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Comparison of Single Shot Methods for R2* Comparison

Comparison of Single Shot Methods for R2* Comparison. Presentation for Kana Lab, Lab Meeting Rishi Deshpande Thesis Committee: Dr. Donald Twieg, Chair Dr. N. Shastry Akella Dr. Georg Deutsch.

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Comparison of Single Shot Methods for R2* Comparison

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  1. Comparison of Single Shot Methods for R2* Comparison • Presentation for Kana Lab, Lab Meeting • RishiDeshpande • Thesis Committee: • Dr. Donald Twieg, Chair • Dr. N. ShastryAkella • Dr. Georg Deutsch University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  2. Outline • Introduction • Basics of MRI, fMRI • Significance of reliable R2* estimation • Single-shot methods: MEPI and SS-PARSE • Experiment and Analytical Methods • Trajectory generation • Data acquisition • Reconstruction and comparison of accuracy and temporal variability • Discussion • Conclusion • Future scope University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  3. Basics of MRI Image Acquisition RF pulse (sinc/Gaussian/square) 1H nuclei within tissues 1H nuclei under external magnetic field Applying a 2D-FFT to the signal data generates 2D-images in the imaging plane. 1H get dislodged from steady state . They release energy while returning to steady state. Energy is collected as a function of 2D-Inverse Fourier Transform Sources: http://www.cs.sfu.ca/~stella/main/_spins_figure8.gifhttp://www.cs.sfu.ca/~stella/main/_spins_figure7.gif http://videos.howstuffworks.com/discovery-health/14537-human-atlas-mri.jpghttp://www.mr-tip.com/exam_gifs/brain_mri_transversal_t2_002.jpg University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd , 2009

  4. fMRI • Control/Stimulation acquisition Estimation of Neuronal activity ↓ BOLD effect ↓ R2* University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  5. Significance of reliable R2* estimation BOLD Response Model: *BOLD = Blood Oxygenation Level Dependent * R2* = 1/T2* University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  6. R2* Measurement: Multiple Shot Method Gradient Echo Multiple Shot (GEMS) • Echoes can be closely stacked, thus enabling accurate R2* calculation • Serves as a gold standard in the comparison study University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  7. Single Shot Methods Multiple Gradient Echo – Echo Planar Imaging (MEPI) University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  8. SS-PARSE Single-Shot Parameter Assessment by Retrieval from Signal Encoding Estimates map:M(x) Censored for gratuitous math Conventional model Include local phase evolution & local signal decay Estimate maps (images) of M(x), R2*(x), ω(x) by solving an inverse problem. It uses Progressive Length Conjugate Gradient (PLCG) algorithm which requires optimal parameters to minimize least squared residuals to generate parameter maps. SS-PARSE model Censored for gratuitous math M(x) w(x) R2*(x) University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  9. Comparing Conventional MRI & SS-PARSE Methods Encoding Strategy (k-trajectory) k, t space k space Modeling Acquired Data Inverse FFT Decoding Strategy Inverse Estimation University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  10. Source: http://commons.ucalgary.ca/at-wld/images/cartoon02.gif University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  11. Project Goals - experimental • Create gradient waveforms and generate trajectories for 7 different gradient strengths (1.9 G/cm to 3.8 G/cm): • Implement the sequence on Varian 4.7 T vertical scanner using phantoms • Compare performance of SS-PARSE with MEPI based on: • Accuracy of R2* estimates (compare with Gradient-Echo results) • Temporal variability of R2* (over time-series of 50 acquisitions) • Find correlation between R2* and TSD values • Find correlation between maximum gradient strength and accuracy University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  12. Project goals – Theoretical Inferences • Factors contributing towards performance of SS-PARSE: • Gmax values – Find relationship between • Gmax and R2* estimates (compared with gradient-echo values) • Shimming – Find effects of field inhomogeneity in SS-PARSE and MEPI studies. • Performance over R2*range - Observe the changes in temporal behavior over R2* values typically found in human brain tissues (20 to 40 sec-1 in 4.7 T MRI systems) University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  13. k-trajectory Generation and Calibration Calibration data acquired at: ±2, ±4, ±6, ±8, ±10, ±12 mm displacements in x & y planes For Gmax: 1.9, 2.29, 2.5, 2.9, 3.2, 3.5 and 3.8 G/cm. 65 ms Censored for gratuitous math 1.9 G/cm 2.29 G/cm 2.5 G/cm 2.9 G/cm 3.2 G/cm 3.5 G/cm 3.8 G/cm University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd , 2009

  14. Phantom For Data Acquisition R2* Range: 15 sec-1 to 45 sec-1 University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd , 2009

  15. Data Acquisition: GEMS, MEPI and SS-PARSE Hardware: 4.7 T 60 cm-vertical-bore Varian primate MRI system (Varian Inc., Palo Alto, CA) • SS-PARSE acquisitions • Per study = (7x Gmax) x (50x repetitions) • Repetition time = 5 second • Slice Thickness = 3 mm • MEPI acquisitions • Per study = 50x repetitions at 4 echo times • Resolution = 64 x 64 • Repetition time = 5 second • Echo Times = 22.3, 66.8, 96.4 and 124.2 millisecond • Slice Thickness = 3 mm • GEMS acquisitions • Per study = 16 x echo times • Resolution = 128 x 128 • Echo Times = 5, 8, 10, 12, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65 and 70 millisecond • Slice Thickness = 3 mm • Performed total 18 experiments to obtain the R2* values in the desired range (15 to 45 sec-1) University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  16. Source: http://www.hagencartoons.com/cartoon159.gif University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  17. Development of GUI For Analysis & File Handling File Handling PLCG Tweakers Parameter Maps University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  18. R2* Evaluation: GEMS and MEPI MEPI GEMS • R2* is computed over a ROI • Monoexponential fitting of signal to echo times. University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd , 2009

  19. Parameters Estimates in SS-PARSE • Reconstruction (SS-PARSE) • Parameter maps were computed using the PLCG algorithm from all the SS-PARSE acquisitions. Maps were created for all Gmax values (1.9 G/cm to 3.8 G/cm). University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  20. Accuracy of R2* Estimation SS-PARSE and MEPI estimates and accuracy plot at SS-PARSE Gmax = 2.9 G/cm R2* estimates from SS-PARSE and MEI plotted vs. R2* from GEMS Ratio of R2* accuracy plotted vs. R2* estimates from GEMS University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  21. Accuracy Over Gradient Amplitudes Accuracy of R2* estimation computed by using the ratio: |R2*MEPI - R2*GEMS | |R2*SSPARSE - R2*GEMS| was > 1 for following percentage points over the Gmax range: 1.9 G/cm: 61.3% 2.29 G/cm: 64.2% 2.5 G/cm: 66.4% 2.9 G/cm: 68.3% 3.2 G/cm: 67.6% 3.5 G/cm: 65.6% 3.8 G/cm: 61.2% Accuracy of estimation (ratio) was maximum at Gmax = 2.9 G/cm University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  22. Temporal Variation of R2* Over 50 Repetitions • TSD computed for: • Each pixel over 50 repetitions • Each ROI over 50 repetitions • For MEPI and SS-PARSE • For Gmax with best accuracy University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  23. Mark with lower temporal variability, Thus lower TSD Good Mark with higher temporal variability, Thus higher TSD Not Good University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  24. Depiction of TSD in MRI Studies University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  25. TSD Plots R2* (GEMS) vs. TSD (SS-PARSE) • Dot indicates TSD at a single pixel • Each blob of pixels represents a tube with a different R2* • Scatter plot for the difference TSD(MEPI) – TSD (SS-PARSE) shows points around the difference = 0 line • Dots above the difference=0 line show locations where the performance of SS-PARSE was better than of MEPI R2* (GEMS) vs. TSD (MEPI) R2* (GEMS) vs. [TSD (MEPI) and TSD (SS-PARSE)] The difference was > 0 for 79.3% to 97.3% for R2* values between 15 sec-1 and 45 sec-1 University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  26. Performance Under Field Inhomogeneity MEPI SS-PARSE University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  27. Parameter Estimation Under Field Inhomogeneity • SS-PARSE parameter maps have an one-on-on correspondence with the ROI from GEMS image (obtained before intention deshimming) • MEPI image appears distorted in one direction and the ROI does not correspond with ROI from GEMS. Even though we have studied the behavior of MEPI, the same behavior is also observed in standard EPI scans, which is the common modality used in clinical fMRIsudies. • R2* computation in MEPI is impossible under field-inhomogeneity because of a noticeable geometric distortion. University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  28. Source: http://www.yachigusaryu.com/blog/pics/sci_principles_cartoon.jpg University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  29. Conclusions • Gradient waveforms for seven Gmax values were developed for SS-PARSE and were used to acquire phantom data • Performance of SS-PARSE and MEPI was compared using GEMS as the gold standard (for accuracy and TSD) over range of Gmax values. • Performance of SS-PARSE improved with increasing gradient amplitude until 2.9 G/cm. Thereafter the performance deteriorates. • SS-PARSE has a lower TSD than MEPI. This means it can estimate the parameters much reliably over several repetitions when used in fMRI studies. • SS-PARSE is able to reconstruct reliable parameter maps even in the presence of field inhomogeneities. University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  30. Future Scope • PLCG algorithm requires adjusting the algorithm tweakers heuristically. With better knowledge about the estimation process we should be able to set the parameters in a deterministic manner. • With better problem conditioning, and with MRI systems capable of delivering more than 6.5 G/cm (hardware limit of Varian 4.7 T system), we should be create trajectories with much higher sampling rates, thus giving accurate parameter estimation. • Parallel acquisition and multiple shot trajectories, increases the number of sample points, thus improving conditioning of the inverse problem and leading to more accurate estimates. University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

  31. Acknowledgement • Parents and Sister • FriendsMichelleJonChris • Grant Support: NIH # R21/R33 EB003292 • City of Birmingham • Advisor:Dr. Donald Twieg • Committee MembersDr. N. ShastryAkellaDr. Georg Deutsch • Dr. Stan Reeves (Auburn) • CDFI & VSRC colleagues:Mark BoldingRajiv MenonNingzhi LiMatt WardDebbie WhittenJerry Millican University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  32. Thank You http://upload.wikimedia.org/wikipedia/commons/b/b1/Thumbs_up_by_Wakalani.jpg University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  33. Questions Source: http://www.lifehack.org/wp-content/files/2007/12/question.jpg University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  34. Extras University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd, 2009

  35. Rosette (k,t)-trajectories acquire more information on R2* than multiple-echo EPI trajectory Cramer-Rao Lower Bound for standard deviation of error for Multiple-Echo EPI (MEPI) and Rosette, SNR=200 MEPI Rosette Idealized radial s.d. of R2* R2* (sec-1) University of Alabama at Birmingham, Department of Psychology, Lab Meeting Presentation, September 3rd 2009

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