Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies
The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Tomography |
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| Online Access: | https://www.mdpi.com/2379-139X/7/1/1 |
| _version_ | 1811180394461003776 |
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| author | Joseph D. Kalen David A. Clunie Yanling Liu James L. Tatum Paula M. Jacobs Justin Kirby John B. Freymann Ulrike Wagner Kirk E. Smith Christian Suloway James H. Doroshow |
| author_facet | Joseph D. Kalen David A. Clunie Yanling Liu James L. Tatum Paula M. Jacobs Justin Kirby John B. Freymann Ulrike Wagner Kirk E. Smith Christian Suloway James H. Doroshow |
| author_sort | Joseph D. Kalen |
| collection | DOAJ |
| description | The small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veterinary definitions, NCI Metathesaurus) were utilized to assist in defining terms implemented in pre-clinical imaging and new codes were added to integrate the specific small animal procedures and handling processes, such as housing, biosafety level, and pre-imaging rodent preparation. In addition to the standard DICOM fields, the small animal SR includes fields specific to small animal imaging such as tumor graft (i.e., melanoma), tissue of origin, mouse strain, and exogenous material, including the date and site of injection. Additionally, the mapping and harmonization developed by the Mouse-Human Anatomy Project were implemented to assist co-clinical research by providing cross-reference human-to-mouse anatomies. Furthermore, since small animal imaging performs multi-mouse imaging for high throughput, and queries for co-clinical research requires a one-to-one relation, an imaging splitting routine was developed, new Unique Identifiers (UID’s) were created, and the original patient name and ID were saved for reference to the original dataset. We report the implementation of the small animal SR using MRI datasets (as an example) of patient-derived xenograft mouse models and uploaded to The Cancer Imaging Archive (TCIA) for public dissemination, and also implemented this on PET/CT datasets. The small animal SR enhancement provides researchers the ability to query any DICOM modality pre-clinical and clinical datasets using standard vocabularies and enhances co-clinical studies. |
| first_indexed | 2024-04-11T09:01:20Z |
| format | Article |
| id | doaj.art-159cd52aebc34647a124be6719126750 |
| institution | Directory Open Access Journal |
| issn | 2379-139X |
| language | English |
| last_indexed | 2024-04-11T09:01:20Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Tomography |
| spelling | doaj.art-159cd52aebc34647a124be67191267502022-12-22T04:32:45ZengMDPI AGTomography2379-139X2021-02-01711910.3390/tomography7010001Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine StudiesJoseph D. Kalen0David A. Clunie1Yanling Liu2James L. Tatum3Paula M. Jacobs4Justin Kirby5John B. Freymann6Ulrike Wagner7Kirk E. Smith8Christian Suloway9James H. Doroshow10Small Animal Imaging Program, Laboratory Animal Sciences Program, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USAPixelMed Publishing, Bangor, PA 18013, USAImage and Visualization Group, Advanced Biomedical and Computational Sciences, Biomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USACancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Rockville, MD 20892, USACancer Imaging Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institute of Health, Rockville, MD 20892, USACancer Imaging Informatics Lab, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USACancer Imaging Informatics Lab, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USABiomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USADepartment of Biomedical Informatics, University of Arkansas for Medical Sciences, Little Rock, AR 72205, USAImage and Visualization Group, Advanced Biomedical and Computational Sciences, Biomedical Informatics and Data Science, Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USADivision of Cancer Treatment and Diagnosis, Center for Cancer Research, National Cancer Institute, National Institute of Health, Rockville, MD 20892, USAThe small animal imaging Digital Imaging and Communications in Medicine (DICOM) acquisition context structured report (SR) was developed to incorporate pre-clinical data in an established DICOM format for rapid queries and comparison of clinical and non-clinical datasets. Established terminologies (i.e., anesthesia, mouse model nomenclature, veterinary definitions, NCI Metathesaurus) were utilized to assist in defining terms implemented in pre-clinical imaging and new codes were added to integrate the specific small animal procedures and handling processes, such as housing, biosafety level, and pre-imaging rodent preparation. In addition to the standard DICOM fields, the small animal SR includes fields specific to small animal imaging such as tumor graft (i.e., melanoma), tissue of origin, mouse strain, and exogenous material, including the date and site of injection. Additionally, the mapping and harmonization developed by the Mouse-Human Anatomy Project were implemented to assist co-clinical research by providing cross-reference human-to-mouse anatomies. Furthermore, since small animal imaging performs multi-mouse imaging for high throughput, and queries for co-clinical research requires a one-to-one relation, an imaging splitting routine was developed, new Unique Identifiers (UID’s) were created, and the original patient name and ID were saved for reference to the original dataset. We report the implementation of the small animal SR using MRI datasets (as an example) of patient-derived xenograft mouse models and uploaded to The Cancer Imaging Archive (TCIA) for public dissemination, and also implemented this on PET/CT datasets. The small animal SR enhancement provides researchers the ability to query any DICOM modality pre-clinical and clinical datasets using standard vocabularies and enhances co-clinical studies.https://www.mdpi.com/2379-139X/7/1/1DICOMpre-clinicalco-clinicalin vivo imaginganimal modelpatient-derived xenograft (PDX) |
| spellingShingle | Joseph D. Kalen David A. Clunie Yanling Liu James L. Tatum Paula M. Jacobs Justin Kirby John B. Freymann Ulrike Wagner Kirk E. Smith Christian Suloway James H. Doroshow Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies Tomography DICOM pre-clinical co-clinical in vivo imaging animal model patient-derived xenograft (PDX) |
| title | Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies |
| title_full | Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies |
| title_fullStr | Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies |
| title_full_unstemmed | Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies |
| title_short | Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies |
| title_sort | design and implementation of the pre clinical dicom standard in multi cohort murine studies |
| topic | DICOM pre-clinical co-clinical in vivo imaging animal model patient-derived xenograft (PDX) |
| url | https://www.mdpi.com/2379-139X/7/1/1 |
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