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DW-MRI and MRS to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas

Protocol MRS data status 12/18/07 – 1/6/08 Thomas Chong. DW-MRI and MRS to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas. Status Summary 12/18/07 - 1/6/08. Last Time Summary overview of MRS work Phantom experiments, dbase, processing of patient data, issue of noisy data

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DW-MRI and MRS to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas

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  1. Protocol MRS data status 12/18/07 – 1/6/08 Thomas Chong DW-MRI and MRS to Differentiate Radiation Necrosis and Recurrent Disease in Gliomas

  2. Status Summary 12/18/07 - 1/6/08 • Last Time • Summary overview of MRS work • Phantom experiments, dbase, processing of patient data, issue of noisy data • discovery of EU INTERPRET project (tumor classifier app and large dbase of scan data)‏ • report on INTERPRET journal article • Questions/ Tasks from last time • Excellent background references

  3. Previous Tasks • Process patient 11 (now up to 12) scan data – not done yet • Answer questions from previous status - done • Return to INTERPRET website, continue looking for useful information • Read source ref for mean brain MRS data: Tate et al. NMR Biomed. 19:411-434, 2006 - Not done • Request e-mailed for access to their tool download page and database - done

  4. Questions • What is water-suppressed spectrum? • non-suppressed spectrum? • What is the water line artifact in spectrum? • Shimming procedure for optimization of field homogeneity? • What does van der Graaf, et al refer to as signal linearity? • WBW (water bandwidth): line width at half max intensity of water resonance in real non-suppressed spectrum - a measure of field homogeneity [1]. significance?

  5. What exactly is water-suppression? • References, possibly useful, but unavailable online • Sklenar, Vladimir. Selective excitation techniques for water suppression in one- and two-dimensional NMR spectroscopy. Basic Life Sciences (1990), 56(NMR Appl. Biopolym.), 63-84. CODEN: BLFSBY ISSN:0090-5542. CAN 115:172984 AN 1991:572984 • Moonen, Chrit T. W.; Van Zijl, Peter C. M. Highly effective water suppression for in vivo proton NMR spectroscopy (DRYSTEAM).Journal of Magnetic Resonance (1969-1992) (1990), 88(1), 28-41. CODEN: JOMRA4 ISSN:0022-2364. CAN 113:55290 AN 1990:455290 • Dumoulin, Charles L. The application of multiple-quantum techniques for the suppression of water signals in proton NMR spectra.Journal of Magnetic Resonance (1969-1992) (1985), 64(1), 38-46. CODEN: JOMRA4 ISSN:0022-2364. CAN 103:119241 AN 1985:519241 • Hore, P. J. Two-dimensional chemical-shift correlation using water suppression pulses.Journal of Magnetic Resonance (1969-1992) (1984), 56(3), 535-8. CODEN: JOMRA4 ISSN:0022-2364. CAN 100:113737 AN 1984:113737 • Useful reference • Proton MR Spectroscopic Imaging without Water Suppression. Jan Willem C. van der Veen, PhD, Daniel R. Weinberger, MD, Gioacchino Tedeschi, MD, Joseph A. Frank, MD and Jeff H. Duyn, PhD • http://radiology.rsnajnls.org/cgi/content/abstract/217/1/296

  6. Water Suppression • Def. Suppression of water signal in proton NMR. In brain, necessary because • water conc. 30-55M vs mM for metabolites • Limited dynamic range of MR receiver (pre-amp & A/D converter)‏ • Suppression techniques • Popular Chemical-shift-selective saturation -CHESS (van der Veen 2000). water suppression pulse. • Haas A, Frahm J, Haenicke W, Matthei D. 1H NMR chemical shift selective (CHESS) imaging, Phys Med Biol 1985; 30:341-344. • Suppression errors increase w/ non-homogeneity of volume of interest. Leads to signal distortion. • What do these errors look like, and do we see them?

  7. With and Without Water Suppression

  8. Water Suppression pg 2 • Interesting results from van der Veen, 2000: • Improved hardware and signal processing techniques extends dynamic range • Thereby, allowing for acq of metabolite data w/o distorting suppression • Further, water peak used as reference to allow for metabolite concentration data and data normalization, facilitates non-linear curve-fitting of metabolite peaks • A/D BW increased from 16bit to 20bit (effectively) by oversampling

  9. Non-Water Suppressed Method: A)B) processing & filtering, C) fit

  10. Water Suppression pg 3 • Van der Veen 2000 conclusion • Errors from water suppression pulse avoided and feasible w/ careful analysis of non-suppressed signal • “elimination particularly important in studies with large volume coverage” • “metabolites closest to water peak” (like Cho) are likely directly affected by CHESS. • saturation pulse causes an additional variance in these metabolites between studies because of differences in frequency offset and water-suppsn pulse calibrations. • Others Serrai 2002 (good paper)‏ • http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=1941760. References Hurd.

  11. Non-Water Suppression pg 4 • To Note • van ver Veen et. al.'s study was with 1.5T GE machine and was published in year 2000. • Stronger field -> greater resolution • What suppression method does our 3T use?

  12. Area for Patentable Ideas (e.g US Patent 6104191, 1998)‏ • Quantitative in vivo spectroscopy using oversampling, waterline referencing, and prior knowledge fitting • Disclosed is improved quantitative in vivo spectroscopy by means of F1-oversampled J-Resolved 2D spectroscopy. Reconstruction makes full use of internal signals for 2D water lineshape, T2 and partial volume correction, and analysis uses 2D complex model spectra fitting. The preferred embodiment of the new method integrates these features into PRESS localized brain spectroscopy and is carried out without the need for water suppression. • By Hurd 1998 (G.E.)‏

  13. Hurd, et al 1998 • “Water suppression is perhaps the most restrictive aspect of in vivo proton spectroscopy and spectroscopic imaging. • “The potential loss of signals and the impact of spin coupling are common problems which are aggravated in many cases by even modest in-homogeneity.

  14. Q: What is water line artifact? • Simply, artifacts resulting from suppression of the water resonance peak • Not just main peak but also sidebands • Higher field strength (3T vs 1.5T) gives greater S/N but greater level of imaging artifacts (Bernstein Jrn Mag Resn 2006)‏ • wrt MRI, but could extend to MRS

  15. Q: Shimming procedure for optimization of field homogeneity? • Introduction to Shimming • http://www.acornnmr.com/Sam/shimintro.htm • Described for 1-D NMR but likely analogous for MRS • My description: fine-adjustment of the magnetic field necessary to make it more homogeneous, i.e. parallel, and important for instrument performance. • Affects instrument performance: • Frequency resolution, signal lineshape “which is critical for solvent suppression”

  16. Q: What does van der Graaf, et al refer to as signal linearity? • This is from the quality paper, MRS quality assessment in a multicentre study on MRS-based classification of brain tumours. M. van der Graaf, et. al., NMR in Biomedicine, DOI: 10.1002, 2007. • Inferred from text: linearity of spectral characteristics wrt voxel volume, as a test voxel container in a phantom is increased in volume from (10mm)3 to (15mm)3 to (20mm)3

  17. Q: Significance of Water Bandwidth? • WBW (water bandwidth): line width at half max intensity of water resonance in real non-suppressed spectrum - a measure of field homogeneity [van der Graaf]. significance? • It's a measure of field homogeneity. How? I don't know. • Guess: more homogeneous <--> more narrow BW

  18. Good/Essential MRS Overview Reference • A.A. Maudsley, Future Prospects for in-vivo MR spectroscopy, Magnetic Resonance Materials in Physics, biology and Medicine 9 (1999) 164-166. • Maudsley - “first to describe MR Spectroscopic imaging”, UCSF • http://www.springerlink.com/content/w8743386w51360t0/fulltext.pdf • S/N, water suppression are very important factors in why MRS resolution is low. • Re: MRSI limitations/issues - “effect of B0 inhomogeneity making water suppression problematic and limiting observation of resonances close to water”

  19. More INTERPRET info • International Network For Pattern Recognition of Tumours Using Magnetic Resonance • Groups involved with INTERPRET (proj. ended 2002) extended to HealthAgents and eTumour • Huge multidisciplinary project w/ many areas of expertise • On cutting edge of in vivo MRS brain tumor classification research • HealthAgents • an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a distributed network of local databases or Data Marts.

  20. More INTERPRET info, pg 2 • Q: How useful was their prototype decision support system (DSS) in the clinical setting? • Results from demo evaluations 2002 (link)‏ • Survey of 52 participants from 14 countries • 21 clinicians, rest were physicists and spectrologists • Evaluations were very positive, particularly from clinicians • “The prototype decision support system (DSS) successfully classified 89% of the cases in an independent test set of 91 cases of the most frequent tumour types (meningiomas, low-grade gliomas and high-grade malignant tumours—glioblastomas and metastases).” from Tate, et al 2006. • Significance: When considering any outcome of our MRS-related studies for clinical use, it would help to be aware of this DSS tool.

  21. More INTERPRET info, pg 3 • Many, many related references to publications on website. http://azizu.uab.es/INTERPRET • Proton magnetic resonance spectroscopy (1H MRS) of human brain tumours: assessment ofdifferences between tumour types and its applicability in brain tumour categorization. C Majós, J Alonso, C Aguilera, M Serrallonga, J Pérez-Martín, JJ Acebes, C Arús, J Gili. European Radiology.2003 Mar;13(3):582-91. • The Contribution of 1H MRS to brain tumour diagnosis. M. Murphy, A. Loosemore, A. G. Clifton, F. A. Howe, A. R. Tate, S. A. Cudlip, P. R. Wilkins, J. R. Griffiths, and B. A. Bell. British Journal of Neurosurgery, 16:329-334, 2002. • MRUI - a tool interface available for processing in vivo MR spectra using time domain methods • Written in Java, requires access request for non-profits. • Accesses tools VARPRO, AMARES, HLSVD water-suppression algorithm • Conc: FuncTools as a research tool is sorely out-of-date

  22. Spatial Trends in Cho/NAA • Direction: “construct similar plots for anterior posterior distances, etc” • “can be more quantitative than with just images.” • Data at left for P1, exam 2916

  23. Spatial Trends in Cho/NAA P1 Exam 2916, Slice S36 • Same data already available through contour plots. Better, i.e. more spatial information, because 2-dimensional instead of 1-D and no interpolation assumptions made. http://radonc.wiki.zoho.com/P1-ratio-analysis-2916-to-3103-rev-0807.html

  24. Spatial Trends in Cho/NAA, P1 Med Slice

  25. Spatial Trends in Cho/NAA, P2 Med Slice

  26. Inf-Med-Sup Slice Spatial Trends in Cho/NAA, P1 ex 2916 • Voxels in middle are for medial slice S36 (may have to redo)‏

  27. Tasks • Process P11, P12 data • Generate color field plots for Inf-Med-Sup slices for P1 (2nd scan)‏ • Generate color field plots for Inf-Med-Sup slices for P2 (both scans) and P5 • Read source ref for mean brain MRS data: Tate et al. NMR Biomed. 19:411-434, 2006 • This is the INTERPRET results publication “Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra” • 26 co-authors

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