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

Valacyclovir-associated neurotoxicity (VAN) is a recognized adverse effect in elderly patients with renal impairment but remains underdiagnosed due to its nonspecific presentation and overlap with acute neurologic emergencies. We report a 78-year-old Filipino female with end-stage renal disease on maintenance hemodialysis who developed acute disorientation, agitation, vivid visual hallucinations and generalized weakness shortly after initiation of valacyclovir for herpes zoster. Given the abrupt onset of neuropsychiatric symptoms, viral encephalitis was initially considered. Magnetic resonance imaging of the brain showed no evidence of acute infarction or encephalitis, while electroencephalography demonstrated diffuse generalized slowing consistent with an encephalopathic process. Review of the medication history revealed valacyclovir dosing that exceeded recommendations for patients with end-stage renal disease. Valacyclovir was discontinued and emergent hemodialysis was initiated resulting in marked improvement in sensorium after the second session and complete resolution of symptoms after the third. This case shows VAN as an important diagnostic mimic of acute encephalopathy in elderly patients with renal failure and emphasizes the critical role of early medication review in preventing unnecessary investigations and enabling prompt, reversible management.

BACKGROUND

Magnetic resonance imaging (MRI) has gained increased diagnostic utility for patients with transient global amnesia (TGA), particularly for unwitnessed events or those with diagnostic uncertainty based on clinical grounds.

The objectives are first, to determine the demographic and comorbid conditions of TGA patients; second, to determine the percentage of MRI diffusion weighted imaging (MRI DWI) hippocampal lesions, their time relationship from symptom onset, and their morphological characteristics; and lastly, to determine the dementia visual rating scale scores on neuroimaging for these patients.

A total of 20 TGA patients in a tertiary hospital from 2018 to 2022 were included in this retrospective study, and their medical records and neuroimaging were reviewed.

TGA patients had a mean age of 61.4 years and a female predominance. Prevalent comorbid conditions include hypertension, dyslipidemia, and diabetes, and the majority were discharged with antithrombotic medications. An emotionally triggering event was identified in 15% (n = 3). Mean symptom onset-to-scan time was 8.33 h, and one patient (detection rate of 5%) who underwent neuroimaging after 21.7 h demonstrated typical punctate hippocampal DWI hyperintensity. None exhibited significant cortical atrophy.

TGA patients showed female predominance, occurring mostly within the 5th–6th decade, with a moderate prevalence of vascular risk factors and absence of significant cerebral atrophy based on the Dementia Visual Rating Scales. A conventional MRI protocol yielded a 5% detection rate with a delay of 21 h from symptom onset. Hence, in a resource-limited setting such as the Philippines, it may be suggested, with limited evidence, that performing the procedure in TGA patients when the event is unwitnessed or uncertain could be reasonable, as correctly diagnosing TGA has therapeutic implications. Further studies may investigate prospectively the diagnostic utility of MRI, neuropsychological profile, and estimate cardiovascular and cognitive deterioration risk.

OBJECTIVE: To screen the population for acupuncture treatment of neck pain, using functional magnetic resonance imaging (fMRI) technology and based on machine learning algorithms. METHODS: Eighty patients with neck pain were recruited. Using FPX25 handheld pressure algometer, the tender points were detected in the areas with high-frequent onset of neck pain and high degree of acupoint sensitization. Acupuncture was delivered at 4 tender points with the lowest pain threshold, once every two days; and the treatment was given 3 times a week and for 2 consecutive weeks. The amplitude of low-frequency fluctuation (ALFF) of the brain before treatment was taken as a predictive feature to construct support vector machine (SVM), logistic regression (LR), and K-nearest neighbors (KNN) models to predict the responses of neck pain patients to acupuncture treatment. A longitudinal analysis of the ALFF features was performed before and after treatment to reveal the potential biological markers of the reactivity to the acupuncture therapy. RESULTS: The SVM model could successfully distinguish high responders (48 cases) and low responders (32 cases) to acupuncture treatment, and its accuracy rate reached 82.5%. Based on the SVM model, the ALFF values of 4 brain regions were identified as the consistent predictive features, including the right middle temporal gyrus, the right superior occipital gyrus, and the bilateral posterior cingulate gyrus. In the patients with high acupuncture response, the ALFF value in the left posterior cingulate gyrus decreased after treatment (P<0.05), whereas in the patients with low acupuncture response, the ALFF value in the right superior occipital gyrus increased after treatment (P<0.01). The longitudinal functional connectivity (FC) analysis found that compared with those before treatment, the high responders showed the enhanced FC after treatment between the left posterior cingulate gyrus and various regions, including the bilateral Crus1 of the cerebellum, the right insula, the bilateral angular gyrus, the left medial superior frontal gyrus, and the left middle cingulate gyrus (GRF: corrected, voxel level: P<0.05, mass level: P<0.05). In contrast, the low responders exhibited the enhanced FC between the left posterior cingulate gyrus and the left Crus2 of the cerebellum, the left middle temporal gyrus, the right posterior cingulate gyrus, and the left angular gyrus; besides, FC was reduced in low responders between the left posterior cingulate gyrus and the right supramarginal gyrus (GRF: corrected, voxel level: P<0.05, mass level: P<0.05). CONCLUSION This study validates the practicality of pre-treatment ALFF feature prediction for acupuncture efficacy on neck pain. The therapeutic effect of acupuncture on neck pain is potentially associated with its impact on the default mode network, and then, alter the pain perception and emotional regulation.
Humans ; Neck Pain/physiopathology* ; Acupuncture Therapy ; Female ; Male ; Adult ; Middle Aged ; Machine Learning ; Magnetic Resonance Imaging ; Young Adult ; Brain/physiopathology* ; Acupuncture Points ; Aged

Electroencephalography (EEG) and magnetic resonance imaging (MRI), as neuroimaging technologies, provided objective and visualized technical tools for analyzing the brain effect mechanisms of acupuncture and moxibustion from the perspectives of brain structure, function, metabolism, and hemodynamics. The advancement of artificial intelligence (AI) algorithms can compensate for issues such as the large and scattered nature of neuroimaging data, inconsistent quality, and high heterogeneity of image information. The integration of AI with neuroimaging can facilitate individualized, intelligent, and precise prediction of acupuncture and moxibustion effects, enable intelligent classification of differential acupuncture responses, and identify brain activation patterns. This paper focuses on EEG and MRI, analyzing how machine learning and deep learning optimize multimodal neuroimaging data and their applications in the study of acupuncture and moxibustion brain effects mechanisms. Furthermore, it highlights current research gaps and limitations to provide insights for future studies on acupuncture brain effects mechanisms.
Humans ; Acupuncture Therapy ; Brain/physiology* ; Moxibustion ; Neuroimaging/methods* ; Artificial Intelligence ; Magnetic Resonance Imaging ; Electroencephalography

OBJECTIVES: To develop a risk prediction model for left ventricular adverse remodeling (LVAR) based on cardiac magnetic resonance (CMR) parameters in patients undergoing percutaneous coronary intervention (PCI) for acute ST-segment elevation myocardial infarction (STEMI). METHODS: A total of 329 acute STEMI patients undergoing primary PCI at 8 medical centers from January, 2018 to December, 2021 were prospectively enrolled. The parameters of CMR, performed at 7±2 days and 6 months post-PCI, were analyzed using CVI42 software. LVAR was defined as an increase >20% in left ventricular end-diastolic volume or >15% in left ventricular end-systolic volume at 6 months compared to baseline. The patients were randomized into training (n=230) and validation (n=99) sets in a 7∶3 ratio. In the training set, potential predictors were selected using LASSO regression, followed by univariate and multivariate logistic regression to construct a nomogram. Model performance was evaluated using receiver-operating characteristic (ROC) curves, area under the curve (AUC), calibration curves, and decision curve analysis. RESULTS: LVAR occurred in 100 patients (30.40%), who had a higher incidence of major adverse cardiovascular events than those without LVAR (58.00% vs 16.16%, P<0.001). Left ventricular global longitudinal strain (LVGLS; OR=0.76, 95% CI: 0.61-0.95, P=0.015) and left atrial active strain (LAAS; OR=0.78, 95% CI: 0.67-0.92, P=0.003) were protective factors for LVAR, while infarct size (IS; OR=1.05, 95% CI: 1.01-1.10, P=0.017) and microvascular obstruction (MVO; OR=1.26, 95% CI: 1.01-1.59, P=0.048) were risk factors for LVAR. The nomogram had an AUC of 0.90 (95% CI: 0.86-0.94) in the training set and an AUC of 0.88 (95% CI: 0.81-0.94) in the validation set. CONCLUSIONS LVGLS, LAAS, IS, and MVO are independent predictors of LVAR in STEMI patients following PCI. The constructed nomogram has a strong predictive ability to provide assistance for management and early intervention of LVAR.
Humans ; Percutaneous Coronary Intervention ; Prospective Studies ; ST Elevation Myocardial Infarction/diagnostic imaging* ; Ventricular Remodeling ; Magnetic Resonance Imaging ; Male ; Female ; Middle Aged ; Risk Factors ; Aged ; Risk Assessment

OBJECTIVES: To construct a bone tumor classification model based on feature decoupling and fusion for processing modality loss and fusing multimodal information to improve classification accuracy. METHODS: A decoupling completion module was designed to extract local and global bone tumor image features from available modalities. These features were then decomposed into shared and modality-specific features, which were used to complete the missing modality features, thereby reducing completion bias caused by modality differences. To address the challenge of modality differences that hinder multimodal information fusion, a cross-attention-based fusion module was introduced to enhance the model's ability to learn cross-modal information and fully integrate specific features, thereby improving the accuracy of bone tumor classification. RESULTS: The experiment was conducted using a bone tumor dataset collected from the Third Affiliated Hospital of Southern Medical University for training and testing. Among the 7 available modality combinations, the proposed method achieved an average AUC, accuracy, and specificity of 0.766, 0.621, and 0.793, respectively, which represent improvements of 2.6%, 3.5%, and 1.7% over existing methods for handling missing modalities. The best performance was observed when all the modalities were available, resulting in an AUC of 0.837, which still reached 0.826 even with MRI alone. CONCLUSIONS The proposed method can effectively handle missing modalities and successfully integrate multimodal information, and show robust performance in bone tumor classification under various complex missing modality scenarios.
Humans ; Bone Neoplasms/diagnosis* ; Multimodal Imaging/methods* ; Magnetic Resonance Imaging ; Tomography, X-Ray Computed ; Image Processing, Computer-Assisted/methods* ; Algorithms

OBJECTIVES: To propose a single repetition time (TR) quantitative magnetic susceptibility imaging method for the lumbar spine using bipolar readout gradient, and compare the quantitative magnetic susceptibility measurement using single TR and dual TR methods for the lumbar spine with different bone densities. METHODS: A translation correction method was proposed to correct spatial misalignment along the frequency encoding direction between positive and negative gradient readout images, and the phase difference between the images was eliminated using a phase correction method. The data of lumbar vertebrae L1-L5 were collected using single TR and dual TR methods from 6 normal individuals, 2 patients with osteopenia, and 2 patients with osteoporosis. The magnetic susceptibility map was reconstructed, the quantitative results of single TR before and after correction were compared with those of the dual TR method. RESULTS: The linear regression result of the lumbar spine magnetic susceptibility values obtained by the single TR method before calibration and the dual TR method is Y=0.64*X-11.61. The linear regression result of the lumbar spine magnetic susceptibility values corrected by the single TR method and the dual TR method is Y=1.03*X+0.25. The results of the corrected single TR method were highly consistent with those of the dual TR method, and the calibrated single TR method could effectively distinguish osteopenia and osteoporosis patients from normal individuals. CONCLUSIONS The calibrated single TR bipolar readout gradient method can generate artifact-free lumbar spine quantitative magnetic susceptibility distribution maps and reduce data acquisition time by 50%.
Humans ; Lumbar Vertebrae/pathology* ; Magnetic Resonance Imaging/methods* ; Female ; Middle Aged ; Male ; Osteoporosis/diagnosis* ; Adult ; Bone Density ; Aged ; Bone Diseases, Metabolic/diagnosis*

OBJECTIVES: To qualitatively assess the diagnostic performance of dynamic contrast enhancement (DCE), diffusion-weighted imaging (DWI), and T2-weighted imaging (T2WI), alone or in combination, in the evaluation of breast cancer. METHODS: We retrospectively reviewed the records of 394 consecutive patients with pathologically confirmed breast lesions who had undergone 3-T magnetic resonance imaging (MRI). The morphological characteristics of breast lesions were evaluated using DCE, DWI, and T2WI based on BI-RADS lexicon descriptors by trained radiologists. Patients were categorized into mass and non-mass groups based on MRI characteristics of the lesions, and the differences between benign and malignant lesions in each group were compared. Clinical prediction models for breast cancer diagnosis were constructed using logistic regression analysis. Diagnostic efficacies were compared using the area under the receiver operating characteristic curve (AUC) and DeLong test. RESULTS: For mass-like lesions, all the morphological parameters significantly differentiated benign and malignant lesions on consensus DCE, DWI, and T2WI (P<0.05). The combined method (DCE+DWI+T2WI) had a higher AUC (0.865) than any of the individual modality (DCE: 0.786; DWI: 0.793; T2WI: 0.809) (P<0.05). For non-mass-like lesions, DWI signal intensity was a significant predictor of malignancy (P=0.036), but the model using DWI alone had a low AUC (0.669). CONCLUSIONS Morphological assessment using the combination of DCE, DWI, and T2WI provides better diagnostic value in differentiating benign and malignant breast mass-like lesions than assessment with only one of the modalities.
Humans ; Female ; Breast Neoplasms/pathology* ; Retrospective Studies ; Middle Aged ; Adult ; Diffusion Magnetic Resonance Imaging/methods* ; Aged ; Magnetic Resonance Imaging/methods* ; Young Adult ; Aged, 80 and over

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