Brain Imaging Patterns Moving Closer To Identifying Schizophrenia on Functional MRI

MedicalResearch.com Interview with:

Irina Rish PhD IBM T.J. Watson Research Center Yorktown Heights, NY 10598

Dr. Rish

Irina Rish PhD
IBM T.J. Watson Research Center
Yorktown Heights, NY 10598 

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Schizophrenia is a chronic and severe psychiatric disorder that affects roughly about 1% of population. Although it is not as common as other mental disorders, such as depression, anxiety, and attention deficit disorder (ADD), and so on, schizophrenia  is perhaps one of  the most debilitating psychiatric disorders,  preventing people from normal  functioning in daily life. It is characterized primarily by a range of psychotic symptoms, including hallucinations (false auditory, visual or tactile perceptions detached from reality), as well as delusions, disorganized thoughts, speech and behavior, and multiple other symptoms including difficulty showing (and recognizing) emotions, poor executive functioning, inattentiveness, problems with working memory,  and so one. Overall, schizophrenia has a devastating impact not only on patients and their families, but on the economy, as it was estimated to cost the US about 2% off  gross national product in treatment costs, missed work, etc.
Thus, taking steps towards better understanding of the disease can potentially lead to more accurate early diagnosis and better treatments.

In this work, the objective was to identify “statistical biomarkers’ of schizophrenia from brain imaging data (specifically, functional MRI), i.e. brain activity patterns that would be capable of accurately discriminating between schizophrenic patients and controls, and reproducible (stable) across multiple datasets. The focus on both predictive accuracy (generalization to previously unseen subjects) as well as on stability (reproducibility) across multiple datsets differentiates our work from majority of similar studies in neuroimaging field that tend to focus only on statistically significant differences between such patterns on a fixed dataset, and may not reliably generalize to new data.

Our prior work on neuroimaging-based analysis of schizoprenia http://journals.plos.org/plosone/article/related?id=10.1371/journal.pone.0050625, as well as other research in the field, suggest that disrupted functional connectivity can be a much more informative source of discriminative patterns than local changes in brain activations, since schizophrenia is well known to be a “network disease”, rather than a localized one.

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MRI At Six Months Can Predict Which High Risk Babies Will Develop Autism

MedicalResearch.com Interview with:

Joseph Piven, MD The Thomas E. Castelloe Distinguished Professor of Psychiatry UNC School of Medicine Director of the Carolina Institute for Developmental Disabilities Co-senior author of the study

Dr. Piven

Joseph Piven, MD
The Thomas E. Castelloe Distinguished Professor of Psychiatry
UNC School of Medicine
Director of the Carolina Institute for Developmental Disabilities
Co-senior author of the study

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Babies with older siblings with autism are at an increased risk (20%) of getting autism over the general population (1%).  Infants who later are diagnosed with autism don’t have any of the stigmata of autism in the first year of life. The symptoms of autism unfold in the first and particularly in the second year of life and beyond.

We have evidence to support the idea that behavioral symptoms of autism arise from changes in the brain that occur very early in life. So we have employed MRI and computer analyses to study those early brain changes and abnormalities in infancy to see if early brain changes at 6 months of age can predict whether babies at high-risk of developing autism will indeed develop the condition at age two.

For this particular study, we used data from MRIs of six-month olds to show the pattern of synchronization or connection across brain regions throughout the brain and then predict which babies at high familial risk of developing autism would be most likely to be diagnosed with the condition at age two.

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MRI Guided Prostate Biopsies Can Improve Care and Reduce Costs

MedicalResearch.com Interview with:

Vikas Gulani, MD, PhD Director, MRI, UH Cleveland Medical Center Associate Professor, Radiology, CWRU School of Medicine

Dr. Gulani

Vikas Gulani, MD, PhD
Director, MRI, UH Cleveland Medical Center
Associate Professor, Radiology, CWRU School of Medicine

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: We wanted to learn if performing MR before prostate biopsy, followed by MR guided strategies for biopsy, are cost effective for the diagnosis of prostate cancer in men who have not previously undergone a biopsy and who have a suspicion of prostate cancer.

The most significant findings are as follows:

We found that all three MR guided strategies for lesion targeting (cognitive targeting, MR-ultrasound fusion targeting, and in-gantry targeting) are cost effective, as the increase in net health benefits as measured by addition of quality adjusted life years (QALY), outweigh the additional costs according to commonly accepted willingness to pay thresholds in the United States.

Cognitive targeting was the most cost effective. In-gantry biopsy added the most health benefit, and this additional benefit was cost-effective as well.

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Ischemic Stroke: Collateral Blood Vessels Detected by Arterial Spin Labeling MRI Correlates With Good Neurological Outcome

MedicalResearch.com Interview with:
Jalal B. Andre M.D., D.A.B.R.®

Drector of neurological MRI and
MRI safety officer at Harborview Medical Center
University of Washington 

MedicalResearch.com: What is the background for this study?

Response: Acute ischemic stroke (AIS) patients with good collaterals have better clinical outcomes. AIS is characterized by an ischemic penumbra, a region of salvageable brain tissue, that surrounds a core of irreversible ischemic infarct. The penumbra is tenuously perfused by collateral blood vessels which, if extensive enough, can maintain penumbral perfusion, improving the odds that a larger volume of brain tissue will survive. Standard, first-line methods for evaluating collaterals in the acute setting include CT angiography, MR angiography, and (less commonly) digital subtraction angiography. Arterial spin labeling (ASL) is an emerging MRI technique that assesses cerebral perfusion. Its advantages include relatively short scan time (4-6 minutes), lack of ionizing radiation, and independence from an exogenous contrast agent (contraindicated in patients with impaired renal function or documented sensitivity). Collaterals can be identified within ASL images as foci of curvilinear hyperintensity bordering regions of hypoperfusion. We sought to explore a novel relationship between the presence of ASL collaterals (ASLc) and neurological outcome in acute ischemic stroke patients.

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Subtle Differences in Brain Volume Detected On MRI In ADHD

MedicalResearch.com Interview with:
M. (Martine) Hoogman PhD.

Postdoc and PI of ENIGMA-ADHD
Radboud universitair medisch centrum
Department of Human Genetics
Nijmegen, The Netherlands

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: There are many neuro-imaging studies aimed at investigating structural brain changes related to ADHD, but the results are often inconclusive.

There are two main reasons for this:

1) the small sample size of the studies and
2) the heterogeneous methods used.

We tried to address these issues by forming an international collaboration to provide a sample size sufficient to detect even small effects in volume differences. And in addition, we analyzed all the raw scans again using homogenized methods. There are data of more than 1700 patients (aged 4-63 years of age) and more than 1500 healthy controls in our dataset, coming from 23 sites around the world. We studied the possible volume differences between cases and controls of 7 subcortical regions and intracranial volume by performing mega- and meta-analysis.

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Can Patients With A Pacemaker or Defibrillator Get An MRI?

MedicalResearch.com Interview with:

Robert Russo, MD, PhD, FACC The Scripps Research Institute The La Jolla Cardiovascular Research Institute

Dr. Robert Russo

Robert Russo, MD, PhD, FACC
The Scripps Research Institute
The La Jolla Cardiovascular Research Institute 

MedicalResearch.com: What is the background for this study?

Response: For an estimated 2 million people in the United States and an additional 6 million people worldwide, the presence of a non-MRI-conditional pacemaker or implantable cardioverter defibrillator (ICD) is considered a contraindication to magnetic resonance imaging. This creates a dilemma for at least half of these patients, who are predicted to require an MRI scan during their lifetime after a cardiac device has been implanted. Safety concerns for patients with an implanted cardiac device undergoing MRI are related to the potential for magnetic field-induced cardiac lead heating resulting in myocardial thermal injury, and a detrimental change in pacing properties. As a result, patients with an implanted device have long been denied access to MRI, although it may have been the most appropriate diagnostic imaging modality for their clinical care. Despite the development of MRI-conditional cardiac devices, a strategy for mitigating risks for patients with non MRI-conditional devices and leads will remain an enduring problem for the foreseeable future due to an ever increasing demand for MRI and the large number of previously and currently implanted non-MRI-conditional devices.

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MRI Can Better Diagnose Fetal Brain Abnormalities in-Utero

MedicalResearch.com Interview with:
Prof Paul D Griffiths, FRCR and

Cara Mooney, Study Manager: MERIDIAN
Clinical Trials Research Unit
The University of Sheffield 

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Around three in every 1000 pregnancies is complicated by a fetal abnormality. In the UK Ultrasonography (USS) has, for many years, been the mainstay of antenatal screening and detailed anomaly scanning to detect such abnormalities.  However previous studies have suggested that in utero Magnetic Resonance (iuMR) imaging may be a useful adjunct to USS for detecting these brain abnormalities in the developing fetus.

This study was designed to test the diagnostic accuracy and clinical impact of introducing fetal MR in to the diagnostic pathway.

Our results show that iuMR has an overall diagnostic accuracy of 93% compared to ultrasound at 68%, this is an increase in diagnostic accuracy of 25%. When divided into gestational age group the improvement in diagnostic accuracy ranged from 23% in the 18-23 week group, and 29% in the 24 week and over group.

IuMR provided additional diagnostic information in 49% of cases, changed prognostic information in at least 20% and the contribution to clinical management was felt to be at least ‘significant’ in 35% of cases. IuMR also had high patient acceptability with at least 95% of women stating that they would have an iuMR if a future pregnancy were complicated by a fetal brain abnormality.

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Cerebral Perfusion Is Perturbed by Preterm Birth and Brain Injury

MedicalResearch.com Interview with:
Eman S. Mahdi, MD, MBChB
Pediatric Radiology Fellow

Catherine Limperopoulos, PhD Director, Developing Brain Research Laboratory Co-Director of Research, Division of Neonatology Diagnostic Imaging and Radiology Children’s National Health System Washington, DC

Dr. Catherine Limperopoulos

Catherine Limperopoulos, PhD
Director, Developing Brain Research Laboratory
Co-Director of Research, Division of Neonatology
Diagnostic Imaging and Radiology
Children’s National Health System
Washington, DC

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Premature birth is a major public health concern in the United States affecting 1 in 10 infants each year. Prematurity-related brain injury is very common and associated with a high prevalence of brain injury and accompanying lifelong neurodevelopmental morbidities.

Early disturbances in systemic and cerebral hemodynamics are thought to mediate prematurity-related brain injury. The extent to which cerebral blood flow (CBF) is disturbed in preterm birth is poorly understood, in large part because of the lack of monitoring techniques that can directly and non-invasively measure cerebral blood flow.

We report for the first time early disturbances in global and regional cerebral blood flow in preterm infants following brain injury on conventional magnetic resonance imaging (MRI) over the third trimester of ex-uterine life using arterial spin labelling images. In terms of regional differences, we saw a marked decrease in blood flow to the thalamus and the pons, regions known to be metabolically active during this time.

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Virtual Reality Systems Can Generate Immersive 3D Images of Fetuses

Close-up of fetus at 26 weeks RSNA16

Close-up of fetus at 26 weeks

MedicalResearch.com Interview with:
Dr. Heron Werner Junior
Clínica de Diagnóstico por Imagem – CDPI
Rio de Janeiro – Brazil

MedicalResearch.com: What is the background for this study?

Response: A growing number of technological advancements in obtaining and viewing images through noninvasive techniques have brought major breakthroughs in fetal medicine.

In general, two main technologies are used to obtain images within the uterus during pregnancy i.e. ultrasound (US) and magnetic resonance imaging (MRI).

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Brain Scans Can Predict Specific Spontaneous Emotions

MedicalResearch.com Interview with:

Kevin S. LaBar, Ph.D. Professor and Head, Cognition & Cognitive Neuroscience Program Co-Director of Undergraduate Studies in Neuroscience Center for Cognitive Neuroscience Duke University Durham, NC

Dr. Kevin LaBar

Kevin S. LaBar, Ph.D.
Professor and Head, Cognition & Cognitive Neuroscience Program
Co-Director of Undergraduate Studies in Neuroscience
Center for Cognitive Neuroscience
Duke University
Durham, NC

MedicalResearch.com: What is the background for this study? What are the main findings?

Response: Emotion research is limited by a lack of objective markers of emotional states. Most human research relies on self-report, but individuals may not have good insight into their own emotions. We have developed a new way to identify emotional states using brain imaging and machine learning tools. First, we induced emotional states using film and music clips while individuals were in an MRI scanner. We trained a computer algorithm to identify the brain areas that distinguished 7 emotions from each other (fear, anger, surprise, sadness, amusement, contentment, and a neutral state). This procedure created a brain map for each of the 7 emotions. Then, a new group of participants self-reported their emotional state every 30 seconds in an MRI scanner while no stimuli were presented. We could predict which emotion was spontaneously reported by the subjects by comparing their brain scans to each of the 7 emotion maps. Finally, in a large group of 499 subjects, we found that the presence of the fear map during rest predicted state and trait anxiety while the presence of the sadness map predicted state and trait depression.

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