Author Archives: birblog2013

Radiography, Research, and You

Kim Mason head and shoulders image
Kim Mason

Kim Mason, an Audit and Research Radiographer for Mid Yorkshire Teaching Hospitals Trust, talks about their role as well as the value of radiographer engagement in research activities and how to get involved.

In December, 1895, Wilhelm Röntgen would x-ray the hand of Anna Bertha Ludwig, his wife, using a photographic plate. The new discovery lit a fire in the scientific community, and was so sensational that in the following year over 1,000 articles would be published on the topic of X-rays. Over the next 130 years, medical imaging has undergone many varied evolutions to become a cornerstone of modern-day medicine. All beginning with that first piece of research.

Radiography has exploded into a variety of modalities and specialisms from CT to Ultrasound to MRI; all driven by research and development. That is where I come in.

Hi, I’m Kim and I am an alternative-styled, funky-haired, septum-pierced, disabled Audit and Research Radiographer. That is to say, I’m fairly easy to pick out of a line up. I’m also passionate about education, research, and (of course) radiography. This, I’ve been told, is also very easy to pick up on.

I graduated with my radiography degree in 2018 and since then I’ve worked in a wide variety of departments, from plain film to nuclear medicine. Since I found something to love in every modality it never really mattered which one I was in. Prior to my current position, I’ve spent time as a Radiation Protection Supervisor, and well as a trainer for graduate and post graduate radiographers. Now I’m in Audit and Research, which is far different to anything I’ve done before.

So, what is an Audit and Research Radiographer?

Kim sat in their wheelchair at the UKIO 2023 conference

My position is entirely based in research so I do not currently undertake any non-research imaging. However, I’m not entirely non-clinical. I get trained to undertake research scans on new equipment as required for me to carry out the necessary imaging for research trials. I also provide support to all trials requiring access to our radiography department, regardless of the imaging modality.

My job requires that I read a lot of trial protocols so that I can determine whether we have the necessary resources to undertake the trial. It can be hard work, and for me to be effective I have to have a good understanding of how each of our trusts’ imaging modalities function. I also need to have strong communication skills, especially in regards to explaining radiography perspectives to multi-disciplinary team members who may have little to no understanding of imaging. More than this, I need to be able to form and maintain good relations with all sides to ensure that effective communication can take place.

The work I do allows for better outcomes between radiology and research departments. It also affords me the opportunity to be a part of progress, seeking out better practice or improved technology for the future of imaging. In addition, I am able to undertake my own research, working towards my goals of further academic qualifications.

My role is important. I feel that I and my work contributions are valued by both the radiology and research teams. My pathway for personal development is clear and I am able to see the benefits in the set-up and management of the trials my Trust undertakes.

What is Radiography research and why is it important?

There is often research aimed at improving and advancing the field of diagnostic imaging. Currently there are trials into new scanning techniques; new equipment with the potentials for dose reduction and/or improved image quality and patient experiences; and the use of AI in imaging and reporting.

The benefits of improvements in our field are numerous. Every radiographer wants to give patients the best experience they can, however this is often at odds with the nature of our job. Requiring patients to hold uncomfortable positions when they are in pain or worried; perhaps having to go through narrow tubes which are sometimes incredibly loud; needing injections which makes them feel weird or mean they are radioactive and have to keep distance from other people at a time when they could really do with support. With research, we can aim to improve these experiences; reduce scan times or radiation exposures, wider bore scanners or open scanners, even finding new imaging or testing which removes the need for the ionising radiation all together!

Patients are at the heart of the NHS, and diagnostic imaging is often an area in which a good patient experience can be harder to provide (that is not to say that we don’t try!). With research, we have the potential to make those improvements to service, to provide for our patients in the way which we want to and the way that they deserve.

How can I get involved?

Often, radiography research is overseen by radiologists, doctors and orthopaedic surgeons, but there is no reason why radiographers shouldn’t also get involved. As we are the ones who use the equipment on a daily basis, consent and care for the patients during imaging, and come into contact with the faults and issues. Our profession contains a wealth of knowledge which can be used to improve all aspects of radiography.

You don’t need any academic qualifications to get started with research activities. In fact, many radiographers image research patients without being privy to the research aims. In a busy department, such patients are treated the same as any other in most regards. If you do image a research patient, perhaps look into the trial itself. As well as being interesting additional information, it can be used as material for CPD in the form of a case study or reflective piece. You may also discover potential ways to improve the patient experience within your department and help to enact future change.

Look into what your hospital requires for research involvement. The Good Clinical Practice (GCP) qualification, which is usually necessary, can be found for free as an online e-learning module. The NIHR website provides a lot of helpful information for getting started. NIHR also provides help for those who are wanting to gain further academic qualifications, such as through grant applications for fellowship awards. These are highly competitive but allow better access for NHS employees to undertake Masters or Doctorate level qualifications. The NIHR also run conferences for those who are new to research but interested in how they can take part.

You could also look at taking part in your department’s audits. Audits are a great way to check in on the health of your department, what you are doing well, and what you can improve on. Audit skills can also overlap with those necessary for research work, as well as provide possible avenues for research within your department.

How do I get a research job?

The roles of radiographers in research are expanding. Some hospitals offer clinical research radiographer positions, which give additional responsibility to train for and undertake specialised research imaging, often alongside a multi-disciplinary team. Other trusts may offer training for those wanting to aid research trials.

For research-specific roles, take a look at NHS jobs. You will find posts for Research Radiographers or Research Clinical Practitioners/AHPs. When I applied for my Audit and Research radiographer post, I had no specific research skills however I was well versed in audits and had learned about the processes of research in my own time. Enthusiasm goes a long way when applying for research roles, we need radiographers who are driven and raring to get stuck in.

There is so much experience and knowledge that radiographers have to offer research, and there’s so much improvement and advancement to be received in turn. I strongly encourage any radiographers to give it a try. You never know, you may get hooked!

To submit your research to a BIR journal find out more here:

BJR https://www.editorialmanager.com/bjr/default2.aspx

BJR Case|reports https://www.editorialmanager.com/bjrcr/default2.aspx

BJR|Open            https://www.editorialmanager.com/bjro/default2.aspx

About Kim Mason

Kim Mason is a HCPC registered diagnostic radiographer, graduating from the University of Leeds with a 1st Class BSc Honours in Diagnostic Radiography in 2018. They have experiences in education both inside and outside of radiography, and have a passion for improving the radiography services in the UK.

Kim has multiple chronic conditions, and as such, they are an ambulatory wheelchair user. This has given them keen insight into the experiences of patients within the radiography department, having undergone imaging in most modalities as a patient. They have a vested interest in educating the public about radiography, and educating radiographers on improvements to patient care. 

Artificial Intelligence Embedded Imaging Modality

In the third blog of her series on AI and the radiographer, Shamie Kumar explores the impact on the radiographer when AI is integrated within an imaging modality.

In previous BIR blog posts, I have explored how AI is integrated into PACS with the AI outputs seen on radiology systems, and whether non-reporting radiographers could learn and benefit from AI. The question to explore in this blog is when AI is integrated within an imaging modality itself and how that may impact a radiographer.

AI embedded into a portable digital X-ray machine

Radiographic images are acquired in multiple modalities within different patient pathways. I will explore how AI embedded into a portable digital X-ray machine might change and affect how the radiographer works and learns.

Every radiographer is trained to take X-rays on portable machines and this is a core skill and it is an adapted technique compared with dedicated static X-rays rooms. It is unique in the sense patient positioning can vary depending on the environment and situation, whether this be on a ward or in A/E resus. Patient’s conscious level and mobility can vary, often supine and not all being cooperative. There can be situations where other healthcare professionals (HCP) are in proximity of the patient being imaged due to the image being acquired outside of the main radiology department.

AI output

Some hospitals have adopted digital portable X-ray machines to provide an instant image, the radiographer can see the chest X-ray immediately after exposure and decide whether the image quality is optimal. As AI becomes integrated within the modality, in this instance on a portable digital X-ray machine, the radiographer will also see the AI output and findings alongside the original X-ray. Not only does the radiographer see the AI output but other HCP that are present will also have the accessibility to view the same in the given environment. As we all know, X-rays need to be reported by radiologist or reporting radiographers, but often clinicians make clinical decision before these inpatient portable x-rays reports are finalised and available on the hospital system, especially if quick intervention is required.

When AI integration is done in such a way that radiographer need not log into PACs to view the AI output and is shown on the modality once the image is acquired, all radiographers can utilise AI to its full potential. The focus quickly shifts to: does the radiographer have the relevant education and training to understand the AI intended use, the AI outputs, what are the functions, features of the AI, how do they clinically interpret these images, how does AI work and what are the limitation of AI. All these questions become important when an AI is implemented; radiographers need to be trained how to use it, become familiar with the outputs, and educate others around them. If this is approached robustly, it will empower radiographers to learn and upskill themselves with AI being part of their daily clinical workflow, giving them the confidence to support and guide other healthcare professionals (HCPs) who also are looking at the X-ray when it acquired.

AI is an assistive tool

It’s important to recognize that AI findings are never the final diagnoses. Ultimately AI is an assistive tool, embedded within portable machines. Doctors and HCPs will also view the AI output and, with time, it will be the role of the radiographers to appropriately manage and guide other healthcare professionals.

About Shamie Kumar

Shamie Kumar is a practicing HCPC Diagnostic Radiographer; graduated from City University London with a BSc Honors in Diagnostic Radiography in 2009 and is a part of Society of Radiographers with over 12 years of clinical knowledge and skills within all aspects of radiography.

She studied further in leadership, management, and counselling with a keen interest in artificial intelligence in radiology.

An explosion in imaging: Is this the future?

Prof Simon Padley

Following the recent BIR live event Imaging explosion across the pond – causes and solutions in which the UK and USA radiology and healthcare systems were compared, DMC Radiology Reporting co-director Professor Simon Padley reflects on the UK position.

The USA often provides a window into our own future

In the application of imaging technology, we often follow trends that emerge in the US – the rise in CT and MRI utilisation are two examples, and more recently the growth of outsourcing is following a similar trajectory.

With different healthcare models, the US does not rely on central funding to replace or add to CT and MRI capacity. NHS funding comes from the government’s general revenue, and healthcare services are provided to all residents of the UK, regardless of their ability to pay. In contrast, the US medical system is a mixed system of public and private funding. It includes a combination of private health insurance, employer-based insurance, individual out-of-pocket payments, and public programs like Medicare and Medicaid, which are funded through federal and state taxes.

In 2022 there were 6.6 million CT studies on NHS funded patients according to NHS Digital, at a time when the population was reported to be 55 million. This equates to 121 studies per 1000 of the population. In the USA  this figure is more than double at 278 CT studies per 1000 of the population (84 million CT studies in a population of about 333 million CT Scans Each Year – iData Research).

And that is just CT! Official data for 2021/22 shows that between April 2021 and March 2022, NHS services in England carried out 43.8 million imaging tests across all modalities Ref. This reflects an ever-growing requirement for imaging studies to be undertaken and reported.

At the same time, the workforce needed for this activity has fallen far behind that required. We bump along the bottom of the league table for radiologists per 100,000 of the population (8.5). Europe has 13, the US 11. Couple this with complexities of pension taxation, IR35 and COVID related burnout all nudging older highly skilled and efficient radiologists towards the exit door and we have a perfect storm. Even today we have 2000 full-time consultant clinical radiologist posts unfilled across the UK. The RCR predicts a 39% workforce shortfall by 2026 (equating to 3166 full time radiologists).

This may create stress in the radiology department, but rest assured it also causes grey hair and sleepless nights for those that inhabit the carpeted management corridors. Hidden amongst every backlog of reporting there is serious pathology lying undiagnosed. When that report is provided, and the treatment options are discussed, some options will have closed, tumours will have stage shifted and outcomes will be less good. This constitutes a chief executive’s nightmare but has caught the medicolegal world’s attention. So, what are we to do?

Teleradiology and the NHS

Almost all acute trusts have turned to the services of the teleradiology community, now playing a vital role in helping to address this capacity shortfall. In the past 10 years the market has grown with a compound annual growth rate of about 10-15%.

Who are all these extra radiologists and where do they come from? Well of course, by-and-large, they are you and me. But we are a limited pool, the market rates for reporting (set by the NHS) are not great and there are only so many hours in the day.

So where can we look for additional workforce capacity and will we be allowed to access it? To allow this to happen the NHS will need to engage more readily with the solutions that are now emerging and examine the detail of how we, in the teleradiology world, are already addressing data governance and medicolegal concerns.

At DMC Radiology Reporting, we already work in partnership with many NHS Trusts. We strive to deliver fast, accurate radiology reporting with innovation and efficiency. We have a rigorous commitment to clinical governance, and we are proud of our work force of GMC-registered/FRCR-radiologists with sub-specialty interests.  Like many others, we are interested in how these problems are being addressed in the US.

About Professor Simon Padley

In 2013 Simon co-founded DMC-Radiology Reporting, which has been growing and developing ever since, focusing on sub-specialist high quality outsourced reporting.

Simon is a cardiothoracic and interventional radiologist, appointed in 1994. As a previous imaging director in the NHS for many years he developed a range of new services, most recently as lead radiologist for Royal Brompton Hospital Diagnostic Imaging Centre, opened in 2022. This facility incorporates one of the only combined interventional bronchoscopy and radiology facilities in the country.

As a Professor of Practice (Diagnostic and Interventional Radiology) since 2016, at the National Heart & Lung Institute, Imperial College London, he maintains an active academic career, publishing widely with over 220 articles in peer reviewed journals.

The Promise of Automation in Radiation Oncology

Radiation oncology clinics face numerous challenges in the present environment, including the simultaneous management of multiple tasks (many of which are manual in nature), various degrees of standardisation, and the potential for errors to impact patient treatment. Automation can help address these challenges by reducing the time required to execute manual portions of the workflow and positively impacting the quality and safety of patient care. Tyler Blackwell, Medical Physicist discusses more:

Efficiency

To a large degree, many departments have already integrated automation into their departments. However, it stands to be a driving force of innovation in our field for the foreseeable future, coinciding with efforts to improve plan quality and reduce errors inherent in human interaction. Increasing the productivity and efficiency of our daily clinical tasks by minimizing time spent on tedious, routine tasks “below our licenses” (as worded by physicist Eric Ford as part of a Radformation Focal Spot interview) allows more time to address other critical clinical elements that require human expertise.

In developing smarter tools, we have an opportunity to improve the patient experience. Radformation CEO Kurt Sysock, MS, DABR, explains, “On average, it takes five days after simulation to create a finished plan that is ready for treatment, and we want to reduce that to less than one day.” Indeed, reducing the time between simulation and treatment can have a significant impact not only on patient satisfaction, but also on patient outcomes. Delays in treatment planning times are associated with an overall higher risk of mortality ranging from 1.2–3.2% per week for curative diseases. Reducing the time between simulation and treatment maximizes tumor control probability and patient survival.

Quality and Safety

The quality and consistency of patient care are greatly improved when the care team is able to deliver treatment as efficiently as possible. In this environment, they can devote more resources toward tasks that require greater attention or collective experience. From the clinician’s point of view, smart automation reduces the time spent on tasks that do not add value to patient care but are nonetheless important for sustaining operations.

Over the last decade, clinicians have largely embraced a culture of safety and quality improvement. This paradigm shift delivers a number of benefits for patients and involves a continued effort toward reducing errors in radiation oncology.  While a number of interventions can positively influence safety and quality, automation is highly effective in this regard. Absent automation, this ongoing commitment will be inhibited by a lack of efficiency and scalability as clinicians grapple with manual processes and endless checklists.

Automation is one of the most effective ways to impact change in medicine. Source: Cafazzo, J and St-Cry, O. From Discovery to Design: The Evolution of Human Factors in HealthCare. Healthcare Quarterly. April 2012. doi:10.12927/hcq.2012.22845

Automation plays a part in advances in clinical care as well. Radformation CSO Alan Nelson, DMP, DABR, argues that, “just as IMRT significantly improved the effectiveness of treatment while reducing side-effects, automation will enable the field to explore and implement new solutions for therapy protocols that otherwise simply would not have been feasible due to lack of resources.”

An Elevated Workflow At Every Step


Finding steps along the treatment care path that involve manual inputs isn’t a challenge. Wherever they exist, there is an opportunity for automation to provide value. From planning and on-treatment to billing and quality assurance, the results of these workflow improvements are impressive.

Structure Segmentation

The proper delineation of anatomical structures in the vicinity of the target is important in understanding the impact of a treatment plan on the surrounding healthy tissues. But manual contouring can be resource-intensive, and some structure boundaries—especially for target structures—can vary widely based on who is performing the work. According to physicist Noah Bice of New York University Langone, “Contouring is subjective. With any mix of individuals, there are inherently varying levels of expertise and personal preference involved.”

Within the past few years, the introduction of deep-learning algorithms for contouring has transformed the landscape. By exploiting cloud-based computational resources, structure sets, including organs-at-risk and target structures, can be generated in a fraction of the time as manual contours. Departments have been quick to adopt this new technology, which will likely become a global standard of care within the decade.

Treatment Planning

Given that every patient’s anatomy and disease state is unique, it might feel safe to assume that it may not be possible to automate this process. Despite this inherent variation, the approach to planning is algorithmic and repetitive. By scripting various repetitive processes—field-in-field or electronic compensator planning, for example—departments are capable of producing consistently high-performing plans in a fraction of the time.

This process, when applied to the Halcyon machine, has made it feasible to plan electronic compensator breast plans when otherwise manual planning is impractically cumbersome and time-consuming.

Plan Evaluation and Reporting

Determining the quality of any given treatment plan is no small task. Often, it is not easy to compare comprehensive plan quality elements within the treatment planning system (TPS). By tapping into the plan data via scripting interfaces, it’s possible to pull dosimetric information for comparison against dose constraint templates to verify the quality of a plan during or after the plan is complete.

Automated platforms are quickly becoming the standard of care, providing intuitive assessments of plan quality, including dose constraints, plan checks, machine collision risk, and reporting. While default TPS reports are often limited in scope, third-party options offer fast, customized plan reports as well as the ability to populate directly into ARIA Documents.

Comprehensive new tools allow for faster, user-friendly plan revaluation and reporting.

Quality Assurance

Collecting and sorting quality assurance information can be a challenging task given the variety of equipment and vendor products in the clinic that requires tracking. The frequency of the tasks adds another layer of complexity as well, with new data being acquired daily. Thankfully, new quality assurance platforms make short work of managing this data, providing a central location for all data from linacs and CTs to ionisation chambers and GM meters. Automation is capable of detecting new test information—from daily or monthly tests—and effortlessly syncing data to the centralized platform for quick analysis and review. These databases bring efficiency while reducing the dependency on multiple separate spreadsheets in unique locations.

Conclusion

In conclusion, the use of intelligent automation in radiation oncology—such as the solutions offered by Radformation—has the potential to revolutionize clinical workflows, leading to bottom-line improvements in patient care. By reducing the time required to execute manual portions of the workflow, clinicians can devote more time to critical clinical elements that require human expertise, such as addressing treatment planning and ensuring patient safety. Automation also plays a part in advances in clinical care and enables the field to explore and implement new solutions that may not have been feasible without this technology. In short, the benefits of automation in radiation oncology are numerous and diverse, and they can significantly enhance the overall quality and safety of patient care.


To learn more about how automation can play a role in your department, visit us at Radformation’s booth at BIR’s Annual Radiotherapy an Oncology Meeting 2023 where we will highlight our workflow automation solutions. See the possibilities for improving clinic efficiency and effectiveness with products, including AutoContour for autosegmentation and RadMachine for machine QA, by scheduling a demonstration today.

About Tyler Blackwell

Tyler Blackwell

Tyler Blackwell, MS, DABR, is a medical physicist at Radformation focused on clinical collaborations and community engagement. Before joining Radformation, he spent a decade working as a clinical physicist. He is active on several committees for the American Association of Physicists in Medicine, including the board of directors, and volunteers for the American Board of Radiology.

Can We Upskill Radiographers through Artificial Intelligence? 

Shamie Kumar describes how AI fits into a radiology clinical workflow and her perspective on how a clinical radiographer could use this to learn from and enhance their skills.

AI in radiology and workflow

We all know that AI is already here, actively being implemented and used in many trusts in seeing its real world value supporting radiology departments to solve current challenges. 

Often this is focused on benefits to radiologist, clinicians, reporting radiographers, patients, and cost savings, but what about clinical non-reporting radiographers undertaking the X-ray or scans – can AI benefit them too?

Let’s think about how AI is implemented and where are the AI outputs displayed? 

If the AI findings are seen in PACS, how many radiographers actually log into PACS after taking a scan or X-ray? Good practice is seen to have PACS open to cross-check images that have been sent from the modality. Often this doesn’t happen for various reasons but maybe it should be a part of the radiographers’ routine practice, just like post-documentation is.

Can Radiographers Up-Skill?

Given the view it does happen, radiographers will have the opportunity to look at the AI outputs and potentially take away learnings on whether the AI found something that they didn’t see initially or whether there was a very subtle finding. We all know people learn through experience, exposure, and repetition, so if the AI is consistently picking up true findings, then the radiographer can learn from it too.

But what about when AI is incorrect – could it fool a radiographer, or will it empower them to research and understand the error in more detail?

As with many things in life, nothing is 100% and this includes AI in terms of false positive and false negatives. The radiographers have the opportunity to research erroneous findings in more detail to enhance their learning, but do they actually have time to undertake additional learning and steps to interpret AI? 

CPD, self-reflection, learning through clinical practice are all key aspects of maintaining your registration, and self-motivation is often key to furthering yourself and your career. The question remains: are radiographers engaged and self-motivated to be part of the AI revolution and use it to their professional benefit with potential learnings at their fingertips? 

There have been a few recent publications that share insight on how AI is perceived by radiographers, what is their understanding, training and educational needs.

Many Universities like City University London and AI companies like Qure.ai are taking the initial steps in understanding this better and taking active efforts in filling the knowledge gap, training and understanding of AI in radiology.

Radiographers who are key part of any radiology pathway, are yet to see the real-world evidence on whether AI can upskill radiographers, but there is no doubt this will unfold with time.

About Shamie Kumar

Shamie Kumar

Shamie Kumar is a practicing HCPC Diagnostic Radiographer; graduated from City University London with a BSc Honors in Diagnostic Radiography in 2009 and is a part of Society of Radiographers with over 12 years of clinical knowledge and skills within all aspects of radiography. She studied further in leadership, management, and counselling with a keen interest in artificial intelligence in radiology.

References

Akudjedu, T. K. K. N. M., 2022. Knowledge, perceptions, and expectations of Artificial intelligence in radiography practice: A global radiography workforce survey. Journal of Medical Imaging and Radiation Sciences.

Coakley, Y. M. E. C. M. M., 2022. Radiographers’ knowledge, attitudes and expectations of artificial intelligence in medical imaging. Radiography International Journal of Diagnostic Imaging and Radiation Therapy, 28(4), pp. P943-948.

Malamateniou, K. P. W. H., 2021. Artificial intelligence in radiography: Where are we now and what does the future hold?. Radiography International Journal of Diagnostic Imaging and Radiation Therapy, 27(1), pp. 58-62.

Kumar, D., 2022. CoR endorsed CPD Super User Training by Qure.ai. [Online]
Available at: https://www.qure.ai/gain-cor-endorsed-super-user-training/
[Accessed 23rd January 2023].

Why understanding breast density matters

Cheryl Cruwys, European Education Coordinator at DenseBreast-info.org/Europe, highlights the importance of understanding the screening and risk implications of dense breast tissue. DenseBreast-info.org’s mission is to advance breast density education and address the gap in knowledge about dense breasts.

Mammography remains the standard of care in screening for breast cancer and has been proven to reduce the mortality rate [1].  However, in dense breasts, cancers can be hidden/obscured on mammography [2,3] (Fig.1) and may go undetected until they are larger and more likely to present with clinical symptoms [4]. Breast density has also been identified as the most prevalent risk factor for developing breast cancer [5].   

Women with dense breasts are BOTH more likely to develop breast cancer and more likely to have that cancer missed on a mammogram [5]

Fig. 1 – Cancer on a mammogram of a fatty vs a dense breast

What is Dense Breast Tissue?

Breasts are made of fat and glandular tissue, held together by fibrous tissue. The more glandular and fibrous tissue present, the “denser” the breast. Breast density has nothing to do with the way breasts look or feel. Whilst dense breasts are normal and common, dense breast tissue makes it more difficult for radiologists to detect cancer on a mammogram.  

Breast density is determined through a mammogram and described as one of four categories (Fig. 2), (A) Fatty, (B) Scattered, (C) Heterogeneously Dense, (D) Extremely Dense.  Breasts that are (C) heterogeneously dense, or (D) extremely dense are considered “dense breasts”.  Fig. 2

Figure 2

Dense Breasts Facts

  • 40% of women over age 40 have dense breasts.
  • Dense breast tissue is an independent risk factor for the development of breast cancer; the denser the breast, the higher the risk.
  • Mammograms will miss about 40% of cancers in women with extremely dense breasts.
  • Women with extremely dense breasts face an increased risk of late diagnosis of breast cancer.
  • In these women, screening tests, such as ultrasound or MRI, when added to mammography, substantially increase the detection of early-stage breast cancer.

Dense Breast Educational Resources

DenseBreast-info.org/Europe is the world’s leading website about dense breasts. This medically-sourced resource is the collaborative effort of world-renowned experts in breast imaging and medical reviewers. Fig 3.

Figure 3

                                                     

The website features educational tools for both European Patients and Providers Fig. 4. (a and b)

Figure 4 (a)

CME Course – Learn Why Breast Density Matters!

The DenseBreast-info.org resource includes a free CME/CE course, Dense Breasts and Supplemental Screening suitable for primary care healthcare providers, including family medicine, internal medicine, and OB/GYN physicians and midlevel providers, as well as radiologists, and radiologic technologists (UEMS-EACCME® mutual recognition for AMA credits).

A growing number of medical organisations link to the DenseBreast-info.org website, including the EFRS (European Federation of Radiographer Societies) and the Society of Radiographers.  

                               

Figure 4 (b)

                                                                                                                                        

The website includes breast screening guidelines in Europe. A comparative analysis table summarises the guidelines in each country.

NHS Breast Screening Programme

Currently in the UK, population routine screening mammograms are offered to women aged 50–74, every 3 years. Though dense breasts affect the likelihood that a cancer will be masked and increases a woman’s risk for developing breast cancer, it is not part of UK data collection. A woman’s breast density is not assessed, not recorded in medical records, nor reported to her. For diagnostic purposes, this may differ. However, in many other European country screening programs, a woman’s breast density is assessed, recorded, and the woman’s personal breast density category is included in the mammography report.

News in Europe:  the EUSOBI Recommendations

Population based breast screening guidelines vary across Europe. In the UK, asymptomatic women attending routine national breast screenings receive mammography alone. In some countries (e.g., Austria, Croatia, Hungary, France, Serbia, Spain, Switzerland) screening guidelines for women with dense breasts include that they be offered supplement ultrasound following a mammogram.

Following recent MRI screening trials there is cumulating evidence which confirms that women with dense breasts are underserved by screening with mammography alone [7,8]. In March 2022, new guidelines were issued in Breast cancer screening in women with extremely dense breasts by the European Society of Breast Imaging (EUSOBI) [9] highlighting the growing evidence, particularly the results of a randomised, multicentre controlled study, the Dense Tissue and Early Breast Neoplasm Screening (DENSE) Trial. [7,8]

The European Society of Breast Imaging 2022 recommendations now step away from the one-size-fits all approach of mammography that is currently adopted by most European screening organizations and advocates for tailored screening programmes. There is compelling evidence that the new recommendations enable an important reduction in breast cancer mortality for these women. 

Summary of the EUSOBI Recommendations

Below is EUSOBI’s summary graphic of the recommendations (Fig. 7) that highlight:   

  • Supplemental screening is recommended for women with extremely dense breasts.  
  • Supplemental screening should be done preferably with MRI …. where MRI is unavailable… ultrasound in combination with mammograph may be used as an alternative.

In addition to recommended additional screening in women with extremely dense breasts, note that EUSOBI recommends that “women should be appropriately informed about their individual breast density in order to help them make well-balanced choices.”

EUSOBI acknowledges that it may take time before the new recommendations are implemented in Europe and that the level of implementation is dependent on the resources that are available locally. 

It is important to emphasize that the EUSOBI recommendations highlighted in this article are not yet guidelines in Europe. Of course, it is hoped that in Europe, national breast screening committees try to implement these recommendations as soon as possible to benefit women.   

                                                                                                                                                                                                                       

Figure 7

World Dense Breast Day Success!

DenseBreast-info.org launched the first #WorldDenseBreastDay on 28 September 2022.

Nearly 100 posts with great images were created and ran for 24 hours across social media channels.  Analytics detailed participation from people in 37 countries, over 8.6 million people saw/read the posts and over 17,000 people interacted with the posts.

The purpose of the day is to raise awareness about dense breasts and share medically-sourced educational resources available for women and health providers.                                                                                          

Please join us next year for #WorldDenseBreastDay which will take place on 27 September 2023!                               

Take Home Message:

  • Breast density can both hide cancers on a mammogram and increases the risk of developing breast cancer.
  • Women with dense breasts benefit from additional screening tests after their mammogram
  • Breast density education and access to supplemental screening can mean the difference between early- or late-stage diagnosis
  • Physicians should be educated and prepared to have patient conversations about breast density   
  • For more information about Dense Breasts visit: DenseBreast-info.org/Europe

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1, Tabar L, Vitak B, Chen T H et al. Swedish two-county trial: impact of mammographic screening on breast cancer mortality during 3 decades. Radiology 2011;260:658-63

2. Hooley RJ, Greenberg KL, Stackhouse RM, Geisel JL, Butler RS, Philpotts LE (2012) Screening US in patients with mammographically dense breasts: initial experience with Connecticut Public Act 09-41. Radiology 265:59–69

3. Kolb TM, Lichy J, Newhouse JH (2002) Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations. Radiology 225:165–175

4. RoubidouxMA, Bailey JE,Wray LA, HelvieMA(2004) Invasive cancers detected after breast cancer screening yielded a negative result: relationship of mammographic density to tumor prognostic factors. Radiology 230:42–48

5. McCormack VA, dos Santos Silva I (2006) Breast density and parenchymal patterns as markers of breast cancer risk: a metaanalysis. Cancer Epidemiol Biomarkers Prev 15:1159–1169

6. Vourtsis A, Berg W A. Breast density implications and supplemental screening. Eur Radiol 2019;29:1762-77.

7. Bakker M F, de Lange S V, Pijnappel R M et al. Supplemental MRI screening for women with extremely dense breast tissue. N Engl J Med 2019;381:2091-102.

8. Stefanie G. A. Veenhuizen, Stéphanie V. de Lange, Marije F. Bakker, Ruud M. Pijnappel, Ritse M. Mann, Evelyn M. Monninkhof, Marleen J. Emaus, Petra K. de Koekkoek-Doll Published online: Mar 16 2021 https://doi.org/10.1148/radiol.2021203633Radiology Vol. 299, No. 2 Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial

9. Mann, R.M., Athanasiou, A., Baltzer, P.A.T. et al. (2022) Breast cancer screening in women with extremely dense breasts recommendations of the European Society of Breast Imaging (EUSOBI) Eur Radiol 32, 4036–4045 

Cheryl Cruwys is a British breast cancer patient, advocate, author and educator. While living in France (2016) she was diagnosed with early-stage breast cancer and credits the early detection of breast cancer to the French standard practice of performing supplemental screening on dense breast tissue. She is founder of Breast Density Matters UK, European Education Coordinator at DenseBreast-info.org/Europe, a member of the European Society of Radiology Patient Advisory Group and a Patient Rep on the ecancer.org Editorial Board.

Cheryl works at the European level with patient advocacy and medical societies, attends/presents at key scientific symposiums and works with international breast imaging experts to disseminate education on dense breasts. DenseBreast-info.org 

Is Artificial Intelligence a glorified red dot system?

Shamie Kumar

We are all familiar with the concept of artificial intelligence in radiology and its application that is expanding rapidly. But how will AI in the workplace affect the radiographer and how does it differ from the red dot system radiographers are so familiar with?

Shamie Kumar describes her perspective on how radiography has evolved over time, the impact radiographers can have in detecting abnormal X-rays and reflects how she views fast approaching AI in advancing current skills.

The Red Dot System

Often one of the first courses a newly qualified radiographer attends is the red dot course. This course demonstrates pathologies and abnormalities often seen in X-rays some obvious, others not, giving radiographers the confidence to alert the referring clinician and/or radiologist that there is something abnormal they have seen.

The red dot system is a human alert system, often two pairs of eyes are better than one and assist with near misses. How this is done in practice can vary between hospitals, in the era of films the radiographer would place a red dot sticker on the film itself before returning it to clinician or radiologist. In the world of digital imaging this is often done during “post documentation” a term used once the X-ray is finished, the radiographer will complete the rest of the patient documentation to suggest the X-ray is complete, ready to be viewed and reported. As part of this process the radiographer can change the status of the patient to urgent along with a note for what has been observed. From this the radiologist knows the radiographer has seen something urgent on the image and the patient appears at the top of their worklist for reporting and, so the radiologist can view the radiographer’s notes.

The Role of AI in Radiology

Artificial Intelligence (AI) is moving at a pace within healthcare and fast approaching radiology departments, with algorithms showing significant image recognition in detecting, characterisation and monitoring of various diseases within radiology. AI excels in automatically recognising complex patterns in imaging data providing quantitative assessments of radiological characteristics. With the numbers for diagnostic imaging requests forever increasing, many AI companies are focusing on how to ease this burden and supporting healthcare professionals.

AI triage is done by the algorithm based on abnormal and normal findings. This is used to create an alert for the referring clinician/radiologist. It can be customised to the radiologist, for example colour-coded flags, red for abnormal, green for normal, patients with a red flag would appear at the top of the radiologist worklist. For the referring clinicians who don’t have access to the reporting worklist, the triage would be viewed on the image itself with an additional text note suggesting abnormal or normal.

Image courtesy of qure.ai

What does AI do that a radiographer doesn’t already? AI is structured in a way that it gives the findings; for example, a pre-populated report with its findings or an impression summary and its consistent without reader variability. So, the question now becomes what can AI do beyond the red dot system. Here, the explanation is straightforward. Often a radiographer wouldn’t go to the extent of trying to name what they have seen, especially in more complex X-rays like the chest where there are multiple structures and pathologies. For example, a radiographer would mention right lower lobe and may not go beyond this, often due to confidence and level of experience.

AI can fill this gap; it can empower radiographers and other healthcare professionals with its classification of pathologies identifying exactly what has been identified on the image, based on research and training of billions of data sets with high accuracy.

The radiographers may have the upper hand with reading the clinical indication on the request form and seeing the patient physically, which undoubtably is of significant value. However, the red dot system has many variables specific to that individual radiographer’s skills and understanding. It is also limited to giving details of what they have noted to just the radiologist. What about the referring clinician who doesn’t have access to the radiology information system (RIS) where the alert and notes are? Do some radiographers add a text note on the X-ray itself?

Summary

Yes, AI is a technological advancement of the red dot system and will continue to evolve. It is structured in how it gives the findings and does this consistently with confidence adding value to early intervention, accurate patient diagnosis, contributing to reducing misdiagnosis and near misses. AI is empowering radiographers, radiologists, referring clinicians and junior doctors by enhancing and leveraging their current knowledge to a level where there are consistent alerts and classified findings that can even be learned from. This doesn’t replace the red dot system but indeed enhances it.

The unique value a radiographer adds to the patient care, experience and physical interaction can easily be supplemented with AI, allowing them to alert with confidence and manage patients, focusing the clinician time more effectively.

About Shamie Kumar

Shamie Kumar is a practicing HCPC Diagnostic Radiographer; graduating from City University London, BSc Honors in Diagnostic Radiography in 2009 and part of Society of Radiographers with over 10 years of clinical knowledge and skills within all aspects of radiography. She studied further in leadership, management and counselling with a keen interest in artificial intelligence in radiology.

Unlock the advantage of time across the breast health continuum of care

Tim Simpson

Time is everything when it comes to breast cancer care. If we can embrace smarter technology, this will help to provide better workflow efficiency and clinical confidence across the patient pathway, unlocking that much needed time to care for breast cancer patients. Tim Simpson General manager, UK and Ireland at Hologic explores how we can achieve this across the breast health continuum of care.

More accurate and efficient detection is instrumental for better patient outcomes. 3D Mammography™ systems have become smarter, bringing breast cancer diagnosis to a new level, improving cancer detection accuracy, optimising workflow, and supporting personalised patient care[1]. The integrated AI powered software solutions employ machine-learning and deep learning algorithms developed and trained on a large number of tomosynthesis (3D Mammography™) images to aid cancer detection, assess breast density, and accelerate diagnosis.

What’s more, using 3D Mammography™ can result in up to 40% fewer recalls[2], [3], helping to reduce the physical and emotional burden on patients and giving back valuable time to health care professionals.

To mitigate the time challenges typically faced when reporting tomosynthesis images, advanced imaging technology can reconstruct high-resolution tomosynthesis slices which results in a reduction in radiologist reading time.

More efficient detection can also be achieved when performing a contrast mammography examination. It’s possible to combine the power of Contrast Enhanced Mammography (CEM) with 2D and tomosynthesis images all in one compression to provide anatomical and functional imaging in a singular exam. The use of comprehensive imaging using co-registered functional and morphological information can reduce reading time to seven – ten minutes versus thirty to sixty minutes for a standard breast MRI[4],[5].

Almost 43% of women over 40 years old have dense breast tissue that can obscure lesions on traditional 2D mammograms, making cancers harder to detect and recalls more likely[6]. Women with very dense breasts have a four to five times greater risk of developing breast cancer in comparison to women with less dense breasts[7].

This is where new AI–powered technologies have the potential to help identify women who are particularly at high risk of breast cancer, specifically those women with extremely dense breasts.

Assessing women using automated breast density analysis software is a simple way to ensure that those most at risk of developing breast cancer are prioritised for screening, on potentially a more regular basis, whilst the screening interval for those women at lower risk could be extended, creating a more efficient and personalised breast screening program in the longer term.

Diagnostic innovation is on a trajectory that we cannot ignore. It is evident that AI is sure to revolutionise healthcare. There will be multiple benefits associated with the adoption of AI technology in breast imaging for patients and clinicians alike; for example, enhanced clinical confidence, improved workflow efficiencies, accelerated disease detection and increased accuracy of breast cancer diagnosis. Hologic is proud to be leading the way with its AI solutions for our customers and partners, helping to save time and lives across the breast health continuum of care.

1 Philpotts L, Kalra V, Crenshaw J, Butler R ‐ Radiological Society of North America 2013, SSK01‐09

[2] Friedewald SM, Rafferty EA, Rose SL, et al. Breast cancer screening using tomosynthesis in combination with digital mammography. JAMA. 2014 Jun 25;311(24):2499-507.

[3] Olivia DiPrete, Ana P. Lourenco , Grayson L. Baird, Martha B. Nov 2017. Mainiero. Screening Digital Mammography Recall Rate: Does It Change with Digital Breast Tomosynthesis Experience?. Radiology: Volume 286: Number 3—March 2018

[4] Cancer.org. 2022. What Is a Breast MRI? | Breast Cancer Screening. [online] Available at: <https://www.cancer.org/cancer/breast-cancer/screening-tests-and-early-detection/breast-mri-scans.html&gt; [Accessed 28 April 2022].

[5] Julie Sogani,a Victoria L. Mango,a Delia Keating,a Janice S. Sung,a and Maxine S. Jochelson. Contrast-Enhanced Mammography: Past, Present, and Future. Clin Imaging. 2021 Jan; 69: 269–279.

[6] Sprague BL, Gangnon RE, Burt V, et al. Prevalence of mammographically dense breasts in the United States. J Natl Cancer Inst. 106(10), 2014.

[7] Ingrid Schreer. Dense Breast Tissue as an Important Risk Factor for Breast Cancer and Implications for Early Detection. Breast Care (Basel). 2009 May; 4(2): 89–92.

ADS-03644-EUR-EN Rev 002

See the latest BIR special publication on Breast Imaging and AI

A Roadmap to Enterprise Imaging

Steve Holloway

Steve Holloway, from Signify Research explores the daunting challenge of navigating the road to Enterprise Imaging.

Cloud technology is transforming how we live and work today. For healthcare providers undergoing long-term digitalisation, the potential of cloud technology resonates, yet the complexities of adoption are daunting and difficult to navigate. Nowhere is this more evident in healthcare than imaging informatics.

A front-runner of healthcare digital innovation, the imaging sector has a complex legacy of on-premise, siloed, best-of-breed applications that interact with and influence every point of the care continuum.

Many providers have taken the positive steps of embarking on an enterprise imaging strategy, federating imaging service line applications, centralising data management and transforming access for diagnosticians, care givers, and patients.

Progress on this mission has been challenging however, in part due to an over-reliance on aging on-premise applications and limited availability of alternatives.

Today, a new generation of cloud-based enterprise imaging solutions is emerging, offering a tangible route to cloud. In this paper, we’ll identify the key characteristics of this new generation of cloud-based products and outline the key drivers and barriers to their adoption.

Further, we’ll describe the long-term transformative power that cloud offers for enterprise imaging and the future of healthcare provision, providing our view on the key considerations for providers navigating cloud adoption for enterprise imaging.

DOWNLOAD WHITEPAPER HERE

Innovation Through a Pandemic – How to survive when there’s nothing to report

Dr Gareth Davies describes the massive impact the COVID 19 pandemic had on elective cross-sectional reporting, reducing output to almost zero. Here he reflects on how the drive for innovation and the motivation to think differently led to a better teleradiology service for both patients and staff.

Dr Gareth Davies

The pandemic will certainly define us as an organisation. A period of uncertainty, business survival, the protection of our staff and their livelihoods and a readiness to provide a clinical service our patients rely on.

Let’s go back to the 1 January 2020. It was a time when the UK’s radiology reporting capacity was at a tipping point, backlogs of unreported examinations were in the thousands, demand for imaging services was constantly increasing, and more and more patients were being scanned.  Just in one single day in that month, Telemedicine Clinic (TMC) reported over 1400 elective cross-sectional scans to its NHS customer base.

Wind the clock forward to May 2020, and during the midst of the Coronavirus pandemic a grand total of 11 plain films were reported in a whole week.

TMC’s business is teleradiology, a service that underpins delivery of clinical services to the customers it reports for. Take away the need for outsourcing by having to stop elective scanning and there is no need for teleradiology.  Take away elective scanning and the backlogs built up over time can be cleared.  The reset button had been pressed and no one knew what was going to happen next.

TMC employ over 300 radiologists, with over 50 radiologists working in the emergency section. The recovery for this section was quick with demand returning  to normal volumes after 3 months. The recovery of the elective service has stalled in line with countrywide lockdowns but is now about 60% and getting busier.

So how did a company that had 50% of its business disappear overnight survive? The simple answer was innovation!

Response team

The first thing TMC did was to call on its European based radiologists, staff, and management teams to team up to provide an unrivalled knowledge-share hub. Coronavirus imaging from hospitals all over the world was collated to provide real-time COVID reporting best practice as the world started to understand the virus more.  In addition, top thoracic specialist radiologists from Europe who had already experienced COVID radiology were called to report cases for NHS hospitals.  A new “24/7 COVID response” reporting team was established in less than 2 weeks. 

On the back of our experience with the 24/7 COVID Response service, the TMC Academy used our reporting experience and best practice from other nations experience to create two COVID-19 online reporting modules on the TMC Academy platform and made these free to all to view and learn from.

Platform

Our next step was the deployment of the TMC Platform for our NHS customers. Where TMC had a contract in place with a Trust who also had reporting radiologists collaborating with TMC, TMC enabled the radiologist to work for their hospital using the TMC infrastructure and IT, free of charge such that the radiologist could work remotely reporting their cases, where home reporting was not available at that time. Driving down costs to our customers in the future is a focus of TMC.

TMC is proud of its recruitment process for radiologists. Our traditional model was to invite potential colleagues to our head office in Barcelona, to undergo a series of interviews and undertake test case examinations specific to their subspecialty. What do you do when you need to recruit radiologists in a period of complete lockdown, with the inability to travel even a few miles? You challenge your teams to virtualise a 3-week induction/test period of course!  This was completed again using the online TMC Academy platform to make sure all radiologists were fully vetted, interviewed, examined and quality-assured to comply with our standards and strict working regulations required to support  the UK market and the NHS.

Hub

Prior to the pandemic, TMC were aware of a growing need for acute reporting services ranging from neuro MRI ad hoc reporting to Emergency CT daytime cover to sub-specialist short turn around reporting. One of our major ambitions during this period was to innovate more integrated clinical care and break the traditional concept of teleradiology and the clearing of backlogs and night time on call. TMC are good at elective reporting and using UK and European based radiologists. TMC are also good at UK overnight Emergency CT reporting from wide awake UK and European radiologists who have moved to Australia. However, there is a mix of requirements that TMC did not fully cater for and the NHS desperately requires. From conversations with customers, it was clear that elective reporting, although destined to return with a vengeance, was not the priority. The main driver in fact was a mixture of acute and semi-urgent work so, from this, The TMC Hub and TMC Oncology concepts were created.  

Any time of the day or night, a clinician, radiographer, or radiology manager can call TMC to discuss scanning a patient.  These can be emergency patients in the day or night, they can be acute inpatients who simply need that next step in their pathway or to be discharged safely, or perhaps just a routine scan which feels urgent. The TMC Hub can help put the patient on the right pathway for their care, anytime day or night, Monday to Friday or a weekend.  TMC’s customers love the new HUB concept, it provides a real safety net that they can contact us to get a patient scan completed, all within the hospitals set guidelines.

Artificial Intelligence

Last but not least, during the pandemic, TMC has had the opportunity to establish a dedicated team to evaluate the plethora of AI products on the market and implement products which we believe will improve patient care. Through stringent evaluation, TMC now has a number of AI products in place to assist its radiologists in making a clinical report.  For the emergency section, AI now looks at all CT PA examinations for pulmonary embolism (PE), subtle C-spine fractures in trauma scans and intracranial haemorrhage in CT brains. For elective services, the AI software looks for PEs in all CT examinations that involve the thorax as soon  as the examination arrives in the TMC PACS.  In our new low dose CT thorax reporting for the NHS lung screening / lung health check service, we are using nodule detection and automated reporting to the requirements of the NHS QA standards for such a service.  And new to TMC’s repertoire is a novel service, bringing AI to its clients without them knowing it.  Through TMC’s IT infrastructure, our AI solution can look at ALL images in a customers PACS to identify incidental PEs, assign them to a TMC radiologist for immediate reporting which is flagged to the clinician team on-site in real-time.  A scan that could have waited 3 weeks for reporting with unknown downstream costs to the Trust.    AI will not replace radiologists, but it will improve radiology workflows, something which TMC can help clients do.

Benefits

With innovation comes benefit, a benefit that can be passed on to our customers in terms of reduced costs for delivery as well as reduced costs further down the patient pathway. Innovative services such as the TMC Hub or the TMC Oncology service will give clients the confidence they need to get a scan reported first time by the most appropriate and qualified radiologists.

Teleradiology and outsourced radiology are looked upon as a cost to the NHS which needs to be removed. With over 90% of NHS services relying on overnight emergency services being delivered from the independent sector, it is hard to see how this will change any time soon.  Instead, looking at how teleradiology can help underpin service delivery, provide the AI analysis and expertise, provide the IT network to telework over international borders whilst using capacity from Europe to add to the overstretched UK workforce, the question should be how can we integrate more with our providers to deliver value-driven innovative healthcare to all people. 

About Gareth Davies

Dr Gareth Davies, UK Medical Director Head and Body Section (Full time employed)
Dr Davies has 18 years’ experience as a Consultant Radiologist in the South Wales NHS prior to joining TMC in 2019. He has a specialist interest in interventional and oncological radiology and held various national roles including the Regional Specialty advisor for training in Wales  (Royal College of Radiologists), a member of the Clinical Radiology Specialty Training committee (RCR), Lead Radiologist and Lead QA of the Wales Abdominal Aortic Aneurysm Screening Programme (WAAASP), Associate Medical Director of Cancer Diagnostics and the Clinical Lead of the Early Cancer Diagnosis Programme, Wales Cancer Network and member of the Clinical Advisory Panel for CRUK. Since Joining TMC, Dr Davies has been involved in helping form TMC Oncology as well as working within the UK Business Unit to develop a more clinically integrated approach to telemedicine with the NHS forming the TMC Hub concept.