http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202401 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.1674-8034.2024.01.001 ^,s health and quality of life. MRI is an important tool in the diagnosis of breast diseases. With the improvement of software and hardware technology in recent years, more and more quantitative features of MRI have been found, and show greater advantages over non-quantitative features such as morphology. In this article, we briefly reviewed the application of MRI quantitative analysis methods, including conventional MRI sequences, MRI new techniques and methods, and MRI radiomics and deep learning, in the differential diagnosis of benign and malignant breast lesions, the efficacy of adjuvant and neoadjuvant therapy, and prognosis. At the same time, several problems were put forward. The era of accurate diagnosis and treatment of breast cancer has put forward higher requirements for MRI research. It is hoped to inspire researchers to further explore the quantitative features and quantitative analysis methods of MRI in the future, combined with non-quantitative features, to promote the application of MRI in the diagnosis and treatment of breast cancer, promote clinical transformation, and improve the survival time and quality of life for breast cancer patients. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.002 ObjectiveTo explore the value of magnetic resonance imaging (MRI) features combined with clinicopathologic features in distinguishing human epidermal growth factor receptor 2 (HER-2) expression status, especially in HER-2-low breast cancer. Materials and MethodsThe pre-treatment breast MRI images of 205 patients with pathologically confirmed breast cancer from January 2018 to December 2019 at Fudan University Shanghai Cancer Center were retrospectively analyzed. All patients underwent a bilateral breast scan and a dynamic contrast enhancement MRI. HER-2 status was categorized into HER-2 negative (including HER-2-zero and HER-2-low) and HER-2 positive based on immunohistochemistry and fluorescence in situ hybridization results. Clinicopathologic features and MRI features were analyzed in each group. Clinicopathologic features included age, menstrual status, estrogen receptor (ER), progesterone receptor (PR), hormone receptor (HR), molecular subtypes and Ki-67 level. MRI features included fibroglandular tissue, background parenchymal enhancement, multifocal or multicentric, intratumoral T2WI high signal, peritumoral edema, lesion type, lesion size, shape, margin and internal enhancement pattern of the mass, and distribution and internal enhancement pattern of non-mass enhancement. In the univariate analysis, for the comparison between HER-2 negative and positive groups, an independent sample t-test was used for age, a Mann-Whitney U test was used for lesion size, and a χ² test was used for the remaining clinicopathologic and MRI features. For the comparison of HER-2 zero, low, and overexpression groups, a one-way analysis of variance was used for age, a Kruskal-Wallis H test was used for lesion size, and a χ² test was used for the remaining clinicopathologic and MRI features. Multifactorial analysis was performed by binary logistic regression analysis, and the diagnostic efficacy of the model was evaluated by area under the curve (AUC), sensitivity and specificity of the receiver operating characteristic. ResultsThere were 67 HER-2-positive (HER-2-overexpression), 59 HER-2-zero and 79 HER-2-low cases. Between the HER-2-negative and positive group, the difference in clinicopathologic features of ER, PR, HR, and molecular typing were statistically significant (all P<0.001), and the differences in the margin of the mass in MRI features were statistically significant (P=0.020). Further comparing the HER-2 low with HER-2-zero group or HER-2-overexpression group, the differences in clinicopathologic features were statistically significant in ER, PR, HR, molecular subtypes, and Ki-67 levels (with a cutoff value of 40% of the median) between HER-2-low and HER-2-zero or HER-2-overexpression group (ER, PR, HR, and molecular subtypes: all P<0.001; Ki-67: P<0.001, P= 0.037); among the MRI features, the differences in the intratumoral T2WI hyperintensity and mass shape were statistically significant between HER-2-low and HER-2-zero or HER-2-overexpression group (intratumoral T2WI hyperintensity: P=0.031, P=0.011; mass shape: P=0.012, P=0.025), and the difference in the mass margin was statistically significant between HER-2-zero and HER-2-low group (P=0.036). In the multifactorial analysis combining clinicopathologic and MRI features, PR status, Ki-67 and mass shape were independent predictors to distinguish HER-2-low and -zero expression, with an AUC, sensitivity, and specificity of 0.772, 79.7%, and 70.9%, respectively; and PR status and intratumoral T2WI hyperintensity were independent predictors to distinguish HER-2-low versus -overexpression, with an AUC, sensitivity, and specificity of 0.793, 69.8% and 76.1%, respectively. ConclusionsMRI features have a differential diagnostic value for HER-2 expression status in breast cancer, especially in distinguishing HER-2 low-expression and HER-2-zero or -overexpression status. Combining clinicopathologic features and MRI features, PR positivity, Ki-67 lower than 40%, irregular mass shape, and intratumoral T2WI hyperintensity can indicate HER-2 low-expression breast cancer. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.003 ObjectiveTo investigate the diagnostic significance of R2^* values obtained from iterative decomposition of water and fat with echo asymmetrical and least-squares estimation quantitation sequence (IDEAL-IQ) in distinguishing between benign and malignant breast tumors, and compare these values with those obtained from traditional multiple echo T2^* gradient recalled echo (GRE) series. Materials and MethodsA total of 50 cases of benign tumors in 42 patients admitted to the First Hospital of China Medical University from September 2021 to October 2023 were retrospectively analyzed. The propensity score matching was used to match the longest diameter of the largest plane of the tumor in picture archiving and communication systems (PACS), and 150 cases of malignant tumors in 150 patients were included according to the 1∶3 ratio. Malignant tumors were grouped based on the positive/negative expression of prognostic factors such as estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER-2). All patients underwent multi-parameter MRI with IDEAL-IQ and multi-echo T2^* GRE sequences, and the following quantitative parameters were measured: R2^* IDEAL from IDEAL-IQ sequence, R2^* GRE from multi-echo T2^* GRE sequence, apparent diffusion coefficient (ADC), and tumor diameter. The intra-class correlation coefficient (ICC) was used to evaluate the consistency between the researchers. Depending on the type of raw data, the differences of each parameter were compared and analyzed using one-way analysis (independent samples t-test, Mann-Whitney U-test, etc.). Spearman correlation analysis was used to analyze the correlation between R2^* IDEAL and R2^* GRE, as well as their correlation with ADC. The difference between R2^* IDEAL and R2^* GRE was compared by paired sample t-test. A joint diagnostic model was established by using logistic regression analysis, and the receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to analyze the efficacy of single and combined parameters in differentiating benign and malignant breast tumors. ResultsCorrelation analysis showed that R2^* IDEAL and R2^* GRE in patients with breast tumors were moderately strongly correlated (r=0.763, P<0.001), and both were weakly negatively correlated with ADC values [r=-0.300 (R2^* IDEAL), -0.306 (R2^* GRE), P<0.001]. In benign group and malignant group, R2^* IDEAL and R2^* GRE showed moderate correlation (r=0.745, 0.680, P<0.001), and there was no correlation between them and ADC. The R2^* values obtained by the two sequences were statistically different (P<0.05). There was a significant difference in R2^* IDEAL between benign and malignant groups (P<0.001), and the R2^* value of luminal HER-2 negative group was the highest. For a single parameter, ADC value had the largest AUC (0.857) in differentiating benign and malignant groups. For the combined parameters, R2^* IDEAL+ADC had the largest AUC (0.927) in differentiating benign group from luminal negative group. The differences were statistically significant (P<0.05). ConclusionsThe R2^* value generated by IDEAL-IQ sequence can be used to distinguish benign and malignant breast tumors, and may be another non-contrast parameter in addition to ADC to assist the differentiation of benign and malignant breast tumors. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.004 ObjectiveTo investigate the relationship between MRI clinicopathological features and breast cancer susceptibility gene (BRCA) gene mutation in breast cancer. Materials and MethodsRetrospective collection clinicopathological, MRI and prognosis data of 81 BRCA gene non-mutant breast cancer and 76 BRCA gene mutant breast cancer patients (including 38 BRCA1 gene mutation and 38 BRCA2 gene mutation) diagnosed and detected BRCA gene status by next generation sequencing technology in Fudan University Shanghai Cancer Center from June 2011 to July 2017. Chi-square test, Fisher^,s exact test and multivariate logistic regression were used to analyze the differences of clinicopathologic and MRI features between BRCA gene mutant and non-mutant, BRCA1 gene mutant and BRCA2 gene mutant breast cancer patients. ResultsThere was a statistically significant difference in the distribution of histological types between BRCA gene mutation group and non-mutant breast cancer (P=0.037). The proportion of BRCA-mutated breast cancer with invasive ductal carcinoma (IDC) was high, and the proportion of BRCA1 and BRCA2 mutated breast cancer with IDC was 92.11% and 94.74%, respectively. In univariate analysis, BRCA non-mutant breast cancer was more performed as I+Ⅱ other than type Ⅲ enhancement curve (P=0.041). There was a statistically significant difference in the distribution of mass lesions between BRCA1 gene mutation breast cancer and BRCA2 gene mutation breast cancer (P=0.030). The proportion of BRCA2 gene mutation lesions showing irregular shape was higher, accounting for 87.10% of BRCA2 gene mutation lesions showing mass type. There was no significant difference in fibroglandular composition and BPE characteristics between BRCA mutated and non-mutated breast cancer. ConclusionsHistology, molecular subtype and Ki-67 index were different in BRCA mutant and non-mutant breast cancer. Lesion type and enhancement curve type on MRI were also associated with BRCA gene status in univariate analysis. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.005 ObjectiveTo develop a spatiotemporal heterogeneity based radiomics model for the early prediction of pathological complete response (pCR) in triple-negative breast cancer (TNBC). Materials and MethodsThe data of 173 TNBC patients who received neoadjuvant chemotherapy (NAC) in our hospital from September 2017 to March 2022 were retrospectively analyzed. MRI images of each patient were collected at pretreatment (Pre-) and after two cycle of NAC (During-). The 55 patients from the DUKE university constituted the external validation cohort. Radiomics features were extracted from the intratumoral subregions and peritumoral region to characterize spatial heterogeneity, and the changes of features before and during NAC (Delta-) were calculated to characterize temporal heterogeneity. The radiomics models were developed by least absolute shrinkage and selection operator (LASSO) regression using the Pre-, During-, and Delta- features. Multi-factor logistic regression was used to integrate single-mode models to develop the longitudinal fusion (Stacking) model. The diagnostic performance and clinical application value of models were evaluated by the receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). ResultsFinally, 8, 4 and 10 features were respectively selected from the Pre-‍, During- and Delta- feature sets to construct the models. The Pre- model based on spatial heterogeneity could predict pCR, with area under the curve (AUC) of 0.74, 0.71 and 0.71 in the training set, validation set and external validation set, respectively. In the training and validation sets, the Stacking model achieved the best performance to predict pCR, and the AUC was 0.86 in both sets. DCA indicated that the value of Stacking model was highest in clinical practice. ConclusionsFeatures based on MRI spatial heterogeneity can effectively predict the pCR of TNBC. The longitudinal fusion model integrated spatiotemporal heterogeneity has the potential to further improve the prediction performance. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.006 ObjectiveTo select the baseline MRI features and clinicopathological factors that relate to tumor shrinkage patterns of breast cancers after neoadjuvant therapy (NAT), and construct a predicting nomogram. Materials and MethodsA total of 272 consecutive patients with breast invasive ductal carcinoma who underwent NAT and surgical resection in our hospital were retrospectively analyzed. The patients were randomly divided into training group (190 cases) and validation group (82 cases). According to the morphological changes of tumor on MRI before and after NAT, the shrinkage patterns were divided into type I shrinkage (complete response, concentric shrinkage) and type Ⅱ shrinkage (non-concentric shrinkage, stable and progressing disease). Baseline MRI features (size, enhancement mode, semi-quantitative parameters of enhancement, etc.) together with clinical and pathological information (degree of differentiation, immunohistochemical molecular type, etc.) were collected. Univariate and multivariate logistic regression analysis were used to select effective factors and to establish the predictive models. The area under the curve (AUC) was used to evaluate the diagnostic performance of the model and select the best one to construct a nomogram. ResultsType I and Ⅱ shrinkage pattern were seen in 174 (64.0%) and 98 (36.0%) patients respectively. Baseline MRI enhancement mode and hormone receptor (HR) were independently correlated with shrinkage types with AUCs of 0.844 [95% confidence intervals (CI): 0.784-0.892] and 0.593 (95% CI: 0.519-0.663) respectively in predicting type Ⅱ shrinkage. A combined predictive model was established with AUC of 0.890 (95% CI: 0.837-0.931), higher than that of any single parameter (P<0.05) with accuracy of 85.8%, and a nomogram was constructed. The AUC and accuracy for predicting type Ⅱ shrinkage in the validation group was 0.871 (95% CI: 0.779-0.935) and 82.9%. ConclusionsNon single mass enhancement on MRI and positive HR are two independent risk factors for type Ⅱ shrinkage after NAT in breast cancer. A simple analysis of tumor enhancement mode and HR can provide a reasonable evaluation of the feasibility and effect of breast conservation after NAT. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.007 ObjectiveTo investigate the preoperative MRI features and clinicopathological features associated with breast conserving surgery (BCS) failure and success. Materials and MethodsThe data of patients who planned to undergo BCS and underwent preoperative MRI examination from March 2018 to May 2021 were retrospectively analyzed, and divided into failure group and success group according to whether convert to mastectomy. Image features collected included: size, right and left side, whether the mass was a mass, depth, amount of fibroglandular tissue, whether it was symmetrical, associated signs, background parenchymal enhancement (BPE), temporal intensity profile, T1 signal, and T2 signal. Clinicopathological features included patient age, human epidermal growth factor receptor 2 (HER-2), estrogen receptor (ER), progesterone receptor (PR), proliferation-marker Ki-67, molecular subtype, and intraductal carcinoma or not. Univariate and multivariate logistic regression were used to analyze the imaging features and clinicopathological features between the two groups, and differences were considered statistically significant at P<0.05. ResultsThe sample sizes of the BCS failure and success groups were 47 and 91 respectively. Univariate and multivariate logistic regression analysis showed that BPE was significantly different between the two groups. Using BPE minimal reinforcement as a reference, there was no statistical difference between it and BPE mild reinforcement [dominance ratio (OR)=0.317, 95% confidence interval (CI): 0.374-6.552, P=0.654] There was a statistical difference between it and moderate enhancement (OR=1.674, 95% CI: 1.392-26.420, P=0.022) and heavy enhancement of BPE (OR=1.569, 95% CI: 1.128-25.809, P=0.044). However, there was no significant difference in other clinicopathological and imaging features between failure group and success group. ConclusionsBPE has a certain correlation with the success of BCS, higher BPE levels suggest a greater likelihood of BCS failure, which may be used as an effective indicator for the feasibility analysis of preoperative MRI evaluation of BCS and the formulation of accurate surgical strategies. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.008 ObjectiveTo investigate the application value of fractional-order calculus (FROC) model diffusion weighted imaging (DWI) combined with simultaneous multi-slice (SMS) acquisition technology in the differentiation between benign and malignant breast lesions. Materials and MethodsA total of 124 patients (with 141 lesions) who underwent breast MRI scan at our hospital from January 2021 to December 2022 were retrospectively analyzed. All patients underwent DWI scanning with two sets of multiple b values (14 b values, the highest b value was 3 000 s/mm²) using a 3.0 T MRI system. One group underwent conventional single-shot echo planar imaging (SSEPI-DWI), while the other group underwent SMS-SSEPI-DWI. Independent sample t test or Mann-Whitney U test was used to compare the image quality scores, FROC model parameters (D, β, μ) and apparent diffusion coefficient (ADC) value between benign and malignant groups. The receiver operating characteristic curve was used to evaluate the diagnostic efficacy of each parameter. Bland-Altman plots were used to assess the agreement between the two DWI-derived parameters. ResultsThe ADC, D and β values of malignant breast lesions were significantly lower than those of benign breast lesions (P<0.05), while the μ value of malignant breast lesions was notably higher than that of benign breast lesions (P<0.05). Among the SSEP-DWI and SMS-SSEP-DWI sequences, the D value had the largest area under the curve, the β value demonstrated the highest diagnostic sensitivity, and the D value displayed the highest specificity. Bland-Altman plot indicated unbiased and substantial agreement between the corresponding parameter values derived from the two DWI sequences were unbiased and had good agreement. ConclusionsThe FROC model based on SMS-SSEPI DWI can provide high-quality images and lesion characteristic parameter values with shorten scan time. Compared with SSEPI-DWI. It has a comparable diagnostic performance in distinguishing between benign and malignant breast lesions.Particularly. The D and β value show better diagnostic performance. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.009 ObjectiveTo train and verify an automatic image classification model based on deep learning and program. Materials and MethodsA total of 862 breast MRI images were collected from the picture archiving and communication system (PACS) system from January 2010 to November 2020 (dataset I). The images were divided into three categories: T2WI, fat-suppressed (FS) T2WI, apparent diffusion coefficient (ADC). A deep learning model of sequence differentiation was trained with the dataset I. Another group of 377 breast MRI images from February 2013 to April 2020 (data set Ⅱ) were collected and divided into three categories: no-contrast (NoC), contrast enhanced early (CEearly), contrast enhanced (CE) according to the phase characteristics of dynamic contrast-enhanced (DCE). A deep learning model of phase differentiation of DCE was trained with the dataset Ⅱ. A third group of 95 breast MRI images (data set Ⅲ) were collected from October 2021 to December 2021 for independent validation of the classification models (different sequences and different phases of DCE). Then the diffusion weighted imaging (DWI) parameters were classified by the program in the data set Ⅲ (DWI-high and DWI-low). Using the classification results of radiologists on images as the gold standard, according to image sequence, enhancement characteristics and parameters on as the gold standard, the confusion matrix was used to evaluate the classification performance of the model. ResultsIn the sequence classification model, the overall prediction accuracy was 92.0%, and the prediction accuracy for each sequence of ADC, T2WI and FS T2WI were 100.0%, 84.9%, and 100.0%, respectively. In the DCE classification model, the overall prediction accuracy was 90.4%, and the prediction accuracy for each sequence of NoC, CEearly, and CE were 89.7%, 39.2%, and 95.7%,respectively. The program^,s classification of DWI-high and DWI-low was exactly the same as that of the radiologist. ConclusionsUsing deep learning model and program technology to classify the image sequence, phase and parameters of multi-parameter breast MRI, the output results are highly consistent with the classification results of physicians, which basically meet the clinical needs. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.010 ObjectiveUsing diffusion tensor imaging (DTI) to observe the changes in the microstructure of white matter in children with autism spectrum disorder (ASD) before and after acupuncture treatment, in order to explore the value of acupuncture in treating ASD and the role of DTI in evaluating the effectiveness of acupuncture. Materials and MethodsProspective inclusion of children diagnosed with ASD in our hospital from November 2021 to October 2022, randomized using a random number table into an acupuncture group or a sham acupuncture group, for 12 weeks of intervention. Before treatment (week 0) and after treatment (week 12), the Child Autism Rating Scale (CARS), Autism Behavior Checklist (ABC), Autism Treatment Evaluation Checklist (ATEC) and DTI examination were performed. The changes in scores of various scales between the two groups were compared, and the tract-based spatial statistics (TBSS) was used to analyze the differences in fractional anisotropy (FA) of white matter between the two groups. Then compare the differences in mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD) of brain regions with varying fractional anisotropy (FA), and explore the correlations between scale ratings and DTI parameters. ResultsCompared to the sham acupuncture group, the acupuncture group showed a significant decrease in various scale scores after treatment, and the difference was statistically significant (P<0.05). There was a statistically significant difference in FA values between the two groups after treatment (P<0.05), but no significant difference in RD values (P>0.05). In terms of AD values, there was a statistically significant difference between the two groups in the left inferior longitudinal fasciculus (P<0.05). The correlation analysis revealed in children with ASD, the ATEC scores were negatively correlated with the FA values of the right uncinate fasciculus, positively correlated with the RD values of the right infero-frontal-occipital fasciculus, right inferior longitudinal fasciculus, and right uncinate fasciculus, and positively correlated with the AD values of the right uncinate fasciculus. The CARS scores were positively correlated with the AD values of the right uncinate fasciculus (P<0.05). The FA values of the right inferior longitudinal fasciculus were negatively correlated with language problems and sensory abnormalities in children with ASD, while the RD values were positively correlated with social impairments and sensory abnormalities. The FA values of the right uncinate fasciculus were negatively correlated with language problems, social impairments, and sensory abnormalities, while the RD values were positively correlated with these clinical symptoms. The AD values of the right uncinate fasciculus were positively correlated with social impairments and health issues. In addition, the FA values of bilateral infero-frontal-occipital fasciculus were negatively correlated with sensory abnormalities, and the RD values of the right infero-frontal-occipital fasciculus were positively correlated with social impairments and sensory abnormalities. The RD values of the right superior longitudinal fasciculus were positively correlated with sensory abnormalities. The AD values of the left anterior thalamic radiation were positively correlated with sensory abnormalities (P<0.05). ConclusionsAcupuncture may improve clinical symptoms in children with ASD, particularly in areas such as speech, social interaction, perception, and health problems, possibly by promoting the integrity of brain white matter fiber bundles. This further indicates the important value of DTI in evaluating the therapeutic effect of acupuncture. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.011 ObjectiveTo investigate the imaging features of striatal-thalamo-cortical (STC) circuit disturbance in patients with Parkinson^,s disease (PD) from the perspective of metabolic network connectivity. Materials and MethodsThe data of cerebral blood flow (CBF) from 62 patients with PD and 65 healthy control (HC) subjects were obtained using arterial spin labeling imaging. For both the HC and PD groups, the connectivity properties of metabolic networks within basal ganglia region-cortical circuit were calculated based on their CBF information, including seed-connectivity, cortical-connectivity and modular-connectivity. Permutation test were then employed for the intergroup comparisons of these three types of network connectivity, respectively. ResultsThere were no significant differences in terms of age, sex, education and cognitive scale scores between the two groups (P>0.05). Compared with HC subjects, the value of seed-connectivity in patients with PD was significantly higher in the bilateral inferior temporal gyrus, bilateral fusiform gyrus, bilateral medial frontal gyrus, left middle occipital gyrus and right posterior central gyrus; whereas were significantly lower in the bilateral middle temporal gyrus, left rectus gyrus, left superior temporal gyrus, bilateral inferior frontal gyrus, bilateral precuneus, right supplementary motor area and bilateral inferior parietal gyrus (P<0.05); there were significantly enhanced cortical-connectivity with sensorimotor cortex, whereas significantly weakened cortical-connectivity with motor cortex and parietal-occipital cortex (P<0.05); the modular-connectivity was significantly increased in modules of frontal and motor, modules of sensorimotor and parietal-occipital as well as modules of parietal-occipital and temporal, whereas significantly decreased in modules of frontal and temporal, modules of motor and parietal-occipital and modules of sensorimotor and temporal (P<0.05). ConclusionsPatients with PD exhibited with metabolic disturbance of neural network, involving extensive connectivity abnormalities in the STC loop with basal ganglia region as the hub . ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.012 ObjectiveTo assess microstructural changes in the posterior thalamus of type 2 diabetes mellitus (T2DM) patients using diffusion kurtosis imaging (DKI) and investigate the correlation between DKI parameter changes, cognitive function scores, and alterations in short-chain fatty acids in the gut. Materials and MethodsDKI data were collected from both sides of the thalamus in 57 T2DM patients [comprising 29 T2DM-mild cognitive impairment (MCI) cases and 28 T2DM-nonMCI and 30 healthy controls (HC group)]. Various DKI parameters including fractional anisotropy (FA), mean kurtosis (MK), radial kurtosis (RK), and fractional anisotropy of kurtosis (FAK) were measured. Additionally, short-chain fatty acid levels in the gut were assessed. Correlation analyses were performed between the average DKI parameter values in different brain regions among the three groups, cognitive function scores, and short-chain fatty acids. ResultsThe T2DM-MCI group exhibited significantly lower left thalamic MK values compared to both the T2DM-nonMCI and HC groups (P<0.05). In comparison to HC, the T2DM-MCI group showed a general decrease in left thalamic RK, right thalamic FA, and KFA values (P<0.05). Pairwise comparisons revealed statistically significant differences in left thalamic RK values between HC and T2DM-nonMCI groups (P<0.05), as well as in right thalamic FA and KFA values between T2DM-nonMCI and T2DM-MCI groups (P<0.05). Furthermore, in T2DM patients, there was a positive correlation between right thalamic FA and FAK values and MoCA scores (r=0.328, P=0.015; r=0.435, P=0.001). Left thalamic RK values were positively correlated with butyric acid (r=0.431, P=0.001). Left thalamic MK values exhibited positive correlations with MoCA scores and butyric acid (r=0.294, P=0.030; r=0.287, P=0.033). Right thalamic FAK values showed a negative correlation with TMT-A scores (r=-0.318, P=0.018). ConclusionsMicrostructural changes in the thalamus of T2DM patients may be an important physiological mechanism underlying cognitive impairment, and gut butyric acid levels may partially influence the microstructural integrity of the left thalamus. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.013 ObjectiveTo investigate the temporal properties of brain functional connectivity in patients with type 2 diabetes mellitus (T2DM) and the correlation between dynamic functional connectivity and clinical parameters by using dynamic functional network connectivity (dFNC) analysis. Materials and MethodsThe clinical and imaging data of 31 patients with T2DM were prospectively collected, and the diabetes-related biochemical indicators and neuropsychological test scores were recorded. At the same time, 32 healthy controls (HC) matched with age, gender and education level were recruited. Four functional connectivity states and three dFNC indexes (mean dwell time, fraction time, number of transitions) were obtained by using sliding time window technology. Two independent samples t-test was used to calculate the differences of FNC matrix and dFNC indexes between groups in different states. Spearman correlation analysis was used to calculate the correlation between dFNC indexes and clinical data in T2DM group. ResultsIn state 1 weak connection, compared with HC group, T2DM group had longer mean dwell time (t=2.086, P<0.05). In state 3 local strong connection, compared with HC group, T2DM group had shorter mean dwell time (t=-2.250, P<0.05) and smaller fraction time (t=-2.582, P<0.05) ; the functional connectivity between default mode network (DMN) and visual network (VIS) was decreased (t=-4.875, P<0.05, FDR corrected). The duration of T2DM was positively correlated with the mean dwell time of state 1 weak connection (r=0.42, P<0.05), while other diabetes-related biochemical indexes and cognitive function scores were not correlated with dFNC indexes (P>0.05). ConclusionsThe dFNC analysis can capture more potential information about the changes of brain network connectivity in T2DM patients, and reveal the complex temporal characteristics and activity patterns of brain networks, which is expected to provide a new perspective for the neurobiological mechanisms of T2DM related cognitive impairment. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.014 ObjectiveTo explore the value of a nomogram constructed by integrating radiomics and deep learning-based score (RD-score) with hematological inflammatory markers in preoperatively predicting the prognosis of glioma. Materials and MethodsA total of 166 clinically diagnosed glioma patients were retrospectively enrolled and randomly divided into a training set (133 cases) and a validation set (33 cases) in an 8:2 ratio. Clinical and hematological inflammatory marker of the patients were collected. Composite variables, including systemic immune inflammation index (SII), systemic immune response index (SIRI), derived neutrophil-to-lymphocyte ratio (dNLR), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) were constructed, and their optimal cut-off values were calculated. Delineating the volume of interest (VOI) for gliomas and extracting radiomics and deep learning features, utilizing least absolute shrinkage and selection operator (LASSO)-Cox for feature selection. Constructing radiomics-score (Rad-score), deep learning-score (DL-score), and RD-score, and comparing their receiver operating characteristic area under the curve (AUC) to assess predictive performance. Kaplan-Meier survival analysis was used to stratify glioma patients based on their RD-score. Integrating clinical data, hematological inflammatory marker, and RD-score, employing multivariable Cox regression to build RD-score model, clinical hematology model, and joint model to predict overall survival (OS). Calculating AUC to evaluate the efficiency of each model in predicting glioma 1, 3, and 5-year survival rates. Drawing joint model nomogram and assessing their performance using C-index, calibration curves, and decision curve analysis (DCA). ResultsAfter feature selection, 10 radiomics features and 8 deep learning features were selected. The predictive performance of RD-score surpassed that of Rad-score and DL-score (DeLong test, P<0.05). The constructed RD-score divided gliomas into high-risk group (RD-score≥1.09) and low-risk group (RD-score<1.09). The results of the multivariable Cox regression showed that age, tumor grade, postoperative chemotherapy, SIRI, and RD-score were independent prognostic factors for glioma. The joint model, incorporating these factors, exhibited higher AUC in the training and validation sets compared to the RD-score model and clinical hematology model (DeLong test, P<0.05). The visual nomogram of the joint model predicted OS with C-indices of 0.844 and 0.849 in the training and validation sets, respectively. Calibration curves indicated good consistency between observed and predicted values, and DCA demonstrated a high net benefit for the nomogram. ConclusionsThe nomogram constructed by combining radiomics and deep learning-based RD-score with clinical- hematological inflammatory marker can effectively predict the prognosis of glioma patients preoperatively. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.015 ObjectiveTo study the changes of percentage fluctuation amplitude (PerAF) in patients with primary angle-closure glaucoma (PACG) at rest using resting-state functional magnetic resonance imaging (rs-fMRI) technique. Materials and MethodsA total of 31 cases of PACG patients diagnosed in the ophthalmology department of Jiangxi Provincial People^,s Hospital were included. During the same period, 31 sex, age, and duration of education-matched healthy controls (HC) were included in the control group. Whole-brain rs-fMRI scans were performed on each subject to collect PerAF signals. One-sample t-test and two-sample t-test were used to compare PerAF data across and between groups, respectively. ResultsCompared with HC group, subjects in the PACG patient group had significantly lower PerAF in the left supraparietal gyrus (t=-3.9421, P<0.001), orbital (t=-3.4619, P<0.001), left orbital median frontal gyrus (t=-3.6709, P<0.001), bilateral right median frontal gyrus (t=-3.8257, P<0.001), right inferior frontal gyrus deltoid (t=-3.6708, t=-4.0375, P<0.001); left supramarginal gyrus (t=-3.9570, P<0.001), inferior parietal marginal angular gyrus (t=-3.8230, t=-3.8730, P<0.001), right superior parietal gyrus (t=-4.4581, P<0.001), postcentral gyrus (t=-3.7825, P<0.001), and paracentral lobule (t=-4.0816, P<0.001); right middle temporal gyrus (t=-3.8402, P<0.001); left lingual gyrus (t=-3.5758, P<0.001); left anterior cingulate and paracingulate cingulate gyrus (t=-3.4718, P<0.001), supplementary motor area (t=-3.7209, P<0.001), and right inferior cerebellar area 7b (t=-3.9479, P<0.001) (P<0.001 at voxel level, P<0.05 at cluster level, Gaussian random field corrected). ConclusionsPatients with PACG have abnormal PerAF values in multiple brain regions involving primary and higher visual cortex and brain regions associated with visual, emotional, and cognitive regulation. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.016 ObjectiveTo observe the intervertebral foramen segments of cervical nerve roots by diffusion tensor tractography (DTT) and quantitatively analyze diffusion tensor imaging (DTI) parameters of healthy volunteers, to provide the reference for clinical diagnosis and treatment of cervical spondylotic radiculopathy. Materials and MethodsDTI and DTT of the cervical nerve roots were performed in fifty healthy volunteers (25 males and 25 females). Mean fractional anisotropy (FA) and ADC values of the cervical nerve roots (both sides of cervical nerve roots C5 to C7, proximal,middle and distal to the cervical foraminal zone) were obtained.Differences among various segments of cervical nerve roots were compared with ANOVA test; Differences between two sides of the cervical nerve roots at the same cervical segment were compared with paired samples t-test; Differences between the proximal, middle and distal nerve to the cervical foraminal zone at the same cervical segment were compared with the LSD test. Nerve fiber bundle reconstruction was performed on the both sides of cervical nerve roots C5 to C7. ResultsThere was no significant difference in FA and ADC values among the proximal, middle and distal nerve to the cervical foraminal zone in different segments of C5 to C7. There was no significant difference in FA and ADC values between the left and right sides of the nerve roots at the same cervical segment. The difference in FA and ADC values between the nerve roots at three different levels of the same segment of C5 to C7 was significant (P<0.05). The whole length of the cervical nerve roots C5 to C7 could be visualized clearly by using DTT. ConclusionsDTI and DTT can quantitatively evaluate the cervical nerve roots in the cervical foraminal segment and visually reconstruct the cervical nerve bundles, and can provide quantitative parameters and visual reconstruction images of cervical nerve roots in the proximal, middle and distal segments of the intervertebral foramina for the diagnosis of cervical spondylotic radiculopathy. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.017 ObjectiveTo assess the accuracy of cardiac magnetic resonance (CMR) in evaluating left atrial/ left atrial appendage (LA/LAA) thrombus in patients with atrial fibrillation (AF) and to analyze the difference in diagnostic accuracy of a number of imaging sequences. Materials and MethodsBetween 2000 and 2022, a systematic search was carried out across multiple databases such as PubMed, Web of Science, Embase, the Cochrane Library, China National Knowledge Infrastructure, VIP databases, Wangfang date bases to compare the effectiveness of CMR with transesophageal echocardiogram (TEE) or surgical pathology in detecting LA/LAA thrombus. The literature was divided into four categories: (1) cine-cardiac magnetic resonance (cine-CMR); (2) contrast enhanced magnetic resonance angiography (CE-MRA); (3) contrast enhanced-cardiac magnetic resonance (CE-CMR); (4) CMR. Statistical analysis was then performed separately to extract relevant clinical data. Extracting pertinent clinical records, the analysis and calculation of sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, receiver operating characteristic, and area under the curve (AUC) were conducted using Stata17.0, Review Manager 5.3, and Meta-DiSc 1.4. ResultsThe evaluation encompassed a total of 868 patients across eleven publications. Cine-CMR exhibits a pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, diagnostic odds ratio, and AUC of 92%, 93%, 12.8, 0.08, 154, 0.93, respectively; CE-MRA demonstrates values of 91%, 100%, 476.4, 0.09, 5 044, 0.99, respectively; CE-CMR demonstrates values of 96%, 100%, 247.5, 0.04, 6 656, 1.00, respectively; and CMR demonstrates values of 99%, 99%, 95.1, 0.01, 7 357, 1.00, respectively. ConclusionsCMR has been shown to be a favorable diagnostic method for the detecting and evaluating LA/LAA thrombus, in individuals diagnosed with atrial fibrillation. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.018 ObjectiveTo evaluate and predict the early curative effect of transcatheter arterial chemoembolization (TACE) for hepatocellular carcinoma based on contrast-enhanced magnetic resonance imaging (CE-MRI) histogram parameters of MRI. Materials and MethodsSixty-four patients with hepatocellular carcinoma confirmed by pathological biopsy or clinically diagnosed from June 2018 to December 2021 were selected for study. All patients underwent routine MR scan and multi-phase dynamic enhanced T1WI contrast-enhanced scan within 1 month before TACE treatment and 4-6 weeks after the first TACE treatment. According to the modified solid tumor efficacy evaluation criteria (mRECIST), the patients were divided into effective group of 34 cases and ineffective group of 30 cases. The HCC maximum axial T1WI images (arterial phase, portal phase and delayed phase) of HCC maximum slice images were selected for all patients, and the histogram features of the lesions were manually extracted by sketching ROI with MaZda software, including mean, variance, skewness, kurtosis and the values of the 1st, 10th, 50th, 90th and 99th percentiles (recorded as Perc1, Perc10, Pere50, Perc90 and Perc99, respectively). Statistical software was used to compare the differences of histogram parameters between effective group and ineffective group before and after TACE treatment. The parameters with statistical differences in the postoperative efficacy of HCC were evaluated by the receiver operating characteristic (ROC) curve, and the valuable parameter values and thresholds were obtained. ResultsThe parameters with statistically significant differences between the two groups before TACE treatment including mean value, Perc50, Perc90, Perc99 in arterial phase, Perc1 in venous phase, and peak value in delayed phase (P<0.05); the parameters with statistically significant differences between the two groups after TACE treatment including the mean value of delay period, Perc50, Perc99 (P<0.05); there was no statistically significant difference in the other parameters between the two groups before and after TACE treatment (P>0.05). The ROC curve results showed that the efficacy of each parameter was as follows: preTACE arterial phase mean>postTACE delay phase Perc99>preTACE arterial phase Perc90>postTACE delay phase mean>preTACE delay phase kurtosis>postTACE delay phase Perc50>pretTACE delay phase Perc50>preTACE arterial phase Perc99. The area under the ROC curve of preTACE arterial phase mean was the highest, with a value of 0.710 (95% CI: 0.583-0.817). ConclusionsThe histogram features of CE-MRI can effectively evaluate and predict the characteristics of early curative effect after TACE of hepatocellular carcinoma, which helps guide clinical treatment plans. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.019 ObjectiveTo investigate the feasibility of using quantitative T2^*/R2^* values derived from the ZOOM-mDixon sequence for evaluating lymph node metastasis in pancreatic ductal adenocarcinoma. Materials and MethodsA retrospective analysis was conducted on 59 patients with pathologically confirmed pancreatic ductal adenocarcinoma, including 31 patients with lymph node metastasis (LNM) and 28 patients without lymph node metastasis (nLNM). All patients underwent preoperative MRI scans, which included the ZOOM-mDixon sequence. The analysis involved examining clinical data, such as age and preoperative carbohydrate antigen (CA)19-9 levels, routine radiological features including location and morphology, and T2^*/R2^* values. Intra-class correlation coefficients (ICC) were used to evaluate repeatability, while U-tests, t-tests, or χ² tests were used to compare differences between the two groups. The receiving operator characteristic (ROC) curve was plotted, and the area under curve (AUC) was calculated to assess the diagnostic performance of quantitative indicators. ResultsThe inter-and intra-group ICC values for T2^*/R2^* were excellent, ranging from 0.83 to 0.97. No statistically significant differences were observed in age, tumor morphology, short diameter of the tumor, tumor location, preoperative CA19-9, CA125, carcinoma embryonic antigen (CEA) levels between the LNM and nLNM groups. However, gender, long diameter of the lesion, and lesion boundary exhibited statistically significant differences (P values were 0.023, 0.048, 0.040, respectively). There were significant statistical differences in the T2^* and R2^* values between the two groups (P values <0.05). Compared with the nLNM group, the LNM group exhibited a smaller R2^* value [17.63 (15.10, 22.50) /s vs. 24.00 (20.00, 28.30) /s] and a higher T2^* value [(63.77±13.95) ms vs. (49.71±12.67) ms]. The AUCs for T2^*/R2^* values in predicting lymph node metastasis of pancreatic cancer were 0.775 and 0.766, respectively. ConclusionsQuantitative T2^*/R2^* imaging derived from the ZOOM-mDixon sequences can predict preoperative lymph node metastasis of pancreatic ductal adenocarcinoma, offering valuable insights for clinical treatment decisions. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.020 ObjectiveTo develop and validate the efficacy of a deep learning (DL) model by 50-layer deep residual network (ResNet-50) based on T2WI for preoperative prediction of preoperative pathological grading of bladder cancer (BCa). Materials and MethodsA total of 211 tumors in 169 BCa patients [109 for training and 47 for internal test, from the Tenth Affiliated Hospital of Southern Medical University (centre 1); 55 for external test, from Sun Yat-sen University Cancer centre (centre 2)] were enrolled, including 111 tumors of high grade uroepithelial carcinoma (HGUC) and 100 tumors of low grade uroepithelial carcinoma (LGUC). Grade determination was confirmed by pathological examination. ResNet-50 was used to construct the models based on the internal training set from centre 1. The optimal model was selected from the resulting models after being tested on the internal test set from centre 1 and validated independently on the external test set from centre 2. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, and specificity, with feature visualization images presented. ResultsIn the internal test set, we achieved an AUC of 0.856 [95% confidence interval (CI): 0.723-0.941], accuracy of 80.9% (95% CI: 69.6%-92.1%), sensitivity of 77.8% (95% CI: 65.9%-89.7%), and specificity of 82.8% (95% CI: 72.0%-93.6%). In the external test set, we achieved an AUC of 0.814 (95% CI: 0.686-0.906), accuracy of 78.2% (95% CI: 67.3%-89.1%), sensitivity of 77.3% (95% CI: 66.2%-88.3%), and specificity of 81.8% (95% CI: 71.6%-92.0%). Feature visualization showed that the activated regions overlapped with the BCa lesions largely, indicating the DL model identified the target area of BCa correctly. And the t-distributed stochastic neighbor embedding (T-SNE) helped to distinguish HGUC from LGUC in a certain extent. ConclusionsThis study is the first to establish a preoperative BCa pathological grading prediction model based on T2WI using DL methods and be validated across two centres. With high prediction accuracy, the model is non-invasive, objective, and has strong repeatability and generalization performance, which contribute to more accurate clinical preoperative diagnosis. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.021 ObjectiveTo explore the value of amide proton transfer (APT) imaging in evaluating the efficacy of concurrent chemoradiotherapy (CCRT) for cervical cancer. Material and Methods: A retrospective analysis was conducted on 27 patients with cervical cancer confirmed by pathology. The efficacy of CCRT was evaluated based on the evaluation criteria for solid tumor efficacy. Complete remission (CR) and partial remission (PR) were included in the remission group, while disease stability (SD) and disease progression (PD) were included in the non-remission group. The values of apparent diffusion coefficient (ADC) and ATP of the lesion area were compared and analyzed before and after CCRT, as well as in the remission and non-remission groups. The correlation between ADC value, APT value, and CCRT efficacy were analyzed by using Pearson correlation analysis. ResultsAfter CCRT, there were 3 cases of CR (11.11%), 16 cases of PR (59.26%) and 8 cases of SD (29.63%) in 27 patients with cervical cancer. The local control rate was 100.00%. Compared with before CCRT, the ADC value of the lesion after CCRT increased [(0.89±0.06)×10^-3 mm²/s vs. (1.07±0.07)×10^-3 mm²/s, P<0.05] and the APT value decreased significantly (3.30%±0.05% vs. 3.07%±0.07%, P<0.05). Before CCRT, the values of ADC and APT in the remission group were higher than those in the non-remission group, and the difference was not statistically significant (P>0.05); After CCRT, the ADC value of the remission group was higher than that of the non-remission group [(1.10±0.06)×10^-3 mm²/s vs. (1.01±0.04)×10^-3 mm²/s, P<0.05], while the APT value of the remission group was lower than that of the non-remission group (3.05%±0.06% vs. 3.12%±0.07%, P<0.05). There is a significant negative correlation between the ADC value after CCRT and the efficacy of CCRT (r=-0.61, 95% CI: -0.82--0.39, P<0.01), while there is a significant positive correlation between APT value and CCRT efficacy (r=0.50, 95% CI: 0.20-0.76, P=0.01). ConclusionsCCRT for cervical cancer has a good therapeutic effect. The APT value is positively correlated with the CCRT effect and an effective imaging marker for reflecting the efficacy of CCRT in cervical cancer. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.022 ObjectiveTo investigate the application value of radiomics model based on MR T2WI for prenatal predicting placenta accreta spectrum disorders (PAS) and determining the subtype of PAS. Materials and MethodsThe data of 193 pregnant women with singleton pregnancies who were hospitalized for delivery in Beijing Obstetrics and Gynecology Hospital from January 2018 to January 2023 were retrospectively analyzed, including 134 cases of PAS and 59 cases of non-PAS. All pregnant women were randomly divided into training set and test set in a 2∶1 ratio based on the total number of patients with the same subtype. The radiomics features were extracted from T2WI sequence, Pearson correlation coefficient and least absolute shrinkage and selection operator (LASSO) regression were used for feature screening, and the radiomics models for predicting PAS were constructed. Then, a radiomics scoring system for clinical application is constructed and trained to evaluate the subtypes of PAS, and univariate analysis and multivariate analysis are used to further analyze other potential clinical risk factors, including age, gestational age, previous gravidity, previous parity, the history of cesarean section, placental problems (placenta previa), and the history of uterine-related operations. Establish a nomogram based on the selection of clinical major risk factors. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive performance of the model, and DeLong test was used to compare the predictive efficiency of these models, the calibration curve is used to evaluate the degree of calibration of the prediction model, and the decision curve is used to evaluate the clinical value of the prediction model. Results806 radiomics features were extracted from T2WI sequence, 147 radiomics features were retained after Pearson correlation analysis, and 10 radiomics features were screened out after LASSO regression processing, and a radiomics model that is applied to scoring was established. The area under the curve (AUC) value of the radiomics model in the training set was 0.933 (95% CI: 0.888-0.978), the accuracy was 88.37%, the sensitivity was 88.78%, the specificity was 87.10%, the positive predictive value (PPV) was 95.60%, and the negative predictive value (NPV) was 71.05%; the AUC value in the test set was 0.914 (95% CI: 0.835-0.993), the accuracy was 89.06%, the sensitivity was 90.91%, the specificity was 85.00%, the PPV was 90.00%, and the NPV was 80.95%. The calibration curve and decision curve showed that the model had high performance and potential clinical application value. The radiomics scoring model has a strong ability to identify placenta percreta, the accuracy of training set and test set reached 82.95% and 89.06%, the sensitivity and NPV reached 100.00% in training set and test set, and the specificity reached 81.35% and 88.33%, respectively. In addition, this study successfully constructed a clinical-radiomics model and draws a nomogram for visualizing PAS in patients. In the training set, the AUC of the clinical-imaging model was 0.969 (95% CI: 0.946-0.993), in the test set, the AUC value was 0.976 (95% CI: 0.947-1.000). DeLong test results showed that there were significant differences in the performance of the two models (P＜0.05), and the clinical-imaging model had better performance. ConclusionsThe clinical-radiomics model based on the clinical major risk factors and radiomics scoring system has a good performance, and can be used as a method to predict the presence of PAS before delivery. And the radiomics scoring system has a good ability to distinguish the subtype of PAS, especially the placenta percreta. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.023 ObjectiveUsing the magnetic resonance multi-echo DIXON (mDIXON) technique analyze the differences between thigh muscle and paravertebral muscle fat content between patients with type 2 diabetes mellitus (T2DM) and healthy controls and explore the relationship of each skeletal muscle fat content with duration, triglyceride glucose (TyG) index, and other indicators. Materials and methodsThe study prospectively enrolled 42 clinically diagnosed T2DM patients and 44 age, gender, and recruitment-matched healthy volunteers as the control group. All subjects underwent thigh and abdomen mDIXON sequence scanning. An independent-sample t-test was employed to compare the fat fraction (FF) values of each muscle group between the two groups. Multivariate linear regression and logistic regression analyses were conducted to assess the correlation between FF values, duration of diabetes, and TyG index. ResultsThe FF values of all thigh muscle groups in the T2DM group were higher than those in the control group, and the FF value of the quadratus lumborum was significantly higher than that in the healthy control group (t=3.402, P<0.001). There was no significant difference in the FF value of the other paravertebral muscles between the two groups (P>0.05). The thigh muscle FF values of females in the T2DM group were significantly higher than those of males (P<0.001). The FF values of vastus lateralis, vastus medialis, and rectus femoris in the T2DM group were positively correlated with the course of the disease (r=0.057, 0.073, 0.125, P<0.001). Increased FF values of erector spinae and vastus lateralis are a risk factor for a high TyG index (OR=1.934, P<0.001; OR=2.516, P<0.001). ConclusionsThe mDIXON sequence has a good ability to evaluate skeletal muscle fat content. Skeletal muscle fat content is higher in patients with T2DM than in healthy people. Combined with the course of the disease and TyG index, further analysis of the changes in skeletal muscle fat content in T2DM patients is helpful to guide the clinical diagnosis and treatment of T2DM patients. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.024 ObjectiveTo determine the efficacy of contrast enhanced T2 fluid attenuated inversion recovery (CE-T2 FLAIR) sequence and contrast enhanced T1 weighted imaging (CE-T1WI) of brain metastases after injection of different doses of gadolinium contrast agent, and to investigate the clinical value of half-dose contrast agent enhanced T2 FLAIR sequence in the diagnosis of brain metastases. Materials and MethodsA total of 30 patients with a history of extracranial primary malignant tumors confirmed by pathological diagnosis and brain metastases confirmed by pathological or clinical follow-up were prospectively enrolled. On the basis of conventional non-enhanced T1WI and T2 FLAIR sequences using a 3.0 T MRI equipment, CE-T2 FLAIR and CE-T1WI scans were performed after administration of half-dose (0.05 mmol/kg) gadolinium-based contrast agent (GBCA), followed by fractional supplementation of GBCA to the conventional-dose (0.1 mmol/kg) and double-dose (0.2 mmol/kg). After injection of the GBCA, both CE-T2 FLAIR and CE-T1WI scans were performed. Objective measurements of images were performed by two observers. The contrast-to-noise ratio (CNR), relative-contrast (RC), and percentage increase (PI) of CE-T2 FLAIR and CE-T1WI images under different doses were calculated. Analysis of variance were used to analyze objective measurements between different groups and multiple comparisons were performed when the difference was statistically significant (P<0.05). The t-test was used to analyze the differences between two groups. ResultsThe objective scores were consistent between two observers. There was no significant difference in CNR and RC values among CE-T2 FLAIR images under three different doses of GBCA (P>0.05). Compared with non-enhanced T2 FLAIR scanning, the PI of the lesion was increased. There were significant differences in the CNR and RC values between the CE-T1WI images at three different doses of GBCA (P<0.05). The results of pairwise comparison showed that the CNR and RC values on the doubling-dose CE-T1WI images were significantly higher than those on the half-dose group (P<0.05). The CNR and RC values of CE-T2 FLAIR images at half-dose and conventional-dose were significantly increased compared to CE-T1WI in this group, and the difference was statistically significant (P<0.05). The CNR and RC values of the half-dose CE-T2 FLAIR images were higher than those of the conventional-dose CE-T1WI (P<0.05). Compared with doubling-dose CE-T1WI, the CNR value of the half-dose CE-T2 FLAIR image increased (P<0.05), while the difference in RC value was not statistically significant (P>0.05). ConclusionsIn comparison with CE-T1WI, the CE-T2 FLAIR sequence with half-dose GBCA could achieve similar image quality and show values in clinical diagnosis of brain metastases. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.025 ObjectiveTo explore the value of self-developed 16-channel high-resolution pelvic-specific coil (16C) in pelvic 3.0 T MRI. Methods and Materials: Thirty-five patients underwent routine pelvic MRI were prospectively included, and the same axial and sagittal T2WI sequences were acquired with a 16C coil and a 32-channel body coil (32C), respectively. Signal to noise ratio (SNR) and contrast to noise ratio (CNR) of the third sacral vertebrae, myometrium, peripheral band of prostate, rectal wall, and internal obturator muscle were compared between images of the same sequences acquired with the two coils. Qualitative image quality and rectal wall depiction were evaluated by two radiologists for both groups. ResultsCompared with 32C, SNR of third sacral vertebrae, myometrium, peripheral band of the prostate on T2WI sagittal images, SNR of intraocclusal muscle on T2WI axial images, CNR of third sacral vertebrae, myometrium on T2WI sagittal images and CNR of rectal wall on T2WI axial images were all higher, and all difference were statistically significant (P<0.05). Rectal wall depiction on T2WI axial images and all qualitative image quality were better in 16C group than that of 32C group (P<0.05). ConclusionsCompared with conventional 32C coils, images acquired with 16C coils have better imaging quality and diagnostic confidence. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.026 ObjectiveTo explore the feasibility and the diagnostic accuracy of MRI-guided vacuum-assisted biopsy (VAB) in lesions visualized by MRI only. Materials and MethodsRetrospective analyzed 27 patients with 27 lesions who underwent MR-guided VAB between September 2019 and December 2022. All of the breast lesions were categorized as 4 or 5 BI-RADS. All biopsies were performed on a 3.0 T system with a dedicated eight-channel open breast coil, an MRI compatible biopsy positioning frame and consumables. We recorded the lesion^,s imaging characteristics, the pathological outcomes of the biopsy and the final pathological results of the malignant lesions, as well as intraoperative and postoperative complications. The pathological results after surgery or the follow-up results of benign lesions at least six months later were used as the gold standard, the diagnostic accuracy, sensitivity, specificity, positive predictive value and negative predictive value of VAB were calculated, as well as the histological underestimation of biopsied lesions. ResultsTechnical success was achieved in all biopsies. The average operation time was (39.92±8.34) min. After biopsy, 7 of 27 lesions (25.93%) were malignant, 2 of 27 lesions (7.41%) were atypical ductal hyperplasia, and 18 of 27 lesions (66.67%) were remaining benign. When the pathological results were compared with preoperative MRI images, no radiology-pathology inconsistency were discovered. All patients who were diagnosed with malignant tumors or atypical ductal hyperplasia underwent additional surgical resection. Without any histological underestimate, the biopsy results were consistent with the postoperative pathological outcomes. The lesions of two mammary inflammatory lesions diminished in half a year follow-up in all patients who were diagnosed with benign lesions by biopsy, and no significant changes were seen in the rest. The results of VAB showed 100% (27/27) accuracy,100% (7/7) sensitivity, 100% (20/20) specificity, 100% (7/7) positive predictive and 100% (20/20) negative predictive value. One patient experienced vagal response symptoms during the procedure, which were primarily brought on by emotional stress, and immediately recovered. ConclusionsFor breast suspicious lesions detected on MRI only, MRI-guided VAB provides a safe, accurate and efficient procedure for pathological diagnosis, with high accuracy of pathological diagnosis and few complications, which is worthy of clinical application and advancement. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.029 ^,s disease (AD) is a degenerative disease of the central nervous system characterized by cognitive impairment. There is a preclinical period of approximately 20 years before the onset of clinical symptoms, making it the optional time window for disease intervention. Therefore, the early diagnosis of AD is essential for disease delay and prognosis improvement. Resting-state functional magnetic resonance imaging (rs-fMRI) has the advantages of non-invasive and high spatial-temporal resolution. It is one of the most widely used neuroimaging techniques to study brain functional activity abnormalities in AD, which provides the possibility to find non-invasive markers of early AD. Based on rs-fMRI techniques, we reviewed the application value in the early diagnosis of AD in this article, in order to find non-invasive imaging markers for early monitoring of AD. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.030 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.031 ^, physical and mental health and quality of life. Among which, the temporal lobe epilepsy (TLE) is a common drug-resistant epilepsy in adults, so timely diagnosis and treatment is particularly important. diffusion MRI (dMRI) technology can use the diffusion information of water molecules to reflect the changes in the microstructure of TLE patients^, brain tissu, dMRI mainly includes diffusion weighted imaging (DWI) and various diffusion techniques derived from it, such as diffusion tensor imagin (DTI), diffusion kurtosis imaging (DKI), diffusion spectrum imaging (DSI) and neurite orientation dispersion and density imaging (NODDI). In this review, we briefly summarized the clinical application progress of various dMRI technologies in TLE, and prospected its future research prospects, aiming to understand the application status of diffusion technology in TLE, and provide certain references for the study of TLE diagnosis, treatment and diffusion technology in related fields. ]]> Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.032 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.033 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.034 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.035 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.036 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.037 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.038 Sat,20 Jan 2024 00:00:00 GMT http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2024.01.039 ^, quality of life. However, the exact mechanisms underlying this neurocognitive deficit are unknown, making it challenging to detect and manage this cognitive impairment at an early stage. Multimodal magnetic resonance imaging has yielded many results in this area in recent years and holds the promise of selecting imaging biomarkers to guide early screening and diagnosis of cognitive deficits in patients with chronic kidney disease (CKD). This paper will briefly describe the research progress of various emerging MRI technologies and artificial intelligence in end-stage renal disease (ESRD) patients with cognitive impairment, and try to reveal the connection between brain structure, function, perfusion, metabolism, neurovascular coupling and cognitive dysfunction in ESRD patients, so as to help clinical understanding of the potential neuronal mechanism of brain defects in ESRD patients. It is beneficial to the early diagnosis, treatment and follow-up of ESRD patients with cognitive impairment. ]]> Sat,20 Jan 2024 00:00:00 GMT