Chinese Journal of Magnetic Resonance Imaging RSS feed

Review on the application of MRI functional and quantitative imaging techniques in the diagnosis and treatment of cervical cancer

Tue,20 Aug 2024 00:00:00 GMT

Cervical cancer (CC) is the fifth most common cancer among women in our country, and the incidence is tending to be younger, which seriously threatens the life and health of women. The treatment plans for different stages and risks are not the same, and with the popularization of fertility preserving surgical treatment, higher requirements are placed on accurate preoperative staging and risk assessment. Magnetic resonance imaging (MRI) is an important method for the diagnosis, staging and efficacy evaluation of CC. However, the diagnosis and evaluation of CC by conventional MRI sequences are limited by subjective experience and lack of objective quantification, resulting in poor accuracy. New technologies, such as MRI functional imaging and quantitative imaging, can provide accurate quantitative information in multiple dimensions, including hemodynamic changes, varies in tissue microstructure, tumor hypoxia environment, cell proliferation and protein metabolism, which can be used for accurate preoperative diagnosis and risk assessment of CC and provide a visual basis for the comprehensive understanding of the pathophysiology and metabolism of tumors. Mining big imaging data by artificial intelligence can help solve clinical problems. This article will review the application progress of MRI functional imaging and quantitative imaging in the diagnosis and treatment of CC, aiming at clinical problems such as the staging, efficacy and recurrence assessment of CC, so as to promote its clinical application and improve the level of diagnosis and treatment.

A preliminary application study of magnetic resonance elastography in the diagnosis of cervical cancer

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo explore the clinical value of magnetic resonance elastography (MRE) in cervical cancer. Materials and MethodsIn this prospective study, a total of 39 patients diagnosed with cervical cancer (cervical cancer group) were prospectively recruited, along with 39 healthy female volunteers (control group) matched for age and body mass index (BMI). The participants underwent routine cervical MRI and MRE examinations with a frequency of 60 Hz. The stiffness values of the cervix were measured in both groups, along with the volume and depth of infiltration of tumors in the cervical cancer group, were measured. Tumor staging was collected for patients in the cervical cancer group. A paired sample t-test was used to compare the elasticity values between the cervical cancer group and the healthy control group. Spearman^{^,}s rank correlation coefficient and receiver operating characteristic (ROC) curve analysis were conducted to assess the correlation between stiffness values, tumor volume, infiltration depth, and cervical cancer staging, as well as the diagnostic efficiency of staging cervical cancer. ResultsThe average stiffness value of the cervical cancer group [(5.76±0.99)] kPa was significantly higher than the healthy control group [(2.94±0.25) kPa; P<0.001]. Stiffness values, tumor volume, and infiltration depth showed statistically significant differences between early (≤ⅡA stage) and advanced stage (≥ⅡB stage) cervical cancer and were positively correlated with cervical cancer staging (r=0.439, 0.384, 0.322; P<0.05). The diagnostic efficacy of stiffness values was superior to tumor volume and infiltration depth, with the area under the curve (AUC) of ROC for stiffness values (0.754) > tumor volume (0.722) > infiltration depth (0.687). ConclusionsMRE technology can serve as a non-invasive adjunct diagnostic tool for the diagnosis and staging of cervical cancer, holding potential clinical application prospects in the research and formulation of treatment strategies for cervical cancer.

Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in locally advanced cervical squamous cell carcinoma

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo establish a radiomics model based on pre-treatment multi-parametric magnetic resonance imaging (MRI) combined with clinical factors for early prediction of lymph node metastasis in patients with locally advanced cervical squamous cell carcinoma (LACSCC) after neoadjuvant chemotherapy (NACT). Materials and MethodsThe baseline radiological image and case data of 265 LACSCC patients who received NACT and radical hysterectomy from January 2013 to Febrary 2022 in two centers were retrospectively analyzed. The data of center 1 were used for training, and the data of center 2 were used for validation. All patients underwent pelvic MRI before NACT. Radiomics features were extracted from sagittal T2-weighted imaging (Sag_T2WI), axial diffusion-weighted imaging (Ax_DWI) and sagittal delayed T1-weighted contrast-enhanced imaging (Sag_T1C). The K-Best and least absolute shrinkage and selection operator (LASSO) were used to reduce the dimension and screen out the radiomics features strongly related to lymph node metastasis. Three single-sequence models were constructed based on the radiomics features selected from each sequence. Correlation analysis was performed among all features, excluding highly correlated radiomics features, and multivariate regression analysis was performed on clinical variables, which were combined to construct the clinical-radiomics model. Model performance was compared using receiver operating characteristic (ROC) curves and decision curve analysis (DCA) to evaluate diagnostic performance and clinical efficacy. ResultsSix, three, and seven radiomics features were screened out from Sag_T2WI, Ax_DWI, and Sag_T1C sequences, respectively, which were highly correlated with lymph node metastasis, including 4 shape features and 12 texture features, of which 2 shape features and 10 texture features were included in the combined model. Multivariate logistic regression analysis showed that radiological lymph node status (LNr) was a correlative factor of lymph node metastasis (P<0.05). Compared with the single-sequence model, the combined model had better predictive ability and the highest diagnostic ability in the training and validation sets, the area under the curve (AUC) of ROC, sensitivity and specificity were 0.848 [95% (confidence interval, CI): 0.785-0.912], 78.2%, 74.4% and 0.827 (95% CI: 0.737-0.917), 80.8%, 69.4%, respectively. DCA showed that if the risk threshold exceeded 60%, the combination model could obtain greater clinical benefit in predicting lymph node status of LACSCC patients after NACT. ConclusionsBased on pre-treatment MRI, the combination of the radiomics features of Sag_T2WI, Ax_DWI, and Sag_T1C sequences and clinical information can predict lymph node metastasis after NACT in LACSCC patients.

Prediction of lymphovascular space invasion in locally advanced cervical cancer patients after neoadjuvant chemotherapy based on pre-treatment multi-parameter MRI radiomics features

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo develop a model utilizing radiomic features from pre-treatment multiparametric magnetic resonance imaging (mpMRI) to predict lymphovascular space invasion (LVSI) status after neoadjuvant chemotherapy (NACT) in locally advanced cervical cancer (LACC). Materials and MethodsA retrospective analysis was conducted on clinical and imaging data of 300 patients with locally advanced cervical cancer (LACC) who underwent neoadjuvant chemotherapy (NACT) followed by radical hysterectomy. These patients were divided into a training set (187 patients, with 73 LVSI positive cases) from Henan Provincial People^{^,}s Hospital and a validation set (113 patients, with 31 LVSI positive cases) from Henan Provincial Cancer Hospital. Tumor regions of interest (ROIs) were delineated on axial diffusion-weighted imaging (Ax_DWI), sagittal T2-weighted imaging (Sag_T2WI), and sagittal T1-weighted contrast-enhanced imaging (Sag_T1C), and features were extracted. Radiomic features were selected using recursive feature elimination (RFE) algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. Subsequently, single-sequence models, dual-sequence models, and combined model based on three-sequence radiomic features were established using logistic regression classifiers. The performance of each model was evaluated using receiver operating characteristic (ROC) curves, with area under the curve (AUC) compared using the Delong test. Clinical utility was assessed using decision curves. ResultsIn the validation set, the AUCs of the single-sequence models constructed based on Ax_DWI, Sag_T2WI, and Sag_T1C were 0.717 [95% confidence interval (CI): 0.605-0.829], 0.734 (95% CI: 0.633-0.836), and 0.733 (95% CI: 0.626-0.841) respectively. The AUCs of the dual-sequence models constructed based on Ax_DWI+Sag_T2WI, Ax_DWI+Sag_T1C, and Sag_T2WI+Sag_T1C were 0.763 (95% CI: 0.660-0.866), 0.786 (95% CI: 0.692-0.881), and 0.815 (95% CI: 0.731-0.899) respectively. The AUC of the combined model was 0.829 (95% CI: 0.740‍-‍0.914), which was higher than that of the single-sequence and dual-sequence models, however, the difference in AUC between the combined sequence model and the Ax_DWI model, Sag_T2WI model, as well as the Ax_DWI+Sag_T2WI model was not statistically significant (P=0.015‍-‍0.047). Decision curves showed that the clinical net benefit of the joint-sequence model was higher than that of the single-sequence and dual-sequence models. ConclusionsThe combined model constructed based on pre-treatment multiparametric MRI radiomic features can effectively predict the LVSI status after NACT in LACC patients based on pre-treatment mpMRI.

The radiomics model based on APT for preoperative prediction of cervical cancer lymphovascular space invasion

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo explore the value of amide proton transfer weighted imaging (APTw) radiomics in the preoperative assessment of lymphovascular space invasion (LVSI) in cervical cancer. Materials and MethodsRetrospective analysis of 66 cases of pathologically confirmed cervical cancer and their imaging data. All patients underwent pelvic 3.0 T MRI examination, including axial T2WI, sagittal T2WI, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), and 3D-APTw sequence scanning. Region of interest (ROI) within the tumor parenchyma were delineated on the APTw-T2WI fusion images, and APT values were recorded. Tumor lesions were segmented on the reconstructed APTw images, and radiomics features were extracted. Intra-class correlation coefficient (ICC) was employed to select radiomics features with good test-retest reliability both intra- and inter-observer assessments (ICC>0.900). Recursive feature elimination (RFE) and least absolute shrinkage and selection operator (LASSO) algorithms were employed for feature dimensionality reduction and selection. A clinical model, APTw radiomics model and combined model were constructed based on logistic regression classifier. The diagnostic performance and clinical utility of the models were evaluated using receiver operating characteristic (ROC) curves and decision curve analysis (DCA). The predictive performance of different models was compared using the DeLong test. ResultsIn the training set, the APTw radiomics model demonstrated higher efficacy in predicting cervical cancer LVSI compared to the clinical model (AUC=0.826 vs. 0.675), with statistically significant differences (DeLong test P<0.05). In the training set and the test set, the AUC values of the combined model were 0.838 and 0.825, respectively. DeLong test results showed that the combined model significantly outperformed the clinical model and APTw radiomics model in preoperative assessment of LVSI in the training set (all P<0.05). The decision curve demonstrated that the APTw radiomics model and the combined model exhibit higher clinical utility in both the train and test sets. ConclusionsThe radiomics model based on the APTw shows great potential in preoperatively predicting the LVSI status of patients with cervical cancer. Integration with clinical factors further enhances predictive performance, holding prospects to provide crucial support for individualized treatment and prognosis assessment of cervical cancer patients.

The value of amide proton transfer weighted combined with dynamic contrast-enhanced MRI in evaluating cervical cancer nerve invasion

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo explore the value of amide proton transfer weighted (APTw) combined with dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) sequence in evaluating perineural invasion (PNI) of cervical cancer. Materials and MethodsA retrospective analysis was conducted on 36 patients who underwent pelvic 3.0 T MRI examination (including APTw and DCE-MRI sequences) and were confirmed to have cervical cancer by surgical pathology. Among them, there were 12 cases in the PNI group and 24 cases in the non-PNI (NPNI) group. Two observers measured the APT value and DCE-MRI quantitative parameter values of the lesion, including volume transfer constant (K^trans), exchange rate between EES and blood plasma (K_ep), extravascular volume fraction (V_e), and capillary plasma volume (V_p). The mean of the measurements was then taken for statistical analysis. Using intra-class correlation coefficient (ICC) to test the consistency of the measurement results of two observers for each parameter value; Kolmogorov-Smirov test was used to determine whether the data conforms to a normal distribution. Two independent sample t-tests or Mann-Whitney U-tests were used to compare the differences in parameter values between the two groups. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the parameters with differences, and the corresponding area under the curve (AUC), threshold, sensitivity, and specificity were obtained. Calculate the joint diagnostic efficacy of differential parameters using binary logistic regression, and compare the AUC of each parameter and the joint parameter using DeLong test. Use Spearman correlation to detect the correlation between APT values and differential DCE-MRI parameters. ResultsThe APT values, K^trans values, K_ep values, V_e values, and V_pvalues measured by the two observers showed good consistency, with ICC values greater than 0.75. The difference in APT and V_p values between the two groups was statistically significant (P<0.05), while the difference in K^trans, K_ep, and V_e was not statistically significant (P>0.05). The APT value (2.89%±0.72%) and V_p value [7.80×10^-3 (6.80×10^-3, 1.14×10^-2)] of the PNI group were both higher than those of the NPNI group [APT value 2.31% ± 0.71%; V_p value 4.19×10^-3 (2.04×10^-3, 7.35×10^-3)]. The AUC for evaluating the APT value and V_pvalue of cervical cancer PNI were 0.717 and 0.785, respectively; the thresholds are 2.7% and 6.46×10^-3, respectively, and the sensitivity and specificity are 66.7% and 75.0%, 83.3% and 75.0%, respectively. The AUC of APT value combined with V_p value is 0.792; there was no statistically significant difference (P>0.05) between the APT value, V_p value, and the AUC of the combined evaluation of PNI. There is no correlation between APT value and V_p value (r=0.219, P=0.198). ConclusionsThe quantitative parameters of APTw sequence and DCE-MRI can effectively predict cervical cancer PNI, which has certain clinical application value.

Intra- and peritumoral sagittal T2WI radiomics nomogram for preoperative prediction of patients with stage ⅠB and stage ⅡA cervical cancer

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveA comprehensive nomogram based on radiomics signature and clinical risk factors in the intra-and peritumoral regions of T2 weighted imaging (T2WI) was developed for the prediction of ⅠB and ⅡA stage in cervical cancer. Materials and MethodsA total of 120 patients with stage ⅠB and ⅡA cervical cancer, who underwent preoperative MRI and radical hysterectomy with systematic pelvic lymph node dissection, were analysed retrospectively from two hospitals, and then randomly divided into training (n=80) and external validation groups (n=40). Intra- and peritumoral features (0-6 mm) were extracted separately in T2WI and selected by the Pearson analysis and the least absolute shrinkage and selection operator (LASSO) regression. Radiomic models were built using the best selected features from different regions. Receiver operating characteristic (ROC) was drew and the prediction performance of multi-regional radiomic models was built. Finally, the optimal peritumoral region was selected and the nomogram was developed combining the optimal peritumoral radiomics signature and the most predictive clinical parameters. The calibration degree of the model was evaluated by calibration curve and the application value of the model was evaluated by decision curve analysis (DCA). ResultsSix effective radiomics features, selected from the peritumoral regions with 3 mm distances in the T2WI, had the best predictive performance, achieving an area under curve (AUC) of 0.972 and 0.857 in the training and validation groups, respectively. The prediction efficiency of the model based on the maximum diameter and red blood cell (RBC), which were the clinical independent risk factors, is next, achieving an AUC of 0.940 and 0.847 in the training and validation groups, respectively. The prediction efficiency of the nomogram based on the maximum diameter, red RBC and six effective radiomics features from the peritumoral regions with 3 mm distances was more stable, achieving an AUC of 0.952 and 0.939 in the training and validation groups, respectively. The nomogram, tested by calibration curve and DCA, had the higher calibration and greater net clinical benefit. ConclusionsThe nomogram that was developed by intra- and peritumoral regions with 3 mm distances radiomics was excellent for the preoperative prediction of ⅠB and ⅡA stage in cervical cancer. It is important clinical significance to guide the individual treatment of patients.

Altered brain morphometry and structural covariant networks based on cortical thickness in Alzheimer^{^,}s disease

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo investigate the alteration of cerebral grey matter volume and cortical thickness and structural covariance network (SCN) based on cortical thickness in patients with Alzheimer^{^,}s disease (AD). Materials and MethodsIn this study, a total of 100 patients with AD and 150 healthy controls (HCs) were included. Firstly, we conducted voxel-based morphometry (VBM) and surface-based morphometry (SBM) analysis in Computational Anatomy Toolbox 12 (CAT12) to acquire grey matter volume and cortical thickness. Subsequently, partial correlation analysis was applied to explore the correlation between brain regions with statistical differences and cognitive scales. Lastly, we constructed the SCN based on cortical thickness and analyzed its alternation of topology properties by graph theory analysis. ResultsFirstly, we observed the decreased grey matter volume and cortical thickness in patients with AD [P-values after family-wise error (FWE) correction, P_FWE-corr<0.001]. The volumetrically decreased brain regions included bilateral hippocampus, bilateral orbitofrontal cortex, left insula, right inferior occipital gyrus,left precuneus, left precentral gyrus, left middle cingulate gyrus. The cerebral regions with thinner cortical thickness in AD group included bilateral temporal lobe, frontal lobe, parietal lobe, cingulate gyrus, fusiform gyrus, insula, precuneus, et al. Secondly, partial correlation analysis in AD group showed that Mini-Mental State Examination (MMSE) scores were respectively positively correlated to the volumes of right hippocampus [r_s=0.35, P-values after false discovery rate (FDR) correction, P_FDR-corr<0.001], left hippocampus (r_s=0.38, P_FDR-corr<0.001), the thickness of right fusiform gyrus (r_s=0.38, P_FDR-corr<0.001), and the clinical dementia rating sum of boxes (CDR-SB) scores was negatively correlated to the thickness of left fusiform gyrus (r_s=-‍0.39, P_FDR-corr<0.001). Lastly,in SCN analysis, we found the global efficiency (P<0.001), local efficiency (P=0.03), sigma (P<0.001) were higher in AD patients compared to HCs, while the shortest path length (P<0.001) was lower in AD patients. ConclusionsThe combination of morphological analysis by VBM and SBM and SCN analysis by graph theory was helpful to comprehensively understand the reconfiguration of brain networks and its significance, and thus provided new insights and evidence for neuroimaging changes in AD patients.

A resting-state functional magnetic resonance imaging study of abnormal brain function in patients with Internet gaming disorder

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo explore the changes of local intrinsic brain connectivity in the resting state of Internet gaming disorder (IGD) using a combination of regional homogeneity (ReHo) and functional connectivity (FC). Materials and MethodsResting-state functional magnetic resonance imaging (rs-fMRI) was performed on 44 patients with IGD and 49 healthy controls with matching age, sex, and years of education. The ReHo of the two groups was calculated and compared to detect the changes of local connections in the brain of IGD patients. FC was performed with ReHo abnormal brain regions to obtain changes in the connectivity of different brain regions. The Internet Addiction Test (IAT) was used to assess the severity of Internet gaming disorder. Pearson correlation analysis was used to assess the relationship between brain regions with ReHo alterations and IAT scores. ResultsIn the IGD group, the bilateral medial superior frontal gyrus, bilateral dorsolateral superior frontal gyrus, left auxiliary motor area, and right middle frontal gyrus increased ReHo. Left inferior occipital gyrus, left middle occipital gyrus, left lingual gyrus, left calcarine sulcus cortex, left fusiform gyrus, left superior temporal gyrus, and left cerebellar ReHo are reduced (voxel level P<0.005, mass level P<0.05, Gaussian random field correction). In the IGD group, the functional connectivity of the right dorsolateral superior frontal gyrus and the right superior frontal gyrus, bilateral accessory motor areas, and right precentral gyrus was increased (voxel level P<0.005, mass level P<0.05, Gaussian random field correction). In addition, the ReHo value of the cortex around the left calcarine sulcus cortex was negatively correlated with the IAT score. ConclusionsAlterations in local connections in the prefrontal cortex and temporal-occipital cortex may indicate that cognitive control and reward processing and visual and auditory networks in IGD have been affected. In addition, the ReHo value of the cortex around the left calcarine sulcus cortex was negatively correlated with the IAT score, which may provide a new understanding of the neuropathological mechanism of IGD.

Research on aquaporin magnetic resonance molecular imaging of hippocampal subfields in Alzheimer^{^,}s disease

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveThis study applied aquaporin magnetic resonance molecular imaging (AQP-MRMI) technology to quantitatively analyze the hippocampal subfield, aiming to explore the application value of AQP-MRMI technology in the diagnosis of Alzheimer^{^,}s disease (AD). Materials and MethodsA total of 59 subjects were included in this study, including 16 subjects in the AD group and 22 subjects in the mild cognitive impairment (MCI) group, and 21 subjects in the normal control (NC) group. Aquaporin apparent diffusion coefficient (AQP-ADC) values were measured and recorded to analyze whether the differences in AQP-ADC values among the three groups were statistically significant, and correlation analysis was conducted with cognitive scores. The receiver operating characteristic (ROC) curve of AQP-ADC values was drawn, and the area under the sensitivity and specificity curve and diagnostic threshold were analyzed. ResultsThere were statistical differences in AQP-ADC values of all hippocampal subfields except the right entorhinal cortex among the three groups (P<0.05). Compared with the NC group, the MCI group only showed increased AQP-ADC value of cornu ammonis-1 (CA1) on the left side (P<0.05), the AD group showed increased AQP-ADC values of bilateral dentate gyrus (DG) -CA4, bilateral CA1-3, bilateral para-hippocampus and left entorhinal cortex (P<0.05); compared with the MCI group, the AQP-ADC values of bilateral DG-CA4, bilateral CA1-3, right subiculum and right para-hippocampus in AD group were increased (P<0.05). The AQP-ADC values of all hippocampal subfields were negatively correlated with the total score of Mini-Mental State Examination (MMSE), except for the right subiculum, and the left DG-CA4 (r=-0.607, P<0.001) and the left CA1-3 (r=-0.633, P<0.001) showed a significant correlation with MMSE. The ROC curve analysis showed that AQP-ADC values of multiple hippocampal subfields region of interest (ROI) could be used to identify NC and AD, MCI, among which the AQP-ADC values of left DG-CA4 and left CA1-3 had the largest area under the curve (AUC=0.905, 0.940) between NC and AD group with high sensitivity and specificity. ConclusionsIn this study, AQP-ADC values in several hippocampal subfields were correlated with cognitive function, especially the left DG-CA4 and left CA1-3 subregions, which helped evaluate the severity of cognitive impairment and had superior diagnostic efficacy in distinguishing AD from cognitively normal elderly people, and could be used as biomarkers for the detection of AD. The AQP-ADC values of the left CA1 may be expected to be a potential biomarker for early AD. AQP-MRMI, as an emerging aquaporin molecular imaging technology, can reflect the pathophysiological changes of AD, and provide more information for the diagnosis, treatment, and prognosis assessment of AD at the molecular level.

Study on cerebral perfusion characteristic network of type 2 diabetes mellitus patients based on MR arterial spin labeling imaging

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo analyze the cerebral microcirculation blood flow perfusion and perfusion patterns in patients with type 2 diabetes mellitus (T2DM) by using MR arterial spin labeling (ASL), and to analyze the correlation between these changes and biochemical indexes. Materials and MethodsTwenty-eight patients who met our T2DM diagnostic criteria and 26 healthy control (HC) were selected in this study. We conducted ASL, principal component analysis, and calculated the cerebral blood flow (CBF) and perfusion feature network on subjects. ResultsCompared with HC group, the perfusion areas including bilateral paracentral lobules, left supplementary motor area, the middle bilateral gyrus cinguli, left opercular part of the inferior frontal gyrus, left middle temporal gyrus, and left inferior temporal gyrus in diabetic patients were significantly lower (P<0.05, GRF adjusted). The ratios of the variance components of the two disease-related perfusion networks to the total variance were 17.6% and 11.7% (95% confidence interval), and they were statistically significant. The first perfusion network characteristic expression value was significantly positively correlated with fasting blood glucose (r=0.32, P=0.001), and the extracted CBF of the diabetic group using the second perfusion characteristic network as a template was negatively correlated with the patient^{^,}s fasting blood glucose (r=0.12, P =0.03). ConclusionsThe diabetic patients had low regional cerebral blood flow. Principal component-based perfusion characteristics can identify patients with diabetes. The changes in perfusion patterns reflected the remodeling of cerebral blood flow perfusion, which had more important value and significance for the early diagnosis and intervention of diabetic microangiopathy.

Evaluation of rest-state fMRI in patients with lumbar disc herniation based on ALFF

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo analyze the changes in resting-state functional magnetic resonance imaging (rs-fMRI) in patients with lumbar disc herniation (LDH) and explore potential neuroimaging mechanisms. Materials and MethodsA total of 24 LDH patients were prospectively included, along with 30 chronic nonspecific low back pain patients (CNLBP) and 27 healthy controls (HC) as the control group. First, the LDH group and CNLBP group underwent Visual Analog Scale (VAS), Oswestry Disability Index (ODI), and Japanese Orthopedic Association (JOA) assessments. Then, all three groups underwent rs-fMRI scanning, and the differences in amplitude of low-frequency fluctuation (ALFF) values among the three groups were compared. Finally, the ALFF values of the brain regions differed between the LDH group and CNLBP group were extracted and correlated with the clinical scales. ResultsThe clinical scale evaluation results showed that there was no difference in VAS scores between the LDH group and CNLBP group, but there were differences in ODI and JOA scores, indicating that LDH patients had more severe lumbar dysfunction. The brain regions with altered ALFF values among the three groups were bilateral calcarine/cuneus cortex, left thalamus (GRF correction, P<0.005 at voxel level, P<0.01 at cluster level). Compared with the HC group, the LDH group had decreased ALFF values in the bilateral calcarine/cuneus cortex, and increased ALFF values in the left thalamus; the CNLBP group had decreased ALFF values in the bilateral calcarine/cuneus cortex but no increased ALFF values. Compared with the CNLBP group, the LDH group had increased ALFF values in the left thalamus but no decreased ALFF values. No correlation was found between the ALFF values of the brain regions differed between the LDH group and CNLBP group and the clinical scales. ConclusionsPatients with LDH have both shared and unique pain central regulatory mechanisms with CNLBP patients.The change of left thalamic functional activity may be an important characteristic of the LDH central mechanism.

Preliminary study of MK parametric map based on DKI technique in evaluating brain microstructural damage and cognitive impairment in patients with moderate and severe OSA

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveThe mean kurtosis (MK) of diffusion kurtosis imaging (DKI) was used to investigate the changes of brain microstructural integrity and its relationship with neurocognitive impairment in adult patients with moderate and severe obstructive sleep apnea (OSA), and to explore the potential neuropathological mechanism of cognitive impairment in OSA patients. Materials and MethodsA total of 40 patients with moderate and severe OSA (OSA group) and 40 healthy controls (control group) were collected. Age, sex and years of education were matched between the two groups. Cognitive function evaluation and MRI examination were performed. The gray and white matter regions of the whole brain on the MK parameter map were extracted quantitatively by post-processing program. The differences of MK values in different brain regions between the two groups were compared. Partial correlation analysis was used to analyze the correlation between MK values and respiratory sleep parameters and cognitive scores in OSA group. ResultsCompared with the control group, the MK values of 20 brain regions in the OSA patient group were decreased, including the bilateral precentral and postcentral cortex, the left cingulate, and the hippocampus, etc, and the difference was statistically significant (P<0.05, FDR correction). The total score of Montreal Cognitive Assessment (MoCA), the scores of visual space and executive function, abstract and delayed recall in the OSA group were significantly lower, the difference was statistically significant (P<0.05). The results of partial correlation analysis showed that the lowest oxygen saturation (LSaO₂) was positively correlated with the MK of the right precentral gyrus, postcentral gyrus and bilateral parietal cortex (r=0.446, 0.350, 0.456, 0.442, P<0.05) in OSA group. The delayed recall score was positively correlated with the MK of the left hippocampus (r=0.353, P<0.05). ConclusionsDKI imaging can sensitively detect the microstructural damage of brain tissue in patients with moderate and severe OSA, and the abnormal microstructural changes in some brain regions are related to cognitive dysfunction, which provides imaging basis for exploring the neuropathological mechanism of cognitive impairment in patients with OSA.

Clinical study of hypertension-related brain volume and white matter hyperintensity changes based on multimodal MRI

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveThe volume and white matter hyperintensities (WMH) in the brain were studied,based on voxel-based morphometry (VBM) and semi-quantitative assessment of WMH in hypertensive patients. Materials and MethodsThis retrospective study included confirmed hypertensive cases and healthy control cases from Suzhou Science and Technology City Hospital Affiliated to Nanjing University from January 2018 to November 2022. All enrolled cases underwent thin layers T1WI sequence examination. Firstly, images were imported into the brain structure EKM-KELM⁺ classification algorithm model to calculate gray matter volume (GMV), white matter volume (WMV) and total intracranial volume (TIV). The gray and white matter volume of each brain region was expressed as the ratio of GMV/TIV and WMV/TIV, respectively, to analyze the variation characteristics of brain gray matter volume in hypertensive patients of different ages. At the same time, Scheltens Visual Quantitative Assessment of WMH was performed on fluid attenuated inversion recovery (FLAIR) images. Results(1) A total of 509 cases were included in this study, including 91 cases in the normal blood pressure group and 418 cases in the hypertension group. Among them, 136 cases were young (20-40 years old), 218 cases were middle-aged (41-60 years old) and 155 cases were elderly (61-80 years old). There were no significant differences in gender and age within groups (all P>0.05). (2) There were significant differences among hypertension grades in GMV/TIV of the left olfactory cortex (P=0.031), left straight gyrus (P=0.036), right straight gyrus (P=0.022), and right inferior occipital gyrus (P=0.011) in young patients. (3) The comparison of GMV/TIV in the middle-aged group showed that there was significant difference in the volume of the left supplementary motor area among different hypertension levels (P=0.036), while there was no significant difference in WMV/TIV. (4) GMV/TIV comparison showed that there was significant difference in right olfactoid cortex volume among different hypertension grades (P=0.047), while there was no significant difference in WMV/TIV. (5) Scheltens visual score showed that there was no significant difference in the young group (P>0.05). In the middle age group, there were statistically significant differences in the high signal of voidural quality (frontal angle, occipital angle and lateral ventricle) (P=0.028, 0.032, 0.020), and statistically significant differences in deep white matter (frontal lobe) (P=0.024). There was significant difference in the frontal Angle, frontal lobe and pallidum WMH in the old group (P=0.022, 0.024, 0.015). ConclusionsMulti modal semi-quantitative analysis of MRI can effectively evaluate changes in BVM and WMH in hypertensive patients.With the increase of blood pressure level, the gray matter volume of the young group changed more than that of the middle and old group. WMH was more likely to appear in the middle-aged group than in the young group.

Exploring the cut-off age value of marrow transformation in children^{^,}s clivus by MRI

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo analyze the characteristics of MRI of normal slopes in children, and to explore the cut-off age value for the onset of marrow transformation of the clivus in children, so as to better identify myelopathy. Materials and MethodsThe children who underwent cerebral magnetic resonance examination in the Department of Radiology of our hospital from April 2022 to October 2023 were selected as the research objects. By analyzing the relationship between the characteristics of normal clivus^{^,}s signal and age distribution in 2141 children, the age standard of the beginning of marrow transformation in children^{^,}s clivus was explored. The signal characteristics of the clivus were observed on the median sagittal plane of the craniocerebral MRI T1WI sequence, and the age distribution characteristics of non-transformation and transformation were analyzed. Youden index was calculated and the receiver-operating chatacteristic (ROC) curve was drawn to explore the cut-off age value of the beginning of marrow transformation in children^{^,}s clivus. ResultsAmong the 2141 children, 1339 were boys and 802 were girls. Among 1339 boys, 521 boys (1 month-36 months) had clivus with non-transformated marrow and 818 boys (4 months-180 monts) had clivus with transformated marrow. Among the 802 girls, 326 girls (1 month-35 months) had clivus with non-transformated marrow and 476 girls (5 months-201 months) had clivus with transformated marrow. When the boy was 13.5 months old, the Youden index was the highest (0.814), and the area under ROC curve was the largest [0.976 (95% CI: 0.969-0.982)]. When the girl was 11.5 months old, the Youden index was 0.836 and the area under the ROC curve was 0.980 (95% CI: 0.973-0.987). ConclusionsThe age of boys >13.5 months can be regarded as the cut-off age value of marrow transformation of the clivus. The age of girls was >11.5 months, which could be used as the cut-off age value of marrow transformation of the clivus. Marrow transformation begins later in boys than in girls.

Differentiation of high-grade glioma and metastatic tumor based on MRI radiomics and semantic features

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo combine traditional MRI sequences and enhancement scans, extract multimodal high-throughput radiomics features along with semantic features, and use different learning classifiers to construct various models and draw Normogragh for the differentiation of high-grade glioma (HGG) and solitary brain metastasis (SBM). Materials and MethodsThis study retrospectively analyzed multiparametric MRI images of 101 patients. Tumor region of interest (ROI) were delineated by two experienced physicians, and 107 sets of radiomic features for each sequence were extracted using the Pyradiomics software package. To eliminate variability in manual delineation, an intraclass correlation coefficient (ICC) consistency test was carried out. The features with the highest relevance were selected using the maximum relevance minimum redundancy algorithm, and then redundant features were further eliminated using the least absolute shrinkage and selection operator method. Classification models were established using four algorithms: support vector machine, logistic regression, random forest, and K-nearest neighbors. Combining seven semantic features evaluated by radiologists, chi-square test and multivariate analysis were used to remove semantically irrelevant features. Then, a comprehensive model incorporating both radiomics and semantic features was formed and illustrated using nomogram. Finally, the diagnostic capability of each model was evaluated to determine the optimal classifier. ResultsAmong the radiomics models for HGG and SBM patients, the model with the highest area under the curve (AUC) value was logistic regression, with AUC values of 0.90 for both the training set and test set. In models constructed using semantic features, the random forest model exhibited the best performance, with AUC values of 0.82 and 0.87 for the training and test sets, respectively. After combining semantic features with radiomics scores, the model constructed using logistic regression demonstrated optimal performance, with AUC values of 0.91 and 0.92 for the training and test sets, respectively. ConclusionsThe non-invasive approach proposed in this study that utilizes radiomics machine learning classifiers and combines image semantic features to draw nomogram for differentiating between HGG and SBM, demonstrates good accuracy and provides significant assistance for clinical decision-making and practice.

Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson^{^,}s disease based on SyMRI relaxation quantitative analysis and QSM

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo investigate the clinical application value of synthetic magnetic resonance imaging (SyMRI) and quantitative susceptibility mapping (QSM) in predicting microstructural alterations of substantia nigra (SN) in early Parkinson^{^,}s disease. Materials and MethodsA total of thirty early Parkinson^{^,}s disease (PD) patients with Hoehn-Yahr stages ranging from 1 to 2.5 were prospectively recruited from our hospital and assigned to the PD group, and simultaneously selected 30 healthy subjects as the healthy control (HC) group. All subjects underwent brain SyMRI and QSM scanning. The SyMRI relaxation quantitative maps and QSM maps were extracted, and the T1, T2, proton density (PrD) and QSM values of SN in each quantitative maps were measured. Independent samples t test or Mann-Whitney U test was used to compare the differences in T1, T2, PrD and QSM values of SN between PD group and HC group. Receiver operating characteristic (ROC) curve was plotted to analyze the quantitative parameters as well as a diagnostic efficiency of the joint diagnostic model. The differences of area under the curve (AUC) values were compared by DeLong test. Spearman correlation coefficient was used to analyze the correlation between various relaxation quantitative values and QSM value in PD group. ResultsThere were significant differences in T1, T2, PrD and QSM values between PD group and HC group (P<0.001). The AUC values for T1, T2, PrD, QSM and T1-T2-PrD-QSM joint diagnostic model in distinguishing PD group from HC group were 0.872, 0.788, 0.749, 0.838 and 0.930. There were statistically significant differences in AUC values between T2 value and joint diagnostic model, PrD value and joint diagnostic model, QSM value and joint diagnosis model (P=0.007, 0.004, 0.034). T1 values were positively correlated with QSM values (r=0.436, P=0.016), T2 values were negatively correlated with QSM values (r=-0.364, P=0.048), and PrD values were negatively correlated with QSM values (r=-0.393, P=0.032). ConclusionsQuantitative analysis of SN based on SyMRI and QSM demonstrates promising diagnostic value for early PD, offering distinct quantitative feedbacks into microstructural alterations within the SN. Moreover, integration of relaxation quantitative values and QSM value in a joint diagnostic model can further enhance the diagnostic efficiency, providing objective and quantitative imaging indicators for early PD diagnosis.

Value of a clinical-multiparametric MRI diagnostic model based on Kaiser score in the differential diagnosis of benign and malignant breast lesions

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo establish a clinical-multiparameter breast MRI diagnostic model based on Kaiser score (KS) and explore its value in the diagnosis and differentiation of benign and malignant breast lesions. Materials and MethodsClinical and preoperative MRI data of 389 patients with 403 lesions confirmed by pathology were retrospectively analyzed between January 2019 and December 2022, collected MRI, clinical and pathological data of breast lesions, including 100 cases in benign group and 303 cases in malignant group. Based on MRI image features, apparent diffusion coefficient (ADC) value and related clinical indicators in KS, comparing the differences between the indicators of benign and malignant breast lesions by univariate analysis, multivariate logistic regression analysis established clinical-multiparameter MRI imaging diagnosis model. The receiver operating characteristic (ROC) cruve was plotted to evaluate the diagnostic performance. DeLong test was used to compare the diagnostic efficacy of clinical-multiparameter MRI imaging diagnosis model with the KS. ResultsRoot features, time-signal intensity curves (TIC) type, margin, internal enhancement, edema, ADC value, age, gynecological tumor history, menopausal status between benign and malignant breast lesions with a statistical difference (P<0.001). Multivariate logistic regression analysis showed positive root sign, TIC type Ⅲ, rough margins, old age, and history of gynecological tumors [odds ratio (OR)=7.889, 7.707, 4.398, 1.122, 0.239, P<0.05] was an independent predictor of malignant breast lesions. A clinical-multiparametric MRI imaging diagnostic model was established based on KS correlation characteristics, age, and gynecological tumor history. The ROC curves of KS and clinically-multi-parameter MRI diagnostic models were mapped using benign and malignant breast as criteria. Sensitivity was 97.4% and 91.1%, specificity was 69.3% and 84.2%, respectively. Area under the curve (AUC) values were 0.912 and 0.950. The AUC difference was statistically significant (P=0.006). There were significant differences between the positive and negative ALN metastasis groups in breast cancer root sign (χ²=6.477, P=0.011), peritumoral edema (χ²=12.241, P<0.001), and ADC value (Z=10.988, P=0.015). Multivariate logistic regression analysis showed that peritumoral brain edema (OR=2.807, P=0.006) increased the risk of axillary lymph node (ALN) metastasis, and the presence of peritumoral edema increased the risk of ALN metastasis 2.807 times higher than in patients without this feature. ConclusionsKS has high diagnostic value for breast lesions, the clinical-multiparametric MRI diagnostic model based on KS is subservient to improve the diagnostic efficacy of benign and malignant breast lesions, and the presence of peritumoral edema in the primary breast MRI can be used as an independent predictor of ALN metastasis in breast cancer.

Cardiac magnetic resonance evaluation of myocardial tissue characterization of different left ventricular phenotypes in patients with chronic kidney disease

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo analyze the myocardial strain, native T1 and T2 values of different left ventricular phenotypes in chronic kidney disease (CKD) patients by cardiac magnetic resonance (CMR), and to investigate the myocardial tissue characterization of different left ventricular phenotypes. Materials and MethodsProspective inclusion of 114 CKD patients and 30 age- and gender- matched healthy controls (control group). The scanning sequences included cardiac cine, T1 mapping and T2 mapping sequences. According to the left ventricular remodeling index (LVRI) and left ventricular mass index (LVMI), CKD patients were divided into the following four subgroups: normal geometry (n=43), concentric remodeling (n=22), concentric left ventricular hypertrophy (LVH) (n=20), and eccentric LVH (n=29). Cardiac post-processing software CVI 42 was used to measure left ventricular myocardial strain and strain rate, including global circumferential, radial and longitudinal strain, systolic global circumferential, radial and longitudinal strain rate, diastolic global circumferential, radial and longitudinal strain rate. Native T1 and T2 values were also measured. The myocardial tissue characterization of different left ventricular phenotypes was investigated. Univariate and multivariate linear regression analyses were used to explore the relationship between myocardial tissue characterization and physiological variables. ResultsExcept for global circumferential strain [-18.40% (3.30%) vs. -19.71%±1.66%, P=0.063] and global radial strain (30.63%±7.03% vs. 34.07%±4.61%, P=0.324) in normal geometry group, other myocardial strain parameters in CKD patients were significantly lower than those in control group (all P<0.05). Strain analysis showed that the lowest global radial strain (22.02%±8.31%) was found in the eccentric LVH group. The lowest global circumferential strain (-14.42%±3.24%) and global longitudinal strain (-9.55%±2.79%) were found in the concentric LVH group. Strain rate analysis showed that eccentric LVH group had the lowest systolic global circumferential strain rate [(-0.84±0.25) s^-1], diastolic global circumferential strain rate [(0.73±0.29) s^-1], systolic global radial strain rate [(1.25±0.46) s^-1] and diastolic global radial strain rate [(-1.18±0.50) s^-1]. Concentric LVH group had the lowest systolic global longitudinal strain rate [(-0.62±0.16) s^-1] and diastolic global longitudinal strain rate [(0.53±0.14) s^-1]. There was no significant difference in native T1 values between concentric remodeling group and control group [1 285.50 (85.25) ms vs. (1 262.53±38.18) ms, P=0.083]. Eccentric LVH group had the largest native T1 value, which was significantly higher than that of control group [(1 351.10±58.49) ms, vs. (1 262.53±38.18) ms, P<0.001). Compared with control group, T2 values were significantly increased in all four patient subgroups (all P<0.05), and the T2 value [(54.86±8.71) ms] of eccentric LVH group was the largest. There was no significant difference in T2 values among different subgroups of CKD patients (all P>0.05). Native T1 value was independently correlated with hemoglobin content (adjusted R²=0.216, β=-0.442, P<0.001) and serum creatinine (adjusted R²=0.216, β=‍-‍0.220, P=0.010). ConclusionsCKD patients have decreased myocardial strain and increased native T1 and T2 values. The changes of myocardial tissue characterization are most obvious in patients with eccentric LVH.

Clinical application value of predicting microvascular invasion in hepatocellular carcinoma using intratumoral and peritumoral radiomics models: A multicenter study

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveThe aim of this study was to evaluate the predictive value of intratumoral and peritumoral radiomics models for microvascular invasion (MVI) in hepatocellular carcinoma (HCC). Materials and MethodsGadoxetic acid disodium (Gd-EOB-DTPA) enhanced MRI images of patients with surgically pathologically confirmed HCC at three hospitals between 2016 and 2023 were retrospectively analyzed, as well as seven clinical information, including gender, age, maximum tumor diameter, alpha-fetoprotein (AFP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and the presence or absence of hepatitis B. Intratumoral regions and 5 mm and 10 mm peritumoral regions of interest (ROI) were outlined in arterial phase images, portal venous phase images, and hepatobiliary phase images, from which radiomics features were extracted; in the training cohort, multifactorial logistic regression analysis was applied to screen independent clinical predictors of MVI; support vector machine (SVM) was applied to establish a total of 10 models including intratumoral models, peritumoral models, intratumoral combined peritumoral models, clinical model, and clinical-radiomics combined model. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the models and DeLong test was employed to compare the difference of area under the curve (AUC). ResultsMaximum tumor diameter [dominance ratio (OR): 1.449, 95% confidence interval (CI): 1.212-1.733] and AFP (OR: 1.645, 95% CI: 0.665-4.071) were independent clinical predictors of MVI based on the training cohort. In the validation cohort, the AUCs of the clinical model, intratumoral models, peritumoral models, intratumoral plus peritumoral models, and clinical-radiomics combined model for predicting MVI of HCC were 0.728, 0.764-0.820, 0.791-0.795, 0.804-0.828, and 0.747, respectively, and those of the intratumoral plus 5 mm peritumoral model, intratumoral plus 10 mm peritumoral model were 0.828 (95% CI: 0.728-0.929), 0.804 (95% CI: 0.696-0.913). Among the models, the AUC of the intratumoral plus 5 mm peritumoral model was statistically different from that of the clinical model and the clinical-radiomics combined model (P=0.039, 0.028), and the differences in the AUCs among the rest of the models were not statistically significant (P>0.05). ConclusionsThe Gd-EOB-DTPA-based enhanced MRI radiomics models can be used for preoperative prediction of HCC MVI, in which the intratumoral plus 5 mm peritumoral model has a higher predictive ability for HCC MVI. This model helps in the development of individualized treatment.

Prenatal MRI findings of type I congenital choledochal cyst and parameter measurement of liver and gallbladder

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo observe the MRI findings of type I congenital choledochal cyst (CCC) during the fetal period, analyze the differences in CCC fetal lung-to-liver ratio, liver, spleen, gallbladder, and portal vein measurement parameters compared to normal fetuses. Materials and MethodsFollow-up analysis of clinical data and fetal MRI manifestations of 31 confirmed postnatally operated CCC patients. Observations included the morphology, course, connection with bile duct or gallbladder, relationship between the lower edge of the lesion and the lower edge of the liver, and measurement and calculation of the volume of the choledochal cyst. A control group of 90 healthy fetuses was used for comparison, analyzing differences in fetal lung to liver signal intensity ratio, liver (left and right diameters, upper and lower diameters, maximum cross-sectional area, apparent diffusion coefficient of the liver), spleen (length, thickness, maximum cross-sectional area), gallbladder (length, short diameter, length-to-short diameter ratio, maximum cross-sectional area), and portal vein diameter. The correlation between choledochal cyst volume and MRI measurement parameters was also analyzed. ResultsAmong the 31 CCC patients, there were 9 male fetuses and 22 female fetuses, with a male-to-female ratio of approximately 1∶2.4. Among them, 26 cases had elliptical-shaped lesions, and 5 cases had cystic lesions. In all 31 cases, a pointed angle sign was observed at the upper end of the lesions. The lower edge of the lesions did not exceed the lower edge of the liver in 29 cases, while in 2 cases, the lower edge extended beyond the liver. The course of the lesions in 26 cases was from the upper right to the lower left. There was no statistically significant difference (P>0.05) in fetal lung to liver signal intensity ratio, liver dimensions (left and right diameters, upper and lower diameters, maximum cross-sectional area, apparent diffusion coefficient), spleen dimensions (length, thickness), gallbladder dimensions (length, short diameter, maximum cross-sectional area) between the CCC group and the control group. However, there were statistically significant differences (P<0.05) in the maximum cross-sectional area of the spleen, portal vein diameter, and the ratio of gallbladder length to short diameter between the lesion group and the control group fetuses. Further statistical analysis revealed no correlation (P>0.05) between the volume of the choledochal cyst and the maximum cross-sectional area of the fetal spleen, the ratio of gallbladder length to short diameter, and portal vein diameter. ConclusionsCCC is more common in females. The fetal MRI manifestations include elliptical-shaped lesions, generally not extending beyond the lower edge of the liver. The course of the lesions is often from the upper right to the lower left, with a pointed angle sign at the upper end. The affected fetuses exhibit an enlarged spleen, widened portal vein, and an increased ratio of gallbladder length to short diameter. However, there is no correlation between the volume of the lesion and the maximum cross-sectional area of the fetal spleen, portal vein diameter, and the ratio of gallbladder length to short diameter.

IVIM, mDixon-Quant multiparameter quantitative imaging combined with blood cell parameters to assess Ki-67 expression levels in rectal cancer

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo investigate the application value of intravoxel incoherent motion (IVIM), mDixon‐Quant combined with blood cell parameters in evaluating Ki‐67 expression levels in rectal cancer. Materials and MethodsClinical routine blood count and imaging examination data of 50 patients with clinicopathologically confirmed rectal cancer were retrospectively analyzed. We measured IVIM parameters apparent diffusion coefficient (ADC), pure apparent diffusion coefficient (D), pseudo apparent diffusion coefficient (D^*), perfusion fraction (f) and mDixon‐Quant parameters fat fraction (FF), R2^*, T2^* of the lesion. Independent sample t test or Mann‐Whitney U test was used to compare the differences in the parameters. The efficacy of single and combined parameters in predicting Ki-67 expression status in rectal cancer was evaluated by plotting receiver operating characteristic (ROC) curves and calculating the area under the curve (AUC). Spearman test was used to evaluate the relationship between statistically significant imaging and blood cell parameters between the two groups. ResultsR2^* value, FF value, neutrophil to lymphocyte ratio (NLR), systemic immune inflammation index (SII), systemic inflammatory response index (SIRI) of the Ki‐67 high expression group were higher than those of the Ki-67 low expression group, ADC value, D value of the Ki-67 high expression group were lower than those of the Ki-67 low expression group, and the differences were all statistically significant (P<0.05). The AUC of ADC value, D value, R2^* value, FF value, NLR, SII, SIRI, imaging association parameters (ADC+D+R2^*+FF) and imaging combined with blood cell parameters (ADC+D+R2^*+FF+NLR+SII+SIRI) for evaluating the Ki-67 expression status of rectal cancer were 0.691, 0.775, 0.739, 0.724, 0.784, 0.726, 0.718, 0.839 and 0.906, respectively. The diagnostic efficiency of imaging combined with blood cell parameters was significantly improved compared to single parameters. Spearman test showed a positive correlation between FF values and SII in the Ki‐67 high expression group, and the difference was statistically significant (r=0.525, P=0.012). ConclusionsIVIM, mDixon‐Quantand blood cell parameters are effective in determining Ki‐67 expression levels in rectal cancer, and the imaging combined with blood cell parameters can significantly improve the effectiveness of differential diagnosis. Abnormal lipid metabolism in cancer leads to fat deposition within the tumor lesion, which may cause an inflammatory response to develop.

T2WI-based radiomics for discriminating between ovarian adult-type granulosa cell tumor and ovarian fibroma-thecoma with high-signal intensity on DWI

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo investigate the value of T2WI‑based radiomics nomogram for the preoperative differentiation of ovarian adult-type granulosa cell tumor and ovarian fibroma-thecoma with high-signal intensity on diffusion weighted imaging (DWI). Materials and MethodsThis retrospective study included 29 patients with ovarian granulosa cell tumors and 61 cases with fibroma-thecomas with high-signal intensity on DWI, which were confirmed by surgical pathology in Peking University Third Hospital from January 2019 to October 2023. All tumors were randomly divided into a training set and a validation set at a ratio of 7∶3. The clinical model was constructed by clinical and routine MRI features which were selected by univariate analysis and multivariate logistic regression. Radiomics features were extracted from T2WI. Select K best and least absolute shrinkage and selection operator (LASSO) algorithm were used to reduce the dimension and then the radiomics model was constructed by selected features, and a radiomics score (Rad-score) was calculated. The nomogram model was constructed by combining with clinical model and Rad-score. The receiver operator characteristic (ROC) curves were used to evaluate the performance of three models. The decision curve analysis (DCA) was used to evaluate the clinical value. ResultsThe logistic regression results showed that a "honeycomb" cyst [odds ratio (OR)=0.20, 95% confidence interval (CI)=0.05-0.79, P=0.022] and intratumoral hemorrhage (OR=0.16, 95% CI=0.03-0.98, P=0.048) can be used to construct the clinical model. A total of 9 features were extracted from T2WI to build the radiomics model. Finally, the nomogram model incorporating Rad-score, a "honeycomb" cyst and intratumoral hemorrhage was established. The AUCs of radiomics model and nomogram model were higher than those of clinical model (training set: 0.983 vs. 0.742, Z=-4.058, P<0.001; 0.969 vs. 0.742, Z=-3.817, P<0.001. validation set: 0.858 vs. 0.731, Z=-1.388, P=0.165; 0.883 vs. 0.731, Z=-1.612, P=0.107). There was no significantly difference in AUCs between the radiomics model and nomogram model (training set: Z=-1.040, P=0.298; validation set: Z=0.822, P=0.411). DCA results showed that the nomogram model and radiomics model had higher net benefits than the clinical model. ConclusionsThe MRI-based radiomics model and nomogram model constructed in this study can distinguish ovarian granulosa cell tumor from ovarian fibroma-thecoma with high-signal intensity on DWI effectively, which is better than the conventional T2WI-based clinical model.

The value of magnetic resonance image compilation and T2mapping sequence in the quantitative assessment of chronic supraspinatus tendonitis

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo explore the diagnostic value of magnetic resonance image compilation (MAGiC) and T2mapping sequences in chronic supraspinatus tendinitis, and compare the image quality of the two in supraspinatus tendon scanning, and the T2 values of the two sequences in chronic supraspinatus tendonitis. Correlation of different subregions in supraspinatus tendonitis. Materials and MethodsA retrospective collection of 30 patients with chronic supraspinatus tendonitis (tendinitis group) and 26 healthy persons undergoing physical examination (control group) in our hospital from October 2022 to January 2024, and all underwent conventional MRI, T2mapping sequence and MAGiC sequence scanning. Two radiologists divided the supraspinatus tendon into lateral, middle, and medial subregions according to its course, and measured the T2 values of different subregions on the MAGiC sequence and T2mapping sequence. Compare the image quality of the first echo image of the T2mapping sequence and MAGiC T2WI, and measure the signal to noise ratio (SNR) and contrast to noise ratio (CNR). The Mann-Whitney U test was used to analyze the differences in quantitative parameters between the tendonitis group and the control group in different subregions as well as the image quality of the two sequences. Draw the receiver operating characteristic (ROC) curve and calculate the area under the curve (AUC) to evaluate its diagnostic performance for tendonitis. Pearson correlation analysis was used to evaluate the correlation between T2 values in different subregions measured by T2mapping sequence and MAGiC sequence. ResultsThere is no statistically significant difference in the subjective score of the first echo image quality between MAGiC T2WI and T2mapping sequences reconstructed images (Z=-1.535, P>0.05); the CNR of MAGiC T2WI images [15.45 (12.76, 20.46)] is higher than that of T2mapping sequences the first echo image [9.94 (8.74, 12.23)], the difference is statistically significant (Z=-2.473, P<0.001), while the SNR of the MAGiC T2WI image [2.49 (2.16, 2.71)] was lower than the first in the T2mapping sequence echo image [5.82 (5.16, 7.44)], the difference was statistically significant (Z=-0.609, P<0.001); the T2 values of MAGiC sequence and T2mapping sequence were both higher in the lateral subregion and medial subregion of the tendinitis group. In the control group, the difference was statistically significant (P<0.05); the T1 value of the MAGiC sequence in the lateral subregion of the tendonitis group was higher than that in the control group, and the difference was statistically significant (P<0.05). The AUC of MAGiC sequence T1 and T2 values in diagnosing supraspinatus tendinitis in the lateral sub-region are 0.663 and 0.799 respectively, and the AUC of T2 value in diagnosing supraspinatus tendinitis in the medial sub-region is 0.762; the T2mapping sequence T2 value in the lateral sub-region, the AUCs for diagnosing supraspinatus tendonitis in the medial subregion were 0.822 and 0.711 respectively. The MAGiC sequence T2 value and T2mapping T2 value were positively correlated in the lateral subregion, middle subregion, and medial subregion of the supraspinatus tendon (correlation coefficients were 0.736, 0.437, 0.464 respectively). ConclusionsThe T1 and T2 values of the MAGiC quantitative map and T2mapping T2 values can effectively assess the heterogeneity of the internal components of the supraspinatus tendon, reflect the differences between the internal components of the normal tendon and the regional differences of the tendon itself, and provide an objective basis for the quantification of the supraspinatus tendon degeneration in clinical practice.

Comparative use of artificial intelligence-assisted compressed sensing and parallel imaging for shoulder magnetic resonance imaging

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveBy comparing with parallel imaging (PI), to explore the impact of artificial intelligence-assisted compressed sensing (ACS) technology on the scanning time and image quality of shoulder joint MRI, and optimizes the scanning scheme. Materials and MethodsA total of 70 patients who underwent shoulder MRI in our hospital from November 2023 to February 2024 were prospectively enrolled. The scanning sequences used fast spin echo including oblique coronal T1-weighted (OCor T1WI), oblique coronal T2-weighted with fat saturation (OCor T2WI-fs), oblique sagittal proton density (PD)-weighted with fat saturation (OSag PDWI-fs), and transverse PD-weighted with fat saturation (Tra PDWI-fs), respectively, using two accelerated acquisition technologies: ACS and PI. Compare the scanning time of two technologies. Measure the signal intensity and background standard deviation of the supraspinatus muscle and humeral head, and calculate the signal-to-noise ratio (SNR). Use the Likert scale to rate image quality. ResultsCompared to PI, using ACS reduced scanning time by 33.5%. The images obtained using ACS have few artifacts and low noise. The subjective image quality scores are higher than those obtained using PI, and the differences are statistically significant (all P<0.05). The SNR of images using ACS in OCor T1WI, OCor T2WI-fs, and Tra PDWI-fs sequences were higher than those using PI in the supraspinatus muscle and humeral head, and the differences were statistically significant (all P<0.001). The SNR of the supraspinatus muscle in the OSag PDWI-fs sequence using ACS was not significantly different from that of PI (P>0.05), while the SNR of the humeral head in the images obtained using ACS was higher than that of PI, and the difference was statistically significant (all P<0.001). ConclusionsCompared with PI, using ACS in shoulder MRI can achieve a more efficient and stable rapid imaging, improve image quality, shorten scanning time, and increase patient tolerance, which has clinical application value.

Quantitative evaluation of liver fibrosis by MRE and Gd-EOB-DTPA-enhanced T1 mapping magnetic resonance imaging in a rabbit model

Tue,20 Aug 2024 00:00:00 GMT

ObjectiveTo compare the accuracy of MR elastography (MRE) and Gd-EOB-DTPA-enhanced T1 mapping in the quantitative evaluation of liver fibrosis (LF) staging. Materials and MethodsOne hundred and twenty rabbits were randomly divided into control group (n=20), which were injected subcutaneously with normal saline solution, and LF group (n=100), which were received 50% (carbon tetrachloride) CCl₄ oil solution. The control group (n=5) and LF group (n=25) underwent MRI axial scan, T1WI, MRE, Gd-EOB-DTPA-enhanced T1 mapping at the end of the 4^th, 5^th, 6^th, 15^th week. The pathological LF staging was based on Scheuer staging system. The quantitative parameter included liver stiffness (LS), pre- and post-contrast T1 values of the liver (T1_native and T1_20min), the reduction rate of T1 relaxation time (ΔT1_20min) and the increase in T1 relaxation rate (ΔR1_20min), were compared the differences by one-way ANOVA analysis. Spearman correlation coefficients, Receiver operating characteristic (ROC) analysis was used respectively to determine the correlation and diagnostic performance between quantitative parameters and pathological LF staging. ResultsA total of 96 rabbits were included in F0 (n=15), F1 (n=22), F2 (n=22), F3 (n=18) and F4 (n=19). LS, T1_native, T1_20min, ΔT1_20min, ΔR1_20min showed significant differences among all LF staging (P<0.05). There were correlation between LS, T1_native, T1_20min, ΔT1_20min, ΔR1_20minand LF stage (r=0.935, 0.559, 0.770, -0.418 -0.686, P<0.001), respectively. LS exhibited the largest area under the curve (AUC), which were 0.988, 0.979, 1.000, 0.995 for F0 vs. F1~F4, F0 vs. F1~F2, F0 vs. F3~F4, F1~F2 vs. F3~F4, respectively. Secondly, the AUC of T1_20min were 0.914, 0.852, 0.987, and 0.896, respectively. ConclusionsIn the early quantitative evaluation of LF staging, MRE and Gd-EOB-DTPA enhanced T1 mapping had demonstrated significant diagnostic value, with MRE outperforming Gd-EOB-DTPA enhanced T1 mapping.

Research progress in evaluating brain function of related brain regions in patients with insomnia disorder based on fMRI

Tue,20 Aug 2024 00:00:00 GMT

Insomnia disorder (ID) is a sleep disorder that seriously affects the quality of life, long-term insomnia can lead to daytime dysfunction and depression, anxiety and other mental diseases, but also increase the risk of obesity, type 2 diabetes and cardiovascular disease, ID has become a major public health problem affecting the health of citizens. Functional magnetic resonance imaging (fMRI), as a non-invasive examination means, can reflect the physiological or pathological function of the brain, which is of great significance for the study of the pathogenesis of diseases, and plays an important role in the functional evaluation of brain regions in patients with ID. Studies have shown that patients with ID have functional abnormalities in several brain regions such as the amygdala, hippocampus and frontal lobe. Through fMRI technology, researchers can observe the changes in neuronal activity in these brain regions in patients with ID. The purpose of this paper is to review the recent research progress on the assessment of brain function in relevant brain regions of patients with ID using fMRI analysis, in order to provide a solid theoretical basis and imaging evidence for further exploration of the neuropathological mechanism of ID.

Progress in magnetic resonance imaging studies of the descending pain modulation system in patients with chronic pain

Tue,20 Aug 2024 00:00:00 GMT

Chronic pain is a complex experience that significantly burdens both patients and society. Research on the neural mechanisms of chronic pain typically focus on the areas related to the perception and control of pain. However, there is often less attention to the structural and functional changes in the brain regions associated with the descending pain modulation system. These areas play key roles in both inhibiting and facilitating pain perception. This article reviews the latest MRI research progress on the structural and functional changes in the descending pain modulation system in patients with chronic pain, aiming to explore the physiological and pathological mechanisms of DPMS and further deepen the understanding of chronic pain.

Current status of potential magnetic resonance imaging markers in the neural microenvironment in prostate cancer patients

Tue,20 Aug 2024 00:00:00 GMT

Prostate cancer (PCa) is the most prevalent and second deadliest cancer among men worldwide. The neural microenvironment of PCa is closely related to tumor progression, surgical curative degree, and postoperative recurrence, but the specific mechanism is not yet clear. The neural density (ND), perineural invasion (PNI), and neuroendocrine features (NEF) in the neural microenvironment are closely related to the expression of TMPRSS2 ERG gene, monoamine oxidase A (MAOA), nuclear factor kappa B, neurotrophic factors, and neuropeptide Y (NPY). Exploring imaging biomarkers related to genomics and proteomics can early identify the PCa neural microenvironment and affect clinical diagnosis and treatment plans. Based on the imaging omics features of multi-parameter magnetic resonance imaging (mp-MRI), potential imaging biomarkers for PNI and NEF can be identified. Neural visualization can be performed based on magnetic particle imaging (MPI) and deep neural network (DNN) image classification models. Emerging neuroimaging technologies such as diffusion tensor imaging (DTI), diffusion spectrum imaging (DSI), neurite orientation diffusion and density imaging (NODDI), and the design, synthesis, and neuroimaging of near-infrared fluorophores based on phenoxazine also hold unique value in displaying and predicting ND, PNI, and NEF. This article reviews the current research status of potential imaging biomarkers in the neural microenvironment of PCa patients, in order to further reveal the neurophysiological mechanisms of the PCa neural microenvironment and provide imaging evidence for subsequent diagnosis and treatment processes and improving patient prognosis.

Research advances in the quantitative analysis based on diffusion tensor imaging for grading and molecular typing of gliomas

Tue,20 Aug 2024 00:00:00 GMT

Gliomas represent approximately 80% of primary malignant brain tumors in adults. Accurate preoperative grading and molecular classification of gliomas can aid in formulating personalized treatment plans and extending the survival period of patients. Diffusion tensor imaging, a magnetic resonance imaging technique, evaluates water molecule diffusion to reflect alterations in tissue structure. This method can non-invasively evaluates water molecule diffusion rate and anisotropy within tumors in vivo, offering imaging metrics for predicting preoperative glioma grading and genotyping. This article provides a comprehensive review of the clinical studies of diffusion tensor imaging with quantitative parameters such as diffusion coefficient and anisotropy in the prediction of glioma grading and molecular classification, with the aim of providing reliable imaging indices for the accurate prediction of glioma grading and molecular typing before surgery, thus assisting in the accurate treatment of glioma patients.

Advances in differentiating intracranial isolated fibromas from different grades of meningiomas based on diffusion-weighted imaging

Tue,20 Aug 2024 00:00:00 GMT

Intracranial solitary fibrous tumor (SFT) has the characteristics of easy recurrence and high probability of intraoperative hemorrhage. It must be actively carried out preoperative and intraoperative preparations and systematic postoperative treatment. In contrast, meningiomas, which are similar in imaging manifestations with SFTs, are mostly benign, less prone to intraoperative hemorrhage, and have a better prognosis. So, it is crucial to differentiate between SFTs and meningiomas before surgery or treatment accurately. Therefore, accurate differentiation between SFTs and meningiomas before surgery or treatment is crucial. This article aims to systematically review the research progress and pathophysiological mechanisms of magnetic resonance diffusion-weighted imaging in distinguishing intracranial SFT from high-grade meningiomas, low-grade meningiomas, and angiomatous meningiomas. It thoroughly explores the advantages and value of this sequence in improving diagnostic accuracy, providing reference ideas for subsequent studies. Additionally, it aims to offer effective assistance to clinicians in preoperative evaluation and intraoperative decision-making, with the goal of improving patient prognosis and quality of life.

Progress of machine learning based on magnetic resonance imaging for orbital tumor research

Tue,20 Aug 2024 00:00:00 GMT

Orbital tumors vary in location and histopathological differences, presenting diagnostic challenges. Although advances in imaging technology have improved this problem, its classification and identification remains a challenge. As a key branch of artificial intelligence, machine learning has achieved certain results in the medical field, especially its combination with imaging and ophthalmology has greatly promoted the precision treatment of orbital tumors, and it has shown great potential and broad application prospects in tumor identification, lesion segmentation and image reconstruction, which is expected to improve the diagnosis level of orbital tumors and reduce the cost of clinical practice. This article reviews the application of MRI-based machine learning technology in orbital tumors, aiming to provide clinicians and radiologists with ideas for the diagnosis, treatment and prognosis of orbital tumors, and to further promote the application and popularization of machine learning in this field.

Research progress of conventional MRI characteristics in prognostic prediction of nasopharyngeal carcinoma

Tue,20 Aug 2024 00:00:00 GMT

Nasopharyngeal carcinoma (NPC) is a malignant tumor that originates from the columnar epithelium of the nasopharyngeal mucosa. Currently, the treatment regime for patients with NPC is mainly based on the degree of invasion of the primary tumor and the size and location of cervical lymph nodes on magnetic resonance imaging (MRI), but disease progression still occurs in approximately 10%-30% of patients after treatment. Currently, multi-functional MRI technology has demonstrated better prognosis predictive performance than conventional MRI technology, but the value of conventional MRI in clinical applications cannot be ignored due to its higher resolution, better stability and wider availability. In recent years, several studies have investigated the value of the skull base structures invasion (e.g., skull bone invasion, soft tissue infiltration, etc.) of NPC and other morphological features (e.g., extra-nodal extension, lymph node necrosis, etc.) of metastatic lymph nodes in predicting the prognosis of NPC, and the addition of certain conventional MRI features to the current eighth edition staging can significantly improve the predictive performance. Therefore, the present study summarizes the value of multi-dimensional primary tumor and lymph node features in conventional MRI [including T2WI, contrast-enhanced T1WI (CE-T1WI), diffusion weighted imaging (DWI)] in the prognosis prediction of NPC to provide a reliable basis for clinical diagnosis and treatment.

Research progress of cardiac magnetic resonance feature tracking technique in evaluating myocardial strain in autoimmune rheumatic diseases

Tue,20 Aug 2024 00:00:00 GMT

Autoimmune rheumatic diseases (ARDs) are characterized by abnormal activation of the body^{^,}s immune system, resulting in an inflammatory reaction mediated by antigen-antibody complexes and causing damage to multiple systems as a systemic disease. These diseases frequently involve the cardiovascular system, and long-term inflammatory reaction causes myocardial fibrosis and myocardial remodeling, which ultimately results in poor prognosis for patients. Imaging examinations can provide reliable evidence of cardiac involvement in patients with ARDs. Cardiac magnetic resonance feature tracking (CMR-FT) technology enables quantitative evaluation of myocardial strain, thus playing an important clinical role in recognizing myocardial damage and assessing its severity and prognosis. The present article provided an in-depth explanation of the principle and application value of CMR-FT technology in evaluating cardiovascular involvement in patients with ARDs. Additionally, it summarized the progress made in existing research, highlights limitations, and proposes future improvement measures. The ultimate goal is to integrate CMR-FT technology into clinical practice and provide more reliable imaging for patients with ARDs.

Research progress of artificial intelligence in imaging evaluation of rheumatoid arthritis

Tue,20 Aug 2024 00:00:00 GMT

Rheumatoid arthritis is a common autoimmune disease, which seriously affects the quality of life of patients. Imaging evaluation plays an important role in the diagnosis, treatment and prognosis of rheumatoid arthritis. In recent years, the rapid development of artificial intelligence, especially deep learning technology, has brought new breakthroughs to the image evaluation of rheumatoid arthritis. This paper first expounds the related concepts of artificial intelligence, then mainly based on the application of artificial intelligence in X-ray, CT, MRI and other imaging modalities, summarizes the bone lesions, synovial lesions and cartilage lesions, etc. Finally, puts forward the disadvantages of artificial intelligence at present, and prospects the application prospect of artificial intelligence in RA.

Chinese Journal of Magnetic Resonance Imaging RSS feed

Review on the application of MRI functional and quantitative imaging techniques in the diagnosis and treatment of cervical cancer

A preliminary application study of magnetic resonance elastography in the diagnosis of cervical cancer

Radiomics analysis for prediction of lymph node metastasis after neoadjuvant chemotherapy based on pretreatment MRI in locally advanced cervical squamous cell carcinoma

Prediction of lymphovascular space invasion in locally advanced cervical cancer patients after neoadjuvant chemotherapy based on pre-treatment multi-parameter MRI radiomics features

The radiomics model based on APT for preoperative prediction of cervical cancer lymphovascular space invasion

The value of amide proton transfer weighted combined with dynamic contrast-enhanced MRI in evaluating cervical cancer nerve invasion

Intra- and peritumoral sagittal T2WI radiomics nomogram for preoperative prediction of patients with stage ⅠB and stage ⅡA cervical cancer

Altered brain morphometry and structural covariant networks based on cortical thickness in Alzheimer,s disease

A resting-state functional magnetic resonance imaging study of abnormal brain function in patients with Internet gaming disorder

Research on aquaporin magnetic resonance molecular imaging of hippocampal subfields in Alzheimer,s disease

Study on cerebral perfusion characteristic network of type 2 diabetes mellitus patients based on MR arterial spin labeling imaging

Evaluation of rest-state fMRI in patients with lumbar disc herniation based on ALFF

Preliminary study of MK parametric map based on DKI technique in evaluating brain microstructural damage and cognitive impairment in patients with moderate and severe OSA

Clinical study of hypertension-related brain volume and white matter hyperintensity changes based on multimodal MRI

Exploring the cut-off age value of marrow transformation in children,s clivus by MRI

Differentiation of high-grade glioma and metastatic tumor based on MRI radiomics and semantic features

Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson,s disease based on SyMRI relaxation quantitative analysis and QSM

Value of a clinical-multiparametric MRI diagnostic model based on Kaiser score in the differential diagnosis of benign and malignant breast lesions

Cardiac magnetic resonance evaluation of myocardial tissue characterization of different left ventricular phenotypes in patients with chronic kidney disease

Clinical application value of predicting microvascular invasion in hepatocellular carcinoma using intratumoral and peritumoral radiomics models: A multicenter study

Prenatal MRI findings of type I congenital choledochal cyst and parameter measurement of liver and gallbladder

IVIM, mDixon-Quant multiparameter quantitative imaging combined with blood cell parameters to assess Ki-67 expression levels in rectal cancer

T2WI-based radiomics for discriminating between ovarian adult-type granulosa cell tumor and ovarian fibroma-thecoma with high-signal intensity on DWI

The value of magnetic resonance image compilation and T2mapping sequence in the quantitative assessment of chronic supraspinatus tendonitis

Comparative use of artificial intelligence-assisted compressed sensing and parallel imaging for shoulder magnetic resonance imaging

Quantitative evaluation of liver fibrosis by MRE and Gd-EOB-DTPA-enhanced T1 mapping magnetic resonance imaging in a rabbit model

Research progress in evaluating brain function of related brain regions in patients with insomnia disorder based on fMRI

Progress in magnetic resonance imaging studies of the descending pain modulation system in patients with chronic pain

Current status of potential magnetic resonance imaging markers in the neural microenvironment in prostate cancer patients

Research advances in the quantitative analysis based on diffusion tensor imaging for grading and molecular typing of gliomas

Advances in differentiating intracranial isolated fibromas from different grades of meningiomas based on diffusion-weighted imaging

Progress of machine learning based on magnetic resonance imaging for orbital tumor research

Research progress of conventional MRI characteristics in prognostic prediction of nasopharyngeal carcinoma

Research progress of cardiac magnetic resonance feature tracking technique in evaluating myocardial strain in autoimmune rheumatic diseases

Research progress of artificial intelligence in imaging evaluation of rheumatoid arthritis

Altered brain morphometry and structural covariant networks based on cortical thickness in Alzheimer^{^,}s disease

Research on aquaporin magnetic resonance molecular imaging of hippocampal subfields in Alzheimer^{^,}s disease

Exploring the cut-off age value of marrow transformation in children^{^,}s clivus by MRI

Clinical value in predicting the microstructural alterations of substantia nigra in patients with early Parkinson^{^,}s disease based on SyMRI relaxation quantitative analysis and QSM