scholarly journals A Multimodal Imaging Approach Demonstrates Reduced Midbrain Functional Network Connectivity Is Associated With Freezing of Gait in Parkinson's Disease

2021 ◽  
Vol 12 ◽  
Author(s):  
Amgad Droby ◽  
Elisa Pelosin ◽  
Martina Putzolu ◽  
Giulia Bommarito ◽  
Roberta Marchese ◽  
...  
Keyword(s):  
Structural Damage ◽  
Imaging Techniques ◽  
Freezing Of Gait ◽  
Cognitive Networks ◽  
Functional Network ◽  
Cortical Atrophy ◽  
Seed Region ◽  
Whole Brain ◽  
Severity Scores ◽  
Imaging Approach

Background: The pathophysiological mechanisms underlying freezing of gait (FOG) are poorly defined. MRI studies in FOG showed a distinct pattern of cortical atrophy and decreased functional connectivity (FC) within motor and cognitive networks. Furthermore, reduced rs-FC within midbrain, frontal, and temporal areas has been also described. This study investigated the patterns of whole-brain FC alterations within midbrain inter-connected regions in PD-FOG patients, and whether these patterns are linked to midbrain structural damage using a multi-modal imaging approach, combing structural and functional imaging techniques.Methods: Thirty three PD patients (16 PD-FOG, 17 PD noFOG), and 21 sex- and age-matched healthy controls (HCs) were prospectively enrolled. All subjects underwent MRI scan at 1.5T, whereas only PD patients underwent clinical and cognitive assessment. Grey matter (GM) integrity was measured using voxel-based morphometry (VBM). VBM findings served as basis to localize midbrain damage, and were further used as a seed region for investigating whole-brain FC alterations using rs-fMRI.Results: In rs-fMRI, patients with PD and FOG demonstrated significant decrease of midbrain-cortical FC levels in the R PCG, right postcentral, and supramarginal gyri compared to controls and the middle cingulate compared to noFOG group. Based on the regression analysis, MOCA, UPDRS-III total score, and FOG severity scores were associated with FC levels in several frontal, parietal and temporal regions.Discussion: The present results suggest that midbrain structural damage as well as decreased FC within the brainstem functional network might contribute to FOG occurrence in PD patients.

Identification of a specific functional network altered in poststroke cognitive impairment

Neurology ◽  
2018 ◽  
Vol 90 (21) ◽  
pp. e1879-e1888 ◽  
Author(s):  
Clément Bournonville ◽  
Hilde Hénon ◽  
Thibaut Dondaine ◽  
Christine Delmaire ◽  
Stephanie Bombois ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Clustering Coefficient ◽  
Functional Network ◽  
Cognitive Domain ◽  
Cortical Atrophy ◽  
Node Degree ◽  
Resting State Functional Connectivity ◽  
Stroke Patients ◽  
Whole Brain ◽  
Cognitive Domains

ObjectiveTo study the association between poststroke cognitive impairment and defining a specific resting functional marker.MethodsThe resting-state functional connectivity 6 months after an ischemic stroke in 56 patients was investigated. Twenty-nine of the patients who had an impairment of one or several cognitive domains were compared to 27 without any cognitive deficit. We studied the whole-brain connectivity using 2 complementary approaches: graph theory to study the functional network organization and network-based statistics to explore connectivity between brain regions. We assessed the potential cortical atrophy using voxel-based morphometry analysis.ResultsThe overall topological organization of the functional network was not altered in cognitively impaired stroke patients, who had the same mean node degree, average clustering coefficient, and global efficiency as cognitively healthy stroke patients. Network-based statistics analysis showed that poststroke cognitive impairment was associated with dysfunction of a whole-brain network composed of 167 regions and 178 connections, and functional disconnections between superior, middle, and inferior frontal gyri and the superior and inferior temporal gyri. These regions had connections that were specifically and positively correlated with cognitive domain scores. No intergroup differences in overall gray matter thickness and ischemic infarct topography were observed. To assess the effect of prestroke white matter hyperintensities on connectivity, we included the initial Fazekas scale in the regression model for a second network-based analysis. The resulting network was associated with the same key alterations but had fewer connections.ConclusionsThe observed functional network alterations suggest that the appearance of a cognitive impairment following stroke may be associated with a particular functional alteration, shared specifically between cognitive domains.

Diagnostic Imaging for Structural Damage

2008 ◽  
Vol 47-50 ◽  
pp. 1157-1160 ◽  
Author(s):  
Zhong Qing Su ◽  
Li Cheng ◽  
Xiao Ming Wang ◽  
Long Yu
Keyword(s):  
Diagnostic Imaging ◽  
Lamb Wave ◽  
Structural Damage ◽  
Imaging Techniques ◽  
Prior Probabilities ◽  
Damage Location ◽  
Active Sensor ◽  
Imaging Approach ◽  
Engineered Structures ◽  
Traditional Approaches

There has been increasing awareness of the use of intuitional imaging techniques to describe a damage event in the engineered structures. A Lamb wave-based diagnostic imaging approach was developed in this study, by fusing the prior probabilities established by the sensors of an active sensor network at different spatial positions of the structure under inspection. Rather than pinpointing the damage location and shape with definitive parameters, such an approach was intended to probabilistically predict the occurrence of a damage event, which is in nature more consistent with the implication of ‘estimating’ damage in SHM than traditional approaches. As validation, the approach was employed to detect mono- and dual-delamination in CF/EP laminates, and the results were represented in probability contour diagrams, where the structural damage became intuitional. Other major benefits of the approach include the independence of its effectiveness on the number of damage and enhanced tolerance to noise/uncertainties.

Imaging Damage Using Mixed Passive and Active Sensors

2013 ◽  
Vol 558 ◽  
pp. 244-251 ◽  
Author(s):  
Chun H. Wang ◽  
L.R. Francis Rose
Keyword(s):  
Structural Damage ◽  
Guided Waves ◽  
Imaging Techniques ◽  
Scattered Wave ◽  
Strain Gauges ◽  
Active Sensors ◽  
Active Sensor ◽  
Imaging Approach ◽  
Damage Imaging ◽  
Passive Sensors

Existing damage imaging techniques rely on the use of active sensors, such as piezoelectric actuators, that can both transmit and receive guided waves. This paper presents a new time-reversal imaging approach to enable the use of passive sensors, such as optical fibre sensors and strain gauges, to augment active sensors for imaging structural damage. Computational simulations have revealed that damage size and severity can be accurately determined from the scattered wave using as few as six sensors: one active sensor and five passive sensors.

scholarly journals Imaging of Joint and Soft Tissue Involvement in Systemic Lupus Erythematosus

2021 ◽  
Vol 23 (9) ◽  
Author(s):  
Andrea Di Matteo ◽  
Gianluca Smerilli ◽  
Edoardo Cipolletta ◽  
Fausto Salaffi ◽  
Rossella De Angelis ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Soft Tissue ◽  
Lupus Erythematosus ◽  
Structural Damage ◽  
Structural Changes ◽  
Soft Tissues ◽  
Imaging Techniques ◽  
Joint Involvement ◽  
Systemic Lupus ◽  
Muscle Involvement

Abstract Purpose of Review To highlight the potential uses and applications of imaging in the assessment of the most common and relevant musculoskeletal (MSK) manifestations in systemic lupus erythematosus (SLE). Recent Findings Ultrasound (US) and magnetic resonance imaging (MRI) are accurate and sensitive in the assessment of inflammation and structural damage at the joint and soft tissue structures in patients with SLE. The US is particularly helpful for the detection of joint and/or tendon inflammation in patients with arthralgia but without clinical synovitis, and for the early identification of bone erosions. MRI plays a key role in the early diagnosis of osteonecrosis and in the assessment of muscle involvement (i.e., myositis and myopathy). Conventional radiography (CR) remains the traditional gold standard for the evaluation of structural damage in patients with joint involvement, and for the study of bone pathology. The diagnostic value of CR is affected by the poor sensitivity in demonstrating early structural changes at joint and soft tissue level. Computed tomography allows a detailed evaluation of bone damage. However, the inability to distinguish different soft tissues and the need for ionizing radiation limit its use to selected clinical circumstances. Nuclear imaging techniques are valuable resources in patients with suspected bone infection (i.e., osteomyelitis), especially when MRI is contraindicated. Finally, dual energy X-ray absorptiometry represents the imaging mainstay for the assessment and monitoring of bone status in patients with or at-risk of osteoporosis. Summary Imaging provides relevant and valuable information in the assessment of MSK involvement in SLE.

Whole brain atlas-based diffusion kurtosis imaging parameters for evaluation of minimal hepatic encephalopathy

2021 ◽  
pp. 197140092110269
Author(s):  
Prateek Gupta ◽  
Sameer Vyas ◽  
Teddy Salan ◽  
Chirag Jain ◽  
Sunil Taneja ◽  
...  
Keyword(s):  
Hepatic Encephalopathy ◽  
Clinical Symptoms ◽  
Early Stage ◽  
Imaging Techniques ◽  
Clinical Stage ◽  
Minimal Hepatic Encephalopathy ◽  
Brain Atlas ◽  
Diffusion Kurtosis Imaging ◽  
Whole Brain ◽  
Diffusion Kurtosis

Background and purposes Minimal hepatic encephalopathy (MHE) has no recognizable clinical symptoms, but patients have cognitive and psychomotor deficits. Hyperammonemia along with neuroinflammation lead to microstructural changes in cerebral parenchyma. Changes at conventional imaging are detected usually at the overt clinical stage, but microstructural alterations by advanced magnetic resonance imaging techniques can be detected at an early stage. Materials and methods Whole brain diffusion kurtosis imaging (DKI) data acquired at 3T was analyzed to investigate microstructural parenchymal changes in 15 patients with MHE and compared with 15 age- and sex-matched controls. DKI parametric maps, namely kurtosis fractional anisotropy (kFA), mean kurtosis (MK), axial kurtosis (AK) and radial kurtosis (RK), were evaluated at 64 white matter (WM) and gray matter (GM) regions of interest (ROIs) in the whole brain and correlated with the psychometric hepatic encephalopathy score (PHES). Results The MHE group showed a decrease in kFA and AK across the whole brain, whereas MK and RK decreased in WM ROIs but increased in several cortical and deep GM ROIs. These alterations were consistent with brain regions involved in cognitive function. Significant moderate to strong correlations (–0.52 to –0.66; 0.56) between RK, MK and kFA kurtosis metrics and PHES were observed. Conclusion DKI parameters show extensive microstructural brain abnormalities in MHE with minor correlation between the severity of tissue damage and psychometric scores.

scholarly journals Alzheimer’s Disease Projection From Normal to Mild Dementia Reflected in Functional Network Connectivity: A Longitudinal Study

2021 ◽  
Vol 14 ◽  
Author(s):  
Mohammad S. E. Sendi ◽  
Elaheh Zendehrouh ◽  
Robyn L. Miller ◽  
Zening Fu ◽  
Yuhui Du ◽  
...  
Keyword(s):  
Default Mode Network ◽  
Early Stage ◽  
Network Connectivity ◽  
Functional Network ◽  
Normal Brain ◽  
Whole Brain ◽  
Mild Dementia ◽  
Sensorimotor Network ◽  
Functional Network Connectivity ◽  
The Brain

BackgroundAlzheimer’s disease (AD) is the most common age-related problem and progresses in different stages, including mild cognitive impairment (early stage), mild dementia (middle-stage), and severe dementia (late-stage). Recent studies showed changes in functional network connectivity obtained from resting-state functional magnetic resonance imaging (rs-fMRI) during the transition from healthy aging to AD. By assuming that the brain interaction is static during the scanning time, most prior studies are focused on static functional or functional network connectivity (sFNC). Dynamic functional network connectivity (dFNC) explores temporal patterns of functional connectivity and provides additional information to its static counterpart.MethodWe used longitudinal rs-fMRI from 1385 scans (from 910 subjects) at different stages of AD (from normal to very mild AD or vmAD). We used group-independent component analysis (group-ICA) and extracted 53 maximally independent components (ICs) for the whole brain. Next, we used a sliding-window approach to estimate dFNC from the extracted 53 ICs, then group them into 3 different brain states using a clustering method. Then, we estimated a hidden Markov model (HMM) and the occupancy rate (OCR) for each subject. Finally, we investigated the link between the clinical rate of each subject with state-specific FNC, OCR, and HMM.ResultsAll states showed significant disruption during progression normal brain to vmAD one. Specifically, we found that subcortical network, auditory network, visual network, sensorimotor network, and cerebellar network connectivity decrease in vmAD compared with those of a healthy brain. We also found reorganized patterns (i.e., both increases and decreases) in the cognitive control network and default mode network connectivity by progression from normal to mild dementia. Similarly, we found a reorganized pattern of between-network connectivity when the brain transits from normal to mild dementia. However, the connectivity between visual and sensorimotor network connectivity decreases in vmAD compared with that of a healthy brain. Finally, we found a normal brain spends more time in a state with higher connectivity between visual and sensorimotor networks.ConclusionOur results showed the temporal and spatial pattern of whole-brain FNC differentiates AD form healthy control and suggested substantial disruptions across multiple dynamic states. In more detail, our results suggested that the sensory network is affected more than other brain network, and default mode network is one of the last brain networks get affected by AD In addition, abnormal patterns of whole-brain dFNC were identified in the early stage of AD, and some abnormalities were correlated with the clinical score.

scholarly journals A whole-brain and cross-diagnostic perspective on functional brain network dysfunction

2018 ◽  
Author(s):  
Marjolein Spronk ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
Brian P. Keane ◽  
Alan Anticevic ◽  
...  
Keyword(s):  
Mental Illness ◽  
Resting State ◽  
Brain Network ◽  
Functional Network ◽  
Graph Distance ◽  
Network Organization ◽  
Whole Brain ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Mental Diseases

AbstractA wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation – we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.

scholarly journals Cardiac Tumors: Diagnosis, Prognosis, and Treatment

2020 ◽  
Vol 22 (12) ◽  
Author(s):  
Rossana Bussani ◽  
Matteo Castrichini ◽  
Luca Restivo ◽  
Enrico Fabris ◽  
Aldostefano Porcari ◽  
...  
Keyword(s):  
Multimodality Imaging ◽  
Imaging Techniques ◽  
Final Diagnosis ◽  
Cardiac Tumors ◽  
Imaging Evaluation ◽  
The Past ◽  
Positron Emission ◽  
Imaging Approach ◽  
Oncology Practice ◽  
Cardiac Masses

Abstract Purpose of Review Cardiac masses frequently present significant diagnostic and therapeutic clinical challenges and encompass a broad set of lesions that can be either neoplastic or non-neoplastic. We sought to provide an overview of cardiac tumors using a cardiac chamber prevalence approach and providing epidemiology, imaging, histopathology, diagnostic workup, treatment, and prognoses of cardiac tumors. Recent Findings Cardiac tumors are rare but remain an important component of cardio-oncology practice. Over the past decade, the advances in imaging techniques have enabled a noninvasive diagnosis in many cases. Indeed, imaging modalities such as cardiac magnetic resonance, computed tomography, and positron emission tomography are important tools for diagnosing and characterizing the lesions. Although an epidemiological and multimodality imaging approach is useful, the definite diagnosis requires histologic examination in challenging scenarios, and histopathological characterization remains the diagnostic gold standard. Summary A comprehensive clinical and multimodality imaging evaluation of cardiac tumors is fundamental to obtain a proper differential diagnosis, but histopathology is necessary to reach the final diagnosis and subsequent clinical management.

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