Category: DICOM

Categories
DICOM

Benefits and Challenges of AI-powered Medical Image Analysis

In our previous blog post, we explored six pivotal medical imaging trends shaping the future of healthcare. Today, we dive deeper into one of the most game-changing developments – AI-powered medical image analysis. 

The Transformation of Medical Imaging through AI

Over the past decades, medical imaging has undergone remarkable advancements. Now, artificial intelligence (AI) is taking it to an entirely new level. Imagine a world where early disease detection is faster and more accurate, where real-time clinical decisions can be made seamlessly, and clinical trials are more effective than ever before. With AI-driven medical imaging solutions, this future is not just a dream; it is becoming a reality.

While the benefits are clear, the road to widespread AI adoption is not without hurdles. Questions around data quality, interpretability, regulatory compliance and workflow integration remain major challenges. 

How can AI support clinical decision-making or clinical research without compromising patient safety? How can ClinFlows help integrate AI into existing imaging processes?   

Let’s take a closer look at the opportunities and challenges of AI-powered medical image analysis.

Benefits of AI in Medical Imaging

The integration of AI into medical image analysis provides numerous advantages: 

  • Consistency and Objectivity: AI algorithms can enhance image quality, reconstruct high-resolution images and integrate multiple imaging modalities. Standardization minimizes subjectivity in image assessments, delivering reproducible clinical data analyses. 
  • Speed and Cost Effectiveness: AI can perform repetitive tasks, such as image processing, significantly faster than traditional methods. This saves both time and costs, enabling real-time decision-making in clinical settings and accelerating patient-eligibility checks in clinical trials. 
  • Personalized Medicine: By merging imaging data with patient history and genetic profiles, AI empowers healthcare professionals to tailor treatment plans. This paves the way for more personalized and effective healthcare solutions.  

Challenges of AI in medical imaging 

Despite its promising potential, AI in medical imaging faces several challenges:

  • Bias in training data: According to Armato et al (2023), AI models are only as reliable as the datasets they learn from and not all imaging data is suitable for AI analysis. Insufficiently diverse or high-quality data can introduce biases that result in misdiagnosis, incorrect treatment plans or unreliable trial outcomes.  
  • Interpretability: Clinicians may find it difficult to put full trust in AI findings due to a lack of transparency in how these tools arrive at conclusions. Without clear explanations and human review mechanisms, validating AI outputs becomes a significant hurdle.
  • Regulatory Compliance: Particularly in Europe, strict regulations for data governance exist such as GDPR and the EU AI Act. AI developers must adopt robust validation processes and mitigation strategies, to safeguard patient data against risks like cyberattacks and data breaches. 
  • Workflow integration: Incorporating AI-powered imaging tools into existing clinical workflows can be challenging. Concerns over job displacement for radiologists, medical staff and central readers persist, and the technical integration of multi-component systems requires careful planning and execution

Conclusion: Embracing AI for a Smarter Future in Medical Image Analysis  

AI-driven image analysis is revolutionizing healthcare, offering enhanced speed, accuracy and efficiency in clinical workflows and trials. From faster diagnosis to precise treatment planning, AI streamlines clinical processes, minimizes human errors and enhances real-time decision-making.  

However, to fully unlock AI’s potential, the industry must address critical challenges such as data bias, regulatory compliance, and clinical integration. 

At ClinFlows, we bridge the gap between AI technology, researchers and healthcare professionals. Our secure, regulatory-compliant decidemedical platform serves as a HUB, enabling the seamless transfer, preview and quality control of medical images from dispatched clinical sites to AI-powered analysis tools. Through our integrated, web-based smart uploader, specific imaging datasets can be selected, anonymized and sent for image analysis uniquely tailored to certain pathologies and imaging modalities. In our understanding, ensuring the right AI tool meets the right data is key to unlocking AI’s full potential. 

By embracing new technologies, responsible innovation, collaboration and continuous refinement of AI applications, we can create a future where AI enhances—not replaces—human expertise, leading to better patient outcomes and groundbreaking medical advancements. 

Want to explore more medical imaging trends? Stay tuned for our next blog post. 

Categories
DICOM Non classé

Medical Imaging: Six Trends Shaping the Future of Healthcare

Medical imaging is transforming, pushing the boundaries of healthcare with technological innovations at its core. Advancements in AI-driven imaging, hybrid imaging, and functional or molecular imaging, to name just a few, are redefining diagnostics, personalized medicine and patient care.

At ClinFlows, we actively facilitate the exchange of medical images and clinical data through our software solutions and closely follow new developments in medical imaging technologies. How do these advancements impact healthcare providers, researchers, and the industry? Below we present six key trends of medical imaging technologies, focusing on real-world applications and their transformative potential. 

Trend 1

Smarter Image Analysis through AI and Machine Learning

Nowadays, healthcare providers and life science companies make increasingly use of Artificial intelligence (AI) and machine learning (ML). Among others, AI-powered tools can automate the processing and analysis of medical images. Often, they reveal patterns that otherwise be overlooked – a clear win for diagnostics, patient-specific product design, clinical decision-making, and monitoring of the disease’s progression.

One possible application is Transcatheter Aortic Valve Replacement (TAVR). In this example, AI-based software solutions automatically segment medical scans (CTs or MRIs). They provide 3D or 4D visualizations and precise anatomical measurements of the heart supporting the work of healthcare professionals.

Trend 2

Clinical Cloud Integration and Digital Transformation

Digital transformation and integration of cloud technology into clinical projects are growing. They facilitate seamless data exchange, enable remote clinical decision-making and collaboration between healthcare professionals, researchers, and industry. 

Centralized access to imaging data is available via cloud-based platforms like decidemedical. It allows medical experts to review patient cases for clinical trials or daily medical care at any time and from anywhere. For instance, if a doctor needs to know the patient’s eligibility, or determine a certain implant size for pre-operative planning, he can send medical images online to another expert. The expert then quickly provides a second opinion on the patient’s case.

Trend 3

Personalized Medicine enhanced by Molecular Imaging and Theranostics

Molecular imaging provides real-time insights into cellular activity, allowing early and precise disease detection and the development of personalized treatments. The field continues to develop strongly through technological advances. These include higher sensitivity of PET/CT scanners and radiopharmaceuticals that combine diagnostics with targeted therapy. 

A leading example of theranostic or theragnostic treatment is Lutetium-177 PSMA Therapy for prostate cancer. It integrates PSMA (Prostate-Specific Membrane Antigen) PET imaging with radioligand therapy (RLT). This method delivers radiation directly to cancerous cells and reduces harm to healthy tissues. It maximizes treatment efficacy. This demonstrates how molecular imaging and theranostics are shaping better patient outcomes. 

Trend 4

Functional Imaging Enabling Structural Analysis

Medical imaging is no longer just about anatomy – it’s about physiology. Functional or physiological imaging enables clinicians to analyze organ activity, blood flow and cell metabolism, leading to valuable insights for research and clinical practice.  

Take Fluorodeoxyglucose (FDG) or Fibroblast activation protein inhibitor (FAPI) PET/CT scans as examples. In oncology, both cutting-edge techniques allow more informed treatment decision-making. FDG accumulation in metabolically active tumor cells or FAP expression in cancer-associated fibroblasts allow tumor visualization, metastasis detection, and treatment response monitoring in conditions like lymphoma, lung and breast cancer to mention a few. 

Trend 5

Hybrid Imaging for Greater Precision 

Why settle for one imaging technique when you can have two? Hybrid imaging merges scans from multiple modalities into a single comprehensive view.  

One well-known method is PET/MRI. It combines PET’s metabolic and molecular insights with MRI’s detailed soft-tissue contrast. In neurodegenerative diseases like Alzheimer’s, this technology is proving invaluable. It helps to detect amyloid plaques, assess brain atrophy, and evaluate treatment efficacy. 

Trend 6

Intelligent Assistance for Surgery via Image-Guided Robotics

Image-guided navigation is revolutionizing modern surgery. Clinicians use pre- and intraoperative imaging with robotic instruments. This combination allows them to perform surgical procedures with greater accuracy leading to better results.  

Let’s take iMRI-guided neurosurgery for the resection of brain tumors as an example. Before surgery, the patient’s brain is scanned using MRI to create a 3D map. This map is transferred to the robotic system and used during surgery in combination with intraoperative MRI imaging to track tumor removal and adjust the surgical approach if necessary. 

Conclusion

Imaging the Future of Healthcare 

The rapid evolution of medical imaging technologies is improving diagnostics, treatment planning, and personalized medicine. But more importantly, it is revolutionizing patient care. Unlocking their full potential enables earlier disease detection, more targeted therapies, and true precision medicine.   

However, associated challenges like costs, patient risks, accessibility, and regulatory compliance must also be addressed.

At ClinFlows, we are at the forefront of medical image exchange. We ensure that medical data reaches the right experts – taking regulatory requirements for information security and privacy into account. By leveraging cloud integration and customized imaging workflows, we help to bridge the gap between technology and real-world clinical applications.   

Are you curious about what’s next?   

Stay tuned for the second part of our blog post. We will dive into challenges and opportunities of the above trends and explore how they will shape the future of modern medicine. 

Categories
clinical decision support DICOM Products

Medical Devices vs. Drugs: ClinFlows is your provider for medical image exchange in clinical trials

Medical Devices vs. Drugs

The clinical trial landscape for new medicines and medical devices continually expands. Working with a software provider that has extensive experience in this area is becoming increasingly important for sponsors and clinical research organizations (CROs).  Although similar goals are shared, there are inherent differences between clinical trials for the two product types.

Regulatory requirements, clinical study designs, and the on-site team composition reflect this disparity, making drug trials typically longer and more complex than device trials. In this blog post, we’ll explore the key distinctions and show you how ClinFlows can support you along the way by simplifying complex study workflows, especially concerning medical imaging and data exchange.

Medical Devices vs. Drugs - Clinflows

Navigating the Regulatory Maze

Pharmaceuticals: A Rigorous Approval Process

In the United States, market approval for medicines is regulated by the Center for Drug Evaluation and Research (CDER) of the Food and Drug Administration (FDA). After extensive clinical studies, manufacturers submit a New Drug Application (NDA) or Biologics License Application (BLA). This process ensures that new medicines are safe and effective for public use.

In Europe, the responsible regulatory authority is the European Medicines Agency (EMA). In collaboration with National Competent Authorities (NCAs) drugs are approved centrally or through national regulatory routes, depending on the market entry strategy chosen by the manufacturer.

Despite both regions demanding rigorous testing and post-market monitoring, the structure and execution of these regulations differ, impacting timelines and complexity.

Medical Devices: Risk classification is key

For manufacturers of medical devices, it is a different situation. Here, the regulatory focus shifts to a detailed examination of engineering, mechanical function, and the device’s performance (efficiency) in the body.

Unlike pharmaceuticals, medical devices are categorized by risk classes:

  • Low- to Moderate-Risk Devices: Class I/II in the USA and Class I/IIa in Europe. Comparable data are often available for these devices, potentially bypassing the need for clinical investigations.
  • High-Risk Devices: Class III devices, in the USA, and Class IIb/III devices, in Europe, require more extensive scrutiny.

In the United States, the FDA’s Center for Devices and Radiological Health (CDRH) manages market authorizations of high-risk devices through a Premarket Approval (PMA). For low-risk devices, the 510(k) process is utilized.

In Europe, the Medical Device Regulation (MDR 2017/745) mandates clinical investigations for all Class IIb/III devices with Notified Bodies assessing data for CE marking.

Medical Devices vs. Drugs - usa
Medical Devices vs. Drugs - Europe

Clinical Trials: Different Paths to Market

Pharmaceuticals: Standard Progression through Phase 1-3

Clinical drug trials are highly structured and typically follow these phases:

  1. Phase I: Evaluates safety and dosage in a small group of healthy volunteers.
  2. Phase II: Explores efficacy and side effects in a larger patient group with the target condition.
  3. Phase III: Confirms effectiveness, monitors side effects, and compares the drug to commonly used treatments in large populations.

Drug development can often take up to 10+ years, with a few exceptions, such as specific fast-track or orphan drug designations. The long timelines are mainly caused by the extensive clinical testing required and the fact that manufacturers cannot speed up the process by risk classification and clinical equivalent data of existing therapies.

Medical Devices: A More Flexible Approach

  • Pilot Studies: Evaluate safety and functionality in a small group of patients
  • Pivotal Studies: Confirm safety and efficiency in a larger patient population, akin to Phase III in pharmaceuticals.

Bringing a medical device from concept to approval takes approximately 3 to 7 years.

Phase IV: Ongoing Surveillance for Both

Phase IV refers to post-market surveillance studies to continuously monitor the product’s safety and efficacy or performance in the general population. Both pharmaceuticals and medical devices engage in this crucial phase to ensure long-term patient protection.

The Stakeholders on-site: Who’s Involved?

Behind every successful clinical trial is a dedicated team of professionals on-site:

  • Investigators: In pharmaceutical trials, investigators are usually physicians with extensive expertise in a specific therapeutic area. In medical device trials, investigators can also be surgeons, specialized clinicians, or technical experts.
  • Clinical Research Coordinators and Study Nurses: Manage daily study operations, patient coordination, and data collection.
  • Technical Staff: Certain clinical investigations require medical imaging staff on site for DICOM data collection and image-based patient eligibility checks. Additionally, device trials, often involve highly trained technicians and programmers to set up, maintain, and calibrate devices. In drug trials, there is no need for this technical expertise.

Understanding the different team compositions and tasks on-site in drug and medical device trials can enhance collaboration between sponsors, CROs, and software providers and help to efficiently manage your clinical workflows.

How ClinFlows Can Simplify Your Clinical Study?

When it comes to medical imaging, ClinFlows is your trusted partner.

In early-phase trials, patient data and medical images (DICOMs) need to be reviewed to determine eligibility.  We provide you with the necessary tools to quickly and safely exchange this information with other stakeholders, for second opinions and/or screening reviews. You can ensure that the right patients participate in the trial while saving great time and travel expenses.

Do your projects involve central imaging reads? Then quality checks of images, timely communication, and data handling between different electronic systems can sometimes be a challenge. With almost 15 years of experience, we know about the particularities of medical image exchange in clinical drug and medical device trials. We can tailor our online solutions to your specific needs, making complex workflows easily manageable.

Ready to optimize your clinical trials? Contact ClinFlows today to discover how we can assist with medical imaging and data exchange.

Categories
clinical decision support DICOM dicomdrop GDPR Products

How to Use dicomdrop: Secure and Convenient Transfer of Medical Images in DICOM Format

Due to increasing interdisciplinary cooperation between medical specialists and the digitalization of healthcare in general, efficiently transferring medical images in DICOM format is crucial, especially in fields like medical device development, clinical research, and physician consultations. This process, however, comes with its own set of challenges, such as ensuring the secure transmission of these files while adhering to stringent data protection laws like the GDPR. In this article, we introduce dicomdrop, an easy-to-use yet powerful, privacy-compliant solution from ClinFlows for the online transfer of medical images.

The era of using physical media, such as CDs or DVDs, for exchanging medical images is fading, especially when data exchanges between physicians or medical experts are needed quickly. Today, the focus is on smarter, digital solutions. DICOM files, which contain both critical image data and sensitive patient information, demand an advanced approach to ensure secure and confidential transfers.

Facing these challenges head-on requires a strategic shift to digital platforms that prioritize security and compliance. While general web-based file-sharing platforms offer convenience for regular, non-regulated data, they are typically not designed to adequately manage DICOM file structures or maintain patient privacy by treating metadata (DICOM tags) which contain patient’s private information. This is where specialized tools like dicomdrop make a significant difference.

dicomdrop: A Tailored Solution for Secure Image Exchange 

dicomdrop is a state-of-the-art, web-based tool designed specifically for the secure exchange of medical images. It facilitates the quick, effortless transfer of DICOM files in a manner that fully complies with data protection regulations. One of its standout features is the ability to anonymize defined DICOM tags, ensuring that only pseudonymized or fully anonymized data sets are exchanged, depending on the need, and provided consent of the patient. Technical and organizational measures, like encryption during data transfer and during the controlled hosting of data, are mandatory prerequisites provided by dicomdrop, in order to meet GDPR requirements.

Choosing dicomdrop means peace of mind, knowing that your medical image transfers are not only secure but also fully compliant with privacy regulations. This eliminates risks associated with unauthorized access to sensitive patient data and ensures adherence to GDPR standards. Still, every data controller dealing with medical images is responsible for obtaining the patient’s consent before sharing their medical information.

Beyond security, dicomdrop excels in project management efficiency. Whether you are collaborating on a research project, seeking expert medical opinions, or involved in medical device development, dicomdrop streamlines your workflow and manages DICOM transfers effectively within your projects. Sponsors or initiators of a clinical project can take care of the payment for the dicomdrop service and invite their participating physicians to use the service within a clinical project.

Here’s how dicomdrop works:

  1. Go to https://dicomdrop.com and register to begin.
  • Receive three complimentary credits for your initial DICOM transfers. Additional credits can be purchased for 5 Euros each.
  • Enter up to 7 recipient’s email addresses.
  • Compress your DICOM folder or CD into a single file (zip) and select or simply drag and drop it onto dicomdrop. The maximum file size is 4 GB.
  • Utilize our integrated anonymization and de-identification features. Choose from “Full Anonymization,” “De-Identification,” or “No Anonymization” to ensure data privacy.
  • Use the CASE ID feature. This ID automatically replaces the patient’s name (DICOM tag 0010,0010), making case tracking very simple. This feature is often used within clinical studies.
  • Click “Send” to initiate the data protection-compliant, real-time transmission of your DICOM data. 

All participants of the transfer are informed by automated email notifications about available data downloads. Data is deleted automatically after 10 days.

Additional Benefits:

  • Create collaborative projects, ideal for clinical studies, especially for investigator-initiated studies.
  • Sponsors can provide credits and invite all project participants.
  • No software installation required; a web browser and internet connection are all you need.
  • Self-explaining and very easy to use.

Curious to see how it can transform your medical image transfer process? Register at dicomdrop.com, claim your free credits, and experience this innovative tool firsthand.

Have further questions or would like a demo? Contact us at info@clinflows.com.

Categories
DICOM GDPR

DICOM explained Part 2: GDPR, Security and Personal Information – The Challenges with DICOM Data

In part 1 of our DICOM explained-series, you already learned that imaging plays an important role in modern medicine and that the focus is on files in DICOM format. You got to know what is behind the abbreviation DICOM, how it is used in healthcare, how a DICOM file is structured and that the DICOM headers and tags contain a lot of personal data. In part 2 of our DICOM series, we will go into detail about the latter and explain what problems the data contained can cause when working with DICOMs in practice.

Of course, it has many advantages that DICOM images contain a lot of technical and personal data (you don’t remember exactly which ones? Then go back and take a look into part 1 of our DICOM explained-series here). However, this is also problematic at the same time: If DICOMs are sent unencrypted by mail on a CD, for example – as it is still regularly done today, e.g., as part of a study or to obtain a second opinion – they can be directly assigned to the patient; and this is, of course, not in compliance with data protection laws. Who would want their neighbor to find out unintentionally that they suffer from a certain illness? Especially since the General Data Protection Regulation (GDPR) came into force in May 2018, there are many discussions and unknowns that lead to uncertainty among clinicians and healthcare workers who work with medical images. There are many aspects to consider, but here we will focus on personal identifiable data in DICOM images and its technical aspects.

DICOM data: Anonymization vs. pseudonymization

In this context, there are two terms that are often misused when talking about privacy protection of medical images. “anonymization” and “pseudonymization.” Anonymization means that there is no way to retrieve or identify the patient if you only have the medical images. Often physicians or study nurses use this term when informing the patient that “all data will be completely anonymized,” for example, in the context of clinical trials or eligibility testing by outside medical experts. However, the recipient of the images, a core lab or central reader, in most cases needs to know the date of the exam and from which location the images were sent, as these identifiers are an essential parameter of the clinical trial or project. Often, the purpose of a clinical project is to obtain a second opinion on a treatment recommendation, meaning it is imperative to match the right patient to the right images and verify the outcome. In these cases, the data is absolutely not anonymous. 

Is that a problem? No. But first, you would have to obtain written consent from a well-informed patient, and second, you would have to make sure that the data processor provides a technical and organizational GDPR-compliant environment. And if data must be shared for such a purpose, one should pseudonymize the data sets as much as possible. Pseudonymization means that identifying information (name, date of birth, etc.) is removed or replaced, reducing the possibility of tracing it back to the patient.

Where can I find personal information in DICOM data?

When viewing medical images with a DICOM viewer, one does not necessarily see the personal information immediately. As described above, a patient’s personal data, but possibly also that of the operator, is part of the well-defined DICOM tags. Viewers can usually make these DICOM headers or metadata visible and even allow them to be edited.

Another source where personal data can be part of the DICOM data are the so-called “burned-in annotations”. The following example shows that the patient’s name and date of birth: As you can see the personal information Max Mustermann, born on 19 August 1938 – don’t worry, this is a fake person – is part of the pixel information and can only be removed with special tools, usually by drawing black boxes over the visible information.

Figure 1: Burned-in annotations in echocardiography

Also, DICOM studies often contain series which hold patient reports or dicomized letters with patient private information. These reports are normally in series marked with modalities like PR, SR or OT.

Depending on the needs of a clinical project, the user must be cautious and decide which information shall be shared or not. Finally, we want to mention, that the reconstruction or 3D rendering of images by an increasing special resolution, can lead to a patient identification. If for example CT or MRI slices of a head from a patient are rendered, the facial features can be reconstructed and allowing the identification of patients.

It’s our article’s objective to increase the awareness of healthcare professionals dealing with medical images and as such with personal patient information or often called Private Health Information (PHI). However, you might be glad to hear, that exchanging does not need to be complicated at all, for example with the use our dicomdrop- and decidemedical-tools.

You would like to learn about different ways to exchange DICOM files? Then stay with us: In part 3 of our DICOM explained-series, we will explain the different options available for DICOM-exchange and will tell you more about their pros and cons.

For more information on our ClinFlows-solutions, visit our website or get in touch via info(at)clinflows.com!

See the article on the new Blog

Categories
Clients decidemedical DICOM

Leading medical device maker chooses ClinFlows’ decidemedical application for complex European clinical trial

A leading medical technology company headquartered in the US, trusts in ClinFlows’ decidemedical solution for its upcoming EU Trial. Via the web-based platform, the complete patient screening process of the study including the subsequent 5-year follow-up phase will be organized and conducted: All medical images (DICOM) and documents will be handed in, reviewed, and evaluated in a GDPR-compliant manner via ClinFlows’ online service.

“We are excited to see this complex exchange of medical images and study documents, within such groundbreaking clinical trial, realized on our decidemedical platform, involving multiple prominent researchers in the cardiovascular space”, says Uwe Gladbach, founder and CEO of ClinFlows.

The online submission and review of required data allows fast turn around times between the study teams, when it comes to subject eligibility checks – also very beneficial for the patients to be treated in a timely manner.

ClinFlows’ decidemedical platform has registered users from 96 countries worldwide and is in use since more than 10 years.

Categories
DICOM GDPR

DICOM explained Part 1: What is DICOM, DICOM Tags and Data Sets?

Imaging techniques play an important role in many areas of modern medicine. This applies to diagnostics and therapy, but also to research, for example, in the context of clinical trials. The most important medical image format is DICOM. 

Within clinical projects, utilizing our ClinFlows’ solutions to exchange medical images, we frequently meet users (physicians, study nurses and coordinators) who are not that familiar with the topic “DICOM”. Time for us as DICOM experts to start a series in which we explain the format and obstacles that come when dealing with it (spoiler: among others, it’s about personal data!).

In the coming time, we will gradually publish articles here in which we explain the most important background and facts about DICOM data. We start today with part 1 of our DICOM explained-series, in which you will learn what is behind the abbreviation, how the DICOM format is structured, what makes it so characteristic and what it is used for in healthcare.

DICOM: the format behind the five letters

JPEG, TIFF, PNG – almost everyone knows these file formats of images. DICOM is also an image format, but it is used primarily in the medical industry. The abbreviation DICOM stands for “Digital Imaging and Communications in Medicine”. The term already makes it clear that the format not only includes the respective image data, the pixels or its storage as a specific file format, but that the DICOM standard includes further information, which we will explain in more detail later. The DICOM standard has its origins in the 1970s, when it was still called the ACR/NEMA standard and was initiated by the American College of Radiology and the National Electrical Manufacturers Association. DICOM as we know it today has only existed since 1992. The use of this image format is intended to facilitate and standardize the exchange of medical image data.

DICOM: Open standard to exchange medical images

The DICOM format is one of the so-called open standards, openly accessible and usable by anyone. This allows many medical professionals in the fields of research and clinical practice, diagnostics and therapy to exchange, view and perform measurements of medical images independently of manufacturers.

What are DICOM Headers, DICOM Tags and Data Sets?

A set of medical images in DICOM format usually has the following overall structure: Patient – Exam – Series – Images. That is, a patient undergoes a study or examination, such as a computed tomography (CT) scan. This examination consists of several series, and each series contains multiple images (hundreds or thousands) or multiple frames (like a video, e.g., for echocardiographies).

A DICOM medical image file, such as a single CT slice, consists of two distinct parts. One is the medical image itself, the other is the DICOM header. The DICOM header is a block of data that contains specific information that complements the image, called DICOM tags. This usually includes relevant patient data such as name, age, gender and date of birth, but also a lot of technical data and parameters, such as the device used to generate the images, the names of the surgeon and the administered drugs such as contrast agents, as well as data on the imaging technique, such as pixels, matrix size or the dimensions of the image. This usually facilitates the assignment of an image to a patient. In medical jargon, this data is referred to as attributes. Depending on the image and the circumstances, certain information is mandatory, while other attributes are optional. In addition, the DICOM header has DIN standards, which are defined by law.

What are DICOM Tags good for?

The DICOM Tags are organized as a constant and standardized series; thus, they are used in the management of information belonging to medical image data. The DICOM Tags are assigned as metadata elements to each image object in medicine. These can be segmentations, definitions of surfaces, and registration numbers for the images. The format is used for both standardization and storage of the files, as well as a uniform communication protocol for sharing. As data elements, tags consist of an attribute that is used for identification. Usually they are composed of hexadecimal numbers (XXXX,XXXX) with a comma in the middle. If necessary, a further subdivision into the group and element number is possible. In this way, DICOM tags are easier to read, and patient data can be printed directly on them when developing X-ray images. In this way, the X-ray image and the associated data are combined digitally in one file.

What DICOM Tags are available?

There are a variety of DICOM tags that assist in organizing medical image data as well as searching for them. These include, for example:

DescriptionNumber
Accession Number0008,0050
Procedure Creation Date0014,4076
Modality0008,0060
Patient’s Birth Name0010,1005
Operator’s Name0008,1070
Patient’s ID0010,0020
Patient’s Birth Date0010,0030
Patient’s Body Mass Index0010,1022
Table 1, DICOM Tags

Thanks to the numbers, an extremely large amount of information can be assigned to the images, which is immediately recognized by the medical authorities. By the way: A full list of all DICOM tags can be found at MITA (The Medical Imaging Technology Association) or NEMA here.

In the next part of our DICOM explained series, we will dive deeper into the topic: Among others, you will learn more about the problems that the data contained in DICOM files pose for working with them. Stay tuned!

See the article on the new Blog