title: Diagnosis and prognosis of breast cancer by magnetic resonance spectroscopy of fine-needle aspirates analysed using a statistical classification strategy.
abstract: BACKGROUND
  The aim was to develop robust classifiers to analyse magnetic resonance spectroscopy (MRS) data of fine-needle aspirates taken from breast tumours. The resulting data could provide computerized, classification-based diagnosis and prognostic indicators.
  
  
  METHODS
  Fine-needle aspirate biopsies obtained at the time of surgery for both benign and malignant breast diseases were analysed by one-dimensional proton MRS at 8.5 Tesla. Diagnostic correlation was performed between the spectra and standard pathology reports, including the presence of vascular invasion by the primary cancer and involvement of the excised axillary lymph nodes.
  
  
  RESULTS
  Malignant tissue was distinguished from benign lesions with an overall accuracy of 93 per cent. From the same spectra, lymph node involvement was predicted with an overall accuracy of 95 per cent, and tumour vascular invasion with an overall accuracy of 94 per cent.
  
  
  CONCLUSIONS
  The pathology, nodal involvement and tumour vascular invasion were predicted by computerized statistical classification of the proton MRS spectrum from a fine-needle aspirate biopsy taken from the primary breast lesion.
authors.affiliation: Department of Magnetic Resonance in Medicine, Institute for Magnetic Resonance Research, University of Sydney, Sydney, New South Wales, Australia. caro@imrr.usyd.edu.au
authors.forename: C E
authors.initials: CE
authors.lastname: Mountford
authors.forename: R L
authors.initials: RL
authors.lastname: Somorjai
authors.forename: P
authors.initials: P
authors.lastname: Malycha
authors.forename: L
authors.initials: L
authors.lastname: Gluch
authors.forename: C
authors.initials: C
authors.lastname: Lean
authors.forename: P
authors.initials: P
authors.lastname: Russell
authors.forename: B
authors.initials: B
authors.lastname: Barraclough
authors.forename: D
authors.initials: D
authors.lastname: Gillett
authors.forename: U
authors.initials: U
authors.lastname: Himmelreich
authors.forename: B
authors.initials: B
authors.lastname: Dolenko
authors.forename: A E
authors.initials: AE
authors.lastname: Nikulin
authors.forename: I C
authors.initials: IC
authors.lastname: Smith
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D001707:Biopsy, Needle / Q000379:methods* / Q000592:standards; D001943:Breast Neoplasms / Q000145:classification / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008207:Lymphatic Metastasis; D009682:Magnetic Resonance Spectroscopy; D008875:Middle Aged; D009361:Neoplasm Invasiveness / Q000473:pathology; D011379:Prognosis