title: Multiparametric 3T MR approach to the assessment of cerebral gliomas: tumor extent and malignancy.
abstract: BACKGROUND
  Contrast-enhanced MR imaging is the method of choice for routine assessment of brain tumors, but it has limited sensitivity and specificity. We verified if the addition of metabolic, diffusion and hemodynamic information improved the definition of glioma extent and grade.
  
  
  METHODS
  Thirty-one patients with cerebral gliomas (21 high- and 10 low-grade) underwent conventional MR imaging, proton MR spectroscopic imaging ((1)H-MRSI), diffusion weighted imaging (DWI) and perfusion weighted imaging (PWI) at 3 Tesla, before undergoing surgery and histological confirmation. Normalized metabolite signals, including choline (Cho), N-acetylaspartate (NAA), creatine and lactate/lipids, were obtained by (1)H-MRSI; apparent diffusion coefficient (ADC) by DWI; and relative cerebral blood volume (rCBV) by PWI.
  
  
  RESULTS
  Perienhancing areas with abnormal MR signal showed 3 multiparametric patterns: "tumor", with abnormal Cho/NAA ratio, lower ADC and higher rCBV; "edema", with normal Cho/NAA ratio, higher ADC and lower rCBV; and "tumor/edema", with abnormal Cho/NAA ratio and intermediate ADC and rCBV. Perienhancing areas with normal MR signal showed 2 multiparametric patterns: "infiltrated", with high Cho and/or abnormal Cho/NAA ratio; and "normal", with normal spectra. Stepwise discriminant analysis showed that the better classification accuracy of perienhancing areas was achieved when regarding all MR variables, while (1)H-MRSI variables and rCBV better differentiated high- from low-grade gliomas.
  
  
  CONCLUSIONS
  Multiparametric MR assessment of gliomas, based on (1)H-MRSI, PWI and DWI, discriminates infiltrating tumor from surrounding vasogenic edema or normal tissues, and high- from low-grade gliomas. This approach may provide useful information for guiding stereotactic biopsies, surgical resection and radiation treatment.
authors.affiliation: Department of Health Sciences, University of Molise, Via de Sanctis 2, 86100, Campobasso, Italy. alfonso.dicostanzo@unimol.it
authors.forename: Alfonso
authors.initials: A
authors.lastname: Di Costanzo
authors.forename: Tommaso
authors.initials: T
authors.lastname: Scarabino
authors.forename: Francesca
authors.initials: F
authors.lastname: Trojsi
authors.forename: Giuseppe M
authors.initials: GM
authors.lastname: Giannatempo
authors.forename: Teresa
authors.initials: T
authors.lastname: Popolizio
authors.forename: Domenico
authors.initials: D
authors.lastname: Catapano
authors.forename: Simona
authors.initials: S
authors.lastname: Bonavita
authors.forename: Nicola
authors.initials: N
authors.lastname: Maggialetti
authors.forename: Michela
authors.initials: M
authors.lastname: Tosetti
authors.forename: Ugo
authors.initials: U
authors.lastname: Salvolini
authors.forename: Vincenzo A
authors.initials: VA
authors.lastname: d'Angelo
authors.forename: Giocchino
authors.initials: G
authors.lastname: Tedeschi
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001224:Aspartic Acid / Q000031:analogs & derivatives / Q000032:analysis; D001932:Brain Neoplasms / Q000737:chemistry / Q000175:diagnosis*; D002794:Choline / Q000032:analysis; D003287:Contrast Media; D003401:Creatine / Q000032:analysis; D038524:Diffusion Magnetic Resonance Imaging; D005260:Female; D005910:Glioma / Q000737:chemistry / Q000175:diagnosis*; D006801:Humans; D019344:Lactic Acid / Q000032:analysis; D008055:Lipids / Q000032:analysis; D018810:Magnetic Resonance Angiography; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy; D008297:Male; D008875:Middle Aged
chemical_list: D003287:Contrast Media; D008055:Lipids; D001224:Aspartic Acid; D019344:Lactic Acid; C000179:N-acetylaspartate; D003401:Creatine; D002794:Choline