Use Of Brain Imaging Research Articles

Neuroimaging Methods for Nursing Science.

Since the inception of magnetic resonance imaging, thousands of studies have appeared in the literature reporting on multiple imaging techniques. However, there is a paucity of neuroimaging research programs developed by nurse scientists. The purpose of this article is to introduce the nurse scientist to complex neuroimaging methods with the ultimate goal of creating impetus for future use of brain imaging in nursing research. This article reviews common neuroimaging methods, presents vocabulary frequently used in neuroimaging work, provides information on access to resources in neuroimaging education, and discusses considerations for use of neuroimaging in research. Ten imaging modalities are reviewed, including structural and functional magnetic resonance imaging, computed tomography, positron emission tomography, and encephalography. Choosing an imaging modality for research depends on the nature of the research question, needs of the patient population of interest, and resources available to the novice and seasoned nurse scientist. Neuroimaging has the potential to innovate the study of symptom science and encourage interdisciplinary collaboration in research.

Brain imaging in rem sleep behavior disorder

REM sleep behavior disorder (RBD) is a parasomnia typically occurring during REM sleep, characterized by complex and often violent behaviors. More than 80% of idiopathic RBD (iRBD) eventually develop a neurodegenerative disease, mostly a synucleinopathy. Brain imaging techniques provide in vivo demonstration of structural and functional abnormalities in such patients. Several studies have shown that iRBD patients often exhibit brain imaging finding suggestive of incipient neurodegenerative process, even without clinical sign of parkinsonism or dementia. On the one hand, these findings are allowing a better understanding of the pathophysiological basis underlying RBD. Moreover, growing evidence are suggesting that the use of brain imaging may allow the identification of iRBD patients at high risk of short-term conversion in a definite neurodegenerative disorder. Neuroprotective therapies for synucleinopathies are not available yet, but the identification of patients to be included in neuroprotective clinical trials is a main research priority nowadays.

Findings of Brain Imaging among Tuberculous Meningitis Patients: A Study of 30 Cases in Bangladesh

Background: Tuberculous meningitis is a serious health hazard and difficult to diagnose.
 Objectives: The purpose of the present study was to observe the role of CT/MRI in TBM diagnosis.
 Methodology: This was a retrospective study done from January 2010 to December 2011 for a period of two (02) years. Patients of TBM were reviewed in a medical college hospital of Bangladesh.
 Results: A total number of reviewed 30 TBM patients; among them 11 cases were confirmed TBM patients and 19 were probable patients. Brain imaging (CT/MRI) was performed in 15 cases. The use of brain imaging allowed the Brain lesions in 93.3% patients.
 Conclusion: Brain imaging was done in 15 out of 30 TBM patients and most of them (14/15) had got various forms of radiological abnormalities that aid in diagnosis and monitor of disease progression in TBM.
 Bangladesh Journal of Infectious Diseases, June 2019; 6(1):8-11

Epidemiological analyses to inform stroke clinical practice guidelines development.

Stroke is one of the leading causes of mortality and the leading cause of functional impairment and cognitive deficits worldwide. It is important that clinical practice guidelines development is based on robust statistical and epidemiological data and their analysis throughout the whole process of guidelines development and implementation. The aim of this short communication is to analyse epidemiology of prevalence and incidence of ischaemic stroke, its main causes, brain imaging using MRI, recanalization therapies, secondary prevention with antiplatelet and anticoagulants, mortality data and to inform development of stroke clinical practice guidelines in the Czech Republic. The main analysed diagnosis was I63 (cerebral infarction) and secondary diagnoses were: I48 (atrial fibrillation and flutter), I35.9 (nonspecified aortic valve disease), Q21.1 (atrial septal defect) or I33.0 (acute and subacute endocarditis). We have also analysed use of brain imaging with MRI, recanalization treatment using intravenous thrombolysis and mechanical thrombectomy, stroke secondary prevention with antiplatelet drugs and anticoagulation as well as hospital admissions and mortality. In total, 159 344 patients were diagnosed with an ischaemic stroke from 2015 to 2017. Average prevalence of ischaemic stroke in the Czech Republic is 54.9 patients per 100 000. 22.2% of patients with stroke received intravenous thrombolysis or mechanical thrombectomy in 2017.

Reconstruction of Photoacoustic Tomography Inside a Scattering Layer Using a Matrix Filtering Method

Photoacoustic (PA) tomography (PAT) has potential for use in brain imaging due to its rich optical contrast, high acoustic resolution in deep tissue, and good biosafety. However, the skull often poses challenges for transcranial brain imaging. The skull can cause severe distortion and attenuation of the phase and amplitude of PA waves, which leads to poor resolution, low contrast, and strong noise in the images. In this study, we propose an image reconstruction method to recover the PA image insider a skull-like scattering layer. This method reduces the scattering artifacts by combining a correlation matrix filter and a time reversal operator. Both numerical simulations and PA imaging experiments demonstrate that the proposed approach effectively improves the image quality with less speckle noise and better signal-to-noise ratio. The proposed method may improve the quality of PAT in a complex acoustic scattering environment, such as transcranial brain imaging.

Imaging, Technology, and Parkinson’s Disease

Nora Vanegas Dr Vanegas is a neurologist who specializes in deep brain stimulation (DBS) and the treatment of movement disorders including Parkinson’s disease, dystonia, and essential tremor. Dr Vanegas completed her combined clinical-research fellowship at the National Institutes of Health (NIH) under the mentorship of Dr Mark Hallett. Her training had a special focus on neuroimaging and neuromodulation. She transitioned to being an Assistant Professor of Neurology in Columbia University in 2016, and is now an established local expert in neuromodulation for movement disorders. Dr Vanegas is also a clinical investigator whose research involves clinical and translational areas of movement disorders, specifically the use of brain imaging for the understanding of DBS and the physiology of the basal ganglia. As part of multi-disciplinary research activities, Dr Vanegas has developed strong collaborations for various projects with the departments of Biomedical Engineering, Speech Pathology, Neurosurgery and Psychiatry at Columbia University. Such collaborative research activities include the use of instrumented assessments to measure gait characteristics in patients with Parkinson’s disease, the benefits of various airway protection interventions in patients with Parkinson’s disease who aspirate with food and the activity of brain neurons during decision making tasks.

Chapter 20 - Vascular cognitive impairment: A preventable component of dementia

For many decades during the 20th century, the common belief was that the slow strangulation of the brains' blood supply from hardening of the brain arteries led to chronic brain ischemia and neuronal death. Not surprisingly, to counter this, vasodilators rapidly became one of the most commonly used and profitable medications worldwide; however, no clinical benefits were ever proven. In the 1970s and early 1980s cerebral blood flow studies strongly disproved the idea of brain failure due to chronic ischemia. It was also shown that infarcts and not chronic ischemia caused dementia, leading to the concept of multiinfarct dementia. In addition to infarcts, it was then realized that other vascular lesions can also cause cognitive decline. Gradually, as "atherosclerotic dementia" lost ground, Alzheimer's disease (AD) that once had been considered a presenile dementia and rare, became almost synonymous with dementia. Subsequent memory-based definitions and evaluations of dementia led to a bias in favor of diagnosing AD, overshadowing vascular contributions. The widespread use of brain imaging in the 1980s and 1990s contributed to the resurgence of evidence of cerebrovascular diseases. Moreover, it was shown that most cognitive impairment of the elderly results from mixed pathologies, emphasizing the need for a change in the traditional categorical diagnosis of dementia, e.g., AD vs vascular dementia. The alternative diagnostic method was named the vascular cognitive impairment approach, meaning identifying any impairment caused by or associated with vascular factors. The importance of this approach is that vascular lesions are currently the most important treatable and preventable components of dementia, even before any symptoms manifest, i.e., at the brain at risk stage. This chapter provides a summary of the vascular cognitive impairment approach to diagnosis, treatment, and prevention of cognitive decline.

Profiles of women in science: Nora Volkow, Director of the National Institute of Drug Abuse, Bethesda MD.

Profiles of women in science: Nora Volkow, Director of the National Institute of Drug Abuse, Bethesda MD.

Age-specific association between blood pressure and vascular and non-vascular chronic diseases in 0·5 million adults in China: a prospective cohort study.

SummaryBackgroundThe age-specific association between blood pressure and vascular disease has been studied mostly in high-income countries, and before the widespread use of brain imaging for diagnosis of the main stroke types (ischaemic stroke and intracerebral haemorrhage). We aimed to investigate this relationship among adults in China.Methods512 891 adults (59% women) aged 30–79 years were recruited into a prospective study from ten areas of China between June 25, 2004, and July 15, 2008. Participants attended assessment centres where they were interviewed about demographic and lifestyle characteristics, and their blood pressure, height, and weight were measured. Incident disease was identified through linkage to local mortality records, chronic disease registries, and claims to the national health insurance system. We used Cox regression analysis to produce adjusted hazard ratios (HRs) relating systolic blood pressure to disease incidence. HRs were corrected for regression dilution to estimate associations with long-term average (usual) systolic blood pressure.FindingsDuring a median follow-up of 9 years (IQR 8–10), there were 88 105 incident vascular and non-vascular chronic disease events (about 90% of strokes events were diagnosed using brain imaging). At ages 40–79 years (mean age at event 64 years [SD 9]), usual systolic blood pressure was continuously and positively associated with incident major vascular disease throughout the range 120–180 mm Hg: each 10 mm Hg higher usual systolic blood pressure was associated with an approximately 30% higher risk of ischaemic heart disease (HR 1·31 [95% CI 1·28–1·34]) and ischaemic stroke (1·30 [1·29–1·31]), but the association with intracerebral haemorrhage was about twice as steep (1·68 [1·65–1·71]). HRs for vascular disease were twice as steep at ages 40–49 years than at ages 70–79 years. Usual systolic blood pressure was also positively associated with incident chronic kidney disease (1·40 [1·35–1·44]) and diabetes (1·14 [1·12–1·15]). About half of all vascular deaths in China were attributable to elevated blood pressure (ie, systolic blood pressure >120 mm Hg), accounting for approximately 1 million deaths (<80 years of age) annually.InterpretationAmong adults in China, systolic blood pressure was continuously related to major vascular disease with no evidence of a threshold down to 120 mm Hg. Unlike previous studies in high-income countries, blood pressure was more strongly associated with intracerebral haemorrhage than with ischaemic stroke. Even small reductions in mean blood pressure at a population level could be expected to have a major impact on vascular morbidity and mortality.FundingUK Wellcome Trust, UK Medical Research Council, British Heart Foundation, Cancer Research UK, Kadoorie Charitable Foundation, Chinese Ministry of Science and Technology, and the National Science Foundation of China.

Quality of care and variability in lung cancer management across Belgian hospitals: a population-based study using routinely available data.

To evaluate the quality of care for all patients diagnosed with lung cancer in Belgium based on a set of evidence-based quality indicators and to study the variability of care between hospitals. A retrospective study based on linked data from the cancer registry, insurance claims and vital status for all patients diagnosed with lung cancer between 2010 and 2011. Evidence-based quality indicators were identified from a systematic literature search. A specific algorithm to attribute patients to a centre was developed, and funnel plots were used to assess variability of care between centres. None. The proportion of patients who received appropriate care as defined by the indicator. Secondary outcome included the variability of care between centres. Twenty indicators were measured for a total of 12 839 patients. Good results were achieved for 60-day post-surgical mortality (3.9%), histopathological confirmation of diagnosis (93%) and for the use of PET-CT before treatment with curative intent (94%). Areas to be improved include the reporting of staging information to the Belgian Cancer Registry (80%), the use of brain imaging for clinical stage III patients eligible for curative treatment (79%), and the time between diagnosis and start of first active treatment (median 20 days). High variability between centres was observed for several indicators. Twenty-three indicators were found relevant but could not be measured. This study highlights the feasibility to develop a multidisciplinary set of quality indicators using population-based data. The main advantage of this approach is that not additional registration is required, but the non-measurability of many relevant indicators is a hamper. It allows however to easily point to areas of large variability in care.

Validation of an algorithm that determines stroke diagnostic code accuracy in a Japanese hospital-based cancer registry using electronic medical records

BackgroundThis study aimed to validate an algorithm that determines stroke diagnostic code accuracy, in a hospital-based cancer registry, using electronic medical records (EMRs) in Japan.MethodsThe subjects were 27,932 patients enrolled in the hospital-based cancer registry of Osaka University Hospital, between January 1, 2007 and December 31, 2015. The ICD-10 (international classification of diseases, 10th revision) diagnostic codes for stroke were extracted from the EMR database. Specifically, subarachnoid hemorrhage (I60); intracerebral hemorrhage (I61); cerebral infarction (I63); and other transient cerebral ischemic attacks and related syndromes and transient cerebral ischemic attack (unspecified) (G458 and G459), respectively. Diagnostic codes, both “definite” and “suspected,” and brain imaging information were extracted from the database. We set the algorithm with the combination of the diagnostic code and/or the brain imaging information, and manually reviewed the presence or absence of the acute cerebrovascular disease with medical charts.ResultsA total of 2654 diagnostic codes, 1991 “definite” and 663 “suspected,” were identified. After excluding duplicates, the numbers of “definite” and “suspected” diagnostic codes were 912 and 228, respectively. The proportion of the presence of the disease in the “definite” diagnostic code was 22%; this raised 51% with the combination of the diagnostic code and the use of brain imaging information. When adding the interval of when brain imaging was performed (within 30 days and within 1 day) to the diagnostic code, the proportion increased to 84% and 90%, respectively. In the algorithm of “definite” diagnostic code, history of stroke was the most common in the diagnostic code, but in the algorithm of “definite” diagnostic code and the use of brain imaging within 1 day, stroke mimics was the most frequent.ConclusionsCombining the diagnostic code and clinical examination improved the proportion of the presence of disease in the diagnostic code and achieved appropriate accuracy for research. Clinical research using EMRs require outcome validation prior to conducting a study.

A national survey of the management of patients with incidental meningioma in the United Kingdom

Background: Incidental meningiomas are increasingly being diagnosed due to widespread use of brain imaging. Treatment options include surveillance, surgery and stereotactic radiosurgery, but the natural history of these tumours is not fully understood and there are no accepted management guidelines to aid clinical decision-making. The aim of this study was to assess current practice in the United Kingdom and identify areas of variation for further study.Methods: A questionnaire was distributed to all members of the Society of British Neurosurgeons (SBNS). The main components of the survey included the assessment of which factors and tumour characteristics are considered in the management and follow-up of incidental meningiomas. Two case scenarios were also presented.Results: The response rate was 12.5% (44 completed surveys) with 74% (25/34) of neurosurgical centres represented. Absence of calcification was only considered by 36% (16/44) of neurosurgeons. Most neurosurgeons opt for surveillance at initial presentation, and the length of follow-up was 5 years (14/33) and 10 years (11/33). The case scenarios highlighted that tumour growth at follow-up resulted in a preference to change from surveillance to treatment with surgery or SRS. SRS was preferred in skull-base (23/36) and medial sphenoid wing (16/39) tumours.Conclusions: This survey has demonstrated that certain aspects of incidental meningioma management show variation and remain controversial. Further research through prospective cohort studies is required to provide evidence to support guidelines for the management of incidental meningiomas.

Deception detection based on neuroimaging: Better than the polygraph?

Abstract Polygraph tests have been used to detect deception for almost a century. Yet for almost as long, the validity of these tests has been criticized. Over the last decade, the use of brain imaging – most notably fMRI - for the detection of deception has attracted increased attention. The expectation is that fMRI can overcome – at least some of - the shortcomings of the polygraph. In this review, we discuss whether this expectation is warranted. Based on our review of the empirical evidence, we argue that fMRI deception research has boosted the theory development of deception. But for practical purposes, fMRI research has thus far done surprisingly little to solve or circumvent the problems than have been associated with deception research for ages.

Adverse Events Associated with Antipsychotic Use in Hospitalized Older Adults After Cardiac Surgery.

To evaluate in-hospital adverse events associated with typical and atypical antipsychotic medications (APMs) after cardiac surgery. Retrospective cohort study. Nationwide inpatient database, 2003 to 14. Individuals (mean age 70) newly treated with oral atypical (n = 2,580) or typical (n = 1,126 APMs) after coronary artery bypass grafting or valve surgery (N = 3,706). In-hospital mortality, arrhythmia, pneumonia, use of brain imaging (surrogate for oversedation and neurological events), and length of stay after drug initiation RESULTS: In the propensity score-matched cohort, median treatment duration was 3 days (interquartile range (IQR) 1-6 days) for atypical APMs and 2 days (IQR 1-3 days) for typical APMs. There were no large differences in in-hospital mortality (atypical 5.4%, typical 5.3%; risk difference (RD) = 0.1%, 95% confidence interval (CI) = -2.1 to 2.3%), arrhythmia (2.0% vs 2.2%; RD = 0.0%; 95% CI = -1.4 to 1.4%), pneumonia (16.1% vs 14.5%; RD = 1.6%, 95% CI = -1.9 to 5.0%), and length of stay (9.9 days vs 9.3 days; mean difference = 0.5 days, 95% CI = -1.2 to 2.2). Use of brain imaging was more common after initiating atypical APMs (17.3%) than after typical APMs (12.4%; RD = 4.9%, 95% CI = 1.4-8.4). In hospitalized individuals who underwent cardiac surgery, short-term use of typical APMs was associated with risks of adverse events similar to those with atypical APMs. Moreover, greater use of brain imaging associated with atypical APMs suggests that these drugs may cause oversedation or adverse neurological events. Because of the low event rates, the analysis could not exclude modest differences in adverse events between atypical and typical APMs.

Biomarkers for Musculoskeletal Pain Conditions: Use of Brain Imaging and Machine Learning.

Chronic musculoskeletal pain condition often shows poor correlations between tissue abnormalities and clinical pain. Therefore, classification of pain conditions like chronic low back pain, osteoarthritis, and fibromyalgia depends mostly on self report and less on objective findings like X-ray or magnetic resonance imaging (MRI) changes. However, recent advances in structural and functional brain imaging have identified brain abnormalities in chronic pain conditions that can be used for illness classification. Because the analysis of complex and multivariate brain imaging data is challenging, machine learning techniques have been increasingly utilized for this purpose. The goal of machine learning is to train specific classifiers to best identify variables of interest on brain MRIs (i.e., biomarkers). This report describes classification techniques capable of separating MRI-based brain biomarkers of chronic pain patients from healthy controls with high accuracy (70-92%) using machine learning, as well as critical scientific, practical, and ethical considerations related to their potential clinical application. Although self-report remains the gold standard for pain assessment, machine learning may aid in the classification of chronic pain disorders like chronic back pain and fibromyalgia as well as provide mechanistic information regarding their neural correlates.

Fahr Syndrome - an Important Piece of a Puzzle in the Differential Diagnosis of Many Diseases.

SummaryFahr syndrome is a rare neurodegenerative disorder characterized by symmetrical, bilateral calcifications in the basal ganglia, nucleus gyrus and cerebral cortex. The continuous advancement as well as widespread use of brain imaging have contributed to the increasing detection rates of such changes. Nevertheless, their etiology is understood only partially and the methods of causative treatment are limited. Due to various symptoms, Fahr syndrome may resemble diseases from the field of neurology, psychiatry, cardiology and even urology. This article provides an up-to-date review of the literature concerning Fahr syndrome in terms of clinical practice.

Successful classification of cocaine dependence using brain imaging: a generalizable machine learning approach.

BackgroundNeuroimaging studies have yielded significant advances in the understanding of neural processes relevant to the development and persistence of addiction. However, these advances have not explored extensively for diagnostic accuracy in human subjects. The aim of this study was to develop a statistical approach, using a machine learning framework, to correctly classify brain images of cocaine-dependent participants and healthy controls. In this study, a framework suitable for educing potential brain regions that differed between the two groups was developed and implemented. Single Photon Emission Computerized Tomography (SPECT) images obtained during rest or a saline infusion in three cohorts of 2–4 week abstinent cocaine-dependent participants (n = 93) and healthy controls (n = 69) were used to develop a classification model. An information theoretic-based feature selection algorithm was first conducted to reduce the number of voxels. A density-based clustering algorithm was then used to form spatially connected voxel clouds in three-dimensional space. A statistical classifier, Support Vectors Machine (SVM), was then used for participant classification. Statistically insignificant voxels of spatially connected brain regions were removed iteratively and classification accuracy was reported through the iterations.ResultsThe voxel-based analysis identified 1,500 spatially connected voxels in 30 distinct clusters after a grid search in SVM parameters. Participants were successfully classified with 0.88 and 0.89 F-measure accuracies in 10-fold cross validation (10xCV) and leave-one-out (LOO) approaches, respectively. Sensitivity and specificity were 0.90 and 0.89 for LOO; 0.83 and 0.83 for 10xCV. Many of the 30 selected clusters are highly relevant to the addictive process, including regions relevant to cognitive control, default mode network related self-referential thought, behavioral inhibition, and contextual memories. Relative hyperactivity and hypoactivity of regional cerebral blood flow in brain regions in cocaine-dependent participants are presented with corresponding level of significance.ConclusionsThe SVM-based approach successfully classified cocaine-dependent and healthy control participants using voxels selected with information theoretic-based and statistical methods from participants’ SPECT data. The regions found in this study align with brain regions reported in the literature. These findings support the future use of brain imaging and SVM-based classifier in the diagnosis of substance use disorders and furthering an understanding of their underlying pathology.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1218-z) contains supplementary material, which is available to authorized users.

Carotid atherosclerosis, silent ischemic brain damage and brain atrophy: A systematic review and meta-analysis

BackgroundThe widespread use of brain imaging has led to increased recognition of subclinical brain abnormalities, including white matter hyperintensities (WMH) and silent brain infarctions (SBI), which have a vascular origin, and have been associated to a high risk of stroke, disability and dementia. Carotid atherosclerosis (CA) may be causative in the development of WMH, SBI and eventually brain atrophy. Aim of the present systematic review and meta-analysis was to assess the existing evidence linking CA to WMH, SBI and brain atrophy. MethodsThe relation between CA and WMH, SBI and brain atrophy was investigated through the systematic search of online databases up to September 2015 and manual searching of references and related citations. Pooled estimates were calculated by random-effects model, using restricted maximum likelihood method with inverse variance weighting method. ResultsOf the 3536 records identified, fifteen were included in the systematic review and 9 were found to be eligible for the meta-analysis. CA was significantly associated with the presence of WMH (Odds Ratio, OR 1.42, confidence interval, CI 1.22–1.66, p<0.0001) and of SBI (OR 1.89, CI 1.46–2.45, p<0.0001). No meta-analysis could be performed for the relation between CA and brain atrophy due to the lack of suitable studies. ConclusionsCA was found to be associated to WMH and SBI. While no causative association can be inferred from the available data, the presence of carotid plaque may be considered a significant risk factor for subclinical cerebral damage.

The Current Role of Radiotherapy in the Treatment of Small Cell Lung Cancer

Radiotherapy has been shown to play a key role in the management of small cell lung cancer. There are well-established data in the literature for the use of concurrent chemoradiotherapy for stage I–III disease, although key questions remain over the timing of radiation, the optimal dose/fractionation and particularly once versus twice daily treatment, the use of elective nodal irradiation and drug combinations. Data for the use of thoracic radiation in stage IV disease, after chemotherapy, have recently become available and are leading to a change in practice. Prophylactic cranial irradiation has been shown to be of use in both stage I–III and stage IV disease, although uncertainties surround its use in the elderly population and the use of brain imaging before treatment. This overview will address the current available evidence and focus on areas for future research.

88P Use of brain imaging in the management of patients with lymph node negative multifocal lung cancer

88P Use of brain imaging in the management of patients with lymph node negative multifocal lung cancer