Subcortical tau is linked to hypoperfusion in connected cortical regions in 4-repeat tauopathies.

4-repeat (4R) tauopathies are neurodegenerative diseases characterized by cerebral accumulation of 4R tau pathology. The most prominent 4R-tauopathies are progressive-supranuclear-palsy (PSP) and corticobasal-degeneration (CBD) characterized by subcortical tau accumulation and cortical neuronal dysfunction, as shown by PET-assessed hypoperfusion and glucose hypometabolism. Yet, there is a spatial mismatch between subcortical tau deposition patterns and cortical neuronal dysfunction, and it is unclear how these two pathological brain changes are interrelated. Here, we hypothesized that subcortical tau pathology induces remote neuronal dysfunction in functionally connected cortical regions to test a pathophysiological model that mechanistically links subcortical tau accumulation to cortical neuronal dysfunction in 4R tauopathies. We included 51 Aß-negative patients with clinically diagnosed PSP variants (n=26) or Corticobasal Syndrome (CBS; n=25) who underwent structural MRI and 18F-PI-2620 tau-PET. 18F-PI-2620 tau-PET was recorded using a dynamic one-stop-shop acquisition protocol, to determine an early 0.5-2.5 min post-tracer-injection perfusion window for assessing cortical neuronal dysfunction, as well as a 20-40 min post-tracer-injection window to determine 4R-tau load. Perfusion-PET (i.e. early-window) was assessed in 200 cortical regions, and tau-PET was assessed in 32 subcortical regions of established functional brain atlasses. We determined tau epicenters as subcortical regions with highest 18F-PI-2620 tau-PET signal and assessed the connectivity of tau epicenters to cortical ROIs using a resting-state fMRI-based functional connectivity template derived from 69 healthy elderly controls from the ADNI cohort. Using linear regression, we assessed whether i) higher subcortical tau-PET was associated with reduced cortical perfusion and ii) whether cortical perfusion reductions were observed preferentially in regions closely connected to subcortical tau epicenters. As hypothesized, higher subcortical tau-PET was associated with overall lower cortical perfusion, which remained consistent when controlling for cortical tau-PET. Using group-average and subject-level PET data, we found that the seed-based connectivity pattern of subcortical tau epicenters aligned with cortical perfusion patterns, where cortical regions that were more closely connected to the tau epicenter showed lower perfusion. Together, subcortical tau-accumulation is associated with remote perfusion reductions indicative of neuronal dysfunction in functionally connected cortical regions in 4R-tauopathies. This suggests that subcortical tau pathology may induce cortical dysfunction, which may contribute to clinical disease manifestation and clinical heterogeneity.

Associations between sex, body mass index and the individual microglial response in Alzheimer's disease.

BACKGROUND AND OBJECTIVES: 18-kDa translocator protein position-emission-tomography (TSPO-PET) imaging emerged for in vivo assessment of neuroinflammation in Alzheimer's disease (AD) research. Sex and obesity effects on TSPO-PET binding have been reported for cognitively normal humans (CN), but such effects have not yet been systematically evaluated in patients with AD. Thus, we aimed to investigate the impact of sex and obesity on the relationship between ß-amyloid-accumulation and microglial activation in AD. METHODS: 49 patients with AD (29 females, all Aß-positive) and 15 Aß-negative CN (8 female) underwent TSPO-PET ([18F]GE-180) and ß-amyloid-PET ([18F]flutemetamol) imaging. In 24 patients with AD (14 females), tau-PET ([18F]PI-2620) was additionally available. The brain was parcellated into 218 cortical regions and standardized-uptake-value-ratios (SUVr, cerebellar reference) were calculated. Per region and tracer, the regional increase of PET SUVr (z-score) was calculated for AD against CN. The regression derived linear effect of regional Aß-PET on TSPO-PET was used to determine the Aß-plaque-dependent microglial response (slope) and the Aß-plaque-independent microglial response (intercept) at the individual patient level. All read-outs were compared between sexes and tested for a moderation effect of sex on associations with body mass index (BMI). RESULTS: In AD, females showed higher mean cortical TSPO-PET z-scores (0.91 ± 0.49; males 0.30 ± 0.75; p = 0.002), while Aß-PET z-scores were similar. The Aß-plaque-independent microglial response was stronger in females with AD (+ 0.37 ± 0.38; males with AD - 0.33 ± 0.87; p = 0.006), pronounced at the prodromal stage. On the contrary, the Aß-plaque-dependent microglial response was not different between sexes. The Aß-plaque-independent microglial response was significantly associated with tau-PET in females (Braak-II regions: r = 0.757, p = 0.003), but not in males. BMI and the Aß-plaque-independent microglial response were significantly associated in females (r = 0.44, p = 0.018) but not in males (BMI*sex interaction: F(3,52) = 3.077, p = 0.005). CONCLUSION: While microglia response to fibrillar Aß is similar between sexes, women with AD show a stronger Aß-plaque-independent microglia response. This sex difference in Aß-independent microglial activation may be associated with tau accumulation. BMI is positively associated with the Aß-plaque-independent microglia response in females with AD but not in males, indicating that sex and obesity need to be considered when studying neuroinflammation in AD.

Individual regional associations between Aß-, tau- and neurodegeneration (ATN) with microglial activation in patients with primary and secondary tauopathies.

ß-amyloid (Aß) and tau aggregation as well as neuronal injury and atrophy (ATN) are the major hallmarks of Alzheimer's disease (AD), and biomarkers for these hallmarks have been linked to neuroinflammation. However, the detailed regional associations of these biomarkers with microglial activation in individual patients remain to be elucidated. We investigated a cohort of 55 patients with AD and primary tauopathies and 10 healthy controls that underwent TSPO-, Aß-, tau-, and perfusion-surrogate-PET, as well as structural MRI. Z-score deviations for 246 brain regions were calculated and biomarker contributions of Aß (A), tau (T), perfusion (N1), and gray matter atrophy (N2) to microglial activation (TSPO, I) were calculated for each individual subject. Individual ATN-related microglial activation was correlated with clinical performance and CSF soluble TREM2 (sTREM2) concentrations. In typical and atypical AD, regional tau was stronger and more frequently associated with microglial activation when compared to regional Aß (AD: ßT = 0.412 ± 0.196 vs. ßA = 0.142 ± 0.123, p < 0.001; AD-CBS: ßT = 0.385 ± 0.176 vs. ßA = 0.131 ± 0.186, p = 0.031). The strong association between regional tau and microglia reproduced well in primary tauopathies (ßT = 0.418 ± 0.154). Stronger individual associations between tau and microglial activation were associated with poorer clinical performance. In patients with 4RT, sTREM2 levels showed a positive association with tau-related microglial activation. Tau pathology has strong regional associations with microglial activation in primary and secondary tauopathies. Tau and Aß related microglial response indices may serve as a two-dimensional in vivo assessment of neuroinflammation in neurodegenerative diseases.

Delineating morbidity patterns in preterm infants at near-term age using a data-driven approach.

BACKGROUND: Long-term survival after premature birth is significantly determined by development of morbidities, primarily affecting the cardio-respiratory or central nervous system. Existing studies are limited to pairwise morbidity associations, thereby lacking a holistic understanding of morbidity co-occurrence and respective risk profiles. METHODS: Our study, for the first time, aimed at delineating and characterizing morbidity profiles at near-term age and investigated the most prevalent morbidities in preterm infants: bronchopulmonary dysplasia (BPD), pulmonary hypertension (PH), mild cardiac defects, perinatal brain pathology and retinopathy of prematurity (ROP). For analysis, we employed two independent, prospective cohorts, comprising a total of 530 very preterm infants: AIRR ("Attention to Infants at Respiratory Risks") and NEuroSIS ("Neonatal European Study of Inhaled Steroids"). Using a data-driven strategy, we successfully characterized morbidity profiles of preterm infants in a stepwise approach and (1) quantified pairwise morbidity correlations, (2) assessed the discriminatory power of BPD (complemented by imaging-based structural and functional lung phenotyping) in relation to these morbidities, (3) investigated collective co-occurrence patterns, and (4) identified infant subgroups who share similar morbidity profiles using machine learning techniques. RESULTS: First, we showed that, in line with pathophysiologic understanding, BPD and ROP have the highest pairwise correlation, followed by BPD and PH as well as BPD and mild cardiac defects. Second, we revealed that BPD exhibits only limited capacity in discriminating morbidity occurrence, despite its prevalence and clinical indication as a driver of comorbidities. Further, we demonstrated that structural and functional lung phenotyping did not exhibit higher association with morbidity severity than BPD. Lastly, we identified patient clusters that share similar morbidity patterns using machine learning in AIRR (n=6 clusters) and NEuroSIS (n=8 clusters). CONCLUSIONS: By capturing correlations as well as more complex morbidity relations, we provided a comprehensive characterization of morbidity profiles at discharge, linked to shared disease pathophysiology. Future studies could benefit from identifying risk profiles to thereby develop personalized monitoring strategies. TRIAL REGISTRATION: AIRR: DRKS.de, DRKS00004600, 28/01/2013. NEuroSIS: ClinicalTrials.gov, NCT01035190, 18/12/2009.

MRI pulmonary artery flow detects lung vascular pathology in preterms with lung disease.

BACKGROUND: Pulmonary vascular disease (PVD) affects the majority of preterm neonates with bronchopulmonary dysplasia (BPD) and significantly determines long-term mortality through undetected progression into pulmonary hypertension. Our objectives were to associate characteristics of pulmonary artery (PA) flow and cardiac function with BPD-associated PVD near term using advanced magnetic resonance imaging (MRI) for improved risk stratification. METHODS: Preterms <32 weeks postmenstrual age (PMA) with/without BPD were clinically monitored including standard echocardiography and prospectively enrolled for 3 T MRI in spontaneous sleep near term (AIRR (Attention to Infants at Respiratory Risks) study). Semi-manual PA flow quantification (phase-contrast MRI; no BPD n=28, mild BPD n=35 and moderate/severe BPD n=25) was complemented by cardiac function assessment (cine MRI). RESULTS: We identified abnormalities in PA flow and cardiac function, i.e. increased net forward volume right/left ratio, decreased mean relative area change and pathological right end-diastolic volume, to sensitively detect BPD-associated PVD while correcting for PMA (leave-one-out area under the curve 0.88, sensitivity 0.80 and specificity 0.81). We linked these changes to increased right ventricular (RV) afterload (RV-arterial coupling (p=0.02), PA mid-systolic notching (t2; p=0.015) and cardiac index (p=1.67×10-8)) and correlated echocardiographic findings. Identified in moderate/severe BPD, we successfully applied the PA flow model in heterogeneous mild BPD cases, demonstrating strong correlation of PVD probability with indicators of BPD severity, i.e. duration of mechanical ventilation (rs=0.63, p=2.20×10-4) and oxygen supplementation (rs=0.60, p=6.00×10-4). CONCLUSIONS: Abnormalities in MRI PA flow and cardiac function exhibit significant, synergistic potential to detect BPD-associated PVD, advancing the possibilities of risk-adapted monitoring.

[18F]F-DED PET imaging of reactive astrogliosis in neurodegenerative diseases: preclinical proof of concept and first-in-human data.

OBJECTIVES: Reactive gliosis is a common pathological hallmark of CNS pathology resulting from neurodegeneration and neuroinflammation. In this study we investigate the capability of a novel monoamine oxidase B (MAO-B) PET ligand to monitor reactive astrogliosis in a transgenic mouse model of Alzheimer`s disease (AD). Furthermore, we performed a pilot study in patients with a range of neurodegenerative and neuroinflammatory conditions. METHODS: A cross-sectional cohort of 24 transgenic (PS2APP) and 25 wild-type mice (age range: 4.3-21.0 months) underwent 60 min dynamic [18F]fluorodeprenyl-D2 ([18F]F-DED), static 18 kDa translocator protein (TSPO, [18F]GE-180) and ß-amyloid ([18F]florbetaben) PET imaging. Quantification was performed via image derived input function (IDIF, cardiac input), simplified non-invasive reference tissue modelling (SRTM2, DVR) and late-phase standardized uptake value ratios (SUVr). Immunohistochemical (IHC) analyses of glial fibrillary acidic protein (GFAP) and MAO-B were performed to validate PET imaging by gold standard assessments. Patients belonging to the Alzheimer's disease continuum (AD, n = 2), Parkinson's disease (PD, n = 2), multiple system atrophy (MSA, n = 2), autoimmune encephalitis (n = 1), oligodendroglioma (n = 1) and one healthy control underwent 60 min dynamic [18F]F-DED PET and the data were analyzed using equivalent quantification strategies. RESULTS: We selected the cerebellum as a pseudo-reference region based on the immunohistochemical comparison of age-matched PS2APP and WT mice. Subsequent PET imaging revealed that PS2APP mice showed elevated hippocampal and thalamic [18F]F-DED DVR when compared to age-matched WT mice at 5 months (thalamus: + 4.3%; p = 0.048), 13 months (hippocampus: + 7.6%, p = 0.022) and 19 months (hippocampus: + 12.3%, p < 0.0001; thalamus: + 15.2%, p < 0.0001). Specific [18F]F-DED DVR increases of PS2APP mice occurred earlier when compared to signal alterations in TSPO and ß-amyloid PET and [18F]F-DED DVR correlated with quantitative immunohistochemistry (hippocampus: R = 0.720, p < 0.001; thalamus: R = 0.727, p = 0.002). Preliminary experience in patients showed [18F]F-DED VT and SUVr patterns, matching the expected topology of reactive astrogliosis in neurodegenerative (MSA) and neuroinflammatory conditions, whereas the patient with oligodendroglioma and the healthy control indicated [18F]F-DED binding following the known physiological MAO-B expression in brain. CONCLUSIONS: [18F]F-DED PET imaging is a promising approach to assess reactive astrogliosis in AD mouse models and patients with neurological diseases.

Microglial Activation and Connectivity in Alzheimer Disease and Aging.

OBJECTIVE: Alzheimer disease (AD) is characterized by amyloid ß (Aß) plaques and neurofibrillary tau tangles, but increasing evidence suggests that neuroinflammation also plays a key role, driven by the activation of microglia. Aß and tau pathology appear to spread along pathways of highly connected brain regions, but it remains elusive whether microglial activation follows a similar distribution pattern. Here, we assess whether connectivity is associated with microglia activation patterns. METHODS: We included 32 Aß-positive early AD subjects (18 women, 14 men) and 18 Aß-negative age-matched healthy controls (10 women, 8 men) from the prospective ActiGliA (Activity of Cerebral Networks, Amyloid and Microglia in Aging and Alzheimer's Disease) study. All participants underwent microglial activation positron emission tomography (PET) with the third-generation mitochondrial 18 kDa translocator protein (TSPO) ligand [18 F]GE-180 and magnetic resonance imaging (MRI) to measure resting-state functional and structural connectivity. RESULTS: We found that inter-regional covariance in TSPO-PET and standardized uptake value ratio was preferentially distributed along functionally highly connected brain regions, with MRI structural connectivity showing a weaker association with microglial activation. AD patients showed increased TSPO-PET tracer uptake bilaterally in the anterior medial temporal lobe compared to controls, and higher TSPO-PET uptake was associated with cognitive impairment and dementia severity in a disease stage-dependent manner. INTERPRETATION: Microglial activation distributes preferentially along highly connected brain regions, similar to tau pathology. These findings support the important role of microglia in neurodegeneration, and we speculate that pathology spreads throughout the brain along vulnerable connectivity pathways. ANN NEUROL 2022;92:768-781.

Variable functional connectivity architecture of the preterm human brain: Impact of developmental cortical expansion and maturation.

Functional connectivity (FC) is known to be individually unique and to reflect cognitive variability. Although FC can serve as a valuable correlate and potential predictor of (patho-) physiological nervous function in high-risk constellations, such as preterm birth, templates for individualized FC analysis are lacking, and knowledge about the capacity of the premature brain to develop FC variability is limited. In a cohort of prospectively recruited, preterm-born infants undergoing magnetic resonance imaging close to term-equivalent age, we show that the overall pattern could be reliably detected with a broad range of interindividual FC variability in regions of higher-order cognitive functions (e.g., association cortices) and less interindividual variability in unimodal regions (e.g., visual and motor cortices). However, when comparing the preterm and adult brains, some brain regions showed a marked shift in variability toward adulthood. This shift toward greater variability was strongest in cognitive networks like the attention and frontoparietal networks and could be partially predicted by developmental cortical expansion. Furthermore, FC variability was reflected by brain tissue characteristics indicating cortical maturation. Brain regions with high functional variability (e.g., the inferior frontal gyrus and temporoparietal junction) displayed lower cortical maturation at birth compared with somatosensory cortices. In conclusion, the overall pattern of interindividual variability in FC is already present preterm; however, some brain regions show increased variability toward adulthood, identifying characteristic patterns, such as in cognitive networks. These changes are related to postnatal cortical expansion and maturation, allowing for environmental and developmental factors to translate into marked individual differences in FC.

Performing group-level functional image analyses based on homologous functional regions mapped in individuals.

Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based on global brain morphology, which cannot establish proper functional correspondence between subjects due to substantial intersubject variability in functional organization. Here, we reliably identified a set of discrete, homologous functional regions in individuals to improve intersubject alignment of fMRI data. These functional regions demonstrated marked intersubject variability in size, position, and connectivity. We found that previously reported intersubject variability in functional connectivity maps could be partially explained by variability in size and position of the functional regions. Importantly, individual differences in network topography are associated with individual differences in task-evoked activations, suggesting that these individually specified regions may serve as the "localizer" to improve the alignment of task-fMRI data. We demonstrated that aligning task-fMRI data using the regions derived from resting state fMRI may lead to increased statistical power of task-fMRI analyses. In addition, resting state functional connectivity among these homologous regions is able to capture the idiosyncrasies of subjects and better predict fluid intelligence (gF) than connectivity measures derived from group-level brain atlases. Critically, we showed that not only the connectivity but also the size and position of functional regions are related to human behavior. Collectively, these findings suggest that identifying homologous functional regions across individuals can benefit a wide range of studies in the investigation of connectivity, task activation, and brain-behavior associations.

Association between aerobic fitness and the functional connectome in patients with schizophrenia.

BACKGROUND: Schizophrenia is accompanied by widespread alterations in static functional connectivity associated with symptom severity and cognitive deficits. Improvements in aerobic fitness have been demonstrated to ameliorate symptomatology and cognition in people with schizophrenia, but the intermediary role of macroscale connectivity patterns remains unknown. OBJECTIVE: Therefore, we aim to explore the relation between aerobic fitness and the functional connectome in individuals with schizophrenia. Further, we investigate clinical and cognitive relevance of the identified fitness-connectivity links. METHODS: Patients diagnosed with schizophrenia were included in this cross-sectional resting-state fMRI analysis. Multilevel Bayesian partial correlations between aerobic fitness and functional connections across the whole brain as well as between static functional connectivity patterns and clinical and cognitive outcome were performed. Preliminary causal inferences were enabled based on mediation analyses. RESULTS: Static functional connectivity between the subcortical nuclei and the cerebellum as well as between temporal seeds mediated the attenuating relation between aerobic fitness and total symptom severity. Functional connections between cerebellar seeds affected the positive link between aerobic fitness and global cognition, while the functional interplay between central and limbic seeds drove the beneficial association between aerobic fitness and emotion recognition. CONCLUSION: The current study provides first insights into the interactions between aerobic fitness, the functional connectome and clinical and cognitive outcome in people with schizophrenia, but causal interpretations are preliminary. Further interventional aerobic exercise studies are needed to replicate the current findings and to enable conclusive causal inferences. TRIAL REGISTRATION: The study which the manuscript is based on is registered in the International Clinical Trials Database (ClinicalTrials.gov identifier [NCT number]: NCT03466112) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

Resting-State Network Alterations Differ between Alzheimer's Disease Atrophy Subtypes.

Several Alzheimer's disease (AD) atrophy subtypes were identified, but their brain network properties are unclear. We analyzed data from two independent datasets, including 166 participants (103 AD/63 controls) from the DZNE-longitudinal cognitive impairment and dementia study and 151 participants (121 AD/30 controls) from the AD neuroimaging initiative cohorts, aiming to identify differences between AD atrophy subtypes in resting-state functional magnetic resonance imaging intra-network connectivity (INC) and global and nodal network properties. Using a data-driven clustering approach, we identified four AD atrophy subtypes with differences in functional connectivity, accompanied by clinical and biomarker alterations, including a medio-temporal-predominant (S-MT), a limbic-predominant (S-L), a diffuse (S-D), and a mild-atrophy (S-MA) subtype. S-MT and S-D showed INC reduction in the default mode, dorsal attention, visual and limbic network, and a pronounced reduction of "global efficiency" and decrease of the "clustering coefficient" in parietal and temporal lobes. Despite severe atrophy in limbic areas, the S-L exhibited only marginal global network but substantial nodal network failure. S-MA, in contrast, showed limited impairment in clinical and cognitive scores but pronounced global network failure. Our results contribute toward a better understanding of heterogeneity in AD with the detection of distinct differences in functional connectivity networks accompanied by CSF biomarker and cognitive differences in AD subtypes.

Hepatic fat is superior to BMI, visceral and pancreatic fat as a potential risk biomarker for neurodegenerative disease.

OBJECTIVES: Prior studies relating body mass index (BMI) to brain volumes suggest an overall inverse association. However, BMI might not be an ideal marker, as it disregards different fat compartments, which carry different metabolic risks. Therefore, we analyzed MR-based fat depots and their association with gray matter (GM) volumes of brain structures, which show volumetric changes in neurodegenerative diseases. METHODS: Warp-based automated brain segmentation of 3D FLAIR sequences was obtained in a population-based study cohort. Associations of temporal lobe, cingulate gyrus, and hippocampus GM volume with BMI and MR-based quantification of visceral adipose tissue (VAT), as well as hepatic and pancreatic proton density fat fraction (PDFFhepatic and PDFFpanc, respectively), were assessed by linear regression. RESULTS: In a sample of 152 women (age 56.2 ± 9.0 years) and 199 men (age 56.1 ± 9.1 years), we observed a significant inverse association of PDFFhepatic and cingulate gyrus volume (p < 0.05) as well as of PDFFhepatic and hippocampus volume (p < 0.05), when adjusting for age and sex. This inverse association was further enhanced for cingulate gyrus volume after additionally adjusting for hypertension, smoking, BMI, LDL, and total cholesterol (p < 0.01) and also alcohol (p < 0.01). No significant association was observed between PDFFhepatic and temporal lobe and between temporal lobe, cingulate gyrus, or hippocampus volume and BMI, VAT, and PDFFpanc. CONCLUSIONS: We observed a significant inverse, independent association of cingulate gyrus and hippocampus GM volume with hepatic fat, but not with other obesity measures. Increased hepatic fat could therefore serve as a marker of high-risk fat distribution. KEY POINTS: • Obesity is associated with neurodegenerative processes. • In a population-based study cohort, hepatic fat was superior to BMI and visceral and pancreatic fat as a risk biomarker for decreased brain volume of cingulate gyrus and hippocampus. • Increased hepatic fat could serve as a marker of high-risk fat distribution.

T1-MPRAGE and T2-FLAIR segmentation of cortical and subcortical brain regions-an MRI evaluation study.

PURPOSE: Development of a warp-based automated brain segmentation approach of 3D fluid-attenuated inversion recovery (FLAIR) images and comparison to 3D T1-based segmentation. METHODS: 3D FLAIR and 3D T1-weighted sequences of 30 healthy subjects (mean age 29.9 ± 8.3 years, 8 female) were acquired on the same 3T MR scanner. Warp-based segmentation was applied for volumetry of total gray matter (GM), white matter (WM), and 116 atlas regions. Segmentation results of both sequences were compared using Pearson correlation (r). RESULTS: Correlation of GM segmentation results based on FLAIR and T1 was overall good for cortical structures (mean r across all cortical structures = 0.76). Comparatively weaker results were found in the occipital lobe (r = 0.77), central region (mean r = 0.58), basal ganglia (mean r = 0.59), thalamus (r = 0.30), and cerebellum (r = 0.73). FLAIR segmentation underestimated volume of the central region compared to T1, but showed a better anatomic concordance with the occipital lobe on visual review and subcortical structures, when also compared to manual segmentation. Visual analysis of FLAIR-based WM segmentation revealed frequent misclassification of regions of high signal intensity as GM. CONCLUSION: Warp-based FLAIR segmentation yields comparable results to T1 segmentation for most cortical GM structures and may provide anatomically more congruent segmentation of subcortical GM structures. Selected cortical regions, especially the central region and total WM, seem to be underestimated on FLAIR segmentation.

Test-retest reliability of prefrontal transcranial Direct Current Stimulation (tDCS) effects on functional MRI connectivity in healthy subjects.

Transcranial Direct Current Stimulation (tDCS) of the prefrontal cortex (PFC) can be used for probing functional brain connectivity and meets general interest as novel therapeutic intervention in psychiatric and neurological disorders. Along with a more extensive use, it is important to understand the interplay between neural systems and stimulation protocols requiring basic methodological work. Here, we examined the test-retest (TRT) characteristics of tDCS-induced modulations in resting-state functional-connectivity MRI (RS fcMRI). Twenty healthy subjects received 20minutes of either active or sham tDCS of the dorsolateral PFC (2mA, anode over F3 and cathode over F4, international 10-20 system), preceded and ensued by a RS fcMRI (10minutes each). All subject underwent three tDCS sessions with one-week intervals in between. Effects of tDCS on RS fcMRI were determined at an individual as well as at a group level using both ROI-based and independent-component analyses (ICA). To evaluate the TRT reliability of individual active-tDCS and sham effects on RS fcMRI, voxel-wise intra-class correlation coefficients (ICC) of post-tDCS maps between testing sessions were calculated. For both approaches, results revealed low reliability of RS fcMRI after active tDCS (ICC(2,1) = -0.09 - 0.16). Reliability of RS fcMRI (baselines only) was low to moderate for ROI-derived (ICC(2,1) = 0.13 - 0.50) and low for ICA-derived connectivity (ICC(2,1) = 0.19 - 0.34). Thus, for ROI-based analyses, the distribution of voxel-wise ICC was shifted to lower TRT reliability after active, but not after sham tDCS, for which the distribution was similar to baseline. The intra-individual variation observed here resembles variability of tDCS effects in motor regions and may be one reason why in this study robust tDCS effects at a group level were missing. The data can be used for appropriately designing large scale studies investigating methodological issues such as sources of variability and localisation of tDCS effects.

Strong Association of Depression and Anxiety With the Presence of Back Pain While Impact of Spinal Imaging Findings is Limited: Analysis of an MRI Cohort Study.

Development of back pain is multifactorial, and it is not well understood which factors are the main drivers of the disease. We therefore applied a machine-learning approach to an existing large cohort study data set and sought to identify and rank the most important contributors to the presence of back pain amongst the documented parameters of the cohort. Data from 399 participants in the KORA-MRI (Cooperative health research in the region Augsburg-magnetic resonance imaging) (Cooperative Health Research in the Region Augsburg) study was analyzed. The data set included MRI images of the whole body, including the spine, metabolic, sociodemographic, anthropometric, and cardiovascular data. The presence of back pain was one of the documented items in this data set. Applying a machine-learning approach to this preexisting data set, we sought to identify the variables that were most strongly associated with back pain. Mediation analysis was performed to evaluate the underlying mechanisms of the identified associations. We found that depression and anxiety were the 2 most selected predictors for back pain in our model. Additionally, body mass index, spinal canal width and disc generation, medium and heavy physical work as well as cardiovascular factors were among the top 10 most selected predictors. Using mediation analysis, we found that the effects of anxiety and depression on the presence of back pain were mainly direct effects that were not mediated by spinal imaging. In summary, we found that psychological factors were the most important predictors of back pain in our cohort. This supports the notion that back pain should be treated in a personalized multidimensional framework. PERSPECTIVE: This article presents a wholistic approach to the problem of back pain. We found that depression and anxiety were the top predictors of back pain in our cohort. This strengthens the case for a multidimensional treatment approach to back pain, possibly with a special emphasis on psychological factors.

Effects of Exercise on Structural and Functional Brain Patterns in Schizophrenia-Data From a Multicenter Randomized-Controlled Study.

BACKGROUND AND HYPOTHESIS: Aerobic exercise interventions in people with schizophrenia have been demonstrated to improve clinical outcomes, but findings regarding the underlying neural mechanisms are limited and mainly focus on the hippocampal formation. Therefore, we conducted a global exploratory analysis of structural and functional neural adaptations after exercise and explored their clinical implications. STUDY DESIGN: In this randomized controlled trial, structural and functional MRI data were available for 91 patients with schizophrenia who performed either aerobic exercise on a bicycle ergometer or underwent a flexibility, strengthening, and balance training as control group. We analyzed clinical and neuroimaging data before and after 6 months of regular exercise. Bayesian linear mixed models and Bayesian logistic regressions were calculated to evaluate effects of exercise on multiple neural outcomes and their potential clinical relevance. STUDY RESULTS: Our results indicated that aerobic exercise in people with schizophrenia led to structural and functional adaptations mainly within the default-mode network, the cortico-striato-pallido-thalamo-cortical loop, and the cerebello-thalamo-cortical pathway. We further observed that volume increases in the right posterior cingulate gyrus as a central node of the default-mode network were linked to improvements in disorder severity. CONCLUSIONS: These exploratory findings suggest a positive impact of aerobic exercise on 3 cerebral networks that are involved in the pathophysiology of schizophrenia. CLINICAL TRIALS REGISTRATION: The underlying study of this manuscript was registered in the International Clinical Trials Database, ClinicalTrials.gov (NCT number: NCT03466112, https://clinicaltrials.gov/ct2/show/NCT03466112?term=NCT03466112&draw=2&rank=1) and in the German Clinical Trials Register (DRKS-ID: DRKS00009804).

Functional connectivity MRI provides an imaging correlate for chimeric antigen receptor T-cell-associated neurotoxicity.

Background: Treatment of hematological malignancies with chimeric antigen receptor modified T cells (CART) is highly efficient, but often limited by an immune effector cell-associated neurotoxicity syndrome (ICANS). As conventional MRI is often unremarkable during ICANS, we aimed to examine whether resting-state functional MRI (rsfMRI) is suitable to depict and quantify brain network alterations underlying ICANS in the individual patient. Methods: The dysconnectivity index (DCI) based on rsfMRI was longitudinally assessed in systemic lymphoma patients and 1 melanoma patient during ICANS and before or after clinical resolution of ICANS. Results: Seven lymphoma patients and 1 melanoma patient (19-77 years; 2 female) were included. DCI was significantly increased during ICANS with normalization after recovery (P = .0039). Higher ICANS grades were significantly correlated with increased DCI scores (r = 0.7807; P = .0222). DCI increase was most prominent in the inferior frontal gyrus and the frontal operculum (ie, Broca's area) and in the posterior parts of the superior temporal gyrus and the temporoparietal junction (ie, Wernicke's area) of the language-dominant hemisphere, thus reflecting the major clinical symptoms of nonfluent dysphasia and dyspraxia. Conclusions: RsfMRI-based DCI might be suitable to directly quantify the severity of ICANS in individual patients undergoing CAR T-transfusion. Besides ICANS, DCI seems a promising diagnostic tool to quantify functional brain network alterations during encephalopathies of different etiologies, in general.

Prognostic validation of a new classification system for extent of resection in glioblastoma: A report of the RANO resect group.

BACKGROUND: Terminology to describe extent of resection in glioblastoma is inconsistent across clinical trials. A surgical classification system was previously proposed based upon residual contrast-enhancing (CE) tumor. We aimed to (1) explore the prognostic utility of the classification system and (2) define how much removed non-CE tumor translates into a survival benefit. METHODS: The international RANO resect group retrospectively searched previously compiled databases from 7 neuro-oncological centers in the USA and Europe for patients with newly diagnosed glioblastoma per WHO 2021 classification. Clinical and volumetric information from pre- and postoperative MRI were collected. RESULTS: We collected 1,008 patients with newly diagnosed IDHwt glioblastoma. 744 IDHwt glioblastomas were treated with radiochemotherapy per EORTC-26981/22981 (TMZ/RT→TMZ) following surgery. Among these homogenously treated patients, lower absolute residual tumor volumes (in cm3) were favorably associated with outcome: patients with "maximal CE resection" (class 2) had superior outcome compared to patients with "submaximal CE resection" (class 3) or "biopsy" (class 4). Extensive resection of non-CE tumor (≤5 cm3 residual non-CE tumor) was associated with better survival among patients with complete CE resection, thus defining class 1 ("supramaximal CE resection"). The prognostic value of the resection classes was retained on multivariate analysis when adjusting for molecular and clinical markers. CONCLUSIONS: The proposed "RANO categories for extent of resection in glioblastoma" are highly prognostic and may serve for stratification within clinical trials. Removal of non-CE tumor beyond the CE tumor borders may translate into additional survival benefit, providing a rationale to explicitly denominate such "supramaximal CE resection."

A Residual Marker of Cognitive Reserve Is Associated with Resting-State Intrinsic Functional Connectivity Along the Alzheimer's Disease Continuum.

BACKGROUND: Cognitive reserve (CR) explains inter-individual differences in the impact of the neurodegenerative burden on cognitive functioning. A residual model was proposed to estimate CR more accurately than previous measures. However, associations between residual CR markers (CRM) and functional connectivity (FC) remain unexplored. OBJECTIVE: To explore the associations between the CRM and intrinsic network connectivity (INC) in resting-state networks along the neuropathological-continuum of Alzheimer's disease (ADN). METHODS: Three hundred eighteen participants from the DELCODE cohort were stratified using cerebrospinal fluid biomarkers according to the A(myloid-ß)/T(au)/N(eurodegeneration) classification. CRM was calculated utilizing residuals obtained from a multilinear regression model predicting cognition from markers of disease burden. Using an independent component analysis in resting-state fMRI data, we measured INC of resting-state networks, i.e., default mode network (DMN), frontoparietal network (FPN), salience network (SAL), and dorsal attention network. The associations of INC with a composite memory score and CRM and the associations of CRM with the seed-to-voxel functional connectivity of memory-related were tested in general linear models. RESULTS: CRM was positively associated with INC in the DMN in the entire cohort. The A+T+N+ group revealed an anti-correlation between the SAL and the DMN. Furthermore, CRM was positively associated with anti-correlation between memory-related regions in FPN and DMN in ADN and A+T/N+. CONCLUSION: Our results provide evidence that INC is associated with CRM in ADN defined as participants with amyloid pathology with or without cognitive symptoms, suggesting that the neural correlates of CR are mirrored in network FC in resting-state.

Differences in electric field strength between clinical and non-clinical populations induced by prefrontal tDCS: A cross-diagnostic, individual MRI-based modeling study.

INTRODUCTION: Prefrontal cortex (PFC) regions are promising targets for therapeutic applications of non-invasive brain stimulation, e.g. transcranial direct current stimulation (tDCS), which has been proposed as a novel intervention for major depressive disorder (MDD) and negative symptoms of schizophrenia (SCZ). However, the effects of tDCS vary inter-individually, and dose-response relationships have not been established. Stimulation parameters are often tested in healthy subjects and transferred to clinical populations. The current study investigates the variability of individual MRI-based electric fields (e-fields) of standard bifrontal tDCS across individual subjects and diagnoses. METHOD: The study included 74 subjects, i.e. 25 patients with MDD, 24 patients with SCZ, and 25 healthy controls (HC). Individual e-fields of a common tDCS protocol (i.e. 2 mA stimulation intensity, bifrontal anode-F3/cathode-F4 montage) were modeled by two investigators using SimNIBS (2.0.1) based on structural MRI scans. RESULT: On a whole-brain level, the average e-field strength was significantly reduced in MDD and SCZ compared to HC, but MDD and SCZ did not differ significantly. Regions of interest (ROI) analysis for PFC subregions showed reduced e-fields in Sallet areas 8B and 9 for MDD and SCZ compared to HC, whereas there was again no difference between MDD and SCZ. Within groups, we generally observed high inter-individual variability of e-field intensities at a higher percentile of voxels. CONCLUSION: MRI-based e-field modeling revealed significant differences in e-field strengths between clinical and non-clinical populations in addition to a general inter-individual variability. These findings support the notion that dose-response relationships for tDCS cannot be simply transferred from healthy to clinical cohorts and need to be individually established for clinical groups. In this respect, MRI-based e-field modeling may serve as a proxy for individualized dosing.