Single Brain Research Articles

Development and Evaluation of Automated Artificial Intelligence-Based Brain Tumor Response Assessment in Patients with Glioblastoma.

To develop and evaluate an automated, AI-based, volumetric brain tumor MRI response assessment algorithm on a large cohort of patients treated at a high-volume brain tumor center. We retrospectively analyzed data from 634 patients treated for glioblastoma at a single brain tumor center over a 5-year period (2017-2021). The mean age was 56 +/-13 years. 372/634 (59%) patients were male, and 262/634 (41%) patients were female. Study data consisted of 3,403 brain MRI exams and corresponding standardized, radiologist-based brain tumor response assessments (BT-RADS). An artificial intelligence (AI)-based brain tumor response assessment algorithm was developed using automated, volumetric tumor segmentation. AI-based response assessments were evaluated for agreement with radiologist-based response assessments and ability to stratify patients by overall survival. Metrics were computed to assess the agreement using BTRADS as the ground-truth, fixed-time point survival analysis was conducted to evaluate the survival stratification, and associated P-values were calculated. For all BT-RADS categories, AI-based response assessments showed moderate agreement with radiologists' response assessments (F1 = 0.587-0.755). Kaplan-Meier survival analysis revealed statistically worse overall fixed time point survival for patients assessed as image worsening equivalent to RANO progression by human alone compared to by AI alone (log-rank P=0.007). Cox proportional hazard model analysis showed a disadvantage to AI-based assessments for overall survival prediction (P=0.012). AI-based volumetric glioblastoma MRI response assessment following BT-RADS criteria yielded moderate agreement for replicating human response assessments and slightly worse stratification by overall survival. GBM＝ Glioblastoma; RANO＝ Response Assessment in Neuro-Oncology; BTRADS＝ Brain Tumor Reporting and Data System; NLP = Natural Language Processing.

Evaluation of Blood–Brain Barrier Disruption Using Low- and High-Molecular-Weight Complexes in a Single Brain Sample in a Rat Traumatic Brain Injury Model: Comparison to an Established Magnetic Resonance Imaging Technique

Traumatic brain injury (TBI), a major cause of death and disability among young people, leads to significant public health and economic challenges. Despite its frequency, treatment options remain largely unsuitable. However, examination of the blood–brain barrier (BBB) can assist with understanding the mechanisms and dynamics of brain dysfunction, which affects TBI sufferers secondarily to the injury. Here, we present a rat model of TBI focused on two standard BBB assessment markers, high- and low-molecular-weight complexes, in order to understand BBB disruption. In addition, we tested a new technique to evaluate BBB disruption on a single brain set, comparing the new technique with neuroimaging. A total of 100 Sprague–Dawley rats were separated into the following five groups: naive rats (n = 20 rats), control rats with administration (n = 20 rats), and TBI rats (n = 60 rats). Rats were assessed at different time points after the injury to measure BBB disruption using low- and high-molecular-weight complexes. Neurological severity score was evaluated at baseline and at 24 h following TBI. During the neurological exam after TBI, the rats were scanned with magnetic resonance imaging and euthanized for assessment of the BBB permeability. We found that the two markers displayed different examples of BBB disruption in the same set of brain tissues over the period of a week. Our innovative protocol for assessing BBB permeability using high- and low-molecular-weight complexes markers in a single brain set showed appropriate results. Additionally, we determined the lower limit of sensitivity, therefore demonstrating the accuracy of this method.

Modular representations emerge in neural networks trained to perform context-dependent tasks.

The brain has large-scale modular structure in the form of brain regions, which are thought to arise from constraints on connectivity and the physical geometry of the cortical sheet. In contrast, experimental and theoretical work has argued both for and against the existence of specialized sub-populations of neurons (modules) within single brain regions. By studying artificial neural networks, we show that this local modularity emerges to support context-dependent behavior, but only when the input is low-dimensional. No anatomical constraints are required. We also show when modular specialization emerges at the population level (different modules correspond to orthogonal subspaces). Modularity yields abstract representations, allows for rapid learning and generalization on novel tasks, and facilitates the rapid learning of related contexts. Non-modular representations facilitate the rapid learning of unrelated contexts. Our findings reconcile conflicting experimental results and make predictions for future experiments.

Mechanisms and Functions of the Cerebral-Cognitive Reserve in Patients with Alzheimer's Disease: A Narrative Review.

The need for scientific knowledge about aging is predicated on the demand of modern society to extend the active life of a person. To maintain intellectual longevity, it is necessary to take into account not only the pathological, but also compensatory mechanisms that arise during aging. The cerebral-cognitive reserve (CCR) influences the rate of transition from pre-phenomenological stages to the clinical stage of the disease, thereby changing the prognosis of Alzheimer's disease (AD). The aim of this work was to review meta-analyses from studies that have examined the principles and functions of the CCR in people with AD. The work included 83 scientific publications devoted to the issues of the CCR in neurodegenerative diseases such as AD. The Results and Discussion sections of this article provide reviews of the results of 12 meta-analyses published from 2012 to 2024 and selected from the PubMed and eLibrary databases using the following keywords in English and Russian: "cerebral reserve", "cognitive "reserve", and "Alzheimer's disease". The scope of the definition was not limited, since the goal here was to determine the terminological boundaries of the concepts of "cognitive reserve" and "single brain reserve". The modern understanding of AD as a biological continuum covering the preclinical, prodromal, and clinical phases of the disease makes it possible to infer that insufficiency of protective factors underlies the progression of AD. The cognitive reserve is involved in the sanogenetic protective mechanism during neurodegeneration. The cognitive reserve is a theoretical concept that reflects modern research's understanding of how the integrative functioning of the brain (cerebral) and cognitive reserves extend the period of active intellectual longevity through energy-saving mechanisms. It considers these mechanisms as central to healthy mental activity and in slowing the progression of neurodegenerative diseases. At some point, an increase in excess interneuronal activity that reflects the hypercompensatory function of the reserve would accelerate the depletion of brain structures and contribute to clinical and psychopathological manifestations of AD. The concept of the CCR puts the spotlight on the need to determine the compensatory indicators of cognitive deficit in AD, assess the architecture and volume of the reserve, and develop and follow protocols for its maintenance. It appears just as crucial to adopt measures to prevent the Reserve's depletion as early as at the preclinical stages of the disease. Elaborating protective and compensatory mechanisms that help to maintain the functional activity of the brain in conditions of neurodegeneration, that is, CCR, require further research and can form a conceptual basis for the prevention of AD, starting from the preclinical stages of the disease.

Reappraising Cladophialophora bantiana phaeohyphomycosis in France: retrospective nation-based study

Cladophialophora bantiana is one of the most virulent phaeohyphomycetes, typically causes non-angiogenic single (or sometimes multiple) cystic brain lesions, and has resulted in a mortality rate of up to 70%.Most Cbantiana cases are described either in a series of isolated reports or in very small cohorts. The aim of this retrospective nation-based study was to share the data on Cbantiana phaeohyphomycosis cases reported in France and French overseas territories over the past two decades to improve understanding of this disease. Patients with Cbantiana infection were processed through the active surveillance programme of invasive fungal infections launched by the National Reference Center for Mycoses and Antifungals, Institut Pasteur (Paris, France), and the French Surveillance Network of Invasive Fungal Infections, which involved 29hospitals from mainland France and overseas French territories. Onlyproven and probable cases of infection, according to the revised and updated consensus definitions from the European Organization for Research and Treatment of Cancer and Mycoses Study Group, were included in the study. Patients were diagnosed or confirmed, or both, using a polyphasic approach at the Institut Pasteur between 2002and2022. Patients were separated into two groups: those with CNS involvement and those with no CNS involvement. Theprimary outcome was the survival rate. A total of 23patients with a Cbantiana invasive infection were included during the study period (Jan 1, 2002, to Dec 31, 2022). The median age was 56years in the CNS involvement group and 65years in the non-CNS involvement group. Until 2021, the annual number of cases varied between zero and two, with six cases observed in 2022, the warmest year recorded in France since 1900. CNS involvement was observed in 15 (65%) patients, including three disseminated cases; skin and soft tissue involvement in seven (30%) patients and an isolated lung infection in one case. Diabetes was observed in five patients, and any immunodepression factor was observed in 14 (61%) of 23patients. When considering only patients with CNS involvement, 9-month survival appeared higher in patients who underwent exeresis or large drainage (three [75%] of four patients vs three [27%] of 11patients; p=0·24) and significantly higher in those treated for 2or more weeks with triple antifungal therapy (liposomal amphotericin Bplus posaconazole and flucytosine; seven [78%] of nine patients vs one [17%] of six patients; p=0·040). Two patients were treated with excision surgery alone (one patient with success, and the other patient lost to follow-up). This study shows that the clinical presentations and underlying medical conditions of Cbantiana infections are more diverse than previously described. It also emphasises a significant difference in mortality rate between those with and without CNS involvement. The prognosis improved when surgery was performed and triple antifungal therapy was administered. Such rare and devastating invasive fungal infections should be managed by a multidisciplinary team. Santé Publique France.

Return to work in younger patients with brain metastases who survived for 2 years or more.

The study's purpose was to analyze return to work and other long-term outcomes in younger patients with newly diagnosed brain metastases, treated before they reached legal retirement age, i.e. younger than 65 years. We included patients who survived greater than 2 years after their first treatment, regardless of approach (systemic therapy, neurosurgical resection, whole-brain or stereotactic radiotherapy). The primary endpoint was the proportion of patients who worked 2 years after their initial treatment for brain metastases. Outcomes beyond the 2-year cut-off were also abstracted from comprehensive electronic health records, throughout the follow-up period. Of 455 patients who received active therapy for brain metastases, 62 (14%) survived for > 2 years. Twenty-eight were younger than 65 years. The actuarial median survival was 81 months and the 5-year survival rate 53%. For patients alive after 5 years, the 10-year survival rate was 54%. At diagnosis, 25% of patients (7 of 28) were permanently incapacitated for work/retired. Of the remaining 21 patients, 33% did work 2 years later. However, several of these patients went on to receive disability pension afterwards. Eventually, 19% continued working in the longer run. Younger age, absence of extracranial metastases, presence of a single brain metastasis, and Karnofsky performance status 90-100 were common features of patients who worked after 2 years. Long-term survival was achieved after vastly different therapeutic approaches, regarding both upfront and sequential management. Many patients required three or more lines of brain-directed treatment. Few patients continued working in the longer run.

Research on brain functional network property analysis and recognition methods targeting brain fatigue

At present, researches on brain fatigue recognition are still in the stage of single task and simple brain region network features, while researches on high-order brain functional network features and brain region state mechanisms during fatigue in multi-task scenarios are still insufficient, making it difficult to meet the needs of fatigue recognition under complex conditions. Therefore, this study utilized functional near-infrared spectroscopy (fNIRS) technology to explore the correlation and differences in the low-order and high-order brain functional network attributes of three task induced mental fatigue, and to explore the brain regions that have a major impact on mental fatigue. Self-training algorithms were used to identify the three levels of brain fatigue. The results showed that during the fatigue development, the overall connection strength of the endothelial cell metabolic activity and neural activity frequency bands of the low-order brain functional network first decreased and then increased, while the myogenic activity and heart rate activity frequency bands showed the opposite pattern. Network topology analysis indicated that from no fatigue to mild fatigue, the clustering coefficient of endothelial cell metabolic activity and myogenic activity frequency bands significantly decreased, while the characteristic path length of myogenic activity significantly increased; when experiencing severe fatigue, the small-world attribute of the neural frequency band significantly weakened. However, each frequency band maintained its small-world attribute, reflecting the self-optimization and adaptability of the network during the fatigue process. During mild fatigue, neuronal activity bands’ node degree, cluster coefficient, and efficiency rose in high-order brain networks, while low-order networks showed no significant changes. As fatigue progressed, the myogenic activity bands of high-order network properties dominated, but neural bands gained prominence in mild fatigue, approaching the level of myogenic bands in severe fatigue, indicating that brain fatigue orchestrated a shift from myogenic to neural dominance in frequency bands. In addition, during the process of fatigue, the four network attributes of the high-order network cluster composed of low-order nodes related to the prefrontal cortex region, left anterior motor region, motor assist region, and left frontal lobe eye movement region significantly increased, indicating that these brain regions had a significant impact on brain fatigue status. The accuracy of using both high-order and low-order features to identify fatigue levels reached 88.095%, indicating that the combined network features of both high-order and low-order fNIRS signals could effectively detect multi-level mental fatigue, providing innovative ideas for fatigue warning.

Plasma biomarkers in chronic single moderate-severe traumatic brain injury.

Blood biomarkers are an emerging diagnostic and prognostic tool that reflect a range of neuropathological processes following traumatic brain injury (TBI). Their effectiveness in identifying long-term neuropathological processes after TBI is unclear. Studying biomarkers in the chronic phase is vital because elevated levels in TBI might result from distinct neuropathological mechanisms during acute and chronic phases. Here, we examine plasma biomarkers in the chronic period following TBI and their association with amyloid and tau PET, white matter microarchitecture, brain age and cognition. We recruited participants ≥40 years of age who had suffered a single moderate-severe TBI ≥10 years previously between January 2018 and March 2021. We measured plasma biomarkers using single molecule array technology [ubiquitin C-terminal hydrolase L1 (UCH-L1), neurofilament light (NfL), tau, glial fibrillary acidic protein (GFAP) and phosphorylated tau (P-tau181)]; PET tracers to measure amyloid-β (18F-NAV4694) and tau neurofibrillary tangles (18F-MK6240); MRI to assess white matter microstructure and brain age; and the Rey Auditory Verbal Learning Test to measure verbal-episodic memory. A total of 90 post-TBI participants (73% male; mean = 58.2 years) were recruited on average 22 years (range = 10-33 years) post-injury, and 32 non-TBI control participants (66% male; mean = 57.9 years) were recruited. Plasma UCH-L1 levels were 67% higher {exp(b) = 1.67, P = 0.018, adjusted P = 0.044, 95% confidence interval (CI) [10% to 155%], area under the curve = 0.616} and P-tau181 were 27% higher {exp(b) = 1.24, P = 0.011, adjusted P = 0.044, 95% CI [5% to 46%], area under the curve = 0.632} in TBI participants compared with controls. Amyloid and tau PET were not elevated in TBI participants. Higher concentrations of plasma P-tau181, UCH-L1, GFAP and NfL were significantly associated with worse white matter microstructure but not brain age in TBI participants. For TBI participants, poorer verbal-episodic memory was associated with higher concentration of P-tau181 {short delay: b = -2.17, SE = 1.06, P = 0.043, 95% CI [-4.28, -0.07]; long delay: bP-tau = -2.56, SE = 1.08, P = 0.020, 95% CI [-4.71, -0.41]}, tau {immediate memory: bTau = -6.22, SE = 2.47, P = 0.014, 95% CI [-11.14, -1.30]} and UCH-L1 {immediate memory: bUCH-L1 = -2.14, SE = 1.07, P = 0.048, 95% CI [-4.26, -0.01]}, but was not associated with functional outcome. Elevated plasma markers related to neuronal damage and accumulation of phosphorylated tau suggest the presence of ongoing neuropathology in the chronic phase following a single moderate-severe TBI. Plasma biomarkers were associated with measures of microstructural brain disruption on MRI and disordered cognition, further highlighting their utility as potential objective tools to monitor evolving neuropathology post-TBI.

Abnormal Structural–Functional Coupling and MRI Alterations of Brain Network Topology in Progressive Supranuclear Palsy

BackgroundProgressive supranuclear palsy (PSP) can cause structural and functional brain reconstruction. There is a lack of knowledge about the consistency between structural–functional (S–F) connection networks in PSP, despite growing evidence of anomalies in various single brain network parameters.PurposeTo study the changes in the structural and functional networks of PSP, network's topological properties including degree, and the consistency of S–F coupling. The relationship with clinical scales was examined including the assessment of PSP severity, and so on.Study TypeRetrospective.SubjectsA total of 51 PSP patients (70.04 ± 7.46, 25 females) and 101 healthy controls (64.58 ± 8.84, 58 females).Field Strength/Sequence3‐T, resting‐state functional MRI, diffusion tensor imaging, and T1‐weighted images.AssessmentA graph‐theoretic approach was used to evaluate structural and functional network topology metrics. We used the S–F coupling changes to explore the consistency of structural and functional networks.Statistical TestsIndependent samples t tests were employed for continuous variables, χ2 tests were used for categorical variables. For network analysis, two‐sample t tests was used and implied an false discovery rate (FDR) correction. Pearson correlation analysis was used to explore the correlations. A P‐value <0.05 was considered statistically significant.ResultsPSP showed variations within and between modules. Specifically, PSP had decreased network properties changes (t = −2.0136; t = 2.5409; t = −2.5338; t = −2.4296; t = −2.5338; t = 2.8079). PSP showed a lower coupling in the thalamus and left putamen and a higher coupling in the visual, somatomotor, dorsal attention, and ventral attention network. S–F coupling was related to the number of network connections (r = 0.32, r = 0.22) and information transmission efficiency (r = 0.55, r = 0.28). S–F coupling was related to basic academic ability (r = 0.39) and disinhibition (r = 0.49).Data ConclusionPSP may show abnormal S–F coupling and intramodular and intermodular connectome in the structural and functional networks.Level of Evidence3Technical EfficacyStage 3

Neuromodulation in Small Animal fMRI.

The integration of functional magnetic resonance imaging (fMRI) with advanced neuroscience technologies in experimental small animal models offers a unique path to interrogate the causal relationships between regional brain activity and brain-wide network measures-a goal challenging to accomplish in human subjects. This review traces the historical development of the neuromodulation techniques commonly used in rodents, such as electrical deep brain stimulation, optogenetics, and chemogenetics, and focuses on their application with fMRI. We discuss their advantageousness roles in uncovering the signaling architecture within the brain and the methodological considerations necessary when conducting these experiments. By presenting several rodent-based case studies, we aim to demonstrate the potential of the multimodal neuromodulation approach in shedding light on neurovascular coupling, the neural basis of brain network functions, and their connections to behaviors. Key findings highlight the cell-type and circuit-specific modulation of brain-wide activity patterns and their behavioral correlates. We also discuss several future directions and feature the use of mediation and moderation analytical models beyond the intuitive evoked response mapping, to better leverage the rich information available in fMRI data with neuromodulation. Using fMRI alongside neuromodulation techniques provide insights into the mesoscopic (relating to the intermediate scale between single neurons and large-scale brain networks) and macroscopic fMRI measures that correlate with specific neuronal events. This integration bridges the gap between different scales of neuroscience research, facilitating the exploration and testing of novel therapeutic strategies aimed at altering network-mediated behaviors. In conclusion, the combination of fMRI with neuromodulation techniques provides crucial insights into mesoscopic and macroscopic brain dynamics, advancing our understanding of brain function in health and disease. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 1.

Optical Transmission in Single-Layer Brain Tissues under Different Optical Source Types: Modelling and Simulation.

The human brain is a complex organ controlling daily activity. Present technique models have mostly focused on multi-layer brain tissues, which lack understanding of the propagation characteristics of various single brain tissues. To better understand the influence of different optical source types on individual brain tissues, we constructed single-layer brain models and simulated optical propagation using the Monte Carlo method. Based on the optical simulation results, sixteen optical source types had different optical energy distributions, and the distribution in cerebrospinal fluid had obvious characteristics. Five brain tissues (scalp, skull, cerebrospinal fluid, gray matter, and blood vessel) had the same set of the first three optical source types with maximum depth, while white matter had a different set of the first three optical source types with maximum depth. Each brain tissue had different optical source types with the maximum and minimum full width at half maximum. The study on single-layer brain tissues under different optical source types lays the foundation for constructing complex brain models with multiple tissue layers. It provides a theoretical reference for optimizing the selection of optical source devices for brain imaging.

Neuropathological mRNA Expression Changes after Single Mild Traumatic Brain Injury in Pigs.

Traumatic brain injury (TBI) is a public health concern, with an estimated 42 million cases globally every year. The majority of TBIs are mild TBIs, also known as concussion, and result from the application of mechanical forces on the head. Most patients make a complete recovery and mortality is rare; therefore, studies investigating cellular changes after mild TBI in a clinical setting are limited. To address this constraint, our group utilized a pig model of closed-head rotational acceleration-induced TBI, which recreated the biomechanical loading parameters associated with concussion on a large gyrencephalic brain similar to humans. While our previous research has focused on immunohistochemical characterization of neuropathology, the current study utilized transcriptomic assays to evaluate an array of TBI-induced neurodegenerative analytes. Pigs subjected to mild TBI were survived for 3 days post-injury (DPI) (n = 3), 30 DPI (n = 3), or 1 year post-injury (YPI) (n = 3) and compared to animals undergoing a sham procedure (n = 8). RNA was isolated from whole coronal sections of fixed tissue and multiplexed on a Nanostring neuropathology panel. Differential expression analysis revealed 11 differentially expressed genes at 3 DPI versus sham, including downregulation of the synaptotagmin calcium sensor gene (SYT1), upregulation of the neurofibromin gene (NF1), and upregulation of the Alzheimer's disease-associated receptor gene (SORL1). There were no differentially expressed genes at 30 DPI or 1 YPI compared to shams. Additionally, high-magnitude undirected global significance scores (GSS) were detected at 3 DPI for chromatin modification and autophagy gene sets, and at 30 DPI for cytokine gene sets, while many dysregulated gene sets were highlighted by directed GSSs out to 1 YPI. This study adds to a growing body of literature on transcriptomic changes in a clinically relevant large animal model of closed-head TBI, which highlights potential therapeutic targets following mild TBI.

3252: Control limits for single isocenter multiple brain targets SRS PSQA with a high resolution detector

3252: Control limits for single isocenter multiple brain targets SRS PSQA with a high resolution detector

Synergy of the mirror neuron system and the mentalizing system in a single brain and between brains during joint actions

Cooperative action involves the simulation of actions and their co-representation by two or more people. This requires the involvement of two complex brain systems: the mirror neuron system (MNS) and the mentalizing system (MENT), both of critical importance for successful social interaction. However, their internal organization and the potential synergy of both systems during joint actions (JA) are yet to be determined. The aim of this study was to examine the role and interaction of these two fundamental systems—MENT and MNS—during continuous interaction. To this hand, we conducted a multiple-brain connectivity analysis in the source domain during a motor cooperation task using high-density EEG dual-recordings providing relevant insights into the roles of MNS and MENT at the intra- and interbrain levels.In particular, the intra-brain analysis demonstrated the essential function of both systems during JA, as well as the crucial role played by single brain regions of both neural mechanisms during cooperative activities. Specifically, our intra-brain analysis revealed that both neural mechanisms are essential during Joint Action (JA), showing a solid connection between MNS and MENT and a central role of the single brain regions of both mechanisms during cooperative actions. Additionally, our inter-brain study revealed increased inter-subject connections involving the motor system, MENT and MNS. Thus, our findings show a mutual influence between two interacting agents, based on synchronization of MNS and MENT systems. Our results actually encourage more research into the still-largely unknown realm of inter-brain dynamics and contribute to expand the body of knowledge in social neuroscience.

An estimate of the longitudinal pace of aging from a single brain scan predicts dementia conversion, morbidity, and mortality.

To understand how aging affects functional decline and increases disease risk, it is necessary to develop accurate and reliable measures of how fast a person is aging. Epigenetic clocks measure aging but require DNA methylation data, which many studies lack. Using data from the Dunedin Study, we introduce an accurate and reliable measure for the rate of longitudinal aging derived from cross-sectional brain MRI: the Dunedin Pace of Aging Calculated from NeuroImaging or DunedinPACNI. Exporting this measure to the Alzheimer's Disease Neuroimaging Initiative and UK Biobank neuroimaging datasets revealed that faster DunedinPACNI predicted participants' cognitive impairment, accelerated brain atrophy, and conversion to diagnosed dementia. Underscoring close links between longitudinal aging of the body and brain, faster DunedinPACNI also predicted physical frailty, poor health, future chronic diseases, and mortality in older adults. Furthermore, DunedinPACNI followed the expected socioeconomic health gradient. When compared to brain age gap, an existing MRI aging biomarker, DunedinPACNI was similarly or more strongly related to clinical outcomes. DunedinPACNI is a "next generation" MRI measure that will be made publicly available to the research community to help accelerate aging research and evaluate the effectiveness of dementia prevention and anti-aging strategies.

Non-coplanar Arc-Involved Beam Arrangement With Sufficient Arc Rotations Is Suitable for Volumetric-Modulated Arc-Based Radiosurgery for Single Brain Metastasis

Non-coplanar Arc-Involved Beam Arrangement With Sufficient Arc Rotations Is Suitable for Volumetric-Modulated Arc-Based Radiosurgery for Single Brain Metastasis

Immediate effect of quadri-pulse stimulation on human brain microstructures and functions

Abstract It remains unclear whether repetitive stimulation of a single brain area immediately alters brain microstructure. Thus, we investigated the immediate changes in human brain microstructures following repetitive extrinsic excitation of the left primary motor cortex (M1) through quadri-pulse stimulation (QPS). Sixteen right-handed healthy adults underwent excitatory (QPS5) and inhibitory (QPS50) QPS. Diffusion magnetic resonance imaging (MRI) and resting-state functional MRI were conducted before and after QPS to detect microstructural and functional changes, respectively. No significant alterations in microstructural indices after QPS5 or QPS50 were observed in the cerebral cortex. The functional connectivity (FC) between the bilateral M1 was significantly decreased after QPS5, while it was not significantly modulated after QPS50. Microstructural changes exhibited no significant correlation with this FC change in any region after QPS5 or QPS50. Although no significant FC change was observed following QPS50, these results may suggest that repetitive stimulation of a single brain area can be insufficient to induce immediate microstructural alterations. This would be supported by demonstrating the lack of microstructural changes after QPS together with changes in cortical excitability of the stimulated region.

Low-level brain somatic mutations in exonic regions are collectively implicated in autism with germline mutations in autism risk genes

Low-level somatic mutations in the human brain are implicated in various neurological disorders. The contribution of low-level brain somatic mutations to autism spectrum disorder (ASD), however, remains poorly understood. Here, we performed high-depth exome sequencing with an average read depth of 559.3x in 181 cortical, cerebellar, and peripheral tissue samples to identify brain somatic single nucleotide variants (SNVs) in 24 ASD subjects and 31 controls. We detected ~2.4 brain somatic SNVs per exome per single brain region, with a variant allele frequency (VAF) as low as 0.3%. The mutational profiles, including the number, signature, and type, were not significantly different between the ASD patients and controls. Intriguingly, when considering genes with low-level brain somatic SNVs and ASD risk genes with damaging germline SNVs together, the merged set of genes carrying either somatic or germline SNVs in ASD patients was significantly involved in ASD-associated pathophysiology, including dendrite spine morphogenesis (p = 0.025), mental retardation (p = 0.012), and intrauterine growth retardation (p = 0.012). Additionally, the merged gene set showed ASD-associated spatiotemporal expression in the early and mid-fetal cortex, striatum, and thalamus (all p < 0.05). Patients with damaging mutations in the merged gene set had a greater ASD risk than did controls (odds ratio = 3.92, p = 0.025, 95% confidence interval = 1.12–14.79). The findings of this study suggest that brain somatic SNVs and germline SNVs may collectively contribute to ASD-associated pathophysiology.

Dosimetric comparison of ZAP-X, Gamma Knife, and CyberKnife stereotactic radiosurgery for single brain metastasis

PurposeTo evaluate the dosimetric characteristics of ZAP-X stereotactic radiosurgery (SRS) for single brain metastasis by comparing with two mature SRS platforms.MethodsThirteen patients with single brain metastasis treated with CyberKnife (CK) G4 were selected retrospectively. The prescription dose for the planning target volume (PTV) was 18–24 Gy for 1–3 fractions. The PTV volume ranged from 0.44 to 11.52 cc.Treatment plans of thirteen patients were replanned using the ZAP-X plan system and the Gamma Knife (GK) ICON plan system with the same prescription dose and organs at risk (OARs) constraints. The prescription dose of PTV was normalized to 70% for both ZAP-X and CK, while it was 50% for GK. The dosimetric parameters of three groups included the plan characteristics (CI, GI, GSI, beams, MUs, treatment time), PTV (D2, D95, D98, Dmin, Dmean, Coverage), brain tissue (volume of 100%-10% prescription dose irradiation V100%-V10%, Dmean) and other OARs (Dmax, Dmean),all of these were compared and evaluated. All data were read and analyzed with MIM Maestro. One-way ANOVA or a multisample Friedman rank sum test was performed, where p < 0.05 indicated significant differences.ResultsThe CI of GK was significantly lower than that of ZAP-X and CK. Regarding the mean value, ZAP-X had a lower GI and higher GSI, but there was no significant difference among the three groups. The MUs of ZAP-X were significantly lower than those of CK, and the mean value of the treatment time of ZAP-X was significantly shorter than that of CK. For PTV, the D95, D98, and target coverage of CK were higher, while the mean of Dmin of GK was significantly lower than that of CK and ZAP-X. For brain tissue, ZAP-X showed a smaller volume from V100% to V20%; the statistical results of V60% and V50% showed a difference between ZAP-X and GK, while the V40% and V30% showed a significant difference between ZAP-X and the other two groups; V10% and Dmean indicated that GK was better. Excluding the Dmax of the brainstem, right optic nerve and optic chiasm, the mean value of all other OARs was less than 1 Gy. For the brainstem, GK and ZAP-X had better protection, especially at the maximum dose.ConclusionFor the SRS treating single brain metastasis, all three treatment devices, ZAP-X system, CyberKnife G4 system, and GammaKnife system, could meet clinical treatment requirements. The newly platform ZAP-X could provide a high-quality plan equivalent to or even better than CyberKnife and Gamma Knife, with ZAP-X presenting a certain dose advantage, especially with a more conformal dose distribution and better protection for brain tissue. As the ZAP-X systems get continuous improvements and upgrades, they may become a new SRS platform for the treatment of brain metastasis.

Texture feature differentiation of glioblastoma and solitary brain metastases based on tumor and tumor-brain interface

BackgroundTexture features, derived from both the entire tumor area and the region of the tumor-to-brain interface, are crucial indicators for distinguishing tumor types and their degrees of malignancy. However, the discriminative value of texture features from both regions for identifying glioblastomas and metastatic tumors has not been thoroughly explored. The aim of this study is to develop and validate a diagnostic model that combines texture features from the entire tumor area and a 10mm tumor-to-brain interface region, in an attempt to identify more stable and effective texture features. MethodWe retrospectively collected enhanced T1-weighted imaging data from 97 patients with glioblastoma(GBM) and single brain metastasis(SBM) between 2010 and 2024. Machine learning is used to establish multiple diagnostic models for discriminating GBM and SBM based on texture features of the entire tumor and 10mm tumor-to-brain interface regions. Results underwent evaluation through 5-fold cross-validation analysis, calculating the area under the receiver operating characteristic curve (AUC) for each model. The performance of each model was compared using the Delong test, and the interpretability of the optimized model was further augmented by employing Shapley additive explanations (SHAP). ResultsThe AUCs for all pipelines in the validation dataset were compared using FeAture Explorer (FAE) software. Among the models established by Relief and autoencoder (AE), the AUC was highest using the “one-standard error” rule. ’10mm_glrlm_GrayLevelNonUniformity’ was considered the most stable and predictive feature. The best models in the training set, test set, and validation set were not the same. In the test set, the Relief19AE model had the highest AUC of 0.869 and an accuracy of 0.857. ConclusionThe texture feature model that combines the overall tumor and the tumor-brain interface is beneficial for distinguishing glioblastoma from solitary metastatic tumors, and the texture features of the tumor interface exhibit higher heterogeneity.