http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202411 zh-cn An RSS feed for Chinese Journal of Magnetic Resonance Imaging http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.001 ObjectiveResting-state functional magnetic resonance imaging (rs-fMRI) combined with seed-based functional connectivity (FC) analysis was used to investigate whether there was a difference between the default network (DMN) and the whole brain functional connectivity between patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) and minimal hepatic encephalopathy (MHE) and healthy controls (HCs), in order to further explore the underlying mechanism of cognitive dysfunction in HBV-ACLF with MHE patients and HCs, and to provide imaging markers for early diagnosis of HBV-ACLF with MHE. Materials and MethodsRs-fMRI was used to observed the FC of the DMN with the whole brain in 27 patients with HBV-ACLF with MHE and 22 HCs in the resting state, and analyze the differences between the two groups, and correlation analysis was performed with Digit Symbol Test (DST), Number Connection Test A (NCT-A), Montreal Cognitive Assessment (MoCA) scores, blood ammonia and white blood cell count. ResultsCompared with the HCs group, the FC of the right temporal pole (middle temporal gyrus), left inferior temporal gyrus, right inferior occipital gyrus and left middle occipital gyrus was reduced in the MHE group (P<0.005), the FC value of the right temporal pole was significantly negatively correlated with the MoCA score in the MHE group (r=-0.394, P<0.05), and the FC score of the left inferior temporal gyrus in the MHE group was significantly negatively correlated with blood ammonia (r=-0.456, P<0.05). ConclusionsThe internal functional integration of DMN in patients with HBV-ACLF with MHE is altered, and the reduction or interruption of FC may be the pathophysiological mechanism of early cognitive decline in patients with HBV-ACLF with MHE. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.002 ObjectiveTo explore the application value of brain functional network topology properties in evaluating transcranial Direct Current Stimulation (tDCS) in improving cognitive impairment after ischemic stroke (IS). Materials and MethodsProspective inclusion of 51 IS patients with mild or above cognitive impairment, randomly assigned to an electrical stimulation group (26 cases) and a control group (25 cases) for 15 days of routine rehabilitation treatment, as well as tDCS treatment or sham stimulation. Collect cognitive scale scores and resting state functional magnetic resonance imaging (rs-fMRI) data from two groups of subjects before and after treatment. Constructing a brain functional network based on graph theory analysis methods, comparing the differences in global and local topological properties between two groups of subjects before and after treatment, as well as their correlation with cognitive scale scores. ResultsThe Mini Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) scores of the electrical stimulation group and the control group after treatment were both better than before treatment, but the improvement in MMSE and MoCA scores of the electrical stimulation group after treatment was higher than that of the control group, with P<0.05. The global efficiency (E_g) and normalized clustering coefficient (γ) of the electrical stimulation group increased after treatment (P<0.05, FDR correction); The nodal efficiency (E_nodal) of the inferior frontal gyrus in the left triangle and the nodal clustering coefficient (C_{p nodal}) of the superior frontal gyrus and posterior central gyrus in the left orbit increased (P<0.05, FDR correction). There was no significant difference in the global and local network topology properties between the control group after treatment. Correlation analysis found that the increase in E_g in the electrical stimulation group after treatment was positively correlated with the improvement in MMSE score (r=0.47, P=0.02). ConclusionsThe improvement of cognitive function in IS patients by tDCS combined with conventional rehabilitation therapy is superior to that of conventional rehabilitation therapy alone. At the same time, tDCS can have an impact on the global or local properties results of some brain functional networks, and the increase of E_g may be an effective predictor of cognitive function rehabilitation. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.003 ObjectiveTo explore the value of assessing the severity of patients with Parkinson^,s disease (PD) based on the T2WI radiology model. Materials and MethodsA total of 201 patients with a clinical diagnosis of PD were retrospectively collected, according to Hoehn-Yahr (H-Y) stage. They were divided into the early group (n=113) and middle-late group (n=88), into a training set of 140 cases and a test set of 61 cases using a 7∶3 ratio at the same time. We established by extracting and screening radiomics features from substantia nigra (SN), red nucleus (RN), caudate nucleus (CN), putamen (PUT), globus pallidus (GP), and used a logistic regression (LR) classifier to build the corresponding models separately. Clinical and imaging data were sequentially incorporated into univariate and multivariate logistic regression analysis to identify independent risk factors about PD severity. Receiver operating characteristic (ROC) curves were used to assess the efficacy of each model, and calibration curves were used to assess calibration accuracy. Results19 optimal features on T2WI were selected from SN, and the AUC (0.817, 0.733) in the training and test set were higher than those of the RN model (0.758, 0.704), the CN model (0.712, 0.643), the PUT model (0.713, 0.708), and the GP model (0.705, 0.708). The white matter hyperintensities burden and the duration of PD were independent risk factors for diagnosing the severity of PD patients, and the AUC of the combined model with the SN model was 0.865(training set) and 0.836 (test set), but there is no significant difference in diagnostic performance between the two models. The calibration curve indicates good consistency between the diagnostic results of the six models and the actual outcomes. ConclusionsSN signatures on T2WI achieved better performance in assessing the severity of PD patients. The assessed efficacy of the combined model established by the combined WMH burden and duration of PD was further improved and provide imaging guidance for timely clinical intervention and treatment. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.004 ObjectiveAn effective integrative analysis of brain regions with significant gray matter volume (GMV) abnormalities in early-onset schizophrenia (EOS) was conducted to identify the most consistent GMV changes in EOS, thus revealing possible pathophysiologic mechanisms of EOS. Materials and MethodsA systematic searched of the PubMed, Web of Science, Embase, as well as the China Knowledge Network and Wanfang databases for studies that used voxel morphometrics (VBM) to explore the differences in whole-brain GMV between EOS patients and healthy controls were conducted, and the data were analyzed using Seed-based d Mapping with Permutation of Subject Images (SDM-PSI) software, from the time of database establishment until April 30, 2024, Brain regions with significant abnormalities in GMV in the patients with EOS relative to healthy controls were extracted and summarized, and the data were analyzed using SDM-PSI software. ResultsA total of 11 studies that met the criteria were included, with a total sample size of 729 cases, including 366 patients with EOS and 363 healthy controls. Voxel-based meta-analysis showed that GMV was significantly reduced in the right superior temporal gyrus extending to the right middle temporal gyrus, and temporal pole in patients with EOS, and no brain regions with significantly increased GMV were identified (P<0.005; peak height Z>1; cluster range>10 voxels). ConclusionsIn the present study, the voxel-based meta-analysis method revealed that the more consistently GMV significantly abnormal brain region in EOS patients was the right superior temporal gyrus (extending to the right middle temporal gyrus and temporal pole), and these findings will help to further deepen the understanding of the pathophysiological mechanisms of schizophrenia. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.005 ObjectiveTo explore the changes in brain microstructure in patients with white matter hyperintensities and depression symptoms based on multimodal MRI. Materials and MethodsThirty-five patients with white matter hyperintensities and mild depression, as well as 35 healthy individuals matched by age, gender and years of education were recruited. Clinical assessments and MRI data were collected. Tract-based spatial statistics (TBSS) and voxel-based morphometry (VBM) were used to investigate the microstructural changes of the brain between the two groups, and the correlation between the structural differences and the Hamilton Depression Scale (HAMD) score was analyzed. ResultsUsing the statistics of no-threshold-freecluster enhancement (TFCE) for permutation test and applying (family-wise error, FEW) to correct for multiple comparisons of the study results (P<0.05). Significantly lower FA (P＜0.05) values were found in areas including the body of corpus callosum, bilateral posterior thalamic radiation, the right retrolenticular part of internal capsule, and right superior longitudinal fasciculus in the experimental group were statistically significant compared to the healthy group (P<0.05); the experimental group showed a reduction in gray matter volume in brain regions such as bilateral hippocampus, right parahippocampal gyrus, anterior central gyrus, superior temporal gyrus, middle temporal gyrus, and lingual gyrus (FDR corrected, P<0.05). The FA value of the corpus callosum was negatively correlated with the volume of the right hippocampus (r=0.495, P=0.004), and significantly negatively correlated with the HAMD score (r=-0.530, P=0.002). ConclusionsPatients with white matter hyperintensities and depression symptoms have extensive involvement of white matter fibers and changes in gray matter microstructure. The integrity of white matter fibers in the body of corpus callosum may be related to depressive symptom, which can provide reference for early clinical identification and intervention. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.006 ObjectiveTo explore the value of the modified Look-Locker inversion recovery (MOLLI) T1 mapping quantitative technique in evaluating the development of brain in children quantitatively. Materials and MethodsFifty-three children with normal head magnetic resonance imaging results were included, and optimized MOLLI and magnetization prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequences were used to perform T1 mapping quantitative analysis on 36 brain regions of each subject. We evaluate the consistency of T1 values in each brain region obtained from two sequences, compared the differences in T1 values in each brain region of the two sequences, and analyze the correlation between T1 values in each brain region of the two sequences and age. ResultsThe intraclass correlation co-efficient (ICC) for the MOLLI sequence and MP2RAGE sequence in all brain regions were greater than 0.8 (P<0.001), except for the bilateral dorsal pontine and cerebral peduncle. The differences in T1 values between the two sequences in each brain region were statistically significant (P<0.05, FDR-corrected), the T1 values in each brain region of the MOLLI group were higher than those in the MP2RAGE group. The T1 values of each brain region in both sequences were negatively correlated with age (P<0.001). ConclusionsThe optimized MOLLI sequence can be used for the quantitative evaluation of brain development in children, showing good consistency with MP2RAGE sequence, and accurately quantifying T1 values of brain regions, providing a new sequence selection for the study of the nervous system of fetuses and children. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.007 ObjectiveTo explore the changes of hippocampal microstructure in patients with cognitive impairment of temporal lobe epilepsy (TLE-CI) and normal temporal lobe epilepsy (TLE-CN) by neurite orientation dispersion and density imagin (NODDI), and to explore the relationship between hippocampal microstructure and clinical features. Materials and MethodsThe head MRI of 35 cases of TLE-CI, 31 cases of TLE-CN and 40 cases of healthy controls (HC) were analyzed. MRtrix3 was used to calculate the fraction of the isotropic diffusion compartment (fiso), orientation dispersion index (ODI) and neurite density index (NDI) of NODDI images. Then superimposed with the structure image after FreeSurfer segmentation, the NODDI index values of the hippocampus were obtained. The differences of NODDI indexes among the three groups of participants were compared, and the correlation between the difference indexes and the clinical characteristics of patients was analyzed. ResultsThe fiso value of ipsilateral and contralateral hippocampus in TLE-CI group was significantly higher than that in HC group (P=0.004, P=0.017), but there was no significant difference in ODI value between groups. The NDI value of ipsilateral hippocampus in the TLE-CI group was significantly lower than that in the HC group (P<0.001), while the NDI value of the affected hippocampus in the TLE-CN group was significantly lower than that in the HC group (P=0.004). In TLE-CI group, the NDI value of ipsilateral hippocampus was positively correlated with the age of onset (r=0.491, P=0.003) and negatively correlated with the course of disease (r=-0.424, P=0.011). ConclusionsThis study shows the ability of NODDI to detect the microstructural changes of hippocampus in patients with temporal lobe epilepsy. Among them, NDI may be a sensitive and progressive biomarker in patients with TLE-CI. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.008 ObjectiveUsing the tract-based spatial statistics (TBSS) method based on diffusion kurtosis imaging (DKI) technology to explore the changes in brain white matter structure of boys with primary nocturnal enuresis and its correlation with child behavior scales. Materials and MethodsMR DKI scans were conducted on 25 enuresis male patients with NE (NE group) and 24 age, gender, and education matched healthy control (HC group). The mean diffusivity (MD), mean kurtosis (MK), and axial kurtosis (AK) values of brain regions with statistical significance were determined, and Spearman correlation analysis was performed to explore the relationship between the MD, AK, and MK values in the different brain regions and children^,s behavioral performance. ResultsCompared with the HC group, the NE group showed significantly increased MK values in the right preoptic tract, bilateral corticospinal tract (P<0.05); There is a significant increase in the AK value in the right lower longitudinal bundle, the left corticospinal tract, the right inferior fronto-occipital fasciculus, and the large claw (P<0.05); and a significant decrease in the MD value in the right anterior thalamic radiation, as well as in the bilateral lower longitudinal bundles, bilateral corticospinal tracts, and left anterior thalamic radiation (P<0.05). Correlation analysis revealed that the scores of the Children^,s Behavior Checklist (CBCL) were positively correlated with the MK and MD values of the right corticospinal tract and the right lower longitudinal bundle. The scores of the Children^,s Sleep Habits Questionnaire (CSHQ) were positively correlated with the MD values of the right lower longitudinal bundle, the right anterior thalamic radiation, and the left lower longitudinal bundle. ConclusionsDKI technology can detect white matter structure alterations in NE patients, and the changes in white matter structure in the different brain regions are associated with the CBCL and CSHQ. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.009 ObjectiveTo investigate the value of ensemble learning model constructed based on MRI visual and diffusion tensor imaging (DTI) histogram for predicting isocitrate dehydrogenase (IDH) phenotypes in adult-type diffuse gliomas. Materials and MethodsA retrospective analysis was conducted on conventional MRI and DTI images of 106 adult diffuse gliomas identified by the 2021 edition of the WHO Classification of Central Nervous System Tumors. Visually accessible Rembrandt images (VASARI) features were evaluated on conventional MRI. The absolute and relative values of fractional anisotropy (FA), relative anisotropy (RA), volume ratio anisotropy (VR), and mean diffusivity (MD) of DTI images were measured, as well as the histogram features. Recursive feature elimination (RFE) and Boruta algorithms were used for feature screening in the training set, and Gaussian Naive Bayes (GNB) models of VASARI features, DTI clinical parameters and DTI histograms were ensembled with a support vector machine (SVM) based on the stacking method. The ensemble machine learning model was then used to predict the IDH phenotype of adult diffuse gliomas. The performance of each model was evaluated by measuring the area under the curve (AUC) of receiver operating characteristic curves. ResultsA total of 106 glioma patients (50.05±15.17 years old, 54 males) were enrolled in the study, comprising 55 patients with IDH-mutant and 51 patients with IDH wildtype. The cascade recursive dimension reduction of RFE and Boruta, respectively, identified six VASARI features, eight DTI clinical parameters features, and eight DTI histogram features as the primary layer classifier. The model constructed based on histogram features had the highest AUC (0.90/0.87, training set/test set), which was superior to the model constructed from DTI clinical parameters (AUC: 0.83/0.78, training dataset/testing dataset) and the model constructed from conventional MRI visual features (AUC: 0.84/0.66, training dataset/testing dataset). The ensemble learning model based on stacking generalization achieved the highest AUC for predicting IDH phenotype (0.92/0.89 for the training dataset/testing dataset). ConclusionsThe ensemble learning model based on the combined conventional MRI features and DTI features can effectively predict the IDH genotype of adult-type diffuse gliomas before surgery and assists in the rapid clinical assessment of the prognosis. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.010 ObjectiveTo explore the value of synthetic magnetic resonance imaging (syMRI) combined with amide proton transfer (APT) in projecting the isocitrate dehydrogenase 1 (IDH1) gene status in gliomas. Materials and MethodsA retrospective analysis was performed on 97 patients diagnosed with glioma with complete pathological data at the General Hospital of Ningxia Medical University from July 2019 to December 2023, including 57 cases of IDH1 mutant (IDH1-mut) and 40 cases of IDH1 wildtype (IDH1-wt), all of whom underwent preoperative pre- and post-contrast syMRI and APT scans, and their quantitative parameters T1-pre, T2-pre, T1-post, T2-post and APT values were measured. Independent samples t-tests or Mann-Whitney U-tests were used to analyse the differences between groups for each parameter, and the diagnostic efficacy of each single and combined parameter for IDH1 gene status was assessed using subject operating characteristic curves and binary logistic regression analyses. The DeLong test was used to compare the differences in AUC for each parameter. ResultsAPT values and T1-pre were higher in IDH1-wt than in IDH1-mut gliomas (P<0.05); T1-pre and T2-pre were lower in IDH1-wt gliomas than in IDH1-mut gliomas (P<0.01); and T2-pre was not statistically significant between the two groups (P=0.107). Among all single parameters, the APT value had the highest diagnostic efficacy for IDH1-mut versus IDH1-wt glioma, with an AUC of 0.867, which was higher than that of T1-pre, T1-post, and T2-post (AUC 0.620, 0.811, and 0.723); the AUC of the multi-parameter combined prediction model (T1-pre+T1-post+T2-post +APT) had an AUC of 0.886, a sensitivity of 80.7%, and a specificity of 85.0%, which was higher than that of any single parameter. The DeLong test showed that the diagnostic efficacy of the multi-parameter combined prediction model was superior to the T1-pre, T1-post, and T2-post values (P<0.05), whereas there was no significant difference in the AUC with APT (P=0.208). ConclusionssyMRI combined with APT is useful for preoperative noninvasive prediction of IDH1 gene status in gliomas, and the highest efficacy was achieved when the two were used in combination for diagnosis. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.011 ObjectiveTo investigate the feasibility of time-dependent diffusion MRI based diagnostic indicators for identifying O⁶-methylguanine deoxyribonucleic acid methyltransferase (MGMT) promoter methylation status in newly diagnosed glioblastomas. Materials and MethodsWe enrolled 22 glioblastomas with methylated MGMT promoter (mMGMT) and 29 glioblastomas with unmethylated MGMT promoter (uMGMT) for diagnostic analysis and then 14 mMGMT glioblastomas and 14 uMGMT glioblastomas for validation application. Time-dependent diffusion MRI data was acquired using pulsed and oscillating gradient sequences on a 3 T scanner. Microstructural diagnostic indicators, including intracellular volume fraction ( f_in), extracellular diffusivity (D_ex), cell diameter (d), cellularity, and diffusivities at different frequencies (D_{0 Hz}, D_{15 Hz}, and D_{30 Hz}), were estimated using a two-compartment model. These indicators were compared between mMGMT and uMGMT glioblastomas, and their discriminative performance was assessed with univariate logistic regression analysis. Significant variables were identified via multivariate logistic regression to construct a combined diagnostic model. Pairwise comparisons were used to evaluate diagnostic abilities. ResultsmMGMT glioblastomas showed higher f_in, D_ex and cellularity (all P<0.05) and lower D_{0 Hz} (P=0.018) compared to uMGMT glioblastomas. Among these indicators, f_in had the highest discriminant power with area under curve (AUC) was 0.95, sensitivity was 95%, specificity was 90%, and showed differences compared to other indicators (all P<0.05). No combined diagnostic model was constructed because f_in was the independent influence variable in the multivariate logistic regression analysis. The accuracy was 82.14% using f_in>0.16 as the diagnostic threshold for validation. ConclusionsTime-dependent diffusion MRI–based f_in show promise for characterizing MGMT promoter methylation status in newly diagnosed glioblastomas. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.012 ObjectiveExplore the feasibility of using single-shot compressed sensing real-time cine (RT-CS) and two-shots compressed sensing cine (2 shots-CS) cardiac magnetic resonance (CMR) sequences to assess left ventricular (LV) strain. Materials and MethodsSixty-four patients undergoing CMR were prospectively enrolled. Each patient underwent conventional segmented cine (Seg), 2 shots-CS, and RT-CS. The acquisition time for each sequence was recorded. Using Seg as the "gold standard", the image quality of the three cine sequences was evaluated, including subjective assessment, artifact evaluation, and edge sharpness. LV volumetric and functional parameters, as well as global and regional strain parameters (basal, mid, apical), were measured. Bland-Altman plots and intra-class correlation coefficients (ICC) were used to compare the consistency of LV volumetric and functional parameters and strain measurements obtained from the three sequences. ResultsAcquisition time for Seg, 2 shots-CS, and RT-CS was (271.72±87.74) s, (62.19±33.09) s, and (29.39±20.60) s, respectively, with statistically significant differences (P<0.001). Subjective image quality ratings showed no significant difference between Seg and 2 shots-CS (P=0.122), but RT-CS had lower ratings than Seg (P=0.001). Artifacts were less pronounced in RT-CS than in both Seg (P=0.038) and 2 shots-CS (P=0.022), while there was no significant difference between Seg and 2 shots-CS (P=0.825). Edge sharpness in 2 shots-CS was similar to Seg (P=0.068), but RT-CS showed significantly lower sharpness than Seg (P<0.001). In quantitative left ventricular function analysis, end-diastolic volume (EDV) and stroke volume (SV) were lower in 2 shots-CS compared to Seg (P<0.001), while end-systolic volume (ESV), ejection fraction (EF), and left ventricular mass (LVM) did not significantly differ between 2 shots-CS and Seg (P>0.05). All functional volumetric parameters in RT-CS were lower than in Seg, with statistically significant differences (P<0.05). Both CS sequences showed excellent agreement with Seg for volumetric and functional parameters (ICC>0.910). For strain analysis, both 2 shots-CS and RT-CS showed lower radial strain (RS), circumferential strain (CS), and longitudinal strain (LS) values compared to Seg, with RT-CS values being the lowest, and all differences were statistically significant (P<0.05). Except for apical RS (ICC=0.559, 0.529), strain values in 2 shots-CS and RT-CS showed good to excellent agreement with Seg (ICC=0.776-0.950 for 2 shots-CS; 0.716-0.941 for RT-CS). Global strain showed higher consistency than regional strain in both CS sequences, with 2 shots-CS demonstrating higher consistency than RT-CS. ConclusionsBoth CS cine sequences significantly reduced scan time while maintaining acceptable image quality. In particular, 2 shots-CS showed good agreement with Seg in strain measurements, with global strain showing better consistency than regional strain. However, strain values from CS cine sequences were lower than those from Seg. To avoid measurement discrepancies due to sequence variation, it is recommended to use the same cine sequence consistently in follow-up of chronic conditions. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.013 ObjectiveThe aim of this study was to investigate the diagnostic value of resting brain activity and functional connectivity characteristics in classifying chemotherapy-related cognitive impairment in breast cancer. Materials and MethodsA total of 40 patients with breast cancer (BC) treated with chemotherapy at baseline (P0), 33 survivors assessed one week following treatment (P1), 19 survivors assessed six months after treatment completion (P2), and 44 female volunteers as the healthy control (HC) group were recruited in this study and underwent resting-state functional magnetic resonance imaging (rs-fMRI) examination and neuropsychological test. After data processing by DPARSF and PRoNTo software, 4 types of rs-fMRI measurements, including low-frequency fluctuations (fALFF), regional homogeneity (ReHo), and hippocampal functional connectivity were obtained. Using the PRoNTo 2.1 toolbox, the four data features were used as inputs to the machine learning algorithm, and the binary classification method was used for modeling. Independent sample t test was used for comparison of clinical data indicators at baseline, and single factor ANOVA was used between groups ResultsCompared with P0, the BC group showed significantly statistical significance in auditory verbal learning test, self-rating depression scale (SDS) and self-rating anxiety scale at P1 (P<0.05). The fALFF feature gave the highest accuracy in classifing chemotherapy related cognitive impairment among these groups. The specific results demonstrated the highest accuracy of classification was between P0 and HC groups (accuracy 86.90%, P<0.001). Among the group P0, P1, and P2, the classification accuracy between the P0 and P1 groups (accuracy 76.27%, P<0.001) was higher than that of other classifications. In all classifications, the regions showing high feature importance calculated by the decision function within the algorithm largely overlapped with those showing significant differences during the comparisons between fALFF maps in t-tests. ConclusionsThe machine learning algorithm based on multiple types of rs-fMRI measurements can effectively identify breast cancer patients with chemotherapy-related cognitive impairment and provide imaging reference for early diagnosis. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.014 ObjectiveTo explore the clinical value of apparent diffusion coefficient (ADC) in predicting distant metastasis of hepatic alveolar echinococcosis (HAE). Materials and MethodsA retrospective analysis was conducted on 267 patients diagnosed with HAE at Qinghai University Affiliated Hospital from January 2019 to March 2024, including 88 cases with distant metastasis and 179 cases without metastasis. Clinical and imaging information was recorded, and the maximum apparent diffusion coefficient (ADC_max), minimum apparent diffusion coefficient (ADC_min), and mean apparent diffusion coefficient (ADC_mean) of the solid part and peripheral zone of the lesions were measured on diffusion-weighted imaging (DWI). Statistical methods were used to compare the differences between patients with distant metastasis and those without metastasis in terms of age, sex, ethnicity, ADC_max, ADC_min, and ADC_mean of the solid part and peripheral zone of the lesions. Receiver operating characteristic (ROC) curves were plotted, and the area under the curve (AUC) was calculated to evaluate the diagnostic performance of each parameter. The optimal diagnostic cutoff values and their corresponding sensitivities and specificities were calculated. ResultsThere were no statistically significant differences in age, sex, or ethnicity between the group with distant metastasis of HAE and the group without metastasis (P>0.05). Regarding the solid part of the lesions, there were no significant differences in ADC_max, ADC_min, or ADC_mean between the group with distant metastasis and the group without metastasis (P>0.05). However, significant differences in ADC_max, ADC_min, and ADC_mean were observed between the two groups in the peripheral zone of the lesions (P<0.05). Additionally, regardless of metastasis occurrence, ADC_max, ADC_min, and ADC_mean in the peripheral zone were lower than those in the solid component. ROC curve analysis demonstrated that ADC values in the peripheral zone could effectively predict distant metastasis of HAE. Among them, the combined index showed the best efficacy in predicting distant metastasis of HAE, the AUC is 0.955 (95% CI: 0.923-0.977), with a sensitivity of 93.2% and a specificity of 86.0%. ConclusionsThe ADC values in the peripheral zone have good predictive value for assessing whether HAE will develop distant metastasis in the clinical setting. The combined use of various parameters can further enhance the predictive efficacy of distant metastasis in HAE, facilitating the realization of individualized and precise medical decision-making. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.015 ObjectiveTo explore the value of T1 mapping combined with diffusion-weighted imaging (DWI) in the early identification of renal interstitial fibrosis (IF). Materials and MethodsA total of 38 patients with chronic kidney disease (CKD) and 20 healthy volunteers who received renal needle biopsy after evaluation by nephrologist were collected from January 2020 to December 2023 in Wuxi People^,s Hospital Affiliated to Nanjing Medical University. Serum creatinine (SCr) and estimated glomerular filtration rate (eGFR) were measured in all subjects. T1 mapping and DWI were performed at the same time, and T1 and ADC values of renal cortex and medulla were measured, respectively. According to the degree of interstitial damage in renal pathology, CKD patients were divided into CKD-IF0 group (7 cases) without interstitial fibrosis and IF1 group (31 cases) with mild interstitial fibrosis. Healthy volunteers were divided into control group (20 cases). Renal medullary T1 and ADC values in control group, CKD-IF0 group and IF1 group were compared. We analyzed the correlation between cutis medulla T1 and ADC values and eGFR, and further evaluated the efficacy of eGFR, cutis medulla T1 and ADC values in the diagnosis of renal interstitial fibrosis without and with mild fibrosis. Results(1) There were no significant differences in T1 and ADC values between control group and CKD-IF0 group (P>0.05). ADC values of cortex and medulla in control group were higher than those of IF1 group (P<0.05), and T1 values of control group were lower than those of IF1 group (P<0.05). The ADC values of cortex and medulla in CKD-IF0 group were higher than those in IF1 group (P<0.05), cT1 was lower than that in IF1 group (P<0.05), and there was no significant difference in mT1 between the two groups (P>0.05). (2) After the control group and CKD-IF0 were combined into IF0 group, the cortex and medulla T1 value of IF0 group was significantly lower than that of IF1 group (P<0.05), and the ADC value was significantly higher than that of IF1 group (P<0.05). (3) cT1 was negatively correlated with eGFR (ρ=-0.476, P<0.05), and cADC was positively correlated with eGFR (ρ=0.391, P<0.05). There was no significant correlation between mT1 and mADC and eGFR (P>0.05). (4) When eGFR, cT1, mT1, cADC and mADC were used separately to distinguish IF0 group and IF1 group, eGFR had the highest efficiency, with AUC of 0.861 [95% confidence interval (CI): 0.761-0.962], sensitivity of 80.6%, and specificity of 88.9%. When cT1 and cADC were combined, the efficiency of differentiation between IF0 group and IF1 group was further improved, with AUC of 0.912 (95% CI: 0.839-0.984), sensitivity of 83.9%, and specificity of 85.2%. When combined with eGFR, cT1 and cADC, the highest differential efficacy was achieved, with AUC of 0.963 (95% CI: 0.922-1.000), sensitivity of 87.1% and specificity of 96.3%. ConclusionsT1 mapping combined with DWI can noninvasculatively and effectively identify renal interstitial fibrosis, and is expected to assist eGFR to further improve the ability of early identification of renal tissue and structure damage. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.016 ObjectiveTo investigate the value of MRI characteristics combined with clinical indicators [carbohydrate antigen 125 (CA125), menopausal status, age] in optimizing the Ovarian-Adnexal Reporting and Data System (O-RADS) MRI score 4 mass risk stratification and whether it can improve the diagnostic performance of the O-RADS MRI scoring system. Materials and MethodsTotally 57 ovarian adnexal masses scored 4 according to O-RADS MRI were retrospectively analyzed. All masses underwent preoperative pelvic MRI enhancement imaging and were confirmed by histopathology. They were evaluated by two experienced radiologists and determined through consultation when the results were inconsistent. The pathological results were used as the gold standard to analyze the differences of MRI and clinical indicators in the O-RADS MRI score 4 group of benign and malignant masses. The classification and regression tree (CART) was employed to construct a model for statistically significant indicators for the further subdivision of the O-RADS MRI 4 mass. Receiver operating characteristic (ROC) analysis was used to evaluate the prediction accuracy of the decision tree model. To evaluate the diagnostic effect of O-RADS MRI scoring system before and after O-RADS MRI score 4 mass optimization, and compare the difference of area under the curve (AUC). The consistency of the optimized prediction results among different viewers was calculated. Results(1) Among 57 O-RADS MRI score 4 masses, 22 masses were benign, and 35 masses were malignant. Solid tissue showed hypointense on T2WI was more common in benign mass well (P<0.001). Papillary projections and irregularly thickened cyst wall or septations were more frequent in malignant mass (P<0.001, P=0.008). The CA125 level in malignant mass was often greater than 35 U/mL (P<0.05). The AUC of the decision tree model for predicting benign and malignant tumors was 0.984 (95% CI: 0.908-1.000), with a sensitivity of 97.1%, specificity of 90.9% and accuracy of 94.7%. (2) The AUC of the O-RADS MRI scoring system increased from 0.838 to 0.945 (P<0.001) in the whole population after optimizing the O-RADS MRI 4 mass with the decision tree model; In premenopausal women, the AUC increased from 0.818 to 0.934 (P<0.001). In postmenopausal women, the AUC increased from 0.871 to 0.962 (P=0.008). There was excellent agreement between the optimized predictions among physicians with different experience levels (Kappa=0.887, 0.869). ConclusionIn this study, a predictive model developed based on solid tissue MRI features combined with CA125 levels helped optimize the risk stratification of O-RADS MRI score 4 mass and significantly improved the diagnostic performance of the O-RADS MRI scoring system, especially in premenopausal women. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.017 ObjectiveTo explore the predictive value of multi-parametric magnetic resonance imaging (mp-MRI) radiomics models for preoperative microsatellite instability (MSI) status in endometrial carcinoma (EC). Materials and MethodsA retrospective analysis was conducted on clinical, pathological, and imaging data of 171 patients with pathologically confirmed EC. The patients were randomly divided into a training set and a validation set in a 7∶3 ratio. Using the 3D Slicer software, regions of interest (ROIs) were delineated on axial T2WI, diffusion-weighted imaging (DWI), and sagittal contrast-enhanced T1WI (CE-T1WI) delayed phase sequences, and radiomic features were extracted. Feature selection and calculation of radiomics scores (Rad-scores) were performed using intra-class correlation coefficient (ICC), least absolute shrinkage and selection operator (LASSO) algorithm, ten-fold cross-validation, and Pearson correlation test. Models were constructed using Rad-scores for individual sequences (T2WI model, DWI model, CE-T1WI model) and a combined model. Receiver operating characteristic (ROC) curves were plotted for each model, and model performance was evaluated using area under the curve (AUC), sensitivity, specificity, and other metrics. The models were validated on the test set. The DeLong test was used to compare the differences in AUC values among the models. ResultsAmong the 171 EC patients, 35 had MSI and 136 had microsatellite stability (MSS). From the T2WI, DWI, and CE-T1WI sequences, 6, 3, and 3 features were retained, respectively. In the training set, the area under the curve (AUC) values for the T2WI model, DWI model, CE-T1WI model, and combine model were 0.869 [95% confidence interval, (CI): 0.772-0.938], 0.768 (95% CI: 0.645-0.865), 0.912 (95% CI: 0.830-0.966), and 0.927 (95% CI: 0.865-0.966), respectively. In the validation set, the AUC values were 0.736 (95% CI: 0.573-0.896), 0.714 (95% CI: 0.560-0.872), 0.856 (95% CI: 0.675-0.990), and 0.907 (95% CI: 0.813-0.977) for the T2WI model, DWI model, CE-T1WI model, and combine model, respectively. The DeLong test indicated that there were statistically significant differences in AUC values between the DWI model and both the combine model and the CE-T1WI model (P<0.05). No statistically significant differences were found between the AUC values of the other model pairs (P>0.05). ConclusionsThe radiomic model based on mp-MRI can effectively predict the MSI status of EC preoperatively. The combined model shows higher predictive performance compared to individual sequences, which helps in formulating personalized treatment plans and improving patient outcomes. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.018 ObjectiveTo explore the application value of T2 fluid-attenuated inversion recovery (Flair) sequence based on deep learning reconstruction (DLR) algorithm in improving the image quality of white matter hyperintensities (WMH). Materials and MethodsFifty patients with suspected cerebral ischemic disease were prospectively recruited. Both the conventional T2 FLAIR sequence and the high-resolution T2 Flair sequence, utilizing the DLR algorithm, were conducted on the patients. The DLR Flair sequence selected for this study retained the pre-processed images that have undergone conventional reconstruction algorithms without DLR processing (referred to as Pre-DLR). Subjective evaluations were performed on three groups of images using a 4-point scale to assess image sharpness, gray-white matter contrast, cerebrospinal fluid-choroid plexus contrast, WMH display, and overall image quality. Comparisons were made between the number of WMH detections, the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of WMH in three sets of images. ResultsIn the subjective evaluation, the DLR group of images scored higher than the conventional group and Pre-DLR group in terms of image sharpness, gray-white matter contrast, cerebrospinal fluid-choroid plexus contrast, WMH display, and overall image quality (all P<0.05). In terms of WMH counting, the DLR group identified a higher number of WMHs than the conventional group (P<0.05), while there was no statistical difference with the Pre-DLR group. In the objective evaluation, the DLR group showed higher SNR and CNR of WMH compared to the conventional group and Pre-DLR group (all P<0.05). ConclusionsCompared to conventional sequences, the high-resolution T2 Flair sequence combined with the DLR algorithm can improve WMH image quality and detect more subtle WMH lesions without increasing scan time. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.019 ObjectiveTo investigate the feasibility and clinical value of 3D high-resolution compressed sensing contrast-enhanced whole-body magnetic resonance angiography (3D-CS-CE-MRA) with single injection and half-dose contrast agent. Materials and MethodsA total of 83 patients who were suspected of systemic arterial disease and underwent MRI systemic vascular examination were prospectively enrolled and randomly divided into two groups, A and B, with 44 patients in group A and 39 patients in group B. Group A underwent 3D-CS-CE-MRA scanning with a total contrast agent volume of 0.15 mmol/kg injected at a flow rate of 2 mL/s, while group B underwent conventional 3D high-resolution contrast-enhanced whole-body magnetic resonance angiography (3D-CE-MRA) scanning with a total contrast agent volume of 0.3 mmol/kg administered in two doses of 0.15 mmol/kg each at a flow rate of 2 mL/s. Two experienced radiologists independently scored the qualitative image quality of 25 arterial segments,and signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) were measured for the common carotid artery, abdominal aorta, femoral artery, and popliteal artery. The independent samples t-test and the Wilcoxon rank sum test was used for statistical analysis. ResultsThere was no significant difference in SNRs and CNRs for the common carotid artery,the femoral artery and the popliteal artery (all P>0.05), but there was significant difference in SNRs and CNRs for the abdominal aorta (all P<0.05), the average value of group B was higher than that of group A. The average score of 3D-CS-CE-MRA was better than 3D-CE-MRA [(3.41±0.52) vs. (3.18±0.48), P<0.05]. There was no significant difference in scores of abdominal aorta, renal artery, superior mesenteric artery, celiac trunk, common iliac artery, external iliac artery, anterior tibial artery, and peroneal artery (all P>0.05); there was no difference in image quality between group A and B. There was significant difference in scores of common carotid artery, brachiocephalic trunk, vertebral artery, thoracic aorta, femoral artery, popliteal artery, and posterior tibial artery (all P<0.05), the scores of group A was higher than group B. ConclusionsCompared with conventional 3D-CE-MRA, 3D-CS-CE-MRA can quickly complete magnetic resonance whole-body vascular examination with only one contrast agent injection and subtractionless, under the premise of ensuring image quality, it reduces the amount of contrast agent, shortens the examination time, and improves patient tolerance, and has great clinical application value. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.020 ObjectiveTo compare the imaging effects of respiratory-triggered three-dimensional magnetic resonance cholangiopancreatography (RT-3D MRCP) and single breath-holding three-dimensional magnetic resonance cholangiopancreatography (BH-3D MRCP) in 5.0 T ultra-high field magnetic resonance imaging. Materials and MethodsThe results of 50 patients (23 males and 27 females) who underwent 5.0 T RT-3D MRCP and BH-3D MRCP were retrospectively analyzed. RT-3D MRCP and BH-3D MRCP images of all patients were subjectively scored and compared with objective data collection. The subjective score included the overall image quality, image artifacts, common bile duct, left hepatic duct, right hepatic duct, right anterior branch, right posterior branch, second and third branches, pancreatic duct and gallbladder duct. The objective data included image signal-to-noise ratio (SNR), contrast ratio (CR) and contrast-to-noise ratio (CNR). The paired t test and Wilcoxon signed rank test were used for intergroup analysis. Spearman correlation analysis was used to analyze the correlation between age, gender, abdominal pain symptoms, body mass index (BMI) and subjective scores. ResultsSNR, CR and CNR in RT-3D MRCP group were higher than those in BH-3D MRCP group (P<0.001). RT-3D MRCP was also superior to BH-3D MRCP sequences in overall image quality, image artifacts, common bile duct, left hepatic duct, right hepatic duct, right anterior branch, right posterior branch, second and third branch, pancreatic duct and gallbladder duct by subjective score (P<0.01). BMI was negatively correlated with RT-3D MRCP image artifacts (r=-0.330, P=0.019). The overall image quality and image artifacts score of RT-3D MRCP in patients with abdominal pain were lower than those without abdominal pain (P=0.011, 0.013). ConclusionsAt 5.0 T ultra-high field magnetic resonance imaging, RT-3D MRCP is better than BH-3D MRCP for general patients but BH-3D MRCP sequence can be given priority for patients with abdominal pain and excessive BMI. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.021 ObjectiveCompared to field of view optimized and constrained undistorted single-shot diffusion-weighted imaging (FOCUS DWI), we aim to explore the clinical diagnostic value for field of view optimized and constrained undistorted multiplexed sensitivity encoding diffusion-weighted imaging (FOCUS-MUSE DWI) in assessing cervical cancer. Materials and MethodsIn this prospective study, 55 cervical cancer patients confirmed by cytopathology between Febrary 2023 and September 2023 were included in the patient group, while 33 healthy volunteers with normal cervical MRI findings and negative cervical pathology were recruited in the control group. All participants underwent routine MRI, FOCUS-MUSE DWI, and FOCUS DWI scans. Two radiologists with over 15 years of experience in abdominal diagnosis independently evaluated DWI images in the patient group in a blinded fashion, subjective rating magnetic susceptibility artifacts, geometric distortion, anatomical detail, and overall image quality and objective calculating signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Apparent diffusion coefficient (ADC) values were also measured in both the patient and control groups. Differences in mean ADC values between two DWI sequences, and between groups and within groups across various International Federation of Gynecology and Obstetrics (FIGO) stages. ResultsThe subjective ratings and objective measurements for the two DWI sequences in the patient group showed good inter-rater consistency [Kappa=0.824-0.942 and intraclass correlation coefficient (ICC)=0.792-0.971, accordingly]. FOCUS-MUSE DWI had significantly higher subjective scores and lower SNR than FOCUS DWI (P<0.001); however, CNR differences between sequences were not statistically significant (P=0.893). No significant differences in mean ADC values were found between the two DWI sequences (P=0.195), while significant differences were observed within the patient group (FIGO ⅠB~ⅡA stage vs. FIGO ⅡB~Ⅳ stage), where ADC values were negatively correlated with FIGO stage (FOCUS-MUSE DWI: r=-0.667, P<0.001; FOCUS DWI: r=-0.613, P<0.001). Both DWI sequences yielded lower ADC values in the patient group compared to the control group (P<0.001). ConclusionsCompared to FOCUS DWI, FOCUS-MUSE DWI effectively reduces magnetic susceptibility artifacts and image distortion, resulting in higher image quality and clearer lesion details, which can better assist clinicians in lesion evaluation. Furthermore, ADC measurements servers an auxiliary tool in assessing FIGO staging in cervical cancer and in differentiating it from normal tissues. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.022 ^,s disease (AD) is the most common type of dementia, and is characterized by the deposition of amyloid plaques and neurofibrillary tangles in the brain, leading to progressive cognitive decline. Plasma biomarkers reflect the characteristics and severity of AD pathological changes in the brain. In addition, with the development of neuroimaging technology, MRI can clarify the specific patterns of neuronal changes in AD pathology. Both of them play increasingly important roles in the early diagnosis of AD. This article reviews the main plasma biomarkers of AD and their association with MRI neuroimaging and cognitive function, with the aim of offering a novel perspective for the diagnosis, prediction and pathological mechanism understanding of AD. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.023 ^,s disease, Parkinson^,s disease and amyotrophic lateral sclerosis can be observed in the patients with flexibly shift their own mental processes and behavior to adapt the environment change ability dropped significantly (i.e, impaired cognitive flexibility). This article aims to review and summarize the previous research progress on behavioral assessment methods and imaging studies of cognitive flexibility in neurodegenerative diseases, so as to provide a theoretical basis for the diagnosis and treatment of cognitive flexibility decline caused by neurodegenerative diseases. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.024 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.025 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.026 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.027 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.028 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.029 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.030 ^, is increasing dramatically. In recent years, the rapid development of artificial intelligence has effectively improved the efficiency and accuracy of physicians^, work, and the combination of various emerging artificial intelligence technology and imaging equipment has achieved positive results in clinical practice, showing a bright future for development, especially the non-invasive cardiac magnetic resonance technology that can simultaneously evaluate the structure and function of heart. This paper summarizes the research status, progress and limitations of the combination of deep learning and magnetic resonance in the diagnosis and treatment of coronary artery disease, aiming to improve the efficiency and accuracy of physicians^, diagnosis and treatment, promote the timely diagnosis and early intervention of coronary artery disease, and promote the development and progress of artificial intelligence in the field of imaging medicine in China. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.031 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.032 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.033 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.034 Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.035 ^,s daily quality of life. When malignant lesions occur in benign EMs lesions, ovarian cancer caused by malignant EMs is clinically referred to as endometriosis associated ovarian cancer (EAOC). Previous studies have not paid enough attention and recognization to the disease that " EMs deteriorates into EAOC". Therefore, how to systematically identify and diagnose this kind of disease through multimodal MRI has become an urgent problem to be solved in clinical practice. Effective early diagnosis can enable patients to get timely intervention treatment, which is crucial to improve the quality of life of patients. In this paper, the clinicopathological features and diagnosis status of these diseases will be introduced, and the characteristic manifestations and application value of different MRI techniques will be detailed, which will help to guide clinicians to diagnose and evaluate the malignant transformation from EMs to EAOC more reasonably and appropriately. ]]> Wed,20 Nov 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.11.036 Wed,20 Nov 2024 00:00:00 GMT