title: High-resolution diffusion tensor imaging of prostate cancer using a reduced FOV technique.
abstract: OBJECTIVE
  Diffusion tensor imaging (DTI) offers the promise of improved tumor localization in prostate cancer but the technique suffers from susceptibility-induced artifacts that limit the achievable resolution. The present work employs a reduced field-of-view technique that enables high-resolution DTI of the prostate at 3T. Feasibility of the approach is demonstrated in a clinical study including 26 patients and 14 controls.
  
  
  METHODS
  Reduced field-of-view acquisition was established by non-coplanar application of the excitation and the refocusing pulse in conjunction with outer volume suppression. Accuracy for cancer detection of apparent diffusion coefficient (ADC) mapping and T2-weighted imaging was calculated and compared with reference to the findings of trans-rectal ultrasound-guided octant biopsy. Mean ADCs and fractional anisotropy (FA) values in the patients with positive and negative biopsies were compared to each other and to the controls.
  
  
  RESULTS
  Fine anatomical details were successfully depicted on the ADC maps with sub-millimeter resolution. Accuracy for prostate cancer detection was 73.5% for ADC maps and 71% for T2-weighted images, respectively. Cohen's kappa (κ=0.48) indicated moderate agreement of the two methods. The mean ADCs were significantly lower, the FA values higher, in the patients with positive biopsy than in the patients with negative biopsy and the controls. Monte Carlo simulations showed that the FA values, but not the ADCs, were slightly overestimated. Bootstrap analysis revealed that the ADC, but not the FA value, is a highly repeatable marker.
  
  
  CONCLUSIONS
  In conclusion, the present work introduces a new approach for high-resolution DTI of the prostate enabling a more accurate detection of focal tumors especially useful in screening populations or as a potential navigator for image-guided biopsy.
authors.affiliation: Institute for Biomedical Engineering, ETH and University of Zurich, Gloriastrasse 35, CH-8092 Zurich, Switzerland. reischauer@biomed.ee.ethz.ch
authors.forename: Carolin
authors.initials: C
authors.lastname: Reischauer
authors.forename: Bertram J
authors.initials: BJ
authors.lastname: Wilm
authors.forename: Johannes M
authors.initials: JM
authors.lastname: Froehlich
authors.forename: Andreas
authors.initials: A
authors.lastname: Gutzeit
authors.forename: Ladislav
authors.initials: L
authors.lastname: Prikler
authors.forename: Roger
authors.initials: R
authors.lastname: Gablinger
authors.forename: Peter
authors.initials: P
authors.lastname: Boesiger
authors.forename: Klaus-Ulrich
authors.initials: KU
authors.lastname: Wentz
mesh_terms: D000328:Adult; D000368:Aged; D016880:Anisotropy; D016477:Artifacts; D001706:Biopsy; D016022:Case-Control Studies; D056324:Diffusion Tensor Imaging / Q000379:methods*; D005240:Feasibility Studies; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D011471:Prostatic Neoplasms / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000473:pathology; D018709:Statistics, Nonparametric; D014463:Ultrasonography