Design and Implementation of the Pre-Clinical DICOM Standard in Multi-Cohort Murine Studies.

Joseph D Kalen,David A Clunie,Justin Kirby,Yanling Liu,Paula M Jacobs,James L Tatum,Ulrike Wagner,John B Freymann,Kirk E Smith,Christian Suloway,James H Doroshow

doi:10.3390/tomography7010001

Abstract

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.

Highlights

The use of the Digital Imaging and Communications in Medicine (DICOM) standard for storage and interchange of radiology images is ubiquitous in human clinical imaging environments
In addition to the required files, we provide a pre-clinical example including a tracking spreadsheet used in a patient-derived xenograft study, associated MRI data, and the resulting image acquisition context structured report (SR)
The small animal imaging community and the National Cancer Institute realized that to advance co-clinical research and to address the issues of translation from bench to bedside, the DICOM information that was developed for clinical images needed to be extended to pre-clinical data

Summary

Introduction

The use of the Digital Imaging and Communications in Medicine (DICOM) standard for storage and interchange of radiology images is ubiquitous in human clinical imaging environments. The new standard provided for (1) for the transfer and display of digital images, (2) development of picture archiving and communication systems (PACS) with interfaces to other health care information systems, and (3) allowed for the creation of diagnostic databases. The DICOM standard has undergone numerous enhancements as manufacturers improved and developed new radiological equipment but retains backward compatibility. Pre-clinical modality manufacturers have either developed their own proprietary image formats or used a minimum subset of features within the clinical DICOM standard. Equipment intended for human imaging that is re-purposed for animal imaging generally produces DICOM, but typically suffers from a lack of animal-specific identifying and descriptive parameters

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