Fast nosologic imaging of the brain

Journal of Magnetic Resonance

Volumn 184, Issue 2, 2007, Pages 292-301

  De Vos, M ^a   Laudadio, T ^a   Simonetti, A W ^a   Heerschap, A ^b   Van Huffel, S ^a  

^a UNIVERSITY OF LEUVEN   (Belgium)

^b RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

Author keywords

Brain tumors; Canonical correlation analysis; Classification; Magnetic resonance imaging; Magnetic resonance spectroscopic imaging; Tissue segmentation

Indexed keywords

BRAIN; CORRELATION METHODS; HISTOLOGY; MAGNETIC RESONANCE IMAGING; METABOLISM; TISSUE; TUMORS;

BRAIN TUMORS; CANONICAL CORRELATION ANALYSIS (CCA); MAGNETIC RESONANCE SPECTROSCOPIC IMAGING; TISSUE SEGMENTATION;

MEDICAL IMAGING;

TUMOR MARKER;

ALGORITHM; ARTICLE; BRAIN; BRAIN TUMOR; COMPUTER ASSISTED DIAGNOSIS; EVALUATION; HUMAN; IMAGE ENHANCEMENT; METABOLISM; METHODOLOGY; NUCLEAR MAGNETIC RESONANCE IMAGING; NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY; PATHOLOGY; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

ALGORITHMS; BRAIN; BRAIN NEOPLASMS; DIAGNOSIS, COMPUTER-ASSISTED; HUMANS; IMAGE ENHANCEMENT; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MAGNETIC RESONANCE SPECTROSCOPY; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TUMOR MARKERS, BIOLOGICAL;

EID: 33846647841     PISSN: 10907807     EISSN: 10960856     Source Type: Journal    
DOI: 10.1016/j.jmr.2006.10.017     Document Type: Article

References (27)

1. Bernstein M., and Parrent A.G. Complications of CT-guided stereotactic biopsy of intra-axial brain lesions. J. Neurosurg. 81 (1994) 165-168
2. Tate A.R., Majós C., Moreno A., Howe F.A., Griffiths J.R., and Arus C. Automated classification of short echo time spectra in in vivo brain spectra: a multicenter study. Magn. Res. Med 49 (2003) 29-36
3. Preul M.C., Caramanos Z., Leblanc R., Villemure J.G., and Arnold D.L. Using pattern analysis of in vivo proton MRSI data to improve the diagnosis and surgical management of patients with brain tumors. NMR Biomed. 11 (1998) 192-200
4. Lindon J., Holmes E., and Nicholson J. Pattern recognition methods and applications in biomedical magnetic resonance. Prog. Nucl. Magn. Res. Spectrosc. 39 (2001) 1-40
5. Duda R., Hart P., and Stork D. Pattern Classification. second ed. (2001), John Wiley, New York
6. Devos A., Simonetti A.W., van der Graaf M., Lukas L., Suykens J.A., Vanhamme L., Buydens L.M., Heerschap A., and Van Huffel S. The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification. J. Magn. Res. 173 (2005) 218-282
7. Wilken B., Dechent P., Herms J., Maxton C., Markakis E., Hanefeld F., and Frahm J. Quantitative proton magnetic resonance spectroscopy of focal brain lesions. J. Pediatr. Neurol. 23 (2000) 22-31
8. Nelson S.J. Minireview: multivoxel magnetic resonance spectroscopy of brain tumors. Mol. Cancer Therap. 2 (2003) 497-507
9. Simonetti A., Melsen W., van der Graaf M., Postma G., Heerschap A., and Buydens L. A chemometric approach for brain tumor classification using magnetic resonance imaging and spectroscopy. Anal. Chem. 75 (2003) 5352-5361
10. Szabo De Edelenyi F., Rubin C., Estve F., Sylvie G., Dcorps M., Lefournier V., Le Bas J.-F., and Rmy C. A new approach for analyzing proton magnetic resonance spectroscopic images of brain tumors: nosologic images. Nat. Med. 6 (2000) 1287-1298
11. Castillo M., Smith J.K., and Kwock L. Correlation of myo-inositol levels and grading of cerebral astrocytomas. Am. J. Neuroradiol. 21 (2000) 1645-1649
12. 1H HR-MAS spectroscopy of intact biopsy samples in vitro. Magn. Res. Mater. Phys. Biol. Med. 8 (1999) 121-128
13. Fan G., Sun B., Wu Z., Guo Q., and Guo Y. In vivo single-voxel proton MR spectroscopy in the differentiation of high-grade gliomas and solitary metastases. Clin. Radiol. 59 (2004) 77-85
14. Majos C., Julia-Sape M., Alonso J., Serrallonga M., Aguilera C., Acebes J.J., Arus C., and Gili J. Brain tumor classification by proton MR spectroscopy: comparison of diagnostic accuracy at short and long TE. Am. J. Neuroradiol. 25 (2004) 1696-1704
15. Simonetti A., Melsen W., Szabo de Edelenyi F., van Asten J., Heerschap A., and Buydens L. Combination of feature-reduced MR spectroscopic and MR imaging data for improved brain tumor classification. NMR Biomed. 18 (2005) 34-43
16. Hotelling H. Relations between two sets of variates. Biometrika 28 (1936) 321-371
17. O. Friman, Adaptive analysis of functional MRI Data, PhD thesis, Linköping University, Sweden, 2003.
18. Laudadio T., Pels P., De Lathauwer L., Van Hecke P., and Van Huffel S. Tissue segmentation and classification of MRSI data using Canonical Correlation Analysis. Magn. Res. Med. 54 (2005) 1280-1284
19. Mirkin B. Clustering for data mining (2005), Chapmann & Hall/CRC, Florida, USA
20. J.-B. Poullet, A.W. Simonetti, D.M. Sima, B. De Neuter, L. Vanhamme, Ph. Lemmerling, S. Van Huffel, An open source short echo time MR quantitation software solution: AQSES, NMR Biomed. (2006) submitted.
21. Das S., and Sen P. Restricted canonical correlations. Linear Algebra Appl. 210 (1994) 29-47
22. Omladic M., and Omladic V. More on restricted canonical correlations. Linear Algebra Appl. 321 (2000) 285-293
23. http://azizu.uab.es/INTERPRET/.
24. Klose U. In vivo proton spectroscopy in presence of eddy currents. Magn. Res. Med. 14 (1990) 26-30
25. Laudadio T., Mastronardi N., Vanhamme L., Van Hecke P., and Van Huffel S. Improved Lanczos algorithms for blackbox MRS data quantitation. J. Magn. Res. 157 (2002) 292-297
26. Tong Z., Yamaki T., Harada K., and Houkin K. In vivo quantification of metabolites in normal brain and brain tumors by proton MR spectroscopy using water as an internal standard. Magn. Res. Imag. 22 (2004) 1017-1024
27. http://www.etumour.net/.