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PubMed2026

Transcranial Alternating Current Stimulation at 40 Hz Improves Social Functioning in Children With Autism Spectrum Disorder: A Randomized Clinical Trial.

BACKGROUND: Autism spectrum disorder (ASD) lacks rapid and effective interventions for its core social difficulties. The right temporoparietal junction (rTPJ), a critical hub for social cognition, together with gamma band abnormalities implicated in ASD, provides a promising neuromodulation target. METHODS: In this randomized, double-blind, sham-controlled trial, 47 children with ASD (39 male; mean [SD] age = 8.79 [2.71] years) were assigned to receive either 21 sessions of 40-Hz high-definition transcranial alternating current stimulation (tACS) targeting the rTPJ (3 sessions/day for 7 days) or sham stimulation, with assessments conducted at baseline, postintervention (week 1), and a 3-week follow-up (week 4). The primary outcome was change in Ohio State University Autism Rating Scale-DSM-5 (OARS-5) total scores. Secondary outcomes included the Aberrant Behavior Checklist-Second Edition, Social Responsiveness Scale-Second Edition, and Short Sensory Profile. Eye-tracking metrics during Frith-Happé animations were exploratory measures of theory of mind (ToM)-related social cognitive processing. RESULTS: The active group demonstrated significant improvements in OARS-5 total scores at week 1 (mean difference = -1.13, 95% CI [-1.78 to -0.47], p < .001) and week 4 (mean difference = -1.47, 95% CI [-2.20 to -0.74], p < .001). Improvements in selected behavioral and sensory domains were observed. Average fixation duration during ToM animations showed a significant group × time interaction. No serious adverse events occurred. CONCLUSIONS: These findings suggest that 40-Hz tACS targeting the rTPJ may be associated with rapid improvements in ASD symptom severity, particularly social functioning, in children with ASD, while being well tolerated. Clinical significance requires further evaluation.

Humans↗

PubMed2026

Dissociable neural mechanisms of cognitive enhancement through transcranial stimulation and behavioral training.

BACKGROUND: Transcranial direct current stimulation (tDCS) and adaptive working memory (WM) training are promising cognitive enhancement approaches; however, their neural mechanisms and potential synergies remain poorly understood. OBJECTIVE: We directly compared how tDCS and WM training modulate neural oscillations during WM performance and examined whether combining both interventions produces additive effects. METHODS: We randomized 112 healthy adults into four groups: control (sham tDCS + non-adaptive 1-back), tDCS-only (active tDCS + non-adaptive 1-back), training-only (sham tDCS + adaptive n-back training), or combined (active tDCS + adaptive training). Participants underwent five daily intervention sessions. We recorded high-density EEG during transfer n-back tasks at baseline, post-intervention, and one-week follow-up. RESULTS: All active interventions improved WM performance relative to the control group, with the combined group showing the largest gains (n-back accuracy: +15.6% vs. + 10.1% tDCS-only, +9.7% training-only, +0.7% control; all p < 0.001). Critically, tDCS selectively increased gamma-band (30-50 Hz) power in the frontal and parietal regions (cluster p = 0.018, d > 1.0), whereas WM training enhanced frontal theta-band (4-8 Hz) power and theta-gamma phase-amplitude coupling (both cluster p < 0.012, d > 0.85). The combined group exhibited both neural signatures. Brain-behavior correlations revealed dissociable relationships: gamma increases predicted n-back accuracy improvements (r = 0.61, p < 0.001), whereas theta enhancements correlated with operation span gains (r = 0.58, p = 0.002). CONCLUSIONS: tDCS and WM training enhance cognition through distinct yet complementary neural mechanisms: tDCS via gamma-mediated cortical excitability and WM training via theta-mediated cognitive control. These findings provide neurophysiological evidence for multimodal enhancement strategies that target parallel pathways within WM networks.

Humans↗

PubMed2026

Disentangling oscillatory and aperiodic neural activity in autism: A spectral parameterization analysis of neurofeedback intervention.

BACKGROUND: Autism Spectrum Disorder (ASD) is characterized by atypical neural oscillations and heterogeneous alterations in excitation/inhibition (E/I) balance, the directionality of which varies across individuals, neural circuits, and developmental stages. While Alpha-band neurofeedback (NFB) is a promising intervention, its underlying neurophysiological mechanisms remain unclear, partly due to the conflation of periodic and aperiodic signals in traditional EEG analysis. METHODS: This randomized controlled trial recruited 40 children with ASD, assigned to either an experimental group (Alpha-training NFB) or a no-feedback group. Resting-state EEG and behavioral assessments (SRS, ABC) were collected pre- and post-intervention. We employed spectral parameterization to decompose neural activity into aperiodic (1/f slope, offset) and periodic (periodic alpha power, center frequency) components. RESULTS: NFB training yielded significant behavioral improvements in social cognition and relating skills. Physiologically, the experimental group exhibited a significant steepening of the aperiodic slope (increased exponent), reflecting a reduction in neural noise and potential optimization of inhibitory modulation. Furthermore, we observed enhanced periodic alpha power and an acceleration of the alpha center frequency (ACF), indicative of improved neural efficiency and maturation. These physiological shifts in frontal and occipital regions were significantly correlated with improvements in behavioral scores. CONCLUSION: Alpha-training NFB was associated with improvements in caregiver-rated behavioral scores and modulated spectral features of resting-state EEG in children with ASD. These findings validate the utility of spectral parameterization markers in evaluating neuromodulatory interventions.

Humans↗

PubMed2026

Oxygen-controlled gamma-irradiation and annealing enable terminal processing of collagen-based biomaterials.

Gamma irradiation is a widely adopted method for terminal sterilization of medical devices; however, its application to collagen-based extracellular matrix (ECM) materials remains limited due to radiation-induced degradation of structural integrity and mechanical performance. Here, we present an engineered terminal-processing strategy that combines oxygen controlled gamma irradiation (25-30 kGy) with post-irradiation dry-heat annealing to preserve ECM functionality while achieving effective sterilization. By modulating oxygen availability during irradiation, this approach alters radical reaction pathways, suppresses oxygen-mediated oxidative degradation, and generates a metastable radical-containing intermediate, which is subsequently converted into a structurally stabilized collagen network through thermal annealing. As a result, the treated matrices preserved ECM integrity and recovered clinically relevant mechanical properties. Furthermore, the process achieved cumulative viral reductions exceeding 6 log10 across a representative panel including enveloped and non-enveloped DNA and RNA viruses, demonstrating compatibility with sterility assurance and viral safety requirements for biologically derived medical devices. Notably, preliminary observations indicate that mechanical integrity can be partially preserved even at elevated irradiation doses up to 50 kGy, suggesting potential applicability to sterilization validation frameworks requiring higher assurance levels. Overall, this work establishes a mechanistically grounded terminal-processing paradigm that enables control of radical fate, decouples sterilization efficacy from material degradation, and integrates sterilization, viral safety, and functional preservation into a unified and scalable framework for collagen-based biomaterials. This concept repositions gamma-irradiation from a purely degradative process to a controllable tool for tuning collagen structure and performance.

Gamma Rays↗

PubMed2026

Effect of intraoperative 40-hz gamma-frequency auditory stimulation on postoperative delirium in older adults undergoing major surgery: a randomized clinical trial protocol.

INTRODUCTION: Postoperative delirium (POD) is a common and clinically significant complication among older adults undergoing major surgery under general anesthesia. Gamma-frequency (40-Hz) auditory stimulation has demonstrated potential neuroprotective and cognition-enhancing effects, suggesting a plausible role in perioperative delirium prevention. However, direct clinical evidence supporting intraoperative 40-Hz auditory stimulation in reducing POD remains limited, warranting rigorous evaluation in a randomized trial. PATIENTS AND METHODS: This prospective, parallel-group, randomized controlled trial will enroll 550 older adults scheduled for major noncardiac, nonneurosurgical surgery under general anesthesia. Participants will be randomized in a 1:1 ratio to either the active stimulation group, receiving intraoperative 40-Hz gamma-frequency auditory stimulation delivered via headphones for 2 h following successful anesthesia induction, or the sham stimulation group, wearing headphones without active auditory output. The primary outcome is the incidence of POD on postoperative day 1 though 3, assessed using the Confusion Assessment Method (CAM) or the CAM for the ICU (CAM-ICU). Secondary outcomes include POD severity, sleep quality, pain scores, analgesic consumption, the incidence of postoperative nausea and vomiting (PONV), rescue antiemetic use, duration of post-anesthesia care unit (PACU) stay, length of hospital stay, quality of postoperative recovery, incidence of perioperative adverse events; postoperative morbidity, health-related quality of life, and all-cause 30-day mortality. DISCUSSION: This trial will determine whether intraoperative 40-Hz gamma-frequency auditory stimulation reduces the incidence of POD among older adults undergoing major surgery under general anesthesia. If efficacious, this noninvasive intervention could constitute a feasible perioperative strategy to mitigate delirium risk and enhance postoperative recovery. CLINICAL TRIAL REGISTRATION: Chinese Clinical Trial Registry (ChiCTR2500115156).

Humans↗

PubMed2026

Bacteroides cellulosilyticus-derived 2-hydroxyphenylacetic acid rectifies hepatic lipid homeostasis in MASLD by targeting the PPARγ-CD36 axis.

The gut microbiota plays an important role in the occurrence and development of metabolic dysfunction-associated steatotic liver disease (MASLD), but the specific molecular mechanisms involved have not been fully elucidated. In this study, human cohort studies were performed to identify that the relative abundance of Bacteroides cellulosilyticus (B. cellulosilyticus) was significantly decreased in patients with MASLD. Through the integration of metagenomic and metabolomic analyses, it was confirmed that B. cellulosilyticus and its metabolite 2-hydroxyphenylacetic acid (2HPAA) are key factors regulating the occurrence and development of MASLD. Single-cell sequencing and lipidomic analyses revealed that 2HPAA can enter the liver through the enterohepatic circulation to exert regulatory effects. Specifically, 2HPAA inhibits the peroxisome proliferator-activated receptor γ (PPARγ) signaling pathway, thereby suppressing the expression of the fatty acid transporter CD36. Meanwhile, 2HPAA regulates lipid metabolism in hepatocytes by significantly enhancing palmitate conversion efficiency and inhibiting CD36 palmitoylation. This dual regulatory effect on CD36 expression and palmitoylation can reduce lipid accumulation in hepatocytes and ultimately alleviate MASLD progression. These findings reveal the mechanism by which B. cellulosilyticus and 2HPAA alleviate MASLD by targeting the PPARγ-CD36 pathway. This work provides a new perspective for the study of gut microbiota-host interactions in regulating liver diseases.

PPAR gamma↗

PubMed2026

Natural products alleviate exercise-induced fatigue by modulating gut microbiota: a systematic review.

BACKGROUND: Exercise-induced fatigue critically impairs athletic performance and training quality. The gut microbiota, as a key regulator of the "gut-muscle axis," has emerged as a promising anti-fatigue target. Natural products - owing to their diverse sources, structural complexity, and favorable safety profiles - have attracted growing research interest. However, a systematic synthesis comparing their anti-fatigue effects via gut microbiota modulation across different sources is lacking. SCOPE AND APPROACH: We systematically searched PubMed, Web of Science, the Cochrane Library, and CNKI for original studies that administered natural products and concurrently assessed gut microbiota changes and anti-fatigue outcomes. Twenty-six studies (25 animal experiments and 1 human trial) were included and categorized into seven groups by source and chemical characteristics. A descriptive systematic review was conducted to identify common mechanisms and source-specific differentiations. KEY FINDINGS AND CONCLUSIONS: The enrichment of short-chain fatty acid (SCFA)-producing bacteria and the activation of the SCFA-AMPK/PGC-1α axis were shared core events across all product categories. However, source-dependent mechanistic divergences emerged: polysaccharides acted primarily as fermentable substrates with an optimal dose window; polyphenols and saponins exerted dual modulation on both microbiota and host signaling pathways; compound extracts achieved systemic synergy through functional complementation; marine- and animal-derived products exhibited unique targeting profiles and rapid action. Intestinal barrier maintenance and brain-gut axis regulation further extended the anti-fatigue repertoire. Collectively, natural products possess a solid mechanistic basis for alleviating exercise-induced fatigue via gut microbiota remodeling. The differentiated characteristics of these methods in targeting precision and pathway engagement provide a theoretical foundation for designing precision intervention strategies tailored to specific fatigue contexts.

Humans↗

PubMed2026

The global potential of freshwater microbes for plastic degradation.

Plastic pollution is becoming increasingly severe on a global scale, and the potential for biodegradation as a treatment method that is environmentally friendly merits greater attention. A significant number of genes that associated the degradation of plastic (PDAGs) have been identified, however, the distribution of these genes among microorganisms in global inland waters remains to be elucidated. A global-scale meta-analysis was conducted, incorporating approximately 1000 metagenome datasets of inland waters across seven continents. A total of 13,109 metagenome-assembled genomes (MAGs) were obtained by means of metagenomics binning, and 22,621 PDAGs were identified from these. Among these recognized PDAGs, phenylacetaldehyde dehydrogenase (PAD) was the most dominant (n = 16,664), followed by catalase (n = 5931). The predominant hosts for PAD and catalase were identified as Gamma-proteobacteria and Bacteroidia, respectively. The largest number of both PAD and catalase was found in MAGs from North America, while the average gene number in single MAG was highest in MAGs from Oceania. In accordance with the prediction of traits, PDAG-carrying MAGs from Europe demonstrated the fastest growth rate and the lowest optimal growth rate. Furthermore, 25 styrene monooxygenase (StyA) enzymes were identified, which were found to cluster into two distinct groups hosted by Alpha-proteobacteria and Gamma-proteobacteria, respectively. Moreover, 11 MAGs were observed to possess the complete pathway of polystyrene degradation. These results explored the potential of inland water microorganisms as a biological resource for plastic degradation and provided valuable microbial reference information that can be used to develop biological treatment technologies for mitigating plastics.

Plastics↗

PubMed2026

Beyond species trees: pervasive gene flow limits phylogenomic resolution in the diversification of Juniperus from the Qinghai-Tibet Plateau.

Understanding how lineages diversify despite persistent ancestral polymorphism and recurrent gene flow remains a central challenge in evolutionary biology. Juniperus distributed across the Qinghai-Tibet Plateau provide an ideal system for addressing this question because repeated geological uplift and climatic oscillations have likely promoted cycles of lineage divergence, range shifts, and secondary contact. Here, we combined approximately 1.08 million genome-wide SNPs from 164 individuals representing thirteen Juniperus lineages with phylogenomic datasets comprising 3,381 nuclear single-copy genes and nearly complete plastomes. We detected extensive phylogenomic discordance and cytonuclear incongruence across genomic datasets. Topology weighting, coalescent simulations, quartet-based tests, and analyses of gene flow and reticulation collectively support the interpretation that these patterns were shaped by the combined effects of prolonged incomplete lineage sorting and gene flow during lineage diversification. Ecological niche analyses further provide a spatial and climatic context in which environmentally similar lineages may have had greater opportunities for secondary contact during historical range shifts. Collectively, our results reveal that the evolutionary history of Qinghai-Tibet Plateau Juniperus is characterized by reticulate diversification rather than strictly bifurcating evolution, and demonstrate how genome-wide discordance can provide biological insights into the evolutionary processes underlying lineage diversification.

Gene Flow↗

PubMed2026

Targeting cortico-striatal-amygdalar networks via theta-band frontoparietal synchronization in opioid use disorder: a randomized tACS-fMRI Trial.

Theta-band oscillation is integral to fronto-parietal connectivity in the executive control network and its top-down regulation on subcortical areas. External frontoparietal synchronization using theta-frequency transcranial alternating current (tACS) is a technology to potentially engage this network. In this pre-registered, triple-blind, sham-controlled trial (NCT03907644), we tested this intervention targeting the right frontoparietal network in people with opioid use disorder (OUD) to measure network engagement and behavioral outcomes. Sixty male participants with OUD were randomized to receive 20 min of active or sham 6 Hz tACS (HD electrodes over F4 and P4). Structural, resting-state, task-based fMRI drug cue reactivity, and repeated cue-induced craving assessments were collected immediately before and after stimulation. Pre-registered outcome measures were analyzed using time × group interaction models to examine (1) modulation of drug cue-related brain activity, (2) changes in craving, (3) alterations in functional connectivity, and (4) relationship between electric field, neural responses, and craving behavior. (1) A significant Time × Group interaction revealed decreased post-stimulation opioid cue-related activity in the active group relative to sham, involving key nodes in reward processing (ventral striatum, amygdala and ventral tegmental area) (FWE corrected α = 0.05) (2) subjective craving did not differ significantly between groups (3) Group by time generalized psychophysiological interaction analyses showed increased right frontoparietal network engagement (β = 2.63, p= 0.0308) following stimulation, and increased top-down inhibitory regulation of frontoparietal network on right ventral striatum (β = 1.99, p= 0.037) and left medial amygdala (β = 1.97, p= 0.039) (4) Electric field strength in the right frontal/parietal node predicted frontoparietal network engagement in the active group (r = 0.43, p= 0.02). Together, these findings demonstrate that theta-band frontoparietal tACS can modulate activity and task-dependent coupling within cortical-subcortical circuits in OUD, supporting network-targeted neuromodulation as a potential intervention for addiction.

Humans↗

PubMed2026

Does high fructose consumption trigger microglia activation and neuroinflammation? A systematic review.

This systematic review evaluated the effects of fructose intake on neuroinflammatory markers in rodent models. The search terms Fructose AND neuroinflammation OR Neurodegeneration OR chemokines OR interleukins OR microglia OR behaviour OR memory OR cognition were used in Google Scholar, Scopus and Web of Science. Thirteen animal studies investigating fructose-induced neuroinflammation that matched the eligibility criteria were included in the study. Across the studies, 16 inflammatory markers were identified and significantly altered following exposure to fructose. The findings consistently demonstrated elevated expression of pro-inflammatory cytokines, TNF-α, IL-6, and IL-1β, following fructose administration. Fructose consumption also dysregulated MCP-1, fractalkine, and CX3CR1 levels, thereby promoting inflammatory signalling and microglial activation. Furthermore, fructose exposure significantly increased IBA-1 and CD11b, indicating sustained neuroimmune activation. Alterations in important inflammatory pathways involving TLR4, NLRP3, NF-κB, MyD88, iNOS, and cyclooxygenases (COX-1 and COX-2) were also observed. In contrast, expression of the anti-inflammatory regulator peroxisome proliferator-activated receptor gamma (PPARγ) was reduced after fructose treatment. Overall, the findings suggest that chronic fructose consumption induces neuroinflammation through multiple inflammatory and immune-related mechanisms in the brain. These effects appear to be dose- and duration-dependent and may contribute significantly to neurodegeneration and cognitive impairment.

Microglia↗

PubMed2026

PPRC1 is a prognostic biomarker and key regulator of mitochondrial oxidative phosphorylation in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) remains an incurable haematological malignancy, underscoring the need for novel prognostic biomarkers and therapeutic targets. This study aimed to investigate the clinical and biological significance of peroxisome proliferator-activated receptor gamma coactivator-related protein 1 (PPRC1) in MM. METHODS: Expression and clinical data were obtained from public databases and an independent local cohort. Kaplan-Meier and Cox regression analyses were performed to evaluate prognostic value. Differential expression analysis, pathway enrichment analysis and single-cell RNA-seq data analysis were used to explore biological functions. PPRC1 was silenced in MM cell lines using siRNA to assess its effects on cell survival and oxidative phosphorylation. RESULTS: PPRC1 was significantly upregulated in MM and was associated with advanced disease stage and poor overall survival. Multivariate Cox analysis identified PPRC1 as an independent prognostic factor. A nomogram incorporating PPRC1 and revised-ISS improved survival prediction. Functional analyses revealed that PPRC1 was positively correlated with oxidative phosphorylation and oncogenic signalling pathways. A potential connection between PPRC1 expression and immune cell infiltration was observed. PPRC1 knockdown inhibited cell proliferation, induced cell cycle arrest and apoptosis and impaired oxidative phosphorylation in MM. CONCLUSIONS: PPRC1 acts as a prognostic biomarker and metabolic regulator in MM by sustaining mitochondrial oxidative phosphorylation. These findings highlight PPRC1 as a potential therapeutic target in MM.

Humans↗

PubMed2026

Cognitive-metabolic relationship in temporal lobe epilepsy: A systematic review.

OBJECTIVE: To summarize the current literature on neurometabolic dysfunction identified through brain imaging and its cognitive correlates in temporal lobe epilepsy (TLE). BACKGROUND: Cognitive decline contributes to chronic disability in TLE. The pathophysiology of cognitive decline in TLE is poorly understood, limiting therapeutic advances. Characterizing metabolic changes in patients with TLE and cognitive impairment may identify biomarkers and inform new treatment strategies. DESIGN/METHODS: We conducted a systematic review of five major databases, gathering studies published through December 2024, in accordance with PRISMA guidelines. We included all observational studies describing associations between metabolic imaging findings and cognitive measures in TLE. RESULTS: Of 1449 reports, 38 met the inclusion criteria, encompassing 1161 patients with TLE aged 5-66 years. Twenty-two studies applied fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) to assess interictal brain glucose metabolism. Two studies utilized PET with other tracers to assess more specific metabolic aspects. Fourteen studies used proton magnetic resonance spectroscopy (1H-MRS) to quantify local concentrations of brain metabolites. Impairment of verbal memory was consistently associated with left temporal lobe metabolite changes. Non-memory cognitive impairments correlated with changes in glucose metabolism, N-acetylaspartate, and gamma-aminobutyrate in both temporal and extratemporal areas. CONCLUSION: 18F-FDG PET remains the most widely used imaging modality to assess cognitive-metabolic correlates in TLE, while other PET tracers and 1H-MRS are potentially underexplored. Verbal memory impairment correlates robustly with left temporal dysmetabolism. Cognitive impairment in TLE is multifaceted and correlates with measurable changes in metabolism in both temporal and extratemporal regions. While our synthesis was restricted by some methodological limitations, these neurometabolic signatures may hold promise as potential biomarkers for identifying risk of cognitive decline and highlight avenues for future research.

Humans↗

PubMed2026

Apoptosis protein markers in comorbid type 2 diabetes mellitus and depression; relationships with cognitive performance, incident dementia, and white matter hyperintensities.

Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) are reciprocal risk factors, and both elevate dementia risk. Dysregulation of programmed cell death is implicated in T2DM, MDD, and neurodegeneration, but proteomic markers of apoptosis have yet to be studied as dementia predictors in people with T2DM and/or MDD. This study examines apoptosis markers in comorbid T2DM and MDD, and their associations with cognitive, dementia, and neuroimaging outcomes. The retrospective sample (n = 15,765) consisted of UK Biobank participants (MDD only n = 1230; T2DM only n = 3644; comorbid T2DM + MDD n = 721). Individuals with T2DM + MDD comorbidity had poorer cognitive performance, and a higher 15-year dementia incidence (HR = 4.44, 95% CI = [3.23,6.11]). Among 60 apoptosis-related proteins identified by Kyoto Encyclopedia of Genes and Genomes pathway enrichment, 41 were significantly up-regulated in comorbid T2DM + MDD relative to controls, and 4 were higher in the comorbid group than both T2DM alone and MDD alone. Tumor necrosis factor ligand superfamily member 10 (TNFSF10), growth arrest and DNA damage-inducible protein GADD45 beta, tumor necrosis factor ligand superfamily member 6, and RAC-gamma serine/threonine-protein kinase were associated with dementia risk. Nine proteins (e.g. apoptosis-inducing factor 1, mitochondrial, caspase-2, mitogen-activated protein kinase kinase kinase 5, TNFSF10), were associated with white matter hyperintensity volumes in comorbid T2DM + MDD after FDR correction, but none were associated with cognitive performance, atrophy, or white matter microstructural changes. These findings identify peripheral apoptosis markers that were further elevated in comorbid T2DM + MDD compared to either alone, pointing to an important pathophysiological element underlying adverse outcomes in the context of mood and metabolic comorbidity.

Humans↗

PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

Humans↗