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Objective: Preoperative diagnosis of diffuse midline glioma, H3 K27-altered (DMG-A) and midline high-grade glioma without H3 K27 alteration (DMG-W), as well as midline primary CNS lymphoma (PCNSL) in adults, is challenging but crucial. The aim of this study was to develop a model for predicting these three entities using machine learning (ML) algorithms., Methods: Thirty-three patients with DMG-A, 35 with DMG-W, and 35 with midline PCNSL were retrospectively enrolled in the study. Radiomics features were extracted from contrast-enhanced T1-weighted MR images. Two radiologists evaluated the conventional MRI features of the tumors, such as shape. Patient age, tumor volume, and conventional MRI features were considered clinical features. The data set was randomly stratified into 70% training and 30% testing cohorts. Predictive models based on the clinical features, radiomics features, and integration of clinical and radiomics features were established through ML. The performances of the models were evaluated by calculating the area under the receiver operating characteristic curve, accuracy, sensitivity, and specificity. Subsequently, 10 patients with DMG-A, 10 with DMG-W, and 12 with PCNSL were enrolled from another institution to validate the established models., Results: The predictive models based on clinical features, radiomics features, and the integration of clinical and radiomics features through the support vector machine algorithm had the optimal accuracies in the training, testing, and validation cohorts, and the accuracies in the testing cohort were 0.871, 0.892, and 0.903, respectively. Age, 2 radiomics features, and 3 conventional MRI features were the 6 most significant features in the established integrated model., Conclusions: The integrated prediction model established by ML provides high discriminatory accuracy for predicting DMG-A, DMG-W, and midline PCNSL in adults.

This retrospective study aimed to improve the diagnostic accuracy of breast lymphoma (BL) by analyzing the findings of BL on mammography and magnetic resonance imaging (MRI).Fifteen patients with breast lymphoma (BL, Primary/Secondary: 13/2) were confirmed by pathology. The imaging findings of those patients were analyzed by 2 senior radiologists.BL commonly showed significant enhancement with penetrating vessels and septation in masses on dynamic contrast-enhanced MRI (DCE-MRI). Diffusion limitation of BL is more pronounced than breast cancer on diffusion weighted imaging.The study suggests that the penetrating vessels and diffusion restriction of lesions are helpful for the diagnosis and differential diagnosis of BL.

Crohn's disease (CD) is a chronic, non-specific granulomatous inflammatory disorder that commonly affects the small intestine and is a phenotype of inflammatory bowel disease (IBD). CD is prone to relapse, and its incidence displays a persistent increase in developing countries. However, the pathogenesis of CD is poorly understood, with some studies emphasizing the link between CD and the intestinal microbiota. Specifically, studies point to the brain-gut-enteric microbiota axis as a key player in the occurrence and development of CD. Furthermore, investigations have shown white-matter lesions and neurologic deficits in patients with IBD. Based on these findings, brain activity changes in CD patients have been detected by blood oxygenation level dependent functional magnetic resonance imaging (BOLD-fMRI). BOLD-fMRI functions by detecting a local increase in relative blood oxygenation that results from neurotransmitter activity and thus reflects local neuronal firing rates. Therefore, biochemical concentrations of neurotransmitters or metabolites may change in corresponding brain regions of CD patients. To further study this phenomenon, brain changes of CD patients can be detected non-invasively, effectively and accurately by BOLD-fMRI combined with magnetic resonance spectroscopy (MRS). This approach can further shed light on the mechanisms of the occurrence and development of neurological CD. Overall, this paper reviews the current status and prospects on fMRI and MRS for evaluation of patients with CD based on the brain-gut-enteric microbiota axis., Competing Interests: Conflict-of-interest statement: No potential conflicts of interest exist.

Purpose: Neuroplasticity can partially compensate for the neurological deficits caused by brain tumors. However, the structural plasticity of the brain caused by brain tumors is not fully understood. This study aimed to assess the structural plasticity of the contralesional hemisphere in patients with frontal low-grade gliomas (LGGs). Methods: A total of 25 patients with left frontal LGGs (LFLGGs), 19 patients with right frontal LGGs (RFLGGs), and 25 healthy controls (HCs) were enrolled in this study. High-resolution structural T1-weighted imaging and fluid attenuation inversion recovery were performed on all participants. Voxel-based morphometry (VBM) analysis was used to detect differences in the brain structural plasticity between patients with unilateral LGGs and HCs. Results: VBM analysis revealed that compared with HCs, the gray matter volume (GMV) of the contralesional putamen and amygdala was significantly smaller and larger in the patients with RFLGGs and LFLGGs, respectively, while the GMVs of the contralesional cuneus and superior temporal gyrus (STG) were significantly larger in the patients with LFLGGs. The surviving clusters of the right hemisphere included 1357 voxels in the amygdala, 1680 voxels in the cuneus, 384 voxels in the STG, and 410 voxels in the putamen. The surviving clusters of the left hemisphere were 522 voxels in the amygdala and 320 voxels in the putamen. Conclusion: The unilateral frontal LGGs are accompanied by structural plasticity in the contralesional cortex and vary with tumor laterality. Contralesional structural reorganization may be one of the physiological basis for functional reorganization or compensation in the frontal LGGs. [ABSTRACT FROM AUTHOR]

Glioma is the most common primary malignant brain tumor in adults. It accounts for about 75% of such tumors and occurs more commonly in men. The incidence rate has been increasing in the past 30 years. Moreover, the 5-year overall survival rate of glioma patients is < 35%. Different locations, grades, and molecular characteristics of gliomas can lead to different behavioral deficits and prognosis, which are closely related to patients' quality of life and associated with neuroplasticity. Some advanced magnetic resonance imaging (MRI) technologies can explore the neuroplasticity of structural, topological, biochemical metabolism, and related mechanisms, which may contribute to the improvement of prognosis and function in glioma patients. In this review, we summarized the studies conducted on structural and topological plasticity of glioma patients through different MRI technologies and discussed future research directions. Previous studies have found that glioma itself and related functional impairments can lead to structural and topological plasticity using multimodal MRI. However, neuroplasticity caused by highly heterogeneous gliomas is not fully understood, and should be further explored through multimodal MRI. In addition, the individualized prediction of functional prognosis of glioma patients from the functional level based on machine learning (ML) is promising. These approaches and the introduction of ML can further shed light on the neuroplasticity and related mechanism of the brain, which will be helpful for management of glioma patients. [ABSTRACT FROM AUTHOR]

Background: Magnetic resonance imaging (MRI) is widely used in the diagnosis of tuberculous meningitis (TBM) and its complications. We aimed to explore the relationship between MRI features and neurological deficits and TBM patients' prognosis. Methods: patients diagnosed with TBM were subjected to a neurological evaluation on admission and divided into groups based on the Medical Research Council (MRC) scale. After several years of follow-up, the patients were further divided into groups according to the Modified Rankin Score (MRS). Their MR images were analyzed for meningeal enhancement, tuberculomas, infarction, hydrocephalus, and abscess, including the location and size of the lesion. Any changes in MRI features during the follow-up were recorded. MRI features between groups were compared, and the relationship between dynamic changes in images and Rankin grading was explored. Results: We found significant differences in acute cerebral infarction (ACI) and old cerebral infarctions (OCI) between the MRC groups, and the ORs of ACI and OCI were 21.818 (95% CI: 2.440–195.075) and 6.788 (95% CI: 1.516–30.392), respectively. There were significant differences in ACI, OCI, and Evan's ratio between the MRS groups (p < 0.05), and the ORs of ACI, OCI, and hydrocephalus were 6.375 (95% CI: 1.501–27.080), 5.556 (95% CI: 1.332–23.177), and 9.139 (95% CI: 2.052–40.700), respectively. The changes of Evan's ratio were related to the MRS grading (r = 0.335, p = 0.040). Conclusions: For patients with TBM, the presence of ACI or OCI is associated with neurological deficits, and ACI, OCI, and hydrocephalus can be regarded as poor prognostic predictors. Changes in Evan's ratio will affect the outcome. [ABSTRACT FROM AUTHOR]

Castleman's disease (CD) is a lymphoproliferative abnormality, also referred to as giant lymph node hyperplasia or follicular lymphoid hyperplasia. The occurrence of CD in the liver is rare. Radiological diagnosis of hepatic CD by computed tomography (CT) and magnetic resonance imaging (MRI) remains difficult. On imaging, hepatic CD is often expressed as a single, well.defined soft tissue lesion, with rare cystic degeneration and focal necrosis. The CD lesions appear as hypervascular with abundant cell proliferation on CT and MRI. Polymorphic calcification is commonly identified in the lesion. However, these findings are non.specific for a definitive radiological diagnosis. We herein present a case of hepatic CD and review its pathological and imaging characteristics. In particular, a strip.like area was observed extending from the nodule, which may be helpful for the diagnosis of CD in the liver. [ABSTRACT FROM AUTHOR]