scholarly journals Stereotaxic Magnetic Resonance Imaging Brain Atlases for Infants from 3 to 12 Months

2015 ◽  
Vol 37 (6) ◽  
pp. 515-532 ◽  
Author(s):  
Paul T. Fillmore ◽  
John E. Richards ◽  
Michelle C. Phillips-Meek ◽  
Alison Cryer ◽  
Michael Stevens
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Brain Regions ◽  
Brain Atlas ◽  
First Year ◽  
Resonance Imaging ◽  
Data Set ◽  
Manual Delineation ◽  
Age Appropriate ◽  
The Individual

Background: Accurate labeling of brain structures within an individual or group is a key issue in neuroimaging. Methods for labeling infant brains have depended on the labels done on adult brains or average magnetic resonance imaging (MRI) templates based on adult brains. However, the features of adult brains differ in several ways from infant brains, so the creation of a labeled stereotaxic atlas based on infants would be helpful. The current work builds on the recent creation of age-appropriate average MRI templates during the first year (3, 4.5, 6, 7.5, 9, and 12 months) by creating anatomical label sets for each template. Methods: We created stereotaxic atlases for the age-specific average MRI templates. Manual delineation of cortical and subcortical areas was done on the average templates based on infants during the first year. We also applied a procedure for automatic computation of macroanatomical atlases for individual infant participants using two manually segmented adult atlases (Hammers, LONI Probabilistic Brain Atlas-LPBA40). To evaluate our methods, we did manual delineation of several cortical areas on selected individuals from each age. Linear and nonlinear registration of the individual and average template was used to transform the average atlas into the individual participant's space, and the average-transformed atlas was compared to the individual manually delineated brain areas. We also applied these methods to an external data set - not used in the atlas creation - to test generalizability of the atlases. Results: Age-appropriate manual atlases were the best fit to the individual manually delineated regions, with more error seen at greater age discrepancy. There was a close fit between the manually delineated and the automatically labeled regions for individual participants and for the age-appropriate template-based atlas transformed into participant space. There was close correspondence between automatic labeling of individual brain regions and those from the age-appropriate template. These relationships held even when tested on an external set of images. Conclusion: We have created age-appropriate labeled templates for use in the study of infant development at 6 ages (3, 4.5, 6, 7.5, 9, and 12 months). Comparison with manual methods was quite good. We developed three stereotaxic atlases (one manual, two automatic) for each infant age, which should allow more fine-grained analysis of brain structure for these populations than was previously possible with existing tools. The template-based atlases constructed in the current study are available online (http://jerlab.psych.sc.edu/NeurodevelopmentalMRIDatabase).

scholarly journals Use of Magnetic Resonance Imaging to Predict Outcome after Stroke: A Review of Experimental and Clinical Evidence

2010 ◽  
Vol 30 (4) ◽  
pp. 703-717 ◽  
Author(s):  
Tracy D Farr ◽  
Susanne Wegener
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Complete Recovery ◽  
Research Translation ◽  
Resonance Imaging ◽  
Preclinical Research ◽  
Stroke Research ◽  
Future Potential ◽  
Magnetic Resonance Imaging Mri ◽  
The Individual

Despite promising results in preclinical stroke research, translation of experimental data into clinical therapy has been difficult. One reason is the heterogeneity of the disease with outcomes ranging from complete recovery to continued decline. A successful treatment in one situation may be ineffective, or even harmful, in another. To overcome this, treatment must be tailored according to the individual based on identification of the risk of damage and estimation of potential recovery. Neuroimaging, particularly magnetic resonance imaging (MRI), could be the tool for a rapid comprehensive assessment in acute stroke with the potential to guide treatment decisions for a better clinical outcome. This review describes current MRI techniques used to characterize stroke in a preclinical research setting, as well as in the clinic. Furthermore, we will discuss current developments and the future potential of neuroimaging for stroke outcome prediction.

Integrating Magnetic Resonance Imaging Postprocessing Results into Neuronavigation for Electrode Implantation and Resection of Subtle Focal Cortical Dysplasia in Previously Cryptogenic Epilepsy

Neurosurgery ◽  
2010 ◽  
Vol 66 (1) ◽  
pp. 187-195 ◽  
Author(s):  
Jörg Wellmer ◽  
Yaroslav Parpaley ◽  
Marec von Lehe ◽  
Hans-Jürgen Huppertz
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
High Resolution ◽  
Morphometric Analysis ◽  
Region Of Interest ◽  
Normal Database ◽  
Resonance Imaging ◽  
Electrode Implantation ◽  
Neuronavigation System ◽  
The Individual

Abstract OBJECTIVE Focal cortical dysplasias (FCDs) are highly epileptogenic lesions. Surgical removal is frequently the best treatment option for pharmacoresistant epilepsy. However, subtle FCDs may remain undetected even after high-resolution magnetic resonance imaging (MRI). Morphometric MRI analysis, which compares the individual brain with a normal database, can facilitate the detection of FCDs. We describe how the results of normal database–based MRI postprocessing can be used to guide stereotactic electrode implantation and subsequent resection of lesions that are suspected to be FCDs. METHODS A presurgical evaluation was conducted on a 19-year-old woman with pharmacoresistant hypermotor seizures. Conventional high-resolution MRI was classified as negative for epileptogenic lesions. However, morphometric analysis of the spatially normalized MRI revealed abnormal gyration and blurring of the gray-white matter junction, which was suggestive of a small and deeply seated FCD in the left frontal lobe. RESULTS The brain region highlighted by morphometric analysis was marked as a region of interest, transferred back to the original dimension of the individual MRI, and imported into a neuronavigation system. This allowed the region of interest–targeted stereotactic implantation of 2 depth electrodes, by which seizure onset was confirmed in the lesion. The electrodes also guided the final resection, which rendered the patient seizure-free. The lesion was histologically classified as FCD Palmini and Lüders IIB. CONCLUSION Transferring normal database–based MRI postprocessing results into a neuronavigation system is a new and worthwhile extension of multimodal neuronavigation. The combination of resulting regions of interest with functional and anatomic data may facilitate planning of electrode implantation for invasive electroencephalographic recordings and the final resection of small or deeply seated FCDs.

scholarly journals A Baboon Brain Atlas for Magnetic Resonance Imaging and Positron Emission Tomography Image Analysis

2022 ◽  
Vol 15 ◽  
Author(s):  
Artur Agaronyan ◽  
Raeyan Syed ◽  
Ryan Kim ◽  
Chao-Hsiung Hsu ◽  
Scott A. Love ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Positron Emission Tomography ◽  
Magnetic Resonance ◽  
Standardized Uptake Value ◽  
Emission Tomography ◽  
Brain Atlas ◽  
Resonance Imaging ◽  
Papio Anubis ◽  
Olive Baboon ◽  
Positron Emission

The olive baboon (Papio anubis) is phylogenetically proximal to humans. Investigation into the baboon brain has shed light on the function and organization of the human brain, as well as on the mechanistic insights of neurological disorders such as Alzheimer’s and Parkinson’s. Non-invasive brain imaging, including positron emission tomography (PET) and magnetic resonance imaging (MRI), are the primary outcome measures frequently used in baboon studies. PET functional imaging has long been used to study cerebral metabolic processes, though it lacks clear and reliable anatomical information. In contrast, MRI provides a clear definition of soft tissue with high resolution and contrast to distinguish brain pathology and anatomy, but lacks specific markers of neuroreceptors and/or neurometabolites. There is a need to create a brain atlas that combines the anatomical and functional/neurochemical data independently available from MRI and PET. For this purpose, a three-dimensional atlas of the olive baboon brain was developed to enable multimodal imaging analysis. The atlas was created on a population-representative template encompassing 89 baboon brains. The atlas defines 24 brain regions, including the thalamus, cerebral cortex, putamen, corpus callosum, and insula. The atlas was evaluated with four MRI images and 20 PET images employing the radiotracers for [11C]benzamide, [11C]metergoline, [18F]FAHA, and [11C]rolipram, with and without structural aids like [18F]flurodeoxyglycose images. The atlas-based analysis pipeline includes automated segmentation, registration, quantification of region volume, the volume of distribution, and standardized uptake value. Results showed that, in comparison to PET analysis utilizing the “gold standard” manual quantification by neuroscientists, the performance of the atlas-based analysis was at >80 and >70% agreement for MRI and PET, respectively. The atlas can serve as a foundation for further refinement, and incorporation into a high-throughput workflow of baboon PET and MRI data. The new atlas is freely available on the Figshare online repository (https://doi.org/10.6084/m9.figshare.16663339), and the template images are available from neuroImaging tools & resources collaboratory (NITRC) (https://www.nitrc.org/projects/haiko89/).

scholarly journals Applying 3DPCANet and Functional Magnetic Resonance Imaging to Aided Diagnosis of Alzheimer’s Disease

2021 ◽  
Author(s):  
Yu Wang ◽  
Hongfei Jia ◽  
Yifan Duan ◽  
Hongbing Xiao
Keyword(s):  
Magnetic Resonance Imaging ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Regions ◽  
Support Vector ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Public Data

Abstract Alzheimer's disease (AD) is a progressive neurodegenerative disease, which changes the structure of brain regions by some hidden causes. In this paper for assisting doctors to make correct judgments, an improved 3DPCANet method is proposed to classify AD by combining the mean (mALFF) of the whole brain. The main idea includes that firstly, the functional magnetic resonance imaging (fMRI) data is pre-processed, and mALFF is calculated to get the corresponding matrix. Then the features of mALFF images are extracted via the improved 3DPCANet network. Finally, AD patients with different stages are classified using support vector machine (SVM). Experiments results based on public data from the Alzheimer’s disease neuroimaging initiative (ADNI) show that the proposed approach has better performance compared with state-of-the-art methods. The accuracies of AD vs. significant memory concern (SMC), SMC vs. late mild cognitive impairment (LMCI), and normal control (NC) vs. SMC reach respectively 92.42%, 91.80%, and 89.50%, which testifies the feasibility and effectiveness of the proposed method.

scholarly journals Resting-State Functional Magnetic Resonance Imaging Connectivity Between Semantic and Phonological Regions of Interest May Inform Language Targets in Aphasia

2020 ◽  
Vol 63 (9) ◽  
pp. 3051-3067
Author(s):  
Amy E. Ramage ◽  
Semra Aytur ◽  
Kirrie J. Ballard
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Resting State ◽  
Brain Regions ◽  
Regions Of Interest ◽  
Healthy Controls ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Language Performance

Purpose Brain imaging has provided puzzle pieces in the understanding of language. In neurologically healthy populations, the structure of certain brain regions is associated with particular language functions (e.g., semantics, phonology). In studies on focal brain damage, certain brain regions or connections are considered sufficient or necessary for a given language function. However, few of these account for the effects of lesioned tissue on the “functional” dynamics of the brain for language processing. Here, functional connectivity (FC) among semantic–phonological regions of interest (ROIs) is assessed to fill a gap in our understanding about the neural substrates of impaired language and whether connectivity strength can predict language performance on a clinical tool in individuals with aphasia. Method Clinical assessment of language, using the Western Aphasia Battery–Revised, and resting-state functional magnetic resonance imaging data were obtained for 30 individuals with chronic aphasia secondary to left-hemisphere stroke and 18 age-matched healthy controls. FC between bilateral ROIs was contrasted by group and used to predict Western Aphasia Battery–Revised scores. Results Network coherence was observed in healthy controls and participants with stroke. The left–right premotor cortex connection was stronger in healthy controls, as reported by New et al. (2015) in the same data set. FC of (a) connections between temporal regions, in the left hemisphere and bilaterally, predicted lexical–semantic processing for auditory comprehension and (b) ipsilateral connections between temporal and frontal regions in both hemispheres predicted access to semantic–phonological representations and processing for verbal production. Conclusions Network connectivity of brain regions associated with semantic–phonological processing is predictive of language performance in poststroke aphasia. The most predictive connections involved right-hemisphere ROIs—particularly those for which structural adaptions are known to associate with recovered word retrieval performance. Predictions may be made, based on these findings, about which connections have potential as targets for neuroplastic functional changes with intervention in aphasia. Supplemental Material https://doi.org/10.23641/asha.12735785

scholarly journals How Does Our Brain Process Sugars and Non-Nutritive Sweeteners Differently: A Systematic Review on Functional Magnetic Resonance Imaging Studies

Nutrients ◽  
2020 ◽  
Vol 12 (10) ◽  
pp. 3010
Author(s):  
Andy Wai Kan Yeung ◽  
Natalie Sui Miu Wong
Keyword(s):  
Magnetic Resonance Imaging ◽  
Systematic Review ◽  
Magnetic Resonance ◽  
Functional Magnetic Resonance Imaging ◽  
Brain Regions ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Imaging Studies ◽  
Brain Responses ◽  
Fasting Duration

This systematic review aimed to reveal the differential brain processing of sugars and sweeteners in humans. Functional magnetic resonance imaging studies published up to 2019 were retrieved from two databases and were included into the review if they evaluated the effects of both sugars and sweeteners on the subjects’ brain responses, during tasting and right after ingestion. Twenty studies fulfilled the inclusion criteria. The number of participants per study ranged from 5 to 42, with a total number of study participants at 396. Seven studies recruited both males and females, 7 were all-female and 6 were all-male. There was no consistent pattern showing that sugar or sweeteners elicited larger brain responses. Commonly involved brain regions were insula/operculum, cingulate and striatum, brainstem, hypothalamus and the ventral tegmental area. Future studies, therefore, should recruit a larger sample size, adopt a standardized fasting duration (preferably 12 h overnight, which is the most common practice and brain responses are larger in the state of hunger), and reported results with familywise-error rate (FWE)-corrected statistics. Every study should report the differential brain activation between sugar and non-nutritive sweetener conditions regardless of the complexity of their experiment design. These measures would enable a meta-analysis, pooling data across studies in a meaningful manner.

scholarly journals Biomarkers and antithrombotic treatment in cervical artery dissection – Design of the TREAT-CAD randomised trial

2020 ◽  
Vol 5 (3) ◽  
pp. 309-319
Author(s):  
Christopher Traenka ◽  
Henrik Gensicke ◽  
Sabine Schaedelin ◽  
Andreas Luft ◽  
Marcel Arnold ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Vitamin K ◽  
Vitamin K Antagonists ◽  
Artery Dissection ◽  
Cervical Artery Dissection ◽  
Resonance Imaging ◽  
Antithrombotic Treatment ◽  
Data Set ◽  
Cervical Artery

Introduction The type of antithrombotic treatment in cervical artery dissection patients is still a matter of debate. Most physicians prefer anticoagulants over antiplatelet agents for stroke prevention. However, this approach is not evidence-based and antiplatelets might be as safe and as effective. The ‘Biomarkers and Antithrombotic Treatment in Cervical Artery Dissection’ (‘TREAT-CAD’) trial (clinicaltrials.gov: NCT02046460) compares Aspirin to oral anticoagulants (vitamin K antagonists) with regard to efficacy and safety by using both clinical and imaging surrogate outcome measures. TREAT-CAD tests the hypothesis, that aspirin is as safe and effective as vitamin K antagonists. Patients and methods TREAD-CAD is a Prospective, Randomised controlled, Open-labelled, multicentre, non-inferiority trial with Blinded assessment of outcome Events (PROBE-design). Key eligibility criteria are (i) clinical symptoms attributable to cervical artery dissection and (ii) verification of the cervical artery dissection diagnosis by established magnetic resonance imaging criteria. Patients are randomised to receive either Aspirin 300 mg daily or vitamin K antagonists for 90 days. Results Primary outcomes are assessed at 14 ± 10 days (magnetic resonance imaging and clinical examination) and at 90 ± 30 days (clinical examinations). The primary endpoint is a composite outcome measure – labelled Cerebrovascular Ischemia, major Hemorrhagic events or Death (CIHD) – and includes (i) occurrence of any stroke (including retinal infarction), (ii) new ischaemic lesions on diffusion-weighted magnetic resonance imaging, (iii) any major extracranial haemorrhage, (iv) any symptomatic intracranial haemorrhage, (v) any new haemorrhagic lesion visible on paramagnetic-susceptible sequences and (vi) death. Discussion After database closure, (i) central verification of cervical artery dissection diagnosis will be done by two experienced raters, (ii) adjudication of outcome events will be performed by independent adjudication committees, separately for clinical and imaging outcomes. The primary analysis will be done on the per protocol data set. The targeted sample size consists of 169 evaluable patients in the per protocol data set. Conclusion TREAT-CAD is testing the non-inferiority of Aspirin versus vitamin K antagonists treatment in patients with symptomatic cervical artery dissection by combined clinical and magnetic resonance imaging outcomes.

Combining clinical and magnetic resonance imaging markers enhances prediction of 12-year disability in multiple sclerosis

2016 ◽  
Vol 23 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Tomas Uher ◽  
Manuela Vaneckova ◽  
Lukas Sobisek ◽  
Michaela Tyblova ◽  
Zdenek Seidl ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Magnetic Resonance ◽  
Cumulative Risk ◽  
Resonance Imaging ◽  
Cox Models ◽  
T2 Lesions ◽  
Therapeutic Decisions ◽  
The Individual

Background: Disease progression and treatment efficacy vary among individuals with multiple sclerosis. Reliable predictors of individual disease outcomes are lacking. Objective: To examine the accuracy of the early prediction of 12-year disability outcomes using clinical and magnetic resonance imaging (MRI) parameters. Methods: A total of 177 patients from the original Avonex-Steroids-Azathioprine study were included. Participants underwent 3-month clinical follow-ups. Cox models were used to model the associations between clinical and MRI markers at baseline or after 12 months with sustained disability progression (SDP) over the 12-year observation period. Results: At baseline, T2 lesion number, T1 and T2 lesion volumes, corpus callosum (CC), and thalamic fraction were the best predictors of SDP (hazard ratio (HR) = 1.7–4.6; p ⩽ 0.001–0.012). At 12 months, Expanded Disability Status Scale (EDSS) and its change, number of new or enlarging T2 lesions, and CC volume % change were the best predictors of SDP over the follow-up (HR = 1.7–3.5; p ⩽  0.001–0.017). A composite score was generated from a subset of the best predictors of SDP. Scores of ⩾4 had greater specificity (90%–100%) and were associated with greater cumulative risk of SDP (HR = 3.2–21.6; p < 0.001) compared to the individual predictors. Conclusion: The combination of established MRI and clinical indices with MRI volumetric predictors improves the prediction of SDP over long-term follow-up and may provide valuable information for therapeutic decisions.

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