CEO of Quality Electrodynamics sees teamwork as key to tech start-ups success

When you turn a start-up medical device company into a $12 million international competitor in just four years, people start talking. Hiroyuki Fujita expected it.

But that doesn’t mean he’s comfortable with the attention.

On Thursday, Fujita plans to talk to members of the International Entrepreneur organization at BioEnterprise, an initiative to expand health-care companies and commercialize bioscience technology. Northeast Ohio entrepreneurs and guests will hear about his success at Quality Electrodynamics, which makes detectors used in magnetic resonance imaging machines.

As of Tuesday, Fujita hadn’t written a word. But he knows what people want to hear.

In the last year alone, Gov. Ted Strickland visited his new 27,000-square-foot facility twice. Forbes ranked QED No. 11 among the nation’s top 20 most promising companies. And if you add up all of his international travel, his family and 60 employees can testify that he’s four months visiting customers and prospects.

It’s part of Fujita’s larger plan to turn his Mayfield start-up into a global powerhouse in a few decades.

“Nothing happens by chance,” said Fujita, 43. “You have to make it by determination. You have to have the know-how of something you want to do well, then have a clear mindset of how you’re going to achieve it.”

Already, QED’s customers include Toshiba Medical Systems and Siemens Healthcare, Germany.

If you ask Fujita about his success, he’ll turn attention away from himself. He’d rather talk about a supportive Ohio business community, which includes Case Western Reserve University, where he completed his doctorate in physics in 1998 and later started his company in a 300-square-foot room while working at Case’s Department of Physics in a newly created position as director of imaging.

Baiju Shah, president of BioEnterprise, said it’s unusual for a medical technology company to be profitable and have 60 employees in such a short period of time.

“We see a lot of companies that, five years into their formation, either just began getting sales or they’re still in the process of getting cleared” by the Food and Drug Administration, he said.

“The other thing that makes him unusual is that most technology companies requires substantial venture funding,” Shah said. “He’s done it through strategic partnerships and relationships and a lot of sweat.”

Funding of $1.59 million came from state and industry partners, including a $350,00 grant fromThird Frontier’s Global Cardiovascular Innovation Center.

Years before Fujita decided to become an entrepreneur, he was paying dues learning about medical technology, competition and the importance of building global relationships. His positions included professor and researcher at Case and staff scientist at Picker International. As director of engineering at GE Healthcare, he grew accustomed to using technology at all hours to communicate with colleagues in Japan and Europe.

“I worked so hard at GE that my wife said, you’re probably going to die young,” he said.

Fujita prefers talking about employees and the culture of teamwork he works hard at cultivating. Employees work in an open environment with no partitions or cubicles. And every chance he gets, Fujita tries to remind employees of their value and share company milestones with everyone from hourly employees to engineers.’

“An open environment is key to the company remaining agile and responsive to our customer needs,” said John Schellenberg, general manager of operations. “When we’re not designing and building, we invest considerable time communicating with our customers and visiting key clinical sites.”

Schellenberg is one of about 25 people hired in the last year and a half. Most were in between jobs when they were hired at QED, a company with no bank debt or investors.

“As long as they had technical capabilities, ethics and integrity, I hired them,” Fujita said.

A quick look into Fujita’s office gives a glimpse at how he’s working to build a major firm. Seven rolodexes line his desk, all filled with contacts he’s made in the last four years. A photo of him and Steve Forbes followed a four-month process of filling out paperwork to claim a spot on Forbes’ coveted top 20 list. Fujita speculates that his spot on the list led directly to another photo, an invitation to the Japanese emperor’s birthday reception.

For inspiration, he looks to a photo of him and his 79-year-old role model, Kazuo Inamori, founder of Kyocera Corp. and KDDI of Japan, who helped shape his company’s philosophy. Fujita’s goal is to embrace similar values of keeping a balance of scientific progress while “pursuing what’s right for humankind.”

“If awards and acknowledgements or high revenues make me special, then I’m already failing the test. I want to be a good human being,” he said. “My dream is that when I become 80, our efforts at QED will have a positive impact on society to help other people.”

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Is a project to map the brain’s full communications network worth the money?



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A building that once housed a Second World War torpedo factory seems an unlikely location for a project aiming to map the human brain. But the Martinos Center for Biomedical Imaging — an outpost of the Massachusetts General Hospital in an industrialized stretch of Boston’s riverfront — is home to an impressive collection of magnetic resonance imaging machines. In January, I slid into the newest of these, head first. The operator ran a few test sequences to see whether I experienced any side effects from the unusually rapid changes in this machine’s magnetic field. And, when I didn’t — no involuntary muscle twitches or illusory flashes of light in my peripheral vision — we began. The machine hummed, then started to vibrate. For 90 minutes, I held still as it scanned my brain.

That scan would be one of the first carried out by the Human Connectome Project (HCP), a five-year, US$40-million initiative funded by the National Institutes of Health (NIH) in Bethesda, Maryland, to map the brain’s long-distance communications network. The network, dubbed the ‘connectome’, is a web of nerve-fibre bundles that criss-cross the brain in their thousands and form the bulk of the brain’s white matter. It relays signals between specialized regions devoted to functions such as sight, hearing, motion and memory, and ties them together into a system that perceives, decides and acts as a unified whole.

The connectome is bewilderingly complex and poorly understood. The HCP proposes to resolve this by using new-generation magnetic resonance imaging (MRI) machines, like that used to scan my brain, to trace the connectomes of more than 1,000 individuals. The hope is that this survey will establish a baseline for what is normal, shed light on what the variations might mean for qualities such as intelligence or sociability, and possibly reveal what happens if the network goes awry. “We increasingly believe that brain disorders — from schizophrenia to depressionto post-traumatic stress disorder — are disorders of connectivity,” says Thomas Insel, director of the National Institute of Mental Health (NIMH) in Bethesda and a strong supporter of the HCP. “So it is of vital importance that we have ways of detecting and quantifying these connections.”

Yet many wonder whether the NIH is making a mistake. Researchers have yet to prove that MRI techniques can produce a reliable picture of normal connectivity, never mind the types of abnormal connection likely to be found in brain disorders, and some researchers argue that the techniques have not been adequately validated. “I would do the basic neuroscience before I started running lots of people through MRI scanners,” says David Kleinfeld, a physics and neurobiology researcher at the University of California, San Diego.

The grand challenge

Proponents counter that the HCP is a calculated risk. “No one thinks this is going to produce a wiring diagram like you might have for the electricity in your house,” says Insel. But so little is known about the connectome, he says, that even crude maps would represent a major scientific advance.

The decision to take that risk was made by the NIH’s Blueprint for Neuroscience Research, set up in 2004 as a collaboration among the 15 NIH institutes, centres and offices with an interest in nervous-system research. In 2009, after five years of funding smaller projects, the group asked officials from across the NIH to submit ideas for ‘grand challenges’ in neuroscience: large-scale programmes that, Insel says, “would be both extremely high-impact, and virtually impossible with traditional grant mechanisms”.

The Blueprint group received a dozen submissions, including one from Michael Huerta, then a programme officer at the NIMH and a member of a Blueprint subcommittee. Huerta, now at the NIH’s National Library of Medicine, began his research career studying the organization of mammalian brains using old-school anatomical and neural-tracing techniques, which typically require the injection of a tracer compound that migrates along nerve fibres and reveals their routes. So he was all too familiar with the barriers to such studies in humans. For ethical reasons, tracers can only be used post-mortem — when they don’t migrate far enough to trace a fibre’s full length. “The studies just never panned out,” says Huerta.

Nature Neuropod

Nature’s Kerri Smith discusses the Human Connectome Project at its launch


In 2007, Huerta became fascinated by two new non-invasive imaging methods that might finally allow researchers to study the finer details of connectivity in the brains of living humans. The first was diffusion-spectrum imaging (DSI), developed in 2005 by Van Wedeen, a radiologist at the Martinos Center, and his colleagues1. DSI is a refinement of the two-decades-old diffusion tensor imaging technique, which exploits MRI’s ability to detect the direction in which water molecules are moving at each point in the brain. Because most of those molecules move along the lengths of nerve fibres, like water through a pipe, the data can be used to reconstruct each fibre’s location and trajectory. What DSI adds is a more sophisticated form of signal analysis that allows researchers to continue tracing fibre bundles even when one seems to pass behind another, a situation that posed serious problems for the older technique.

The second method that caught Huerta’s attention was resting-state functional MRI (rs-fMRI), in which people think about nothing in particular while their brain activity is measured. This is quite different from conventional functional-imaging studies, in which participants are asked to carry out a specific cognitive task and researchers look for the brain regions that are activated in the process. In rs-fMRI, there is no task, and researchers look for correlations among the activity levels in different areas. The presumption is that any two regions with a consistently high correlation are linked — perhaps by an actual bundle of nerve fibres, but certainly by working together in some way.

The application of both DSI and rs-fMRI had already led to a number of high-profile publications. But Huerta realized that few groups were applying both methods in the same subjects, and most studies used small samples, limiting their generalizability. So he proposed that the Blueprint group fund a Human Connectome Project that would apply both methods to hundreds of people. This would allow the first large-scale comparison to be made between structural connectivity, as determined by DSI, and functional connectivity, as determined by rs-fMRI. “No single neuroimaging approach would give you the type of gold-standard connectivity data you need,” says Huerta, recalling his argument for the dual data sets.

The Blueprint group was intrigued, but was not blind to the problems inherent in these techniques. One obvious issue is DSI’s spatial resolution: each fibre bundle in the image contains thousands of neurons, meaning that it would miss a great deal of structure on smaller scales.

Partha Mitra, a neuroscientist at Cold Spring Harbor Laboratory in New York, illustrated the problem to me by displaying a series of high-resolution digital pictures of mouse brain slices, each of which had some of its neurons coloured with a dark brown dye. On one such slice, he showed neurons that originated in the left cortex, then branched out and sent fibres to areas on both the left and the right side of the brain. “The brain is not made up of point-to-point connections,” he said. “It’s made up of trees.”

“We increasingly believe that brain disorders are disorders of connectivity.”

This level of connectome structure is invisible to even the most advanced diffusion-imaging methods, says Mitra, who heads the Mouse Brain Architecture Project, a parallel version of the HCP, funded by the NIH and the W. M. Keck Foundation of Los Angeles, that seeks to generate a whole-brain wiring diagram for the mouse using staining techniques. And the problem is made even worse when the data are converted into a ‘connectivity matrix’, which seeks to quantify how much every point in the brain is connected to every other point — but can’t tell the difference between, say, two separate fibres and one fibre with two branches.

The Blueprint group was also aware of concerns about resting-state scans. As with the more familiar form of fMRI, what is actually measured isn’t neural activity itself, but blood flow. The general presumption is that the two quantities are closely related — that blood flow increases in a region of the brain whenever the neurons there are active and need to be supplied with more oxygen. But recently, Kleinfeld points out, several studies have called that assumption into question, showing that some increases in blood flow in the brain occur without an increase in neuronal activity2. “There is no simple one-to-one relationship,” he says.

A remaining concern

That makes rs-fMRI studies particularly hard to interpret, Kleinfeld adds, if only because the brain’s resting-state activity may fluctuate on the same timescales that its blood vessels do. A recent review3 of rs-fMRI admits that this vascular fluctuation “remains a concern”. Other studies show that even something as simple as a subject’s pattern of breathing4 or slight movements of the head5 can significantly confound rs-fMRI measurements.

Even leaving the technical challenges aside, there was no assurance that collecting the connectomes of hundreds of individuals would lead to interesting generalizations. “You could certainly imagine situations in which everyone’s wiring diagrams are quite different,” says Gregory Farber, the programme officer at the NIMH who manages the connectome project. Nonetheless, the Blueprint group was swayed by the argument that imperfect data are better than no data. “The committee asked, ‘Will we have better methods in five years?’,” recalls Huerta. “I’m sure we would. But if we followed that rule, no science would ever get done.”

The group also liked the fact that the findings would be broadly applicable to clinical, as well as scientific, questions. “We thought we could do something like what we did with the Human Genome Project,” Insel says, “because once you have that map of the brain you can compare it to similar maps across development, or to maps of subjects with different disorders of brain circuitry.”

A blueprint for the brain

In July 2009, the Blueprint group announced its choice of the HCP as one of three grand challenges — the other two focused on pain and on drugs for nervous-system disorders — and simultaneously put out a request for proposals. On 15 September 2010, the NIH announced that it would be funding two HCP proposals.

The larger of the two is a 5-year, $30-million effort led by David Van Essen, a neurobiologist at Washington University in St Louis, Missouri, and Kamil Ugurbil, an fMRI pioneer at the University of Minnesota in Minneapolis. (Another collaborator is Olaf Sporns, a neuroscientist at Indiana University in Bloomington, a co-author on the 2005 review article that coined the term ‘connectome’6.) During phase one, now nearing completion in Minneapolis, this team has developed a scanner that will be able to double the resolution of standard MRI.


Once complete, that scanner will be moved to Washington University, where it will immediately begin high-throughput scanning. The plan is to use both DSI and rs-fMRI (see ‘Scanning the connectome’) to study 1,200 people: 300 identical twins, 300 non-identical twins and 600 non-twin siblings. This will allow researchers to explore how much of the brain’s connectivity is mapped out by genes. Volunteers will also complete behavioural tests and other fMRI, magnetoencephalogram and electroencephalogram protocols, so that brain structure can be further correlated with function. All these data will be made public, allowing unaffiliated researchers to answer their own questions, and Van Essen’s group plans to release a set of new data-analysis tools. Connectomics, Van Essen says, “has been a cottage industry. But we expect this project to allow for a much richer, more unified approach”.

The smaller HCP project — a 3-year, $8.5-million effort led by Bruce Rosen, a radiologist at the Massachusetts General Hospital, and Arthur Toga, a neurologist at the University of California, Los Angeles — involved building a new fMRI scanner optimized for the collection of fibre-tracking data. The idea was to massively increase the gradient strength of the machine — a measure of how rapidly the MRI’s magnetic field varies from point to point in the brain. A more intense gradient is like “a bigger mirror in a telescope”, says Wedeen, who is director of connectomics at the Martinos Center. It simultaneously makes the instrument more sensitive to faint signals, and gives it a higher resolution. The machine has now been built — it is the one that collected images of my brain in January — but will require much more tweaking and testing before it is optimized for routine use. But the researchers have already achieved a tenfold increase in sensitivity to the water-diffusion signal, allowing their scanner to trace connections much more precisely than the best off-the-shelf machines.

In a press release announcing the launch of the HCP in July 2009, Insel said that the project would “map the wiring diagram of the entire, living human brain” and that this map could be linked to “the full spectrum of brain function in health and disease”. Such lofty ambitions may or may not succeed in five years. But the project still has its place, says Sebastian Seung, a computational neuroscientist at the Massachusetts Institute of Technology in Cambridge, who studies brain connectivity at the cellular level. “I think it is a mistake to think we have to look at every cell in every region of the brain to make scientific progress,” says Seung, who is not involved in the HCP.

But he also emphasizes that the HCP’s connectivity map will be, at best, a beginning. “That is just going to tell us where to look,” he says. “Then we need to study actual cells to learn more”, to figure out how the brain’s networks actually transmit information.

A week after my visit to the Martinos Center, I received my DSI data. Using free software from the centre, it is easy to explore the architecture of my brain. I can clearly see my hippocampus, and the vast array of fibres projecting from the midbrain sensory hubs up to my cerebral cortex. I am overwhelmed by the visible detail and obvious organization. At present, it is just a pretty picture — a novelty to show friends. But, I wonder: once scientists know what ‘average’ looks like, and once they understand the variations, what, if anything, will this rainbow-coloured highway map of my brain say about me?


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MRI Outpatient volume forecasts for 2011-2016

March 22, 2012

With so much volatility in the outpatient imaging market—evidenced by the economic downturn, continued entrenchment of private payer preauthorization programs, volume redirection and the uncertainty of reform—now is an opportune time to pause and take stock of outpatient growth prospects for the near future.

Outpatient volume forecasts for 2011-2016
Factoring in outpatient and emergency volume , the Advisory Board forecasts healthy outpatient growth for several modalities between 2011 and 2016. For example, we project a total growth rate of 8% and 11% for CT and MRI, respectively, across the next five years. This translates into a five-year incremental volume of 4.3 million CT and 3 million MR procedures.

Growth slows, but doesn’t stop

Nevertheless, current growth rates are projected to be weaker than in years past. In 2000-2004, outpatient MRI and CT grew as much as 10% annually, but since then, volume growth rates have been declining. Our most recent forecasts, tempered by the recent pressures as evidenced in the findings in our latest volumes benchmarking, found flattening of volumes in many modalities including CT and MRI. In addition, widespread penetration of utilization management—including radiology benefit manager steerage—has further chipped away at hospital outpatient volumes specifically.

Imaging volume drivers

However, the outlook is not all negative, as advanced imaging procedures are still buoyed by a variety of volume drivers.

An aging population
Given that adults over 65 are the prime users of imaging exams, we can expect an increase in utilization as the population ages. We estimate that Americans over age 65 will be responsible for 30 million CTs and 10.1 million MRIs in 2016, a full 52% and 34% of the total for each modality, respectively.

Downstream cost reduction
Advanced procedure volumes within both CT and MR can lead to further volume boosts. During our ongoing research for our 2012 national meeting series, we are examining specific scan types where boosting volumes may result in lower downstream care costs.

Case in point, one institution implemented robust coronary CT angiography (CCTA) protocols for patients presenting to the ED with chest pain and low heart failure risk. In many cases, CCTA exams can rule out surgery, reducing length of stay and overall costs. After implementing new protocols in the ED, CCTA volumes rose three-fold and length stay decreased by about 58%. In our estimator, we project as much as 10-11% growth each year, totally about 50% over five years and far exceeding projected growth rates for any other type of CT.

Expanding advanced procedure terrain
MRI volumes, on the other hand, will continue to be driven by growth in brain, musculoskeletal, and spine applications, in addition to newer procedures like breast and cardiac MRI. In fact, we project 15% growth in breast and 24% growth in cardiac MRs over the next five years.

Generate customized volume forecasts for your markets

Imaging Performance Partnership members may access the Outpatient Imaging Market Estimator to evaluate opportunities and barriers in localized markets. Updated to incorporate our latest estimates and forecasts, the tool allows you to access volume estimates and forecasts for any geography within the United States at either the county or zip code level and view market size estimates for specific imaging modalities and individual types of scans.

Not a member of the Imaging Performance Partnership? Check out our website to learn more.

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Do Something Extra this World Down Syndrome Day!

1 Down Syndrome Fact Sheet
2 Down Syndrome Q & A
3 Myths and Truths
4 What Causes Down Syndrome?
5 Incidences and Maternal Age
6 Preferred Language Guide
7 General Info

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Grab This Button

World Down Syndrome Day is celebrated internationally on March 21, symbolic of a third copy of the 21st chromosome that characterizes Down syndrome. This year the celebration is amplified as it is the first time that the date is officially recognized by the United Nations. Join NDSS and “do something extra” in honor of those with an extra 21st chromosome! Please grab this button and add it to your blog, and include posts between now through March 21 that promote the value, acceptance and inclusion of people with Down syndrome. While we encourage frequent relevant posts in anticipation of the day, there is no posting requirement to grab the button – just having it on your blog will raise awareness!

If you’re looking for ideas, click here for a list of initiatives and ways to get invovled. Please spread the word to other bloggers who are interested in raising awareness for people with Down syndrome!

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The iPad 3 with HD display, watch the presentation video

This Ipad looks awesome. Apple tv is next on my list.

Gadget Teck

What you can do with the new iPad 3?

Watch the presentation video and dont wait until it pass you.

That quad core graphics and the 2048 x 1536 resolution is great.

If you want it you can buy it here in all configurations possilbe:

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Whole Body MRI


Due to advances in engineering and technology, the field of MRI evolves at a steady pace. To keep up with these advancements, radiologists and technologists continue to saturate themselves with clinical research, hunting for cutting-edge strategies that will provide state-of-the-art image quality, regardless of the protocol prescribed.MRI has been utilized in mainstream radiology since the mid-1980s. Since that time, there has been a continuous stream of technological progress that is quite remarkable, most recently to include 3T scanning, functional MRI, and clinical spectroscopy of the brain, prostate, and liver. Large bore scanners are now routine, allowing better comfort for patients. Yet despite the tremendous innovations that have already taken place, the technology continues to move forward.


Whole body MRI

Whole body MRI has been available for some time but only recently has become an efficient method for total body screening. The idea of imaging the entire body at a single setting has been validated as an effective imaging protocol for a number of conditions.

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Figure 1:  Whole body MRI using STIR imaging. Images were acquired in the coronal plane in approximately 15 minutes.

The rationale for whole body MRI is clear: Many common diseases are systemic, that is, they are likely to involve the entire body. The most common application is for metastatic cancer evaluation, but cardiovascular disease also affects the entire body.


Whole body MRI does not necessarily require specialized scanners and coils, but these items are strongly recommended for efficient scan acquisition. Critically, the ability to “stitch” together multiple images acquired at different times and locations distinguishes MRI scanners that have the potential for rapid whole body scan acquisition. (See Figure 1.)

As indicated above, no billing codes currently cover dedicated whole body MRI. Separate charges or the multiple body parts make the exam prohibitively expensive, and insurance coverage for separate body parts is unlikely. In parts of Europe, whole body examination has been more common than in the U.S., particularly for self-paying patients and as a component of executive physical exams. If cost were not the driving force, would there be a medical need for whole body MRI?


In the current era of molecular imaging, the PET/CT scanner is considered the gold standard for any PET imaging. That paradigm may be poised for change with the advent of the MR/PET scanner. Three of the world’s leading manufacturers of imaging equipment–Philips, GE, and Siemens–have been focusing their research and development dollars on the concept of creating a system capable of acquiring MR and PET images together, with perfect fusion of the respective modalities.

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Figure 2: Whole body single shot T2-weighted image fused with FDG-PET image. Multiple lesions (circles) are more readily identified on the MRI/PET fusion image (left).

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Figure 3: Fused MRI/PET image (left) obtained in approximately 25 minutes using FDG. The PET-only image obtained on the combination MRI/PET scanner is shown on the right. Small areas of focal activity are noted in the left flank (small circle) and right gluteal muscles (large circle).images/courtesy Dr. Bluemke

For more information go to

 ADVANCE for Imaging & Radiation Oncology

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