Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease

Whole-brain networks derived from diffusion tensor imaging (DTI) data require the identification of seed and target regions of interest (ROIs) to assess connectivity patterns. This study investigated how initiating tracts from gray matter (GM) or white matter (WM) seed ROIs impacts (1) structural networks constructed from DTI data from healthy elderly (control) and individuals with Alzheimer’s disease (AD) and (2) between-group comparisons using these networks. DTI datasets were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Deterministic tractography was used to build two whole-brain networks for each subject; one in which tracts were initiated from WM ROIs and another in which they were initiated from GM ROIs. With respect to the first goal, in both groups, WM-seeded networks had approximately 400 more connections and stronger connections (as measured by number of streamlines per connection) than GM-seeded networks, but shared 94% of the connections found in the GM-seed networks. With respect to the second goal, between-group comparisons revealed a stronger subnetwork (as measured by number of streamlines per connection) in controls compared to AD using both WM-seeded and GM-seeded networks. The comparison using WM-seeded networks produced a larger (i.e., a greater number of connections) and more significant subnetwork in controls versus AD. Global, local, and nodal efficiency were greater in controls compared to AD, and between-group comparisons of these measures using WM-seeded networks had larger effect sizes than those using GM-seeded networks. These findings affirm that seed location significantly affects the ability to detect between-group differences in structural networks

Provisional drug-coated balloon treatment guided by physiology on de novo coronary lesion

Although drug-eluting stents (DES) have become the mainstay of percutaneous coronary intervention, late and very late stent thrombosis remains a concern. Drug-coated balloons (DCB) have the advantage of preserving the anti-restenotic benefits of DES while minimizing potential long-term safety concerns. Currently the two methods to ensure successful DCB treatment of a stenotic lesion are angiography or physiology-guided DCB application. This review will evaluate these two methods based on previous evidence and make suggestions on how to perform DCB treatment more efficiently and safely

Neuroimaging markers for studying Gulf-War illness: single-subject level analytical method based on machine learning

Gulf War illness (GWI) refers to the multitude of chronic health symptoms, spanning from fatigue, musculoskeletal pain, and neurological complaints to respiratory, gastrointestinal, and dermatologic symptoms experienced by about 250,000 GW veterans who served in the 1991 Gulf War (GW). Longitudinal studies showed that the severity of these symptoms often remain unchanged even years after the GW, and these veterans with GWI continue to have poorer general health and increased chronic medical conditions than their non-deployed counterparts. For better management and treatment of this condition, there is an urgent need for developing objective biomarkers that can help with simple and accurate diagnosis of GWI. In this study, we applied multiple neuroimaging techniques, including T1-weighted magnetic resonance imaging (T1W-MRI), diffusion tensor imaging (DTI), and novel neurite density imaging (NDI) to perform both a group-level statistical comparison and a single-subject level machine learning (ML) analysis to identify diagnostic imaging features of GWI. Our results supported NDI as the most sensitive in defining GWI characteristics. In particular, our classifier trained with white matter NDI features achieved an accuracy of 90% and F-score of 0.941 for classifying GWI cases from controls after the cross-validation. These results are consistent with our previous study which suggests that NDI measures are sensitive to the microstructural and macrostructural changes in the brain of veterans with GWI, which can be valuable for designing better diagnosis method and treatment efficacy studies.W81XWH-17-1-0440 - a department of Defense CDMRP new investigator awardPublished versio

Human-to-monkey transfer learning identifies the frontal white matter as a key determinant for predicting monkey brain age

The application of artificial intelligence (AI) to summarize a whole-brain magnetic resonance image (MRI) into an effective “brain age” metric can provide a holistic, individualized, and objective view of how the brain interacts with various factors (e.g., genetics and lifestyle) during aging. Brain age predictions using deep learning (DL) have been widely used to quantify the developmental status of human brains, but their wider application to serve biomedical purposes is under criticism for requiring large samples and complicated interpretability. Animal models, i.e., rhesus monkeys, have offered a unique lens to understand the human brain - being a species in which aging patterns are similar, for which environmental and lifestyle factors are more readily controlled. However, applying DL methods in animal models suffers from data insufficiency as the availability of animal brain MRIs is limited compared to many thousands of human MRIs. We showed that transfer learning can mitigate the sample size problem, where transferring the pre-trained AI models from 8,859 human brain MRIs improved monkey brain age estimation accuracy and stability. The highest accuracy and stability occurred when transferring the 3D ResNet [mean absolute error (MAE) = 1.83 years] and the 2D global-local transformer (MAE = 1.92 years) models. Our models identified the frontal white matter as the most important feature for monkey brain age predictions, which is consistent with previous histological findings. This first DL-based, anatomically interpretable, and adaptive brain age estimator could broaden the application of AI techniques to various animal or disease samples and widen opportunities for research in non-human primate brains across the lifespan

APOE4 allele-specific associations between diet, multimodal biomarkers, and cognition among Puerto Rican adults in Massachusetts

BackgroundApolipoprotein E (APOE) is the strongest genetic risk factor for sporadic Alzheimer’s Disease (AD), and the ε4 allele (APOE4) may interact with lifestyle factors that relate to brain structural changes, underlying the increased risk of AD. However, the exact role of APOE4 in mediating interactions between the peripheral circulatory system and the central nervous system, and how it may link to brain and cognitive aging requires further elucidation. In this analysis, we investigated the association between APOE4 carrier status and multimodal biomarkers (diet, blood markers, clinical diagnosis, brain structure, and cognition) in the context of gene–environment interactions.MethodsParticipants were older adults from a longitudinal observational study, the Boston Puerto Rican Health Study (BPRHS), who self-identified as of Puerto Rican descent. Demographics, APOE genotype, diet, blood, and clinical data were collected at baseline and at approximately 12th year, with the addition of multimodal brain magnetic resonance imaging (MRI) (T1-weighted and diffusion) and cognitive testing acquired at 12-year. Measures were compared between APOE4 carriers and non-carriers, and associations between multimodal variables were examined using correlation and multivariate network analyses within each group.ResultsA total of 156 BPRHS participants (mean age at imaging = 68 years, 77% female, mean follow-up 12.7 years) with complete multimodal data were included in the current analysis. APOE4 carriers (n = 43) showed reduced medial temporal lobe (MTL) white matter (WM) microstructural integrity and lower mini-mental state examination (MMSE) score than non-carriers (n = 113). This pattern was consistent with an independent sample from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) of n = 283 non-Hispanic White adults without dementia (mean age = 75, 40% female). Within BPRHS, carriers showed distinct connectivity patterns between multimodal biomarkers, characterized by stronger direct network connections between baseline diet/blood markers with 12-year blood/clinical measures, and between blood markers (especially lipids and cytokines) and WM. Cardiovascular burden (i.e., hypertension and diabetes status) was associated with WM integrity for both carriers and non-carriers.ConclusionAPOE4 carrier status affects interactions between dietary factors, multimodal blood biomarkers, and MTL WM integrity across ~12 years of follow-up, which may reflect increased peripheral-central systems crosstalk following blood–brain barrier breakdown in carriers

Edited Magnetic Resonance Spectroscopy Detects an Age-Related Decline in Nonhuman Primate Brain GABA Levels

Recent research had shown a correlation between aging and decreasing Gamma-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the brain. However, how GABA level varies with age in the medial portion of the brain has not yet been studied. The purpose of this study was to investigate the GABA level variation with age focusing on the posterior cingulate cortex, which is the “core hub” of the default mode network. In this study, 14 monkeys between 4 and 21 years were recruited, and MEGA-PRESS MRS was performed to measure GABA levels, in order to explore a potential link between aging and GABA. Our results showed that a correlation between age and GABA+/Creatine ratio was at the edge of significance (r=-0.523, p=0.081). There was also a near-significant trend between gray matter/white matter ratio and the GABA+/Creatine ratio (r=-0.518, p=0.0848). Meanwhile, the correlation between age and grey matter showed no significance (r=-0.028, p=0.93). Therefore, age and gray matter/white matter ratio account for different part of R-squared (adjusted R-squared = 0.5187) as independent variables for predicting GABA levels. Adjusted R-squared is about 0.5 for two independent variables. These findings suggest that there is internal neurochemical variation of GABA levels in the nonhuman primates associated with normal aging and structural brain decline

From finance to fascism: the real effect of Germany's 1931 banking crisis

Do financial crises radicalize voters? We study Germany's banking crisis of 1931, when two major banks collapsed and voting for radical parties soared. We collect new data on bank branches and firm-bank connections of 5,610 firms. Incomes plummeted in cities affected by the bank failures; connected firms curtailed payrolls. Nazi votes surged in locations exposed to Danatbank, led by a Jewish manager - but not in those suffering from the other bank's failure. Unobservables or pretrends do not explain the results. Danatbank's collapse boosted Nazi support, especially in cities with deep-seated anti-Semitism, suggesting a synergy between cultural and economic channels

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary,these findings provide complimentary evidence, as well as highlight potential contradictions,regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness

Seed Location Impacts Whole-Brain Structural Network Comparisons between Healthy Elderly and Individuals with Alzheimer’s Disease

Whole-brain networks derived from diffusion tensor imaging (DTI) data require the identification of seed and target regions of interest (ROIs) to assess connectivity patterns. This study investigated how initiating tracts from gray matter (GM) or white matter (WM) seed ROIs impacts (1) structural networks constructed from DTI data from healthy elderly (control) and individuals with Alzheimer’s disease (AD) and (2) between-group comparisons using these networks. DTI datasets were obtained from the Alzheimer’s disease Neuroimaging Initiative database. Deterministic tractography was used to build two whole-brain networks for each subject; one in which tracts were initiated from WM ROIs and another in which they were initiated from GM ROIs. With respect to the first goal, in both groups, WM-seeded networks had approximately 400 more connections and stronger connections (as measured by number of streamlines per connection) than GM-seeded networks, but shared 94% of the connections found in the GM-seed networks. With respect to the second goal, between-group comparisons revealed a stronger subnetwork (as measured by number of streamlines per connection) in controls compared to AD using both WM-seeded and GM-seeded networks. The comparison using WM-seeded networks produced a larger (i.e., a greater number of connections) and more significant subnetwork in controls versus AD. Global, local, and nodal efficiency were greater in controls compared to AD, and between-group comparisons of these measures using WM-seeded networks had larger effect sizes than those using GM-seeded networks. These findings affirm that seed location significantly affects the ability to detect between-group differences in structural networks

Thalamic changes in temporal lobe epilepsy with and without hippocampal sclerosis: A diffusion tensor imaging study

Objective: The seizure network may be different between temporal lobe epilepsy with hippocampal sclerosis (TLE + HS) and without HS (TLE - HS). Chronic seizure activity may alter the diffusion properties of a seizure network. The thalamus is known to have an anatomical connection to the medial temporal area and to play a role in seizure modulation. This study aimed to evaluate differences in thalamic changes between TLE + HS and TLE - HS with diffusion tensor imaging (DTI). Methods: Nine patients with TLE + HS and nine patients with TLE - HS were included in the study. All patients underwent surgery with good seizure outcomes. Hippocampal sclerosis was verified pathologically. Sixteen right-handed, normal subjects were enrolled as controls. DTI was acquired using 3.0 T MRI. The mean diffusivity (MD) and fractional anisotropy (FA) were calculated in the center of the bilateral thalamus with the DTIstudio program. Results: The MD of bilateral thalami increased in both TLE groups compared to controls (p0.05). Conclusion: Bilateral thalamic diffusion properties are altered in temporal lobe epilepsy. The presence of hippocampal sclerosis enhances the change ipsilaterally.Bertram EH, 2009, EPILEPSY BEHAV, V14, P32, DOI 10.1016/j.yebeh.2008.09.017Nilsson D, 2008, EPILEPSY RES, V81, P128, DOI 10.1016/j.eplepsyres.2008.05.002Labate A, 2008, NEUROLOGY, V71, P1094Riederer F, 2008, NEUROLOGY, V71, P419Gong G, 2008, EPILEPSY RES, V80, P184, DOI 10.1016/j.eplepsyres.2008.04.002Keller SS, 2008, EPILEPSIA, V49, P741, DOI 10.1111/j.1528-1167.2007.01485.xFocke NK, 2008, NEUROIMAGE, V40, P728, DOI 10.1016/j.neuroimage.2007.12.031Oouchi H, 2007, AM J NEURORADIOL, V28, P1102, DOI 10.3174/ajnr.A0488Kim CH, 2007, J NEUROSURG, V106, P111Gross DW, 2006, EPILEPSIA, V47, P1360, DOI 10.1111/j.1528-1167.2006.00603.xMueller SG, 2006, EPILEPSIA, V47, P900Kimiwada T, 2006, EPILEPSIA, V47, P167Thivard L, 2005, NEUROIMAGE, V28, P682, DOI 10.1016/j.neuroimage.2005.06.045Concha L, 2005, ANN NEUROL, V57, P188, DOI 10.1002/ana.20334PALMINI A, 2004, NEUROLOGY, V62, P2Kim YK, 2003, J NUCL MED, V44, P1006Natsume J, 2003, NEUROLOGY, V60, P1296Choi JY, 2003, EUR J NUCL MED MOL I, V30, P581, DOI 10.1007/s00259-002-1079-8Arfanakis K, 2002, MAGN RESON IMAGING, V20, P511Yoo SY, 2002, AM J NEURORADIOL, V23, P809Bertram EH, 2001, EPILEPSIA, V42, P967Kim YH, 2001, KOREAN J RADIOL, V2, P63Rugg-Gunn FJ, 2001, BRAIN, V124, P627Eriksson SH, 2001, BRAIN, V124, P617Diehl B, 2001, EPILEPSIA, V42, P21Newberg AB, 2000, J NUCL MED, V41, P1964Men S, 2000, AM J NEURORADIOL, V21, P1837Diehl B, 1999, EPILEPSIA, V40, P1667Bertram EH, 1999, NEUROSCIENCE, V92, P15Baulac M, 1998, ANN NEUROL, V44, P223Ho SS, 1998, NEUROLOGY, V50, P748ENGEL J, 1993, SURG TREATMENT EPILE, P553OLDFIELD RC, 1971, NEUROPSYCHOLOGIA, V9, P97