Ronald Schilling, PhD

Diasonics MRI was an amazing success story – it was No. 2 in the race during the old days. With the development being UCSF-based, Diasonics had access to doctors on a routine basis. This was a wonderful thing for a start-up that is grounded on the Clinical/Technical Tie – having clinical experts and technical experts working side-by-side.

William G. Bradley, Jr, MD, PhD, was in his last year of medical school when he learned about Diasonics. He was staking his career around MRI as Diasonics was staking its company around MRI. We were in the same boat from the start, paddling together.

The early adopters were often private docs who were not as expert as the university players, and therefore relied on additional guidance. Bradley came up with the idea of the “over-read” concept. The docs would provide images to Bradley using teleradiology and receive clarification of the clinical findings from Bradley. This represented a major breakthrough in “customer engagement.”

It was a pleasure to talk with Bradley about business aspects of Diasonics MRI, for example, the sales strategy. Bradley, based on other consulting activities, had a feeling that the private market was going to play a key role in the expansion of MRI. After several strategy sessions, the approach that Diasonics followed came to fruition: Focus on the private market; selective in the hospital market; and opportunistic in the university market.[[{"type":"media","view_mode":"media_crop","fid":"64715","attributes":{"alt":"William G. Bradley, Jr, MD, PhD","class":"media-image media-image-right","id":"media_crop_1313330930810","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"8287","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"height: 207px; width: 150px; float: right;","title":"William G. Bradley, Jr, MD, PhD","typeof":"foaf:Image"}}]]

• Private Market: Organizations were forming to build MRI centers. This included Texas Medical Equipment, Health Images, Medical Imaging Centers of America, and others. Being run by business people, they were in sync with the Diasonics’ “Total Business Solution” model. Bradley was an advisor to several of these groups.

• Hospital Market: Usually a very conservative market segment. Imagine a member of the decision committee asking radiology the question, “do GE and other large companies provide MRI?” Despite Bradley’s presentations, papers, etc., based on his work at UCSF and his Diasonics’ site at Memorial Research Center in Pasadena, it was an uphill battle not worth pursuing.

• University Market: Bradley’s efforts provided the confidence for UCSF, Memorial, University of Michigan, Orlando Regional Medical Center, and the University of Texas to make the big leap to buy from a start-up. These centers, all “triggered” by Bradley’s activity became the family that succeeded.

Bradley’s work with David Stark, MD, created a foundation publication – everyone knew about Bradley and, hence, about Diasonics. As the mobile market started to develop, Bradley once again played a powerhouse position in convincing Diasonics of the merits of mobile. Mobile was a key to finally getting the hospitals into the MRI business. Having the workstation inside the hospital kept the workflow at a high level. The MRI van was most often travelling between a number of sites or stationary on the hospital campus.

Throughout the above activities, it was wonderful to have Bradley on the team. He was, for Diasonics, Dr. MRI. Alex Margulis taught us that, “if you can’t see it on MRI, it’s only because you don’t have the appropriate driving algorithm.” Bradley found them for Diasonics.

We will all miss such an intelligent, caring, hard-driving team member.

Articles

Paying tribute to Bill Bradley, “Dr. MRI.” 

Bill Bradley – a Powerhouse

Being an advisor to several medical imaging publications, requires one to provide a prognosis of what the key dynamics in medical imaging might be in the following year.

At this point in time, I am personally involved in several areas: big data (BD) and interactive virtual reality (IVR). Both areas are beginning to take hold in terms of impacting patient outcomes (PO). This discussion is focused on the synergy between BD and IVR, and the resulting potential for significant gains in PO – an important dynamic for medical imaging.

 about BD is increasing as IBM’s efforts with Watson are coming to fruition. It is most noteworthy that Virginia Rometty, IBM CEO, characterizes Watson as a cognitive-based system that represents supervised learning using BD techniques. Cognition is indeed a critical element in that it impacts knowledge, which is dependent on both cognition and intuition. Knowledge, in turn, represents a fundamental factor in driving PO.

The other critical element in the knowledge equation, intuition, has been shown to be driven by 

. Hence, the power of the BD/IVR intersection.

Consider IVR as the ability to view an object in open 3D space and directly interact with the object (eg, removing a tumor electronically).

Radiologists have noted, that IVR provides a way to communicate more effectively with surgeons. Surgeons have noted that IVR allows them to finally achieve surgical visualization, the ability to view anatomy in a manner that corresponds to their 3D world view – they never open up patients and see 2D views.

Essentially, IVR represents a new paradigm, or “language,” with which different specialists discover an enhanced ability for communicating more effectively with one another.

Why might 2017 be the key year to realize the potential of the BD/IVR intersection? Based on several years of clinical trials, significant improvement in the core areas of PO, clinical efficacy (CE), and workflow (WF), have been demonstrated in a number of applications, due to IVR driven increases in knowledge.

We might think of IVR as focused on “doing the right things” and BD as focused on “doing things right.” A case in point would be a Protocol for optimizing both CE and WF for virtual colonoscopy. Based on the intuitive properties of IVR, a concept of dividing the colon into linear segments emerged with each segment separately analyzed for polyps. This breakthrough led to significant gains in both clinical efficacy and workflow.

BD has already been effectively applied to 

. BD could also be applied to the analysis of all users of the above protocol to establish best practices from data representing all user motions (head, stylus, etc.). In this manner, BD is a key to “doing things right.” This direction was intimated by 

The intersection of BD and IVR therefore provides a significant opportunity for achieving improvements in PO. We could think of this 

 as knowledge modeling. Today, leading organizations in health care are establishing knowledge modeling as the core of effective data management. What could be better than to apply these principles to increasing PO?

Big data meets interactive virtual reality. 

Intersection of Big Data and Interactive Virtual Reality

There is much excitement about big data and its potential applications in medical imaging. The purpose of this blog is to consider related approaches that are providing results today and can therefore serve as a guide for big data driven applications.

Virtual colonoscopy will be used as a clinical example to clarify this subject. Big data in the form of machine learning has been applied to CADx and utilized for virtual 

The CADx approach of analyzing large numbers of 2D images, creating representative algorithms, and applying them to diagnosis is an established approach. Medical Sieve, from 

, is one of the latest versions of diagnostic interpretation of 2D medical imaging datasets guided by clinical knowledge.

“Medical Sieve is an ambitious, long-term exploratory grand challenge project to build a next generation cognitive assistant with advanced multimodal analytics, clinical knowledge, and reasoning capabilities that is qualified to assist in clinical decision making in both radiology and cardiology.”

In all of the above, the fundamental source of data remains in the form of 2D views. When the 2D views are created as a projection of 3D volume data sets, we might refer to them as 2.5D 

. The use of 2D/2.5D as the application of big data in medical imaging, is dated and therefore can be considered as thinking “inside the box.”

, “Deriving value out of insightful analytics that could impact care processes and outcomes is an important, and often the most critical, goal of efforts related to big data.”

By working with “objects,” available with 

 (IVR), as opposed to being limited by images alone, the goals noted by Shrestha are already being realized in virtual colonoscopy as follows:

“With IVR, I can lift the colon out of the display, open up the colon and rotate it in innumerable planes,” Judy Yee, MD, of UCSF, 

. “Image manipulation is more intuitive and I can use the spatial resolution of lesions relative to folds and the background wall more easily, providing an ideal situation to identify polyps including flat lesions.”. This approach can be thought of as thinking, “outside the box,” with intuition driven knowledge, resulting in increasing clinical efficacy and workflow/patient outcomes.

The ultimate goal of big data is to improve patient outcomes. With IVR, the initial results are encouraging. They provide a ground truth and guide for raising the bar further with big data techniques applied to objects. At that point, big data will think outside the box.

Technology can help big data think outside the box in radiology. 

Can Big Data Think Outside The Box?

I just returned from an excellent health care conference, CARS 2016, held this year in the beautiful city of Heidelberg. Now in its 30th year, CARS (computer-assisted radiology and surgery) has been focused on closing the radiology-surgery gap.

Significant progress has recently been made, in closing the gap, with the advent of technologies like interactive virtual reality (IVR), an effective visualization communication tool. By viewing objects in open 3D space, in addition to images, the radiologist can, “speak more intelligently with the surgeon." In addition, the surgeon, who "never opens a patient and sees a 2D view," can have a workstation that relates effectively with their practice.

There’s nothing like excellent communication to bring diverse professionals together. In the case of radiology and surgery, the use of a visualization-based communication tool is the perfect solution.

At CARS, during which several related surgery organizations meet simultaneously, one often finds radiologists and surgeons, side by side, discussing the challenges and future of their joint trade.

There was discussion of radiology creating a surgical plan and streaming the results to the surgeon in the form of a visual report. Consider the area of colonoscopy. The radiologist, using virtual colonoscopy, can find the polyps, create scenes (3D data sets delineating the specific situation) for each polyp, and stream the "visual report" to the surgeon for polyp removal.[[{"type":"media","view_mode":"media_crop","fid":"49977","attributes":{"alt":"PACS","class":"media-image media-image-right","id":"media_crop_4331099277536","media_crop_h":"0","media_crop_image_style":"-1","media_crop_instance":"6076","media_crop_rotate":"0","media_crop_scale_h":"0","media_crop_scale_w":"0","media_crop_w":"0","media_crop_x":"0","media_crop_y":"0","style":"height: 113px; width: 169px; border-width: 0px; border-style: solid; margin: 1px; float: right;","title":"Â©sfam photo/Shutterstock.com","typeof":"foaf:Image"}}]]

Since approximately 10% of patients actually have polyps at the time of an examination, the cost savings are significantly increased and the difficulty for patients is significantly reduced. The radiologist plays a significant role in using IVR to not only characterize standard polyps, but also to find the challenging flat lesions that are twice as likely to be cancerous – followed by creating the scenes for the surgeon. The surgeon, will be provided with only cases containing polyps so that their efforts are more productive.

During discussions at CARS, dealing with the “operating room of the future,” it was evident that by working together, patient outcomes can be significantly improved – and that of course, is the name of the game.

Radiology and surgery speak the same language at CARS 2016.

Ronald Schilling, PhD

Articles

Bill Bradley – a Powerhouse

Intersection of Big Data and Interactive Virtual Reality

Can Big Data Think Outside The Box?

Radiology and Surgery: Progress in Coming Together