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Exploring the temporal quality of fMRI acquisitions

MICCAI 2009 fMRI data analysis workshop. Exploring the temporal quality of fMRI acquisitions. B. Scherrer, O. Commowick , S. K. Warfield. Exploring the temporal quality of fMRI acquisitions. INTRODUCTION A PARADIGM-CENTERED APPROACH EVALUATION SIMULATED ARTIFACTED ACQUISITIONS

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Exploring the temporal quality of fMRI acquisitions

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  1. MICCAI 2009 fMRI data analysis workshop Exploring the temporal quality of fMRI acquisitions B. Scherrer, O. Commowick, S. K. Warfield

  2. Exploring the temporal quality of fMRI acquisitions INTRODUCTION A PARADIGM-CENTERED APPROACH EVALUATION SIMULATED ARTIFACTED ACQUISITIONS REAL PEDIATRIC IMAGING CONCLUSION/DISCUSSION

  3. Introduction Initial context: brain surgery planning (epilepsy, lesion, …) Preoperative fMRI to localize precisely some cognitive functions If no activation is detected If a unusual pattern is detectedIf a lower signal is detected • Is it due to the lesion? • Is it due to artifacts (motion) ? • Did the patient failed to do the task?(low patient cooperation quality) The quality assessment of fMRI acquisitions is crucial

  4. fMRI qualityassessment Inter-experiment quality assessment • Quality Assurance (QA) methods measure the scanner performance stability between centers • Test-retest methods : Quantification of activations certainty over several replicates of the same experimental paradigm [Genovese 1997, Maitra 2009] Intra-experiment quality assessment • Is there major artifacts (motion, …) ? • Did the patient performed the task well (patient cooperation quality) ? Most approaches to date focus on signal characteristics only • Motion estimation based on image variance and/or registration • Signal modeling improvement (auto-correlation, spatial dependencies, …) • …… • Do not consider the experimental paradigm • Could hardly provide information about the patient cooperation quality

  5. Introduction In this work We explore a new way to assess the fMRI data quality • A paradigm-centered approach

  6. Exploring the temporal quality of fMRI acquisitions INTRODUCTION A PARADIGM-CENTERED APPROACH EVALUATION SIMULATED ARTIFACTED ACQUISITIONS REAL PEDIATRIC IMAGING CONCLUSION/DISCUSSION

  7. A paradigm-centered approach • We currently consider block-design paradigms • Repetition of two (or more) conditions in an alternating pattern NB blocks … One block … … … … We propose to focus on the relative information contained in each block, not on signal characteristics. C2 C1 C1 C1 C2 C2 Does each block lead to similar activations? • Could, at least in part, reflect the patient cooperation quality

  8. Information contained in each blocks ? Block analysis Experimental paradigm … What information is contained in that block? For each block Construct ion of a virtual acquisition, composed of Nrepeatrepetitions of xb INCREASES THE SIGNAL … … … … … … … + DECREASES CORRELATIONS Addition of a Gaussian noise Binary activation map for each block • Computation of a thresholdedactivation map (SPM5: realignment, smoothing, GLM)

  9. Information contained in each blocks ? Result of the block analysis Experimental paradigm … B1 B2 BNB NB binary activations maps … … … • How to measure the quality/homogeneity of blocks? • B1, …, BNB considered as the artifacted observation of a (unknown) underlying true activation map T • If we knew T, we could estimate performance parameters associated with each block (specificity, sensitivity) T • Missing-data problemEstimate both T andthe performance parameters Similar idea as in STAPLE (Simultaneous Truth And Performance Level Estimation)

  10. STAPLE A missing data problem B1 Observed data: the NB binary activation mapsD [NxNB] : observed binary decision matrix (N=number of voxels) Dib=1 if the voxel i is activated in Bb. Missing data:T [N] : the “true” underlying binary activation map Parameters: p,q : performances for each of the Nb activations maps p=(p1, …, pNB): sensitivity q=(q1, …, qNB): specificity B2 BNB ? AIM: estimation of the performance parameters ML estimation: maximize the log-likelihoodGenerally not tractable • EM (Expectation-Maximization) algorithm: iterative algorithm. • Idea: maximize at each iteration local approximations of the likelihood Maximize at each iteration (k) the expectation of the complete log-likelihood:

  11. STAPLE - EM algorithm EM algorithm E-Step and M-Step at each iteration (k) E-Step: compute involve the computation of M-Step: update the parameter estimates by maximizing Q over (p,q)leads to:

  12. Synthesis … I. BLOCK ANALYSISComputation of a binary activation map per block BNB B1 B2 II. PERFORMANCE ANALYSISSTAPLE - EM algorithm (Simultaneous Truth And Performance Level Estimation) … … … EM III. OUTPUT Performance parameter Performance parameter Performance parameters Estimated true activation map

  13. Exploring the temporal quality of fMRI acquisitions INTRODUCTION A PARADIGM-CENTERED APPROACH EVALUATION SIMULATED ARTIFACTED ACQUISITIONS REAL PEDIATRIC IMAGING CONCLUSION/DISCUSSION

  14. Evaluation In practice for the evaluation:Low proportion of active voxels compared to the total number of voxels • We prefer to show results in terms of • Positive predictive value (PPVb)proportion of active voxels in Bb which are also active in T • Negative predictive value (NPVb)proportion of non-active voxels in Bb which are also non-active in T • Evaluation with a finger tapping experiments • Experimental block-design paradigm:One minute per block : 30s of left finger tapping / 30s of right finger tapping • Siemens 3T scanner, 12 channel head coil(EPI, TR=3s, TE=30ms, matrix size=64x64, slice thickness = 3.75 mm, pixel size = 3.25 mm)

  15. Evaluation – simulated artifacts Hand change delay GLM with the 4 blocks GLM without block 3

  16. Evaluation – simulated artifacts Double task experiment GLM with the 3 blocks In this case removing the block 2 decreases the final result GLM without block 2

  17. Evaluation – simulated artifacts Motion experiment GLM with the 4 blocks GLM without block 3 Three “normal” blocks PPV and NPV are approximately homogeneous

  18. Evaluation – Real pediatric imaging Real pediatric imaging I (acquired in the Children’s Hospital, Boston)3-blocks finger-tapping clinical acquisitions GLM with the 3 blocks GLM without block 1

  19. Evaluation – Real pediatric imaging Real pediatric imaging II (acquired in the Children’s Hospital, Boston) GLM with the 3 blocks GLM without block 1

  20. Exploring the temporal quality of fMRI acquisitions INTRODUCTION A PARADIGM-CENTERED APPROACH EVALUATION SIMULATED ARTIFACTED ACQUISITIONS REAL PEDIATRIC IMAGING CONCLUSION/DISCUSSION

  21. Discussion • Our approach is paradigm-centeredFocus on the relative homogeneity of blocks instead of signal characteristics Can take into account the patient cooperation quality Remark: detected poor blocks: poor relative to the complete experiment the task has to be correctly performed during some blocks • First results shows interesting detection capabilitiesSimulated artifacts, real pediatric imagingEven with only a few blocks (clinically more realistic) • Statistically problematic for only a few blocks?The estimated “true” activation map may not have a real biological meaningBut the aim here: evaluate the homogeneity of the blocks • The reason for blocks inhomogeneity: cannot be determinedCould be the patient cooperation • Could be signal artifacts (motion, …)

  22. Discussion Paradigm-centered quality assessment appears as promising Clear room for improvement • Repeating the block and adding noise : ad-hocery?Introduce discontinuities & parameters (Nrepeat, Noise intensity)In practice better results than playing with the SPM threshold A better analysis of each block should be considered • A path to explore: to work with probability mapsBinary maps : (1) prevents propagating uncertainties (2) threshold to define  Compute and compare posterior probability maps SOFT-Staple More developments in paradigm-centered approaches should be greatly valuable for fMRI quality assessment • Extensions to event-related designs: To analyze the relative homogeneity of each event responseThe inter-trial time should be sufficiently long (HR  returns to offset level) • Second statistical level analysis To Analyze the relative homogeneity of different subjects activation patterns How normal an activation pattern is compared to the group

  23. THANK YOU E-mail: benoit.scherrer@childrens.harvard.edu Web: http://www.crl.med.harvard.eduhttp://www.benoitscherrer.com

  24. Functional MRI (fMRI) Number of publications with ‘fMRI’ in the title or in the abstract (source: PUBMED). Functional MRI : growing popularity over the past 15 years • Include: • Methodology papers • Neuroscience/clinical studies • … fMRI data analysis a challenging task, sensitive to the acquisition quality • Low resolution • Low signal to noise ratio The quality assessment of fMRI acquisitions is crucial

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