title: Gradient nonlinearity correction to improve apparent diffusion coefficient accuracy and standardization in the american college of radiology imaging network 6698 breast cancer trial.
abstract: OBJECTIVE
  To evaluate a gradient nonlinearity correction (GNC) program for quantitative apparent diffusion coefficient (ADC) measurements on phantom and human subject diffusion-weighted (DW) magnetic resonance imaging (MRI) scans in a multicenter breast cancer treatment response study
  
  
  METHODS
  A GNC program using fifth-order spherical harmonics for gradient modeling was applied retrospectively to qualification phantom and human subject scans. Ice-water phantoms of known diffusion coefficient were scanned at five different study centers with different scanners and receiver coils. Human in vivo data consisted of baseline and early-treatment exams on 54 patients from four sites. ADC maps were generated with and without GNC. Regions of interest were defined to quantify absolute errors and changes with GNC over breast imaging positions.
  
  
  RESULTS
  Phantom ADC errors varied with region of interest (ROI) position and scanner configuration; the mean error by configuration ranged from 1.4% to 19.9%. GNC significantly reduced the overall mean error for all sites from 9.9% to 0.6% (P = 0.016). Spatial dependence of GNC was highest in the right-left (RL) and anterior-posterior (AP) directions. Human subject mean tumor ADC was reduced 0.2 to 12% by GNC at different sites. By regression, every 1-cm change in tumor ROI position between baseline and follow-up visits resulted in an estimated change of 2.4% in the ADC early-treatment response measurement.
  
  
  CONCLUSIONS
  GNC is effective for removing large, system-dependent errors in quantitative breast DWI. GNC may be important in ensuring reproducibility in multicenter studies and in reducing errors in longitudinal treatment response measures arising from spatial variations in tumor position between visits.
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: David C
authors.initials: DC
authors.lastname: Newitt
authors.affiliation: MRI Lab, GE Global Research, One Research Circle, Niskayuna, New York, USA.
authors.forename: Ek T
authors.initials: ET
authors.lastname: Tan
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Lisa J
authors.initials: LJ
authors.lastname: Wilmes
authors.affiliation: Department of Radiology, University of Michigan, Ann Arbor, Michigan, USA.
authors.forename: Thomas L
authors.initials: TL
authors.lastname: Chenevert
authors.affiliation: Department of Epidemiology and Biostatistics, University of California, San Francisco, California, USA.
authors.forename: John
authors.initials: J
authors.lastname: Kornak
authors.affiliation: MRI Lab, GE Global Research, One Research Circle, Niskayuna, New York, USA.
authors.forename: Luca
authors.initials: L
authors.lastname: Marinelli
authors.affiliation: Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA.
authors.forename: Nola
authors.initials: N
authors.lastname: Hylton
mesh_terms: D000328:Adult; D000368:Aged; D016477:Artifacts; D001943:Breast Neoplasms / Q000473:pathology* / Q000628:therapy*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods* / Q000592:standards; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods* / Q000592:standards; D008875:Middle Aged; D017711:Nonlinear Dynamics; D017410:Practice Guidelines as Topic; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016896:Treatment Outcome; D014481:United States
keywords: ADC; breast cancer; diffusion-weighted imaging; gradient nonlinearity; multicenter studies; quantitative imaging