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D
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Co
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lete
Re
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Pro
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Dis
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weeks
Tar
get
Les
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Mea
sure
men
tR
EC
IST
: S
um
of
LD
Tar
get
Les
ion
Mea
sure
men
tR
EC
IST
: S
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of
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Unaided Interpretation
4cm lesion4cm lesion
8mm 8mm D, 13 pixelsD, 13 pixels
73% 73% VolumeVolume
Erasmus et. al., JCO 2003Erasmus et. al., JCO 2003
Intra-observer errorIntra-observer error
PD: PD: 9.5%9.5% of tumors of tumors
PR: PR: 3%3% of tumors of tumors
Inter-observer errorInter-observer error
PD: PD: 30%30% of tumors of tumors
PR: PR: 14%14% of tumors of tumors
Erasmus et. al., JCO 2003Erasmus et. al., JCO 2003
Intra-observer errorIntra-observer error
PD: PD: 9.5%9.5% of tumors of tumors
PR: PR: 3%3% of tumors of tumors
Inter-observer errorInter-observer error
PD: PD: 30%30% of tumors of tumors
PR: PR: 14%14% of tumors of tumors
KitwareKitware
We can do betterWe can do better
TimeTimeTimeTimeS
tab
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Pa
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eC
om
ple
teR
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rog
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siv
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tTar
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Les
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Mea
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men
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: S
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LD
Aided 3D Aided 3D InterpretatioInterpretatio
nn
Improve:Improve:• BiasBias• VarianceVarianceFor Lower:For Lower:• Interval (Interval (t)t)• Study NStudy N
Early Detection & Nodule Sizing ??
4cm lesion4cm lesion
KitwareKitware
First Step: Open Development DatabasesFirst Step: Open Development Databases
All Cases Shown In This Presentation Came From These DatabasesAll Cases Shown In This Presentation Came From These Databases
KitwareKitware
Measurement ChallengesMeasurement Challenges
Patient/Lesion PresentationPatient/Lesion Presentation– SizeSize– ComplexityComplexity– Changes over time (necrosis)Changes over time (necrosis)
ScannersScanners– HardwareHardware– SoftwareSoftware
ProtocolsProtocols– ScanRxScanRx– ContrastContrast– Patient positionPatient position
ObserverObserver– Seed points/ROISeed points/ROI– Data InterpretationData Interpretation 5mm5mm 2.5mm2.5mm
KitwareKitware
Volumetric Algorithm ChallengesVolumetric Algorithm Challenges
Boundary Identification ChallengesBoundary Identification Challenges• Vascular network (Ev)Vascular network (Ev)
• Bronchial network (Eb)Bronchial network (Eb)
• Pleura (Ep)Pleura (Ep)
• Sub-voxel edge (Es)Sub-voxel edge (Es)
Errors at 2 time pointsErrors at 2 time pointsEvEv
Error strongly depends Error strongly depends
on on lesion sizelesion size and and
slice thicknessslice thickness
EpEp
Pleur
a
EsEs
No
/Sm
all
N
o/S
ma
ll
II
KitwareKitware
Solid Algorithm: Operating EnvelopeSolid Algorithm: Operating Envelope
Lesion SizeLesion Size
Slic
e T
hick
ness
Slic
e T
hick
ness
10mm10mm 20mm20mm15mm15mm5mm5mm00
1.25 mm1.25 mm
2.5 mm2.5 mm
3.75 mm3.75 mm
5.0 mm5.0 mm
ComplexComplex
BoundariesBoundaries
PartialPartial
VolumeVolume
Noise…Noise…
Curvature…Curvature…
ClinicalClinical
TrialsTrials
SolutionSolution• <= 1.25mm thickness<= 1.25mm thickness
• Algorithm support for Algorithm support for complex intersectionscomplex intersections
• Validate against wide Validate against wide patient and protocol patient and protocol populationpopulation
KitwareKitware
Motivating ExampleMotivating Example
46d46d 69d69d
59mm59mm 48mm48mm 44mm44mm
1D 25%
RECIST would classify response to therapy as Stable DiseaseRECIST would classify response to therapy as Stable Disease
KitwareKitware
Validation ApproachValidation Approach
TimeTimeTimeTime
Baseline& Treat
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Met
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Met
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Case CollectionCase Collection
• Collect cases w/many Collect cases w/many short interval scansshort interval scans
• Assessment on last Assessment on last scan(s) is clearscan(s) is clear
AnnotationAnnotation
• One or more expert(s) One or more expert(s) classify each case classify each case based on all databased on all data
T1T1 T2T2 T3T3 T4T4 T5T5
MetricMetric
• Measure sens/spec Measure sens/spec between assess pairsbetween assess pairs
• Compare metrics at Compare metrics at last time pointlast time point
• At what time can a At what time can a sens/spec be met?sens/spec be met?
KitwareKitware
Open Database Collection PrioritiesOpen Database Collection Priorities
Add Annotation to Open DatabasesAdd Annotation to Open Databases– Need to assess RECIST as the baseline performanceNeed to assess RECIST as the baseline performance– Need an expert assessment of response for caseNeed an expert assessment of response for case
Add More Cases to Open DatabasesAdd More Cases to Open Databases – Wide range of patient/lesion presentationsWide range of patient/lesion presentations– Wide range of therapy interactionsWide range of therapy interactions
Emphasize Thin SliceEmphasize Thin Slice– Algorithms perform better (e.g. I’’) Algorithms perform better (e.g. I’’)
Collect Data at Smaller Time IntervalsCollect Data at Smaller Time Intervals– Algorithms perform better (e.g. registration)Algorithms perform better (e.g. registration)
KitwareKitware
Edge DetectionEdge Detection
Algorithms that utilize acquisition characteristicsAlgorithms that utilize acquisition characteristics
(e.g. PSF, SNR) can adapt to changes in acquisition(e.g. PSF, SNR) can adapt to changes in acquisition
Step Step FunctionFunction
PSF + NoisePSF + Noise
Object Scanner Image
SmoothLocalize
Recover Edge Using Recover Edge Using
Acquisition CharacteristicsAcquisition Characteristics
Elder et. al. TPAMI 1998
KitwareKitware
Cross-Platform CapabilityCross-Platform Capability
• Goal:Goal:– Software achieves accuracy despite variation in:Software achieves accuracy despite variation in:
• Scanning equipmentScanning equipment• Acquisition protocolsAcquisition protocols
• Solution:Solution:– Establish minimum acquisition standards/protocolsEstablish minimum acquisition standards/protocols– Keep acquisition technique constant per patientKeep acquisition technique constant per patient– Measure scanner characteristics Measure scanner characteristics utilizing a standard utilizing a standard
phantomphantom and publish and publish – Utilize model-based algorithmsUtilize model-based algorithms
KitwareKitware
Unexpected Results Unexpected Results
Many studies report Many studies report greatergreater variance and variance and error when comparing 1D/2D/3D analysiserror when comparing 1D/2D/3D analysis
– Issue 1: More is not always betterIssue 1: More is not always better• All measurements need high precisionAll measurements need high precision• Consider slice thickness Consider slice thickness
– Issue 2: New metrics need optimizationIssue 2: New metrics need optimization• Development data needed to establish best Development data needed to establish best
separation between response classesseparation between response classes