Image-guided thermal ablation (IGTA) has been widely used in the treatment of liver tumors. MRI-guided thermal ablation of liver tumors offers several advantages, including the absence of ionizing radiation; excellent soft-tissue contrast; multi-parametric and multiplanar imaging; non-invasive, real-time temperature monitoring of the thermal field during the procedure; and accurate post-procedural assessment of therapeutic efficacy. To standardize and promote MRI-guided thermal ablation for liver tumors in China, advance the technological development of IGTA for tumor treatment, and enhance the efficacy of "precision ablation" for hepatic tumors, this expert consensus (2025 edition) was collaboratively developed by national experts from multiple societies and committees through multidisciplinary discussions. The contributing groups included the Society of Tumor Ablation Therapy of the Chinese Anti-Cancer Association, the Ablation Expert Committee of the Chinese Society of Clinical Oncology (CSCO), the Tumor Ablation Subgroup of the National Health Commission Comprehensive Interventional Therapy Quality Control Center, the Expert Group on Tumor Ablation Therapy of the Chinese Medical Doctors Association, and the Tumor Ablation Committee of the Chinese College of Interventionalists. The main contents of the consensus include: (1) indications, contraindications, and characteristics of MRI-guided thermal ablation for liver tumors; (2) MRI magnets, guidance sequences, and MRI-compatible thermal ablation equipment and instruments; and (3) protocols for MRI-guided thermal ablation of liver tumors, efficacy assessment, and the prevention and management of complications.
Humans ; Liver Neoplasms/surgery* ; Magnetic Resonance Imaging ; Consensus ; China ; Catheter Ablation/methods* ; Ablation Techniques/methods* ; Surgery, Computer-Assisted

Objective To compare the diagnostic value of transabdominal intestinal ultrasound (IUS) and magnetic resonance enterography (MRE) for intestinal stenosis in inflammatory bowel disease (IBD). Methods A retrospective analysis was conducted on the imaging features of 51 IBD patients who underwent both IUS and MRE at Beijing Friendship Hospital,Capital Medical University,between January 2021 and February 2025.With endoscopy as the gold standard,the diagnostic performance of the two methods was compared. Results The sensitivity (84.2% vs. 52.6%,P=0.008) and accuracy (66.7% vs. 45.1%,P=0.035) of IUS for stenosis were higher than those of MRE.In the localization of stenosis,IUS demonstrated higher sensitivity than MRE for detecting stenosis in the terminal ileum (78.6% vs. 35.7%,P=0.070) and colorectum (86.7% vs. 53.3%,P=0.060).Furthermore,IUS showed higher diagnostic accuracy than MRE for terminal ileum stenosis (70.6% vs. 29.4%,P=0.039).The intestinal wall thickness[(8.2±2.7) mm vs. (10.3±3.8) mm;t=3.20,P=0.002)] and stenosis inner diameter[(3.0±1.6) mm vs. (4.3±1.8) mm;t=2.15,P=0.035] measured by IUS were lower than those measured by MRE,with a moderate level of consistency (ICC:0.19-0.53).In addition,IUS demonstrated a higher detection rate for mesenteric fat hypertrophy (70.6% vs. 27.5%,Kappa=0.27,P=0.005),whereas MRE was more sensitive in detecting lymphadenopathy (90.2% vs. 56.9%,Kappa=0.16,P=0.080). Conclusions IUS is superior to MRE in the diagnosis and localization sensitivity for intestinal stenosis in IBD.However,the two methods showcase poor consistency in detecting and quantitating some inflammatory signs.IUS can be used as a first-line screening method for diagnosing intestinal stenosis in IBD patients,while its clinical application should be combined with specific needs to optimize diagnosis.
Humans ; Retrospective Studies ; Constriction, Pathologic/diagnostic imaging* ; Ultrasonography/methods* ; Magnetic Resonance Imaging/methods* ; Inflammatory Bowel Diseases/diagnostic imaging* ; Male ; Female ; Adult ; Middle Aged ; Intestines/diagnostic imaging* ; Sensitivity and Specificity

OBJECTIVES: To evaluate preterm white matter injury (PWMI) in neonatal rats using multimodal magnetic resonance imaging (MRI) combined with histological assessments and to explore its underlying mechanisms. METHODS: Healthy 3-day-old Sprague-Dawley neonatal rats were randomly divided into a sham operation group and a PWMI group (n=12 in each group). A PWMI model was established in neonatal rats through hypoxia-ischemia. Laser speckle imaging was used to observe changes in cerebral oxygen saturation and blood flow at different time points post-modeling. Multimodal MRI was employed to assess the condition of white matter injury, while hematoxylin-eosin staining was utilized to observe morphological changes in the striatal area on the injured side. Immunofluorescence staining was performed to detect the proliferation and differentiation of oligodendrocyte precursor cells. RESULTS: At 0, 6, 12, 24, and 72 hours post-modeling, the relative blood flow and relative oxygen saturation on the injured side in the PWMI group were significantly lower than those in the sham operation group (P<0.05). At 24 hours post-modeling, T2-weighted imaging showed high signals in the white matter of the injured side in the PWMI group, with relative apparent diffusion coefficient values and Lorenz differential values being lower than those in the sham operation group (P<0.001); additionally, the arrangement of nerve cells in the PWMI group was disordered, and the number of EdU⁺PDGFR-α⁺ cells was higher than that in the sham operation group (P<0.001). At 28 days post-modeling, the relative fractional anisotropy values, the number of EdU⁺Olig2⁺ cells, and the fluorescence intensity of myelin basic protein and neurofilament protein 200 in the white matter region of the PWMI group were all lower than those in the sham operation group (P<0.001). CONCLUSIONS Multimodal MRI can evaluate early and long-term changes in PWMI in neonatal rat models in vivo, providing both imaging and pathological evidence for the diagnosis and treatment of PWMI in neonates. Hypoxia-ischemia inhibits the proliferation and differentiation of oligodendrocyte precursor cells in neonatal rats, leading to PWMI.
Animals ; Rats, Sprague-Dawley ; Magnetic Resonance Imaging/methods* ; Rats ; White Matter/injuries* ; Animals, Newborn ; Female ; Multimodal Imaging ; Male ; Hypoxia-Ischemia, Brain/pathology*

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

The gradient field, one of the core magnetic fields in magnetic resonance imaging (MRI) systems, is generated by gradient coils and plays a critical role in spatial encoding and the generation of echo signals. The uniformity or linearity of the gradient field directly impacts the quality and distortion level of MRI images. However, traditional point measurement methods lack accuracy in assessing the linearity of gradient fields, making it difficult to provide effective parameters for image distortion correction. This paper introduced a spherical measurement-based method that involved measuring the magnetic field distribution on a sphere, followed by detailed magnetic field calculations and linearity analysis. This study, applied to assess the nonlinearity of asymmetric head gradient coils, demonstrated more comprehensive and precise results compared to point measurement methods. This advancement not only strengthens the scientific basis for the design of gradient coils but also provides more reliable parameters and methods for the accurate correction of MRI image distortions.
Magnetic Resonance Imaging/instrumentation* ; Humans ; Image Processing, Computer-Assisted/methods* ; Nonlinear Dynamics ; Magnetic Fields ; Algorithms ; Phantoms, Imaging

Depression, a mental health disorder, has emerged as one of the significant challenges in the global public health domain. Investigating the pathogenesis of depression and accurately assessing the symptomatic changes are fundamental to formulating effective clinical diagnosis and treatment strategies. Utilizing non-invasive brain imaging technologies such as functional magnetic resonance imaging and scalp electroencephalography, existing studies have confirmed that the onset of depression is closely associated with abnormal neural activities and altered functional connectivity in multiple brain regions. Magnetoencephalography, unaffected by tissue conductivity and skull thickness, boasts high spatial resolution and signal-to-noise ratio, offering unique advantages and significant value in revealing the abnormal brain mechanisms and neural characteristics of depression. This review, starting from the rhythmic characteristics, nonlinear dynamic features, and connectivity characteristics of magnetoencephalography in depression patients, revisits the research progress on magnetoencephalography features related to depression, discusses current issues and future development trends, and provides insights for the study of pathophysiological mechanisms, as well as for clinical diagnosis and treatment of depression.
Humans ; Magnetoencephalography/methods* ; Brain/physiopathology* ; Depression/diagnosis* ; Electroencephalography ; Magnetic Resonance Imaging

Aiming at the problems of low accuracy and large difference of segmentation boundary distance in anterior cruciate ligament (ACL) image segmentation of knee joint, this paper proposes an ACL image segmentation model by fusing dilated convolution and residual hybrid attention U-shaped network (DRH-UNet). The proposed model builds upon the U-shaped network (U-Net) by incorporating dilated convolutions to expand the receptive field, enabling a better understanding of the contextual relationships within the image. Additionally, a residual hybrid attention block is designed in the skip connections to enhance the expression of critical features in key regions and reduce the semantic gap, thereby improving the representation capability for the ACL area. This study constructs an enhanced annotated ACL dataset based on the publicly available Magnetic Resonance Imaging Network (MRNet) dataset. The proposed method is validated on this dataset, and the experimental results demonstrate that the DRH-UNet model achieves a Dice similarity coefficient (DSC) of (88.01±1.57)% and a Hausdorff distance (HD) of 5.16±0.85, outperforming other ACL segmentation methods. The proposed approach further enhances the segmentation accuracy of ACL, providing valuable assistance for subsequent clinical diagnosis by physicians.
Humans ; Magnetic Resonance Imaging/methods* ; Anterior Cruciate Ligament/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Knee Joint/diagnostic imaging* ; Neural Networks, Computer ; Algorithms ; Deep Learning

Among numerous medical imaging modalities, diffusion weighted imaging (DWI) is extremely sensitive to acute ischemic stroke lesions, especially small infarcts. However, magnetic resonance imaging is time-consuming and expensive, and it is also prone to interference from metal implants. Therefore, the aim of this study is to design a medical image synthesis method based on generative adversarial network, Stroke-p2pHD, for synthesizing DWI images from computed tomography (CT). Stroke-p2pHD consisted of a generator that effectively fused local image features and global context information (Global_to_Local) and a multi-scale discriminator (M ²Dis). Specifically, in the Global_to_Local generator, a fully convolutional Transformer (FCT) and a local attention module (LAM) were integrated to achieve the synthesis of detailed information such as textures and lesions in DWI images. In the M ²Dis discriminator, a multi-scale convolutional network was adopted to perform the discrimination function of the input images. Meanwhile, an optimization balance with the Global_to_Local generator was ensured and the consistency of features in each layer of the M ²Dis discriminator was constrained. In this study, the public Acute Ischemic Stroke Dataset (AISD) and the acute cerebral infarction dataset from Yantaishan Hospital were used to verify the performance of the Stroke-p2pHD model in synthesizing DWI based on CT. Compared with other methods, the Stroke-p2pHD model showed excellent quantitative results (mean-square error = 0.008, peak signal-to-noise ratio = 23.766, structural similarity = 0.743). At the same time, relevant experimental analyses such as computational efficiency verify that the Stroke-p2pHD model has great potential for clinical applications.
Humans ; Tomography, X-Ray Computed/methods* ; Diffusion Magnetic Resonance Imaging/methods* ; Cerebral Infarction/diagnostic imaging* ; Stroke/diagnostic imaging* ; Neural Networks, Computer ; Image Processing, Computer-Assisted/methods* ; Algorithms

OBJECTIVE: To precise classify sacral meningeal cysts, effective guide minimally invasive neurosurgery and postoperative personalized rehabilitation by multiple dimensions radiographic reconstruction MRI. METHODS: From March to December 2021, based on the original 3D-fast imaging employing steadystate acquisition (FIESTA) scanning sequence, 92 patients with sacral meningeal cysts were pre-operatively evaluated by multiple dimensional reconstruction MRI. The shape of nerve root and the leakage of cyst were reconstructed according to the direction of nerve root or leakage track showed on original MRI scans. Sacral canal cysts were accurately classified as including nerve root and without nerve root, so as to accurately design the incision of skin and formulate corresponding open range of the posterior wall of the sacral canal. Under the microscope intraoperation, the shape of the nerve roots inside cysts or leakage track of the cysts without nerve roots were verified and explored. After the reinforcement and shaping operation, several reexaminations of multiple dimensional reconstruction MRI were performed to understand the deformation of the nerve root and hydrops in the operation cavity, so as to formulate a persona-lized rehabilitation plan for the patients. RESULTS: Among the 92 patients with sacral mengingeal cyst, 58 (63.0%) cysts with nerve root cyst, 29 (31.5%) cysts without nerve root cyst, and 5 (5.4%) cysts with mixed sacral canal cyst. In 58 patients with nerve root cysts, the accuracy of preoperative clinical classification on MRI image reached 96.6% (56/58) through confirmation by operating microscope. Only 2 cases of large single cyst with nerve root on the head of cyst were mistaken for without nerve root type. In 29 patients with sacral cyst without nerve root, the accuracy of preoperative image reached 100% through confirmation by operating microscope. The accuracy of judging the internal nerve root and leakage of 12 cases with recurrent sacral cyst was also 100%. Two cases of delayed postoperative hydrops were found one month after operation. After rehabilitation treatment by moxibustion and bathing, the hydrops disappeared 4-6 months after operation. CONCLUSION Multiple dimensional reconstruction MRI can precisely make clinical classification of sacral meningeal cysts before operation, guide minimally invasive neurosurgery effectively, and improve the rehabilitation effect.
Humans ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Sacrum/surgery* ; Adult ; Middle Aged ; Imaging, Three-Dimensional/methods* ; Cysts/rehabilitation* ; Aged ; Adolescent ; Young Adult ; Spinal Nerve Roots/diagnostic imaging* ; Minimally Invasive Surgical Procedures ; Neurosurgical Procedures/methods*

OBJECTIVE: To investigate the clinical value of MRI modified water-lipid separation technique (mDIXON-Quant) in terms of T2* values and fat fraction (FF) values for evaluating the degree of cervical intervertebral disc degeneration. METHODS: A total of 118 patients who underwent routine MRI of the cervical vertebra and the mDIXON-Quant examination in Fuyang People's Hospital from March 2019 to January 2024 were collected. The T2* values of C2/3 to C6/7 intervertebral discs and FF values of the upper and lower vertebral bodies were measured. Cervical intervertebral disc degeneration was graded according to the Pfirrmann criteria. The T2* values and FF values of different patients were compared with the Pfirrmann grades, and the correlation between T2* values, FF values, and Pfirrmann grades was analyzed by Spearman correlation. RESULTS: The T2* values of cervical intervertebral discs in grades I, II, III, IV, and V all showed a decreasing trend ( P＜0.05). The decreasing order of FF values in the upper cervical vertebra was IV, V, III, II, and I ( F=93.28, P＜0.05), and the decreasing order of FF values in the lower cervical vertebra was IV, III, V, II, and I ( F=112.037, P＜0.05). Spearman correlation analysis showed that the T2* values of cervical intervertebral discs were negatively correlated with the Pfirrmann grades ( P＜0.05), and the FF values of the upper and lower vertebrae were positively correlated with the Pfirrmann grades ( P＜0.05). CONCLUSION The mDIXON-Quant technique can be used to quantify the T2* values and FF values of cervical intervertebral disc degeneration and plays an important role in accurate clinical diagnosis and evaluation of treatment effects.
Humans ; Intervertebral Disc Degeneration/diagnostic imaging* ; Cervical Vertebrae/diagnostic imaging* ; Magnetic Resonance Imaging/methods* ; Male ; Female ; Middle Aged ; Adult ; Intervertebral Disc/diagnostic imaging* ; Lipids