Frontiers in neuroimaging最新文献

Objectives: This study aimed to describe a case of transient neurologic deficits triggered by euglycemic diabetic ketoacidosis (DKA) in brain tissue at risk due to heavy cerebral amyloid angiopathy (CAA) microbleed burden, while demonstrating the rare imaging finding of reversible T2 fluid-attenuated inversion recovery (FLAIR) subcortical hypointensity.

Methods: We present the clinical course, laboratory findings, and neuroimaging features of an 81-year-old man who presented with acute altered mental status and transient focal neurologic deficits.

Results: The patient presented with encephalopathy, headache, left hemianopsia, left sensory neglect, and mild left upper extremity weakness. Laboratory examination showed euglycemic DKA. Brain MRI revealed findings consistent with probable CAA according to Boston Criteria 2.0, including innumerable cortical microbleeds predominantly in the right temporo-parieto-occipital lobes, with superimposed diffuse T2 FLAIR-weighted hypointensity in this region.

Discussion: Reversible T2 FLAIR hypointensity has been described in hyperglycemia-associated syndromes. In this case, T2 FLAIR hypointensity likely represented metabolic dysregulation that triggered cortical dysfunction within brain regions at risk due to heavy CAA-related microbleed burden. We speculate that a common pathway for the development of the patient's transient deficits resulted from cortical spreading depolarization (CSD), which has been associated with both CAA and hyperglycemia.

Introduction: High-dose Methotrexate (HDMTX) can induce neurotoxicity, yet its impact on brain metabolism remains underexplored. This study aimed to assess short- and long-term brain metabolic changes post-HDMTX on 18F-FDG PET/MRI relative to baseline (pre-HDMTX) scans.

Methods: In this IRB approved, retrospective study, we included 19 children and young adults (3 females and 16 males; age 17.9 ± 4.3 years), with lymphoma (n = 13) or osteosarcoma (n = 6). All patients underwent 18F-FDG PET/MRI before (baseline) and after HDMTX (>1000 mg/m²). Post-treatment scans were conducted ≤3 months (short-term group, n = 11) or >3 months (long-term group, n = 8) after completion of HDMTX and were compared with baseline scans. SUVmean and SUVmax of the whole brain cortex and six subregions were measured with PMOD software. A generalized linear regression model was used to evaluate post-pre-HDMTX SUV values differences in whole cortex with p < 0.05 and for with of different brain subregions, with p < 0.008 after Bonferroni correction.

Results: In the short-term group, compared with baseline, both SUVmean (pre-HDMTX vs. post-HDMTX: 5.06 ± 1.62 vs. 6.31 ± 1.71, p < 0.001) and SUVmax (9.16 ± 3.33 vs. 13.25 ± 3.35, p < 0.001) significantly increased in the whole cortex following HDMTX. In contrast, the long-term group showed no significant changes in SUVmean (6.31 ± 1.71 vs. 6.30 ± 1.54, p = 0.1) or SUVmax (12.01 ± 3.53 vs. 11.58 ± 3.07, p = 0.1) after HDMTX.

Discussion: ¹⁸F-FDG PET/MRI revealed short-term increases in brain metabolism post-HDMTX compared with baseline, possibly reflecting neuroinflammation. Long-term follow up scans revealed normalization of brain metabolism or decreased brain metabolism compared to baseline, the latter possibly indicating neurotoxicity.

Depression is a highly disabling mental disorder imposing a substantial burden on global public health. Repetitive Transcranial Magnetic Stimulation (rTMS), as a non-invasive physical treatment modality, demonstrates favorable efficacy and safety in treating depression. However, significant inter-individual variability in treatment response exists, with the reliability of target localization being a key factor influencing efficacy. Traditional non-neuronavigated localization methods (e.g., 5-cm rule, Beam F3 method), while operationally convenient, suffer from limited reliability due to failure to account for individual variations in brain anatomy (e.g., cortical folding) and functional connectivity patterns. In recent years, driven by advances in magnetic resonance imaging (MRI) technology and individualized treatment paradigms, neuronavigated localization methods based on clinical symptom subtypes and patient-specific brain structural/functional connectivity profiles have significantly enhanced localization reliability and personalization, offering novel approaches to overcome efficacy variability. This review systematically summarizes the mechanisms of action and standard treatment protocols of rTMS for depression, with a primary focus on research advances in target localization methodologies. It encompasses the principles, clinical applications, efficacy comparisons, and optimized integration of both non-neuronavigated and neuronavigated techniques across different populations (adolescents, elderly) and symptom subtypes. By critically analyzing current research achievements and challenges, this review aims to provide clinicians with theoretical foundations and practical references for optimizing rTMS treatment protocols, enhancing response rates, and advancing individualized neuronavigated protocols.

Magnetoencephalography (MEG) captures neural activity with high temporal and spatial resolution, but it typically discards other biopotentials, such as cardiac signals, as noise. Here, we demonstrate the feasibility of extracting cardiac signals from MEG recordings using a novel algorithm to compute heart rate variability (HRV), a key autonomic biomarker. Using the Brainstorm MEG auditory dataset and the Open MEG Archive resting-state sample dataset, we developed an approach that isolates MEG-derived electrocardiogram (M-ECG) using either independent component analysis or MEG reference sensors. This algorithm identifies physiologically valid R-peaks, removes outliers, and corrects aberrant RR intervals to enable accurate HRV computation. We evaluated HRV derived from M-ECG against HRV derived from simultaneously recorded electrocardiogram (ECG) using time-domain and frequency-domain measures, along with non-parametric statistical tests and similarity metrics. Results revealed strong temporal and spectral agreement between M-ECG and simultaneously recorded ECG signals, including alignment across HRV bands and minimal bias in RR intervals. These findings highlight the potential of M-ECG for non-invasively assessing autonomic function using existing MEG data. Incorporating HRV into MEG studies could advance our understanding of brain-heart interactions and provide new diagnostic and prognostic insights, particularly in neurological disorders involving autonomic dysregulation.

Purpose: Compressed-sensing (CS) methods can decrease the acquisition time for T₁-weighted (T₁w) structural MRI images to 1-2 min. Rapid acquisitions reduce participant burden, reduce the risk of motion artifacts, and allow for repeat scans to be acquired within a session. This study investigated the tradeoffs of sparse sampling and CS image reconstruction for brain morphometric applications.

Methods: Magnetization-Prepared Rapid Gradient Echo (MPRAGE) images were acquired at 1.0 mm spatial resolution. The effects of the acceleration factor (x2 to x8) and regularization factor were examined. Subcortical volumes and regional cortical thickness estimates of brain structure were obtained for all T₁w images. Within-sequence agreement was evaluated by comparing estimates obtained using the same protocol in the same imaging session. Between-sequence agreement was evaluated by comparing estimates from a fully sampled MPRAGE protocol to the novel CS-accelerated MPRAGE protocols within the same session.

Results: Higher acceleration lowered the SNR in white matter but not in gray matter. SNR could be further manipulated by the regularization parameter. Within-sequence agreement was comparable across all protocols. In fact, the spread in estimates from the 58-s CSx8 protocol was similar to those from the fully sampled protocol. Similarly, high agreement was found between estimates from the fully sampled and under-sampled protocols for all acceleration levels up to eight. Modifying the regularization factor had a quantifiable effect on image smoothness, however it had minimal impact on the agreement of morphometric estimates.

Conclusion: Accelerated CS imaging protocols show comparable performance to traditional longer protocols for morphometric brain estimates.

Background: Neuroimaging plays a key role in the diagnostic workup of patients with idiopathic normal pressure hydrocephalus (iNPH). A flow void in the aqueduct - indicating increased cerebrospinal fluid (CSF) velocity - is a common, but unspecific finding. Aim of this study was to investigate CSF-flow characteristics in iNPH patients before and after spinal tap test (STT) using novel, real-time phase-contrast magnetic resonance imaging (RT-PC MRI).

Methods: We included consecutive patients with clinical signs of iNPH being electively admitted for diagnostic workup, including neurological examination, conventional MRI and STT. RT-PC MRI and clinical examination were performed before and within 24 h after STT. CSF-flow volumes were determined at five regions in the inner and outer CSF spaces.

Results: Fifteen patients with suspected iNPH and five age-matched healthy controls (HC) were included. Baseline RT-PC MRI revealed elevated CSF-flow volumes in the inner ventricular system of iNPH patients compared to healthy controls, being detectable predominantly in the third ventricle (iNPH vs. HC: 15.93 ± 7.01 mL vs. 6.58 ± 2.99 mL, p = 0.020). There was a positive correlation between the Evans Index and CSF-flow in the third ventricle (r = 0.586, p = 0.017), cerebral aqueduct (r = 0.639, p = 0.006) and the fourth ventricle (r = 0.649, p = 0.007). There was no statistically significant change of CSF-flow volumes before and after STT in the iNPH-group.

Conclusion: RT-PC MRI provides a promising, non-invasive approach for evaluating CSF-flow in iNPH. Baseline CSF-flow volumes were elevated in the inner ventricular system, particularly in the third ventricle, and correlated with ventricular enlargement, suggesting that increased CSF-flow may reflect disease progression rather than therapeutic response. However, in contrast to clinical tests, the lack of change of CSF-flow after STT limits its utility for patient selection for ventriculo-peritoneal-shunt implantation.

Introduction: Functional brain connectivity measures extracted from resting-state functional magnetic resonance imaging (fMRI) scans have generated wide interest as potential noninvasive biomarkers. In this context, performing global signal regression (GSR) as a preprocessing step remains controversial. Specifically, while it has been shown that a considerable fraction of global signal variations is associated with physiological and motion sources, GSR may also result in removing neural activity.

Methods: Here, we address this question by examining the fundamental sources of resting global signal fluctuations using simultaneous electroencephalography (EEG)-fMRI data combined with cardiac and breathing recordings.

Results: Our results suggest that systemic physiological fluctuations account for a significantly larger fraction of global signal variability compared to electrophysiological fluctuations. Furthermore, we show that GSR reduces artifactual connectivity due to heart rate and breathing fluctuations, but preserves connectivity patterns associated with electrophysiological activity within the alpha and beta frequency ranges.

Discussion: Overall, these results provide evidence that the neural component of resting-state fMRI-based connectivity is preserved after the global signal is regressed out.

Objective: We used resting-state functional magnetic resonance imaging to identify changes in brain functional connectivity (FC) associated with Organizational Skills Training (OST).

Method: In an open, waitlist-controlled, randomized clinical trial (NCT04108273), 51 children aged 8-12 years with deficient organizational skills were assigned to immediate tele-health OST treatment (twice weekly, 10 weeks) or waitlist. We obtained Children's Organizational Skills Scale-Parent version (COSS-P) scores and examined FC changes between dorsal anterior cingulate cortex (dACC) and preregistered subcortical anterior ventral striatum (aVS) regions-of-interest.

Results: OST produced significantly lower COSS-P scores compared to waitlist, with a large effect size (Cohen's f² = 0.77). Initial imaging analyses revealed a significant increase (instead of the predicted decrease) in FC between dACC and the aVS component of the default mode network in the immediate treatment group (ΔFC = 0.092 ± 0.041, 95% CI [0.009, 0.175], p < 0.05). Analyses were then performed with two additional analytic pipelines, neither of which detected any significant effects.

Conclusion: Although improvements in organizational deficits were associated with increased FC within a circuit linking dACC and the default mode network region of the aVS in one analysis, the direction was the opposite of predicted and results did not replicate. Thus, we highlight the tentativeness of our findings; we have de-identified all the data and made it available for investigators to examine and to combine with other datasets in mega- and meta-analyses. Future studies should also include alternative control conditions and larger samples.

Clinical trial registration: https://clinicaltrials.gov/study/NCT04108273?cond=NCT04108273&rank=1.

Randomized controlled trials (RCTs) are essential for evaluating treatment efficacy, typically comparing active interventions to control conditions. In situations where blinding is impractical-such as in psychological therapies or physical rehabilitation-waitlist controls are often used to account for natural symptom progression and test-retest variability. This study examines the biases introduced by post-hoc analyses under conditions of low statistical power, particularly in neuroimaging research. Through large-scale simulations involving 100 million datasets with varying sample sizes, treatment effects, and test-retest variability, the study demonstrates that the common practice of conducting post-hoc tests only on brain regions showing significant interaction effects can substantially increase the false positive rate in the control condition. These findings underscore the relevance of Berkson's paradox in interpreting unexpected control group outcomes and caution against overinterpreting such results. A complementary neuroimaging simulation reinforces these conclusions, emphasizing the need for critical scrutiny when evaluating significant effects in control groups. Overall, this work challenges conventional post-hoc testing strategies and advocates for a more nuanced and statistically informed interpretation of results, especially in studies with limited power.

Background: The characteristic brain function and network activity patterns in adolescents with first-episode depression (FED) remain systematically underexplored. This study aims to investigate abnormalities in cerebral function and networks in adolescent FED patients through analyses of the amplitude of low-frequency fluctuations (ALFF), fractional amplitude of low-frequency fluctuations (fALFF), and independent component analysis (ICA).

Materials and methods: A cohort of 36 adolescents with first-episode depression (patient group, PT) and 34 healthy controls (HC group) were enrolled. Depressive symptoms were assessed using the Hamilton Depression Rating Scale (HAMD) and Children's Depression Inventory (CDI). All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI). Neuronal activity and functional network alterations were analyzed via ALFF, fALFF, and ICA methodologies.

Results: Compared to the HC group, the PT group exhibited increased ALFF values in the left fusiform gyrus (Fusiform_L), left middle temporal gyrus (Temporal_Mid_L), right middle occipital gyrus (Occipital_Mid_R), right middle temporal gyrus (Temporal_Mid_R), right calcarine cortex (Calcarine_R), right angular gyrus (Angular_R), and left calcarine cortex (Calcarine_L). Elevated fALFF values were observed in the right calcarine cortex (Calcarine_R) and left superior temporal gyrus (Temporal_Sup_L), while decreased fALFF values were detected in the left superior temporal pole (Temporal_Pole_Sup_L), right medial superior frontal gyrus (Frontal_Sup_Medial_R), left superior frontal gyrus (Frontal_Sup_L), and left precuneus (Precuneus_L). Connectivity differences within the visual network (VIN) were identified between groups, with a peak difference in the right inferior temporal gyrus (Temporal_Inf_R), where the PT group demonstrated hyperconnectivity.

Conclusion: In summary, neurofunctional abnormalities in adolescent FED patients involve the temporal lobe emotion-processing network, prefrontal executive control system, and default mode network (DMN). Aberrant low-frequency activity in the temporal pole and superior frontal gyrus may exacerbate emotion dysregulation, whereas hyperactivation of the precuneus and visual cortex could potentiate negative self-referential processing. Notably, the right middle occipital gyrus may represent a distinctive biomarker of adolescent depression. These findings provide novel insights into the early neural mechanisms underlying adolescent depression and suggest that non-invasive neuromodulation techniques targeting specific brain regions (e.g., transcranial magnetic stimulation, TMS) hold therapeutic potential.