Accurate classification of childhood brain tumours by in vivo 1H MRS-A multi-centre study

European Journal of Cancer

Volumn 49, Issue 3, 2013, Pages 658-667

  Vicente, Javier ^a   Fuster Garcia, Elies ^a   Tortajada, Salvador ^a   García Gómez, Juan M ^a   Davies, Nigel ^b   Natarajan, Kal ^b   Wilson, Martin ^b   Grundy, Richard G ^c   Wesseling, Pieter ^d,e   Monleón, Daniel ^f   Celda, Bernardo ^g   Robles, Montserrat ^a   Peet, Andrew C ^b  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^c UNIVERSITY OF NOTTINGHAM   (United Kingdom)

^d RADBOUD UNIVERSITY MEDICAL CENTER   (Netherlands)

^e VU UNIVERSITY MEDICAL CENTER   (Netherlands)

^f HOSPITAL CLÍNICO UNIVERSITARIO   (Spain)

^g UNIVERSITY OF VALENCIA   (Spain)

Author keywords

1H MRS; Classification; Clinical assessment; Feature extraction; Multi centre study; Non invasive diagnosis; Paediatric brain tumours; Pattern recognition; Pre surgery diagnosis assessment

Indexed keywords

4 AMINOBUTYRIC ACID; ALANINE; ASPARTIC ACID; CHOLINE; CREATINE; GLUCOSE; GLUTAMIC ACID; GLUTAMINE; GLYCEROPHOSPHORYLCHOLINE; GUANIDINOACETIC ACID; INOSITOL DERIVATIVE; N ACETYLASPARTIC ACID; PHOSPHORYLCHOLINE; TAURINE;

ARTICLE; ATYPICAL TERATOID RHABDOID TUMOUR; BALANCED ACCURACY RATE; BRAIN TUMOR; CHILD; CHILDHOOD CANCER; CLINICAL EVALUATION; CLINICAL PROTOCOL; COMPUTER PROGRAM; CONCENTRATION (PARAMETERS); DIAGNOSTIC ACCURACY; DIFFERENTIAL DIAGNOSIS; DIFFUSE ASTROCYTOMA; ECHO TIME; EPENDYMOMA; HUMAN; MEDULLOBLASTOMA; METABOLITE; MULTICENTER STUDY; NERVOUS SYSTEM TUMOR; NEUROIMAGING; PEAK INTEGRATION; PILOCYTIC ASTROCYTOMA; PINEOBLASTOMA; POINT RESOLVED SPECTROSCOPY; PRIORITY JOURNAL; PROTON BRAIN EXAM; PROTON NUCLEAR MAGNETIC RESONANCE; RADIOLOGICAL PARAMETERS; STIMULATED ECHO ACQUISITION MODE; SUBEPENDYMAL GIANT CELL ASTROCYTOMA; TUMOR CLASSIFICATION;

ADOLESCENT; BRAIN NEOPLASMS; CHILD; CHILD, PRESCHOOL; HUMANS; INFANT; INFANT, NEWBORN; MAGNETIC RESONANCE SPECTROSCOPY;

EID: 84872686738     PISSN: 09598049     EISSN: 18790852     Source Type: Journal    
DOI: 10.1016/j.ejca.2012.09.003     Document Type: Article

References (38)

1. R. Venkatramani, G. Dhall, and M. Patel Supratentorial ependymoma in children: to observe or to treat following gross total resection? Pediatr Blood Cancer 58 3 2011 380 383
2. B. Horn, R. Heideman, and R. Geyer A multi-institutional retrospective study of intracranial ependymoma in children: identification of risk factors J Pediatr Hematol Oncol 21 3 1999 203 211
3. A.L. Albright, J.H. Wisoff, and P.M. Zeltzer Effects of medulloblastoma resections on outcome in children: a report from the children's cancer group Neurosurgery 38 1996 265 271
4. H. Ogiwara, R.M. Bowman, and T. Tomita Long-term follow-up of pediatric benign cerebellar astrocytomas Neurosurgery 70 1 2012 40 48
5. P.L. Kubben, K.J. ter Meulen, and O.E. Schijns Intraoperative MRI-guided resection of glioblastoma multiforme: a systematic review Lancet Oncol 12 11 2011 1062 1070
6. D. Ellison, M. Kocak, and J. Dalton Definition of disease-risk stratification groups in childhood medulloblastoma using combined clinical, pathologic, and molecular variables J Clin Oncol 29 11 2010 1400 1407
7. A. Peet, N. Davies, and L. Ridley Magnetic resonance spectroscopy suggests key differences in the metastatic behaviour of medulloblastoma Eur J Cancer 6 43 2007 1037 1044
8. A.R. Tate, J. Underwood, and D.M. Acosta Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra NMR Biomed 19 4 2006 411 434
9. G. Hagberg From magnetic resonance spectroscopy to classification of tumors. A review of pattern recognition methods NMR Biomed 11 4-5 1998 148 156
10. B.H. Menze, M.P. Lichy, and P. Bachert Optimal classification of long echo time in vivo magnetic resonance spectra in the detection of recurrent brain tumors NMR Biomed 19 2006 599 609
11. L. Lukas, A. Devos, and J.A.K. Suykens Brain tumor classification based on long echo proton MRS signals Artif Intell Med 31 2004 73 89
12. A.W. Simonetti, W.J. Melssen, and F. Szabo de Edelenyi Combination of feature-reduced MR spectroscopic and MR imaging data for improved brain tumor classification NMR Biomed 18 2005 34 43
13. 1H MR spectra J Magn Reson 170 2004 164 175
14. Y. Huang, P.J.G. Lisboa, and W. El-Deredy Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection Stat Med 22 2003 147 164
15. J.M. García-Gómez, J. Luts, and M. Julià-Sapé Multiproject-multicenter evaluation of automatic brain tumor classification by magnetic resonance spectroscopy Magn Reson Mater Phys Biol Med 22 1 2009 5 18
16. I.F. Pollack Brain tumors in children [review] N Engl J Med 331 1994 1501 1507
17. I.F. Pollack Pediatric brain tumors Semin Surg Oncol 16 1999 73 90
18. K. Imamura Proton MR spectroscopy of the brain with a focus in chemical issues Mag Reson Med Sci 2 3 2003 117 132
19. A. Rossi, C. Gandolfo, and G. Morana New MR sequences (diffusion, perfusion, spectroscopy) in brain tumours Pediatr Radiol 40 2010 999 1009
20. J.M. García-Gómez, S. Tortajada, and C. Vidal The effect of combining two echo times in automatic brain tumor classification by MRS NMR Biomed 21 10 2008 1112 1125
21. eTUMOUR Consortium. eTumour: web accessible MR decision support system for brain tumour diagnosis and prognosis, incorporating in vivo and ex vivo genomic and metabolomic data. Available from: FP6-2002-LIFESCIHEALTH 503094, VI framework programme, EC, http://www.etumour.net [accessed 20.02.12].
22. M. van der Graaf, M. Julià-Sapé, and F.A. Howe MRS quality assessment in a multicentre study on MRS-based classification of brain tumours NMR Biomed 21 2 2008 148 158
23. D.N. Louis, H. Ohgaki, and O.D. Wiestler WHO classification of tumours of the central nervous system 2007 IARC Press Lyon, France
24. M. Julià-Sapé, D. Acosta, and M. Mier A multi-centre, web-accessible and quality control-checked database of in vivo MR spectra of brain tumour patients Magn Reson Mater Phys 19 2006 22 33
25. 1H magnetic resonance spectroscopy data Magn Reson Med 65 2011 1 12
26. 1H MR spectra Magn Reson Med 60 2 2008 288 298
27. Z. Wang, L.N. Sutton, and A. Cnaan Proton MR spectroscopy of pediatric cerebellar tumors Am J Neuroradiol 16 1995 1821 1833
28. J.E. Arle, C. Morriss, and Z.J. Wang Prediction of posterior fossa tumor type in children by means of magnetic resonance image properties, spectroscopy, and neural networks J Neurosurg 86 1997 755 761
29. 1H-MR spectroscopy J Magn Reson Imaging 26 1 2007 1390 1398
30. N.P. Davies, M. Wilson, and L.M. Harris Identification and characterisation of childhood cerebellar tumours by in vivo proton MRS NMR Biomed 21 8 2008 908 918
31. Guyon I, Alamdari ARSA, Dror G, et al. Performance prediction challenge. In: IJCNN '06. International joint conference on neural networks; 2006. p. 1649-56.
32. 1H nuclear magnetic resonance correspond to lipid droplets Cancer Res 57 1997 407 414
33. 1H MRS in vivo pattern. In: Abstracts of Soc Magn Reson Med, New York; 1996. p. 976.
34. 1H-MR spectroscopy of untreated pediatric brain tumors: preoperative diagnosis and characterization Am J Neuroradiol 27 2006 560 572
35. 1H magnetic resonance spectroscopy of childhood brain tumours Childs Nerv Syst 23 2 2007 163 169
36. A. Moreno-Torres, I. Martínez-Pérez, and M. Baquero Taurine detection by proton magnetic resonance spectroscopy in medulloblastoma: contribution to noninvasive differential diagnosis with cerebellar astrocytoma Neurosurgery 4 55 2004 824 8295
37. Sáez C, García-Gómez J, Vicente J, et al. Curiam BT 1.0, decision support system for brain tumour diagnosis. In: ESMRMB 2009 congress: EPOS posters, paper posters, Info-RESO, vol. 22 (Antalya, Turkey). Berlin, Heidelberg: Springer; May 2009. p. 538.
38. C. Sáez, J.M. García-Gómez, and J. Vicente A generic and extensible automatic classification framework applied to brain tumour diagnosis in HealthAgents Knowl Eng Rev 26 Special issue 03 2011 283 301