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  • Kelly H. Zou, PhD; zou@bwh.harvard.edu
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    • 1. An EM-Algorithm forAn EM-Algorithm for Analyzing Multi-CenterAnalyzing Multi-Center Repeated fMRI DataRepeated fMRI Data Kelly H. Zou, PhDKelly H. Zou, PhD Assistant Professor of RadiologyAssistant Professor of Radiology Department of Radiology, Brigham and Women’s HospitalDepartment of Radiology, Brigham and Women’s Hospital Department of Health Care Policy, Harvard Medical SchoolDepartment of Health Care Policy, Harvard Medical School Joint Statistical MeetingsJoint Statistical Meetings August 8, 2004August 8, 2004 Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 2. fBIRNfBIRN Functional ImagingFunctional Imaging Research for SchizophreniaResearch for Schizophrenia Testbed,Testbed, Biomedical InformaticsBiomedical Informatics Research NetworkResearch Network Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 3. Co-AuthorsCo-Authors Steven D. Pieper, PhDSteven D. Pieper, PhD Meng Wang, MSEMeng Wang, MSE Simon K. Warfield, PhDSimon K. Warfield, PhD William M. Wells, PhDWilliam M. Wells, PhD Ron Kikinis, MDRon Kikinis, MD FIRST BIRNFIRST BIRN Brigham and Women‘s HospitalBrigham and Women‘s Hospital Harvard Medical SchoolHarvard Medical School NCRRP41RR13218NCRRP41RR13218 Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 4. BackgroundBackground Multi-Site BIRN Study:Multi-Site BIRN Study: 11 Sites11 Sites (MN, UCI, UNC, UCLA…, BWH, MGH)(MN, UCI, UNC, UCLA…, BWH, MGH) 5 Healthy males as “Human Phantoms”5 Healthy males as “Human Phantoms” 2 Visits on separate days per site per subjec2 Visits on separate days per site per subjec 2 extra visits at one site for 3 of the 52 extra visits at one site for 3 of the 5 subjectssubjects 4 Sensory motor (SM), 2 cognitive (Cog),4 Sensory motor (SM), 2 cognitive (Cog), 2 breath-hold (BH) runs per visit2 breath-hold (BH) runs per visit BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 5. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 6. Clinical ObjectivesClinical Objectives It is meaningful to pool the data to yield aIt is meaningful to pool the data to yield a larger sample size in the next-phaselarger sample size in the next-phase clinical study (clinical study (SchizophrenicSchizophrenic vs. normalvs. normal controls)?controls)? How to assess the effects of variousHow to assess the effects of various factors?factors? BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 7. Statistical ObjectivesStatistical Objectives Ultimate problem (Pooling):Ultimate problem (Pooling): How to combine multi-site data and toHow to combine multi-site data and to validate the pooling mechanism?validate the pooling mechanism? Current problem (Calibration):Current problem (Calibration): How to compare and combine data in theHow to compare and combine data in the calibration step?calibration step? https://share.spl.harvard.edu/users/zouhttps://share.spl.harvard.edu/users/zou BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 8. Materials and MethodsMaterials and Methods Focus onFocus on Reproducibility of the SMReproducibility of the SM TaskTask Subjects perform bilateral finger tappingSubjects perform bilateral finger tapping on button boxes (1 dummy button boxon button boxes (1 dummy button box andand 1 actual) in time with 3Hz audio cue and1 actual) in time with 3Hz audio cue and flashing checkerboard squareflashing checkerboard square They press buttons 1 - 4 in consecutiveThey press buttons 1 - 4 in consecutive order and then back again using bothorder and then back again using both hands at simultaneously and in synchands at simultaneously and in sync BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 9. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment Pulse SequencesPulse Sequences AA Spin echo T2-weighted, obliqueSpin echo T2-weighted, oblique axialaxial 256x192 matrix256x192 matrix 35 slices, 4mm inter35 slices, 4mm inter Scan time=2:24 minScan time=2:24 min T2SET2SE 3D Spoiled Grass, axial3D Spoiled Grass, axial 256x192 matrix256x192 matrix 124-128 slices, 1.2mm124-128 slices, 1.2mm Scan time=9:02 minScan time=9:02 min 3D3D SPGRSPGR FF Echo-planar imaging or spiralEcho-planar imaging or spiral gradient echo imaging, obliquegradient echo imaging, oblique axialaxial 64x64 matrix, 1 shot64x64 matrix, 1 shot 35 slices, 4mm35 slices, 4mm EPI orEPI or SpiralSpiral GREGRE
    • 10. Materials and MethodsMaterials and Methods TaskTask: Sensory Motor: Sensory Motor SiteSite: 5 Sites with 1.5T, 4 with 3T, 1 with: 5 Sites with 1.5T, 4 with 3T, 1 with 4T4T SubjectSubject: #101; 103; 104; 105; 106: #101; 103; 104; 105; 106 RunRun: 4 and registered: 4 and registered DayDay:: #101; 103; 106 tested on 4 days at#101; 103; 106 tested on 4 days at Stanford and other subjects tested on 2Stanford and other subjects tested on 2 Days/SiteDays/Site ThresholdThreshold: Activation data:: Activation data: γγ = – log= – log1010(p-value)sign(F-statistic)=10(p-value)sign(F-statistic)=10-9-9 BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 11. Materials and MethodsMaterials and Methods Image registration over the repeatedImage registration over the repeated runs across sites using FreeSurferruns across sites using FreeSurfer Voxel-to-voxel registration of theVoxel-to-voxel registration of the anatomicalanatomical with thewith the functional volumefunctional volume toto convert the subject's anatomical volumeconvert the subject's anatomical volume to the corresponding functional spaceto the corresponding functional space using a transformation matrixusing a transformation matrix BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 12. Materials and MethodsMaterials and Methods TkRegister defines the registrationTkRegister defines the registration matrixmatrix T=T= -d-dcc 00 00 (N(Ncc/2)d/2)dcc 00 00 ddss -(N-(Nss/2)d/2)dss 00 -dr-dr 00 (N(Nrr/2)d/2)drr 00 00 00 11 ddcc, d, drr, and d, and dss are the resolutions,are the resolutions, NNcc, N, Nrr, and N, and Nss are the numberare the number BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 13. Materials and MethodsMaterials and Methods BWH, HMSBWH, HMSQuality AssessmentQuality Assessment VariablVariabl ee NameName # Values# Values 11 SubjectSubject 1 - 51 - 5 22 SiteSite 1 - 101 - 10 33 VisitVisit 1, 2 (all); 1 - 4 (1site 31, 2 (all); 1 - 4 (1site 3 subjects)subjects) 44 RunRun 1 - 4/visit1 - 4/visit 55 StrengthStrength 1.5T, 3T, 4T1.5T, 3T, 4T 66 MakerMaker Siemens, GE, PickerSiemens, GE, Picker 77 K-SpaceK-Space Raster, Spiral, Dual-EchoRaster, Spiral, Dual-Echo RasterRaster
    • 14. Materials and MethodsMaterials and Methods Selection of Threshold:Selection of Threshold: The threshold was selected on the scaleThe threshold was selected on the scale of the activation dataof the activation data The 3D activation map was furtherThe 3D activation map was further standardized using the absolute valuestandardized using the absolute value for each voxel prior to statisticalfor each voxel prior to statistical inferencesinferences BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 15. Materials and MethodsMaterials and Methods Selection of Threshold:Selection of Threshold: The threshold was selected on the scaleThe threshold was selected on the scale of the activation dataof the activation data The 3D activation map was furtherThe 3D activation map was further standardized using the absolute valuestandardized using the absolute value for each voxel prior to statisticalfor each voxel prior to statistical inferencesinferences BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 16. Complete data density:Complete data density: Binary ground truth TBinary ground truth Tii for voxel ifor voxel i Expert j segmentation DExpert j segmentation Dijij Expert performance characterized byExpert performance characterized by sensitivity p and specificitysensitivity p and specificity We observe expert decisions DWe observe expert decisions D To construct maximum likelihoodTo construct maximum likelihood estimatesestimates for each expert’s sensitivity andfor each expert’s sensitivity and specificityspecificity )|,(lnmaxargˆ,ˆ qp,TDqp qp, f= Materials and MethodsMaterials and Methods Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 17. Solve the incomplete-data log likelihood maximization problem by Expectation Maximization (EM) ˆ arg max ln ( | )f= θ θ D θ ˆ ˆ( | ) ln ( | )|Q E f        =θ θ D,T θ D,θ Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 18. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment Visit 1 Visit 2 Level 1A: STAPLE EM Across 4 Runs/Visit Within Site Within Visit Level 1B: STAPLE EM Across 4 Runs/Visit Within Site Within Visit Level 2A. STAPLE EM Over All Sites Within Visit Level 2B. STAPLE EM Within Field Strength Across the Sites/Field Strength Within Visit Level 2A. STAPLE EM Over All Sites Within Visit Level 2B. STAPLE EM Within Field Strength Across the Sites/Field Strength Within Visit Materials and MethodsMaterials and Methods
    • 19. Materials and MethodsMaterials and Methods Statistical methodsStatistical methods Activation percentageActivation percentage Sensitivity and SpecificitySensitivity and Specificity Receiver operating characteristic curveReceiver operating characteristic curve Linear modelLinear model Analysis of varianceAnalysis of variance BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 20. Subject 104Subject 104 Visit 1Visit 1 Slice #18Slice #18 ResultsResults
    • 21. ResultsResults Statistical significant factors impactingStatistical significant factors impacting onon sensitivitysensitivity:: subject (p=0.01)subject (p=0.01) onon specificityspecificity:: subject (p=0.04)subject (p=0.04) run (p=0.04)run (p=0.04) BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 22. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment ResultsResults Activation PercentageActivation Percentage
    • 23. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment ResultsResults SensitivitySensitivity
    • 24. BWH, HMSBWH, HMSQuality AssessmentQuality Assessment ResultsResults SpecificitySpecificity
    • 25. ConclusionConclusion BWH, HMSBWH, HMSQuality AssessmentQuality Assessment Site vs. SubjectSite vs. Subject: Variability across subjects: Variability across subjects >variability>variability across sitesacross sites Field StrengthField Strength: 3T and 4T were better than 1.5T yielding more: 3T and 4T were better than 1.5T yielding more activation and less variability in sensitivity and specificityactivation and less variability in sensitivity and specificity RunsRuns: There was a non-constant effect after resting and task: There was a non-constant effect after resting and task periodsperiods
    • 26. RemarkRemark BWH, HMSBWH, HMSQuality AssessmentQuality Assessment Our findings may help develop aOur findings may help develop a calibration plan to minimize the variabilitycalibration plan to minimize the variability introduced by the sitesintroduced by the sites Enabling us to pool independentEnabling us to pool independent functional data of normal andfunctional data of normal and schizophrenic subjects across differentschizophrenic subjects across different institutionsinstitutions
    • 27. Future ResearchFuture Research Standardization across subjectsStandardization across subjects Degree of smoothingDegree of smoothing schizophrenic vs. healthy controlsschizophrenic vs. healthy controls Longitudinal changes overtimeLongitudinal changes overtime BWH, HMSBWH, HMSQuality AssessmentQuality Assessment
    • 28. ReferencesReferences Genovese CR, Noll, DC and Eddy, WF.Genovese CR, Noll, DC and Eddy, WF. EstimatingEstimating test-retest reliability in fMRI I. statisticaltest-retest reliability in fMRI I. statistical methodology. Magnetic Resonance in Medicinemethodology. Magnetic Resonance in Medicine 1997; 38: 497-507.1997; 38: 497-507. Le TH and Hu X.Le TH and Hu X. Methods for assessing accuracyMethods for assessing accuracy and reliability in functional MRI. NMR inand reliability in functional MRI. NMR in Biomedicine 1997; 10: 160-164.Biomedicine 1997; 10: 160-164. Machielsen WCM, Rombouts SARB, Barkhof F,Machielsen WCM, Rombouts SARB, Barkhof F, Scheltens P, and Witter MP.Scheltens P, and Witter MP. fMRI of visualfMRI of visual encoding: reproducibility of activation. Humanencoding: reproducibility of activation. Human Brain Mapping 2000; 9: 156-164.Brain Mapping 2000; 9: 156-164. Maitra R, Roys SR, and Gullapalli RP.Maitra R, Roys SR, and Gullapalli RP. Test-retestTest-retest reliability estimation of functional MRI Data.reliability estimation of functional MRI Data. Magnetic Resonance in Medicine 2002; 48: 62-70.Magnetic Resonance in Medicine 2002; 48: 62-70. Quality AssessmentQuality Assessment BWH, HMSBWH, HMS
    • 29. Warfield SK, Zou KH, Wells WM III.Warfield SK, Zou KH, Wells WM III. SimultaneousSimultaneous Truth and Performance Level EstimationTruth and Performance Level Estimation (STAPLE): An Algorithm for the Validation of(STAPLE): An Algorithm for the Validation of Image Segmentation. IEEE Transactions onImage Segmentation. IEEE Transactions on Medical Imaging 2004; 23: 903-921.Medical Imaging 2004; 23: 903-921. Warfield SK, Zou KH, Wells WM III.Warfield SK, Zou KH, Wells WM III. Validation ofValidation of image segmentation andimage segmentation and expert quality with anexpert quality with an expectation-maximization algorithm.expectation-maximization algorithm. MICCAIMICCAI 2002, LNCS 2002; 2488: 290-297.2002, LNCS 2002; 2488: 290-297. Wei XC, Yoo S-S, Dickey CC, Zou KH, GuttmannWei XC, Yoo S-S, Dickey CC, Zou KH, Guttmann CRG,CRG, Panych LP.Panych LP. Functional MRI of auditory verbalFunctional MRI of auditory verbal workingworking memory: long-term reproducibility analysis.memory: long-term reproducibility analysis. NeuroImage 2004; 21: 1000-1008.NeuroImage 2004; 21: 1000-1008. Quality AssessmentQuality Assessment ReferencesReferences on fMRI and EM BWH, HMSBWH, HMS
    • 30. Zou KH, Wells MW III, Kikinis R,Zou KH, Wells MW III, Kikinis R, Warfield.Warfield. ThreeThree validation metrics for automatedvalidation metrics for automated probabilisticprobabilistic image segmentation of brain tumors. Statistics inimage segmentation of brain tumors. Statistics in Medicine 2004; 23: 1259-1282.Medicine 2004; 23: 1259-1282. Zou KH, Warfield SK, Fielding JR, Tempany CM,Zou KH, Warfield SK, Fielding JR, Tempany CM, Wells MW III,Wells MW III, KKaus MR, Jolesz FA, Kikinis R.aus MR, Jolesz FA, Kikinis R. Statistical validation based on parametric receiverStatistical validation based on parametric receiver operating characteristic analysis of continuousoperating characteristic analysis of continuous classification data. Academic Radiology 2003; 10:classification data. Academic Radiology 2003; 10: 1359-1368.1359-1368. Zou KH, Warfield SK, Bharatha A, Tempany CMC,Zou KH, Warfield SK, Bharatha A, Tempany CMC, Kaus M, Haker S, Wells WM III, Jolesz FA, KikinisKaus M, Haker S, Wells WM III, Jolesz FA, Kikinis R.R. Statistical validation of imagage segmentationStatistical validation of imagage segmentation quality based on a spatial overlap index.quality based on a spatial overlap index. AcademicAcademic Radiology 2004; 11: 178-189.Radiology 2004; 11: 178-189. Quality AssessmentQuality Assessment References on Validation MetricsReferences on Validation Metrics BWH, HMSBWH, HMS

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