title: Automated vs. manual pattern recognition of 3D (1)H MRSI data of patients with prostate cancer.
abstract: OBJECTIVE
  The aim of this study was to assess (1) automated analysis methods versus manual evaluation by human experts of three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) data from patients with prostate cancer and (2) the contribution of spatial information to decision making.
  
  
  METHODS
  Three-dimensional proton MRSI was applied at 1.5 T. MRSI data from 10 patients with histologically proven prostate adenocarcinoma, scheduled either for prostatectomy or intensity-modulated radiation therapy, were evaluated. First, two readers manually labeled spectra using spatial information to identify the localization of spectra and neighborhood information, establishing the reference set of this study. Then, spectra were labeled again manually in a blinded and randomized manner and evaluated automatically using software that applied spectral line fitting as well as pattern recognition routines. Statistical analysis of the results of the different approaches was performed.
  
  
  RESULTS
  Altogether, 1018 spectra were evaluable by all methods. Numbers of evaluable spectra differed significantly depending on patient and evaluation method. Compared to automated analysis, the readers made rather binary decisions, using information from neighboring spectra in ambiguous cases, when evaluating MRSI data as a whole. Differences between anatomically blinded and unblinded evaluation were larger than differences between evaluations using blinded data and automated techniques.
  
  
  CONCLUSIONS
  An automated approach, which evaluates each spectrum individually, can be as good as an anatomy-blinded human reader. Spatial information is routinely used by human experts to support their final decisions. Automated procedures that consider anatomic information for spectral evaluation will enhance the diagnostic impact of MRSI of the human prostate.
authors.affiliation: Department of Radiology, German Cancer Research Center, Heidelberg, Germany. c.zechmann@dkfz.de
authors.forename: Christian M
authors.initials: CM
authors.lastname: Zechmann
authors.forename: Bjoern H
authors.initials: BH
authors.lastname: Menze
authors.forename: B Michael
authors.initials: BM
authors.lastname: Kelm
authors.forename: Patrik
authors.initials: P
authors.lastname: Zamecnik
authors.forename: Uwe
authors.initials: U
authors.lastname: Ikinger
authors.forename: Frederik L
authors.initials: FL
authors.lastname: Giesel
authors.forename: Christian
authors.initials: C
authors.lastname: Thieke
authors.forename: Stefan
authors.initials: S
authors.lastname: Delorme
authors.forename: Fred A
authors.initials: FA
authors.lastname: Hamprecht
authors.forename: Peter
authors.initials: P
authors.lastname: Bachert
mesh_terms: D000368:Aged; D000465:Algorithms; D014408:Biomarkers, Tumor / Q000032:analysis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009682:Magnetic Resonance Spectroscopy / Q000379:methods*; D008297:Male; D008875:Middle Aged; D010363:Pattern Recognition, Automated / Q000379:methods*; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D014408:Biomarkers, Tumor