title: Comparison of fitting methods and b-value sampling strategies for intravoxel incoherent motion in breast cancer.
abstract: OBJECTIVE
  To compare fitting methods and sampling strategies, including the implementation of an optimized b-value selection for improved estimation of intravoxel incoherent motion (IVIM) parameters in breast cancer.
  
  
  METHODS
  Fourteen patients (age, 48.4 ± 14.27 years) with cancerous lesions underwent 3 Tesla breast MRI examination for a HIPAA-compliant, institutional review board approved diffusion MR study. IVIM biomarkers were calculated using "free" versus "segmented" fitting for conventional or optimized (repetitions of key b-values) b-value selection. Monte Carlo simulations were performed over a range of IVIM parameters to evaluate methods of analysis. Relative bias values, relative error, and coefficients of variation (CV) were obtained for assessment of methods. Statistical paired t-tests were used for comparison of experimental mean values and errors from each fitting and sampling method.
  
  
  RESULTS
  Comparison of the different analysis/sampling methods in simulations and experiments showed that the "segmented" analysis and the optimized method have higher precision and accuracy, in general, compared with "free" fitting of conventional sampling when considering all parameters. Regarding relative bias, IVIM parameters fp and Dt differed significantly between "segmented" and "free" fitting methods.
  
  
  CONCLUSIONS
  IVIM analysis may improve using optimized selection and "segmented" analysis, potentially enabling better differentiation of breast cancer subtypes and monitoring of treatment.
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.|Sackler Institute of Graduate Biomedical Sciences, New York University School of Medicine, New York, New York, USA.
authors.forename: Gene Young
authors.initials: GY
authors.lastname: Cho
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.|New York University Langone Medical Center - Cancer Institute, New York, New York, USA.
authors.forename: Linda
authors.initials: L
authors.lastname: Moy
authors.affiliation: Department of Radiology, University of Utah, Salt Lake City, Utah, USA.
authors.forename: Jeff L
authors.initials: JL
authors.lastname: Zhang
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: Steven
authors.initials: S
authors.lastname: Baete
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: Riccardo
authors.initials: R
authors.lastname: Lattanzi
authors.affiliation: New York University Langone Medical Center - Cancer Institute, New York, New York, USA.
authors.forename: Melanie
authors.initials: M
authors.lastname: Moccaldi
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: James S
authors.initials: JS
authors.lastname: Babb
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: Sungheon
authors.initials: S
authors.lastname: Kim
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: Daniel K
authors.initials: DK
authors.lastname: Sodickson
authors.affiliation: Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, New York University School of Medicine, New York, New York, USA.
authors.forename: Eric E
authors.initials: EE
authors.lastname: Sigmund
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000473:pathology*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008875:Middle Aged; D009038:Motion
keywords: IVIM; b-value optimization; breast cancer; diffusion gradient; diffusion weighted MRI