title: Identification of pediatric brain neoplasms using Raman spectroscopy.
abstract: OBJECTIVE
  Raman spectroscopy can quickly and accurately diagnose tissue in near real-time. This study evaluated the capacity of Raman spectroscopy to diagnose pediatric brain tumors.
  
  
  METHODS
  Samples of untreated pediatric medulloblastoma (4 samples and 4 patients), glioma (i.e. astrocytoma, oligodendroglioma, ependymoma, ganglioglioma and other gliomas; 27 samples and 19 patients), and normal brain samples (33 samples and 5 patients) were collected fresh from the operating room or from our frozen tumor bank. Samples were divided and tested using routine pathology and Raman spectroscopy. Twelve Raman spectra were collected per sample. Support vector machine analysis was used to classify spectra using the pathology diagnosis as the gold standard.
  
  
  RESULTS
  Normal brain (321 spectra), glioma (246 spectra) and medulloblastoma (82 spectra) were identified with 96.9, 96.7 and 93.9% accuracy, respectively, when compared with each other. High-grade ependymomas (41 spectra) were differentiated from low-grade ependymomas (25 spectra) with 100% sensitivity and 96.0% specificity. Normal brain tissue was distinguished from low-grade glioma (118 spectra) with 91.5% sensitivity and 97.8% specificity. For these analyses, the tissue-level classification was determined to be 100% accurate.
  
  
  CONCLUSIONS
  These results suggest Raman spectroscopy can accurately distinguish pediatric brain neoplasms from normal brain tissue, similar tumor types from each other and high-grade from low-grade tumors.
authors.affiliation: Department of Surgery, Wayne State University and Children's Hospital of Michigan, Detroit Medical Center, Wayne State University, Detroit, Mich., USA.
authors.forename: David G
authors.initials: DG
authors.lastname: Leslie
authors.forename: Rachel E
authors.initials: RE
authors.lastname: Kast
authors.forename: Janet M
authors.initials: JM
authors.lastname: Poulik
authors.forename: Raja
authors.initials: R
authors.lastname: Rabah
authors.forename: Sandeep
authors.initials: S
authors.lastname: Sood
authors.forename: Gregory W
authors.initials: GW
authors.lastname: Auner
authors.forename: Michael D
authors.initials: MD
authors.lastname: Klein
mesh_terms: D001254:Astrocytoma / Q000175:diagnosis / Q000473:pathology; D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000473:pathology; D002528:Cerebellar Neoplasms / Q000175:diagnosis* / Q000473:pathology; D002648:Child; D003937:Diagnosis, Differential; D004806:Ependymoma / Q000175:diagnosis / Q000473:pathology; D018303:Ganglioglioma / Q000175:diagnosis / Q000473:pathology; D005910:Glioma / Q000175:diagnosis* / Q000473:pathology; D006801:Humans; D008527:Medulloblastoma / Q000175:diagnosis* / Q000473:pathology; D060787:Neoplasm Grading; D009837:Oligodendroglioma / Q000175:diagnosis / Q000473:pathology; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013059:Spectrum Analysis, Raman / Q000379:methods* / Q000592:standards; D014015:Tissue Banks