1. Medical Imaging Systems
Tamim Alganam

2. Biomedical Imaging
“The science and the branch of medicine concerned with the development and use of imaging devices and techniques to obtain internal anatomic images and to provide biochemical and physiological analysis of tissues and organs.”
Before the purposes, processes, and management issues related to the use of imaging systems in health care are addressed, several terms will be defined. The first one is biomedical imaging from the National Library of Medicine (NLM).
The NLM (2004) defines biomedical imaging as “The science and the branch of medicine concerned with the development and use of imaging devices and techniques to obtain internal anatomic images and to provide biochemical and physiological analysis of tissues and organs” (para. 1).
Biomedical imaging includes technologies that capture, store, analyze and display at the organ, tissue, cellular, and molecular level using techniques such as computed tomography (CT), magnetic resonance imaging (MRI), interventional radiology, positron emission tomography (PET), single photon emission coherence tomography (SPECT), ultrasound imaging, and optical coherence tomography (OCT).

3. Medical Imaging Informatics
Relatively new multidisciplinary field
Intersects with the biological sciences, health services, information sciences, medical physics, and engineering
Touches every aspect of the imaging chain
The Society for Imaging Informatics in Medicine (SIIM), provides the following definition from Andriole (2006), “Medical imaging informatics is a relatively new multidisciplinary field that intersects with the biological sciences, health services, information sciences, medical physics, and engineering. Imaging informatics touches every aspect of the imaging chain from image creation and acquisition, to image distribution and management, to image storage and retrieval, to image processing, analysis and understanding, to image visualization and data navigation; to image interpretation, reporting, and communications. The field serves as the integrative catalyst for these processes and forms a bridge with imaging and other medical disciplines” (para 1-2).
An example of imaging informatics applications is a computerized axial tomography (CAT) scanner, which uses software algorithms to recreate a three-dimensional image of the body parts. Another example would be Picture Archiving and Communication System (PACS) which are a combination of hardware and software dedicated to the short and long term storage, retrieval, management, distribution, and presentation of images.

4. Why Use Imaging Systems
Detection and diagnosis
Assessment and planning
Guidance of procedures
Communication
Education and training
Research
With an understanding of the various terms, let’s next examine the purposes related to the use of imaging systems in health care. According to Greenes and Brinkley (2006), “Imaging is a central part of the healthcare process for diagnosis, treatment planning, image-guided treatment, assessment or response to treatment, and estimation of prognosis. In addition, it plays important roles in medical communication and education, as well as research” (p. 627).
For example, imaging systems:
Improve access to the studies. Remote viewing is possible and thereby expediting diagnosis and treatment.
Enhance image communication. Images can be viewed by multiple clinicians at different locations.
Decrease the amount of time it takes to provide a report back to an ordering physician. Images can be retrieved, interpreted, and a report back to the ordering physician expedited.

5. Imaging Systems and Health care Processes
Acquiring/managing images
Image creation and acquisition, image distribution and management, image storage and retrieval
Interpreting images
Image processing, analysis and understanding, image visualization and data navigation; image interpretation
Communicating the interpretations
Image reporting and communications
The purposes outlined in the last slide related to the use of imaging systems in health care are compelling. But what are the processes associated with the use of imaging systems in health care? Basically the three which cover Andriole’s “image chain” are:
Acquisition and management of the digitized images would include image creation and acquisition, to image distribution and management, to image storage and retrieval.
Image processing, analysis and understanding, to image visualization and data navigation, to image interpretation are a part of the interpretation of the images process.
Image reporting and communication are pieces to the communication of the interpretations process.
The next slide shows a Picture Archiving and Communication System or PACS configuration that shows the processes.

6. PACS Configuration
According to Ralston & Coleman, (2010), “A Picture Archiving and Communication System stores, distributes, and displays medical images for interpretation or review” (p. 34).
As explained by Bhachu (2005), “a Picture Archiving and Communications System (PACS) data network is a computer network system designed to transfer, store and retrieve digital medical images for viewing at the right place, and at the right time. It integrates data from system to system, inside and outside healthcare departments, and ensures that images and image-related data are made available as needed at the point of care” (para. 5).
This image is an example of a facility-wide PACS configuration. At the center is the archiving and communication system (PACS) server. Digital acquisition devices, such as ultrasound (US), computed tomography (CT), mammography (mammo), are sent to the server. An electronic medical record (EMR) also supplies information to the server. The output from the server is to storage devices, and to reading stations, or to the Internet, where access is made available via a web browser to remote locations.
Bhachu (2005) notes, “The PACS data network should provide a seamlessly-integrated information management infrastructure within the department and the enterprise to improve care, service and productivity, while enhancing the quality of the work environment in a secure and reliable manner” (para. 7).
Image courtesy of Keystone Medical Technologies

7. Format Standards
Digital Imaging and Communications in Medicine (DICOM)
Standard for the electronic exchange of medical images
Data associated with the images
Health Level Seven (HL7)
Message standard
The transmission of data about a medical image from acquisition devices to storage devices requires a messaging format. Digital Imaging and Communications in Medicine (DICOM) is a standard for the electronic exchange of medical images and the data associated with the images. According to National Electrical Manufacturers Association (n.d.), “DICOM is a global information technology standard that is used in virtually all hospitals worldwide. Its current structure… is designed to ensure the interoperability of systems used to: produce, store, display, process, send, retrieve, query or print medical images and derived structured documents as well as to manage related workflow” (para. 1). DICOM defines both the file content and communication protocol.
Another communication standard format comes from Health Level Seven International, or HL7. According to HL7’s web site, HL7 is “an ANSI-accredited standards developing organization dedicated to providing a comprehensive framework and related standards for the exchange, integration, sharing, and retrieval of electronic health information that supports clinical practice and the management, delivery and evaluation of health services” (HL7, 2011, para. 1).
Message standards associated with patient demographic and exam ordering information, result reporting, and billing are addressed by HL7.
The Hospital Information System (HIS) and Radiology Information System (RIS) use HL7 while the PACS use DICOM. Both DICOM and HL7 support the integration among systems, which is discussed later on in this lecture.

8. Management Issues Storage concerns Film versus digital
Image modalities differ
Contrast and spatial resolution requirements
Number of images or the size of the data sets
Raw or processed data
Use of data compression
There are a number of management issues that will need to be addressed with regards to imaging systems.
The first issue is storage. Managing the storage and retrieval of digital images involves on-line digital archiving, retrieval of images via the image databases, and transmission of images over communication networks. Once the image has been interpreted, it will need to be stored or electronically archived. While the industry is moving to digital images, film may still be in use. Storage of film involves file space. Film also requires material resources such as film and its jacket, along with staff resources to prepare it for storage, as well as to retrieve it when needed. For digital images the process changes so the identified film issues are eliminated or reduced. For example, as soon as image quality is verified, it can be sent immediately to an electronic archive thereby eliminating the need for shelved film storage.
According to Greenes and Brinkley (2006) “Image modalities differ substantially in their storage requirements, depending on the contrast and spatial resolution needed, the number of images or the size of the data sets, whether raw or processed data are stored, and whether data-compression techniques are used” (p. 634).
Also mentioned by Greenes and Brinkley (2006) is the need for the image archiving system to be able to manage not only on-line maintenance of active images, but must be able to store older image data. They suggest establishing “hierarchies of storage” to address concerns with speed of access. This would involve setting up a process that takes into account higher access mediums, such as a local workstation to storage on slower access mediums such as an optical disk. Greenes and Brinkley (2006) note the need to decide where to place image data based on patterns of expected use, and network traffic, when putting the plan together.
Another way to address storage issues would be with data compression. Krupinski (2010) noted “Compression reduces the volume of data to reduce image processing, transmission times, bandwidth requirements, and storage needs” (p. 106).

9. Management Issues Image integration Viewing stations
On-line image databases
Image-management systems
Networks
In addition to storage concerns, another management issue is image integration. Integration involves viewing stations, image databases, image management systems, and networks. Greenes and Brinkley (2006) state “The network configuration and the capacity of each part must be planned in relation to considerations such as patterns of expected use and cost” (p. 637).
Image transmission times would be different given choice of network method and degree of compression (Greenes and Brinkley, 2006).
Because of their own distinctive management issues, viewing station factors will be examined further on the next slide.
Image integration with other health care information is addressed later under major challenges.

10. Management Issues Technological and human engineering factors
Radiologist
View and interpret
Referring clinicians
Review and consultation
Economic factors
Setting up workstations where radiologists will view and interpret digital images and referring clinicians will review the interpreted images pose their own unique management challenges. First, technological factors associated with digital displays will be discussed. Greenes and Brinkley (2006) point out that radiologist viewing consoles for image interpretation need to support general image manipulation operations and other operations that the radiologist performs while analyzing images. They stress “the ability to reshuffle images, to shift attention, to zoom in on a specific area, and to step back again to get an overview are all essential to the interpretive and analytic processes” and go on to further state “the design of practical image-interpretation workstations thus requires considerable human engineering and experimentation” (Greenes and Brinkley, 2006, p. 639, 641).
For referring clinicians, Greenes and Brinkley (2006) indicate their workstation “must be easily accessible and thus must be conveniently distributed throughout the institution, or throughout an extended integrated delivery network” (p. 641).
Regarding economic factors, Greenes and Brinkley (2006) make note of the fact that “costs for the network infrastructure and for image acquisition, storage, and review can be shared by the entire healthcare system rather than falling exclusively to radiology departments” (p. 641).

11. Major Challenges Image integration Hospital Information System (HIS)
Contains all the clinical, administrative, financial, and demographic information
Just having a medical image is not of much benefit if it is not accessible for use by various applications. The ability to have an efficient image distribution and access process is dependent on the successful integration of multiple information systems. Connectivity, or integrating medical images with information systems, such as the hospital information system, is a major challenge for health care institutions and informaticians.
AHIMA defines hospital information system as “The comprehensive database containing all the clinical, administrative, financial, and demographic information about each patient served by a hospital” (AHIMA, 2012, p. 171). The HIS plays an integral part in providing the data about the patient such as what is captured at registration which helps maintain data consistency.

12. Major Challenges Medical imaging system
Radiology Information Systems (RIS)
Standalone
Components of HIS
The Radiology Information System (RIS) is not the same as the HIS. RIS is one of the most recognizable components of a medical imaging system. The RIS is used by a radiology department to support the radiology department’s information needs by managing workflow of such things as maintaining the film library and digital archive, scheduling of patient exams, registering of patients, distributing reports, and billing. According to Branstetter (2010), an RIS “Can receive orders from the Hospital Information System, or allow manual input of orders locally” (p. 438).
Greenes and Brinkley (2006), make note that “RISs have been implemented either as standalone systems or as components of HISs. In either case, an RIS must be integrated with other information systems within an institution to allow reconciliation of patient data, to support examination scheduling and results reporting, and to facilitate patient billing” (p. 643).
Medical imaging systems are likely to have their own informatics support, separate from that of hospital information systems which makes integration more difficult.

13. Integration Example PACS integration Hospital information system
Radiology information system
Benefits to integration
Economic
Rapid access enhances the quality of patient care
PACS is the other most recognizable component of a medical imaging system. As you will recall from previous material in this lecture, PACS deals with storage and communication of medical images. Integration is necessary between the components of the medical imaging system and HIS for PACS implementation to be successful. As Greenes and Brinkley (2006) explained, “Picture-archiving and communication system (PACS) image-management functions must be integrated with RISs and HISs. Because RIS (or, in some cases, an HIS) keeps track of examinations and associates them with patients, and a PACS keeps track of images and associates them with examinations, the task is to provide coordination between the examination data on the two systems” (p. 643).
Benefits to integration per Arenson, Andriole, Avrin, & Gould (2000) include “…economic advantages, secure rapid access to all clinical information on patients, including imaging studies, anytime and anywhere, enhances the quality of patient care, although it is difficult to quantify” (p. 145).

14. Major Challenges Reporting methods Dictation/transcription
Speech recognition
Structured
Tools for entering data
Defined data elements
May use predefined list or vocabulary
Another major challenge for health care institutions and informaticians is the selection of a method for producing and distributing image reports. Traditionally, this has been done through clinician dictation followed by a transcriptionist typing a report and then review and approval by the dictator.
Speech recognition is another way for clinicians to document his or her interpretation of an image. AHIMA defines speech recognition technology as “technology that translates speech to text (AHIMA, 2012, p. 321). There are two types of speech recognition: front-end and back-end. According to AHIMA (2003), “Front-end” speech recognition is the term generally used to describe a process where the dictator (end user) speaks into a microphone or headset attached to a PC. The recognized words are displayed as they are recognized, and the dictator is expected to correct misrecognitions. Server-based speech recognition takes place after the dictator has created audio input in much the same way as usual, and the process then takes place at the server level, or on the “back end” (para. 30).
The final reporting method option is structured. Fenton (as cited in van Bemmel & Musen, 1999) states “Structured data entry largely involves the use of forms and other tools to enter information. Forms or computer entry screens include defined data elements or fields, some of which may be mandatory, some of which may be optional. Often the content entered into the different fields is specified via lists or a predefined vocabulary. Sometimes the system will intelligently follow the data entry and, based on what is entered, determine the next fields needing completion” (p. 52).

15. Medical Imaging Systems References
AHIMA e-HIM Work Group on Speech Recognition in the EHR. (2003). Speech recognition in the electronic health record. Retrieved from
American Health Information Management Association. (2012). Pocket glossary for health information management and technology (3rd ed.). Chicago, IL: Author.
Arenson, R. L., Andriole, K. P., Avrin, D. E., & Gould, R. G. (2000). Computers in imaging and health care: Now and in the future. Journal of Digital Imaging,13(4), Abstract retrieved from
Bhachu, D. (2005, September 1). The medical digital imaging revolution. Retrieved from
Branstetter, B. F. (Ed.), Practical imaging informatics: Foundations and applications for PACS professionals (pp ). New York, NY: Springer Science + Business Media.
Centers for Medicare and Medicaid Services. (2011, November 7). EHR incentive programs overview. Retrieved from
College of American Pathologists. (2010, September 16). Medical imaging standard extension for pathology will help advance health information interoperability. Retrieved from
Goedert, J. (2010, October 14). Advanced imaging app approved. Retrieved from
Greenes, R. A. & Brinkley, J. F., (2006). Imaging systems in radiology. In Shortliffe. E. H., & Cimino, J. J. (Eds.), Biomedical informatics: Computer applications in health care and biomedicine (3rd ed) (pp ). New York, NY: Springer Science + Business Media.
No audio.

16. Medical Imaging Systems References
AHIMA e-HIM Work Group on Speech Recognition in the EHR. (2003). Speech recognition in the electronic health record. Retrieved from
American Health Information Management Association. (2012). Pocket glossary for health information management and technology (3rd ed.). Chicago, IL: Author.
Arenson, R. L., Andriole, K. P., Avrin, D. E., & Gould, R. G. (2000). Computers in imaging and health care: Now and in the future. Journal of Digital Imaging,13(4), Abstract retrieved from
Bhachu, D. (2005, September 1). The medical digital imaging revolution. Retrieved from
Branstetter, B. F. (Ed.), Practical imaging informatics: Foundations and applications for PACS professionals (pp ). New York, NY: Springer Science + Business Media.
Centers for Medicare and Medicaid Services. (2011, November 7). EHR incentive programs overview. Retrieved from
College of American Pathologists. (2010, September 16). Medical imaging standard extension for pathology will help advance health information interoperability. Retrieved from
Goedert, J. (2010, October 14). Advanced imaging app approved. Retrieved from
Greenes, R. A. & Brinkley, J. F., (2006). Imaging systems in radiology. In Shortliffe. E. H., & Cimino, J. J. (Eds.), Biomedical informatics: Computer applications in health care and biomedicine (3rd ed) (pp ). New York, NY: Springer Science + Business Media.
No audio.