Unveiling functional-metabolic synergy in the healthy brain: multivariate integration of dynamic [F]FDG-PET and resting-state fMRI.

Introduction: Despite accounting for only 2% of body weight, the human brain requires significant amounts of glucose, even at rest, underscoring the importance of functional-metabolic relationships. Previous studies revealed moderate associations between resting-state fMRI functional connectivity (FC) and local metabolism via [F]FDG-PET, yet much remains to be understood, particularly regarding their coupling between functional and metabolic networks.

Methods: To this end, we employed multivariate Partial Least Squares Correlation (PLSC) to investigate the functional-metabolic relationship at both nodal and network level.

Structural-functional fingerprinting for abnormalities investigation in glioma patients.

Gliomas alter brain function and integrity, but these disruptions are often studied separately. This study utilised a novel approach that integrated functional, structural and microstructural connectivity information to investigate glioma-induced brain network changes and their clinical implications. It focused on the impact of gliomas on key brain networks, with a particular emphasis on the relationship between tumour topology and its effect on homotopic areal-level parcellation.

Biomarker treatment effects in two phase 3 trials of gantenerumab.

Introduction: We report biomarker treatment effects in the GRADUATE I and II phase 3 studies of gantenerumab in early Alzheimer's disease (AD).

Methods: Amyloid and tau positron emission tomography (PET), volumetric magnetic resonance imaging (vMRI), cerebrospinal fluid (CSF), and plasma biomarkers used to assess gantenerumab treatment related changes on neuropathology, neurodegeneration, and neuroinflammation over 116 weeks.

Results: Gantenerumab reduced amyloid PET load, CSF biomarkers of amyloid beta (Aβ)40, total tau (t-tau), phosphorylated tau 181 (p-tau181), neurogranin, S100 calcium-binding protein B (S100B), neurofilament light (NfL), alpha-synuclein (α-syn), neuronal pentraxin-2 (NPTX2), and plasma biomarkers of t-tau, p-tau181, p-tau217, and glial fibrillary acidic protein (GFAP) while increasing plasma Aβ40, Aβ42.

EMATA: a toolbox for the automatic extraction and modeling of arterial inputs for tracer kinetic analysis in [F]FDG brain studies.

Purpose: PET imaging is a pivotal tool for biomarker research aimed at personalized medicine. Leveraging the quantitative nature of PET requires knowledge of plasma radiotracer concentration. Typically, the arterial input function (AIF) is obtained through arterial cannulation, an invasive and technically demanding procedure.

Individual-level metabolic connectivity from dynamic [F]FDG PET reveals glioma-induced impairments in brain architecture and offers novel insights beyond the SUVR clinical standard.

Purpose: This study evaluates the potential of within-individual Metabolic Connectivity (wi-MC), from dynamic [F]FDG PET data, based on the Euclidean Similarity method. This approach leverages the biological information of the tracer's full temporal dynamics, enabling the direct extraction of individual metabolic connectomes. Specifically, the proposed framework, applied to glioma pathology, seeks to assess sensitivity to metabolic dysfunctions in the whole brain, while simultaneously providing further insights into the pathophysiological mechanisms regulating glioma progression.

Revealing the Spatial Pattern of Brain Hemodynamic Sensitivity to Healthy Aging through Sparse Dynamic Causal Model.

Age-related changes in the BOLD response could reflect neurovascular coupling modifications rather than simply impairments in neural functioning. In this study, we propose the use of a sparse dynamic causal model (sDCM) to decouple neuronal and vascular factors in the BOLD signal, with the aim of characterizing the whole-brain spatial pattern of hemodynamic sensitivity to healthy aging, as well as to test the role of hemodynamic features as independent predictors in an age-classification model. sDCM was applied to the resting-state functional magnetic resonance imaging data of a cohort of 126 healthy individuals in a wide age range (31 females), providing reliable estimates of the hemodynamic response function (HRF) for each subject and each region of interest.

The contribution of paramagnetic rim and cortical lesions to physical and cognitive disability at multiple sclerosis clinical onset: evaluating the power of MRI and OCT biomarkers.

Background: In multiple sclerosis (MS), imaging biomarkers play a crucial role in characterizing the disease at the time of diagnosis. MRI and optical coherence tomography (OCT) provide readily available biomarkers that may help to define the patient's clinical profile. However, the evaluation of cortical and paramagnetic rim lesions (CL, PRL), as well as retinal atrophy, is not routinely performed in clinic.

A blood-free modeling approach for the quantification of the blood-to-brain tracer exchange in TSPO PET imaging.

Introduction: Recent evidence suggests the blood-to-brain influx rate ( ) in imaging as a promising biomarker of blood-brain barrier () permeability alterations commonly associated with peripheral inflammation and heightened immune activity in the brain. However, standard compartmental modeling quantification is limited by the requirement of invasive and laborious procedures for extracting an arterial blood input function. In this study, we validate a simplified blood-free methodologic framework for estimation by fitting the early phase tracer dynamics using a single irreversible compartment model and an image-derived input function ().

The brain's "dark energy" puzzle: How strongly is glucose metabolism linked to resting-state brain activity?

Brain glucose metabolism, which can be investigated at the macroscale level with [F]FDG PET, displays significant regional variability for reasons that remain unclear. Some of the functional drivers behind this heterogeneity may be captured by resting-state functional magnetic resonance imaging (rs-fMRI). However, the full extent to which an fMRI-based description of the brain's spontaneous activity can describe local metabolism is unknown.

Controlling target brain regions by optimal selection of input nodes.

The network control theory framework holds great potential to inform neurostimulation experiments aimed at inducing desired activity states in the brain. However, the current applicability of the framework is limited by inappropriate modeling of brain dynamics, and an overly ambitious focus on whole-brain activity control. In this work, we leverage recent progress in linear modeling of brain dynamics (effective connectivity) and we exploit the concept of target controllability to focus on the control of a single region or a small subnetwork of nodes.

Trans-synaptic degeneration in the optic pathway: Exploring the role of lateral geniculate nucleus in early stages of relapsing-remitting multiple sclerosis.

Background: Optic pathway is considered an ideal model to study the interaction between inflammation and neurodegeneration in multiple sclerosis (MS).

Methods: Optical Coherence Tomography (OCT) and 3.0 T magnetic resonance imaging (MRI) were acquired in 92 relapsing remitting (RR) MS at clinical onset.

A new framework for metabolic connectivity mapping using bolus [F]FDG PET and kinetic modeling.

Metabolic connectivity (MC) has been previously proposed as the covariation of static [F]FDG PET images across participants, i.e., MC (ai-MC).

The dynamic functional connectivity fingerprint of high-grade gliomas.

Resting state fMRI has been used in many studies to investigate the impact of brain tumours on functional connectivity (FC). However, these studies have so far assumed that FC is stationary, disregarding the fact that the brain fluctuates over dynamic states. Here we utilised resting state fMRI data from 33 patients with high-grade gliomas and 33 healthy controls to examine the dynamic interplay between resting-state networks and to gain insights into the impact of brain tumours on functional dynamics.

Case report: Multiple disconnection patterns revealed by a multi-modal analysis explained behavior after a focal frontal damage.

Introduction: There is overwhelming evidence that focal lesions cause structural, metabolic, functional, and electrical disconnection of regions directly and indirectly connected with the site of injury. Unfortunately, methods to study disconnection (positron emission tomography, structural and functional magnetic resonance imaging, electroencephalography) have been applied primarily in isolation without capturing their interaction. Moreover, multi-modal imaging studies applied to focal lesions are rare.

Increased Levels of the Parkinson's Disease-Associated Gene ITPKB Correlate with Higher Expression Levels of α-Synuclein, Independent of Mutation Status.

Autosomal dominant mutations in the gene encoding α-synuclein () were the first to be linked with hereditary Parkinson's disease (PD). Duplication and triplication of has been observed in PD patients, together with mutations at the N-terminal of the protein, among which A30P and A53T influence the formation of fibrils. By overexpressing human α-synuclein in the neuronal system of , we functionally validated the ability of , an ortholog of the GWAS identified risk gene, Inositol-trisphosphate 3-kinase B (), to modulate α-synuclein toxicity in vivo.

Presurgical predictors of early cognitive outcome after brain tumor resection in glioma patients.

Gliomas are commonly characterized by neurocognitive deficits that strongly impact patients' and caregivers' quality of life. Surgical resection is the mainstay of therapy, and it can also cause cognitive impairment. An important clinical problem is whether patients who undergo surgery will show post-surgical cognitive impairment above and beyond that present before surgery.

Modeling venous plasma samples in [F] FDG PET studies: a nonlinear mixed-effects approach.

The gold-standard approach to quantifying dynamic PET images relies on using invasive measures of the arterial plasma tracer concentration. An attractive alternative is to employ an image-derived input function (IDIF), corrected for spillover effects and rescaled with venous plasma samples. However, venous samples are not always available for every participant.

Image-derived Input Function in brain [F]FDG PET data: which alternatives to the carotid siphons?

Quantification of brain [F] fluorodeoxyglucose ([F]FDG) positron emission tomography (PET) data requires an input function. A noninvasive alternative to gold-standard arterial sampling is the image-derived input function (IDIF), typically extracted from the internal carotid arteries (ICAs), which are however difficult to segment and subjected to spillover effects. In this work, we evaluated the feasibility of extracting the IDIF from two different vascular sites, i.

Variability of regional glucose metabolism and the topology of functional networks in the human brain.

The brain consumes the most energy per relative mass amongst the organs in the human body. Theoretical and empirical studies have shown that behavioral processes are relatively inexpensive metabolically, and that most energy goes to maintaining the status quo, i.e.

Assessment of structural disconnections in gliomas: comparison of indirect and direct approaches.

Gliomas are amongst the most common primary brain tumours in adults and are often associated with poor prognosis. Understanding the extent of white matter (WM) which is affected outside the tumoral lesion may be of paramount importance to explain cognitive deficits and the clinical progression of the disease. To this end, we explored both direct (i.

Widespread cortical functional disconnection in gliomas: an individual network mapping approach.

Assessment of impaired/preserved cortical regions in brain tumours is typically performed via intraoperative direct brain stimulation of eloquent areas or task-based functional MRI. One main limitation is that they overlook distal brain regions or networks that could be functionally impaired by the tumour. This study aims (i) to investigate the impact of brain tumours on the cortical synchronization of brain networks measured with resting-state functional magnetic resonance imaging (resting-state networks) both near the lesion and remotely and (ii) to test whether potential changes in resting-state networks correlate with cognitive status.

Fertility sparing surgery in sex-cord stromal tumors: oncological and reproductive outcomes.

Sex cord stromal tumors are rare neoplasms, frequently diagnosed in young women often as early-stage disease. In patients who desire to preserve fertility, when possible, unilateral salpingo-oophorectomy with peritoneal surgical staging is a safe alternative to radical treatment. In this review, we analyze the available literature on the obstetrical outcomes after fertility-sparing surgery in a total of 255 patients with sex cord stromal tumors.

Magnetic Resonance Imaging Correlates of Immune Microenvironment in Glioblastoma.

Background: Glioblastoma (GBM) is the most commonly occurring primary malignant brain tumor, and it carries a dismal prognosis. Focusing on the tumor microenvironment may provide new insights into pathogenesis, but no clinical tools are available to do this. We hypothesized that the infiltration of different leukocyte populations in the tumoral and peritumoral brain tissues may be measured by magnetic resonance imaging (MRI).

Diffusion-based microstructure models in brain tumours: Fitting in presence of a model-microstructure mismatch.

Diffusion-based biophysical models have been used in several recent works to study the microenvironment of brain tumours. While the pathophysiological interpretation of the parameters of these models remains unclear, their use as signal representations may yield useful biomarkers for monitoring the treatment and the progression of this complex and heterogeneous disease. Up to now, however, no study was devoted to assessing the mathematical stability of these approaches in cancerous brain regions.

Impaired cognitive control in patients with brain tumors.

Though the assessment of cognitive functions is proven to be a reliable prognostic indicator in patients with brain tumors, some of these functions, such as cognitive control, are still rarely investigated. The objective of this study was to examine proactive and reactive control functions in patients with focal brain tumors and to identify lesioned brain areas more at "risk" for developing impairment of these functions. To this end, a group of twenty-two patients, candidate to surgery, were tested with an AX-CPT task and a Stroop task, along with a clinical neuropsychological assessment, and their performance was compared to that of a well-matched healthy control group.