New Year Thoughts About the Past Year and 2017


The Biotronics3D team wishes you the warmest wishes for a joyous season!

Title: The Madonna of Port Lligat
Artist: Salvador Dali
Medium: Oil on Canvas
Location: The Patrick and Beatrice Haggerty Museum of Art
Time: 1949
Dimensions: 19 in x 15 in

2017 and the celebration of New Year’s Day is almost here! As we plan for the coming year, I have been thinking about the past year and how our team in Biotronics3D  has continued to dynamically change and grow in the market.  The implementation of new methods and procedures continues to allow us to alter products and services to meet emerging and growing needs and to better serve our customers.  We have also taken a fresh look at our goals for the coming year, many of which are outgrowths of the past year’s initiatives and explorations.

Here is some of what has changed in our world in 2016:

  • We have reached the milestone of 15,000 registered users.
  • In 2016 our innovation became global; the 3Dnet system is used daily across 14 timezones (from San Francisco, USA all the way to Tbilisi, Georgia!).
  • Based on ample anecdotal evidence, at least 15% increase in referrals is what some of the Imaging Centers running our system report.  They attribute that mainly on our online technology and our tools which makes it possible for them to engage better with their referring doctors and strengthen their relationship.

The team at Biotronics3D looks forward to what 2017 will bring for us.

While we plan on pursuing even more partnerships and collaborative ventures with medical imaging providers, we will continue to explore what our users need in terms of expertise, services and features as well as satisfaction with what we offer.

The following are a few areas we plan to focus on more depth in 2017.

  • to launch our new product (code named “3Dnet-Edge”)
  • to  manage the successful roll-out of our system to cover the complete operations of our 3 strategic customers (a Herculean task on its own).
  • to try to reach and even exceed two milestones: the “25,000 registered users” milestone AND the “deployed in 25 countries” milestone. We call them the milestone “25”.
  • to implement better approaches for co-creating with our partners, the medical image providers and the medical image innovative companies.
  • to implement new technologies bringing information and services to our 3Dnet users and their patients whilst increasing cohesion within our 3dnet community.

I would love to hear your thoughts, suggestions and ideas for 2017! Please share at

Shall we Uberise healthcare?

The Doctor exhibited 1891 by Sir Luke Fildes 1843-1927

Title: The Doctor
Artist: Sir Luke Fildes
Medium: Oil on Canvas
Location: Tate Britain
Time: 1891
Dimensions: 1664 x 2419 mm

I can’t remember where it was – perhaps waiting for yet another flight to board at yet another anonymous airport in Europe- when I received a call from Ed Rudd, our chairman. He was very excited about the concept Uberisation of our modern economy, he kept on talking how most of the business plans he receives (Ed is a keen investor among other things) try to Uberise their market. The Uberisation of everything, he said “To Uberise, to replace the middleman is the theme of our times.”

Last week I was discussing with Soeren the new version of our system (soon to be released), and all of a sudden my discussion with Ed sounded very familiar. Our new version once more pushes the boundaries of innovation in our market, the core difference being that we now offer a system that positions the patient at the centre of the clinical workflow. We do that by enabling multi-directional communications amongst the care-givers in a true patient centric model. Effectively, by doing that we replace the middleman, and interesting enough I believe we make the first step to Uberise Radiology.

For those living in the last two years on a different planet, I think I should explain what Uber is.

Like the gigantic health systems (NHS and the likes), the taxi business model was inefficient, not mobile, and as any passenger using a minicab in London on a Saturday night can testify, often very unpleasant.  It was a model built around the needs of taxi drivers and their companies, rather than me and you, the needs of the guys paying for their services.  Mobile technology and the internet has existed for over a decade, but the taxi industry has simply refused to embrace it, holding on to its old ways. Enter Uber, a Silicon Valley startup.  It uses a mobile platform.  It is GPS-enabled.  It allows you and me, the passenger to rate the driver.  It’s paperless.  It’s efficient. It reduces the cost of service. And while Uber has faced regulatory pushback in almost every country launched, its innovation has seriously disrupted the existing models and it has been handsomely rewarded.  Regulation typically drafts behind, not ahead, of innovation (Brussels please take notice!).

Today we are seeing a major shift in healthcare globally, mainly brought by cultural and socio-economic forces.  The population is ageing and chronic conditions requiring management during patients’ daily lives are on the rise. Alongside these issues, we are seeing widespread connectivity emerge across all economic classes.  Portio Research estimates some 6.9 billion cell phones are currently in use worldwide. That’s up from 2 billion in 2005, according to Wireless Intelligence. My mother, for example with no prior experience in computers, bought a tablet 2 years ago and within a month not only did she manage to skype her grandchildren but also to send her MRI scans to a consultant in the Mayo Clinic for a second opinion.

Technology has set all of this change in motion. We are already seeing more empowered patients. In our company we call those patients the “super patients”, the ones who are very close to Dr.Google.  People want information. They want to make their own diagnosis.   They want to research their doctors.  They want to find ways to get to be 100 years old and still enjoy quality of life. They want to have instant access to clinical skills regardless where they are.

I imagine a world in the next 30 years that looks like this:  Patients receive personal care around the clock.  Virtual coaches and doctors work with patients to optimize day-to-day preventative care.  Everyone has their own virtual care team that lives with them in augmented reality.  Meanwhile, primary care physicians (real humans) are assigned to a pool of patients who they monitor remotely, supported by a team of real human specialists. But much of the “personal” connection will be done through virtual humans (maybe there is a place for IBM’s Watson AI system in healthcare after all, you clearly need the machines to help us with the deluge of clinical information overload, the clinical information obesity).

And in this brave new world, medical Imaging will be asked to play a major role. I think it will be the catalyst driving the next evolutionary step in healthcare. Why? Because Medical Imaging is the only way to present a pretty accurate picture of the anatomy and pathology of a person remotely, to a doctor miles away.

Today doctors say, “Use this medication”  or, “Use this pump; it’ll save your life,” and they assume that patients will readily adopt these products. But what we see happening is that as new products are created for the modern patient, companies will have to shift their focus toward how these products fit into the larger context of people’s lives. Understanding and meeting patients’ needs and desires will become a bigger differentiator, and more crucial to adoption than ever before. And technology and the internet will be the vehicle for this transformation.

It all starts now.  Healthcare must shift its focus toward the patient.  There is no other way. Healthcare services should put the patient’s needs first and foremost. This is what Biotronics3d, our company is doing with our new product. Just as Uber has demonstrated with putting the passenger first, ignoring the patient will be fatal for health solutions companies: they will be the new taxi drivers, baffled by how the world has passed them by.

At Biotronics3D we are building the next Uber-like disruption in the Medical Imaging service.

And in this new framework the Radiologist will evolve to a new role where the patient is in the centre of the workflow.

I think I ought to add a postscript to this blog. There are many modern thinkers, as Andrew Keen in his book “The internet is not the answer” is very keen to emphasise. He claims that drawing on the formidable example of Uber, billions could be made by destroying taxi unions, to cite just one example. Another example is Dr Jay Parkinson, who on Sep 2007 launched probably first Uber-like medical services, using the internet to connect directly patients with doctors. His venture sadly lasted only 6 months and argues that Uber-like business models in Healthcare are doing a massive disservice to our system, and that we all should focus more on doctors’ efficiencies.

I would passionately disagree.

And although I think we should always listen to this new generation of naysayers, the post 2000 internet has provided the catalyst for business growth, by putting conventional business models on steroids, and by accelerating the evolution of everything. An exponential acceleration… Just consider that: when a kid with a laptop working from a beach in Mexico could invent Instagram, a photo-sharing app, and singlehanded bring Kodak, the old giant of photography, to bankruptcy, it is obvious that organisations and companies that fail to understand and adopt the new business models will have the same future. And “Uberise everything” is the new kid in the block, dinosaurs who fail to understand and evolve fast, will die regardless their size.

The Internet of Medical Things: Were is the next Claude Shannon when you need one?


Title: Galatea of the Spheres
Artist: Salvador Dali
Medium: Oil on Canvas
Location: Dalí Theatre and Museum, Figueres,  Spain
Time: 1952
Dimensions: 65.0 x 54.0 cm

Most of the people working for Biotronics3D started their professional lives and learnt their trade in Academia. As old habits die last and are difficult to forget, it was almost by instinct that right from the beginning we have created and fostered an environment welcoming and promoting research collaborations with UK and EU based Academia. Anyhow, most of our friends work in Academia, and it was only natural that we wanted to keep contact with them. And although this was never part of our original vision (a different technology model- a different business model- a different philanthropy model), nevertheless, collaborative research with Academia quickly became the norm for us.

Today, we all at Biotronics3D are very proud for the copious amount of the collaborative research outcome this company has produced through-out its existence in the past 12 years. We have sponsored, supported and were actively involved with PhD studentships with City University, UCL and ICR in London and the University of Venezuela, we have been active in ample Industry-Academic knowledge transfer partnerships, members of our team frequently lecture at Universities, but most notably we have collaborated in many European wide research projects, often funded by the European Union.

I remember the first European project we participated was under the FP6 framework way back in 2005. It was for the development of an autostereoscopic monitor that was designed to be used for medical Imaging for the diagnosis of diseases. Way ahead of its time, it was very useful for us as we learnt a very valuable lesson: it was very interesting to observe how very innovative products are deemed to fail in the market unless they accompanied by very strong value propositions. As it happened, for autostereoscopic medical graded monitors, the value proposition was not strong enough to justify the extra overhead cost.

Today Biotronics3D is actively involved in 6 collaborative research projects, one is UK based, the others are EU based supported by the H2020 framework. I am very proud that our company is so active in collaborative research, with an output that many academic research groups would had been very keen to have.

But before I explain my theory on IoT, I would like to comment on that chaotic disaster known as Brexit and the very negative impact this will have in collaborative pan-European research (or the result of an ill-fated referendum where a very narrow majority deciding for UK to exit the EU, mainly based on badly constructed and incomplete arguments combined by bone-breaking ignorance and copious amounts of xenophobia). I admit that I am a very big supporter of the unified Europe vision and for me the result was a massive disappointment. I was sad, upset, angry and disappointed all at the same time. After a period of depression that felt like fighting a duel with an invisible enemy (I still cannot understand who the 52% of the UK population are who voted for exit) I have now entered the period of the day after. And I believe this post Brexit UK will be a very sad time for UK based companies and academics wishing to promote collaborative European research. This is sadly the side-effects of Democracy, or how a bunch of misguided hoi polloi can damage, or at least create serious obstacles to academic research with direct negative consequences to the wellbeing of society as a whole. Most of my Academic friends are very worried and very fed up. Because post-millennium it is ridiculous to practice science without the ability to establish close links with other academics in Europe. The times of the monolithic and isolated ivory towers of knowledge belong to the middle ages, not to the modern and fast evolving knowledge based economy. But the 52% of the population was mesmerised by Mr. Farage’s Nazi-inspired demagogic poster of the tragic lines of immigrants desperately trying to enter Europe to seek a better and safe life. Enough of that and please accept my apologies for diversifying from our subject.

The Holy Grail of our current research in Biotronics3D is how to use the Internet of Things (or rather the Internet of Medical Things) and create innovative business models based on that, which the company could exploit commercially. Thus the name of the article of this blog. Let me please explain.

In the late 1940s Claude Shannon invented a mathematical theory of communication that gave the first systematic framework to optimally design digital communication systems. His ground-breaking approach introduced a simple abstraction of human communication, called the channel. Shannon’s communication channel consisted of a sender (a source of information), a transmission medium (with noise and distortion), and a receiver (whose goal is to reconstruct the sender’s messages).

And now this is where it gets interesting. In order to quantitatively analyse transmission through the channel he also introduced a measure of the amount of information in a message. To Shannon the amount of information is a measure of surprise and is closely related to the chance of one of several messages being transmitted. For Shannon a message is very informative if the chance of its occurrence is small. If, in contrast, a message is very predictable, then it has a small amount of information—one is not surprised to receive it. To complete his quantitative analysis of the communication channel, Shannon introduced the concept of entropy rate, a quantity that measured a source’s information production rate. By doing that, singlehandedly he laid the foundations of one of the main cornerstones of the internet (next time your Netflix steam freezes, you can always blame Shannon).

And this is where it gets interesting for us. My theory is that as intelligent devices invade our everyday lives and we connect everything online (aka the Internet of Things or IoT for short) and as we bury humanity deeper and deeper under layers of the unexpected deluge of information overload, I claim that the value proposition of the IoT is directly proportionate to how surprised we are to receive a certain packet of information. In Shannon’s words the value proposition of the IoT is related to the entropy the channel produces and is only loosely and weakly related to the communication channel capacity.

Take one of my favourite research projects my company participates in. The PD_Manager project, a mHealth IoT platform for Parkinson’s disease. ( This is the archetypal Internet of Medical Things project, as it attempts to connect diversified operators to the Biotronics3D cloud for the monitoring and prognosis of PD. The operators include not only a number of very innovative wearable devices, but also clinical mobile applications and data analysers. It is this holistic approach that makes this project so different from other PD monitoring IoT projects. As such you could claim that this project differs because the communication channel capacity is large. However, I believe the most interesting aspect of this project is the inherent entropy that the information carries. And assuming that our research has the ability to construct robust methods to harvest this entropy for the benefit of PD patients, I think we are placing our bets on a very strong horse for the race of IoMT.

Soeren delivered a lectured recently where he claimed (and I would strongly agree with him) that the Internet of Medical Things (IoMT) and cloud based disease management in general is one of the most promising applications of the proliferation of the internet in our everyday lives. In his talk he argued that the three current application directions of the IoMT (and inevitably the Biotronics3D research) are for the care for paediatric and the aged, for chronic disease management and for personal health management.  He then went on to explain that this is not an easy path to follow and there are many challenges, challenges that better to be approached in a multidisciplinary and European-wide manner. For example: how do we manage data integration and device diversity and interoperability? How do we scale humongous size of data for performance yet make sure that all the doors for data privacy and security are properly locked? How do we deal with the evolution of applications and data operators and the need for a new type of medical expertise that uses the internet as a de facto tool for the everyday clinical work? How do we develop new business models that can successfully launch IoMT initiatives?

The following slide is from his presentation and I think it frames the thrust and vision of our research.


PS. A very sad epilogue to this blog:

The value of the network: Metcalfe’s omissions.


Title: Initiation ceremony in Viennese Masonic Lodge, during reign of Joseph II
Artist: Ignaz Unterberger (1748-1797)
Medium: Oil on Canvas
Location: Wien Museum, Vienna, Austria
Time: circa 1786

Last week I was discussing with a very dear friend of mine on the value of modern networks. He is a mystic, a philosopher and a Freemason, and the discussion, although started from the famous Metcalfe’s aphorism of N-squared, grew fast to the point of discussing how social networks start from a selected elite and fast become the tools to be used by the hoi polloi. And as the discussion was flowing fueled by a very nice Cabernet from Chile, and after we discussed the modern market anomalies like facebook, it hit us: Metcalfe’s N-squared is a very old fashioned approximation to the value of a network, and sadly is no longer applicable. In the modern large-scale social and economic systems this equation for sure must take new forms.

Now this is very important for me to understand. Our company, Biotronics3D, wishes to become eventually a community facilitator, and not just a product provider. And although our community is that of doctors, and it is rather elitistic and not accessible to the public, still it is one that has the potential to grow fast to a very large size. Monitoring and measuring the value of our 3Dnet community is paramount to us, as it defines our compass of innovation and growth. For sure it cannot be as simple as N-squared. I am very sorry Mr. Metcalfe, but I think you have ignored a very important dimension of modern networks:

And this is the value of the network related to the Information flowing across it.

My friend’s insights on the subject were invaluable as information (or the secure exchange of it) became an important asset on early Masonic networks.

Based on our company’s experience of facilitating and fostering doctors’ networks, but also my friend’s philosophical insights, we had a go in trying to improve Metcalfe’s equation and this is what we came with:

The personbyte

Doctors need to form networks because of one important consideration: the limited ability of humans to embody knowledge and know-how. To fight their individual limitations, they need to collaborate. Thus they form networks that allow them to embody more clinical knowledge and know-how. Those networks are essential to manage complex diseases that require knowledge and know-how that cannot be embodied in one individual. A new term was introduced recently to signify the maximum personal capacity to hold knowledge: the personbyte. What we have here is the concept of the clinical personbyte.

The concept of clinical personbyte suggests a relationship between the complexity of the activity (for example the complexity of the disease to be managed) and the size of the network to be executed (directly related to the N-squared aphorism).  Activities that require more clinical personbytes need to be executed by larger clinical networks (like for example large academic NHS Trusts). Thus if our theory is right then the value of a clinical network must take into consideration that:

  1. Simple clinical activities will be more ubiquitous (thus the value of a network with those activities is diminished)
  2. Diversified clinical networks will be the ones capable of executing complex disease management activities (thus the value of a network is increased the more multi-disciplinary in nature it is, with varied clinical personbytes across the network).
  3. Over the long run, the value of our clinical network will approach the complexity of the accumulated knowledge.

All those predictions were empirically testable and consistent with all the data we had from our customers. Interesting enough, they became important also in the growth of Masonic lodges in the 20th century.

And as, me and my friend were opening a new bottle of wine, we concluded that as life goes on, and entropy continues to increase, our society continues its rebellious path marked by pockets rich in information; pockets that Erwin Schrodinger (of the feline paradox reputation) used to call the out-of-equilibrium corners of the networks. We constantly form and cull social and personal relationships, make professional alliances, beget children, and of course laugh and cry. This is what Metcalfe saw and tried to measure. But what he didn’t see was the beauty of information on the network. And this is what modern networks are all about: owning the responsibility of perpetuating this godless creation.

I missed you K and I hope we have the opportunities to share our wine more often.

Fifteen thousand reasons to be happy about.


2016 was a landmark year for all of us at Biotronics3D; it was the year that our 3Dnet community of users reached 15,000.

In numerology the number 15 is the number of family and harmony, the number most likely to be in the forefront of innovation. And this is exactly how we also perceive our 3Dnet community, a family of likely-minded individuals striving for innovation in medical imaging. And this is why this number was such an interesting and amazing milestone and achievement for us and we are immensely proud for that.

Today our 15,000 users are spread across 12 countries and work at more than 500 organisations using our system 24/7. We call them internally “3dNet PersonBytes”. Cesar Hidalgo, a professor from MIT, was the first to introduce the concept of a PersonByte, trying to define and to describe the amount of knowledge that one person can reasonable know. This is particularly relevant in the medical domain, a knowledge driven domain, where the size of this knowledge is growing exponentially. The last doctor that successfully managed to have a PersonByte with all the modern clinical knowledge available was Dr. Robert Floyd. The bad news is that he died at 1637, 200 years after Gunteberg and 350 years before the internet. Today clinical practitioners strive for sub-specialisation which is undeniable the one-way highway to the village of Babel: each new medical procedure, each new imaging protocol comes with its own particular embedded ideology and failure to communicate.

In medical imaging especially, the presumptions and dogmas that prevailed Radiology in the era of PACS prior to 2000, are not valid any more. Especially this statement is even more evident when it comes to imaging services which, in my considered opinion, has entered an existentialist crisis (and not just an economic one) due to ever increasing size and complexity of data, the proliferation of imaging outside the confines of Radiology and the incapacity of healthcare eco-systems to withstand the shockwaves of that. As a result, the Radiology PersonBytes are required to take critical disease management decisions whilst suffering from the effects of digital information obesity, stimulus overload and isolated “nichification”.

I believe our  3Dnet community of 15,000, collectively, has the answer to that. I believe the best way to escape the constraints of the PersonByte tower of Babel, is to use technology such as 3Dnet to work collaboratively in even larger teams, something that the modern doctor is very familiar with. This is in line with what Metcalfe defines as the value of the network. The main question here is how easy is this remote collaboration especially when multidisciplinary disease management requires a far more challenging working paradigm and, the very often the exchanged token, is clinical knowledge and not data, something that is tacit, hard or impossible to describe. In Biotronics3D we realise that everyday; with our system, 3Dnet, it’s easy for our users to send medical images and other data around the planet but only data is proven not to be enough. Far from it.  Clinical knowledge and know-how may be weightless in principle but, as Ceasar Hidalgo points out, it’s easier to move heavy copper from mines in Chile to factories in Korea than to move manufacturing know-how from Korea to Chile. Sadly, the same applies in medical imaging today even more than ever.

We perceive the 15,000 PersonBytes in our 3Dnet community as a distributed network of imaging data and clinical skills, and it is very powerful because it consolidates in one place such vast and tacit clinical knowledge. This is the main reason 3Dnet is becoming fast an essential part to organisations of different sizes. It represents a rich source of collective capabilities that are essential to them as it enables them to improve business and clinical processes and outcomes.

And exactly this is our mission, vision and pledge to the clinical community we serve: Disease management and medical imaging is unlikely to become simpler. But our company will raise to this challenge by focusing on social, institutional and technical support that makes distributed clinical collaborations possible and also helps organisations break the vicious cycle of the post-PACS era of commoditised medical imaging and big data.

The war of Analytics vs. Intuition in Medical Imaging.


Title: Weeping Woman
Artist: Pablo Picasso
Medium: Oil on Canvas
Location: Tate Modern, London, UK
Time: 1937
Dimensions: 608 x 500 mm

The first time I became aware of the HIPPO phenomenon in business was around 2000, in one of the companies I worked for. Of course HIPPO is an acronym; it stands for the “Highest Paid Person Opinion”. The company I am referring was a company with decent market share and ample in-house skills, but with a product that had reached obsolescence and to a very large extent was facing a commoditised market. I had an idea about how to pivot that company and restart its growth engine as it rightly deserved. I was convinced that my idea was a good one, assuming it had the backing from the board. Before I presented my idea, I spent time analysing the market and finding the figures to build a proper business case. It was based on the analysis of factual market data and this was the basis for building my arguments. When I was given the floor my 60 minutes presentation was met with much sympathy; I even managed to raise a few eyebrows. But the result was not the implementation of my ideas but instead what the HIPPO proposed. However his ideas were based only on his intuition (and not any data at all) and he went on to justify his proposed strategy on the number of grey hairs he was carrying on his head. To summarise, his idea was to keep on pumping more money into the existing strategy. This HIPPO also had an acute case of Christensen’s “Innovator’s Dilemma” syndrome.


Today I am one of the HIPPOs in my company. My desire is to create processes to de-HIPPO-tise Biotronics3D. I try to build a culture of “Trusting only what your numbers say, NOT what your HIPPOs intuition says”. But my vision and goal also is to help our clients to de-HIPPO-tise their companies. To enable them to take decisions based on real data and not their intuition. And this is what I hope will offer to them.

Take for example the case of one of our customers, a managing director of a small group of imaging clinics in the UK. He recently had a request from two of his clinics to replace their MRI scanners with new ones, but he only had the budget for one this year. How does he know which clinic to favour? The answer is that he doesn’t, unless he has accurate and up to date data for his organisation. Favouring the one that shouts loudest or delivers the best power point presentation is a high risk strategy in my opinion.

I am sure dear reader, at this stage you may quote the “faster horse” statement that Henry Ford once made. To paraphrase, Ford said that if he looked at his data to figure out what people wanted, he would not invent a car but a way to make a horse faster. You may even claim that it is intuition that makes you see “around corners” and helps you innovate and differentiate. If analytics are the bricks of the decision making process, for sure you would say, intuition is the mortar.

But how true is that? Can intuition with no analytics help a group of imaging clinics innovate?

Let us please consider some facts:

To help organisations understand the opportunity of information and advanced analytics, the MIT Sloan Management Review partnered with the IBM Institute for Business Value to conduct a survey of nearly 3,000 executives, managers and analysts working across more than 30 industries and 100 countries. The research was also included a number of US based organisations with medical imaging operations. The key finding was that top-performing organisations use analytics five times more than lower performers with a widespread belief that analytics offers value. The research went even further, attempting to dispel the myth of intuition.  Albert Einstein once referred to intuition as the “real valuable thing”, but, this research found that six out of the ten respondents cited that they use analytics extensively to innovate and achieve competitive differentiation.

We found that organisations who strongly agreed that the use of business information and analytics differentiates them within their industry were twice as likely to be top performers as lower performers.

The research goes even further and attempts to classify all companies in 3 classes in terms of analytics adoption, and how prepared they are to turn challenges into opportunities.

Aspirational. These organisations are the farthest from achieving their desired analytical goals. In Medical Imaging, often they would adopt a traditional PACS and try to focus on efficiency or automation of existing processes, and searching for ways to cut costs. “Do the same for less” seems to be the way of operating. Aspirational organisations currently have few of the necessary building blocks – people, processes or tools – to collect, understand, incorporate or act on analytic insights.

Experienced. Having gained some analytic experience – often through successes with efficiencies at the Aspirational phase – these organisations are looking to go beyond cost management. “Do more with less” is the way they operate. Experienced organisations are developing better ways to effectively collect, incorporate and act on analytics so they can begin to optimise their organisations.

Transformed. These organisations have substantial experience using analytics across a broad range of functions. They use analytics as a competitive differentiator and are already adept at organising people, processes and tools to optimise and differentiate. Transformed organisations are less focused on cutting costs than Aspirational and Experienced organisations, possibly having already automated their operations through effective use of insights. They are most focused on driving profitability and taking strategic decisions as they keep pushing the organisational envelope.

When I read this analysis, my thoughts went to the three stages of Medical Imaging evolution I presented in my last blog. Phase 1, the golden era of PACS, is really all about “Aspirational” health organisations. Phase 2, the era of enterprise imaging, and as PACS became clinical norm, is all about “Experienced” healthcare organisations. However, phase 3, the evolutionary phase where big data changed Radiology and medical imaging, is all about “Transformed” organisations.

In Biotronics3D we came with the idea and had the vision to help our customers thought this evolution. In this process I think we will murder their HIPPOs and help them substantially outperform their industry peers. I am fully convinced that this performance advantage will come from the potential rewards of using our .

The value of Big Data Analytics: “Facts do not cease to exist because they are ignored.”


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Title: painting of Isaac Newton
Artist: William Blake
Medium: engraving
Location: Tate Modern, London, UK
Time: 1795
Dimensions: 460 x 600 cm
“The tree which moves some to tears of joy is in the eyes of others only a green thing that stands in the way. Some see nature all ridicule and deformity… and some scarce see nature at all. But to the eyes of the man of imagination, nature is imagination itself. ” William Blake


Of course the quote in the title belongs to one of my all-time favourite authors, the amazing Aldous Huxley from his book “Note on Dogma”. At the end of the day, this quote represents why our product roadmap points directly in the direction of big data medical imaging analytics and we are adding features in faster than the speed of light.

But why predictive analytics in medical imaging you may ask?

Let’s consider the evolutionary steps of medical imaging after the 90’s.

Phase 1 – The golden era of PACS: At the beginning digital medical imaging, strictly the new toy of the radiology department became an indispensable tool for modern healthcare. We started seeing more images, richer images, performed more often. This was the heroic period of medical imaging, the transition from film to filmless, and the focus was on generating and interpreting digital content.

Phase 2 – The era of enterprise imaging: In phase 2 we realised that the same digital content has more value than what is needed for a radiologist to perform and be efficient. Other healthcare professionals needed to see them, either in the same building or at a remote location.  And to make it even more interesting, it wasn’t just radiology anymore. Many other healthcare disciplines started to generate their own stream of rich imaging data contributing to the digital information obesity. And I am not talking here only about the cardiology department next door, I am talking doctors very often located at remote locations acquiring images.  It is my prediction that the amount of data generated by these other disciplines will overcome the modest needs of the radiology function within this year. Many companies refer to this phase as the era of enterprise imaging and name their offerings appropriately. Perhaps VNA is the illegitimate heir of that era (more on that I hope in another blog)

Phase 3 – when Big Data changed Radiology: And then increasingly healthcare managers and other clinical professionals (even academics) realised that there is a treasure trove of extremely valuable data embedded in those images and associated information; and they collectively raised their hands and requested easy access and a slice of that extreme digital consumption. And soon everybody got in the game. Regulators and auditors asked for access, Insurance companies and other players wanted access, and of course the well informed patient, amply educated by Dr. Google asked nicely if he could please have access. And one day all of a sudden, Radiology is not just about capturing and interpreting images anymore; it is not just about making sure that images are shared in the Enterprise any more. It is about providing different facets of valuable information well hidden within the Big Data Imaging archives, facets based on how you can use them and benefit from them. Welcome to the brave new world and the era of Big Data Analytics.

Because this is what big data medical imaging is all about. Multiple medical imaging producers and multiple consumers of extremely valuable content, difficult to manage using traditional PACS systems. And every time traditional PACS tried to provide an answer to the questions all those varied stakeholders asked, it increasingly felt like being given a car without anyone telling them how to drive it, and without a road map, increasingly driving blind. A car not fit for purpose. That’s a virtual anarchy in medical imaging. will provide the answer to that. Because it is with predictive analytics that we will see the true and essential point in this anarchy of never ending information overload, and we will leave the rest as surplus. Albert Einstein once said that 90% of the data we collect will never be actionable or even helpful, and then he admitted that he made that up because he could not actually measure it. Moreover, what we really hope to offer with is Actionable Analytics, or the discovery and communication of meaningful patterns in medical imaging data that hopefully lead to actions. Ideally those actions should be predictive, shining a light to the future, focusing on the big picture.

The value of Medical Imaging Analytics: “Sustaining high clinical and business performance is a product of continuous strategic alignment.”

The writing is on the wall. Analytics is fast emerging as the “next big thing” in health IT. In Medical imaging, the main culprit for the production of more than 95% of health IT data, everybody realises that analytics is even more important. 3Dnet customers are asking at an  increasingly and alarming rate for advanced tools to get valuable insights to the hidden information wihtin their medical imaging repositories and use that not only to streamline their work and improve efficiencies, but more importantly to help them with their growth strategies whilst improving their clinical outcomes.

Let me please tell you this story. A CEO of one of our large clients with a couple of hundred imaging clinics under his management told me recently:  ”The monthly reports that I get from my guys are of not use to me anymore. I want real time dashboards to provide virtually immediate feedback on my operations. This is absolutely essential to have information at my fingertips and be able to take critical decisions for the growth of my company”. What he was demanding from us, as his technology partners, was to be a big part of his internal digital strategy by providing to him the business analytics he needs and deserves. He wanted to get better and real-time insights of his equipment utilisation and determine each clinic’s efficiency. For example “Is one machine used a lot?” “Are patient wait a long time?” He also demands better insights in personnel utilisation. “How busy his radiologists are truly are?” “Can he come with better ways of utilising their rare and expansive skills?” “Can he merge or blend services to improve the overall outcome?”

We went for dinner and we started talking about all that, the future of medical imaging analytics and the implementation challenges we are facing. We had with us his Chief of Clinical Operations, a very prominent Radiologists and opinion leader. As the discussion was progressing we realised that it is only with analytics that we can provide a solution to one of the most interesting problems of modern medical imaging; that of lack of proper quality control mechanisms and the overall drop in quality of medical imaging. The proliferation of medical imaging outside radiology, combined with the introduction of new and very complicated protocols and scanners and the increasing realisation of lack of the wider availability of proper skills to deal with that amplifies the problem of quality, to a point where it is maybe one of the biggest threats in modern Radiology. Interestingly enough, it is not only us that outline that as a major risk, it is also the American College of Radiology and RSNA in USA and Royal College of Radiology in the UK. Quality control in medical can be addressed either the inefficient way (by manually auditing a random 10% of examinations as NHS recommends but has no resources available to implement), or the efficient way with automated, real time predictive analytics that number-crunch all the examinations of the repository. Our company with 3dNet analytics has embarked in a journey to address that. As Radiology Services are entering the commodity stage, this is the only way to truly de-commoditise this market.

Peter Drucker, one of the gurus of modern management, pioneered the concept of “Management By Objectives,” which shifts the focus from process to goals and to the purpose of the activity rather the activity itself. I believe that this concept will form the new cornerstone of this evolutionary phase of medical image management systems and processes It even has the potential to offer a realistic solution to the problem of medical imaging obesity. Instead of asking, “What do I do?” the medical imaging business and clinical professional will ask, “What is the objective toward which I am working and how do I measure it?”. will enable clinicians to use medical imaging do five things really well:

  1. organize and structure the whole range of available medical imaging data and knowledge,
  2. test these structures,
  3. predict behaviour, and test “what if” scenaria
  4. gauge the soundness of decisions and clinical diagnosis in disease management,
  5. and analyse and improve the performance of the healthcare provision when it comes to medical imaging services.

Inevitably nobody can stop the clinical knowledge progress in the rapid evolutionary phases of medical imaging. If doctors cannot survive all the information the data producers with increasingly create, we are in serious trouble. No one is going to stop creating information, contributing to the medical imaging obesity problem. The quest for the cure of Clinical Nerve Attenuation Syndrome is more urgent than ever, and only medical imaging analytics can provide a sustainable and viable cure.

I think ten years from now, when we look back at how this era of big data in medical imaging has evolved, we will be stunned at how uninformed we used to be when we made business and clinical decisions.

analytics  Analytics at










Medical Imaging Obesity


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TITLE: Prometheus attacked by an eagle
ARTIST: (attributed to) Rene-Michel Slodtz
MEDIUM: Red chalk on paper
LOCATION: Baillieu Library Print Collection, University of Melbourne, Australia
TIME: c. 1750
DIMENSIONS: 31.9 x 53.3 CM

In my last blog I was sharing my thoughts after a visit to a Radiology department in a busy NHS hospital in London. My observation was that, in the age where information has become the most valuable commodity for clinical practice, our Radiologists have become the information Midas.  Like Midas–the mythical king who was granted his thoughtless wish that everything he touched turned into gold, only to discover that he could no longer eat or drink. Similarly, because of the easy electronic access to medical imaging, our modern Radiologists have found that nearly everything they touch turns into digital information to be downloaded, uploaded, archived, VNAed, analysed, reanalysed and rendered. And to amplify this problem, they are under extreme pressure to consume all this information wealth as fast as it is humanly possible. But what is this wealth really worth? In today’s everyday clinical practice, most doctors realise repeatedly that information is only valuable as it is useful.  Is it the case also for Radiology when it comes to Medical Imaging? I am not sure.

In my opinion, it is ironic that Medical Imaging has become a lot cheaper-cheaper to produce, cheaper to manipulate, cheaper to disseminate. One of our customers, a group of family practitioners in Georgia, USA, bought 3 years ago a refurbished 16-slice CT scanner for next to nothing. Of course they used our SaaS 3dnet platform, as the cost model is utility based, and it lets them adjust the costs based on the workload. For years now they have performed imaging procedures (and a lot of them) with almost no Capital overlay and very controlled costs. Yet another example, closer to home, is my brother in law, an orthopaedic surgeon.  He always carries with him a portable ultrasound device, and he has 2 more of them in his office. I estimated recently that every week he produces around 75 scans. Consequently, virtually any doctor can easily become an information hub for medical imaging. Interestingly, the same statement is also valid for patients (but I hope this is the subject of another blog, so let’s forget about it for now). In Medical Imaging, we are now entering the era of big data and the prospect of living with severe clinical information obesity, unless we invent an efficient diet.

Perhaps another observation is that too many medical experts and too much medical information spoil the clarity, dramatically impacts the quality of clinical outcomes, and puts Radiology at a brinkmanship position. In our era of limitless medical data, there is always the opportunity for some doctor, or researcher to crunch more numbers, produce a few more derived images, spin them a bit, and prove the opposite. We, as a company, provide them with the tools to do that. However with the widening pool of elaborate studies and arguments on every side of every question, more expert knowledge has, paradoxically, led to less clarity.

But this information obesity anathema is not only in medicine and medical imaging, it is everywhere around us; just as fat has replace starvation as this nation’s number one dietary concern, information overload has replaced information scarcity as an important emotional, social, and political problem. Every time I open my browser I get overwhelmed and confused with the plethora of information instantly available to me. I feel under pressure to review and understand it, and I feel increasingly frustrated if I don’t. I am sure you feel the same. My dear reader, even this blog contributes to the information obesity you have to suffer. It appears that the real problem for future technologies in medicine and medical imaging does not appear to be the production of information or the transmission of it. Almost everyone and everything can add information. The difficult question is how to reduce it or even better, filter it. How do we go on an information diet.

The whole debate reminds me of my favourite and greatest story of knowledge acquisition and regret; that of the mythical Greek God Prometheus as told by Aeschylus. Prometheus’ punishment for stealing fire and passing it down to human beings was to be chained naked to a pillar where each day a vulture tore out his liver. The liver was divinely replenished each night, and the vulture would return to eat it out again the following day. In the dialogue Protagoras, Plato puts the story in more contemporary perspective. It wasn’t the fire, but it was the techne–the knowledge of how to make things, or the value of information.

If Prometheus was the prophet, then Johannes Gunteberg was the Messiah of making knowledge public domain. And then somebody in the 80s came with the DICOM idea, the absolute Messiah in Medical Imaging. Today, six centuries after Gunteberg, and 30 years after DICOM became accepted by all, computers and the internet have helped Medical Imaging to move faster and become more plentiful. Doctors everywhere can benefit from this change.  Medical Imaging and the associated information, once cherished like caviar, is now plentiful and taken for granted like potatoes.

However, increasingly we can observe the dramatic postscript to this Medical Imaging information highway; it is the nightmarish prophesies of William Gibson, the man who first coined the word, and even the very concept of, ‘cyberspace’ in his novel Neuromancer. In his novels, he describes a future destroyed by information excess-a disease called Nerve Attenuation Syndrome.

So here it goes. My diagnosis after my visit to our customer is that modern Radiologists suffer from the Nerve Attenuation Syndrome mainly caused by severe information obesity.

Is there a cure for it?

Diagnostic Paralysis by Analysis.


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I was visiting one of our customers recently. I admit that this is a favorite pastime of mine.

When we started this company, I was the first salesperson, product manager and marketer, all at the same time, and for years I had been around customers constantly. I have enjoyed that tremendously. However, as Biotronics3D is growing, I find myself increasingly distant from our customers in my day-to-day activities. I do not like that at all. When managing a rapidly growing technology company, it is easy to focus on improving products, systems, operations etc. Sometimes you act as you ignore why and who you’re improving these things for. And answers to those questions are only can be found “out there”, where our customers work, in hospitals and imaging clinics, and definitely not within the walls of the Biotronics3D office, were I work.

Seeking this unfiltered and candid feedback, I stepped through the doors of the fore mentioned customer. And once more there were very important lessons to be learnt. I was very surprised and overwhelmed with the vast amount of work our customers had to do during their day. All the information they needed to understand before they take any action in a very busy, sometime rather chaotic environment. A heap of hundreds of radiology examinations to be interpreted and the heap looked like increasing constantly and not going down. 5 minutes for interpreting a CT study which I would consider a minimum before my visit, I realized that it was a luxury. They were under immense pressure to do more, much more, spending less time, which was once more a big surprise for me. Most of them were at a crisis and breaking point.

But how can the quality of the clinical outcome can be protected when you are asked to operate in such an environment, were meeting targets and increasing throughput is the name of the game? How can you target clinical excellence? Moreover, has our technical innovation, something that we are so immensely proud off, created this problem for them? Have we given them the tools they needed to get greater access to information only for them to discover there is too much of it? Are we the catalyst that multiplied their problem?

As it happens, I am reading these days an excellent book called “Descartes, Spinoza, Leibniz: the Concept of Substance in 17th Century Metaphysics” by Woolhouse, a retired Prof. of Philosophy from the University of York, UK. My visit to our customer reminded me of what I was reading the night before.

Prof. Woolhouse in his book revisits one of the great philosophical battles of all time between seventeenth-century philosophers Rene Descartes and Baruch Spinoza. The debate centered on how people perceive, and at what precise juncture a person decides whether to accept or reject a proposition. Put simply, Descartes suggested that first we comprehend a notion, and then we either accept or reject. In contrast, Spinoza suggested that we first simultaneously comprehend and accept a notion, and only afterward, if we have time, are we able to reject it. Thus Spinoza implies that the rejection of a notion is a secondary psychological act. Prof. Woolhouse argues that intensive psychological testing has proven Spinoza to be correct.

Hold on, let’s think about it for a minute. It seems that my dear Professor’s finding is of critical importance in the context of accurate clinical diagnosis and medical imaging, because under conditions of cognitive overload, Radiologists rarely have the time or the focus to go back and question their initial diagnosis. Mistakes thus are inevitable. Thinking deeply cannot be done when they are (over)loaded. The implications of this for the medical community are extraordinary. Radiologists are almost certain to be increasingly more vulnerable to data solicitation that potentially can lead to making the wrong decisions.

Should our Radiologists celebrate when the next generation CT scanner able of producing few thousand of images per scan arrives in their hospital, or should they seek a different discipline? I am not sure.

If Descartes was living today he could claim that our technology, 3Dnet, not only reduces the amount of time it takes to do any one medical task but also leads to the expansion of tasks that healthgivers are expected to do safely, with a given working day. And assuming he had a different dress sense, I would even had given him an offer to join us in our Sales Department. Actually I saw that “expansion of tasks” phenomenon in action during my visit and it was an eye opener. This is what happens to people when they get computers, faxes, mobile phones and other new technologies. In essence, computers are our modern taskmasters, constantly picking up the pace. When humans can’t keep up in certain tasks, computers simply replace people altogether. If you don’t have the right skills, computers and technology may be your enemy.

I was talking to my ex-wife about that, a brilliant Research Psychologist, and she had some very interesting insights to volunteer for the problem of the intense information overload that our Radiologist have to cope with in their everyday work. She said that recent psychological research in the clinical profession reveals a wide variety of effects from information and stimulus overload:

  1. Overconfidence: as Radiologists are given more clinical information to digest, confidence in their judgment increased, but accuracy did not.
  2. Decreased benevolence: a Doctor’s response to someone needing assistant decreases in likelihood as his environment increases its input bombardment.
  3. Impaired judgment: As clinical information load increases, integrated decision making first increases, reaches an optimum, and then decreases. The old law of diminishing returns applies.
  4. Frustration: Background noise in the form of unwanted clinical information lowers frustration tolerance and cognitive complexity.
  5. Confusion: Radiologists are simply unable to effectively and efficiently process the information.

What is the solution then? Moreover, is there one? Do we switch off our computers and go back to the good old days of film? Do we pretend that this heap of data on our desk does not exist? Nothing is perfect. The good old days definitely were not. The future won’t be. And certainly there is no such thing as technological innovation without tradeoffs. It is not only the luddites that find that hard to accept. The inevitable question thus is how do we negotiate the tradeoffs of the innovation and evolution in Medical Imaging?

Please allow me to list some thoughts in my next blog.


Reliability Is a Tech Problem, but the Way You Solve It Is Not with Technology Alone – It’s with Communication.


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The first time I realised we had a problem was when Soeren stepped in my room and I could see more white than usual in his eyes. It turns out that during a scheduled replication task, a common task that we do almost every day, our team observed a serious performance degradation affecting a small number of our organisations. Further analysis revealed that the root cause was a simultaneous multiple hardware failure. One of my nightmares that prevents me from getting a good sleep at nights has happened.

Our technology team immediately stepped to the mark and took care of the problem. The way they reacted was very impressive. I wish I could say the same for the management of the company.

You see, one of the biggest issues for any cloud company in any market is to ensure reliability of services. With, when doctors use it for clinical decisions that affect human lives, this statement is one thousand times more important. For this reason, we had made massive efforts to ensure that our service, would always be up, (such as establishing multiple resilience across devices, servers and Datacentres), yet we had a problem. Customers quickly began to grumble that the service was not reliable.

When this happened, we actually had an uptime rate of more than 99 per cent, and our service was much better and much more reliable than any traditional Medical Image Management and PACS software. But any disruption was understandably maddening our customers. It took us a few days to restore normal operations for the small number of customers affected by this issue, but during that period we were losing their faith.

For me personally, as the CEO of a cloud organisation, it was an incredibly challenging time. It felt like sailing in uncharted seas with heavy weather. In my mind, I had no doubts for our foundation, our technology model, and its ability to scale as much as it needed to, or its ability to deliver our crazy ideas to the market. Yet with some customers we were hitting a roadblock.

When this happened, I felt that our public response was not our primary concern. I was thinking like an engineer, not like a manager. I thought we needed to focus 100% on fixing the issue and to remain as low profile as possible until the problem is solved. Once everything is fixed, I thought, we could respond with a proper explanation and share the good news. This seemed like the safe response, but yet, I was feeling increasingly uncomfortable about it.

I cannot tell you enough how wrong I was. Because what I did was based on a very antiquated assumption, and this is not how modern companies need to operate. Especially cloud and SaaS companies.

My silence had been a terrible a potentially disastrous strategy. And it wasn’t just the decision not to talk that had been a shocking error, it was that I had not talked immediately. Part of the problem was exacerbated by the very nature of what we do: because we host everything, people could not call their own techies to complain and learn what was happening.

Customers were getting very annoyed. The emails were coming in.

At the end, it was an email I received from one of our customers affected by the issue (who is also a very dear friend of mine) that shook me out of my lethargic self-indulging trance (thank you Phil, I owe you yet another one). Phil wrote:

“We have to accept that an occasional system failure is an unfortunate fact of life despite all our best endeavours and regrettably a system recovery may be the only option available. However for me, this recent issue has been compounded by the lack of notification that a problem had occurred and it consequences. It was only through the repeated logging of faults that the story slowly came out in small pieces. In general your support guys are excellent, very responsive, patient and honest with their observations but it’s events like these that need the next layer of management to co-ordinate directly with the likes of me to give an open and accurate evaluation of the situation so that we can manage things on our side.”

I had to find a way to communicate quickly and candidly – even if going public with this issue felt like a defeat at the moment, a bolt move and a leap of faith was what needed. I convinced the team that we should allow the public – and the competition – to see exactly how our system was functioning every day. It meant that we would be sharing embarrassing details every time the system slowed or stopped working. One of our engineers was very sceptical about it. Why would a company make itself vulnerable in that way? I will tell you why. For one very simple but very important reason:

Only by embracing transparency we can build Trust in the market we serve.

I realised that complete transparency was what we needed if we were to restore trust for the small number of affected users. Moreover, I also considered that by embracing transparency we would encourage good behaviour from our guys as it added a new level of accountability and responsibility. Then in the middle of my crisis, I have decided to do two things at once: send an email and explain what was happening to all our affected users, and to opened up our internal system for everyone to see. We call it the trust site:

The site offers real-time information on system performance with up-to-the minute planned maintenance, historical information on transactions, reports on current and recent phishing and malware attempts and information on our security technologies and best practices. Instead of hiding behind our problems, we started educating customers and prospects about where they could find the information they needed. Let me tell you that, it felt so liberating not to have to act defensively. That night I got a very good night sleep.

There is no question: we would not be around today with 14,000 users, if we were not always bettering the technology and improving its features, speed and reliability. At the same time, I don’t think this unprecedented growth we’re experiencing will be sustainable if we do not embrace transparency. The difficult decision to launch the trust site I think differentiates us even more. As the CEO of the company, I hope and wish Transparency and Trust will be a strong part of this company’s identity and DNA in the years to come.