OBJECTIVE: To explore the genotype-phenotype correlation in a Chinese family with structural brain abnormalities due to variant of the TUBB gene. METHODS: A family undergoing prenatal diagnosis at Beijing Obstetrics and Gynecology Hospital in October 2024 was selected as the study subject. Clinical data were collected. Amniotic fluid sample was subjected to chromosomal copy number variation sequencing (CNV-seq). Trio whole-exome sequencing (Trio-WES) was carried out on the amniotic fluid and parental blood samples, and candidate variant was verified by Sanger sequencing. This study was approved by the Medical Ethics Committee of the hospital (Ethics No.: 2023-KY-076-01). RESULTS: Both prenatal ultrasound and fetal MRI showed deviation of brain midline, unilateral lateral ventriculomegaly, and bilateral gyral asymmetry. Trio-WES revealed that the fetus has harbored a maternally derived heterozygous missense variant of the TUBB gene [NM_178014.4: c.155A>G (p.N52S)]. Sanger sequencing confirmed that the woman and a previously terminated fetus both harbored the same variant. Both the proband and two fetuses exhibited similar neuroimaging abnormalities including midline deviation and asymmetrical gyri. Based on the guidelines from the American College of Medical Genetics and Genomics (ACMG), the variant was classified as likely pathogenic (PM2_Supporting+PS2_Moderate+PS3). CONCLUSION The heterozygous c.155A>G (p.N52S) variant was the TUBB gene probably underlay the pathogenesis of the structural brain abnormalities in this family. Above findings have expanded the phenotypic spectrum associated with the variant and facilitated the prenatal diagnosis for this family.
Humans ; Female ; Pregnancy ; Prenatal Diagnosis ; Tubulin/genetics* ; Adult ; Brain/diagnostic imaging* ; Male ; Pedigree ; DNA Copy Number Variations/genetics* ; Exome Sequencing ; Genetic Association Studies ; Magnetic Resonance Imaging

OBJECTIVE: Comorbid pain and depression are common but remain difficult to treat. Electroacupuncture (EA) can effectively improve symptoms of depression and relieve pain, but its neural mechanism remains unclear. Therefore, we used resting-state functional magnetic resonance imaging (rs-fMRI) to detect cerebral changes after initiating a mouse pain model via constriction of the infraorbital nerve (CION) and then treating these animals with EA. METHODS: Forty male C57BL/6J mice were divided into 4 groups: control, CION model, EA, and sham acupuncture (without needle insertion). EA was performed on the acupoints Baihui (GV20) and Zusanli (ST36) for 20 min, once a day for 10 consecutive days. The mechanical withdrawal threshold was tested 3 days after the surgery and every 3 days after the intervention. The depressive behavior was evaluated with the tail suspension test, open-field test, elevated plus maze (EPM), sucrose preference test, and marble burying test. The rs-fMRI was used to detect the cerebral changes of the functional connectivity (FC) in the mice following EA treatment. RESULTS: Compared with the CION group, the mechanical withdrawal threshold increased in the EA group at the end of the intervention (P < 0.05); the immobility time in tail suspension test decreased (P < 0.05); and the times of the open arm entry and the open arm time in the EPM increased (both P < 0.001). There was no difference in the sucrose preference or marble burying tests (both P > 0.05). The fMRI results showed that EA treatment downregulated the amplitude of low-frequency fluctuations and regional homogeneity values, while these indicators were elevated in brain regions including the amygdala, hippocampus and cerebral cortex in the CION model for comorbid pain and depression. Selecting the amygdala as the seed region, we found that the FC was higher in the CION group than in the control group. Meanwhile, EA treatment was able to decrease the FC between the amygdala and other brain regions including the caudate putamen, thalamus, and parts of the cerebral cortex. CONCLUSION EA can downregulate the abnormal activation of neurons in the amygdala and improve its FC with other brain regions, thus exerting analgesic and antidepressant effects. Please cite this article as: Yin X, Zeng XL, Lin JJ, Xu WQ, Cui KY, Guo XT, Li W, Xu SF. Brain functional changes following electroacupuncture in a mouse model of comorbid pain and depression: a resting-state functional magnetic resonance imaging study. J Integr Med. 2025; 23(2): 159-168.
Animals ; Electroacupuncture ; Male ; Magnetic Resonance Imaging ; Depression/diagnostic imaging* ; Mice, Inbred C57BL ; Brain/diagnostic imaging* ; Disease Models, Animal ; Mice ; Pain/diagnostic imaging* ; Acupuncture Points

Alzheimer's disease (AD) classification models usually segment the entire brain image into voxel blocks and assign them labels consistent with the entire image, but not every voxel block is closely related to the disease. To this end, an AD auxiliary diagnosis framework based on weakly supervised multi-instance learning (MIL) and multi-scale feature fusion is proposed, and the framework is designed from three aspects: within the voxel block, between voxel blocks, and high-confidence voxel blocks. First, a three-dimensional convolutional neural network was used to extract deep features within the voxel block; then the spatial correlation information between voxel blocks was captured through position encoding and attention mechanism; finally, high-confidence voxel blocks were selected and combined with multi-scale information fusion strategy to integrate key features for classification decision. The performance of the model was evaluated on the Alzheimer's Disease Neuroimaging Initiative (ADNI) and Open Access Series of Imaging Studies (OASIS) datasets. Experimental results showed that the proposed framework improved ACC and AUC by 3% and 4% on average compared with other mainstream frameworks in the two tasks of AD classification and mild cognitive impairment conversion classification, and could find the key voxel blocks that trigger the disease, providing an effective basis for AD auxiliary diagnosis.
Alzheimer Disease/diagnosis* ; Humans ; Neuroimaging/methods* ; Neural Networks, Computer ; Brain/diagnostic imaging* ; Magnetic Resonance Imaging ; Deep Learning ; Machine Learning

Lung cancer is still one of the most common malignant tumors in the world. With the increase of its incidence and the development of medical technology, the overall survival of lung cancer patients has significantly extended compared to before. The incidence of brain and meningeal metastases from lung cancer has also been rising year by year, but patients with brain and meningeal metastases from lung cancer have a poor prognosis and a very high mortality rate, and the diagnosis is mainly based on computed tomography (CT), magnetic resonance imaging (MRI) and other imaging examinations. However, the imaging features are diverse and the specificity is low, which makes it easy to be misdiagnosed and missed. Therefore, accurately identifying brain and meningeal metastases and timely targeted treatment is crucial for improving patient prognosis. This paper analyzed the diagnosis and treatment of a case of lung cancer with no obvious recurrence and metastasis in nearly 7-year long-term follow-up after radical lung cancer surgery, but the patient with abnormal behavior, impaired consciousness and epilepsy in the past 5 months, and multiple punctate calcifications in the brain found by head CT and MRI. This paper consider that the patient's mental and behavioral symptoms were caused by brain and meningeal metastasis of lung cancer after excluding infectious disease and ineffective treatment of autoimmune encephalitis, and further pathological biopsy and genetic detection confirmed the diagnosis of metastatic lung adenocarcinoma with epidermal growth factor receptor (EGFR) L858R gene mutation, and the patient's symptoms were significantly improved after targeted therapy by Osimertinib. This paper also searched the relevant literatures of brain calcifications in databases such as China National Knowledge Infrastructure (CNKI), Wanfang, UpToDate, PubMed, etc., and found that intracerebral calcifications exist in a variety of diseases, including infectious, genetic and neurodegenerative diseases, vascular diseases, metabolic diseases and tumors. However, brain calcification in brain and meningeal metastases are often underestimated, and the consequent risk is misdiagnosis and delayed treatment. Therefore, brain and meningeal metastases manifested as brain calcification should not be ignored in patients with a history of previous tumors.
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Humans ; Lung Neoplasms/pathology* ; Brain Neoplasms/diagnostic imaging* ; Meningeal Neoplasms/diagnostic imaging* ; Calcinosis/diagnostic imaging* ; Male ; Middle Aged ; Tomography, X-Ray Computed ; Magnetic Resonance Imaging

OBJECTIVE: Evaluate the clinical application effect of low-field infant MRI. METHODS: Using literature review, expert consultation, and two rounds of Delphi to determine the evaluation index system. Then retrospectively analyze and compare the data of low-field infant MRI and high-field MRI from January 2023 to December 2024. RESULTS: There is a certain gap between low-field infant MRI and high-field MRI in terms of signal-to-noise ratio, image uniformity, software system reliability, scanning time, user interface friendliness and image result consistency. However, there was no difference in terms of spatial resolution and image quality. The noise, hardware system reliability, mean time between failure and the rate of examination completed without sedation are better than that of high-field MRI. CONCLUSION Low-field infant MRI meets needs of clinical diagnostic and has stable performance. It can be used as a routine screening tool for brain diseases near the bed.
Magnetic Resonance Imaging/methods* ; Humans ; Infant ; Retrospective Studies ; Signal-To-Noise Ratio ; Reproducibility of Results ; Brain Diseases/diagnostic imaging* ; Brain/diagnostic imaging* ; Software

Electrical impedance tomography (EIT) represents an emerging medical functional imaging technology, which operates by applying safe-to-human excitation currents through surface-mounted electrodes, measuring boundary voltages between electrodes, and selecting appropriate image reconstruction algorithms to visualize resistivity in tomographic cross-sections. Compared to traditional medical imaging techniques, EIT offers non-invasive and radiation-free operation, high sensitivity to tissue resistivity changes, and superior temporal resolution, meeting the real-time requirements of clinical dynamic condition monitoring. This paper comprehensively reviews the research status of brain EIT technology, systematically summarizes its advantages and technical limitations in perioperative applications, and prospectively forecasts future development directions of perioperative brain EIT based on current research foundations and clinical application demands, with the aim of providing methodological references for further optimization and clinical promotion of this technology.
Electric Impedance ; Tomography/methods* ; Humans ; Brain/diagnostic imaging*

OBJECTIVE: To elucidate how spinal manipulative therapy (SMT) exerts its analgesic effects through regulating brain function in lumbar disc herniation (LDH) patients by utilizing resting-state functional magnetic resonance imaging (rs-fMRI). METHODS: From September 2021 to September 2023, we enrolled LDH patients (LDH group, n=31) and age- and sex-matched healthy controls (HCs, n=28). LDH group underwent rs-fMRI at 2 distinct time points (TPs): prior to the initiation of SMT (TP1) and subsequent to the completion of the SMT sessions (TP2). SMT was administered once every other day for 30 min per session, totally 14 treatment sessions over a span of 4 weeks. HCs did not receive SMT treatment and underwent only one fMRI scan. Additionally, participants in LDH group completed clinical questionnaires on pain using the Visual Analog Scale (VAS) and the Japanese Orthopedic Association (JOA) score, whereas HCs did not undergo clinical scale assessments. The effects on the brain were jointly characterized using the amplitude of low-frequency fluctuations (ALFF) and regional homogeneity (ReHo). Correlation analyses were conducted between specific brain regions and clinical scales. RESULTS: Following SMT treatment, pain symptoms in LDH patients were notably alleviated and accompanied by evident activation of effects in the brain. In comparison to TP1, TP2 exhibited the most significant increase in ALFF values for Temporal_Sup_R and the most notable decrease in ALFF values for Paracentral_Lobule_L (voxelwise P<0.005; clusters >30; FDR correction). Additionally, the most substantial enhancement in ReHo values was observed for the Cuneus_R, while the most prominent reduction was noted for the Olfactory_R (voxelwise P<0.005; clusters >30; FDR correction). Moreover, a comparative analysis revealed that, in contrast to HCs, LDH patients at TP1 exhibited the most significant increase in ALFF values for Temporal_Pole_Sup_L and the most notable decrease in ALFF values for Frontal_Mid_L (voxelwise P<0.005; clusters >30; FDR correction). Furthermore, the most significant enhancement in ReHo values was observed for Postcentral_L, while the most prominent reduction was identified for ParaHippocampal_L (voxelwise P<0.005; clusters >30; FDR correction). Notably, correlation analysis with clinical scales revealed a robust positive correlation between the Cuneus_R score and the rate of change in the VAS score (r=0.9333, P<0.0001). CONCLUSIONS Long-term chronic lower back pain in patients with LDH manifests significant activation of the "AUN-DMN-S1-SAN" neural circuitry. The visual network, represented by the Cuneus_R, is highly likely to be a key brain network in which the analgesic efficacy of SMT becomes effective in treating LDH patients. (Trial registration No. NCT06277739).
Humans ; Magnetic Resonance Imaging ; Intervertebral Disc Displacement/diagnostic imaging* ; Male ; Female ; Brain/diagnostic imaging* ; Adult ; Manipulation, Spinal/methods* ; Middle Aged ; Lumbar Vertebrae/physiopathology* ; Pain Management ; Rest ; Case-Control Studies

OBJECTIVES: To investigate the associations between Tau protein deposition and brain biochemical metabolites detected by proton magnetic resonance spectroscopy (¹H-MRS) in patients with advanced Alzheimer's disease (AD). METHODS: From April, 2022 to December, 2024, 64 Tau-positive AD patients and 29 healthy individuals underwent ¹⁸F-APN-1607 PET/MR and simultaneously acquired multi-voxel ¹H-MRS in the Department of Nuclear Medicine, Nanjing First Hospital. Visual analysis and voxel-based analysis of PET/MR data were performed to investigate the Tau protein deposition patterns in AD patients. Valid voxels within the ¹H-MRS field of view were selected, and their standardized uptake value ratio (SUVr) in PET and metabolite levels of N-acetylaspartate (NAA), choline (Cho), creatine (Cr), NAA/Cr, and Cho/Cr were recorded. The Tau-positive (Tau⁺) voxels and Tau-negative (Tau^-) voxels of the AD patients were compared for PET and ¹H-MRS parameters, and the correlations between the metabolites and Tau PET SUVr within Tau⁺ voxels were analyzed. RESULTS: Significant Tau protein deposition were observed in the AD patients, involving mainly the bilateral frontal lobes (30.07%), parietal lobes (29.96%), temporal lobes (21.07%), and occipital lobes (15.89%). A total of 1422 valid voxels in AD group (including 994 Tau⁺ and 428 Tau^- voxels) and 814 voxels in the control group were selected. The AD patients showed significantly decreased NAA level and increased SUVr compared with the control group (P<0.05). Subgroup analyses revealed that Tau⁺ voxels had higher SUVr and lower Cr and Cho/Cr than Tau^- voxels (P<0.05). Compared with the control group, Tau⁺ voxels exhibited higher SUVr and lower Cr (P<0.05), while Tau^- voxels showed lower NAA (P=0.004). No significant differences were found in Cho or NAA/Cr among the subgroups (P>0.05). Within Tau⁺ voxels, NAA, Cho, and Cr were negatively correlated with SUVr (P<0.001). CONCLUSIONS The patients with progressive AD have significant Tau protein deposition in the brain, which is correlated with alterations in metabolite levels. Decreased NAA is more prominent in early or pre-tau deposition stages, while Cr changes is more significant in the regions with Tau protein deposition, suggesting the potential of NAA and Cr as biomarkers for Tau protein deposition in AD for disease monitoring and treatment evaluation.
Humans ; Alzheimer Disease/diagnostic imaging* ; Aspartic Acid/metabolism* ; tau Proteins/metabolism* ; Creatine/metabolism* ; Brain/metabolism* ; Biomarkers/metabolism* ; Positron-Emission Tomography ; Male ; Female ; Proton Magnetic Resonance Spectroscopy ; Choline/metabolism* ; Aged ; Middle Aged

Attention deficit hyperactivity disorder (ADHD), a prevalent neurodevelopmental disorder influenced by both genetic and environmental factors, remains poorly understood regarding how its polygenic risk score (PRS) impacts functional networks and symptomology. This study capitalized on data from 11,430 children in the Adolescent Brain Cognitive Development study to explore the interplay between PRS_ADHD, brain function, and behavioral problems, along with their interactive effects. The results showed that children with a higher PRS_ADHD exhibited more severe attention deficits and rule-breaking problems, and experienced sleep disturbances, particularly in initiating and maintaining sleep. We also identified the central executive network, default mode network, and sensory-motor network as the functional networks most associated with PRS and symptoms in ADHD cases, with potential mediating roles. Particularly, the impact of PRS_ADHD was enhanced in children experiencing heightened sleep disturbances, emphasizing the need for early intervention in sleep issues to potentially mitigate subsequent ADHD symptoms.
Humans ; Attention Deficit Disorder with Hyperactivity/physiopathology* ; Male ; Female ; Sleep Wake Disorders/physiopathology* ; Adolescent ; Child ; Brain/diagnostic imaging* ; Multifactorial Inheritance ; Genetic Predisposition to Disease

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks