Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI.
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| Title: | Data Format Standardization and DICOM Integration for Hyperpolarized 13C MRI. |
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| Authors: | Diaz, Ernesto1, Sriram, Renuka1, Gordon, Jeremy W.1, Sinha, Avantika1, Liu, Xiaoxi1, Sahin, Sule I.1,2, Crane, Jason C.1, Olson, Marram P.1, Chen, Hsin-Yu1, Bernard, Jenna M. L.1, Vigneron, Daniel B.1,2, Wang, Zhen Jane1, Xu, Duan1,2, Larson, Peder E. Z.1,2 peder.larson@ucsf.edu |
| Source: | Journal of Digital Imaging. Oct2024, Vol. 37 Issue 5, p2627-2634. 8p. |
| Subjects: | Database management standards, Stretch (Physiology), Digital diagnostic imaging, Magnetic resonance imaging, Metabolites, Dicom (Computer network protocol), Information retrieval, Metadata, Digital image processing |
| Abstract: | Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique. [ABSTRACT FROM AUTHOR] |
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| Database: | Engineering Source |
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| Abstract: | Hyperpolarized (HP) 13C MRI has shown promise as a valuable modality for in vivo measurements of metabolism and is currently in human trials at 15 research sites worldwide. With this growth, it is important to adopt standardized data storage practices as it will allow sites to meaningfully compare data. In this paper, we (1) describe data that we believe should be stored and (2) demonstrate pipelines and methods that utilize the Digital Imaging and Communications in Medicine (DICOM) standard. This includes proposing a set of minimum set of information that is specific to HP 13C MRI studies. We then show where the majority of these can be fit into existing DICOM attributes, primarily via the "Contrast/Bolus" module. We also demonstrate pipelines for utilizing DICOM for HP 13C MRI. DICOM is the most common standard for clinical medical image storage and provides the flexibility to accommodate the unique aspects of HP 13C MRI, including the HP agent information but also spectroscopic and metabolite dimensions. The pipelines shown include creating DICOM objects for studies on human and animal imaging systems with various pulse sequences. We also show a python-based method to efficiently modify DICOM objects to incorporate the unique HP 13C MRI information that is not captured by existing pipelines. Moreover, we propose best practices for HP 13C MRI data storage that will support future multi-site trials, research studies, and technical developments of this imaging technique. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 08971889 |
| DOI: | 10.1007/s10278-024-01100-2 |
