Alzheimer's disease genetic pathways impact cerebrospinal fluid biomarkers and imaging endophenotypes in non-demented individuals.

INTRODUCTION: Unraveling how Alzheimer's disease (AD) genetic risk is related to neuropathological heterogeneity, and whether this occurs through specific biological pathways, is a key step toward precision medicine. METHODS: We computed pathway-specific genetic risk scores (GRSs) in non-demented individuals and investigated how AD risk variants predict cerebrospinal fluid (CSF) and imaging biomarkers reflecting AD pathology, cardiovascular, white matter integrity, and brain connectivity. RESULTS: CSF amyloidbeta and phosphorylated tau were related to most GRSs. Inflammatory pathways were associated with cerebrovascular disease, whereas quantitative measures of white matter lesion and microstructure integrity were predicted by clearance and migration pathways. Functional connectivity alterations were related to genetic variants involved in signal transduction and synaptic communication. DISCUSSION: This study reveals distinct genetic risk profiles in association with specific pathophysiological aspects in predementia stages of AD, unraveling the biological substrates of the heterogeneity of AD-associated endophenotypes and promoting a step forward in disease understanding and development of personalized therapies. HIGHLIGHTS: Polygenic risk for Alzheimer's disease encompasses six biological pathways that can be quantified with pathway-specific genetic risk scores, and differentially relate to cerebrospinal fluid and imaging biomarkers. Inflammatory pathways are mostly related to cerebrovascular burden. White matter health is associated with pathways of clearance and membrane integrity, whereas functional connectivity measures are related to signal transduction and synaptic communication pathways.

Sharing brain imaging data in the Open Science era: how and why?

The sharing of human neuroimaging data has great potential to accelerate the development of imaging biomarkers in neurological and psychiatric disorders; however, major obstacles remain in terms of how and why to share data in the Open Science context. In this Health Policy by the European Cluster for Imaging Biomarkers, we outline the current main opportunities and challenges based on the results of an online survey disseminated among senior scientists in the field. Although the scientific community fully recognises the importance of data sharing, technical, legal, and motivational aspects often prevent active adoption. Therefore, we provide practical advice on how to overcome the technical barriers. We also call for a harmonised application of the General Data Protection Regulation across EU countries. Finally, we suggest the development of a system that makes data count by recognising the generation and sharing of data as a highly valuable contribution to the community.

Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure.

OBJECTIVE: Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. METHODS: Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid ß1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS: AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. INTERPRETATION: Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.

The pursuit for markers of disease progression in behavioral variant frontotemporal dementia: a scoping review to optimize outcome measures for clinical trials.

Behavioral variant frontotemporal dementia (bvFTD) is a neurodegenerative disorder characterized by diverse and prominent changes in behavior and personality. One of the greatest challenges in bvFTD is to capture, measure and predict its disease progression, due to clinical, pathological and genetic heterogeneity. Availability of reliable outcome measures is pivotal for future clinical trials and disease monitoring. Detection of change should be objective, clinically meaningful and easily assessed, preferably associated with a biological process. The purpose of this scoping review is to examine the status of longitudinal studies in bvFTD, evaluate current assessment tools and propose potential progression markers. A systematic literature search (in PubMed and Embase.com) was performed. Literature on disease trajectories and longitudinal validity of frequently-used measures was organized in five domains: global functioning, behavior, (social) cognition, neuroimaging and fluid biomarkers. Evaluating current longitudinal data, we propose an adaptive battery, combining a set of sensitive clinical, neuroimaging and fluid markers, adjusted for genetic and sporadic variants, for adequate detection of disease progression in bvFTD.

Recommendations for quantitative cerebral perfusion MRI using multi-timepoint arterial spin labeling: Acquisition, quantification, and clinical applications.

Accurate assessment of cerebral perfusion is vital for understanding the hemodynamic processes involved in various neurological disorders and guiding clinical decision-making. This guidelines article provides a comprehensive overview of quantitative perfusion imaging of the brain using multi-timepoint arterial spin labeling (ASL), along with recommendations for its acquisition and quantification. A major benefit of acquiring ASL data with multiple label durations and/or post-labeling delays (PLDs) is being able to account for the effect of variable arterial transit time (ATT) on quantitative perfusion values and additionally visualize the spatial pattern of ATT itself, providing valuable clinical insights. Although multi-timepoint data can be acquired in the same scan time as single-PLD data with comparable perfusion measurement precision, its acquisition and postprocessing presents challenges beyond single-PLD ASL, impeding widespread adoption. Building upon the 2015 ASL consensus article, this work highlights the protocol distinctions specific to multi-timepoint ASL and provides robust recommendations for acquiring high-quality data. Additionally, we propose an extended quantification model based on the 2015 consensus model and discuss relevant postprocessing options to enhance the analysis of multi-timepoint ASL data. Furthermore, we review the potential clinical applications where multi-timepoint ASL is expected to offer significant benefits. This article is part of a series published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group, aiming to guide and inspire the advancement and utilization of ASL beyond the scope of the 2015 consensus article.

Developing blood-brain barrier arterial spin labelling as a non-invasive early biomarker of Alzheimer's disease (DEBBIE-AD): a prospective observational multicohort study protocol.

INTRODUCTION: Loss of blood-brain barrier (BBB) integrity is hypothesised to be one of the earliest microvascular signs of Alzheimer's disease (AD). Existing BBB integrity imaging methods involve contrast agents or ionising radiation, and pose limitations in terms of cost and logistics. Arterial spin labelling (ASL) perfusion MRI has been recently adapted to map the BBB permeability non-invasively. The DEveloping BBB-ASL as a non-Invasive Early biomarker (DEBBIE) consortium aims to develop this modified ASL-MRI technique for patient-specific and robust BBB permeability assessments. This article outlines the study design of the DEBBIE cohorts focused on investigating the potential of BBB-ASL as an early biomarker for AD (DEBBIE-AD). METHODS AND ANALYSIS: DEBBIE-AD consists of a multicohort study enrolling participants with subjective cognitive decline, mild cognitive impairment and AD, as well as age-matched healthy controls, from 13 cohorts. The precision and accuracy of BBB-ASL will be evaluated in healthy participants. The clinical value of BBB-ASL will be evaluated by comparing results with both established and novel AD biomarkers. The DEBBIE-AD study aims to provide evidence of the ability of BBB-ASL to measure BBB permeability and demonstrate its utility in AD and AD-related pathologies. ETHICS AND DISSEMINATION: Ethics approval was obtained for 10 cohorts, and is pending for 3 cohorts. The results of the main trial and each of the secondary endpoints will be submitted for publication in a peer-reviewed journal.

Reproducibility of arterial spin labeling cerebral blood flow image processing: A report of the ISMRM open science initiative for perfusion imaging (OSIPI) and the ASL MRI challenge.

PURPOSE: Arterial spin labeling (ASL) is a widely used contrast-free MRI method for assessing cerebral blood flow (CBF). Despite the generally adopted ASL acquisition guidelines, there is still wide variability in ASL analysis. We explored this variability through the ISMRM-OSIPI ASL-MRI Challenge, aiming to establish best practices for more reproducible ASL analysis. METHODS: Eight teams analyzed the challenge data, which included a high-resolution T1-weighted anatomical image and 10 pseudo-continuous ASL datasets simulated using a digital reference object to generate ground-truth CBF values in normal and pathological states. We compared the accuracy of CBF quantification from each team's analysis to the ground truth across all voxels and within predefined brain regions. Reproducibility of CBF across analysis pipelines was assessed using the intra-class correlation coefficient (ICC), limits of agreement (LOA), and replicability of generating similar CBF estimates from different processing approaches. RESULTS: Absolute errors in CBF estimates compared to ground-truth synthetic data ranged from 18.36 to 48.12 mL/100 g/min. Realistic motion incorporated into three datasets produced the largest absolute error and variability between teams, with the least agreement (ICC and LOA) with ground-truth results. Fifty percent of the submissions were replicated, and one produced three times larger CBF errors (46.59 mL/100 g/min) compared to submitted results. CONCLUSIONS: Variability in CBF measurements, influenced by differences in image processing, especially to compensate for motion, highlights the significance of standardizing ASL analysis workflows. We provide a recommendation for ASL processing based on top-performing approaches as a step toward ASL standardization.

Treatment Response Prediction in Major Depressive Disorder Using Multimodal MRI and Clinical Data: Secondary Analysis of a Randomized Clinical Trial.

OBJECTIVE: Response to antidepressant treatment in major depressive disorder varies substantially between individuals, which lengthens the process of finding effective treatment. The authors sought to determine whether a multimodal machine learning approach could predict early sertraline response in patients with major depressive disorder. They assessed the predictive contribution of MR neuroimaging and clinical assessments at baseline and after 1 week of treatment. METHODS: This was a preregistered secondary analysis of data from the Establishing Moderators and Biosignatures of Antidepressant Response in Clinical Care (EMBARC) study, a multisite double-blind, placebo-controlled randomized clinical trial that included 296 adult outpatients with unmedicated recurrent or chronic major depressive disorder. MR neuroimaging and clinical data were collected before and after 1 week of treatment. Performance in predicting response and remission, collected after 8 weeks, was quantified using balanced accuracy (bAcc) and area under the receiver operating characteristic curve (AUROC) scores. RESULTS: A total of 229 patients were included in the analyses (mean age, 38 years [SD=13]; 66% female). Internal cross-validation performance in predicting response to sertraline (bAcc=68% [SD=10], AUROC=0.73 [SD=0.03]) was significantly better than chance. External cross-validation on data from placebo nonresponders (bAcc=62%, AUROC=0.66) and placebo nonresponders who were switched to sertraline (bAcc=65%, AUROC=0.68) resulted in differences that suggest specificity for sertraline treatment compared with placebo treatment. Finally, multimodal models outperformed unimodal models. CONCLUSIONS: The study results confirm that early sertraline treatment response can be predicted; that the models are sertraline specific compared with placebo; that prediction benefits from integrating multimodal MRI data with clinical data; and that perfusion imaging contributes most to these predictions. Using this approach, a lean and effective protocol could individualize sertraline treatment planning to improve psychiatric care.

Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy?

Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.

Improving advanced intraoperative MRI methods during pediatric neurosurgery.

Advanced intraoperative MR images (ioMRI) acquired during the resection of pediatric brain tumors could offer additional physiological information to preserve healthy tissue. With this work, we aimed to develop a protocol for ioMRI with increased sensitivity for arterial spin labeling (ASL) and diffusion MRI (dMRI), optimized for patient positioning regularly used in the pediatric neurosurgery setting. For ethical reasons, ASL images were acquired in healthy adult subjects that were imaged in the prone and supine position. After this, the ASL cerebral blood flow (CBF) was quantified and compared between both positions. To evaluate the impact of the RF coils setups on image quality, we compared different setups (two vs. four RF coils) by looking at T1-weighted (T1w) signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR), as well as undertaking a qualitative evaluation of T1w, T2w, ASL, and dMR images. Mean ASL CBF did not differ between the surgical prone and supine positions in any of the investigated regions of interest or the whole brain. T1w SNR (gray matter: p = 0.016, 34% increase; white matter: p = 0.016, 32% increase) and CNR were higher (p = 0.016) in the four versus two RF coils setups (18.0 ± 1.8 vs. 13.9 ± 1.8). Qualitative evaluation of T1w, T2w, ASL, and dMR images resulted in acceptable to good image quality and did not differ statistically significantly between setups. Only the nonweighted diffusion image maps and corticospinal tract reconstructions yielded higher image quality and reduced susceptibility artifacts with four RF coils. Advanced ioMRI metrics were more precise with four RF coils as the standard deviation decreased. Taken together, we have investigated the practical use of advanced ioMRI during pediatric neurosurgery. We conclude that ASL CBF quantification in the surgical prone position is valid and that ASL and dMRI acquisition with two RF coils can be performed adequately for clinical use. With four versus two RF coils, the SNR of the images increases, and the sensitivity to artifacts reduces.

Long-Term Brain Structure and Cognition Following Bariatric Surgery.

Importance: Weight loss induced by bariatric surgery (BS) is associated with improved cognition and changed brain structure; however, previous studies on the association have used small cohorts and short follow-up periods, making it difficult to determine long-term neurological outcomes associated with BS. Objective: To investigate long-term associations of weight loss after BS with cognition and brain structure and perfusion. Design, Setting, and Participants: This cohort study included participants from the Bariatric Surgery Rijnstate and Radboudumc Neuroimaging and Cognition in Obesity study. Data from participants with severe obesity (body mass index [BMI; calculated as weight in kilograms divided by height in meters squared] >40, or BMI >35 with comorbidities) eligible for Roux-en-Y gastric bypass and aged 35 to 55 years were enrolled from a hospital specialized in BS (Rijnstate Hospital, Arnhem, the Netherlands). Participants were recruited between September 2018 and December 2020 with follow-up till March 2023. Data were collected before BS and at 6 and 24 months after BS. Data were analyzed from March to November 2023. Exposure: Roux-en-Y gastric bypass. Main Outcomes and Measures: Primary outcomes included body weight, BMI, waist circumference, blood pressure, medication use, cognitive performance (20% change index of compound z-score), brain volumes, cortical thickness, cerebral blood flow (CBF), and spatial coefficient of variation (sCOV). Secondary outcomes include cytokines, adipokines, depressive symptoms (assessed using the Beck Depression Inventory), and physical activity (assessed using the Baecke Questionnaire). Results: A total of 133 participants (mean [SD] age, 46.8 [5.7] years; 112 [84.2%] female) were included. Global cognition was at least 20% higher in 52 participants (42.9%) at 24 months after BS. Compared with baseline, at 24 months, inflammatory markers were lower (mean [SD] high-sensitivity C-reactive protein: 4.77 [5.80] µg/mL vs 0.80 [1.09] µg/mL; P < .001), fewer patients used antihypertensives (48 patients [36.1%] vs 22 patients [16.7%]), and patients had lower depressive symptoms (median [IQR] BDI score: 9.0 [5.0-13.0] vs 3.0 [1.0-6.0]; P < .001) and greater physical activity (mean [SD] Baecke score: 7.64 [1.29] vs 8.19 [1.35]; P < .001). After BS, brain structure and perfusion were lower in most brain regions, while hippocampal and white matter volume remained stable. CBF and sCOV did not change in nucleus accumbens and parietal cortex. The temporal cortex showed a greater thickness (mean [SD] thickness: 2.724 [0.101] mm vs 2.761 [0.007] mm; P = .007) and lower sCOV (median [IQR] sCOV: 4.41% [3.83%-5.18%] vs 3.97% [3.71%-4.59%]; P = .02) after BS. Conclusions and Relevance: These findings suggest that BS was associated with health benefits 2 years after surgery. BS was associated with improved cognition and general health and changed blood vessel efficiency and cortical thickness of the temporal cortex. These results may improve treatment options for patients with obesity and dementia.

A systematic review of (semi-)automatic quality control of T1-weighted MRI scans.

PURPOSE: Artifacts in magnetic resonance imaging (MRI) scans degrade image quality and thus negatively affect the outcome measures of clinical and research scanning. Considering the time-consuming and subjective nature of visual quality control (QC), multiple (semi-)automatic QC algorithms have been developed. This systematic review presents an overview of the available (semi-)automatic QC algorithms and software packages designed for raw, structural T1-weighted (T1w) MRI datasets. The objective of this review was to identify the differences among these algorithms in terms of their features of interest, performance, and benchmarks. METHODS: We queried PubMed, EMBASE (Ovid), and Web of Science databases on the fifth of January 2023, and cross-checked reference lists of retrieved papers. Bias assessment was performed using PROBAST (Prediction model Risk Of Bias ASsessment Tool). RESULTS: A total of 18 distinct algorithms were identified, demonstrating significant variations in methods, features, datasets, and benchmarks. The algorithms were categorized into rule-based, classical machine learning-based, and deep learning-based approaches. Numerous unique features were defined, which can be roughly divided into features capturing entropy, contrast, and normative measures. CONCLUSION: Due to dataset-specific optimization, it is challenging to draw broad conclusions about comparative performance. Additionally, large variations exist in the used datasets and benchmarks, further hindering direct algorithm comparison. The findings emphasize the need for standardization and comparative studies for advancing QC in MR imaging. Efforts should focus on identifying a dataset-independent measure as well as algorithm-independent methods for assessing the relative performance of different approaches.

ASL lexicon and reporting recommendations: A consensus report from the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI).

The 2015 consensus statement published by the International Society for Magnetic Resonance in Medicine (ISMRM) Perfusion Study Group and the European Cooperation in Science and Technology ( COST) Action ASL in Dementia aimed to encourage the implementation of robust arterial spin labeling (ASL) perfusion MRI for clinical applications and promote consistency across scanner types, sites, and studies. Subsequently, the recommended 3D pseudo-continuous ASL sequence has been implemented by most major MRI manufacturers. However, ASL remains a rapidly and widely developing field, leading inevitably to further divergence of the technique and its associated terminology, which could cause confusion and hamper research reproducibility. On behalf of the ISMRM Perfusion Study Group, and as part of the ISMRM Open Science Initiative for Perfusion Imaging (OSIPI), the ASL Lexicon Task Force has been working on the development of an ASL Lexicon and Reporting Recommendations for perfusion imaging and analysis, aiming to (1) develop standardized, consensus nomenclature and terminology for the broad range of ASL imaging techniques and parameters, as well as for the physiological constants required for quantitative analysis; and (2) provide a community-endorsed recommendation of the imaging parameters that we encourage authors to include when describing ASL methods in scientific reports/papers. In this paper, the sequences and parameters in (pseudo-)continuous ASL, pulsed ASL, velocity-selective ASL, and multi-timepoint ASL for brain perfusion imaging are included. However, the content of the lexicon is not intended to be limited to these techniques, and this paper provides the foundation for a growing online inventory that will be extended by the community as further methods and improvements are developed and established.

Effect of Physical Exercise on MRI-Assessed Brain Perfusion in Chemotherapy-Treated Breast Cancer Patients: A Randomized Controlled Trial.

BACKGROUND: Exercise is a promising intervention to alleviate cognitive problems in breast cancer patients, but studies on mechanisms underlying these effects are lacking. PURPOSE: Investigating whether an exercise intervention can affect cerebral blood flow (CBF) in cognitively impaired breast cancer patients and to determine if CBF changes relate to memory function. STUDY TYPE: Prospective. POPULATION: A total of 181 chemotherapy-treated stage I-III breast cancer patients with cognitive problems and relatively low physical activity levels (≤150 minutes moderate to vigorous physical activity per week), divided into an exercise (N = 91) or control group (N = 90). FIELD STRENGTH/SEQUENCE: Two-dimensional echo planar pseudo-continuous arterial spin labeling CBF sequence at 3 T. ASSESSMENT: The 6-month long intervention consisted of (supervised) aerobic and strength training, 4 × 1 hour/week. Measurements at baseline (2-4 years post-diagnosis) and after 6 months included gray matter CBF in the whole brain, hippocampus, anterior cingulate cortex, and posterior cingulate cortex. Physical fitness and memory function were also assessed. Subgroup analyses were performed in patients with high fatigue levels at baseline. STATISTICAL TESTS: Multiple regression analyses with a two-sided alpha of 0.05 for all analyses. RESULTS: There was a significant improvement in physical fitness (VO2peak in mL/minute/kg) in the intervention group (N = 53) compared to controls (N = 51, ß = 1.47 mL/minute/kg, 95% CI: 0.44-2.50). However, no intervention effects on CBF were found (eg, whole brain: P = 0.565). Highly fatigued patients showed larger but insignificant treatment effects on CBF (eg, whole brain: P = 0.098). Additionally, irrespective of group, a change in physical fitness was positively associated with changes in CBF (eg, whole brain: ß = 0.75, 95% CI: 0.07-1.43). There was no significant relation between CBF changes and changes in memory performance. DATA CONCLUSION: The exercise intervention did not affect CBF of cognitively affected breast cancer patients. A change in physical fitness was associated with changes in CBF, but changes in CBF were not associated with memory functioning. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 5.

ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): ASL pipeline inventory.

PURPOSE: To create an inventory of image processing pipelines of arterial spin labeling (ASL) and list their main features, and to evaluate the capability, flexibility, and ease of use of publicly available pipelines to guide novice ASL users in selecting their optimal pipeline. METHODS: Developers self-assessed their pipelines using a questionnaire developed by the Task Force 1.1 of the ISMRM Open Science Initiative for Perfusion Imaging. Additionally, each publicly available pipeline was evaluated by two independent testers with basic ASL experience using a scoring system created for this purpose. RESULTS: The developers of 21 pipelines filled the questionnaire. Most pipelines are free for noncommercial use (n = 18) and work with the standard NIfTI (Neuroimaging Informatics Technology Initiative) data format (n = 15). All pipelines can process standard 3D single postlabeling delay pseudo-continuous ASL images and primarily differ in their support of advanced sequences and features. The publicly available pipelines (n = 9) were included in the independent testing, all of them being free for noncommercial use. The pipelines, in general, provided a trade-off between ease of use and flexibility for configuring advanced processing options. CONCLUSION: Although most ASL pipelines can process the common ASL data types, only some (namely, ASLPrep, ASLtbx, BASIL/Quantiphyse, ExploreASL, and MRICloud) are well-documented, publicly available, support multiple ASL types, have a user-friendly interface, and can provide a useful starting point for ASL processing. The choice of an optimal pipeline should be driven by specific data to be processed and user experience, and can be guided by the information provided in this ASL inventory.

Advanced intraoperative MRI in pediatric brain tumor surgery.

Introduction: In the pediatric brain tumor surgery setting, intraoperative MRI (ioMRI) provides "real-time" imaging, allowing for evaluation of the extent of resection and detection of complications. The use of advanced MRI sequences could potentially provide additional physiological information that may aid in the preservation of healthy brain regions. This review aims to determine the added value of advanced imaging in ioMRI for pediatric brain tumor surgery compared to conventional imaging. Methods: Our systematic literature search identified relevant articles on PubMed using keywords associated with pediatrics, ioMRI, and brain tumors. The literature search was extended using the snowball technique to gather more information on advanced MRI techniques, their technical background, their use in adult ioMRI, and their use in routine pediatric brain tumor care. Results: The available literature was sparse and demonstrated that advanced sequences were used to reconstruct fibers to prevent damage to important structures, provide information on relative cerebral blood flow or abnormal metabolites, or to indicate the onset of hemorrhage or ischemic infarcts. The explorative literature search revealed developments within each advanced MRI field, such as multi-shell diffusion MRI, arterial spin labeling, and amide-proton transfer-weighted imaging, that have been studied in adult ioMRI but have not yet been applied in pediatrics. These techniques could have the potential to provide more accurate fiber tractography, information on intraoperative cerebral perfusion, and to match gadolinium-based T1w images without using a contrast agent. Conclusion: The potential added value of advanced MRI in the intraoperative setting for pediatric brain tumors is to prevent damage to important structures, to provide additional physiological or metabolic information, or to indicate the onset of postoperative changes. Current developments within various advanced ioMRI sequences are promising with regard to providing in-depth tissue information.

Eigenvector centrality dynamics are related to Alzheimer's disease pathological changes in non-demented individuals.

Amyloid-ß accumulation starts in highly connected brain regions and is associated with functional connectivity alterations in the early stages of Alzheimer's disease. This regional vulnerability is related to the high neuronal activity and strong fluctuations typical of these regions. Recently, dynamic functional connectivity was introduced to investigate changes in functional network organization over time. High dynamic functional connectivity variations indicate increased regional flexibility to participate in multiple subnetworks, promoting functional integration. Currently, only a limited number of studies have explored the temporal dynamics of functional connectivity in the pre-dementia stages of Alzheimer's disease. We study the associations between abnormal cerebrospinal fluid amyloid and both static and dynamic properties of functional hubs, using eigenvector centrality, and their relationship with cognitive performance, in 701 non-demented participants from the European Prevention of Alzheimer's Dementia cohort. Voxel-wise eigenvector centrality was computed for the whole functional magnetic resonance imaging time series (static), and within a sliding window (dynamic). Differences in static eigenvector centrality between amyloid positive (A+) and negative (A-) participants and amyloid-tau groups were found in a general linear model. Dynamic eigenvector centrality standard deviation and range were compared between groups within clusters of significant static eigenvector centrality differences, and within 10 canonical resting-state networks. The effect of the interaction between amyloid status and cognitive performance on dynamic eigenvector centrality variability was also evaluated with linear models. Models were corrected for age, sex, and education level. Lower static centrality was found in A+ participants in posterior brain areas including a parietal and an occipital cluster; higher static centrality was found in a medio-frontal cluster. Lower eigenvector centrality variability (standard deviation) occurred in A+ participants in the frontal cluster. The default mode network and the dorsal visual networks of A+ participants had lower dynamic eigenvector centrality variability. Centrality variability in the default mode network and dorsal visual networks were associated with cognitive performance in the A- and A+ groups, with lower variability being observed in A+ participants with good cognitive scores. Our results support the role and timing of eigenvector centrality alterations in very early stages of Alzheimer's disease and show that centrality variability over time adds relevant information on the dynamic patterns that cause static eigenvector centrality alterations. We propose that dynamic eigenvector centrality is an early biomarker of the interplay between early Alzheimer's disease pathology and cognitive decline.

Genetic, vascular and amyloid components of cerebral blood flow in a preclinical population.

Aging-related cognitive decline can be accelerated by a combination of genetic factors, cardiovascular and cerebrovascular dysfunction, and amyloid-ß burden. Whereas cerebral blood flow (CBF) has been studied as a potential early biomarker of cognitive decline, its normal variability in healthy elderly is less known. In this study, we investigated the contribution of genetic, vascular, and amyloid-ß components of CBF in a cognitively unimpaired (CU) population of monozygotic older twins. We included 134 participants who underwent arterial spin labeling (ASL) MRI and [18F]flutemetamol amyloid-PET imaging at baseline and after a four-year follow-up. Generalized estimating equations were used to investigate the associations of amyloid burden and white matter hyperintensities with CBF. We showed that, in CU individuals, CBF: 1) has a genetic component, as within-pair similarities in CBF values were moderate and significant (ICC > 0.40); 2) is negatively associated with cerebrovascular damage; and 3) is positively associated with the interaction between cardiovascular risk scores and early amyloid-ß burden, which may reflect a vascular compensatory response of CBF to early amyloid-ß accumulation. These findings encourage future studies to account for multiple interactions with CBF in disease trajectory analyses.

Imaging blood-brain barrier dysfunction: A state-of-the-art review from a clinical perspective.

The blood-brain barrier (BBB) consists of specialized cells that tightly regulate the in- and outflow of molecules from the blood to brain parenchyma, protecting the brain's microenvironment. If one of the BBB components starts to fail, its dysfunction can lead to a cascade of neuroinflammatory events leading to neuronal dysfunction and degeneration. Preliminary imaging findings suggest that BBB dysfunction could serve as an early diagnostic and prognostic biomarker for a number of neurological diseases. This review aims to provide clinicians with an overview of the emerging field of BBB imaging in humans by answering three key questions: (1. Disease) In which diseases could BBB imaging be useful? (2. Device) What are currently available imaging methods for evaluating BBB integrity? And (3. Distribution) what is the potential of BBB imaging in different environments, particularly in resource limited settings? We conclude that further advances are needed, such as the validation, standardization and implementation of readily available, low-cost and non-contrast BBB imaging techniques, for BBB imaging to be a useful clinical biomarker in both resource-limited and well-resourced settings.