Identification and characterisation of childhood cerebellar tumours by in vivo proton MRS

NMR in Biomedicine

Volumn 21, Issue 8, 2008, Pages 908-918

  Davies, Nigel P ^a,b,c   Wilson, M ^a,c   Harris, L M ^a,c   Natarajan, K ^a,b   Lateef, S ^c   MacPherson, L ^c   Sgouros, S ^c   Grundy, R G ^d   Arvanitiss, T N ^a,c   Peet, A C ^a,c  

^a UNIVERSITY OF BIRMINGHAM   (United Kingdom)

^b UNIVERSITY HOSPITALS BIRMINGHAM NHS FOUNDATION TRUST   (United Kingdom)

^c BIRMINGHAM CHILDREN S HOSPITAL NHS FOUNDATION TRUST   (United Kingdom)

^d UNIVERSITY OF NOTTINGHAM   (United Kingdom)

Author keywords

1H MRS; Bootstrapping; Classification; Cross validation; Magic angle spinning NMR; Metabolite profiles; Paediatric brain tumours

Indexed keywords

RECONNAISSANCE AIRCRAFT;

1H MRS; BOOTSTRAPPING; CLASSIFICATION; CROSS-VALIDATION; MAGIC-ANGLE-SPINNING NMR; METABOLITE PROFILES; PAEDIATRIC BRAIN TUMOURS;

TUMORS;

CREATINE; GLUTAMIC ACID; GLUTAMINE; GLYCEROPHOSPHORYLCHOLINE; INOSITOL; N ACETYLASPARTIC ACID; PHOSPHORYLCHOLINE; TAURINE;

ARTICLE; ASTROCYTOMA; CANCER CLASSIFICATION; CEREBELLUM TUMOR; CHILD; CHILDHOOD CANCER; CLINICAL ARTICLE; CONTROLLED STUDY; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; EPENDYMOMA; EX VIVO STUDY; FEMALE; HUMAN; HUMAN TISSUE; IN VIVO STUDY; INTERMETHOD COMPARISON; MALE; MEDULLOBLASTOMA; METABOLITE; NUCLEAR MAGNETIC RESONANCE; PRIORITY JOURNAL; PROTON NUCLEAR MAGNETIC RESONANCE; TUMOR BIOPSY;

CEREBELLAR NEOPLASMS; CHILD; FEMALE; HUMANS; MAGNETIC RESONANCE SPECTROSCOPY; MALE; PROTONS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; TUMOR MARKERS, BIOLOGICAL;

EID: 53849134180     PISSN: 09523480     EISSN: 10991492     Source Type: Journal    
DOI: 10.1002/nbm.1283     Document Type: Article

References (36)

1. Preul MC, Caramanos Z, Collins DL, Villemure JG, Leblanc R, Olivier A, Pokprupa R, Arnold DL. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy. Nat Med 1996; 2: 323-325.
2. Burtscher IM, Holtas S. Proton magnetic resonance spectroscopy in brain tumours: clinical applications. Neuroradiology 2001; 43: 345-352.
3. 1H MR spectroscopy of brain tumours and masses. NMR Biomed 2003; 16: 123-131.
4. 1H magnetic resonance imaging. Magn. Reson Med. 2003; 49: 223-232.
5. Hagberg G, Burlina AP, Mader I, Roser W, Radue EW, Seelig J. In vivo proton MR spectroscopy of human gliomas: definition of metabolic coordinates for multi-dimensional classification. Magn Reson Med. 1995; 34: 242-52.
6. Poptani H, Kaartinen J, Gupta RK, Niemitz M, Hiltunen Y, Kauppinen RA. Diagnostic assessment of brain tumours and non-neoplastic brain disorders in vivo using proton nuclear magnetic resonance spectroscopy and artificial neural networks. J. Cancer Reson Clin Oncol. 1999; 125: 343-9.
7. Gajewicz W, Papierz W, Szymczak W, Goraj B. The use of proton MRS in the differential diagnosis of brain tumors and tumor-like processes. Med. Sci. Monit. 2003; 9: MT97-T105.
8. 1H brain tumor spectra: a multicenter study. Magn. Reson Med. 2003; 49: 29-36.
9. Lukas L, Devos A, Suykens JA, Vanhamme L, Howe FA, Majós C, Moreno-Torres A, Van der Graaf M, Tate AR, Arús C, Van Huffel S. Brain tumor classification based on long echo proton MRS signals. Artif Intell Med. 2004; 31: 73-89.
10. 1H MR spectra. J. Magn Reson 2004; 164-175.
11. Tate AR, Underwood J, Acosta DM, Julia-Sape M, Majos C, Moreno-Torres A, Howe FA, van der Graaf M, Lefournier V, Murphy MM, Loosemore A, Ladroue C, Wesseling P, Luc Bosson J, Cabanas ME, Simonetti AW, Gajewicz W, Calvar J, Capdevila A, Wilkins PR, Bell BA, Remy C, Heerschap A, Watson D, Griffiths JR, Arus C. Development of a decision support system for diagnosis and grading of brain tumours using in vivo magnetic resonance single voxel spectra. NMR Biomed. 2006; 19: 411-434.
12. Galanaud D, Nicoli F, Chinot O, Confort-Gouny S, Figarella-Branger D, Roche P, Fuentes S, Le Fur Y, Ranjeva JP, Cozzone PJ. Noninvasive diagnostic assessment of brain tumors using combined in vivo MR imaging and spectroscopy. Magn Reson Med. 2006; 55: 1236-45.
13. Opstad KS, Ladroue C, Bell BA, Griffiths JR, Howe FA. Linear discriminant analysis of brain tumour (1)H MR spectra: a comparison of classification using whole spectra versus metabolite quantification. NMR Biomed. 2007; 20: 763-770.
14. Huang Y, Lisboa PJ, El-Deredy W. Tumour grading from magnetic resonance spectroscopy: a comparison of feature extraction with variable selection. Stat Med. 2003; 22: 147-64.
15. Wang Z, Sutton LN, Cnaan A, Haselgrove JC, Rorke LB, Zhao H, Bilaniuk LT, Zimmerman RA. Proton MR spectroscopy of pediatric cerebellar tumors. AJNR Am J Neuroradiol 1995; 16: 1821-1833.
16. Arle JE, Morriss C, Wang ZJ, Zimmerman RA, Phillips PG, Sutton LN. Prediction of posterior fossa tumor type in children by means of magnetic resonance image properties, spectroscopy, and neural networks. J. Neurosurg. 1997; 86: 755-61.
17. 1H-MR spectroscopy. J. Magn Reson Imaging. 2007; 26: 1390-1398.
18. Byrd SE, Tomita T, Palka PS, Darling CF, Norfray JP, Fan J. Magnetic resonance spectroscopy (MRS) in the evaluation of pediatric brain tumors. Part II: clinical analysis. J. Natl Med Assoc. 1996; 88: 717-23.
19. 1H-MR spectroscopy of untreated pediatric brain tumors: preoperative diagnosis and characterization. AJNR Am J Neuroradiol 2006; 27: 560-572.
20. Kauppinen RA. Monitoring cytotoxic tumour treatment response by diffusion magnetic resonance imaging and proton spectroscopy. NMR Biomed. 2002; 15: 6-17.
21. Weybright P, Maly P, Gomez-Hassan D, Blaesing C, Sundgren PC. MR spectroscopy in the evaluation of recurrent contrast-enhancing lesions in the posterior fossa after tumor treatment. Neuroradiology. 2004; 46: 541-9.
22. Pollack IF. Pediatric brain tumors. Semin Surg Oncol. 1999; 16: 73-90.
23. Tzika AA, Cheng LL, Goumnerova L, Madsen JR, Zurakowski D, Astrakas LG, Zarifi MK, Scott RM, Anthony DC, Gonzalez RG, Black PM. Biochemical characterization of pediatric brain tumors by using in vivo and ex vivo magnetic resonance spectroscopy. J. Neurosurg. 2002; 96: 1023-31.
24. Geisser S. The predictive sample reuse method with applications. J. Am. Stat. Assoc. 1975; 70(350): 320-328.
25. Efron B, Tibshirani R. An Introduction to the Bootstrap. Chapman and Hall: London, 1993.
26. Provencher SW. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn Reson Med. 1993; 30: 672-9.
27. LCModel manual http://s-provencher.com/pub/LCModel/manual/manual.pdf.
28. Efron B. Estimating the error rate of a prediction rule: improvement on crossvalidation. J. Am. Stat. Assoc. 1983; 78: 316-331.
29. Efron B, Tibshirani R. Improvements on cross-validation: the .632+ bootstrap method. J. Am. Stat. Assoc., 1997; 92: 548-560.
30. Fu WJ, Carroll RJ, Wang S. Estimating misclassification error with small samples via bootstrap cross-validation. Bioinformatics. 2005; 21: 1979-86.
31. Tong Z, Yamaki T, Harada K, Houkin K. In vivo quantification of the metabolites in normal brain and brain tumors by proton MR spectroscopy using water as an internal standard. Magn. Reson. Imaging 2004; 22: 1017-1024.
32. 1H MR spectra of a pediatric posterior fossa lesion. Int J Mol Med. 2005; 16: 301-7.
33. 1H NMR spectroscopy. NMR Biomed. 2005; 18: 413-20.
34. 31P MRS in untreated pediatric brain tumors. Magn Reson Med. 2005; 53: 22-9.
35. Florian CL, Pietsch T, Noble M, Williams SR. Metabolic studies of human primitive neuroectodermal tumour cells by proton nuclear magnetic resonance spectroscopy. Br J Cancer. 1997; 75: 1007-13.
36. Nikulin AE, Dolenko B, Bezabeh T, Somorjai RL. Near-optimal region selection for feature space reduction: novel preprocessing methods for classifying MR spectra. NMR Biomed. 1998; 11: 209-16.