11 - Data Security and Protection for Medical Images

Nowadays, Digital Imaging and Communications in Medicine (DICOM), an international standard used worldwide to access and handle various medical images through Picture Archiving and Communication System (PACS). This helps eliminate completely the use of costly and harmful traditional films. Besides, the existing infrastructures of the Internet have allowed us to develop the telemedicine services. However, the usage of foreign PACS is not suitable to diagnosis and medical consultation over the distance in Vietnam. This paper researches to implement PACS, online medical video consultation system and security DICOM Web Viewer serving diagnosis in Vietnam. First, we mention our methods of implementation. Then we discuss the results of completing image compression technology, connection technology, load balance technology for manufacturing PACS and online medical video consultation system. Next, the result of designing DICOM Web Viewer is introduced and updated. In order to solving security issue over Internet, modern security techniques are integrated into software system. Specially, by exploiting different techniques of data encoding, cryptography and watermarking, we propose an efficient solution to enhance information security in DICOM images over the Internet. Finally, our completed system has also been implemented and evaluated in hospitals.

Picture archiving and communication system (PACS) has played an important role in hospital and developed rapidly in recent years. It is an important part of PACS architecture that X-ray video output connects with PACS. In this paper, a method to digitize the video signals of X-ray facility is introduced. By means of the video capture card, we can acquire digital medical images from X-ray facility. The American College of Radiology (ACR) and the National Electrical Manufacturers Association (NEMA) developed a standard for Digital Imaging and Communications in Medicine (DICOM), this DICOM standard introduces a rule of medical image conversion from conventional format to DICOM one. According to abovementioned standard, X-ray video signals can be connected to PACS easily. This project has been applied in some hospitals successfully and there is satisfied result.

Avoiding Unread Images with PACS

This article provides an overview on the literature published on the topic of cybersecurity for PACS (Picture Archiving and Communications Systems) and medical imaging. From a practical perspective, PACS specific security measures must be implemented together with the measures applicable to the IT infrastructure as a whole, in order to prevent incidents such as PACS systems exposed to access from the Internet. Therefore, the article first offers an overview of the physical, technical and organizational mitigation measures that are proposed in literature on cybersecurity in healthcare information technology in general, followed by an overview on publications discussing specific cybersecurity topics that apply to PACS and medical imaging and present the “building blocks” for a secure PACS environment available in the literature. These include image de-identification, transport security, the selective encryption of the DICOM (Digital Imaging and Communications in Medicine) header, encrypted DICOM files, digital signatures and watermarking techniques. The article concludes with a discussion of gaps in the body of published literature and a summary.

PAC system is extending increasingly from the now well-established radiology applications into a hospital-wide PACS. New challenges are accompanying its spread into other clinical fields. With awareness of the importance of PAC systems among various medical experts, this system has been enhanced through the PAC system's pipeline, and simplification of image display for analysis via an interaction with the user. Generally PAC system consists of medical image, patients' data acquisition, storage, and display subsystems integrated by digital networks and application software. PAC system facilitates the systematic utilization of medical imaging for patient care. However, even though PAC system consist of medical image, data acquisition, storage and display subsystems, most of available PAC system does not have image analysis as required by the clinical expert. If the PAC system do have this element, it need interaction or interference from the clinical expert as user, and the PAC system storage mostly is an unstructured storage with no analysis element and report modules. And unfortunately in most cases, for the web-based PAC system, there are delayed in retrieval and visualize the required image from outside of the hospital. Most of the PACS with function of 3D display, it did not communicate information clearly and efficiently to users (clinical expert). Most of the visualization did not visual accurate information as required by the clinical expert. These listed constraints limited the clinical expert perspective regarding his/her decision. From market validation observation we concluded that most of the PAC system available in market does not have medical image processing functions for the purposes of decision analysis with minimum user interaction. Research towards this limitation has been conducted in accordance with the needs of clinical experts. Among these studies are: (i) angiography image processing for stenosis position detection and measurement of its dimensions, (ii) echocardiography image processing for detection of ventricular cardiac abnormalities (walls and volume) and (iii) 2D angiography images reconstructed to 3D images for display purposes and to identify the location of artery tree. With the result of these studies, the PAC system will integrate with extra modules, which are: i) 3D reconstruction function from single image angiogram with identification of the stenosis location, ii) Identification of abnormality heart wall chamber, iii) 3D reconstruction echocardiography left and right ventricular heart, and iv) 3D fused within CTA, angiography and MRI. As stated above, the common limitation for the web-based PAC system is the delayed in retrieval and visualize the required image from outside of the hospital/clinics. To overcome this limitation, we proposed a technique and integrated a related function for faster transmission of the processed image without sacrifice any importance information. And to complete the PAC system so that the new PAC system able to compete with current PAC system that available in market, we link the PACS with our Patients Clinical Record Database with report modules as required by the medical expert. The outputs of all those said researches will be integrated with the PAC system where each research output has been tested and validate by numbers of cardiac expert, the patients clinical record database has been tested in UKMMC and the PAC system currently being beta tested in a Private Clinic in Kelang, Selangor, Malaysia. Eventually the PAC system with the Patients Clinical Record Database will be integrated with these image analysis and 3D image visualization and it is plan to be tested in Veterinary Hospital of Universiti Putra Malaysia. To forward this project to commercialization activity, we have distributed questioners to Clinics in area Bangi (Selangor, Malaysia) and Nilai (Negeri Sembilan, Malaysia). There are 58 Medical, Veterinary and Dental Clinics received the questioner (currently we expand the distribution towards Serdang and Kajang (Selangor, Malaysia). Out of 58 clinics; a) 16% interested to collaborate and looking forward to see PAC system, b)8% interested with the PAC system but do not willing to have any demo, c) 44% not interested but open for demo of system, d) 28% not interested and not willing to have demo system and e) 4% return the form without answered for that particular question. To secure and protect the ownership, each research output has been submitted for Patent filed in Malaysia and with three chosen country, where 2 of the patent filed has been granted in Malaysia. We also copyrighted each module. This project has been selected by Universiti Putra Malaysia to be commercialized by a startup company seeded by UPM (CASD Medical Private Limited) under program INNOHUB. We realize to implement the complete PAC system in Hospital there are 10 main problems exist that we might need to overcome or try to minimize the consequences. These problems are; i) Integration with the Hospital Information System. Although a lack of inter-vendor device and IT integration can often make the problem worse, the market is improving as providers and meaningful use demand greater integration. Unfortunately, still, many radiologists and PACS administrators prefer to make full use of hospital IT to configure their own systems and achieve a bit more autonomy, ii) Every system has downtime where we need to establish alternate workflows. Both scheduled and unscheduled, but they need not have to be too serious to minimize the effect on patient care, iii) Non-standardized hanging protocol display is a common and pesky challenge for PACS users. Images from different modalities are not organized by default even though each of them generally will be transmitted through DICOM format getaway, each study takes a little longer to read. As the number of scanners increases and the sample of vendors expands, the problem grows worse, iv) Integration problems concern hardware, from digitizing pre-DICOM modalities to integrating systems for advanced image reconstruction. Add-ons like a DICOM converter can help squeeze out additional value from older CT, angiography and fluoroscopy systems, v) As with downtime, failures are unavoidable, there is a need to demonstrate strong support activities, vi) Effective training can be a cost-effective way to demonstrate to administrators and physicians many of PACS' underused and undervalued features. Training wil help to expose staff to what the system can do to make their jobs easier and more efficient, vii) The migration of data to the new PACS is often the most challenging part of the process, both in negotiating the release of data from the current PACS and in sorting out all the data entry errors that have accumulated over the lifespan of the system, viii) As other specialties realize the value of PACS, the system is slowly being taken out of radiologists' hands. PACS has become a mission-critical enterprise-wide tool used by nearly all specialties. With this change, decision-making for PACS-related purchases, upgrades and configurations has, in some cases, shifted from radiologists to a more central process, ix) Hiring a certified public ergonomist to evaluate the department's workstations can ease radiologists' repetitive stress symptoms and contribute substantially to productivity. Despite accelerating advances in technology, many interface tools have changed little since the introduction of PACS, and finally x) Like business continuity, disaster recovery can prevent a painful experience from becoming fatal. Many hospitals opt for either redundant servers, cloud storage or both. At the very least, preparation for downtime can spare physicians and patients from experiencing significant losses. To minimize the consequences of the listed 10 main problems, this project (in early stage) targeting potential customers among the owner of the small private clinics where the numbers of patients is less and the bureaucracy of the administration is limited.

Providing eligibility, efficacy and security evaluation by quantitative and qualitative disease findings, medical imaging has become increasingly important in clinical trials. Here, subject’s data is today captured in electronic case reports forms (eCRFs), which are offered by electronic data capture (EDC) systems. However, integration of subject’s medical image data into eCRFs is insufficiently supported. Neither integration of subject’s digital imaging and communications in medicine (DICOM) data, nor communication with picture archiving and communication systems (PACS), is possible. This aggravates the workflow of the study personnel, in special regarding studies with distributed data capture in multiple sites. Hence, in this work, a system architecture is presented, which connects an EDC system, a PACS and a DICOM viewer via the web access to DICOM objects (WADO) protocol. The architecture is implemented using the open source tools OpenClinica, DCM4CHEE and Weasis. The eCRF forms the primary endpoint for the study personnel, where subject’s image data is stored and retrieved. Background communication with the PACS is completely hidden for the users. Data privacy and consistency is ensured by automatic de-identification and re-labelling of DICOM data with context information (e.g. study and subject identifiers), respectively. The system is exemplarily demonstrated in a clinical trial, where computer tomography (CT) data is de-centrally captured from the subjects and centrally read by a chief radiologists to decide on inclusion of the subjects in the trial. Errors, latency and costs in the EDC workflow are reduced, while, a research database is implicitly built up in the background.

4 - Digital Imaging and Communications in Medicine

INTRODUCTION Over the years, the number of patients undergoing radiological examinations has increased tremendously, concomitant with the growing concern regarding the long-term risks of cancer arising from ionising radiation exposure. Consequently, more attention has been focused on the levels of radiation doses received by patients. Large-scale dose surveys have been performed to assess the radiation doses from radiological examinations. A survey carried out in the UK in the early 1980s showed that the average doses from similar radiographic examinations could vary by up to seven times between different hospitals and up to 100 times between hospitals and that radiation doses could vary by up to 100 times between patients.[1] In many instances, the doses were higher than what was necessary to produce an image quality sufficient enough to make a diagnosis. Since the findings of these dose surveys were publicised, more emphasis has been placed on the need to optimise imaging conditions to minimise the risk to patients from radiation exposure.[2] The results of these and similar surveys had formed the basis of recommendations for the levels of dose quantities surveyed. These recommendations were referred to in diverse terms such as guidance levels, exposure guides, guideline doses, reference doses, and in 1996, the International Commission on Radiological Protection (ICRP) introduced the term 'diagnostic reference levels (DRLs)' in their recommendations.[3] Since the publication of this document in 1996, many countries have established national DRLs for various imaging modalities. The latest guidance on DRLs from the ICRP was released in 2017.[4] In 1999, the European Commission issued guidance on the establishment of DRLs in its directive on radiation protection, and these recommendations have been updated regularly since then.[5] DRLs are dose levels for typical imaging examinations that are determined from groups of standard sized patients and these imaging examinations are performed on broadly defined types of equipment. Also, DRLs have been recognised to be an effective means to indicate whether, in routine conditions, the dose to a patient in a specified radiological procedure for medical imaging is unusually high or low. Currently, there are no national DRLs for Singapore or recommended DRLs at our institution. Therefore, we conducted an institutional dose study to determine the typical radiation doses and DRLs for selected imaging examinations or procedures performed in our institution. We also compared our typical radiation dose levels and DRLs with those published for similar imaging practices, which serves to provide a broad indication of our institution's relative performance in terms of radiation dose. Importantly, establishing our baseline dose levels and DRLs will also enable benchmarking with other institutions and the worldwide literature, so that dose improvement processes may be implemented where necessary. METHODS The survey on radiation doses from imaging examinations was reviewed and approved by the hospital's Institutional Review Board. The dose data was collected retrospectively from the examination databases of a picture archiving and communication system (PACS). A sample size of about 100 patients (on average) was used for each selected radiographic examination. As the radiation dose for an X-ray examination is dependent on the size of the patient, it is essential to have some criteria to control the patient size if the number of patients in a sample (from which data are collected) is limited. For this dose survey, we achieved this by using dose data from patients with weights restricted to a range of 50–80 kg. The radiographic examinations or procedures selected for the dose survey were: (a) abdomen anteroposterior (AP); (b) ankle two views; (c) chest posteroanterior (PA); (d) chest lateral (lat); (e) cervical spine AP; (f) cervical spine lat; (g) thoracic spine AP; (h) thoracic spine lat; (i) lumbar spine AP; (j) lumbar spine lat; (k) elbow two views; (l) knee two views; (m) pelvis AP; and (n) shoulder AP and lateral scapula view. After each radiographic examination, the X-ray images will be transferred to PACS in the Digital Imaging and Communications in Medicine (DICOM) format. The DICOM medical image consists of two components: a header and the actual image.[6] The header consists of data that describe the image, the critical data being patient information and the dose quantity recorded for radiation exposure. We have chosen to collect dose data from the selected DICOM studies to perform the dose survey. The dose quantity surveyed should be easily available and preferably the one that directly evaluates the radiation that the patient is exposed to during the examination.[4] In our institution, air kerma–area product (PKA) meters are installed in all digital radiography (DR) rooms, and thus, PKA was the dose quantity collected for this survey. An illustration of PKA measurement is presented in Figure 1. This quantity is quoted in units of Gray square centimetre (Gy cm²); it assesses the amount of radiation (measured in Gray) and the area to which it is delivered (measured in square centimetre).Figure 1: Air kerma–area product PKA measurement.RESULTS Based on the 1992 recommendations of the Institute of Physical Sciences in Medicine/National Radiological Protection Board/College of Radiographers, a survey for a radiographic examination in an X-ray facility should generally involve collection of data on the dose quantity for at least 20 patients to achieve sufficient accuracy in the results.[7] In this dose survey, the average sample size for the various examinations was 109. Age of the selected patients ranged from 17 to 94 years. The results of the dose survey and the 75th percentile values of the dose distributions are presented in Table 1. Data from a dose survey could be used to develop institution DRL for a group of examination rooms or imaging facilities. In surveys where several examination rooms or facilities are involved, having the institution DRL value fixed at the 75th percentile of the dose distribution will help us to consider if more attention is required for optimisation of the radiation dose and to identify which X-ray units require this optimisation.Table 1: Median and 75th percentile doses.DISCUSSION In the current study, PKA was the ideal dose quantity collected, especially for radiography and fluoroscopy, as all the X-rays incident on the patient can be assessed by the PKA meter. The assumption is that the X-ray beam to the patient will be collimated aptly. Since both the X-ray beam size and the air kerma will determine the values of PKA, all factors that could influence patient dose during an examination have been considered. In an X-ray system installed with a PKA meter or where PKA is calculated, this dose quantity is easily available. As the PKA values are based on actual radiographic projections, these data from imaging examinations will provide DRL quantities that are closely related to clinical practice. However, we should note that if the X-ray beam passes through the patient table before exposing the patient, the PKA values will be influenced by beam attenuation by the table. Although the PKA values (evaluated by the meter or calculated by the system) reported in the DICOM header are readily available, we should always verify the accuracy of these values before a survey. The values of PKA may be considerably higher than those appearing on the DICOM header unless these values have been verified periodically. The ICRP has recommended that a procedure should be set up to calibrate the PKA meters and verify the accuracy of PKA displayed by the imaging system, before the readings are recorded in the DICOM radiation dose structured report.[4] The report was developed to record and store all information on each irradiation event that are related to the radiation dose received by the patient. For irradiation-based imaging modalities, this information will include the radiation dose from projection X-ray, computed tomography and radiopharmaceutical administration in nuclear medicine. Before this dose survey, we checked the accuracy of the PKA meters in the DR rooms during quality assurance testing of these systems. There are no established national DRLs for imaging examinations in Singapore. Therefore, we compared our results with the DRLs of the UK and Republic of Ireland, and with the most common values of DRLs from the European Union (EU) member states in terms of PKA.[8,9] The most common values of DRLs are published in the European Union document, Radiation Protection No. 180.[10] Compared to these published figures, our median and 75th percentile values from the dose survey were all demonstrably lower. Figure 2 shows the comparison of DRLs (75th percentile values) from the UK, Republic of Ireland, European Union and our dose survey. We also compared the median DRLs from our dose survey with those from the Republic of Ireland [Figure 3].Figure 2: Graph shows outcome of 75th percentile of survey as referenced to published diagnostic reference levels. AP: anteroposterior, DRLs: diagnostic reference levels, EU: European Union, Lat: lateral, PA: posteroanterior, UK: United kingdom, Y: lateral scapulaFigure 3: Graph shows comparison of dose survey median vs. Irish national median. AP: anteroposterior, Lat: lateral, PA: posteroanterior, Y: lateral scapulaThe current UK DRL is based on their 2010 national dose review, where 65% of the observed PKA doses were acquired from the computed radiography (CR) systems and only 32% from the DR (flat panel detector) systems.[11] The remaining 3% came from the systems using film screen (FS). This review also showed that the doses for DR systems were lower compared to the CR systems and the FS systems. The most common values for DRLs from the European Union were released in 2014. Hence, these values were acquired from a mixture of DR, CR and FS systems. Even for the Irish national DRLs that were released in 2021, only 79% of the surveyed facilities used the DR systems, 8% of the facilities used a combination of DR and CR systems and the remaining 13% of the facilities were using the CR systems. Our results, which are based entirely on DR systems, are therefore, lower than these DRLs. Another factor contributing to our lower DRLs is the difference in patient weight. The weight range for these international DRLs was around 70 ± 15 kg compared to our weight range of 50–80 kg. Performing a dose survey required considerable time and effort to manually collect the dose data and determine the typical (median) doses and DRLs for selected imaging examinations. After conducting the dose survey, we realised that a patient radiation dose monitoring system will improve the collection, analysis and reporting of radiation dose data compared to the current manual method. Having a patient radiation dose monitoring system installed in our institution will enable us to collect, monitor and analyse the radiation dose received by to our patients, and to create DRLs for imaging examinations in a largely automated way. With the advantage of more data from the imaging examinations, it will render assessment of radiation doses a lot easier and more accurate. The established dose values will also be more precise. The detailed information provided by dose monitoring software will allow us to optimise the image quality while minimising radiation exposure to the patient. Overall, the radiation doses obtained in this study were lower compared to the published DRLs of other countries around the world. As the imaging procedures are being optimised and improved, and as advances are being made in the imaging technology, the radiation dose received by patients for radiological examinations is projected to drop progressively. Hence, the DRL values should be reviewed regularly.[4] Countries with established DRLs had conducted reviews of radiation doses every 3–5 years, but this interval between the dose surveys will depend on the availability of the required manpower to undertake these surveys, the introduction of new hardware or software for imaging procedures, consistency of the survey results and participation of the imaging facilities in these countries. Financial support and sponsorship Nil. Conflicts of interest There are no conflicts of interest.

Introduction/ Background In recent years different technological solutions have emerged for the scanning or digitization of histological and cytological slides in pathology, from several manufacturers. High resolution scanning is usually based in tile (small fragment) or stripes (longitudinal areas) that are combined or stitched together to create a high magnification (usually equivalent to 20x to 40x magnification) global image. Thus, a large digital slide can be displayed using specific viewers to simulate the functions of a conventional microscope. A pyramid of images is a common solution. But each scanner manufacturer optimizes the process of collecting, managing and storing images in its own format, making difficult the interconnection between systems and the ability to share images between different formats, and, generally a heavy process of image conversion and a loss of information is needed. Aims The objective is to present the process performed on proprietary image formats of histological and cytological slides in pathology to convert them the be compliant with the Digital Imaging and Communication in Medicine (DICOM) standard, according to 145 and 122 supplements, and their subsequent storage in a Picture Archiving and Communication System (PACS). Methods Python was chosen as programming platform due to its versatility and available tools. Furthermore, for future projects, Python can be used to apply signal analysis on digital images. A Pentium Core i3 4GB RAM, 1TB server with Ubuntu 14.04.3 LTS Server was used. In the server, a developer platform Eclipse Version 3.8.1 allowed the installation of PyDev for Eclipse 4.3.0 and Eclipse Jgit 1.3.0 plugins. It has been connected to a Github repository to manage developing versions. The solutions has been structured into a Python package to obtain images coming from proprietary images to be standardized to an image compliant with DICOM supplement 145, and sending them to the PACS. Results In order to test compatibility, David A. Clunie’s dicom3tools was used. This allowed verification of all Tags of the generated files, indicating those who are required according to each image, and also it offers information of those tags where included data does not match the standard and those with values that do not correspond to that standard. This tool helped to finally obtain a result of 0% errors in all generated files. Regarding storage tests, two different PACS were used. First, in collaboration with T-systems Company, an open source dcm4chee DICOM Archive 2 (dcm4che.org), and second, in collaboration with IRE Rayos X company, a commercial IRE Store Channel 4.3 was also used in several tests. After some tests with commercial and open source PACS, we could obtain the following conclusions: In the negotiation phase, the PACS did not recognize the predetermined configuration stated in supplement 145. The solution was changing SOP to “VL Microscopic Image Storage”. Each level of the pyramid will be stored as an instance inside the same series, and each tile as a frame inside a multi-frame object. The dcm4che.org PACS offers a WADO service that allows accessing each frame separately, inside the same object, which can be useful for the implementation of slide viewers in pathology. Acknowledgment: This work has been supported by the AIDPATH project, an EU 7FP IAPP Marie Curie action, contract number 612471

The picture archiving and communication system (PACS) originated as an image management system for improving the efficiency of radiologic practices. It has evolved into a hospital-integrated system that stores information media in many forms, including voice, text, medical records, waveform images, and video recordings. The integration of these various types of information requires the technology of multimedia, including hardware platforms, information systems and databases, communication protocols, display technology, and system interfacing and integration. The purpose of this book is to discuss the conceptual and technologic advances in PACS development for all of these previously mentioned technologies. The book also emphasizes the growing field of PACS-based imaging informatics, where existing PACS resources are used for largescale horizontal and longitudinal clinical service, research, and education applications. The book is intended for those who are involved in a health care environment that manages the everyday practical realities of PACS planning, operation, and maintenance. The book will also serve as excellent curriculum material for the training of PACS information technology personnel because the author provides comprehensive concepts that tie medical imaging, medical physics, information technology, and clinical workflow with enterprise PACS (multiple, hospital-wide PACS). The author, H. K. Huang, has been involved in PACS development since the 1980s and is a leading scientist in the field. The book is divided into five parts and 23 chapters. Part 1, titled “Medical Imaging Principles,” summarizes the history of PACS, the fundamental concepts of digital medical imaging, and the different types of modalities integrated into PACS. Part 2, titled “PACS Fundamentals,” describes in detail the PACS subsystems and industry standards (Digital Imaging and Communications in Medicine and Health Level 7) that are used to integrate PACS with the hospital information system and radiology information system. Part 3, titled “PACS Operation,” describes the practical problems encountered by PACS administrators and users and discusses different techniques to solve these problems, with many examples from installed PACS sites around the world. Because the author developed PACS at the University of California, Los Angeles, in 1991 and the University of California, San Francisco, in 1995, he is able to draw from his expertise on the subject. The author also uses his experience from developing many state-of-theart prototypes (eg, fault tolerant storage system) funded by research grants. Part 4, titled “PACS-based Imaging Informatics,” presents image-processing techniques that can be used to mine the huge image and clinical data resources stored in the PACS archive. The analysis of lung nodules by using temporal computed tomographic and contentbased image indexing are some of the examples of advanced processing applications applied to PACS data mining. Part 5, titled “Enterprise PACS,” describes different models for implementing an enterprise PACS in terms of the architectural design of the system and financial and business models. This new book builds on two previous volumes on PACS that were written by the author. The text, image collections, and schematic diagrams in this current work achieve the author’s goal of providing up-to-date material concerning the technologic advances in PACS and imaging informatics. The text serves as a guide for those who are planning an enterprise PACS and provides teaching material for training PACS developers in industry and health care. The author has used portions of this book as lecture material for graduate courses at leading universities in the United States and abroad. The author also uses many examples to emphasize that the integration of heterogeneous health care information systems is becoming more complex and that, as more radiologists and clinicians expect higher standards in the reliability of the data, a systemic understanding of Digital Imaging and Communications in Medicine, Health Level 7, and Integrating the Healthcare Enterprise becomes ever more important to optimize enterprise workflow. The strength of the book lies in the vast experience that the author, who has implemented PACS at numerous institutions in the United States and abroad, has transmitted into this new book. Huang has conducted first-hand analysis of the various systems from PACS manufacturers that are used in clinical operation at large medical institutions and has performed up-to-date research in data mining of the huge image and data resources stored in the PACS repository.

In recent times, technological advancements have remarkably improved picture archiving and communication system(PACS) capabilities beyond their conventional use in radiology departments. Researchers and instructors have started employing PACS functionalities to improve medical research processes, promote interdisciplinary collaborations, and facilitate learning. To illustrate this point further, the PACS enables researchers to handle and analyze huge amounts of imaging data with superior precision and speed, supporting innovative studies in areas like disease progression, treatment outcomes, and imaging modalities. Moreover, a PACSintegrated with artificial intelligence (AI) algorithms leads to significant improvements in image processing, diagnostic accuracy, and personalized treatment, thus marking a new approach to medical imaging. The PACSsupported by AI is mostly transformative since they allow for improved early disease detection capabilities as well as automated image processing and decision assistance, which increase diagnostic accuracy and clinical outcomes. Such systems can rapidly process large quantities of visual data with an accuracy rate surpassing earlier endeavors. In medical research, however, combining PACSwith AI allows challenging imaging datasets to be examined, thereby making findings that were not previously possible. The capacity to combine imaging outcomes with clinical information is valuable for medical students and professionals in the field of education. They can access extensive medical image collections and case studies using PACS. This link is critical for teaching and learning as it allows students to interact with concrete events and improve their diagnostic accuracy in a controlled environment. This review discusses how the PACS affects educational courses and clinical outcomes based on the available literature. Our aim was not only to outline recent research or developments but also to present a comprehensive overview regarding the growing role played by PACS in the modern healthcare system and academics. Similarly, we look at the challenges and opportunities associated with the wide adoption of PACS, highlighting possible future areas of study or teaching methodologies. Issues such as data security, interoperability, and the need for defined protocols are included to give an exhaustive understanding of what PACS can and cannot do. Through this study, we stress PACS's revolutionary potential in advancing research methodology and educational practices, eventually contributing to enhanced patient care and knowledge dissemination in healthcare areas. The continual growth of PACS technology and its applications is expected to reshape the landscape of medical research and education, making it a vital component in the quest for medical excellence. By knowing the present trends and future potential, stakeholders in healthcare and education may better employ PACS to reach their objectives and boost overall results.

This study presents a software technology to transform paper-based 12-lead electrocardiography (ECG) examination into (1) 12-lead ECG electronic diagnoses (e-diagnoses) and (2) mobile diagnoses (m-diagnoses) in emergency telemedicine. While Digital Imaging and Communications in Medicine (DICOM)-based images are commonly used in hospitals, the development of computerized 12-lead ECG is impeded by heterogeneous data formats of clinically used 12-lead ECG instrumentations, such as Standard Communications Protocol (SCP) ECG and Extensible Markup Language (XML) ECG. Additionally, there is no data link between clinically used 12-lead ECG instrumentations and mobile devices. To realize computerized 12-lead ECG examination procedures and ECG telemedicine, this study develops a DICOM-based 12-lead ECG information system capable of providing clinicians with medical images and waveform-based ECG diagnoses via Picture Archiving and Communication System (PACS). First, a waveform-based DICOM-ECG converter transforming clinically used SCP-ECG and XML-ECG to DICOM is applied to PACS for image- and waveform-based DICOM file manipulation. Second, a mobile Structured Query Language database communicating with PACS is installed in physicians' mobile phones so that they can retrieve images and waveform-based ECG ubiquitously. Clinical evaluations of this system indicated the following. First, this developed PACS-dependent 12-lead ECG information system improves 12-lead ECG management and interoperability. Second, this system enables the remote physicians to perform ubiquitous 12-lead ECG and image diagnoses, which enhances the efficiency of emergency telemedicine. These findings prove the effectiveness and usefulness of the PACS-dependent 12-lead ECG information system, which can be easily adopted in telemedicine.

Since May 2002, temporal subtraction and nodule detection systems for digital chest radiographs have been integrated into our hospital's picture archiving and communication systems (PACS). Image data of digital chest radiographs were stored in PACS with the digital image and communication in medicine (DICOM) protocol. Temporal subtraction and nodule detection images were produced automatically in an exclusive server and delivered with current and previous images to the work stations. The problems that we faced and the solutions that we arrived at were analyzed. We encountered four major problems. The first problem, as a result of the storage of the original images' data with the upside-down, reverse, or lying-down positioning on portable chest radiographs, was solved by postponing the original data storage for 30 min. The second problem, the variable matrix sizes of chest radiographs obtained with flat-panel detectors (FPDs), was solved by improving the computer algorithm to produce consistent temporal subtraction images. The third problem, the production of temporal subtraction images of low quality, could not be solved fundamentally when the original images were obtained with different modalities. The fourth problem, an excessive false-positive rate on the nodule detection system, was solved by adjusting this system to chest radiographs obtained in our hospital. Integration of the temporal subtraction and nodule detection system into our hospital's PACS was customized successfully; this experience may be helpful to other hospitals.

Picture archiving and communication systems (PACS) require high- speed networks to transmit large image files between components. While transmitting data through public networks, privacy, authenticity, and integrity have always been some critical problems. Recent years, IPv6 brings significant improvements in mechanisms for assuring a higher level of security. In this pa- per, we first analyzes how actual security threats and different types of attacks affect IPv6 networks while transmitting Digital Imaging and Communications in Medicine (DICOM) files through the public Internet. Second, illustrate some shortcomings of IPv6 and IPv6's traffic loads. Finally, one possible solution against the security threats in IPv6 DICOM files transmitting networks has been given.

ObjectivesTo present an adapted Clinical Trial Processor (CTP) test set-up for receiving, anonymising and saving Digital Imaging and Communications in Medicine (DICOM) data using external input from the original database of an existing clinical study information system to guide the anonymisation process.MethodsTwo methods are presented for an adapted CTP test set-up. In the first method, images are pushed from the Picture Archiving and Communication System (PACS) using the DICOM protocol through a local network. In the second method, images are transferred through the internet using the HTTPS protocol.ResultsIn total 25,000 images from 50 patients were moved from the PACS, anonymised and stored within roughly 2 h using the first method. In the second method, an average of 10 images per minute were transferred and processed over a residential connection. In both methods, no duplicated images were stored when previous images were retransferred. The anonymised images are stored in appropriate directories.ConclusionsThe CTP can transfer and process DICOM images correctly in a very easy set-up providing a fast, secure and stable environment. The adapted CTP allows easy integration into an environment in which patient data are already included in an existing information system.Key PointsStore DICOM images correctly in a very easy set-up in a fast, secure and stable environmentAllows adaptation of the software to perform a certain task based on specific needsAllows easy integration into an existing environmentReduce the possibility of inappropriate anonymisation