Posts tagged MRI
Posts tagged MRI
Magnetic resonance imaging (MRI) provides a noninvasive way to measure iron levels in the brains of people with attention deficit hyperactivity disorder (ADHD), according to a study being presented today at the annual meeting of the Radiological Society of North America (RSNA). Researchers said the method could help physicians and parents make better informed decisions about medication.
ADHD is a common disorder in children and adolescents that can continue into adulthood. Symptoms include hyperactivity and difficulty staying focused, paying attention and controlling behavior. The American Psychiatric Association reports that ADHD affects 3 to 7 percent of school-age children.
Psychostimulant medications such as Ritalin are among the drugs commonly used to reduce ADHD symptoms. Psychostimulants affect levels of dopamine, a neurotransmitter in the brain associated with addiction.
"Studies show that psychostimulant drugs increase dopamine levels and help the kids that we suspect have lower dopamine levels," said Vitria Adisetiyo, Ph.D., postdoctoral research fellow at the Medical University of South Carolina in Charleston, S.C. "As brain iron is required for dopamine synthesis, assessment of iron levels with MRI may provide a noninvasive, indirect measure of dopamine."
Dr. Adisetiyo and colleagues explored this possibility by measuring brain iron in 22 children and adolescents with ADHD and 27 healthy control children and adolescents using an MRI technique called magnetic field correlation (MFC) imaging. The technique is relatively new, having been introduced in 2006 by study co-authors and faculty members Joseph A. Helpern, Ph.D., and Jens H. Jensen, Ph.D.
"MRI relaxation rates are the more conventional way to measure brain iron, but they are not very specific," Dr. Adisetiyo said. "We added MFC because it offers more refined specificity."
The results showed that the 12 ADHD patients who had never been on medication had significantly lower MFC than the 10 ADHD patients who had been on psychostimulant medication or the 27 typically developing children and adolescents in the control group. In contrast, no significant group differences were detected using relaxation rates or serum measures. The lower brain iron levels in the non-medicated group appeared to normalize with psychostimulant medication.
MFC imaging’s ability to noninvasively detect the low iron levels may help improve ADHD diagnosis and guide optimal treatment. Noninvasive methods are particularly important in a pediatric population, Dr. Adisetiyo noted.
"This method enables us to exploit inherent biomarkers in the body and indirectly measure dopamine levels without needing any contrast agent," she said.
If the results can be replicated in larger studies, then MFC might have a future role in determining which patients would benefit from psychostimulants—an important consideration because the drugs can become addictive in some patients and lead to abuse of other psychostimulant drugs like cocaine.
"It would be beneficial, when the psychiatrist is less confident of a diagnosis, if you could put a patient in a scanner for 15 minutes and confirm that brain iron is low," she said. "And we could possibly identify kids with normal iron levels who could potentially become addicts."
Along with replicating the results in a larger population of patients, the researchers hope to expand their studies to look at the relationship between cocaine addiction and brain iron.
The ability to measure brain functions non-invasively is important both
for clinical diagnoses and research in Neurology and Psychology. Two main imaging techniques are used: positron emission tomography (PET), which reveals metabolic processes in the brain; and activity of different brain regions is measured on the basis of the cells’ oxygen consumption by magnetic resonance imaging (MRI). A direct comparison of PET and MRI measurements was previously difficult because each had to be performed in a separate machine.
Researchers from the Werner Siemens Imaging Center at the University of Tübingen under the direction of Professor Bernd J. Pichler in collaboration with the Department of Diagnostic and Interventional Radiology, University Hospital Tübingen, and the Tübingen Max Planck Institute for Intelligent Systems have now successfully combined both methods. The researchers are able to explore functional processes in the brain in detail and can better assess what course of action to take. These results were achieved by the use of a PET insert enabling complementary, simultaneous PET/MRI scans. It was developed and built at the University of Tübingen.
The researchers could identify in certain regions a mismatch between glucose metabolism related brain activation measured with PET and oxygenation related signals, measured with MRI. Furthermore information about functional connectivity in the brain could be derived from MRI and from dynamic PET data. These results help to further decipher the nature of brain function, and are ultimately useful for basic research as well as clinical practice. The study, by lead author Dr. Hans Wehrl of Professor Bernd J. Pichler’s research team is soon to be published in the journal “Nature Medicine”.
In PET imaging the distribution of a weakly radioactive substance is shown in cross sections of the body, enabling doctors to see many different metabolic and physiological functions at work. Functional MRI (fMRI) allows researchers to depict changes in blood oxygenation that are associated with brain function. This measurement of functional active brain regions is also important for the planning of brain surgeries, where particular care must be taken in certain areas. The ability to collect different kinds of data from different scans simultaneously represents a major step forward in the fields using these technologies.
Autism affects different parts of the brain in females with autism than males with autism, a new study reveals. The research is published today in the journal Brain as an open-access article.
Scientists at the Autism Research Centre at the University of Cambridge used magnetic resonance imaging to examine whether autism affects the brain of males and females in a similar or different way. They found that the anatomy of the brain of someone with autism substantially depends on whether an individual is male or female, with brain areas that were atypical in adult females with autism being similar to areas that differ between typically developing males and females. This was not seen in men with autism.
“One of our new findings is that females with autism show neuroanatomical ‘masculinization’,” said Professor Simon Baron-Cohen, senior author of the paper. “This may implicate physiological mechanisms that drive sexual dimorphism, such as prenatal sex hormones and sex-linked genetic mechanisms.”
Autism affects 1% of the general population and is more prevalent in males. Most studies have therefore focused on male-dominant samples. As a result, our understanding of the neurobiology of autism is male-biased.
“This is one of the largest brain imaging studies of sex/gender differences yet conducted in autism. Females with autism have long been under-recognized and probably misunderstood,” said Dr Meng-Chuan Lai, who led the research project. “The findings suggest that we should not blindly assume that everything found in males with autism applies to females. This is an important example of the diversity within the ‘spectrum’.”
Dr Michael Lombardo, who co-led the study, added that although autism manifests itself in many different ways, grouping by gender may help provide a better understanding of this condition.
He said: “Autism as a whole is complex and vastly diverse, or heterogeneous, and this new study indicates that there are ways to subgroup the autism spectrum, such as whether an individual is male or female. Reducing heterogeneity via subgrouping will allow research to make significant progress towards understanding the mechanisms that cause autism.”
A combination of brain scans and reading tests has revealed that several regions in the brain are responsible for allowing humans to read.
The findings open up the possibility that individuals who have difficulty reading may only need additional training for specific parts of the brain — targeted therapies that could more directly address their individual weaknesses.
“Reading is a complex task. No single part of the brain can do all the work,” said Qinghua He, postdoctoral research associate at the USC Brain and Creativity Institute, based at the USC Dornsife College of Letters, Arts and Sciences, and first author of a study on this research that was published in The Journal of Neuroscience on July 31.
The study looked at the correlation between reading ability and brain structure revealed by high-resolution magnetic resonance imaging (MRI) scans of more than 200 participants.
To control for external factors, the participants were about the same age and education level (college students); right-handed (lefties use the opposite hemisphere of their brain for reading); and all had about the same language skills (Chinese-speaking, with English as a second language for more than nine years). Their IQ, response speed and memory were also tested.
The study first collected data for seven different reading tests of a sample of more than 400 participants. These tests were intended to explore three aspects of their reading ability: phonological decoding ability (the ability to sound out printed words); form-sound association (how well participants could make connections between a new word and sound); and naming speed (how quickly participants were able to read out loud).
Each of these aspects, it turned out, was related to the gray matter volume — the amount of neurons — in different parts of the brain.
The MRI analysis showed that phonological decoding ability was strongly connected with gray matter volume in the left superior parietal lobe (around the top/rear of the brain); form-sound association was strongly connected with the hippocampus and cerebellum; and naming speed lit up a variety of locations around the brain.
“Our results strongly suggest that reading consists of unique capacities and is supported by distinct neural systems that are relatively independent of general cognitive abilities,” said Gui Xue, corresponding author of the study. Xue was formerly a research assistant professor at USC and now is a professor and director of the Center for Brain and Learning Sciences at Beijing Normal University.
“Although there is no doubt that reading has to build up existing neural systems due to the short history of written language in human evolution, years of reading experiences might have finely tuned the system to accommodate the specific requirement of a given written system,” Xue said.
He and Xue collaborated with Chunhui Chen and Qi Dong of Beijing Normal University; Chuansheng Chen of the University of California, Irvine; and Zhong-Lin Lu of Ohio State University.
One of the top features of this study was its unusually wide sample size, according to researchers. Typically, MRI studies test a relatively small sample of individuals — perhaps around 20 to 30 — because of the high cost of using the MRI machine. Testing a single individual can cost about $500, depending on the nature of the research.
The team had the good fortune of receiving access to Beijing Normal University’s new MRI center — the BNU Imaging Center for Brain Research — just before it opened to the public. With support from several grants, the researchers were able to conduct MRI tests on 233 individuals.
Next, the group will explore how to combine data from other factors, such as white matter, resting and task functional MRI, as well as more powerful machine-learning techniques, to improve the accuracy of individuals’ reading abilities.
“Research along this line will enable the early diagnosis of reading difficulties and the development of more targeted therapies,” Xue said.
Software for processing satellite pictures taken from space is now helping medical researchers to establish a simple method for wide-scale screening for Alzheimer’s disease.
Used in analysing magnetic resonance images (MRIs), the AlzTools 3D Slicer tool was produced by computer scientists at Spain’s Elecnor Deimos, who drew on years of experience developing software for ESA’s Envisat satellite to create a program that adapted the space routines to analyse human brain scans.
“If you have a space image and you have to select part of an image – a field or crops – you need special routines to extract the information,” explained Carlos Fernández de la Peña of Deimos. “Is this pixel a field, or a road?”
Working for ESA, the team gained experience in processing raw satellite image data by using sophisticated software routines, then homing in on and identifying specific elements.
“Looking at and analysing satellite images can be compared to what medical doctors have to do to understand scans like MRIs,” explained Mr Fernández de la Peña.
"They also need to identify features indicating malfunctions according to specific characteristics.”
Adapting the techniques for analysing complicated space images to an application for medical scientists researching into the Alzheimer disease required close collaboration between Deimos and specialists from the Technical University of Madrid.
The tool is now used for Alzheimer’s research at the Medicine Faculty at the University of Castilla La Mancha in Albacete in Spain.
Space helping medical research
“We work closely with Spanish industry and also with Elecnor Deimos though ProEspacio, the Spanish Association of Space Sector Companies, to support the spin-off of space technologies like this one,” said Richard Seddon from Tecnalia, the technology broker for Spain for ESA’s Technology Transfer Programme.
“Even if being developed for specific applications, we often see that space technologies turn out to provide innovative and intelligent solutions to problems in non-space sectors, such as this one.
“It is incredible to see that the experience and technologies gained from analysing satellite images can help doctors to understand Alzheimer’s disease.”
Using AlzTools, Deimos scientists work with raw data from a brain scan rather than satellite images. Instead of a field or a road in a satellite image, they look at brain areas like the hippocampus, where atrophy is associated with Alzheimer’s.
In both cases, notes Mr Fernández de la Peña, “You have a tonne of data you have to make sense of.”
UC Berkeley researchers have found that a lack of sleep, which is common in anxiety disorders, may play a key role in ramping up the brain regions that contribute to excessive worrying.
Neuroscientists have found that sleep deprivation amplifies anticipatory anxiety by firing up the brain’s amygdala and insular cortex, regions associated with emotional processing. The resulting pattern mimics the abnormal neural activity seen in anxiety disorders. Furthermore, their research suggests that innate worriers – those who are naturally more anxious and therefore more likely to develop a full-blown anxiety disorder – are acutely vulnerable to the impact of insufficient sleep.
“These findings help us realize that those people who are anxious by nature are the same people who will suffer the greatest harm from sleep deprivation,” said Matthew Walker, a professor of psychology and neuroscience at UC Berkeley and senior author of the paper, which was published in the Journal of Neuroscience.
The results suggest that people suffering from such maladies as generalized anxiety disorder, panic attacks and post-traumatic stress disorder, may benefit substantially from sleep therapy. At UC Berkeley, psychologists such as Allison Harvey, a co-author on the Journal of Neuroscience paper, have been garnering encouraging results in studies that use sleep therapy on patients with depression, bipolar disorder and other mental illnesses.
“If sleep disruption is a key factor in anxiety disorders, as this study suggests, then it’s a potentially treatable target,” Walker said. “By restoring good quality sleep in people suffering from anxiety, we may be able to help ameliorate their excessive worry and disabling fearful expectations.”
While previous research has indicated that sleep disruption and psychiatric disorders often occur together, this latest study is the first to causally demonstrate that sleep loss triggers excessive anticipatory brain activity associated with anxiety, researchers said.
“It’s been hard to tease out whether sleep loss is simply a byproduct of anxiety, or whether sleep disruption causes anxiety,” said Andrea Goldstein, a UC Berkeley doctoral student in neuroscience and lead author of the study. “This study helps us understand that causal relationship more clearly.”
In their experiments, performed at UC Berkeley’s Sleep and Neuroimaging Laboratory, Walker and his research team scanned the brains of 18 healthy young adults as they viewed dozens of images, first after a good night’s rest, and again after a sleepless night. The images were either neutral, disturbing or alternated between both.
Participants in the experiments reported a wide range of baseline anxiety levels, but none fit the criteria for a clinical anxiety disorder. After getting a full night’s rest at the lab, which researchers monitored by measuring neural electrical activity, their brains were scanned via functional MRI as they waited to be shown, and then viewed 90 images during a 45-minute session.
To trigger anticipatory anxiety, researchers primed the participants using one of three visual cues prior to each series of images. A large red minus sign signaled to participants that they were about to see a highly unpleasant image, such as a death scene. A yellow circle portended a neutral image, such as a basket on a table. Perhaps most stressful was a white question mark, which indicated that either a grisly image or a bland, innocuous one was coming, and kept participants in a heightened state of suspense.
When sleep-deprived and waiting in suspenseful anticipation for a neutral or disturbing image to appear, activity in the emotional brain centers of all the participants soared, especially in the amygdala and the insular cortex. Notably, the amplifying impact of sleep deprivation was most dramatic for those people who were innately anxious to begin with.
“This discovery illustrates how important sleep is to our mental health,” said Walker. “It also emphasizes the intimate relationship between sleep and psychiatric disorders, both from a cause and a treatment perspective.”
Researchers at the University of British Columbia have developed a new magnetic resonance imaging (MRI) technique that detects the telltale signs of multiple sclerosis in finer detail than ever before – providing a more powerful tool for evaluating new treatments.
The technique analyzes the frequency of electro-magnetic waves collected by an MRI scanner, instead of the size of those waves. Although analyzing the number of waves per second had long been considered a more sensitive way of detecting changes in tissue structure, the math needed to create usable images had proved daunting.
Multiple sclerosis (MS) occurs when a person’s immune cells attack the protective insulation, known as myelin, that surrounds nerve fibres. The breakdown of myelin impedes the electrical signals transmitted between neurons, leading to a range of symptoms, including numbness or weakness, vision loss, tremors, dizziness and fatigue.
Alexander Rauscher, an assistant professor of radiology, and graduate student Vanessa Wiggermann in the UBC MRI Research Centre, analyzed the frequency of MRI brain scans. With Dr. Anthony Traboulsee, an associate professor of neurology and director of the UBC Hospital MS Clinic, they applied their method to 20 MS patients, who were scanned once a month for six months using both conventional MRI and the new frequency-based method.
Once scars in the myelin, known as lesions, appeared in conventional MRI scans, Rauscher and his colleagues went back to earlier frequency-based images of those patients. Looking in the precise areas of those lesions, they found frequency changes – indicating tissue damage – at least two months before any sign of damage appeared on conventional scans. The results were published in the June 12 issue of Neurology.
“This technique teases out the subtle differences in the development of MS lesions over time,” Rauscher says. “Because this technique is more sensitive to those changes, researchers could use much smaller studies to determine whether a treatment – such as a new drug – is slowing or even stopping the myelin breakdown.”
MRI may be an effective way to diagnose mental illnesses such as bipolar disorder, according to experts from the Icahn School of Medicine at Mount Sinai. In a landmark study using advanced techniques, the researchers were able to correctly distinguish bipolar patients from healthy individuals based on their brain scans alone. The data are published in the journal Psychological Medicine.
Currently, most mental illnesses are diagnosed based on symptoms only, creating an urgent need for new approaches to diagnosis. In bipolar disorder, there may be a significant delay in diagnosis due to the complex clinical presentation of the illness. In this study, Sophia Frangou, MD, Professor of Psychiatry and Chief of the Psychosis Research Program at the Icahn School of Medicine at Mount Sinai teamed up with Andy Simmons, MD, of the Kings College London and Janaina Mourao-Miranda, MD, of University College London, to explore whether brain imaging could help correctly identify patients with bipolar disorder.
“Bipolar disorder affects patients’ ability to regulate their emotions successfully, which puts them at great disadvantage in their lives,” said Dr. Frangou. “The situation is made worse by unacceptably long delays, sometimes of up to 10 years, in making the correct diagnosis. Bipolar disorder may be easily misdiagnosed for other disorders, such as depression or schizophrenia. This is why bipolar disorder ranks among the top ten disorders causing significant disability worldwide.”
Dr. Frangou and her team used MRI to scan the brains of people with bipolar disorder and of healthy individuals. Using advanced computational models, they were successful in correctly separating people with bipolar disorder from healthy individuals with 73 percent accuracy using their brain imaging scans alone. They replicated their finding in a separate group of patients and healthy individuals and found a 72 percent accuracy rate.
Dr. Simmons added, “The level of accuracy we achieved is comparable to that of many other tests used in medicine. Additionally, brain scanning is very acceptable to patients as most people consider it a routine diagnostic test.”
“This approach does not undermine the importance of rigorous clinical assessment and the importance of building relationships with patients but provides biological justification for the type of diagnosis made,” said Dr. Frangou. “However, diagnostic imaging for psychiatry is still under investigation and not ready for widespread use. Nonetheless, our results together with those from other labs are a harbinger of a major shift in the way we approach diagnosis in psychiatry.”
The Quantified Brain of a Self-Tracking Neuroscientist
A neuroscientist is getting a brain scan twice every week for a year to try to see how neural networks behave over time
Russell Poldrack, a neuroscientist at the University of Texas at Austin, is undertaking some intense introspection. Every day, he tracks his mood and mental state, what he ate, and how much time he spent outdoors. Twice a week, he gets his brain scanned in an MRI machine. And once a week, he has his blood drawn so that it can be analyzed for hormones and gene activity levels. Poldrack plans to gather a year’s worth of brain and body data to answer an unexplored question in the neuroscience community: how do brain networks behave and change over a year?
Older people with a history of migraines and depression may have smaller brain tissue volumes than people with only one or neither of the conditions, according to a new study in the May 22, 2013, online issue of Neurology®, the medical journal of the American Academy of Neurology.
“Studies show that people with migraine have double the risk of depression compared to people without migraine,” said study author Larus S. Gudmundsson, PhD, with the National Institute on Aging and the Uniformed Services University of the Health Sciences, in Bethesda, Md. Gudmundsson is also a member of the American Academy of Neurology. “We wanted to find out whether having both conditions together possibly affected brain size.”
For the study, 4,296 people with an average age of 51 were tested for migraine headache from 1967 to 1991; they were later assessed from 2002 to 2006 at an average age of 76 for a history of major depressive disorder (depression). Participants also underwent MRI, from which brain tissue volumes were estimated. A total of 37 participants had a history of both migraine and depression, while 2,753 had neither condition.
The study found that people with both migraine and depression had total brain tissue volumes an average of 19.2 milliliters smaller than those without either condition. There was no difference in the total brain volume when comparing people with only one of the conditions to people with neither condition.
“It is important to note that participants in this study were imaged using MRI once, so we cannot say that migraine and depression resulted in brain atrophy. In future studies, we need to examine at what age participants develop both migraine and depression and measure their brain volume changes over time in order to determine what comes first,” said Gudmundsson.
Gudmundsson noted that some of the factors leading to a joint effect of migraine and depression on brain volume may include pain, brain inflammation, genetics and differences in a combination of social and economic factors. “Our study suggests that people with both migraine and depression may represent a unique group from those with only one of these conditions and may also require different strategies for long-term treatment.”