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Global diffusion tensor imaging derived metrics differentiate glioblastoma multiforme vs. normal brains by using discriminant analysis: introduction of a novel whole-brain approach


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1. Zolal A, Hejcl A, Malucelli A, Novakova M, Vachata P, Bartos R, et al. Distant white-matter diffusion changes caused by tumor growth. J Neuroradiol 2013; 40: 71-80.10.1016/j.neurad.2012.05.006 Search in Google Scholar

2. Rees JH, Smirniotopoulos JG, Jones RV, Wong K. Glioblastoma multiforme: radiologic-pathologic correlation. Radiographics 1996; 16: 1413-38.10.1148/radiographics.16.6.8946545 Search in Google Scholar

3. Watanabe M, Tanaka R, Takeda N. Magnetic resonance imaging and histopathology of cerebral gliomas. Neuroradiology 19 92; 34: 463-9.10.1007/BF00598951 Search in Google Scholar

4. Zimmerman RA. Imaging of adult central nervous system primary malignant gliomas. Staging and follow-up. Cancer 1991 ; 67: 1278-83.10.1002/1097-0142(19910215)67:4+<1278::AID-CNCR2820671526>3.0.CO;2-U Search in Google Scholar

5. Johnson PC, Hunt SJ, Drayer BP. Human cerebral gliomas: correlation of postmortem MR imaging and neuropathologic findings. Radiology 198 9; 170: 211-7.10.1148/radiology.170.1.2535765 Search in Google Scholar

6. DeAngelis LM. Brain tumors. N Engl J Med 2001 ; 344: 114-23.10.1056/NEJM200101113440207 Search in Google Scholar

7. Smets T, Lawson TM, Grandin C, Jankovski A, Raftopoulos C. Immediate post-operative MRI suggestive of the site and timing of glioblastoma recurrence after gross total resection: a retrospective longitudinal preliminary study. Eur Radiol 2013 ; 23: 1467-77.10.1007/s00330-012-2762-1 Search in Google Scholar

8. De Bonis P, Anile C, Pompucci A, Fiorentino A, Balducci M, Chiesa S, et al.The influence of surgery on recurrence pattern of glioblastoma. Clin Neurol Neurosurg 201 3; 115: 37-43.10.1016/j.clineuro.2012.04.005 Search in Google Scholar

9. Young GS. Advanced MRI of adult brain tumors. Neurol Clin 200 7; 25: 947-73.10.1016/j.ncl.2007.07.010 Search in Google Scholar

10. Cortez-Conradis D, Favila R, Isaac-Olive K, Martinez-Lopez M, Rios C, Roldan- Valadez E. Diagnostic performance of regional DTI-derived tensor metrics in glioblastoma multiforme: simultaneous evaluation of p, q, L, Cl, Cp, Cs, RA, RD, AD, mean diffusivity and fractional anisotropy. Eur Radiol 2013 ; 23: 1112-21.10.1007/s00330-012-2688-7 Search in Google Scholar

11. Chaudhry NS, Shah AH, Ferraro N, Snelling BM, Bregy A, Madhavan K, et al. Predictors of long-term survival in patients with glioblastoma multiforme: advancements from the last quarter century. Cancer Invest 2013 ; 31: 287-308.10.3109/07357907.2013.789899 Search in Google Scholar

12. Lopez-Acevedo ML, Martinez-Lopez M, Favila R, Roldan-Valadez E. Secondary MRI-findings, volumetric and spectroscopic measurements in mesial temporal sclerosis: a multivariate discriminant analysis. Swiss Med Wkly 2012 ; 142: w13549.10.4414/smw.2012.13549 Search in Google Scholar

13. Toh CH, Wei KC, Ng SH, Wan YL, Lin CP, Castillo M. Differentiation of brain abscesses from necrotic glioblastomas and cystic metastatic brain tumors with diffusion tensor imaging. Am J Neuroradiol 2011 ; 32: 1646-51.10.3174/ajnr.A2581 Search in Google Scholar

14. Wang W, Steward CE, Desmond PM. Diffusion tensor imaging in glioblastoma multiforme and brain metastases: the role of p, q, L, and fractional anisotropy. Am J Neuroradiol 20 09; 30: 203-8.10.3174/ajnr.A1303 Search in Google Scholar

15. Rorden C, Karnath HO, Bonilha L. MRIcron dicom to nifti converter. In: Neuroimaging Informatics Tools and Resources Clearinghouse (NITRC). Available from: http://www.mccauslandcenter.sc.edu/mricro/mricron/dcm2nii.html, Accessed on June 07, 2012. Search in Google Scholar

16. Smith SM, Jenkinson M, Woolrich MW, Beckmann CF, Behrens TE, Johansen- Berg H, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 200 4: 23: 208-21.10.1016/j.neuroimage.2004.07.051 Search in Google Scholar

17. Smith SM. Fast robust automated brain extraction. Hum Brain Mapping 2002; 17: 143-55.10.1002/hbm.10062 Search in Google Scholar

18. Moseley ME, Cohen Y, Kucharczyk J, Mintorovitch J, Asgari HS, Wendland MF, et al. Diffusion-weighted MR imaging of anisotropic water diffusion in cat central nervous system. Radiology 1990 ; 176: 439-45.10.1148/radiology.176.2.2367658 Search in Google Scholar

19. Le Bihan D, Mangin JF, Poupon C, Clark CA, Pappata S, Molko N, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging 2001; 13: 534-46.10.1002/jmri.1076 Search in Google Scholar

20. Brown SR, Gregory WM, Twelves CJ, Buyse M, Collinson F, Parmar M, et al. Designing phase II trials in cancer: a systematic review and guidance. Br J Cancer 201 1; 105: 194-9.10.1038/bjc.2011.235 Search in Google Scholar

21. Obuchowski NA, McClish DK. Sample size determination for diagnostic accuracy studies involving binormal ROC curve indices. Stat Med 1997 ; 16: 1529-42.10.1002/(SICI)1097-0258(19970715)16:13<1529::AID-SIM565>3.0.CO;2-H Search in Google Scholar

22. Tabachnik BG, Fidell SL. Discriminant analysis. In: Tabachnik BG, Fidell SL, editors. Using multivariate statistics. Boston: Pearson Education Inc.; 201 3. p. 377-438. Search in Google Scholar

23. Pallant J. Assesing normality. In: Pallant J, editor. SPSS survival manual. Crows Nest: Allen & Unwin; 2 011. p. 59-64. Search in Google Scholar

24. Pallant J. Multivariate analysis of variance. In: Pallant J, editor. SPSS survival manual. Crows Nest: Allen & Unwin; 20 11. p. 283-96. Search in Google Scholar

25. Chan YH. Biostatistics 104: correlational analysis. Singapore Med J 20 03; 44: 614-9. Search in Google Scholar

26. Field A. Output from the discriminant analysis. In: Field A, editor. Discovering statistics using SPSS. London: SAGE Publications Ltd; 20 09. p. 618-21. Search in Google Scholar

27. Cohen JW. Statistical power analysis for the behavioral sciences. 2nd edition. Hillsdale: Lawrence Erlbaum Ass ociates; 1988. Search in Google Scholar

28. Bossuyt PM, Reitsma JB, Bruns DE, Gatsonis CA, Glasziou PP, Irwig LM, et al. The STARD statement for reporting studies of diagnostic accuracy: explanation and elaboration. Ann Int Med 200 3; 138: W1-12.10.7326/0003-4819-138-1-200301070-00012-w1 Search in Google Scholar

29. Tabachnik BG, Fidell SL. Multicollinearity and singularity. In: Tabachnik BG, Fidell SL, editors. Using multivariate statistics. Boston: Pearson Education Inc.; 2 013. p. 88-91. Search in Google Scholar

30. Field A. Discriminant function variates. In: Field A, editor. Discovering statistics using SPSS. London: SAGE Publications Inc.; 200 9. p. 599-624. Search in Google Scholar

31. Pena A, Green HA, Carpenter TA, Price SJ, Pickard JD, Gillard JH. Enhanced visualization and quantification of magnetic resonance diffusion tensor imaging using the p:q tensor decomposition. Br J Radiol 20 06; 79: 101-9.10.1259/bjr/24908512 Search in Google Scholar

32. Budde MD, Xie M, Cross AH, Song SK. Axial diffusivity is the primary correlate of axonal injury in the experimental autoimmune encephalomyelitis spinal cord: a quantitative pixelwise analysis. J Neurosci 2009; 29: 2805-13.10.1523/JNEUROSCI.4605-08.2009 Search in Google Scholar

33. Feng S, Hong Y, Zhou Z, Jinsong Z, Xiaofeng D, Zaizhong W, et al. Monitoring of acute axonal injury in the swine spinal cord with EAE by diffusion tensor imaging. J Magn Reson Imaging 200 9; 30: 277-85.10.1002/jmri.21825 Search in Google Scholar

34. Schmierer K, Wheeler-Kingshott CA, Boulby PA, Scaravilli F, Altmann DR, Barker GJ, et al. Diffusion tensor imaging of post mortem multiple sclerosis brain. Neuroimage 200 7; 35: 467-77.10.1016/j.neuroimage.2006.12.010 Search in Google Scholar

35. Song SK, Yoshino J, Le TQ, Lin SJ, Sun SW, Cross AH, et al. Demyelination increases radial diffusivity in corpus callosum of mouse brain. Neuroimage 2005; 26: 132-40.10.1016/j.neuroimage.2005.01.028 Search in Google Scholar

36. Westin CF, Maier SE, Mamata H, Nabavi A, Jolesz FA, Kikinis R. Processing and visualization for diffusion tensor MRI. Med Image Anal 20 02; 6: 93-108.10.1016/S1361-8415(02)00053-1 Search in Google Scholar

37. Woodworth DC, Pope WB, Liau LM, Kim HJ, Lai A, Nghiemphu PL, et al. Nonlinear distortion correction of diffusion MR images improves quantitative DTI measurements in glioblastoma. J Neurooncol 2013. 2014; 116: 551-8.10.1007/s11060-013-1320-2391890724318915 Search in Google Scholar

38. Saksena S, Jain R, Schultz L, Jiang Q, Soltanian-Zadeh H, Scarpace L, et al. The corpus callosum Wallerian degeneration in the unilateral brain tumors: evaluation with diffusion tensor imaging (DTI). J Clin Diagn Res 2 013; 7: 320-5. Search in Google Scholar

39. Saksena S, Jain R, Narang J, Scarpace L, Schultz LR, Lehman NL, et al. Predicting survival in glioblastomas using diffusion tensor imaging metrics. J Magn Reson Imaging 2010; 32: 788-95. 10.1002/jmri.2230420882608 Search in Google Scholar

eISSN:
1581-3207
ISSN:
1318-2099
Language:
English
Publication timeframe:
4 times per year
Journal Subjects:
Medicine, Clinical Medicine, Internal Medicine, Haematology, Oncology, Radiology