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Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies.
Malyarenko, Dariya; Fedorov, Andriy; Bell, Laura; Prah, Melissa; Hectors, Stefanie; Arlinghaus, Lori; Muzi, Mark; Solaiyappan, Meiyappan; Jacobs, Michael; Fung, Maggie; Shukla-Dave, Amita; McManus, Kevin; Boss, Michael; Taouli, Bachir; Yankeelov, Thomas E; Quarles, Christopher Chad; Schmainda, Kathleen; Chenevert, Thomas L; Newitt, David C.
Affiliation
  • Malyarenko D; University of Michigan, Radiology, Ann Arbor, Michigan, United States.
  • Fedorov A; Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, United States.
  • Bell L; Barrow Neurological Institute, Division of Imaging Research, Phoenix, Arizona, United States.
  • Prah M; Medical College of Wisconsin, Radiology Research, Milwaukee, Wisconsin, United States.
  • Hectors S; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
  • Arlinghaus L; Vanderbilt University Medical Center, Institute of Imaging Science, Nashville, Tennessee, United States.
  • Muzi M; University of Washington, Imaging Research Laboratory, Seattle, Washington, United States.
  • Solaiyappan M; Johns Hopkins School of Medicine, The Russell H. Morgan Department of Radiology and Radiological Science and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, United States.
  • Jacobs M; Johns Hopkins School of Medicine, The Russell H. Morgan Department of Radiology and Radiological Science and Sidney Kimmel Comprehensive Cancer Center, Baltimore, Maryland, United States.
  • Fung M; Memorial Sloan Kettering Cancer Center, GE Healthcare, New York, Unites States.
  • Shukla-Dave A; Memorial Sloan Kettering Cancer Center, Departments of Medical Physics and Radiology, New York, New York, United States.
  • McManus K; University of Colorado Boulder, Department of Physics, Boulder, Colorado, United States.
  • Boss M; National Institute of Standards and Technology, Applied Physics Division, Boulder, Colorado, United States.
  • Taouli B; Translational and Molecular Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, United States.
  • Yankeelov TE; Vanderbilt University Medical Center, Institute of Imaging Science, Nashville, Tennessee, United States.
  • Quarles CC; University of Texas at Austin, Biomedical Imaging, Austin, Texas, United States.
  • Schmainda K; Barrow Neurological Institute, Division of Imaging Research, Phoenix, Arizona, United States.
  • Chenevert TL; Medical College of Wisconsin, Radiology Research, Milwaukee, Wisconsin, United States.
  • Newitt DC; University of Michigan, Radiology, Ann Arbor, Michigan, United States.
J Med Imaging (Bellingham) ; 5(1): 011006, 2018 Jan.
Article in En | MEDLINE | ID: mdl-29134189
This paper reports on results of a multisite collaborative project launched by the MRI subgroup of Quantitative Imaging Network to assess current capability and provide future guidelines for generating a standard parametric diffusion map Digital Imaging and Communication in Medicine (DICOM) in clinical trials that utilize quantitative diffusion-weighted imaging (DWI). Participating sites used a multivendor DWI DICOM dataset of a single phantom to generate parametric maps (PMs) of the apparent diffusion coefficient (ADC) based on two models. The results were evaluated for numerical consistency among models and true phantom ADC values, as well as for consistency of metadata with attributes required by the DICOM standards. This analysis identified missing metadata descriptive of the sources for detected numerical discrepancies among ADC models. Instead of the DICOM PM object, all sites stored ADC maps as DICOM MR objects, generally lacking designated attributes and coded terms for quantitative DWI modeling. Source-image reference, model parameters, ADC units and scale, deemed important for numerical consistency, were either missing or stored using nonstandard conventions. Guided by the identified limitations, the DICOM PM standard has been amended to include coded terms for the relevant diffusion models. Open-source software has been developed to support conversion of site-specific formats into the standard representation.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline Language: En Journal: J Med Imaging (Bellingham) Year: 2018 Type: Article Affiliation country: United States

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Guideline Language: En Journal: J Med Imaging (Bellingham) Year: 2018 Type: Article Affiliation country: United States