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Medical imaging informatics simulators: a tutorial

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

   A medical imaging informatics infrastructure (MIII) platform is an organized method of selecting tools and synthesizing data from HIS/RIS/PACS/ePR systems with the aim of developing an imaging-based diagnosis or treatment system. Evaluation and analysis of these systems can be made more efficient by designing and implementing imaging informatics simulators. This tutorial introduces the MIII platform and provides the definition of treatment/diagnosis systems, while primarily focusing on the development of the related simulators.

Methods

   A medical imaging informatics (MII) simulator in this context is defined as a system integration of many selected imaging and data components from the MIII platform and clinical treatment protocols, which can be used to simulate patient workflow and data flow starting from diagnostic procedures to the completion of treatment. In these processes, DICOM and HL-7 standards, IHE workflow profiles, and Web-based tools are emphasized. From the information collected in the database of a specific simulator, evidence-based medicine can be hypothesized to choose and integrate optimal clinical decision support components. Other relevant, selected clinical resources in addition to data and tools from the HIS/RIS/PACS and ePRs platform may also be tailored to develop the simulator. These resources can include image content indexing, 3D rendering with visualization, data grid and cloud computing, computer-aided diagnosis (CAD) methods, specialized image-assisted surgical, and radiation therapy technologies.

Results

   Five simulators will be discussed in this tutorial. The PACS–ePR simulator with image distribution is the cradle of the other simulators. It supplies the necessary PACS-based ingredients and data security for the development of four other simulators: the data grid simulator for molecular imaging, CAD–PACS, radiation therapy simulator, and image-assisted surgery simulator. The purpose and benefits of each simulator with respect to its clinical relevance are presented.

Conclusion

   The concept, design, and development of these five simulators have been implemented in laboratory settings for education and training. Some of them have been extended to clinical applications in hospital environments.

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Abbreviations

AMS:

Acquisition modality simulator

CAD:

Computer-aided diagnosis and detection

CT:

Computed tomography

DCU:

DICOM conversion unit

DG:

Data grid

DGS:

Data grid simulator

DICOM:

Digital imaging and communications in medicine

DHA:

Digital hand atlas

DICOM SR:

DICOM structured report

DVH:

Dose–volume histogram

ePR:

Electronic patient record

GUI:

Graphical user interface

HIS:

Hospital information system

IAS:

Image-assisted surgery

IAT:

Image-assisted therapy

IHE:

Integrating the healthcare enterprise

IHE XDS-I:

IHE cross-enterprise document sharing for imaging

ITPN:

Intelligent treatment plan navigator

KB:

Knowledge base

MIDG:

Molecular imaging data grid

MIII:

Medical imaging informatics infrastructure

MISS:

Minimally invasive spinal surgery

OGSA:

Open grid services architecture

PACS:

Picture archiving and communications system

PET:

Positron emission tomography

PPM:

Preprocessing manager

Q/R:

Query/retrieve

RIS:

Radiology information system

RSNA:

Radiological Society of North America

RT:

Radiation therapy

TPS:

Treatment planning system

US:

Ultrasound

WS:

Work station

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Acknowledgments

The concept of medical imaging informatics simulators was conceived when the IPILab was established at USC in 2000. The PACS simulator was first exhibited at RSNA in 2002, and different simulators have continued being exhibited thereafter. Many graduate students, fellows, colleagues, and collaborators, during their time at IPILab, have contributed substantially in the development of these simulators

Conflict of interest

H. K. Huang, Ruchi Deshpande, Jorge Documet, Anh Le, Jasper Lee, Kevin Ma, and Brent Liu declare that they have no conflict of interest.

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Authors and Affiliations

  1. IPILab, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, 734 W. Adams Blvd, Los Angeles, CA, 90089, USA

    H. K. Huang, Ruchi Deshpande, Kevin Ma & Brent J. Liu

  2. MedQIA, Los Angeles, CA, USA

    Jorge Documet

  3. Department of Radiation Oncology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA

    Anh H. Le

  4. SCImage Inc, Los Altos, CA, USA

    Jasper Lee

Authors
  1. H. K. Huang
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  2. Ruchi Deshpande
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  3. Jorge Documet
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  4. Anh H. Le
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  5. Jasper Lee
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  6. Kevin Ma
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  7. Brent J. Liu
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Corresponding author

Correspondence to H. K. Huang.

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Huang, H.K., Deshpande, R., Documet, J. et al. Medical imaging informatics simulators: a tutorial. Int J CARS 9, 433–447 (2014). https://doi.org/10.1007/s11548-013-0939-y

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