Identification of pediatric brain neoplasms using raman spectroscopy

Pediatric Neurosurgery

Volumn 48, Issue 2, 2012, Pages 109-117

  Leslie, David G ^a   Kast, Rachel E ^b   Poulik, Janet M ^a   Rabah, Raja ^c   Sood, Sandeep ^a   Auner, Gregory W ^b   Klein, Michael D ^a  

^a CHILDREN'S HOSPITAL OF MICHIGAN   (United States)

^b Wayne State University   (United States)

^c UNIVERSITY OF MICHIGAN HEALTH SYSTEM   (United States)

Author keywords

Brain neoplasm; Diagnostics; Raman spectroscopy

Indexed keywords

ARTICLE; ASTROCYTOMA; BRAIN TUMOR; CANCER TISSUE; CHILD; CHILDHOOD CANCER; CONTROLLED STUDY; DIAGNOSTIC TEST ACCURACY STUDY; DIFFERENTIAL DIAGNOSIS; EPENDYMOMA; GLIOMA; HISTOPATHOLOGY; HUMAN; HUMAN TISSUE; MAJOR CLINICAL STUDY; MEDULLOBLASTOMA; OLIGODENDROGLIOMA; PRIORITY JOURNAL; RAMAN SPECTROMETRY; SENSITIVITY AND SPECIFICITY; TUMOR DIAGNOSIS;

ASTROCYTOMA; BRAIN; BRAIN NEOPLASMS; CEREBELLAR NEOPLASMS; CHILD; DIAGNOSIS, DIFFERENTIAL; EPENDYMOMA; GANGLIOGLIOMA; GLIOMA; HUMANS; MEDULLOBLASTOMA; NEOPLASM GRADING; OLIGODENDROGLIOMA; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPECTRUM ANALYSIS, RAMAN; TISSUE BANKS;

EID: 84868686064     PISSN: 10162291     EISSN: 14230305     Source Type: Journal    
DOI: 10.1159/000343285     Document Type: Article

References (37)

1. Krafft C, Sergo V: Biomedical applications of Raman and infrared spectroscopy to diagnose tissues. Spectroscopy 2006; 20: 195-218. (Pubitemid 46129068)
2. Haka AS, et al: Diagnosing breast cancer by using Raman spectroscopy. Proc Natl Acad Sci USA 2005; 102: 12371-12376. (Pubitemid 41266366)
3. Kast RE, et al: Raman spectroscopy can differentiate malignant tumors from normal breast tissue and detect early neoplastic changes in a mouse model. Biopolymers 2008; 89: 235-241. (Pubitemid 351220116)
4. Wills H, et al: Raman spectroscopy detects and distinguishes neuroblastoma and related tissues in fresh and (banked) frozen specimens. J Pediatr Surg 2009; 44: 386-391.
5. Wills H, et al: Diagnosis of Wilms' tumor using near-infrared Raman spectroscopy. J Pediatr Surg 2009; 44: 1152-1158.
6. Krafft C, et al: Disease recognition by infrared and Raman spectroscopy. J Biophotonics 2009; 2: 13-28.
7. Kanter E, et al: Application of Raman spectroscopy for cervical dysplasia diagnosis. J Biophotonics 2009; 2: 81-90.
8. Nijssen A, et al: Discriminating basal cell carcinoma from perilesional skin using high wave-number Raman spectroscopy. J Biomed Optics 2007; 12: 034004.
9. Shetty G, et al: Raman spectroscopy: elucidation of biochemical changes in carcinogenesis of oesophagus. Br J Cancer 2006; 94: 1460-1464. (Pubitemid 43772281)
10. Lakshmi RJ, et al: Tissue Raman spectroscopy for the study of radiation damage: brain irradiation of mice. Radiat Res 2002; 157: 175-182. (Pubitemid 34101369)
11. Krafft C, et al: Near infrared Raman spectra of human brain lipids. Spectrochim Acta A Mol Biomol Spectrosc 2005; 61: 1529-1535. (Pubitemid 40455305)
12. Wolthuis R, et al: Determination of water concentration in brain tissue by Raman spectroscopy. Anal Chem 2001; 73: 3915-3920. (Pubitemid 32896165)
13. Koljenovic S, et al: Discriminating vital tumor from necrotic tissue in human glioblastoma tissue samples by Raman spectroscopy. Lab Invest 2002; 82: 1265-1277. (Pubitemid 35191530)
14. Krafft C, et al: Methodology for fiber-optic Raman mapping and FTIR imaging of metastases in mouse brains. Anal Bioanal Chem 2007; 389: 1122-1142.
15. Krafft C, et al: Near-infrared Raman spectroscopy to study the composition of human brain tissue and tumors. Proceedings of SPIE/The International Society for Optical Engineering. Diagn Opt Spectroscopy Biomed 2003; 5141: 230-236.
16. Krafft C, et al: Near infrared Raman spectroscopic mapping of native brain tissue and intracranial tumors. Analyst 2005; 130: 1070-1077. (Pubitemid 40980120)
17. Aydin O, et al: Differentiation of healthy brain tissue and tumors using surface-enhanced Raman scattering. Appl Spectroscopy 2009; 63: 1095-1100.
18. Kirsch M, et al: Raman spectroscopic imaging for in vivo detection of cerebral brain metastases. Anal Bioanal Chem 2010; 398: 1707-1713.
19. Koljenovic S, et al: Detection of meningioma in dura mater by Raman spectroscopy. Anal Chem 2005; 77: 7958-7965. (Pubitemid 41831981)
20. Beljebbar A, et al: Ex vivo and in vivo diagnosis of C6 glioblastoma development by Raman spectroscopy coupled to a microprobe. Anal Bioanal Chem 2010; 398: 477-487.
21. Koehler M, et al: Characterization of lipid extracts from brain tissue and tumors using Raman spectroscopy and mass spectrometry. Anal Bioanal Chem 2009; 393: 1513-1520.
22. Reisner LA, Cao A, Pandya AK: An integrated software system for processing, analyzing, and classifying Raman spectra. Chemometr Intell Lab Syst 2011; 105: 83-90.
23. Cortes C, Vapnik V: Support-vector networks. Mach Learn 1995; 20: 273-297.
24. Zomer S, et al: Support vector machines for the discrimination of analytical chemical data: application to the determination of tablet production by pyrolysis-gas chromatography- mass spectrometry. Analyst 2004; 129: 175-181. (Pubitemid 38250698)
25. Majumder SK, Ghosh N, Gupta PK: Support vector machine for optical diagnosis of cancer. J Biomed Opt 2005; 10: 024034.
26. Widjaja E, Zheng W, Huang Z: Classification of colonic tissues using near-infrared Raman spectroscopy and support vector machines. Int J Oncol 2008; 32: 653-662. (Pubitemid 351330472)
27. Sattlecker M, et al: Investigation of support vector machines and Raman spectroscopy for lymph node diagnostics. Analyst 2010; 135: 895-901.
28. Lin W-C, et al: Brain tumor demarcation using in vitro spectroscopy; an in vitro study. J Biomed Opt 2000; 5: 214-220.
29. Cao A, et al: A robust method for automated background subtraction of tissue fluorescence. J Raman Spectroscopy 2007; 38: 1199-1205.
30. Chih-Wei H, Chih-Jen L: A comparison of methods for multiclass support vector machines. IEEE Trans Neur Netw 2002; 13: 415-425.
31. Haka AS, et al: In vivo margin assessment during partial mastectomy breast surgery using raman spectroscopy. Cancer Res 2006; 66: 3317-3322.
32. Hales R, et al: Prognostic factors in pediatric high-grade astrocytoma: the importance of accurate pathologic diagnosis. J Neuro-Oncol 2010; 99: 65-71.
33. Kan P, et al: Oligodendroglioma and juvenile pilocytic astrocytoma presenting as synchronous primary brain tumors. J Neurosurg 2004; 100: 700-705.
34. Merchant TE, Pollack IF, Loeffler JS: Brain tumors across the age spectrum: biology, therapy, and late effects. Semin Radiat Oncol 2010; 20: 58-66.
35. Bristol RE: Low-grade glial tumors: are they all the same? Semin Pediatr Neurol 2009; 16: 23-26.
36. Hyder D, et al: Anaplastic mixed gliomas and anaplastic oligodendroglioma in children: results from the CCG 945 experience. J Neuro- Oncol 2007; 83: 1-8. (Pubitemid 46647158)
37. Sepulveda Sanchez J, et al: Classification of oligodendroglial tumors based on histopathology criteria is a significant predictor of survival -clinical, radiological and pathologic long-term follow-up analysis. Clin Neuropathol 2009; 28: 11-20.