Posts tagged neuroimaging
Articles and news from the latest research reports.
Researchers report progress in quest to create objective method of detecting pain
A method of analyzing brain structure using advanced computer algorithms accurately predicted 76 percent of the time whether a patient had lower back pain in a new study by researchers from the Stanford University School of Medicine.
The study, published online Dec. 17 in Cerebral Cortex, reported that using these algorithms to read brain scans may be an early step toward providing an objective method for diagnosing chronic pain.
“People have been looking for an objective pain detector — a ‘pain scanner’ — for a long time,” said Sean Mackey, MD, PhD, chief of the Division of Pain Medicine and professor of anesthesiology, pain and perioperative medicine, and of neurosciences and neurology. “We’re still a long way from that, but this method may someday augment self-reporting as the primary way of determining whether a patient is in chronic pain.”
The need for a better way to objectively measure pain instead of relying solely on self-reporting has long been acknowledged. But the highly subjective nature of pain has made this an elusive goal. Advances in neuroimaging techniques have initiated a debate over whether this may be possible. Such a tool would be particularly useful in treating very young or very old patients or others who have difficulty communicating, Mackey said.
In a study published last year in PLoS ONE, Mackey and colleagues used computer algorithms to analyze magnetic resonance imaging scans of the brain to accurately measure thermal pain in research subjects 81 percent of the time. But the question remained whether this could be a successful method for measuring chronic pain.
The goal of the new study was to accurately identify patients with lower back pain vs. healthy individuals on the basis of structural changes to the brain, and also to investigate possible pathological differences across the brain.
Researchers conducted MRI scans of 47 subjects who had lower back pain and 47 healthy subjects. Both groups were screened for medication use and mood disorders. The average age was 37.
The idea was to “train” a linear support vector machine — a computer algorithm invented in 1995 — on one set of individuals, and then use that computer model to accurately read the brain scans and classify pain in a completely new set of individuals.
The method successfully predicted the patients with lower back pain 76 percent of the time.
“Lower back pain is the most common chronic condition we deal with,” Mackey said. “In many cases, we don’t understand the cause. What we have learned is that the problem may not be in the back, but in the amplification coming from the back to the brain and nervous system. In this study, we did identify brain regions we think are playing a role in this phenomena.”
Neuroscience offers a glimpse into the mind - and our future
Hassan Rasouli recently accomplished a remarkable feat: He lifted his thumb in a way that suggests he was making a thumbs-up gesture.
The feat was a remarkable one since doctors at Sunnybrook Health Sciences Centre in Toronto had diagnosed him as being in a persistent vegetative state (PVS), a mysterious condition in which patients appear to be awake but show no clinical signs of conscious awareness.
The condition first came to prominence in 1998 when family members, and then courts and politicians, engaged in a protracted battle over the care of Floridian Terri Schiavo. The matter was finally settled in 2005 when Schiavo, who was in a persistent vegetative state, was removed from life support and died.
Doctors at Sunnybrook similarly wanted to transfer Rasouli to palliative care, but Rasouli’s family refused. The doctors therefore sought a court order, and the Supreme Court of Canada heard arguments in the case on Monday.
The court’s decision might not affect Rasouli since, given his ability to give a thumbs-up gesture, he is no longer considered to be in a persistent vegetative state (PVS). But the case could have a profound impact on the many other patients who have been diagnosed as being in a PVS, as it could answer pressing legal questions about when someone can be removed from life support, and who has the authority to order that such support be discontinued.
The Rasouli case also raises further troubling questions of fact: Was Rasouli’s ability to give a thumbs-up gesture an indication that his condition had improved, or was he never in a persistent vegetative state? Was he, and other people similarly diagnosed, always consciously aware, but, thanks to being trapped in a paralyzed body, unable to express his thoughts?
(Illustration by Bert Dodson)
Combination of imaging exams improves Alzheimer’s diagnosis
A combination of diagnostic tests, including imaging and cerebrospinal fluid biomarkers can improve prediction of conversion from mild cognitive impairment (MCI) to Alzheimer’s disease, according to a new study published online in the journal Radiology.
"Because new treatments are likely to be most effective at the earliest stages of Alzheimer’s disease, there is great urgency to develop sensitive markers that facilitate detection and monitoring of early brain changes in individuals at risk," said Jeffrey R. Petrella, M.D., associate professor of radiology, division of neuroradiology, and director of the Alzheimer’s Disease Research Lab at Duke University Medical Center (DUMC) in Durham, N.C. "Our study looks at whether more sophisticated diagnostic tests such as magnetic resonance imaging (MRI), positron emission tomography (PET) and spinal fluid protein analysis might provide additional prognostic information, compared to more readily available cognitive and blood testing."
According to the World Health Organization, more than 35 million people worldwide are living with Alzheimer’s disease, which is incurable, and the prevalence is expected to double by 2030.
"Although there is no cure for Alzheimer’s disease, there are four symptomatic treatments that might provide some benefits," said coauthor P. Murali Doraiswamy, M.D., professor of psychiatry at DUMC. "So developing the right combination of diagnostic tests is critical to make sure we enable an accurate and early diagnosis in patients, so they can evaluate their care options."
Anatomical Brain Images Alone Can Accurately Diagnose Chronic Neuropsychiatric Illnesses
Objective
Diagnoses using imaging-based measures alone offer the hope of improving the accuracy of clinical diagnosis, thereby reducing the costs associated with incorrect treatments. Previous attempts to use brain imaging for diagnosis, however, have had only limited success in diagnosing patients who are independent of the samples used to derive the diagnostic algorithms. We aimed to develop a classification algorithm that can accurately diagnose chronic, well-characterized neuropsychiatric illness in single individuals, given the availability of sufficiently precise delineations of brain regions across several neural systems in anatomical MR images of the brain.
Methods
We have developed an automated method to diagnose individuals as having one of various neuropsychiatric illnesses using only anatomical MRI scans. The method employs a semi-supervised learning algorithm that discovers natural groupings of brains based on the spatial patterns of variation in the morphology of the cerebral cortex and other brain regions. We used split-half and leave-one-out cross-validation analyses in large MRI datasets to assess the reproducibility and diagnostic accuracy of those groupings.
Results
In MRI datasets from persons with Attention-Deficit/Hyperactivity Disorder, Schizophrenia, Tourette Syndrome, Bipolar Disorder, or persons at high or low familial risk for Major Depressive Disorder, our method discriminated with high specificity and nearly perfect sensitivity the brains of persons who had one specific neuropsychiatric disorder from the brains of healthy participants and the brains of persons who had a different neuropsychiatric disorder.
Conclusions
Although the classification algorithm presupposes the availability of precisely delineated brain regions, our findings suggest that patterns of morphological variation across brain surfaces, extracted from MRI scans alone, can successfully diagnose the presence of chronic neuropsychiatric disorders. Extensions of these methods are likely to provide biomarkers that will aid in identifying biological subtypes of those disorders, predicting disease course, and individualizing treatments for a wide range of neuropsychiatric illnesses.
Brain study shows why some people are more in tune with what they want
Wellcome Trust researchers have discovered how the brain assesses confidence in its decisions. The findings explain why some people have better insight into their choices than others.
Throughout life, we’re constantly evaluating our options and making decisions based on the information we have available. How confident we are in those decisions has clear consequences. For example, investment bankers have to be confident that they’re making the right choice when deciding where to put their clients’ money.
Researchers at the Wellcome Trust Centre for Neuroimaging at UCL led by Professor Ray Dolan have pinpointed the specific areas of the brain that interact to compute both the value of the choices we have in front of us and our confidence in those choices, giving us the ability to know what we want.
The team used functional magnetic resonance imaging (fMRI) to measure activity in the brains of twenty hungry volunteers while they made choices between food items that they would later eat. To determine the subjective value of the snack options, the participants were asked to indicate how much they would be willing to pay for each snack. Then after making their choice, they were asked to report how confident they were that they had made the right decision and selected the best snack.
It has previously been shown that a region at the front of the brain, the ventromedial prefrontal cortex, is important for working out the value of decision options. The new findings reveal that the level of activity in this area is also linked to the level of confidence participants placed on choosing the best option. The study also shows that the interaction between this area of the brain and an adjacent area reflects participants’ ability to access and report their level of confidence in their choices.
Dr Steve Fleming, a Sir Henry Wellcome Postdoctoral Fellow now based at New York University, explains: “We found that people’s confidence varied from decision to decision. While we knew where to look for signals of value computation, it was very interesting to also observe neural signals of confidence in the same brain region.”
Dr Benedetto De Martino, a Sir Henry Wellcome Postdoctoral Fellow at UCL, added: “Overall, we think our results provide an initial account both of how people make choices, and also their insight into the decision process.”
(Source: eurekalert.org)
Research shows brain hub activity different in coma patients
A team of French and British researchers has found that brain region activity for coma patients is markedly different than for healthy people. In their paper published in the Proceedings of the National Academy of Sciences, the group describes the differences found when comparing fMRI scans of people in a coma with healthy volunteers.
To gain a better understanding of what goes on in the brain when a person is in a coma, and perhaps the nature of consciousness, the researchers performed fMRI brain scans on 17 people who had recently become comatose due to medical conditions that led to blockage of oxygen to the brain. They then compared those scans to those taken of 20 healthy volunteers.
In analyzing the results the team found that global comparisons between the two groups revealed very few if any differences. Blood continued to flow to all of the parts of the brain. When focusing on the brain as a network however, they found very large differences.
To look at the brain as a network requires looking at its different parts as regions that communicate with one another, forming hubs. In healthy people, certain regions or hubs are busier than others as evidenced by more blood flow. But for the people in a coma, the team found, the normally busy hubs grew less busy, while other hubs grew busier, indicating a major change in the flow of information.
The researchers suggest that the brain scans reveal that the normally busy hubs in healthy people are centers of consciousness and their reduced role in communications in comatose patients suggests that they are most likely not conscious of their existence. They point to prior research that has suggested that being in a coma is more likely closer to the experience of being under anesthesia than being asleep. They add that the their research indicates that regions of the brain that are responsible for conscience thought likely require more oxygen rich blood, and are thus likely to be more sensitive to oxygen deprivation than other areas of the brain, which might explain why people go into a coma when those regions are harmed.
Scientists image brain structures that deteriorate in Parkinson’s
A new imaging technique developed at MIT offers the first glimpse of the degeneration of two brain structures affected by Parkinson’s disease.
The technique, which combines several types of magnetic resonance imaging (MRI), could allow doctors to better monitor patients’ progression and track the effectiveness of potential new treatments, says Suzanne Corkin, MIT professor emerita of neuroscience and leader of the research team. The first author of the paper is David Ziegler, who received his PhD in brain and cognitive sciences from MIT in 2011.
The study, appearing in the Nov. 26 online edition of the Archives of Neurology, is also the first to provide clinical evidence for the theory that Parkinson’s neurodegeneration begins deep in the brain and advances upward.
“This progression has never been shown in living people, and that’s what was special about this study. With our new imaging methods, we can see these structures more clearly than anyone had seen them before,” Corkin says.
MRI shows brain disruption in patients with post-concussion syndrome
MRI shows changes in the brains of people with post-concussion syndrome (PCS), according to a new study published online in the journal Radiology. Researchers hope the results point the way to improved detection and treatment for the disorder.
PCS affects approximately 20 percent to 30 percent of people who suffer mild traumatic brain injury (MTBI)—defined by the World Health Organization as a traumatic event causing brief loss of consciousness and/or transient memory dysfunction or disorientation. Symptoms of PCS include headache, poor concentration and memory difficulty.
Conventional neuroimaging cannot distinguish which MTBI patients will develop PCS.
"Conventional imaging with CT or MRI is pretty much normal in MTBI patients, even though some go on to develop symptoms, including severe cognitive problems," said Yulin Ge, M.D., associate professor, Department of Radiology at the NYU School of Medicine in New York City. "We want to try to better understand why and how these symptoms arise."
Dr. Ge’s study used MRI to look at the brain during its resting state, or the state when it is not engaged in a specific task, such as when the mind wanders or while daydreaming. The resting state is thought to involve connections among a number of regions, with the default mode network (DMN) playing a particularly important role.
"Baseline DMN is very important for information processing and maintenance," Dr. Ge said.
Alterations in DMN have been found in several psychiatric disorders, including Alzheimer’s disease, autism and schizophrenia, but little is known about DMN connectivity changes in MTBI.
For the new study, Dr. Ge and colleagues used resting-state functional MRI to compare 23 MTBI patients who had post-traumatic symptoms within two months of the injury and 18 age-matched healthy controls. Resting state MRI detects distinct changes in baseline oxygen level fluctuations associated with brain functional networks between patients with MTBI and control patients.
The MRI results showed that communication and information integration in the brain were disrupted among key DMN structures after mild head injury, and that the brain tapped into different neural resources to compensate for the impaired function.
"We found decreased functional connectivity in the posterior network of the brain and increased connectivity in the anterior component, probably due to functional compensation in patients with PCS," Dr. Ge said. "The reduced posterior connectivity correlated positively with neurocognitive dysfunction."
Dr. Ge and the other researchers hope to recruit additional MTBI patients for further studies with an eye toward developing a biomarker to monitor disease progression and recovery as well as treatment effects.
"We want to do studies to look at the changes in the network over time and correlate these functional changes with structural changes in the brain," he said. "This could give us hints on treatments to bring back cognitive function."
(Source: medicalxpress.com)
Ever wondered what your brain sounds like? Now you can hear the sweet melody of the mind by listening to sound composed from an analysis of brain activity.
Seeing someone yawn or hearing someone laugh makes you likely to follow suit. The same goes for scratching an itch. Now, for the first time, researchers have investigated the neural basis of contagious itch, identifying several brain regions whose activity predicts how susceptible people are to feeling itchy when they see someone else scratch.
Researchers in the United Kingdom showed volunteers video clips of people scratching an arm or a spot on their chest. Sure enough, subjects reported feeling more itchy, and most scratched themselves at least once during the experiment. When a subset of the volunteers watched the videos inside an functional magnetic resonance imaging scanner, the scans revealed activity in several of the same brain regions known to fire up in response to an itch-inducing histamine injection.
Activity in three of these areas correlated with subjects’ self-reported itchiness, the team reports online in the Proceedings of the National Academy of Sciences. Personality tests suggest that the trait that best predicts susceptibility to contagious itch is neuroticism, not empathy, as some researchers have suggested.