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PET Module Ana Beatriz Solana, MS Qu Tian (Teresa), MS Instructor: Dr. Charles Laymon.

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Presentation on theme: "PET Module Ana Beatriz Solana, MS Qu Tian (Teresa), MS Instructor: Dr. Charles Laymon."— Presentation transcript:

1 PET Module Ana Beatriz Solana, MS Qu Tian (Teresa), MS Instructor: Dr. Charles Laymon

2 Cocaine Study Literature: Cocaine-Dopamine - Decrease dopamine release - Toxic for animal DA neurons [Volkow et al. 1997; Martinez et al. 2007, 2009 & 2011; Seiden et al. 1987] Biological plausibility: Chronic cocaine use  loss of dopaminergic terminals Inconsistent results due to - The time since last use of cocaine - The reliable assessment VMAT2 - [ 11 C]DTBZ

3 Cocaine Study: VMAT2 - [ 11 C] DTBZ Objective To compare VMAT2 in 12 cocaine abusers vs. 12 healthy controls Method In vivo, [ 11 C] DTBZ nondisplaceable binding potential using kinetic analysis Acquisition protocol Hypothesis: Voxel-wise analysis would be valid as ROI approach. Specifically, [ 11 C] DTBZ BP ND would be lower in cocaine abusers than matched healthy controls in subregions of striatum as shown in previous ROI analysis. [ 11 C]DTBZ Arterial blood sample MRI Scan 1.5T MRI Scan 1.5T Transmission scan (10 min) Transmission scan (10 min) Emission data collection (60 min) Emission data collection (60 min) PET

4 Inter-frame Motion Correction* * Pxmod software **SPM8 software Normalization:** PET -> MR template Voxel-wise group analysis: cocaine vs. control ** Voxel-wise 2-tissue Compartment Model Voxel-wise SRTM2 Model Voxel-wise SRTM Model FULL MODEL* SIMPLIFIED MODELS* Analysis Pipeline

5 Inter-frame Motion Correction Normalization: PET -> MR template Voxel-wise group analysis: cocaine vs. control Voxel-wise 2-tissue Compartment Model Voxel-wise SRTM2 Model Voxel-wise SRTM Model FULL MODEL SIMPLIFIED MODELS Analysis Pipeline

6 Inter-frame Motion correction – Subjects can move over the time of the scan – Motion correction is needed to compute voxel Time Activity Curve Time Activity Curve F1 (15s) F2(15s) F3(15s) F9 (2m) F10 (5m) F11(5m) F18(5m) F19(5m) F20(5m)

7 Inter-frame Motion correction 1. Take one or the sum of a few consecutive frames w/o motion as the reference. 2. Sum the first 1-4 or 1-5 frames as the composite initial frame. Frame 1(15s) Frame 2(15s) Frame 3(15s) Frame 4 (15s) Frame 5 (60s) Frame 10 Frame 9-10 Frame 9-10-11 Woods, J Comp Assit Tomography 1998

8 3. Apply correction to all frames to the reference. 4. Apply transformation matrix from the composite initial frame to initial frames individually. 5. Check motion corrected images. Before correction After correction Inter-frame Motion correction Woods, J Comp Assit Tomography 1998

9 Analysis Pipeline Inter-frame Motion Correction Normalization: PET -> MR template Voxel-wise group analysis: cocaine vs. control Voxel-wise 2-tissue Compartment Model Voxel-wise SRTM2 Model Voxel-wise SRTM Model FULL MODEL SIMPLIFIED MODELS

10 PET 2-Tissue Compartment Model Arterial input function A clearance parameter from vasculature to brain A fraction moving to the specific compartment C2 A fraction of the radiotracer diffusing back to plasma If the specific binding is reversible, a fraction of the radiotracer transferring back to C1 Binding potential (BP) (nondisplaceable) =

11 ‘ ‘ Simplified Reference Tissue Model & Simplified Reference Tissue Model 2 Lammertsma and Hume, 1996; Wu and Carson, 2002 Assumption 2: Distribution volume: ROI = Ref Assumption 2: Distribution volume: ROI = Ref Assumption 1: ROI & Ref follow a 1T Assumption 1: ROI & Ref follow a 1T NOTE: - Both bias - SRTM < SRTM2 (k 2 ’ ) a 1 + C 2

12 SRTM & SRTM2 Lammertsma and Hume, 1996; Wu and Carson, 2002 Assumption 1: Both ROI and Reference tissue follows a 1T model RegionModelVTVT ChiSquareAICR2R2 Ref.1Tissue5.5795.73236.8130.963 Ref.2Tissue6.1830.332-13.8260.998 ROI1Tissue22.0450.217-26.7930.997 ROI2Tissue22.0120.246-19.8170.997 Assumption 2: The delivery from plasma to the receptor-rich region and the reference region is the same (K 1 /k 2 = K 1 ’ /k 2 ’ )

13 Single voxel TAC and model fit X(56),y(55),z(33) BP ND = 3.49 Taking one single voxel TACFitting the curve BP ND = 3.49 X(56),y(55),z(33) BP ND = 3.68 SRTM2 SRTM

14 Binding Potential Images AXIAL SAGITAL CORONAL Two tissue Compartment Model Simplified Ref. Tissue Model Simplified Ref. Tissue Model 2 VERY NOISY!!!

15 Analysis Pipeline Inter-frame Motion Correction Normalization: PET -> MR template Voxel-wise group analysis: cocaine vs. control Voxel-wise 2-tissue Compartment Model Voxel-wise SRTM2 Model Voxel-wise SRTM Model FULL MODEL SIMPLIFIED MODELS

16 Normalization Steps Method 1PET -> PET template Method 2PET -> MR -> MR template Method 3PET -> MR -> MR template -> MNI space Method 4PET -> MR -> MNI space Why method 2? 1.Our template is more similar to our images than MNI 2.Subregions of striatum do not appear in standard atlases ROIs manually drawn in the template ROIs transformed to the individual native space

17 Normalization: DARTEL Template Ashburner, Neuroimage 2007 24 MR images 1.5x1x1mm ACPC reorientation Tissue Segmentation Template generation Deformation Maps Composite template

18 Normalization: PET images 2) Apply PET -> MR estimation to BP images (NO RESLICE) MR image Mutual Info N. Mutual Info Entropy Corr Coeff Norm. Cross Coeff 1) Corregistration Reference frame PET to MR (ESTIMATE) 3) Apply MR -> template deformation maps RESLICE (1.5x1.5x1.5mm)

19 Analysis Pipeline Inter-frame Motion Correction Normalization: PET -> MR template Voxel-wise group analysis: cocaine vs. control Voxel-wise 2-tissue Compartment Model Voxel-wise SRTM2 Model Voxel-wise SRTM Model FULL MODEL SIMPLIFIED MODELS

20 Statistical results: cocaine < control SRTM SRTM2 6mm Gaussian smooth, mask BP>0.5, FWE corrected p<0.1 L L L Ldorsal caudate L (18) dorsal caudate L & anterior putamen L (66) posterior putamen L(30) anterior putamen R (11) 4.09 0 t value 4.55 0 t value

21 Comparative with ROI approach Functional subdivisionAnatomical subdivisionp FWEcorrected Associate striatum0.002 Dorsal caudate0.002 Anterior Putamen0.007 Caudate0.02 Sensorimotor striatum0.002 Posterior putamen0.002 Limbic striatum0.05 Ventral striatum0.05 Functional subdivisionAnatomical subdivisionCluster p FWEcorrected N. cluster voxels Associate striatum Dorsal caudate0.02566 Anterior Putamen0.06611 Sensorimotor striatum Posterior putamen0.04430 VOXEL – WISE RESULTS PREVIOUS ROI RESULTS

22 Take home message VOXEL WISE VS. ROI BEST RESULTS WITH SRTM2 IN OUR PROJECT CAUTION WITH SIMPLIFIED MODELS ASSUMPTIONS MR TEMPLATE: o IMPROVES NORMALIZATION AND STATISTICS o ONLY DRAW ROIs IN TEMPLATE

23 THANK YOU FOR YOUR ATTENTION REFERENCES Narendran et al. Am J Psychiatry 169: 55-63, 2012 Narendran et al. Synapse 2011 Boileau et al. J Neurosci: 9850–9856, 2008 Narendran et al. JPET vol. 333 no. 2: 533-539, 2010 Wu and Carson, J Cereb Blood Flow & Metab: 1440–1452, 2002 Lammertsma and Hume, Neuroimage 1996 Ashburner, Neuroimage 2007 Woods, J Comp Assit Tomography 1998 ACKNOWLEDGEMENTS Charles Laymon Seong-Gi Kim Rajesh Narendran Bill Eddy Julie Price Michael L Himes Carl Becker Scott Mason James Ruszkiewicz Cristy Matan Matthew Oborski Chris Cieply Davneet Minhas

24 SMOOTHING

25 Normalization Steps Method 1PET -> PET template Method 2PET -> MR -> MR template Method 3PET -> MR -> MR template -> MNI space Method 4PET -> MR -> MNI space Why method 2? 1.Our template is more similar to our images than MNI 2.Subregions of striatum do not appear in standard atlases 3.Evaluation of semi-automatic procedure to draw the ROIs ROIs manually drawn in the template ROIs transformed to the individual native space


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