MRI Technique Detects Evidence of Cognitive Decline Before Symptoms Appear

A magnetic resonance imaging (MRI) technique can detect signs of cognitive decline in the brain even before symptoms appear, according to a new study published online in the journal Radiology. The technique has the potential to serve as a biomarker in very early diagnosis of preclinical dementia.

The World Health Organization estimates that dementia affects more than 35 million people worldwide, a number expected to more than double by 2030. Problems in the brain related to dementia, such as reduced blood flow, might be present for years but are not evident because of cognitive reserve, a phenomenon where other parts of the brain compensate for deficits in one area. Early detection of cognitive decline is critical, because treatments for Alzheimer’s disease, the most common type of dementia, are most effective in this early phase.

Researchers recently studied arterial spin labeling (ASL), a promising MRI technique that doesn’t require injection of a contrast agent. ASL measures brain perfusion, or penetration of blood into the tissue.

"ASL MRI is simple to perform, doesn’t require special equipment and only adds a few minutes to the exam," said study author Sven Haller, M.D., from the University of Geneva in Geneva, Switzerland.

The study group included 148 healthy elderly participants and 65 people with mild cognitive impairment (MCI). The participants underwent brain MRI and a neuropsychological assessment, a common battery of tests used to determine cognitive ability.

Of the 148 healthy individuals, 75 remained stable, while 73 deteriorated cognitively at 18 months clinical follow-up. Those who deteriorated had shown reduced perfusion at their baseline ASL MRI exams, particularly in the posterior cingulate cortex, an area in the middle of the brain that is associated with the default mode network, the neural network that is active when the brain is not concentrating on a specific task. Declines in this network are seen in MCI patients and are more pronounced in those with Alzheimer’s disease.

The pattern of reduced perfusion in the brains of healthy individuals who went on to develop cognitive deficits was similar to that of patients with MCI.

"There is a known close link between neural activity and brain perfusion in the posterior cingulate cortex," Dr. Haller said. "Less perfusion indicates decreased neural activity."

The results suggest that individuals with decreased perfusion detected with ASL MRI may temporarily maintain their cognitive status through the mobilization of their cognitive reserve, but will eventually develop subtle cognitive deficits.

Previous research done with positron emission tomography (PET), the current gold standard for brain metabolism imaging, found that patients with Alzheimer’s disease had reduced metabolism in the same area of the brain where the perfusion abnormalities were found using ASL MRI. This points to a close link between brain metabolism and perfusion, according to Dr. Haller.

ASL MRI has potential as a standalone test or as an adjunct to PET for dementia screening, Dr. Haller said. While PET can identify markers of Alzheimer’s disease in the brain and cerebrospinal fluid, it exposes the patient to radiation. ASL does not expose the patient to radiation and is easy to perform in routine clinical settings.

"ASL might replace the classic yet unspecific fluordesoxyglucose PET that measures brain metabolism. Instead, PET could be done with the new and specific amyloid PET tracers," Dr. Haller said.

The results also support a role for ASL MRI as an alternative to neuropsychological testing.

The researchers plan to perform follow-up studies on the patient group to learn more about ASL and long-term cognitive changes.

MRI Technique Reveals Low Brain Iron in ADHD Patients

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.

Autism affects different parts of the brain in women and men

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.”

Centers throughout the brain work together to make reading possible

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.

Identifying Alzheimer’s using space software

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.”

New imaging technique holds promise for speeding MS research

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.”

Pioneering Study Demonstrates Benefit of Imaging Technique in Identifying Mental Illness

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.”