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Aberrant resting-state functional connectivity of the globus pallidus interna in first-episode schizophrenia

Qi, Wei; Wen, Zhenfu; Chen, Jingyun; Capichioni, Gillian; Ando, Fumika; Chen, Zhe Sage; Wang, Jijun; Yoncheva, Yuliya; Castellanos, Francisco X; Milad, Mohammed; Goff, Donald C
BACKGROUND:The striatal-pallidal pathway plays an important role in cognitive control and modulation of behaviors. Globus pallidus interna (GPi), as a primary output structure, is crucial in modulating excitation and inhibition. Studies of GPi in psychiatric illnesses are lacking given the technical challenges of examining this small and functionally diverse subcortical structure. METHODS:71 medication-naïve first episode schizophrenia (FES) participants and 73 healthy controls (HC) were recruited at the Shanghai Mental Health Center. Clinical symptoms and imaging data were collected at baseline and, in a subset of patients, 8 weeks after initiating treatment. Resting-state functional connectivity of sub-regions of the GP were assessed using a novel mask that combines two atlases to create 8 ROIs in the GP. RESULTS: = 0.486, p < 0.001). CONCLUSIONS:Our results implicate striatal-pallidal-thalamic pathways in antipsychotic efficacy. If replicated, these findings may reflect failure of neurodevelopmental processes in adolescence and early adulthood that decrease functional connectivity as an index of failure of the limbic/associative GPi to appropriately inhibit irrelevant signals in psychosis.
PMID: 37716202
ISSN: 1573-2509
CID: 5593342

Generalizable deep learning model for early Alzheimer's disease detection from structural MRIs

Liu, Sheng; Masurkar, Arjun V; Rusinek, Henry; Chen, Jingyun; Zhang, Ben; Zhu, Weicheng; Fernandez-Granda, Carlos; Razavian, Narges
Early diagnosis of Alzheimer's disease plays a pivotal role in patient care and clinical trials. In this study, we have developed a new approach based on 3D deep convolutional neural networks to accurately differentiate mild Alzheimer's disease dementia from mild cognitive impairment and cognitively normal individuals using structural MRIs. For comparison, we have built a reference model based on the volumes and thickness of previously reported brain regions that are known to be implicated in disease progression. We validate both models on an internal held-out cohort from The Alzheimer's Disease Neuroimaging Initiative (ADNI) and on an external independent cohort from The National Alzheimer's Coordinating Center (NACC). The deep-learning model is accurate, achieved an area-under-the-curve (AUC) of 85.12 when distinguishing between cognitive normal subjects and subjects with either MCI or mild Alzheimer's dementia. In the more challenging task of detecting MCI, it achieves an AUC of 62.45. It is also significantly faster than the volume/thickness model in which the volumes and thickness need to be extracted beforehand. The model can also be used to forecast progression: subjects with mild cognitive impairment misclassified as having mild Alzheimer's disease dementia by the model were faster to progress to dementia over time. An analysis of the features learned by the proposed model shows that it relies on a wide range of regions associated with Alzheimer's disease. These findings suggest that deep neural networks can automatically learn to identify imaging biomarkers that are predictive of Alzheimer's disease, and leverage them to achieve accurate early detection of the disease.
PMCID:9576679
PMID: 36253382
ISSN: 2045-2322
CID: 5352422

Reduced white matter venous density on MRI is associated with neurodegeneration and cognitive impairment in the elderly

Li, Chenyang; Rusinek, Henry; Chen, Jingyun; Bokacheva, Louisa; Vedvyas, Alok; Masurkar, Arjun V; Haacke, E Mark; Wisniewski, Thomas; Ge, Yulin
High-resolution susceptibility weighted imaging (SWI) provides unique contrast to small venous vasculature. The conspicuity of these mesoscopic veins, such as deep medullary veins in white matter, is subject to change from SWI venography when venous oxygenation in these veins is altered due to oxygenated blood susceptibility changes. The changes of visualization in small veins shows potential to depict regional changes of oxygen utilization and/or vascular density changes in the aging brain. The goal of this study was to use WM venous density to quantify small vein visibility in WM and investigate its relationship with neurodegenerative features, white matter hyperintensities (WMHs), and cognitive/functional status in elderly subjects (N = 137). WM venous density was significantly associated with neurodegeneration characterized by brain atrophy (β = 0.046± 0.01, p < 0.001), but no significant association was found between WM venous density and WMHs lesion load (p = 0.3963). Further analysis of clinical features revealed a negative trend of WM venous density with the sum-of-boxes of Clinical Dementia Rating and a significant association with category fluency (1-min animal naming). These results suggest that WM venous density on SWI can be used as a sensitive marker to characterize cerebral oxygen metabolism and different stages of cognitive and functional status in neurodegenerative diseases.
PMCID:9475309
PMID: 36118685
ISSN: 1663-4365
CID: 5335222

N-Tools-Browser: Web-Based Visualization of Electrocorticography Data for Epilepsy Surgery

Burkhardt, Jay; Sharma, Aaryaman; Tan, Jack; Franke, Loraine; Leburu, Jahnavi; Jeschke, Jay; Devore, Sasha; Friedman, Daniel; Chen, Jingyun; Haehn, Daniel
Epilepsy affects more than three million people in the United States. In approximately one-third of this population, anti-seizure medications do not control seizures. Many patients pursue surgical treatment that can include a procedure involving the implantation of electrodes for intracranial monitoring of seizure activity. For these cases, accurate mapping of the implanted electrodes on a patient's brain is crucial in planning the ultimate surgical treatment. Traditionally, electrode mapping results are presented in static figures that do not allow for dynamic interactions and visualizations. In collaboration with a clinical research team at a Level 4 Epilepsy Center, we developed N-Tools-Browser, a web-based software using WebGL and the X-Toolkit (XTK), to help clinicians interactively visualize the location and functional properties of implanted intracranial electrodes in 3D. Our software allows the user to visualize the seizure focus location accurately and simultaneously display functional characteristics (e.g., results from electrical stimulation mapping). Different visualization modes enable the analysis of multiple electrode groups or individual anatomical locations. We deployed a prototype of N-Tools-Browser for our collaborators at the New York University Grossman School of Medicine Comprehensive Epilepsy Center. Then, we evaluated its usefulness with domain experts on clinical cases.
PMCID:9580919
PMID: 36304315
ISSN: 2673-7647
CID: 5359642

Bilateral Distance Partition of Periventricular and Deep White Matter Hyperintensities: Performance of the Method in the Aging Brain

Chen, Jingyun; Mikheev, Artem V; Yu, Han; Gruen, Matthew D; Rusinek, Henry; Ge, Yulin
RATIONALE AND OBJECTIVES/OBJECTIVE:Periventricular and deep white matter hyperintensities (WMHs) in the elderly have been reported with distinctive roles in the progression of cognitive decline and dementia. However, the definition of these two subregions of WMHs is arbitrary and varies across studies. Here, we evaluate three partition methods for WMH subregions, including two widely used conventional methods (CV & D10) and one novel method based on bilateral distance (BD). MATERIALS AND METHODS/METHODS:The three partition methods were assessed on the MRI scans of 60 subjects, with 20 normal control, 20 mild cognitive impairment, and 20 Alzheimer's disease (AD). Resulting WMH subregional volumes were (1) compared among different partition methods and subject groups, and (2) tested for clinical associations with cognition and dementia. Inter-rater, intrarater, and interscan reproducibility of WMHs volumes were tested on 12 randomly selected subjects from the 60. RESULTS:For all three partition methods, increased periventricular WMHs were found for AD subjects over normal control. For BD and D10, but not CV method, increased Periventricular WMHs were found for AD subjects over mild cognitive impairment. Significant correlations were found between PVWMHs and Mini-Mental State Examination, Montreal Cognitive Assessment, and Clinical Dementia Rating scores. Furthermore, PVWMHs under BD partition showed higher correlations than D10 and CV. High intrarater and interscan reproducibility (ICCA = 0.998 and 0.992 correspondingly) and substantial inter-rater reproducibility (ICCA = 0.886) were detected. CONCLUSION/CONCLUSIONS:Different WMH partition methods showed comparable diagnostic abilities. The proposed BD method showed advantages in quantifying PVWMH over conventional CV and D10 methods, in terms of higher consistency, larger contrast, and higher diagnosis accuracy. Furthermore, the PVWMH under BD partition showed stronger clinical correlations than conventional methods.
PMID: 33127308
ISSN: 1878-4046
CID: 4770722

Development of a Deep Learning Model for Early Alzheimer’s Disease Detection from Structural MRIs and External Validation on an Independent Cohort

Liu, Sheng; Masurkar, Arjun V; Rusinek, Henry; Chen, Jingyun; Zhang, Ben; Zhu, Weicheng; Fernandez-Granda, Carlos; Razavian, Narges
ORIGINAL:0015178
ISSN: n/a
CID: 4903432

Image Segmentation and Nonuniformity Correction Methods

Chapter by: Chen, Jingyun; Bokacheva, Louisa; Rusinek, Henry
in: 3D printing for the radiologist by Wake, Nicole (Ed)
[S.l.] : Elsevier, 2021
pp. 31-43
ISBN: 032377573x
CID: 4903312

Aberrant Resting-State Functional Connectivity of the Globus Pallidus Subregions in First-Episode Schizophrenia [Meeting Abstract]

Qi, Wei; Wen, Zhenfu; Chen, Jingyun; Wang, Jijun; Milad, Mohammed; Goff, Donald C.
ISI:000645683800773
ISSN: 0006-3223
CID: 5263092

Plasma tau complements CSF tau and P-tau in the diagnosis of Alzheimer's disease

Fossati, Silvia; Ramos Cejudo, Jaime; Debure, Ludovic; Pirraglia, Elizabeth; Sone, Je Yeong; Li, Yi; Chen, Jingyun; Butler, Tracy; Zetterberg, Henrik; Blennow, Kaj; de Leon, Mony J
Introduction/UNASSIGNED:Plasma tau may be an accessible biomarker for Alzheimer's disease (AD), but the correlation between plasma and cerebrospinal fluid (CSF) tau and the value of combining plasma tau with CSF tau and phospho-tau (P-tau) are still unclear. Methods/UNASSIGNED:Plasma-tau, CSF-tau, and P-tau were measured in 97 subjects, including elderly cognitively normal controls (n = 68) and patients with AD (n = 29) recruited at the NYU Center for Brain Health, with comprehensive neuropsychological and magnetic resonance imaging evaluations. Results/UNASSIGNED: < .001, area under the receiver operating characteristic curve = 0.79) similarly to CSF tau and CSF P-tau and was negatively correlated with cognition in AD. Plasma and CSF tau measures were poorly correlated. Adding plasma tau to CSF tau or CSF P-tau significantly increased the areas under the receiver operating characteristic curve from 0.80 and 0.82 to 0.87 and 0.88, respectively. Discussion/UNASSIGNED:Plasma tau is higher in AD independently from CSF-tau. Importantly, adding plasma tau to CSF tau or P-tau improves diagnostic accuracy, suggesting that plasma tau may represent a useful biomarker for AD, especially when added to CSF tau measures.
PMCID:6624242
PMID: 31334328
ISSN: 2352-8729
CID: 3986922

Using fMRI connectivity to define a treatment-resistant form of post-traumatic stress disorder

Etkin, Amit; Maron-Katz, Adi; Wu, Wei; Fonzo, Gregory A; Huemer, Julia; Vértes, Petra E; Patenaude, Brian; Richiardi, Jonas; Goodkind, Madeleine S; Keller, Corey J; Ramos-Cejudo, Jaime; Zaiko, Yevgeniya V; Peng, Kathy K; Shpigel, Emmanuel; Longwell, Parker; Toll, Russ T; Thompson, Allison; Zack, Sanno; Gonzalez, Bryan; Edelstein, Raleigh; Chen, Jingyun; Akingbade, Irene; Weiss, Elizabeth; Hart, Roland; Mann, Silas; Durkin, Kathleen; Baete, Steven H; Boada, Fernando E; Genfi, Afia; Autea, Jillian; Newman, Jennifer; Oathes, Desmond J; Lindley, Steven E; Abu-Amara, Duna; Arnow, Bruce A; Crossley, Nicolas; Hallmayer, Joachim; Fossati, Silvia; Rothbaum, Barbara O; Marmar, Charles R; Bullmore, Edward T; O'Hara, Ruth
A mechanistic understanding of the pathology of psychiatric disorders has been hampered by extensive heterogeneity in biology, symptoms, and behavior within diagnostic categories that are defined subjectively. We investigated whether leveraging individual differences in information-processing impairments in patients with post-traumatic stress disorder (PTSD) could reveal phenotypes within the disorder. We found that a subgroup of patients with PTSD from two independent cohorts displayed both aberrant functional connectivity within the ventral attention network (VAN) as revealed by functional magnetic resonance imaging (fMRI) neuroimaging and impaired verbal memory on a word list learning task. This combined phenotype was not associated with differences in symptoms or comorbidities, but nonetheless could be used to predict a poor response to psychotherapy, the best-validated treatment for PTSD. Using concurrent focal noninvasive transcranial magnetic stimulation and electroencephalography, we then identified alterations in neural signal flow in the VAN that were evoked by direct stimulation of that network. These alterations were associated with individual differences in functional fMRI connectivity within the VAN. Our findings define specific neurobiological mechanisms in a subgroup of patients with PTSD that could contribute to the poor response to psychotherapy.
PMID: 30944165
ISSN: 1946-6242
CID: 3799822