Digital Imaging and Communications in Medicine

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1		Stylianos Karagiannis	--	1398	2023-09-22 10:56:38	\|
2	layout	Jessie Wu	+ 8 word(s)	1406	2023-09-25 03:01:32	\|

This entry is adapted from the peer-reviewed paper 10.3390/app131810072

Medical imaging plays a crucial role in modern healthcare, providing essential information for accurate diagnosis and treatment planning. The Digital Imaging and Communications in Medicine (DICOM) standard has revolutionized the storage, transmission, and sharing of medical images and related data. This research presents an implementation of DICOM communication and the development of a practical demonstration for simulation purposes. The simulation can be used for conducting cybersecurity tests in the context of DICOM communication.

medical imaging DICOM PACS eHealth simulation

1. Introduction

Digital Imaging and Communications in Medicine (DICOM) defines a set of entities representing different aspects of medical imaging and patient information ^[1]:

Patients (P) encapsulates individual patient data, including attributes such as name, ID, and birthdate. A patient p can be associated with one or more studies ( $P \to [S_{1}, S_{2}, \dots]$ ).
Study and Study Series (S and $S e$ ) includes related medical images and metadata, while Series groups images within a study based on common characteristics. A study s can include one or more series ( $S e = [S_{1}, S_{2}, \dots]$ ).
Image (I) refers to a set of DICOM images I; Series $S e$ groups related images ( $S e \to [I_{1}, I_{2}, \dots]$ ).
Physician ( $P h$ ) represents healthcare professionals; images I are interpreted by a physician $P h$ ( $P h \to [I_{1}, I_{2}, \dots]$ ).
Modalities (M) refers to imaging-related equipment or healthcare modalities, including imaging devices, specifying manufacturer details and software version. Images I are generated by a specific modality M ( $M \to [I_{1}, I_{2}, \dots]$ ).

DICOM is designed for the management of medical images and associated data within a healthcare environment.

2. Picture Archiving and Communication System (PACS)

PACS is a crucial system utilized in the medical field for the storage, management, and distribution of medical images and associated patient information. It replaces traditional film-based systems by enabling healthcare providers to capture, store, retrieve, and view medical images electronically. With PACS, the cumbersome task of managing physical film records is replaced by a digital infrastructure that facilitates easy image access and promotes efficient collaboration among healthcare professionals. Orthanc ^[2]^[3], on the other hand, is an open-source implementation of a PACS server. It provides a lightweight, vendor-neutral, and standards-compliant solution for managing medical images and associated data. Orthanc serves as a software platform that can be utilized to establish a PACS server infrastructure. Its open-source nature offers flexibility and customization options, making it an appealing choice for institutions and developers seeking to create their own PACS environment.

3. Encoding and Compression Techniques in DICOM

The Transfer Syntax ^[4] in DICOM refers to the encoding and compression techniques used to represent and transmit DICOM data. It determines how DICOM objects, including images, are serialized into a byte stream that can be transmitted or stored. DICOM supports multiple Transfer Syntaxes to provide flexibility, interoperability, and efficient handling of various data formats. Commonly used Transfer Syntaxes in DICOM include the following ^[4]:

Implicit VR Little Endian: a Transfer Syntax that uses a combination of implicit value representation encoding and little-endian byte ordering. It is widely used for uncompressed DICOM images, and supports a variety of data types. This is the default Transfer Syntax for most DICOM files.
Explicit VR Little Endian: a Transfer Syntax that uses explicit VR encoding and little-endian byte ordering. Commonly used for uncompressed DICOM images, it provides explicit VR tags, which make it easier to parse and understand the data.
JPEG Lossless: a Transfer Syntax that employs the Joint Photographic Experts Group (JPEG) Baseline algorithm for lossless compression of DICOM images, JPEG Lossless ^[4]^[5] is utilized when a balance between compression and preservation of image quality is required. It achieves significant compression ratios while maintaining the integrity of the image data. JPEG Lossless is particularly useful for storing or transmitting DICOM images where lossy compression is not acceptable.
JPEG Baseline: a specific Transfer Syntax that utilizes the JPEG Baseline algorithm for compressing DICOM images, JPEG Baseline ^[4]^[6] is a lossy compression technique that achieves significant compression ratios while maintaining acceptable image quality for many medical imaging applications. JPEG Baseline is often used for transmitting DICOM images over networks with limited bandwidth or storage capacity, as it helps reduce the size of image data.

By supporting various Transfer Syntaxes, DICOM enables interoperability between different systems, ensuring that medical imaging data can be exchanged and interpreted correctly across diverse platforms and applications.

4. Service–Object Pair (SOP) Class and Transfer Syntax

SOP Classes ^[4] are service objects that encapsulate DICOM image files. An SOP Class defines a specific type of medical imaging or non-imaging service that can be performed on a DICOM object. It represents a combination of a service and an object on which the service can be performed. Popular SOP Classes include, among others ^[4]:

CT Image Storage (1.2.840.10008.5.1.4.1.1.2): stores Computed Tomography (CT) images, which are used for diagnostic purposes and provide detailed cross-sectional views of the body.
MR Image Storage (1.2.840.10008.5.1.4.1.1.4): stores Magnetic Resonance Imaging (MRI) images, which are used to visualize internal structures of the body using magnetic fields and radio waves, providing detailed anatomical information.
Ultrasound Image Storage (1.2.840.10008.5.1.4.1.1.6.1): stores ultrasound images; ultrasound imaging uses high-frequency sound waves to generate images of organs and tissues in real-time, and is often used in obstetrics, cardiology, and other medical applications.
X-ray Radiography Image Storage (1.2.840.10008.5.1.4.1.1.1): stores X-ray images; widely used for various medical purposes, X-rays provide two-dimensional images that can help diagnose bone fractures, detect abnormalities, and visualize internal structures.

The above SOP Classes define the necessary metadata, attributes, and operations required to handle and interpret images of their respective modalities.

5. Presentation Contexts

Presentation Contexts in DICOM define the combination of a specific SOP Class and one or more supported Transfer Syntaxes that an application entity (AE) can handle for communication purposes. When two DICOM devices establish a connection or association, they negotiate the set of services and data formats that they can support. This negotiation is accomplished using Presentation Contexts. A Presentation Context consists of the following components ^[4]:

Abstract Syntax: this identifies the class or type of DICOM object being transmitted or requested, and represents a specific SOP Class, such as CT Image Storage or MR Image Storage.
Transfer Syntaxes: these define the encoding and compression techniques used to represent and transmit the DICOM data, and specify how the DICOM object is serialized into a byte stream. Multiple Transfer Syntaxes can be associated with a single Abstract Syntax, allowing for flexibility in data formats and compression options.

The process of association negotiation in the context of medical imaging involves the exchange of information between two devices. During this negotiation, both devices share a list of supported Presentation Contexts. Each Presentation Context is composed of an Abstract Syntax along with one or more Transfer Syntaxes that the device is capable of supporting for that specific Abstract Syntax.

The two devices then compare the lists of Presentation Contexts they have shared and work towards finding a mutually supported Presentation Context. When this mutual agreement is reached, it signifies that the devices can effectively communicate and conduct operations involving DICOM objects. This is done using the designated Abstract Syntax, while the agreed-upon Transfer Syntax is employed for the communication.

For instance, consider a scenario in which two devices establish a Presentation Context with an Abstract Syntax. This agreement indicates that the devices are now equipped to exchange and manipulate magnetic resonance image data using the JPEG Baseline compression algorithm. This enables seamless and efficient communication between the devices while ensuring compatibility in handling medical image information.

6. Application Entities (AEs)

The AE concept ^[4] is fundamental to Digital Imaging and DICOM standards. It represents a node or device in a network that communicates using DICOM protocols. An AE can be a piece of medical imaging equipment, such as a CT scanner, MRI machine, or PACS server. In the context of DICOM, an AE is identified by a unique AE title, which serves as its network address. The AE title is used to establish connections and enable communication between different entities in a DICOM network. Each AE is responsible for sending and receiving DICOM objects, including medical images, patient information, and related metadata.

AEs provide services such as querying/retrieval, storage, and printing of DICOM objects. They can act as a Service Class Provider (SCP), which receives requests for services, or a Service Class User (SCU) ^[4], which initiates requests and interacts with other endpoints. The roles of SCPs and SCUs can be performed by the same AE or by different endpoints depending on the system architecture and requirements. An Application Entity represents a DICOM node or device in the network. In the DICOM simulator, an AE is created using the AE class from Pynetdicom. The AE title is set to “MODALITY”, which identifies the simulated modality in the network.

References

Fritz, S.L.; Roys, S.R.; Munjal, S. Design requirements for DICOM patient, study, and results management. In Proceedings of the Medical Imaging 1996: PACS Design and Evaluation: Engineering and Clinical Issues, Newport Beach, CA, USA, 13–15 February 1996; Volume 2711, pp. 98–108.
Orthanc—DICOM Server—Orthanc-Server.com. Available online: https://www.orthanc-server.com/ (accessed on 8 July 2023).
Welcome to the Orthanc Book 2014; Orthanc Book Documentation—Book.Orthanc-Server.com. Available online: https://book.orthanc-server.com/index.html (accessed on 8 July 2023).
Association, N.E.M. Digital Imaging and Communication in Medicine (DICOM). NEMA PS 3 Supplement 23 Structured Reporting. 1997. Available online: https://www.dicomstandard.org/current (accessed on 5 September 2023).
Mustra, M.; Delac, K.; Grgic, M. Overview of the DICOM standard. In Proceedings of the 2008 50th International Symposium ELMAR, Zadar, Croatia, 10–12 September 2008; Volume 1, pp. 39–44.
Hamamoto, K. Standardization of JPEG quantization table for medical ultrasonic echo images. In Proceedings of the ICECS’99. Proceedings of ICECS’99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No. 99EX357), Paphos, Cyprus, 5–8 September 1999; Volume 2, pp. 683–686.

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Subjects: Mathematics, Applied

Contributors MDPI registered users' name will be linked to their SciProfiles pages. To register with us, please refer to https://encyclopedia.pub/register :

Stylianos Karagiannis

Emmanouil Magkos

Christoforos Ntantogian

Ricardo Cabecinha

Theofanis Fotis

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Update Date: 25 Sep 2023

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