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Toward uniform implementation of parametric map Digital Imaging and Communication in Medicine standard in multisite quantitative diffusion imaging studies
- Source :
- Journal of Medical Imaging. 5:1
- Publication Year :
- 2017
- Publisher :
- SPIE-Intl Soc Optical Eng, 2017.
-
Abstract
- 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.
- Subjects :
- business.industry
Digital imaging
computer.software_genre
Imaging phantom
030218 nuclear medicine & medical imaging
Data modeling
Metadata
03 medical and health sciences
DICOM
0302 clinical medicine
Software
Quantitative Imaging Methods and Translational DevelopmentsāHonoring the Memory of Dr. Larry Clarke
030220 oncology & carcinogenesis
Medicine
Radiology, Nuclear Medicine and imaging
Data mining
business
computer
Parametric statistics
Diffusion MRI
Subjects
Details
- ISSN :
- 23294302
- Volume :
- 5
- Database :
- OpenAIRE
- Journal :
- Journal of Medical Imaging
- Accession number :
- edsair.doi.dedup.....825ef6fa2e98e56dbdd30198145f187a