RSNA2018: What’s in and what’s out.

Let it snow...

The annual radiology tradeshow at McCormick Place in Chicago started with a little hiccup as the Chicago airports closed down on Sunday due to a snowstorm, and slowed the flow of attendees flying in on the second day to only a trickle. Note that the Sunday after Thanksgiving is the busiest travel day of the year so it could not have come at a more inconvenient time. I myself was caught in this travel chaos as I spent all of Monday in the Dallas airport while my plane was trying to get into the arrival queue for O’Hare.

The overall atmosphere at the show was positive, attendance seemed to be similar to last year and most vendors I talked with were optimistic. About a third of the attendees come to the meeting just for the continuing education offerings, but another third come to visit vendors and “kick the tires” and see what’s new. My objective is also to see what the new developments are and to do some networking to get an idea of what is going on in the industry. 

Here are my observations:

1.       Artificial intelligence dominated the floor - Over the past few years, AI has created some

Dedicated area just
for AI showed
80 companies

anxiety as predictions that AI would replace radiologists in the near future. It seems that the anxiety has been relieved to a certain degree, but it has been replaced with a great deal of confusion of what AI really is, and with uncertainty of what the day-to-day impact could be.

A detailed description of the different levels of AI and the main application areas are the topic of an upcoming blog post, but it was clear that the technology is still immature. Despite the fact that there were 100+ dedicated AI software providers, in addition to many companies promoting some kind of AI in their devices or PACS, only a handful of them had FDA clearance. I also believe that the true impact of AI could be in developing countries that have a scarcity or even total lack of trained physicians. It is one thing to improve the detection by a physician of let’s say cancer by a few percent, but if AI could be used in a region that has no radiologists, then an AI application being used that can detect certain abnormalities  would be a 100% improvement.

There could be some workflow improvements possible using AI in the short term, however, one should also realize that the window between conception and actual implementation could be 3-5 years. Users are not too anxious to upgrade their software unless there is a very good reason. So, in short, the AI hype is definitely overrated and I believe that we’ll almost certainly have autonomous self-driving cars before we have self-diagnosing AI software.

a significant dose reduction
 for lung cancer screening

2.       Low dose CT scanning is becoming a reality - One of the near-term applications of AI allows the use of a fraction of a “normal” CT scan. Instead of a typical 40 mAs technique, acceptable images are created using only 5 mAs. This could have a major impact on cancer screening. The product shown did not have FDA clearance (yet) but there is every reason to expect that this can be available one year from now. The algorithm was created using machine learning from a dataset of a million images to identify body parts in lung CTs, and subsequently reduce the noise in those images, which allows for a significant dose reduction, claimed to be 1/20

Extremity
Cone Beam CT

3.       Cone beam CT scanners are becoming mainstream - Cone beam CT scanners were initially
used primarily for dental applications where the resulting precision and high resolution images, especially in 3-D, are ideal for creating implants. However, for ENT applications, such as visualizing cochlear implants and inner ear imaging, its high resolution and relatively low cost makes them ideal. It is also very useful for imaging extremities, again, its high resolution can show hairline fractures well and is superior to standard x-ray. I counted at least 5 vendors offering these types of products; they are being placed in specialty clinics (e.g. ENT) as well as large hospitals.

4.       Point-Of-Care (POC) ultrasound is booming - POC ultrasound is getting inexpensive (between US $2k-15k), which is affordable enough to put one in every ambulance, and in the hands of every emergency room physician, and even for physicians doing “rounds” and visiting bedsides. There are different approaches for the hardware, each with its own advantages and disadvantages:

a.       Using a standard tablet or phone, there is an “app” needed for the user interface, image display, and upload to the cloud and/or PACS. All of the intelligence is inside the probe. However, one of the complaints I heard is that the probe tends to be somewhat heavy and can get very warm.

b.       Using a dedicated tablet modified for this use, it can take some of the load off the probe
for the processing. If the probe is powered through the tablet, it saves on weight as well.

Butterfly POC US, US$2k

Other things to look for is whether a monthly fee is included as several vendors use a subscription model, if it has a cloud based architecture (i.e. no stand-alone operation), and what applications can it be used for. Most of the low-end devices are intended for general use, and have only one or two probes. If you need OB/GYN measurements, you might need to look for a high end (close to US $10k-15k price range).

Also, uploading images into a PACS is nontrivial as one needs to make sure it ends up in the correct patient record of the PACS, VNA, EMR, etc. This is actually the number one problem as each facility seems to deal with these so-called “encounter-based” procedures in a different manner. There are guidelines defined by IHE, but in my opinion with a very narrow scope.

5.       3-D Printing is becoming mainstream - A complete section at the show was dedicated to 3-D  with regard to X3D/VRML models in ongoing. So, before you make major investments, I would make sure you are not locked into a proprietary format and interface.

Many companies showing off
printed body parts

printing. Several vendors showed printers and amazing models based on CT images. The application is not only for surgery planning (nothing better than having a real-size model in your hands prior to surgery) but also for patient education to share a treatment plan. I would caution however that the DICOM standard (as of 2018) includes a definition on how to exchange so-called “STL” models, but the work

There is not (yet) a large volume of these printed models. I talked with a representative of major medical center, who said they do about 5-10 a day, and another institution, i.e. a children’s hospital does about 3 per week. It seems to me that creating orthopedic replacements might become a major application, but then we ae not talking about models you can make with a simple printer that creates objects from nice colorful plastic, but rather one that can compete with the current prosthetics based on titanium and other materials.

6.       Introduction of new modalities - Every year there are several new modalities introduced, which are very promising and could have a major impact on how diagnosis is done in a few years for particular body parts and/or diseases. Examples are a new way to detect stroke by using

Dedicated Breast CT

electromagnetic imaging for the brain. The images look very different from a CT scan, for example, but it gives a healthcare worker the information they need to make treatment decisions. Another new device is a dedicated breast CT device providing very high resolution, 3-D display and is more comfortable for a woman than a regular mammogram. Note that these devices don’t have FDA clearance (yet), but as common for these new technologies, they are deployed in Europe and as soon as the FDA feels comfortable, they be ready for sale in the US as well. On issue with these devices is that there is no real “predicate” device so they need clinical trials to show their benefits.

Equally important to what’s new is also observing what’s “old,” because the technology has become mature, or it has made it beyond the “early-adopter” stage. This is what I found:

1.       PACS/VNA/Enterprise imaging - Over the past few years, PACS systems have become mature and not much talked about. Most investments by institutions have been with new EMR’s so there has not much left over to upgrade the PACS system. The result is that many hospitals run several years behind in upgrading and/or replacing their PACS, which hurts the most when needing to facilitate new modalities such as the breast tomo (3-D) systems. One is forced to stick with proprietary solutions to make these work and/or using the modality vendor’s workstations to view these.

VNA implementations have also been spotty. Some work rather well, but some have major scaling and synchronization issues between the PACS and VNA. Enterprise imaging was touted the past 2 years as well, but as a result of a lack of orders (see discussion above about POC ultrasound) creating work-arounds, has not really taken off as expected. New features are needed such as radiation dose management, peer reviews, critical results reporting, and sophisticated routing and prefetching, which are solved by using third party “middleware” to resolve these issues.

2.       Blockchain - Using blockchain technology in healthcare has a limited application. The reason is that the bulk of the healthcare information does not lend itself to be stored in a public “ledger.” It is nice that the information cannot be altered, but unless it is completely anonymized (which is still an issue as there can be “hidden information in private data elements, embedded in the pixels, etc.), and made available for research purposes for example, there are not that many uses for this technology. As of now, some limited applications such as physician registries seem to be the only ones that are feasible in the short term.

3.       Cloud solutions - Google, Amazon and Microsoft are the big players in this market, but there are still very few “takers” for this technology. One of the reasons is the continuing press on major hacking events into corporations (500 million records from Marriott hotels is the most recent as of this writing) and reports of ransomware events of hospitals. Even though one could argue that the data is probably safer in the hands of one of the top cloud players than on some server in a local hospital, there is definitely a fear factor.

As an illustration, one of the participants told me that their hospitals cut off all of the external communications, so there is no Internet at all on any hospital PC. I have seen many physicians Googling on their personal devices such as tablet or phone instead, to search for information about certain diseases or cases. Despite the push from Google et al we probably need some real success stories before this becomes mainstream. Note that what I call “private cloud” solutions, which are provided by dedicated medical software vendors, are doing better, especially for replacement of CD image distribution and for allowing patients to access their images.

Overall, there was quite a bit to see and listen to at this year’s RSNA. Because of the weather cutting into my visit, I was barely able to cover everything I wanted to during the week. It was interesting to see how mature image processing techniques suddenly appeared as “major new AI” solutions, how there are still so many in their infancy, which makes me to believe that the immediate impact will be relatively little. I was more excited by new modalities and inexpensive ultrasounds, which will have a major impact. 

I am hoping that next year some vendors will spend more effort going back to some of the basics, providing robust integration and workflow support for the day-to-day operations. We’ll see what will be new next year!