Awake imaging device moves diagnostics field forward

A technology being developed at the Department of Energy’s Oak Ridge National Laboratory promises to provide clear images of the brains of children, the elderly and people with Parkinson’s and other diseases without the use of uncomfortable or intrusive restraints.

Awake imaging provides motion compensation reconstruction, which removes blur caused by motion, allowing physicians to get a transparent picture of the functioning brain without anesthetics that can mask conditions and alter test results. The use of anesthetics, patient restraints or both is not ideal because they can trigger brain activities that may alter the normal brain functions being studied.

With this new capability, researchers hope to better understand brain development in babies, pre-teens and teen-agers. In addition, they believe the technology will provide unprecedented insight into conditions such as autism, drug addictions, alcoholism, traumatic brain injuries and Alzheimer’s disease.

"With this work, we’re hoping to establish a new paradigm in noninvasive diagnostic imaging," said Justin Baba, a biomedical engineer who heads the ORNL development team.

The study, which was performed in collaboration with Thomas Jefferson National Accelerator Laboratory and Johns Hopkins University, utilized an awake imaging scanner and awake, unanesthetized, unrestrained mice that had been injected with a radiotracer known as DaTSCAN, provided by GE-Medical.

With awake imaging using DaTSCAN and other molecular probes, Baba and colleagues envision development of new, more effective therapies for a wide assortment of conditions and diseases while also contributing to pharmaceutical drug discovery, development and testing. The technology could also help with real-time stabilization and registration of targets during surgical intervention.

Baba noted that this technical accomplishment, detailed in a paper published in The Journal of Nuclear Medicine, has its origins in past DOE-supported research on biomedical imaging. The paper is titled “Conscious, Unrestrained Molecular Imaging of Mice with AwakeSPECT.” Jim Goddard of ORNL’s Measurement Science and Systems Engineering Division is a co-author.

While a working prototype scanner is located at Johns Hopkins School of Medicine, ORNL is pursuing commercialization of the technology.

Human Connectome Project releases major data set on brain connectivity

The Human Connectome Project, a five-year endeavor to link brain connectivity to human behavior, has released a set of high-quality imaging and behavioral data to the scientific community. The project has two major goals: to collect vast amounts of data using advanced brain imaging methods on a large population of healthy adults, and to make the data freely available so that scientists worldwide can make further discoveries about brain circuitry.

The initial data release includes brain imaging scans plus behavioral information — individual differences in personality, cognitive capabilities, emotional characteristics and perceptual function — obtained from 68 healthy adult volunteers. Over the next several years, the number of subjects studied will increase steadily to a final target of 1,200. The initial release is an important milestone because the new data have much higher resolution in space and time than data obtained by conventional brain scans.

The Human Connectome Project (HCP) consortium is led by David C. Van Essen, PhD, Alumni Endowed Professor at Washington University School of Medicine in St. Louis, and Kamil Ugurbil, PhD, Director of the Center for Magnetic Resonance Research and the McKnight Presidential Endowed Chair Professor at the University of Minnesota.

“By making this unique data set available now, and continuing with regular data releases every quarter, the Human Connectome Project is enabling the scientific community to immediately begin exploring relationships between brain circuits and individual behavior,” says Van Essen. “The HCP will have a major impact on our understanding of the healthy adult human brain, and it will set the stage for future projects that examine changes in brain circuits underlying the wide variety of brain disorders afflicting humankind.”

The consortium includes more than 100 investigators and technical staff at 10 institutions in the United States and Europe (www.humanconnectome.org). It is funded by 16 components of the National Institutes of Health via the Blueprint for Neuroscience Research (www.neuroscienceblueprint.nih.gov).

“The high quality of the data being made available in this release reflects an intensive, multiyear effort to improve the data acquisition and analysis methods by this dedicated international team of investigators,” says Ugurbil.

The data set includes information about brain connectivity in each individual, using two distinct magnetic resonance imaging (MRI) approaches. One, called resting-state functional connectivity, is based on spontaneous fluctuations in functional MRI signals that occur in a complex pattern in space and time throughout the gray matter of the brain. Another, called diffusion imaging, provides information about the long-distance “wiring” – the anatomical pathways traversing the brain’s white matter. Each method has its own limitations, and analyses of both functional connectivity and structural connectivity in each subject should allow deeper insight than by either method alone.

Each subject is also scanned while performing a variety of tasks within the scanner, thereby providing extensive information about “Task-fMRI” brain activation patterns. Behavioral data using a variety of tests performed outside the scanner are being released along with the scan data for each subject. The subjects are drawn from families that include siblings, some of whom are twins. This will enable studies of the heritability of brain circuits.

The imaging data set released by the HCP takes up about two terabytes (2 trillion bytes) of computer memory — the equivalent of more than 400 DVDs — and is stored in a customized database called “ConnectomeDB.”

“ConnectomeDB is the next-generation neuroinformatics software for data sharing and data mining. It’s a convenient and user-friendly way for scientists to explore the available HCP data and to download data of interest for their research,” says Daniel S. Marcus, PhD, assistant professor of radiology and director of the Neuroinformatics Research Group at Washington University School of Medicine. “The Human Connectome Project represents a major advance in sharing brain imaging data in ways that will accelerate the pace of discovery about the human brain in health and disease.”

Brain imaging research shows how unconscious processing improves decision-making

When faced with a difficult decision, it is often suggested to “sleep on it” or take a break from thinking about the decision in order to gain clarity.

But new brain imaging research from Carnegie Mellon University, published in the journal “Social Cognitive and Affective Neuroscience,” finds that the brain regions responsible for making decisions continue to be active even when the conscious brain is distracted with a different task. The research provides some of the first evidence showing how the brain unconsciously processes decision information in ways that lead to improved decision-making.

"This research begins to chip away at the mystery of our unconscious brains and decision-making," said J. David Creswell, assistant professor of psychology in CMU’s Dietrich College of Humanities and Social Sciences and director of the Health and Human Performance Laboratory. "It shows that brain regions important for decision-making remain active even while our brains may be simultaneously engaged in unrelated tasks, such as thinking about a math problem. What’s most intriguing about this finding is that participants did not have any awareness that their brains were still working on the decision problem while they were engaged in an unrelated task."

GE Silent Scan turns down the volume on MRI scanners

GE Healthcare has introduced a new data acquisition technology designed to improve patient comfort by largely eliminating the horrible noise generated during an MRI scan. Conventional MRI scanners can generate noise levels in excess of 110 dBA (creating a din that sounds like a cross between a vehicle’s reverse warning horn and a Star Trek phaser) but GE says its new Silent Scan MRI technology can reduce this to just above background noise levels in the exam room.

The noise that MRI scanners produce is related to changes in the magnetic field that allow the slice by slice body scan to be carried out. In recent years, industry efforts to speed up the scanning process have also resulted in louder and louder scans. The designers have attempted to dampen these noises with mufflers and baffles, achieving only limited success.

Silent Scan is achieved through two new developments. First, acoustic noise is essentially eliminated by using a new 3D scanning and reconstruction technique called Silenz. When the Silenz protocol is used in combination with GE’s new high-fidelity MRI gradient and RF system electronics, the MRI scanning noise is largely eliminated at its source.

At the 2012 meeting of the Radiological Society of North America, an MRI system compatible with the Silent Scan technology was linked into a soundproof room. When the MRI system used conventional scanning methods, a staccato, stuttering racket with noise peaks up to 110 dBA was heard. However, when Silent Scan was switched on, the noise level dropped to 76 dBA, just above the background noise of the MRI electronics. This is accomplished without substantial trade-offs in scanning time or image quality, according to Richard Hausmann, president and CEO, GE Healthcare MR. The comparison is shown in this video.

Silent Scan technology has not yet obtained 510k Premarketing Notification clearance from the FDA, so it’s not yet available for sale. GE is presumably hoping for a decision that Silent Scan is “substantially equivalent” to existing MRI scanners, a result that would greatly simplify the new technology’s entry into the diagnostic market.

Brain imaging insight into cannabis as a pain killer

The pain relief offered by cannabis varies greatly between individuals, a brain imaging study carried out at the University of Oxford suggests.

The researchers found that an oral tablet of THC, the psychoactive ingredient in cannabis, tended to make the experience of pain more bearable, rather than actually reduce the intensity of the pain.

MRI brain imaging showed reduced activity in key areas of the brain that substantiated the pain relief the study participants experienced. 

'We have revealed new information about the neural basis of cannabis-induced pain relief,' says lead researcher Dr Michael Lee of Oxford University's Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB). 

'Cannabis does not seem to act like a conventional pain medicine. Some people respond really well, others not at all, or even poorly,' he says. 'Brain imaging shows little reduction in the brain regions that code for the sensation of pain, which is what we tend to see with drugs like opiates. Instead cannabis appears to mainly affect the emotional reaction to pain in a highly variable way.'

Long-term pain, often without clear cause, is a complex healthcare problem. Different approaches are often needed to help patient manage pain, and can include medications, physiotherapy and other forms of physical therapy, and psychological support. 

For a few patients, cannabis or cannabis-based medications remain effective when other drugs have failed to control pain, while others report very little effect of the drug on their pain but experience side-effects.

'We know little about cannabis and what aspects of pain it affects, or which people might see benefits over the side-effects or potential harms in the long term. We carried out this study to try and get at what is happening when someone experiences pain relief using cannabis,' says Dr Lee.

He adds: ‘Our small-scale study, in a controlled setting, involved 12 healthy men and only one of many compounds that can be derived from cannabis. That’s quite different from doing a study with patients.

'My view is the findings are of interest scientifically but it remains to see how they impact the debate about use of cannabis-based medicines. Understanding cannabis' effects on clinical outcomes, or the quality of life of those suffering chronic pain, would need research in patients over long time periods.'

(The paper ‘Amygdala activity contributes to the dissociative effect of cannabis on pain perception' by Michael C. Lee, Markus Ploner, Katja Wiech, Ulrike Bingel, Vishvarani Wanigasekera, Jonathan Brooks, David K. Menon, Irene Tracey (DOI: 10.1016/j.pain.2012.09.017) will appear in PAIN®, Volume 154, Issue 1 (January 2013) published by Elsevier)

Discovery could eventually help diagnose and treat chronic pain

More than 100 million Americans suffer from chronic pain. But treating and studying chronic pain is complex and presents many challenges. Scientists have long searched for a method to objectively measure pain and a new study from Brigham and Women’s Hospital advances that effort. The study appears in the January 2013 print edition of the journal Pain.

"While we need to be cautious in the interpretation of our results, this has the potential to be an exciting discovery for anyone who suffers from chronic pain," said Marco Loggia, PhD, the lead author of the study and a researcher in the Pain Management Center at BWH and the Department of Radiology at Massachusetts General Hospital. "We showed that specific brain patterns appear to track the severity of pain reported by patients, and can predict who is more likely to experience a worsening of chronic back pain while performing maneuvers designed to induce pain. If further research shows this metric is reliable, this is a step toward developing an objective scale for measuring pain in humans."

Specifically, researchers studied 16 adults with chronic back pain and 16 adults without pain and used a brain imaging technique called arterial spin labeling to examine patterns of brain connectivity (that is, to examine how different brain regions interact, or “talk to each other”). They found that when a patient moved in a way that increased their back pain, a network of brain regions called Default Mode Network exhibited changes in its connections. Regions within the network (such as the medial prefrontal cortex) became less connected with the rest of the network, whereas regions outside network (such as the insula) became connected with this network. Some of these observations have been noted in previous studies of fibromyalgia patients, which suggests these changes in brain connectivity might reflect a general feature of chronic pain, possibly common to different patient populations.

"This is the first study using arterial spin labeling to show common networking properties of the brain are affected by chronic pain," said study author Ajay Wasan, MD, MSc, Director of the Section of Clinical Pain Research at BWH. "This novel research supports the use of arterial spin labeling as a tool to evaluate how the brain encodes and is affected by clinical pain, and the use of resting default mode network connectivity as a potential neuroimaging biomarker for chronic pain perception."

Brain imaging identifies bipolar risk

Researchers from the Black Dog Institute and University of NSW have used brain imaging technology to show that young people with a known genetic risk of bipolar but no clinical signs of the condition have clear and quantifiable differences in brain activity when compared to controls.

“We found that the young people who had a parent or sibling with bipolar disorder had reduced brain responses to emotive faces, particularly a fearful face. This is an extremely promising breakthrough,” says study leader Professor Philip Mitchell.

Affecting around 1 in 75 Australians, bipolar disorder involves extreme and often unpredictable fluctuations in mood. The mood swings and associated behaviours such as disinhibited behaviour, aggression and severe depression, have a significant impact on day-to-day life, careers and relationships. Bipolar has the highest suicide rate of all psychiatric disorders.

“We know that bipolar is primarily a biological illness with a strong genetic influence but triggers are yet to be understood. Being able to identify young people at risk will enable implementation of early intervention programs, giving them the best chance for a long and happy life,” says Prof Mitchell.

Researchers used functional MRI to visualise brain activity when participants were shown pictures of happy, fearful or calm (neutral) human faces. Results showed that those with a genetic risk of bipolar displayed significantly reduced brain activity in a specific part of the brain known to regulate emotional responses.

“Our results show that bipolar disorder may be linked to a dysfunction in emotional regulation and this is something we will continue to explore,” Professor Mitchell said.

“And we now have an extremely promising method of identifying children and young people at risk of bipolar disorder.”

 “We expect that early identification will significantly improve outcomes for people that go on to develop bipolar disorder, and possibly even prevent onset in some people.”

Results are published this week in Biological Psychiatry and come from the NHMRC-funded ‘Kids and Sibs study’, the biggest research study in the world focusing on genetic and environmental aspects of bipolar disorder. Based at the Black Dog Institute, the trial is still recruiting.