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Leading hospital in Cyprus offers Digital Breast Tomosynthesis
YGIA Polyclinic’s Radiology Department has been operating for 27 years and its staff is actively involved in ongoing clinical research and training to ensure the best possible services to all patients. A year ago, it embarked on setting up a breast imaging unit equipped with state-of-the-art technology, culminating in the installation of the Hologic Selenia Dimensions DBT system.
Dr. Annie Papoutsou, Head of the X-ray Department gives us the full picture.
How has your hospital expanded in recent years?
In 2007, after major renovations and an extension of its building facilities, the YGIA Polyclinic private hospital boosted its capacity to 152 beds, extended the number of operating theatres to 12, established and extended the capabilities of its Clinical Laboratory Department, Radiology Department (X-ray, Mammog, Fluoroscopy, MRI, CT, Ultrasound), produced a multi-dynamic Intensive Care Unit (ICU), Obstetrics & Gynecology, and Pediatrics Departments. Furthermore, from mid June 2012, a state-of-the-art Cardio-Vascular Catheterizations Centre was established at the hospital offering the only 24-hour acute percutaneous coronary intervention (PCI) service in Cyprus. Moreover, the hospital has a range of fully equipped ambulances working 24 hours in order to be able to best respond to emergencies.
What type of equipment is used by your department?
Most of our X-ray rooms use the latest DR digital detectors providing superior quality images almost instantly, and are linked to an enterprise-wide fully integrated RiS/PACS.
Last year we organized a breast imaging unit, equipped with the latest technology, FFDM Hologic Selenia Dimensions, a GE ultrasound with strain and shearwave elastography and a Hitachi ultrasound with high frequency linear probe.
In our department we performed more than 90,000 exams yearly.
What was the rationale for selecting the Hologic Selenia Dimensions system?
The decision was based on the special features offered by the Selenia Dimensions; these include:
- 2D imaging or combo mode (2D+3D) imaging in the same compression.
- Exceptionally sharp images with minimal dose.
- Streamlined workflow.
- Ergonomic design for comfort and ease of operation.
- We believe that it offers the best technology available.
What are the advantages of Digital Breast Tomosynthesis?
The use of Digital Breast Tomosynthesis in breast screening enables us to find more invasive cancers than conventional 2D mammography alone.
The masses, distortions and asymmetric densities are better visualized with the Selenia Dimension.
But also it can reduce the costs associated with unnecessary recalls and it can reduce the incidence of negative biopsies.
Has the number of exams been affected by the adoption of DBT?
Since the installation the number of mammography exams has increased up to 50%.
The recalls rate has decreased and also additional views have decreased.
When did you decide to acquire the C-View software and what are the benefits?
C-View software was installed from the first day of the equipment installation, giving us the possibility of eliminating the need for conventional 2D exams after 6 months. The combined tomosynthesis and C-View exam makes lower patient radiation dose possible. Tomosynthesis exams with C-View software offer a patient dose similar to a 2D only exam with superior clinical performance for all breast types.
You are also using the Affirm biopsy device –what is the typical biopsy procedure followed in your department?
Up until now we are using the Affirm stereotactic biopsy device and in the next few days we are going to install the Affirm stereotactic tomosynthesis biopsy device to target lesions seen only with tomosynthesis. The typical biopsy procedures followed in our department are the biopsy under the stereotactic guidance and hookwire localization for subtle masses clusters of microcalcifications and architecture distortion.
What do you see as the next step for improving the performance of your department?
Installing I-view with the contrast media.
I-View is a contrast-enhanced mammography technique that may be a viable alternative to breast MRI in performing contrast agent breast imaging. It offers certain advantages over MRI, including reduced cost and shorter procedure times. The imaging combination of contrast enhanced 2D imaging (CE2D) along with a 3D tomo scan, gives additional information beyond a CE2D examination alone, and may allow localization and morphologic evaluation of an enhancing lesion, further increasing the value of the CE2D procedure.
Anesthesiology and ultrasound today
Since the last decade, ultrasonography (US) has become an essential clinical tool in anesthesiology, intensive care and emergency medicine, improving both safety and patient comfort. US indeed allows an extremely wide use for both bedside examination and technical procedures in a way that was previously not possible. For example, this technology is useful for regional anesthesia [1], but also for placing central venous access with a reduced risk of complications, for assessment of gastric emptiness [2], or for an early assessment of severe trauma patients [3]. Recent reports even suggest that US may be interesting in airway assessment and in predicting difficult airways [4], or to assess lung function and conditions such as pneumothorax, pulmonary edema [5] etc. It is no longer possible to work as an anesthesiologist without having immediate access to bedside high quality ultrasonography.
Among various techniques of regional anesthesia, peripheral nerve blocks (PNBs) consist in anesthetizing only a single limb or a specific anatomical area. A huge body of scientific evidence demonstrates that PNBs provide major interests during perioperative patient care in many surgical specialties. As a matter of fact, PNBs are even frequently superior to general anesthesia. However, PNB techniques require expertise and technical skills, since it is necessary to administer the local anesthetic in close vicinity of nerve trunks or nerve roots in order to interrupt the nerve impulses.
To summarize, the overall safety in regional anesthesia requires the ability to avoid injecting local anesthetic intraneurally as well as intravascularly, and to reduce the injected doses. This is where US plays a role.
Ultrasound-guided regional anesthesia has allowed increasing safety standards and reducing complications as never before [6]. When using US guidance the anesthesiologist is able to identify the various anatomical structures and adapt the procedure to inter-individual anatomy. Furthermore, US guidance allows real-time needle guidance and assessment of local anesthetic spread around neural structures, which was not allowed by previous PNB techniques that were using nerve stimulation [7]. Visualizing the spread of local anesthetic also enables early diagnosis of intravascular or intraneural injection. Furthermore, there is now scientific evidence that US guidance decreases the number of vascular punctures as well as reduces the injected volumes of local anesthetics while increasing the overall success rate of PNBs. Moreover, USGRA improves patient comfort [8].
If ultrasound devices designed for the operating theatre must provide high quality images, all usual imaging modes and at least two probes of compact size enabling the ultrasound systems to be mobile, the recently released EXAPAD, manufactured by the French ECM company, opens a brand new concept of mobile US devices that are designed no longer for the radiologist or cardiologist, but for anesthesiologists and emergency physicians. It features many unique and original tools that make this device really innovative and exceptionally adapted to the operating room or intensive care environment. The EXAPAD comes with a nice and sober look, as a ‘big’ 15′ tablet. It is as easy to use as a smartphone allowing the user to swipe from one menu to another. It is indeed, the first US device having been specially designed for use in intensive care, operating room or in emergency situations where the physician frequently works in a narrow space, surrounded by many devices and under sterile conditions. Therefore, the size and mobility of the EXAPAD are of tremendous importance. For example, the EXAPAD may be orientated either vertically or horizontally according to preference by simply rotating the screen.
The EXAPAD’s new features, such as the IPAD remote control and the voice control of all major settings (i.e. gain, depth, frequency, focus) allow the physician to change the settings without the need to touch the screen. This is highly interesting during sterile procedures (i.e. PNBs or central venous access placement). Another advantage is the fact that the central unit is totally waterproof and its screen can be cleaned.
The IPAD remote control also displays the US image. At the bedside, this tool is not a gadget, but on the contrary offers a real improvement in comfort for the anesthesiologist, since the EXAPAD central unit may
be located ahead of the patient, providing full performance of the system on the IPAD while enabling the user to change the settings and view the image on the IPAD screen. The EXAPAD also offers the possibility, via the Internet or a local network, to share US images in real time for teaching purposes or for remote use of the system.
References
1. Chan VW, et al. Ultrasound guidance improves success rate of axillary brachial plexus block. Can J Anaesth. 2007; 54:176-82.
2. Bouvet L, et al. Clinical assessment of the ultrasonographic measurement of antral area for estimating preoperative gastric content and volume. Anesthesiology. 2011; 114:1086-92.
3. Wiel E, Rouyer F. From E-FAST to clinical echography. Ann Fr Anesth Reanim. 2014; 33:149-50.
4. Pinto J, et al. Predicting difficult laryngoscopy using ultrasound measurement of distance from skin to epiglottis. J Crit Care. 2016; 33:26-31.
5. Moreno-Aguilar G, Lichtenstein D. Lung ultrasound in the critically ill (LUCI) and the lung point: a sign specific to pneumothorax which cannot be mimicked. Crit Care. 2015; 19:311.
6. Barrington MJ, Kluger R. Ultrasound guidance reduces the risk of local anesthetic systemic toxicity following peripheral nerve blockade. Reg Anesth Pain Med. 2013; 38:289-97.
7. Macaire P, Singelyn F, Narchi P, Paqueron X. Ultrasound- or nerve stimulation-guided wrist blocks for carpal tunnel release: a randomized prospective comparative study. Reg Anesth Pain Med. 2008; 33:363-8.
8. Bloc S, et al. The learning process of the hydrolocalization technique performed during ultrasound-guided regional anesthesia. Acta Anaesthesiol Scand. 2010; 54:421-5.
The author
Xavier Paqueron, M.D., Ph.D.
Centre Clinique
16800 Soyaux, France
Artificial intelligence and radiology – threat or tool ?
In spite of alarm bells that artificial intelligence (AI) would decimate the radiology profession, a host of barriers – both technical and regulatory – make this unlikely to happen for the foreseeable future. Instead, over the coming decade, AI is at best likely to help radiologists do their jobs more quickly and lead to improved patient outcomes.
From CAD to AI
AI in radiology, in some senses, has tended to raise the same level of expectation as computer-aided detection (CAD) did for the profession in the 1990s. Indeed, there is now a distinction between computer aided detection which reduces observational oversight and false negatives in interpreting medical images, and computer aided diagnosis (also called CAD) – by virtue of which software is used to analyse a radiographic finding to estimate the likelihood of a specific disease process (e.g. a benign versus malignant tumour).
As a result, in spite of tens of thousands of machine-learning algorithms, there is little connection to clinical application. Most remain confined to the realms of research.
The Black Box barrier
Radiologists, for example, use visual pattern matching. However, few object recognition algorithms have yet been tested on gray-scale images, such as those widely used in radiology.
Though specific algorithms could in principle be tailored for specific tasks, they use different assumptions and targets, and often are written to function in different modalities. Consolidating a set of algorithms into one package and then using this to underpin image or data analysis is not feasible.
In effect, the key problem with CAD detection is its black box’ nature, which means they cannot explain why an object has been identified as abnormal. Many users remain suspicious about sharing the already-grey zone between detection and diagnosis with a machine, which only provides probabilities.
Sensitivity and specificity
The above kind of issues also hinder AI. Nevertheless, the technology is rapidly evolving and may offer some solutions to new challenges.
Like radiologists, AI faces the twin pulls of sensitivity and specificity, between false positives which overcall disease and false negatives which undercall it. It is clear that it will favour sensitivity over specificity.
Technology creates its own momentum
In recent years, radiologists have been forced to cope with an explosion in the stock of medical images, thanks to modern imaging technologies and PACS storage capacity. In the UK, for example, almost 5 million CT scans are performed per year by the NHS. At the upper end, a single pan scan’ CT of a trauma patient, for example, renders about 4,000 images. Indeed, a busy radiologist can read about 20,000 studies a year.
To deal with this burden – both physical and visual – radiologists clearly need help. AI seems to have become one of the most optimal.
There is, nevertheless, some irony here. Technology, in this case consisting of new imaging modalities, has led to an increase in the workload on radiologists. This is in spite of the fact that the disease burden has remained more or less the same, as has the prevalence on imaging of clinically significant pathology. However, the growth of imaging stock has led to a sharp rise in the presence of detectable and potentially significant pathology. Radiologists therefore face the massive challenge of finding ways to use the latter. This is where yet another technology, AI, steps in.
Industry push combines with radiologist pull
While the need to handle the imaging data explosion will see radiologists pulling’ AI, industry has chosen radiology to push’ for clinical validation. There are two reasons for this: the sheer volume of the imaging data and its continuing growth make it a huge market, while the fact that it is stored in structured and computer-readable DICOM format means it is a ready one.
AI’s own dynamics in change
Meanwhile, AI itself has seen some changes. Although, fuelled by science fiction and Hollywood, the popular imagination associates AI with self-awareness, what we really still have is more accurately machine intelligence. The implications of even such a toned-down definition should, however, not be under-estimated. Neither should some recent developments.
From Deep Blue to AlphaGo
In the late 1990s, IBM’s Deep Blue supercomputer defeated grandmaster Garry Kasparov in a chess game. In March 2016, Google DeepMind’s AlphaGo defeated Lee Sedol, a 9th level Go grandmaster 4-1. For AI experts, the AlphaGo win is far more impressive than Deep Blue because Go is less rules-bound than chess.
Due to these constraints, Deep Blue analysed millions of potential combinations and outcomes, in what IT professionals call brute force’ calculation. No computer can yet achieve this with Go, which according to Business Insider’ (March 10, 2016) has ‘more than 300 times the number of plays as chess. Alongside continuous scenario analysis, top Go players require both experience and intuition’. This is why AlphaGo’s win was seen as a paradigm shift in AI.
Deep learning
Unlike Deep Blue’s brute force, AlphaGo used a programming method called deep learning’, with so-called neural networks, which are far more similar to human thought processes than traditional computing. Rather than seeking to map out every possible move combination, deep learning (DL) is a relatively-unregulated process by which a computer figures out why something is what it is, after being shown several examples. It uses a large but still-finite sample of data, draws conclusions from that sample, and then, along with some human inputs, repeat the process over and over again, to simulate millions of games into a decision-making system.
Technically, AlphaGo’s deep neural networks consisted of a 12-layer network of neuron-like connections with a policy network’ to select the next move and a value network’ to predict the winner of the game.
A new benchmark
Neural network-based deep learning is now the benchmark for AI in radiology, with IBM’s poster child Watson leading the way. At the 2015 RSNA meeting, Watson showed its capacity to find clots in brightly shining pulmonary arteries.
Watson, however, has a DL rival in Australia’s Enlitic, which has developed a lung nodule detector claimed to achieve positive predictive values that are 50percent higher than those of a radiologist. As the detection model analyses images, it learns from those images. It not only finds lung nodules, it also provides a probability score for malignancy. Enlitic is now conducting a trial on a model to detect fractures using X-ray images overlaid with a heat map to highlight their location within a conventional PACS viewer. The clinical application will eventually encompass X-ray, CT, and possibly MRI. At the moment, Enlitic is working to incorporate ACR guidelines into it.
Although both Watson and Enlitic use deep learning, the approach is different. Watson seeks to understand’ a disease, Enlitic simply seeks to find source problem data, solve it, and produce a diagnosis.
Another DL developer is MetaMind, since last year part of CRM (customer relationship management) giant Salesforce.com. MetaMind has an alliance with teleradiology provider vRad to identify key radiology elements associated with critical medical conditions, especially in the latter’s focus area of emergency departments (EDs). The first tool to emerge from the partnership was an algorithm to identify intracranial hemorrhage (ICH), often seen in ED patients and requiring prompt action. vRad, which has put the algorithm into a beta phase that will allow it to collect data to demonstrate outcomes, is adapting it to identify other critical conditions, such as pulmonary embolisms and aortic tears.
Swarm AI
Apart from deep learning, radiology is also seeing the first successful experiments with swarm AI, which helps form a diagnostic consensus by turning groups of human experts into super experts. The technology borrows from nature, which sees species accomplishing more by participating in a flock, school or colony (a swarm’) than they can individually. One study, published in Public Library of Science (PLOS)’, stated that swarm intelligence could improve mammography screening and has the potential to improve other types of medical decision-making, ‘including many areas of diagnostic imaging.’ Another study found that accuracy in distinguishing normal versus abnormal patients was significantly higher with swarm AI than the radiologists’ mean accuracy.
Challenges ahead
Nevertheless, there is much more to be achieved before AI becomes an everyday tool in radiology.
The biggest roadblock will consist of regulators, who are unlikely to sanction the use or marketing of intelligent’ machines. In the US, as first of their kind, they lack the predicate devices needed to be regulated under the FDA’s 510(k) rules, and it would take decades to get approval for each algorithm.
A second issue is the time and cost to get datasets to fine-tune the algorithms. Watson, for example, has a backlog of 30 billion medical images to review.
Thirdly, the algorithms would also raise significant legal and ethical issues, such as knowing when they could be trusted.
Finally, even were such machines to become available, referring physicians are unlikely to accept conclusions or interpretations drawn solely by them.
The scale of such challenges has already been seen by developers of computer-aided detection (CAD) algorithms – and the change of CAD to detection’ rather than diagnosis’, as it was called in the early days.
Need and benefit, reality checks
In short, for now, radiologists need AI just as much as AI needs them.
Radiologists will have to begin to work with AI, both to improve the technology itself and to reduce routine, repetitive tasks such as confirming line placements and looking at scans to find nodules.
On its part, AI is likely to become an increasingly smarter tool, to improve efficiency, for example by prioritizing cases, putting thresholds on data acquisition, improving workflow by escalating cases with critical findings to the worklist of a radiologist and providing automatic alerts to both radiologists and other concerned clinicians.
In the longer term, DL algorithms are likely to be trained to recognize disease patterns, identify, outline and measure nodules and possibly highlight suspicious areas in images. This is likely to be followed by the use of DL-based AI as clinical decision tools, for example to help referring physicians select or narrow choices of scans, based on clinical observations in an EMR. Such steps would not only free up resources for additional testing but also improve patient care, thereby making radiologists even more integral in the care management process.
In the final count, a resonant reality check on AI has been provided by Eliot Siegel, MD, professor of radiology at the University of Maryland. He has offered to wash the car of anyone who develops a program than can segment adrenal glands on a CT scan as reliably as a 7-year-old.
Dose reduction in medical radiation – regulators, industry and healthcare professionals seek common front
Ionizing radiation, from the sun and even the earth, is a daily fact of life. There is little that can be done about this, except to stay away from too much sunlight and protect the skin with sunscreens. On the other hand, people are also sometimes exposed to radiation for medical reasons – such as diagnostic X-Rays or CT scans, or a range of interventional radiology procedures. These procedures offer tremendous benefits for patients and for healthcare providers. The evidence for such benefits has become indisputable in recent years, and covers a wide range of diseases and conditions.
Medical imaging has profound impact on patient management
The American Journal of Roentgenology’ reported in 2011 that abdominal surgeries reduced significantly after CT scans. Physicians planned to admit 75percent of patients to hospital before CT. This level was changed to hospital discharge with follow-up in 24percent of patients after CT. The conclusions of the researchers, from Massachusetts General Hospital, were conclusive: CT ‘changes the leading diagnosis, increases diagnostic certainty, and changes potential patient management decisions.’
Massachusetts General Hospital was indeed one of the first institutions to study the impact of medical imaging. In 1998, a team from the hospital reported that CT was 93-98percent accurate in confirming or ruling out appendicitis. The condition accounted for 1 million patient-days per year in the US, with a similar level eventually found to have other conditions.
From emergency rooms to lung cancer
More recently, the New England Journal of Medicine’ published a study on non-invasive coronary CT imaging in the emergency room. The study found that out of the 8 million visits per year to emergency rooms by patients with chest pain, only 5-15percent were eventually found to be suffering from heart attacks or other serious cardiac diseases. As many as 60percent of patients faced unnecessary admission and testing to exclude acute coronary syndrome.
Meanwhile, it has also been reported that low-dose CT screening reduced lung cancer deaths by at least 20percent in a high risk population of current and former smokers aged 55 to 74. These findings were reported by the National Lung Cancer Trial in the US.
Fight against Alzheimer’s, speeding up clinical trials
In the future, medical imaging holds forth significant promise as a tool in the fight against diseases ranging from osteoporosis to Alzheimer’s, whose incidence is likely to grow sharply as the population ages.
Medical imaging also offers increasing promise as a surrogate endpoint in clinical trials, allowing measurement of the effect of a new drug far earlier than traditional endpoints, such as survival times or clinical benefit.
Concerns about over-use, some alarmist
Nevertheless, there are several concerns about over-use’ – especially for imaging accompanied by radiation such as CT. In the US, according to a June 2012 review in the Journal of the American Medical Association’, CT scans tripled in the period 1996-2010, corresponding to a 7.8percent annual increase. Although this was less than a near four-fold increase in MRI and a 30percent fall in nuclear medicine use, CT has been the target of sometimes emotive campaigns.
One good illustration of this was an Op-Ed in the New York Times’ on January 31, 2014. The article was titled ‘We Are Giving Ourselves Cancer.’ It opened with the observation that we are ‘silently irradiating ourselves to death,’ while its closing sentence urged finding ways to use CTs ‘without killing people in the process.’
The Times’ Op-Ed cited a British study which ‘directly demonstrated’ evidence of the ‘harms’ of CT, and it is here that its authors over-stretched their credibility. The study they referred to was published in Lancet’ in August 2012 and titled Radiation exposure from CT scans in childhood and subsequent risk of leukemia and brain tumours: a retrospective cohort study’. Its authors used data on 175,000 children and young adults and found that the cumulative 10-year risk was higher in relative terms, but translated into one extra case of leukemia and one extra case of brain tumour per 10,000 head CT scans.
ALARA and the principle of necessity and justification
In other words, while few would argue that there is no risk from radiation, it is clear that such risks are small and that even these small potential risks could be controlled further by reducing exposure to radiation.
Both industry and healthcare professionals are endeavouring to ensure that such a goal is achieved.
Manufacturers of CT and other radiation imaging equipment seek to keep exposure to radiation for both patients and medical staff to a minimum – and below their regulatory limits – by using the ALARA (As Low As Reasonably Achievable) principle to design their products. Key methods include use of the most dose-efficient technologies available and seeking to ensure that optimum scan parameters are used for a patient and examination type.
Meanwhile, in the clinical setting, doctors seek to ensure that radiation imaging examination is ordered only when absolutely necessary and justified, while radiographers optimize the radiation dose used during each procedure.
Safety, information and awareness
Since the mid-2000s, radiologists and medical physicists have taken steps to increase controls on radiation risks to patients. These have essentially focused on promoting the safe use of medical imaging devices, supporting informed clinical decision making and increasing patient awareness.
One of these initiatives is known as Image Gently, a collaborative initiative by radiology professional organizations and other concerned groups. Its target is to specifically lower radiation dose during the imaging of children.
A related initiative, led by the American College of Radiology (ACR) and the Radiology Society of North America (RSNA), is Image Wisely. This is essentially an awareness campaign whose goals are to eliminate unnecessary’ procedures and lower doses to minimal levels required for clinical effectiveness when necessary. One aspect of Image Wisely is collaboration between medical radiologists and manufacturers to improve performance of radiology equipment and allow physicians to make real-time assessments of whether radiation levels are acceptable.
Initiatives by professional societies
Such initiatives are closely supported by professional radiology societies. The ACR has developed Appropriateness Criteria (corresponding to the federal requirements on appropriate use) to assist referring physicians and radiologists in prescribing the best imaging examination for patients – based on symptoms and circumstances. One tool consists of the display of imaging options and associated radiation levels for a specific procedure. The aim is to reduce imaging examinations by assuring that the most suitable exam is done first.
In Europe, the European Society of Radiology’s flagship EuroSafe Imaging’ has the same objective, to maximize radiation protection and quality/safety in medical imaging. The initiative was launched at the European Congress of Radiology in 2014 and has so far attracted over 50,000 individual supporters (known as Friends of EuroSafe Imaging’). Over 200 institutions (industry and healthcare providers) have also endorsed the initiative.
Accreditation programmes
Accreditation programmes are also being targeted by the ACR and ECR, in order to assess facilities based on imaging competence, adherence to latest dose guidelines, and personnel training. Given the pace of technology development in imaging, certified radiology and nuclear medicine professionals are increasingly recommended or (in some cases) required to earn continuing education credits on radiation safety.
In Europe, the ECR has joined forces with the European Federation of Organizations for Medical Physics (EFOMP), the European Federation of Radiographer Societies (EFRS), the European Society for Therapeutic Radiology and Oncology (ESTRO), the European Association of Nuclear Medicine (EANM), as well as the Cardiovascular and Interventional Radiological Society of Europe (CIRSE) on an EU-promoted radiation education project called MEDRAPET. The findings, published in 2014, revise the previous Radiation Protection 116 Guidelines on Education and Training.
The Bonn Call for Action sets roadmap for the future
Many of these initiatives have been inspired by a conference held in Bonn, Germany, at the end of 2012, which was sponsored jointly by two United Nations bodies – the International Atomic Energy Agency (IAEA) and the World Health Organization (WHO). The outcome of the conference, which was attended by participants from 77 countries, is known as the Bonn Call for Action, and aims to strengthen medical radiation practices into the 2020s.
The Bonn Call consists of ten major actions. These are described below:
- To enhance implementation of the principle of justification. There is explicit emphasis on the use of clinical decision support (CDS) technology towards such a goal.
- To enhance implementation of the principle of optimization of protection and safety. There is a specific call to ensure the establishment, use and regular updating of diagnostic reference levels for radiological procedures, including interventional procedures, and to develop and apply technological solutions for patient exposure records, harmonize dose data formats provided by imaging equipment and increase utilization of electronic health records.
- Strengthen manufacturers’ role in contributing to the overall safety regime. This seeks to enhance radiation protection features in the design of both physical equipment and software, and to make these available as default features rather than optional extras.
- Strengthen radiation protection education and training of health professionals.
- Increase availability of improved global information on medical exposures and occupational exposures in medicine, with specific attention to developing countries.
- Improve prevention of medical radiation incidents and accidents. One interesting facet here is a call to work towards including all modalities of medical ionizing radiation as part of a voluntary safety reporting process, with specific emphasis on brachytherapy, interventional radiology, and therapeutic nuclear medicine, in addition to external beam radiotherapy.
- Strengthen radiation safety culture in healthcare.
- Foster an improved radiation benefit-risk-dialogue.
- Strengthen the implementation of safety requirements globally.
- Develop practical guidance to provide for the implementation of the International Basic Safety Standards in healthcare globally.
Although some of the Bonn Call points are repetitive, the document is noteworthy in terms of setting a minimal set of common rules for a very wide range of stakeholders – manufacturers, health professionals and professional societies.
Point 6 seeks new work on effective’ dose
Point 6 of the Bonn Call is both ambitious and timely. Although the concept of effective dose’ (or effective dose equivalent) was introduced in the mid-1970s to provide a common framework for evaluating the impact of exposure to ionizing radiation via any means, technology’s uneven leaps have not made it easy to follow through. Data for doses by different radiographic imaging modalities used in radiation therapy are scattered widely through literature, making it difficult to estimate the total dose that a patient receives during a particular treatment scenario. In addition, interventional systems are often configured differently from diagnostic set-ups and imaging systems do not distribute radiation in similar ways. For example, planar kV imaging attenuates rapidly along the line of sight, while CT dose is uniformly distributed through a patient. This makes it difficult to sum dose in a radiobiologically consistent manner.
Mobile health – a potentially disruptive technology ?
Mobile health or mHealth has recently become one of the fastest growing and potentially disruptive segments of healthcare technology. Some typical mHealth segments include medication reminders, remote patient monitoring and wellness management. Key challenges faced by mHealth include data storage and management, network availability and maintenance, compatibility and interoperability. The single biggest issue however is considered to be security and privacy – in terms of access control, infrastructure integrity and data anonymity.
M&A, drug costs and mHealth shake up US healthcare
In December 2015, consultants PricewaterhouseCoopers (PwC) said that mHealth ranked just behind mergers & acquisitions (M&A) and the escalating costs of prescription drugs as a key factor shaking up US healthcare.
PwC noted that one reason for such an impact was mHealth’s status as a late starter. Smartphones and apps have been relatively underutilized by the healthcare industry, and playing catch-up has catalysed an ultra-fast pace of growth. The consulting firm noted that 71% of US adults now own a web-enabled smartphone or wireless device and users with health or fitness apps doubled from 16% to 32% in 2015 compared to the year before.
Other figures endorse the enthusiasm about mHealth.
93% of US clinicians now believe that mHealth apps can improve patient’s health, according to a GreatCall survey on their rising popularity. This is well above a level of just 52% in 2013, according to a survey cited by US telecoms carrier Qualcomm. That report also noted that another 16% percent also noted ‘that the use of mobile technology will dramatically change the way that healthcare is delivered in the future.’
Europe and mHealth
The picture is more nuanced in other parts of the world.
In Europe, for example, Pew Research figures show smartphone penetration is roughly equal to US levels in northern countries such as Sweden, Denmark and the Netherlands, as well as on the other side, in Spain. The levels are 60-70% in Germany and the UK and 50% in France. These three, together, account for 45% share of the European mHealth market.
There also are some major differences between European countries in the mHealth climate, as another recent report, by Germany’s r2G, shows. As a result, usage of ePrescription varies dramatically, from 0 all the way to 100%. In Europe, regulatory differences can indeed have profound implications for mHealth. For example, ‘remote treatment of patients is prohibited’ in Germany, ‘whereas in Spain telemedicine is encouraged.’
In spite of being Europe’s largest economy, Germany remains a major challenge. According to a report from FTI Consulting, ‘only 28% of German hospitals have a clear strategy’ on digital healthcare. In spite of this, a proposed new law on eHealth ‘does not even mention the opportunities’ provided by mHealth (or personalized medicine). In effect, Europe has some way to go before it approaches mHealth benchmarks in the US, where doctors in several states can ‘bill health insurance companies for the costs of email-based consultations,’ according to a survey by A.T Kearney.
India among most mHealth-ready
Overall, revenues in the global mHealth market are expected to rise annually at a rate of 33.5% between 2015 and 2020, based on forecasts in an Allied Market Research report. Leading the pack will be the Asia-Pacific, with a growth rate estimated by Allied at more than 35%.
India is a special case for several reasons. Although Pew reports penetration of just 17% in the country in 2015, India recently overtook the US to become the second largest market for smartphones, after China (where penetration is much higher, at 58%).
Indeed, the speed of growth in the Indian market has surprised experts. As recently as August 2015, researchers IDC were forecasting that India would surpass the US in smartphone sales, in 2017.
India is in fact considered as one of the most mHealth-ready markets, in spite of a per capita income which is still among the world’s lowest. A survey in 2012 by PwC and the Economist Intelligence Unit (EIU) explained the reasons for the paradox: ‘In developed markets, mHealth is perceived as disrupting the status quo, whereas in emerging countries it is seen as creating a new market, full of opportunities and growth potential…. Consumers are more likely to use mobile devices and mHealth applications, and more payers are willing to cover the cost of mHealth services.’ The report notes that the pace of adoption of mHealth ‘will likely be led by emerging markets that rank highest among ten countries on a score of mHealth maturity.’
Demand driven by both business and consumers
The Indian case in the PwC/EIU survey illustrates one of the salient features for mHealth, everywhere. mHealth technology is both B2B (business-to-business) as well as B2C (business-to-consumer). Indeed, it is consumers who are pulling mHealth, in both developing and industrialized countries. This is probably less for cost than for reasons of access ( anywhere, anytime’ diagnosis, monitoring and treatment). The title of the PwC/EIU report underscores such an observation: ‘Consumers, it says, ‘are ready to adopt mobile health faster than the health industry is prepared to adapt.’
4 million downloads a day
Overall, the near-frenzied enthusiasm for mHealth is illustrated by figures from German consultant R2G. Even in 2014, it says there were over four million downloads of mHealth apps every day.
The number is expected to keep growing. By 2017, it’s predicted that 50% of smartphone users will have downloaded mobile health apps.
Hospitals and mHealth
In spite of the incipient mHealth consumer boom, heavy-hitters in industry are also marshalling their mHealth strategies.
Hospitals and health plans see mHealth as a tool to contain costs and enhance efficiency, and enhance healthcare safety and quality too. A growing number of top hospitals have begun to incorporate mHealth – the use of mobile technology devices and smartphones for healthcare purposes – to connect patients and clinicians, improve care coordination and reduce avoidable, costly hospital readmissions.
In the US, one driving force for mHealth consists of reforms imposing penalties on hospitals for avoidable readmissions. Although hospital readmissions fell from 19% in 2011 to 17.5% in 2013, more can clearly be done. According to Kaiser Health News’, 2,225 hospitals paid 227 million dollars in penalties during 2013 for high hospital readmission rates.
The reforms have provided strong incentives to implement mHealth systems – for example, to track cardiac rhythms, glucose levels and vital signs, and to identify health issues in time so as to prevent repeat trips.
Evidence for this kind of direct benefit from mHealth is provided by the prestigious Mayo Clinic, who report that use of a smartphone app during cardiac rehabilitation can reduce hospital readmissions by a factor of three. Mayo researchers found that only 20 percent of cardiac patients who used the app visited the emergency department or were readmitted to the hospital within 90 days, compared with 60 percent of those who did not use it.
The role of mHealth in increasing efficiency is apparent from Canada’s Ottawa Hospital. The Hospital and IBM have launched a mobile-enabled platform to streamline workflow and create a circle of care’ around patients. Care providers have 24/7 access to patient information, collaboration tools and available hospital resources via a custom mobile app, which has enhanced process efficiency, leading to more accurate discharge scheduling and reducing over-occupancy rates from levels of 110 percent.
European hospitals are also enthused about mHealth. In Britain, the National Health Service is encouraging remote medical monitoring and mobile health access as part of the country’s digital healthcare revolution, according to a report in The Telegraph’. The programme, which focuses on greater efficiency in providing medical services, includes use of wearables, video link consultations, e-prescription and connected clothing. Its objective is to make virtual healthcare ubiquitous within five years and save the NHS up to 5 billion pounds over a decade.
The pharmaceutical industry and mHealth
The pharmaceutical industry, too, has got into mHealth, with hundreds of mobile apps providing information on drugs, drug interactions and enabling patients to track usage. A study by Avella Specialty Pharmacy found apps focusing on HIV medication significantly boosted adherence. Despite this, it has ‘lagged in mHealth app development and adoption,’ due to concerns about liability and the need to follow strict regulatory compliance.
There are three other reasons for the lack of success. Pharma company app portfolios are not globally available. It is also built around their core products, rather than market demand. In addition, there is no cross-referencing, or a common and recognizable design providing a corporate identity.
Profiling mHealth apps
At present, some sources estimate that there are over 100,000 mobile health apps that have been developed. 85% of the apps are for wellness, while the remaining 15% (or 15,000) are directed at medical purposes. Even though a late starter, as many as 42% of mHealth apps available in major stores have a paid business model.
Nevertheless, the bulk of mHealth apps are forced to struggle.
A November 2015 survey of the global market by R2G found that 62% of app vendors attained less than 5,000 downloads per year for their entire mHealth app portfolio. 11% percent reached over 100,000 downloads. Just 2% had 1 million-plus downloads. Of the latter, about half had been in the business before 2010.
R2G said that as many as 60% of developers of mHealth apps were dissatisfied with the market reception for their apps. Many also found that the performance of the apps fell short of their goals.
The survey also reported that over half mHealth app developers were technology companies, and they viewed the presence of medical professionals on their team as a priority. In terms of targeted customers, patients with chronic conditions were most common, accounting for 48% of apps. Hospitals are the second biggest target, with 32% of developers focusing on them.
Another finding of interest was the fact that the most successful vendors were more likely to develop apps for hospitals as opposed to patients. This may be one of the strongest indicators that the mHealth apps industry still has to mature, and that there is much more to come. During the same month as the R2G survey, New York University School of Medicine released another mHealth report. The study found that though consumers frequently downloaded mHealth apps they ‘don’t necessarily use them a lot.’
For consumers at least, there is much more to explore in mHealth.
Digital breast tomosynthesis – evidence of superiority versus mammography, but more research needed
Digital tomosynthesis creates a three-dimensional (3-D) picture using X-rays. In this respect, tomosynthesis is close to a CT (computed tomography) scan. Nevertheless, there are differences between the two. In fact, the development of CT is considered to be one of the reasons for a decline in interest in tomosynthesis, until recently.
One of the principal applications for tomosynthesis today is breast cancer. The basic difference between a digital breast tomosynthesis (DBT) and conventional mammography lies in detail. DBT removes confusing overlying tissue, thus providing clearer imaging and clarity. It also has improved low contrast visibility over mammography, even at a reduced dose. Some explain the difference between DBT and mammography as that of a ball compared to a circle. Nevertheless, in spite of its higher accuracy, the X-ray dose for DBT is similar to that of a mammogram.
Tomosynthesis and CT
Tomosynthesis is now increasingly seen as a low-dose alternative to CT, and is being evaluated against both CT and radiography in several areas, such as erosion in arthritis, or fractures accompanied by metal artifacts.
Technically, tomosynthesis combines digital image capture with the tube/detector motion of CT. However, there are several differences. In CT, the detector makes at least one complete 180-degree (half circle) rotation around the subject. Images are then reconstructed from this data. Tomosynthesis uses a far smaller rotation angle and a lower number of discrete exposures than CT. The lack of comprehensiveness in projections, compared to CT, is compensated by digital processing – with reconstruction of slices at varying depths and thicknesses. The result is that the images are similar to CT, but have a lower depth of field. The reduction in projections, as compared to CT, cuts down on both radiation dosage and cost.
Mammography : the approaches
A mammogram is basically an X-ray examination. However, it uses a machine designed specifically for examining breast tissue. The X-ray format in a mammogram is different while radiation dosages are lower than a conventional X-ray. One of the problems with the latter is that X-rays do not easily penetrate breast tissue. In a mammogram, two glass plates compress the breast to spread out the tissue allowing for a better and more accurate image, using less radiation.
Mammography, formally known as full-field digital mammography (FFDM), usually takes two X-rays of the breast from above (cranial-caudal view, CC) and from an oblique or angled view (mediolateral-oblique, MLO). Single-view mammography uses only the MLO view, and was widespread in the early days of screening. However, it has lower sensitivity and higher recall rates, compared to two-view mammography. Theoretically, the only advantages of single-view mammography are less radiation (which is especially important for young women, who are more sensitive to radiation) and quicker examination speed.
Breast cancer and the mammogram
Breast cancer shows as a typically denser zone than adjacent healthy breast tissue in a mammogram, where it appears as an irregular white area or shadow’.
The term digital’ mammography sometimes confuses patients. However, it simply applies to the storage medium. While regular mammography provides film pictures, digital mammography records images on a computer.
The DBT procedure
While a mammogram is a modified X-ray machine, DBT is delivered by a modified mammogram. It positions the breast in the same way as a mammogram. However, the compression required is less than the latter, in effect just enough for preventing the breast from movement. The X-ray tube then moves around the breast in a circular arc, typically taking 11 X-ray images of 1 mm thickness from different angles, usually over 10 minutes. The images are synthesized by a computer into a clear and highly-focused 3-D image throughout the breast. This allows specialized breast radiologists to see clearly through layers of tissue, including dense tissue, and examine zones of concern from a full range of angles.
Patient comfort is a factor clearly favouring DBT. The breast compression required for a mammogram can be uncomfortable and even sometimes painful, deterring several women from getting tested.
The challenge of false negatives and positives
From a clinical perspective, the high degree of breast compression required by a mammogram can also result in causing folds and overlaps in breast tissue, which can hide the cancer. In other words, negative results do not a guarantee that a woman is cancer-free. The false negative rate is estimated to be as much as 15-20percent. It is also higher in younger women as well as in women with dense breasts.
On the other side, mammograms also face major challenges from false positives. A mammogram may show areas that are considered suspicious or abnormal. This is followed by additional tests (further mammograms, ultrasound and MRI, or an invasive breast biopsy).
One study, published in the May 2014 issue of Annals of Internal Medicine’ found that after 10 years of annual screening mammography, more than half of women will receive at least one false-positive recall.
Some estimates find that 75-80percent of all breast biopsies are unnecessary – that is, they do not find cancers, and 7-9percent receive a false-positive biopsy recommendation. In general, the higher effectiveness of DBT means that patients require fewer (unnecessary) biopsies or other tests.
DBT and multiple tumours
Tomosynthesis also has another major advantage. It has a far greater likelihood than mammography of detecting multiple tumours (which occur in about one in 7 breast cancer patients).
History of DBT
Massachusetts General Hospital (Mass General) in the US is generally credited with pioneering the development and implementation of DBT into a screening programme. In 1992, the hospital’s specialized breast imaging team began researching application of tomosynthesis. In March 2011, just one month after breast tomosynthesis was approved by the US Food and Drug Administration (FDA), Mass General announced that it had performed the first clinical DBT exam in the US. In 2014, the hospital adopted breast tomosynthesis plus mammography as standard protocol for all breast screening.
The hospital states that breast tomosynthesis research in large populations consistently shows ‘improved breast cancer detection rates, especially invasive cancers’ as well as a ‘decrease in call backs, which may lessen anxiety for patients.’
DBT not yet standard of care
Even though digital breast tomosynthesis is now FDA-approved for more than five years, it is not yet considered the standard of care for breast cancer screening. A 2009 recommendation from the US Preventive Services Task Force (USPSTF) has recently been updated. However, it observes that current evidence still remains insufficient to assess the benefits and harms of DBT as a primary screening methodology for breast cancer.
Nevertheless, DBT is available at a small but growing number of US hospitals. These are generally licensed and accredited by the FDA as well as the American College of Radiology (ACR).
DBT in Europe
In Europe, the European Reference Organisation for Quality Assured Breast Screening and Diagnostic Services (EUREF) has recently updated its breast tomosynthesis protocol (version 1.01). Key changes concern technique and methodology (back-projection, dosimetry etc.).
European breast cancer experts frequently cite US studies that show a significant decrease in recall rate using DBT as adjunct to mammography, as well as the increase in cancer detection rates.
Meanwhile, there have recently been several European trials on DBT.
STORM: DBT versus 2D mammograms
The results of one of the first European trials, known as Screening with Tomosynthesis OR standard Mammography (STORM), were published in 2013. This was a prospective comparative study conducted at the University Hospital of Trento, Italy. It sought to determine if DBT overcame some of the limitations of conventional 2D mammography for detection of breast cancer.
The findings were conclusive. The authors of the study estimated that conditional recall could have reduced false positive recalls by 17.2percent without missing any of the cancers detected in the study population.
DBT and mammography combinations studied in Norway
Combinations of DBT with reconstructed 2D images or standard (digital) mammography have also been investigated for screening in Norway.
The Norwegian study was led by a team at Oslo University Hospital, Ullevaal. It sought to compare the performance of two versions of reconstructed two-dimensional (2D) images in combination with DBT versus standard FFDM plus DBT.
Cancer detection rates over two different periods were 8.0 and 7.8 per 1,000 screening examinations for FFDM plus DBT, and 7.4 and 7.7 per 1,000 screenings for reconstructed 2D images plus DBT. False-positive scores were 5.3percent and 4.6percent (over the two periods for FFDM plus DBT, respectively), and 4.6percent and 4.5percent (for reconstructed 2D images plus DBT).
The conclusion of the Norwegian study, published in the June 2014 issue of Radiology’ was clear:
‘The combination of current reconstructed 2D images and DBT performed comparably to FFDM plus DBT and is adequate for routine clinical use when interpreting screening mammograms.’
Sweden: DBT versus mammography, and combinations
Meanwhile, a trial in Sweden, known as the Malmo Breast Tomosynthesis Screening Trial (MBTST), published its results in 2015. MBTST claims to be the first trial designed to assess the efficacy of one-view DBT versus two-view mammography in brast cancer screening, along with a combination of one-view DBT and one-view mammography versus two-view mammography. The authors, from the University of Lund’s Malmo campus found ‘a significant increase in cancer detection rate when using one-view DBT as a stand-alone screening modality, compared to two-view DM (digital mammography). The recall rate increased significantly but was still low.’ They concluded that one-view DBT might be feasible as a stand-alone breast cancer screening modality.
DBT and ultrasound
European researchers have also sought to go beyond comparing DBT with mammography alone. In March 2016, the European CanCer Organisation (ECCO) released interim results from a trial called ASTOUND (Adjunct Screening with Tomosynthesis or Ultrasound in Mammography-negative Dense breasts) at a conference in Amsterdam.
ASTOUND has been recruiting asymptomatic women who attend for breast screening at five imaging centres in Italy and who have extremely dense breasts (defined by the BI-RADS Breast Imaging and Reporting and Data System as being in Categories 3 and 4).
The researchers, led by Dr. Alberto Tagliafico, a radiologist and Assistant Professor of Human Anatomy at the University of Genoa, Italy, have found that adding either DBT or ultrasound scans to standard mammograms could detect breast cancers that would have been missed in women with dense breasts.
Outlook for the future
In general, whether in the US or Europe, more remains to be done to conclusively establish the advantages of DBT in screening. However, it is indisputable that DBT does results in a significant increase in cancer detection rates.
An article in the April 2016 edition of Breast Cancer’ by P. Skane (who led the Norwegian trial mentioned above) argues that ‘DBT should be regarded as a better mammogram that could improve or overcome limitations of the conventional mammography, and tomosynthesis might be considered as the new technique in the next future of breast cancer screening.’