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<title>Chinese Journal of Magnetic Resonance Imaging RSS feed</title>
<link>http://med-sci.cn/cgzcx/en/contents_list.asp?issue=202112</link>
<language>zh-cn</language>
<copyright>An RSS feed for Chinese Journal of Magnetic Resonance Imaging</copyright>
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<title><![CDATA[Initial application of synthetic MRI in evaluating brain maturation of preterm infants]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.001</link>
<description><![CDATA[Objective: To explore the application value of Synthetic MRI for assessing the brain maturation of preterm infants. Materials and Methods: Conventional and synthetic MRI (magnetic resonance imaging compilation, MAGiC) acquisition on a 3.0 T MRI scanner were performed in 31 preterm infants [29 to 36 weeks gestational age (GA)] and 40 term controls (37 to 41 weeks GA) at term-equivalent age (37 to 45 weeks). The quantitative parameters of T1, T2, and proton density (PD) valus were measured. The correlations between T1, T2, PD and postmenstrual age (PMA) were analyzed at scan. The differences of parameters in relation to brain region location and the groups were evaluated. Results: ①Posterior regions within corpus callosum (CC) and internal capsule (IC) demonstrated significantly lower T1, T2, PD values compared to anterior regions. Centrally located fibers demonstrated lower T1, T2, PD values than peripheral cerebral lobes including the posterior limb of the internal capsule (PLIC), cerebral peduncle (CereP) (all P＜0.05). ②T1 and T2 relaxation times were positively correlated with PMA at scan in most selected white matter regions and deep gray matter of preterm infants. The best correlation was observed in the PLIC (r=-0.695, r=-0.807, all P＜0.001). Similar developmental trends were observed in the term infants, but the correlation coefficient was lower in the same region (P＜0.05). ③Significantly prolonged regional tissue relaxation time was found in PLIC, anterior limb of the internal capsule (ALIC), centrum semiovale (CS) and optic radiation (PTR), which was best illustrated in the PLIC and in the CS (all P＜0.05). Conclusions: Temporal-spatial patterns of brain development at near-term age is identified by Synthetic MRI-based T1 and T2 relaxation times. And the tissue relaxation exhibit differences between the preterm and term control groups. Synthetic MRI may be one of valuable indices to evaluate brain maturation in preterm infants.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[The feasibility study of MRI texture analysis in predicting delayed enhancement status in cardiac amyloidosis]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.002</link>
<description><![CDATA[Objective: To explore the value of magnetic resonance imaging (MRI) texture analysis in predicting delayed enhancement status in patients with cardiac amyloidosis (CA). Materials and Methods: One hundred and thirty-two patients with CA confirmed by pathology were retrospectively analyzed, including presence (87 cases) and absence (45 cases) of late gadolinium enhancement (LGE) groups, and Sixty-six health volunteers were recruited. Regions of interest (ROIs) on native T1 mapping were drawn by two radiologists using open source software ITK-SNAP. FeAture Explorer (FAE) software was used to extract and select features. Finally, eight features were selected to build the model of support vector machine (SVM) A, which was used to differentiate the myocardium between CA patients without LGE and health volunteers. By using the same method of feature dimension reduction, nine features were selected to construct the model of SVM B to further predict the presence or absence of LGE in patients with CA. Finally, sensitivity, specificity, positive predictive value, negative predictive value, accuracy and area under the receiver operating characteristic curve (AUC) were calculated to evaluate the differential diagnostic efficacy of the two models. Results: The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of training set of the model of SVM A were 0.839, 0.957, 0.929, 0.898 and 0.909, respectively, and those of test set were 0.786, 0.950, 0.917, 0.864 and 0.882, respectively. The AUC of the training set and the test set were 0.948 (95% CI: 0.890—0.991) and 0.918 (95% CI: 0.780—1.000), respectively. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of training set of the model of SVM B were 0.853, 0.710, 0.853, 0.710 and 0.804, respectively, and those of test set were 0.846, 0.714, 0.846, 0.714 and 0.800, respectively. The AUC of the training set and the test set were 0.762 (95% CI: 0.639—0.875) and 0.758 (95% CI: 0.565—0.937), respectively. Conclusions: The radiomics models based on MRI texture analysis without contrast agent have a reasonable diagnostic performance in differentiating the myocardium between CA patients without LGE and health volunteers and predicting whether the myocardium of CA patients has delayed enhancement.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Diagnostic efficacy of novel imaging markers and its correlation with clinical symptoms for idiopathic normal pressure hydrocephalus]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.003</link>
<description><![CDATA[Objective: To evaluate the diagnosis efficacy of imaging markers (including linearity, angle, volume and the ratio) of idiopathic normal pressure hydrocephalus (iNPH) and their relationship with clinical symptoms. Materials and Methods: The novel imaging markers, frontal horn diameter (FHD), inner skull diameter (ISD), cella media width (CMW), maximum supratentorial intracranial diameter (MSID), supraventricular width (SVW), callosal-ventricular distance (CVD), callosal-commissural distance (CCD), temporal horn width (THW), callosal height (CH), Evans index (EI), z-Evans index (ZEI), frontal horn vertical diameter (FHVD), brain-to-ventricle ratio (BVR), obtained from 3.0 T brain magnetic resonance imaging in twenty-two patients with idiopathic normal pressure hydrocephalus and twenty-six healthy elders. Diagnostic performance of imaging markers was studied by using receiver operating characteristic (ROC) analysis, t-statistic and Logistic regression models. To analyze the correlation between the clinical symptoms (including gait, cognition and urination function) of the patients diagnosed with INPH and the imaging indexes. Results: EI, CMW, CCD, FHVD, CVD, THW and CH, ZEI showed high specificity (P＜0.001). CMW showed the highest discriminatory power between iNPH and healthy control group (AUC=0.985), followed by EI (AUC=0.981) and THW (AUC=0.946). CMW and THW had the most statistically significant difference between the iNPH group and the normal age group. ZEI, FHVD and CH were correlated with preoperative idiopathic normal pressure hydrocephalus grade scale (iNPHGS) micturition score. Conclusion: The best diagnostic performance among these new imaging markers is EI, CMW, CCD and THW. Thus it can be inferred that lateral ventricular dilatation is more in the Z-axis direction. ZEI, FHVD and CH were correlated with preoperative urination.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[The value of Gd-EOB-DTPA enhanced magnetic resonance imaging for predicting early recurrence of hepatocellular carcinoma after resection]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.004</link>
<description><![CDATA[Objective: To evaluate the predictive value of preoperative Gd-EOB-DTPA enhanced MRI in early recurrence (ER) of hepatocellular carcinoma (HCC) after radical resection. Materials and Methods: The data of patients who underwent radical resection of hepatocellular carcinoma in Shandong Cancer Hospital from January 2016 to May 2020 were retrospectively analyzed. A total of 68 patients who underwent Gd-EOB-DTPA enhanced MRI before resection were included. Among them, 18 cases had early recurrence within 1 year of postoperative follow-up as ER group, and 50 cases without early recurrence as control group. The clinical and imaging data of the two groups were collected, and the differences of clinical data and preoperative MRI signs between the ER group and the control group were compared. The predictive factors of early recurrence after HCC were analyzed by multivariate Logistic regression, and the predictive model was constructed according to the analysis results. The receiver operating characteristic (ROC) curve was drawn, and analyze the prediction value of the prediction model. Results: The parameter of lesion-to-liver contrast enhancement ratio (LLCER) can predict the pathological grade of HCC (P=0.023). The results of comparison between the ER group and the control group showed that there were significant differences in pathological grade, lesion morphology, peritumoral low signal intensity in hepatobiliary phase (HBP), satellite nodules and LLCER between the two groups (P＜0.05). The parameter LLCER in the ER group was lower than that in the control group. Logistic regression analysis showed that HBP peritumoral low signal intensity (OR=7.214, 95% CI=1.230—42.312), satellite nodules (OR=9.198, 95% CI=1.402—60.339) and parameter LLCER value (OR=0.906, 95% CI=0.826—0.995) were independent predictors of early recurrence of hepatocellular carcinoma after resection. According to the analysis results, a prediction model was constructed, and then the predictive value of the model was evaluated by ROC curve. The results showed that the area under ROC curve (AUC) is 0.94, 95% CI=0.883—0.997, sensitivity and specificity of the model for predicting postoperative recurrence of HCC were 0.889 and 0.840 respectively. Conclusions: Preoperative Gd-EOB-DTPA enhanced MRI has a certain predictive value for early recurrence after radical resection of hepatocellular carcinoma.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Diagnostic value of ultra-high b-value DWI in peripheral prostate cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.005</link>
<description><![CDATA[Objective: To investigate the diagnostic efficiency of diffusion weighted imaging (DWI) and apparent diffusion coefficient (ADC) maps with high b value (1000 s/mm2) and ultra-high b value (2000 s/mm2) for benign and malignant lesions of peripheral zone prostate. Materials and Methods: The clinical and imaging data of 64 patients who underwent conventional magnetic resonance imaging and ultra-high b-value DWI imaging of the prostate in the Department of Radiology, General Hospital of Ningxia Medical University from January 2015 to May 2016 were retrospectively analyzed. The images were evaluated by two physicians on T2WI and DWI using a five-point scale based on prostate imaging reporting and data system version 2.0 (PI-RADS V2) and in a double-blind fashion; the lesions were delineated layer by layer on DWI using three-dimensional region of interest (VOI) and the histogram analysis was performed on the ADC values. Results: (1) For the diagnosis of prostate cancer, the sensitivity of DWI image obtained by ultra-high b value (2000 s/mm2) was significantly higher than that of high b value (1000 s/mm2) (P＜0.001); (2) Histogram parameter ADC10 had the highest diagnostic efficiency, with the areas under the receiver operating characteristic (ROC) curves of 0.902 [95% CI (0.802—0.962)] and 0.823 [95% CI (0.707—0.907)] respectively (P＞0.05). Conclusions: The diagnostic performance of histogram of ADC values corresponding to ultra-high b value and high b value for peripheral zone prostate cancer is similar, while when b value is 2000 s/mm2, the sensitivity of DWI image is higher than 1000 s/mm2. Therefore, ultra-high b-value DWI can help to improve the diagnostic value of peripheral zone prostate cancer.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Multiparametric magnetic resonance imaging to characterize pathological grading and stage of cervical squamous cell carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.006</link>
<description><![CDATA[Objective: To investigate the value of quantitative parameters derived from T1 mapping, diffusion weighted imaging (DWI) and dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) in pathologically grading and staging of cervical squamous cell carcinoma (CSCC). Materials and Methods: A total of 65 patients with pathology confirmed CSCC were enrolled in this study, including 11 cases of well differentiated, 32 cases of moderately differentiated, 22 case of poorly differentiated, and 37 case of early-stage (FIGO ⅠB-ⅡA), 28 case of late-stage (FIGO ⅡB-Ⅳ). Patients underwent pretreatment T1 mapping, DWI and DCE-MRI scan and T1, ADC, Ktrans and Kep values of tumor tissues were obtained. One-way ANOVA was used to compare the differences of quantitative parameters among different pathological grades. The independent sample t test was used to assess the difference between the early- and late-stage group. ROC curves analysis was performed to determine the diagnostic efficacy of quantitative parameters. Results: T1, ADC and Ktrans values were significant difference in different pathological grade of CSCC (P＜0.05). In term of distinguishing early-from late-stage, T1 value in the early-stage CSCC was higher, and Ktrans values was lower than the late-stage CSCC. The differences were significant (P＜0.05). The area under ROC curve (AUC) of T1, ADC and Ktrans values in the diagnosis of poorly differentiated CSCC were 0.83, 0.74 and 0.79, respectively. A combination of these quantitative parameters showed the highest diagnostic efficiency with an AUC of 0.91. The AUC of T1 and Ktrans values in the diagnosis of early stage CSCC was 0.67 and 0.65, respectively, and a combination of T1 and Ktrans achieved an AUC of 0.69. Conclusion: T1 mapping, DWI and DCE-MRI quantitative parameters can be used as predictors to evaluate the pathological grade and staging of CSCC. The combination of multiple parameters can improve the diagnostic sensitivity of cervical squamous cell carcinoma, which has high clinical application value.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Application of different radiomics models based on MRI conventional T2WI in preoperative tri-classification of ovarian epithelial tumors]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.007</link>
<description><![CDATA[Objective: Conventional T2WI sequences based on MRI were used to compare the diagnostic efficacy of the radiomics models established by different machine learning algorithms in preoperative tri-classification of epithelial ovarian tumors. Materials and Methods: Preoperative MR images of 300 patients (100 benign, 100 borderline and 100 malignant) with pathologically confirmed ovarian epithelial tumors were retrospectively analyzed, and all the data were randomly divided into training sets and testing sets according to the ratio of 8∶2. Image features are extracted from the volume of interest (VOI) manually drawn on the axial T2WI, and screening them. Four feature selection methods and seven machine learning classifiers were pairwise combined to construct 28 classification models. AUC and accuracy were used to evaluate the prediction performance of all models. Results: The best performance among 28 classification models is the "RFE-KNN" model that combines recursive feature elimination (RFE) and K nearest neighbor (KNN) classifiers. AUC of benign, borderline and malignant group was 0.94, 0.93 and 0.96. Conclusions: Quantitative radiomics features extracted from T2WI have a good performance in differentiating benign, borderline, and malignant epithelial ovarian tumors.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Radiomics features of sub-attention region on the diagnosis of the extracapsular extension of the prostate cancer on magnetic resonance imaging]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.008</link>
<description><![CDATA[Objective: Extract radiomics features from the sub-regions of the generated attention region on magnetic resonance images to help diagnose the extracapsular extension (ECE) of the prostate cancer. Materials and Methods: Seven hundred and eighteen cases with prostate cancer diagnosis including T2 weighted images and apparent diffusion coefficient maps were selected in this study, and divided into 574 training cases and 144 test cases. An attention ROI was generated according to the ROIs of the prostate gland and the prostate cancer lesion. Further, sub-regions of the attention ROI were split into the background, prostate gland and lesion to be used for feature extraction. Radiomics models were built based on features from prostate gland (ModelPro), prostate cancer (ModelPCa), attention ROI (ModelAtt), and sub-regions of attention ROI (ModelRegion), respectively. The area under the receiver operating characteristic (ROC) curve (AUC), confusion matrix and the decision analysis curve were used for statistical analysis. Results: The AUCs of the ModelPro were 0.740 and 0.746, and that of ModelPCa were 0.742 and 0.755 on the training and the test cohorts, respectively. The AUC of ModelAtt was higher and was achieved of 0.732 and 0.766 on the training and test cohorts. Compared to the above models, ModelRegion performed best to achieved an AUC of 0.794 and 0.792 on the training and test cohorts. Conclusion: The radiomics model based on the attention ROI and the sub-regions performed more accurately than the usual prostate gland and cancer lesion, and could provide aids in the ECE diagnosis in the clinics.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[USPIO enhanced SWI MRI to evaluate the effects of cinobufacini on a nude orthotopic hepatocellular carcinoma tumor model]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.009</link>
<description><![CDATA[Objective: To assess the validity of antiangiogenic effects of cinobufacini on nude orthotopic hepatocellular carcinoma (HCC) xenografts with ultrasmall superparamagnetic iron oxide enhanced susceptibility-weighted imaging (USPIO enhanced SWI). Materials and Methods: A total of 16 nude HCC models were made. They were divided into cinobufacini treated and saline control groups randomly with eight in each at twenty-one days after tumor inoculation. USPIO enhanced SWI were performed on a 3.0 T Siemens MR scanner after another twenty-one days with intervention. Intratumoral susceptibility signal intensity (ITSS) of tumor was scored. They were compared between two groups. The correlations between ITSS, micro-vessel density (MVD) and tumor volume were analyzed. Results: There were 5 mice survived in the treated group and 7 in the saline control group. ITSS was significantly lower in the treated than in the saline control group (P＜0.05). In 12 mice, significantly good positive correlation was found between ITSS and MVD (r=0.647, P=0.022), and ITSS correlated moderately with tumor volume (r=0.645, P=0.023). Conclusions: This USPIO enhanced SWI MRI study showed that cinobufosin can inhibit the formation of large blood vessels in tumors of nude HCC mice.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Feasibility study on quantification method of fat infiltration in thigh muscle based on axial T1WI image]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.010</link>
<description><![CDATA[Objective: To explore the feasibility of using ImageJ to segment and quantify subcutaneous adipose tissue (SAT), intramuscular fat (IntraMF) and intermuscular fat (InterMF) on MRI T1WI images. Materials and Methods: MRI scans of the midthigh were performed on 28 volunteers, including 14 patients with type 2 diabetes. Goutallier classification was performed for the degree of muscle fat infiltration on the axial T1 image. The SAT, IntraMF and InterMF areas of the thigh were measured by ImageJ segmentation. The area of IntraMF was calculated by the fat fraction as measured by iterative decomposition of water and fat with echo asymmetry and least squares estimation quantification sequence (IDEAL-IQ). The correlation between ImageJ segmentation and Goutallier classification and IDEA-IQ fat quantification method was analyzed. The intra-observer and inter-observer reliability of the ImageJ segmentation method was tested. Results: There was a strong correlation between the ImageJ segmentation and the fat fraction as measured by IDEA-IQ (r=0.998, P＜0.001); the inter-observer and intra-observer ICC for ImageJ segmentation of thigh SAT area was 0.999, P＜0.001; the inter-observer ICC of InterMF area was 0.941, P=0.003, intra-observer ICC was 0.992, P＜0.001; the inter-observer ICC of thigh IntraMF area was 1.000, P＜0.001, and the intra-observer ICC was 0.997, P＜0.001. Conclusion: ImageJ was reliable in quantifying thigh SAT, IntraMF and InterMF on MR T1 images, and was strongly correlated with IDEA-IQ fat quantification. ImageJ segmentation is a feasible alternative to semi-quantitative Goutallier classification.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Features fusion of brain networks and its application to autism recognition by machine learning based on resting-state functional magnetic resonance imaging]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.011</link>
<description><![CDATA[Objective: The resting-state functional magnetic resonance imaging (rs-fMRI) technology combined with machine learning algorithm was used to classify the patients with autism, trying to provide reference for early identification of autism. Materials and Methods: The rs-fMRI data of a total of 24 patients with autism and 25 healthy people were pre-processed. Then, the partial correlation functional connection (FC) was used to construct the network and the sparsity space of 0.05—0.50 with a step size of 0.05, the brain functional networks were constructed by GRETNA software. A total of 4 local nodes metrics were calculated respectively for patients and healthy individuals. Finally, the proportion of classification accuracy of each index is used as the weight coefficient for feature fusion, so as to construct the feature vector, input into the support vector machine model for classification and cross validation to test the feature fusion effect.Results: The average accuracy of weighted features fusion can reach up 89.47%, which is 21.05% higher than that of a single feature and 4.74% higher than non-weighted feature fusion method. Conclusions: This work might provide a new index and a new method to recognize the autism by rs-fMRI.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[The effect of fast scan parameters on evaluation of T1, T2 relaxation times and proton density of normal brain using synthetic MRI]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.012</link>
<description><![CDATA[Objective: To investigate the differences of T1, T2 relaxation times, and proton density (PD) measured from multi-dynamic multi-echo (MDME) sequence between fast scan parameters and standard parameters in healthy individuals using 3.0 T scanner, and evaluate the correlations between these quantitative values. Materials and Methods: Twenty-five healthy volunteers were included in the study. Each of them was scanned 3 times using 3 MDME sequences with different scan parameters (group EME, NOR, and RES) respectively. T1, T2 and PD values were simultaneously measured in each of the 28 regions of interest and were compared among different groups with One-way ANOVA. Values of group RES were set as reference values and linear regression was performed for values of group EME and NOR versus the reference values with Pearson correlation. Statistical analysis was performed using SPSS software (23.0.0.0, IBM). Results: Significant differences were displayed when comparing T1, T2, and PD values among 3 groups in the most of brain regions (P＜0.05). T1 and PD values have lower discrepancy with the highest intergroup coefficient of variations (CVs) of 3.33% and 5.80%, while T2 values has a higher discrepancy with the highest intergroup CV of 6.48%. The linearity in T1, T2, and PD were very strong between group EME and RES (T1, r=0.999; T2, r=0.982; PD, r=0.978) as well as group NOR and RES (T1, r=0.999; T2, r=0.985; PD, r=0.986). Conclusions: Quantitative T1, T2 and PD values acquired from MDME sequence can be affected by fast imaging protocols. The bias of measured T1 and PD values are lower than that of T2 values and the linear correlation between them is positive. It is necessary to set a certain scan parameter for comparing or following up cases quantitatively.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Preliminary study on the application value of 3.0 T magnetic resonance amide proton transfer (APT) imaging in breast diseases]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.013</link>
<description><![CDATA[Objective: To investigate the application value of 3.0 T magnetic resonance amide proton transfer (APT) imaging in breast diseases. Materials and Methods: In this retrospective study, 81 cases with pathological confirmed breast diseases in Nation Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital & Shenzhen Hospital from January 2020 to December 2020 were enrolled. The baseline preoperative APT images and clinical-pathological data were collected and analyzed. In total, there were 81 patients with 81 lesions, including 56 malignant breast lesions and 25 benign breast lesions, between which the differences of APT values were compared. Also, the APT values of breast cancer with different lymph node metastasis status, estrogen receptor, progesterone receptor, human epidermal growth factor receptor 2 and Ki-67 expression were compared. Results: There was significant difference in the mean APT values among malignant lesion, benign lesion and normal breast tissues (P＜0.01). Both breast cancer lesions (1.781± 1.103)% and benign breast lesions (1.756±0.752)% had significantly higher mean APT values than that of the corresponding contralateral normal gland tissue (0.868±0.565)% and (1.101±0.372)% (all P＜0.01). However, there was no significant difference in the mean APT value between malignant and benign breast lesions (P=0.917). The APT value of breast cancer in high Ki-67 expression group (2.073±1.278)% was higher than that of the low Ki-67 expression group (1.362±0.592)% (P＜0.05). The APT value of low breast cancer infiltrating grade (grade Ⅰand Ⅱ) was 1.163 (0.833)% , which was significantly lower than that of grade Ⅲ 1.675 (0.887)%. There was no significant difference in APT value between lymph node metastasis group and non-metastasis group, ER positive group and negative group, PR positive group and negative group, Her-2 positive group and negative group (all P＞0.05). Conclusion: Benign and malignant breast lesions have significantly higher APT effect than normal tissues, which proves the feasibility of using APT to evaluate breast lesions. Moreover, preliminary studies have shown that the APT effect can reflect the degree of breast cancer invasion and cell proliferation index, suggesting that APT imaging can potentially be used to predict the prognosis of breast cancer.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Value of 3.0 T dynamic contrast-enhanced MRI of breast combined with mammography in the differential diagnosis of benign and malignant small breast nodules with diameter ≤≤2 cm]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.014</link>
<description><![CDATA[Objective: To evaluate the imaging characteristics and diagnostic value of 3.0 T dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of breast combined with mammography on small breast nodules with diameter≤2 cm. Materials and Methods: A retrospective analysis was performed on the clinical data of 135 patients with small breast nodules with diameter≤2 cm who were admitted between January 2018 and September 2020. All patients were confirmed by surgical pathology or tissue biopsy, and they performed mammography and DCE-MRI examination before surgery. The morphological characteristics, time-signal intensity curve (TIC) classification, TIC maximum signal intensity value (SImax), peak height (PH), maximum linear slope (Slope) and Slope ratio (SlopeR) of breast cancer and benign lesions were analyzed under DCE-MRI examination. Taking pathological examination results as the gold standard, mammography diagnosis results were combined to explore the diagnostic value of DCE-MRI on small breast cancer with diameter≤2 cm. Results: There were statistical differences in the morphological characteristics of DCE-MRI margin and internal enhancement and TIC classification and early enhancement rate between breast cancer group and benign group (P＜0.05), and the proportions of marginal burr sign, internal uneven enhancement, TIC classification of type Ⅲ and early enhancement rate≥60% were 73.49%, 59.04%, 75.90% and 83.13% in breast cancer group and were 3.85%, 34.62%, 7.69% and 28.85% in benign group. The Slope and SlopeR value in breast cancer group was significantly higher than those in benign group (P＜0.05). Taking pathological diagnosis results as the gold standard, the sensitivity, specificity, accuracy rate and Kappa value with pathological diagnosis of DCE-MRI in diagnosing breast cancer with diameter≤2 cm were 0.964, 0.904, 0.941 and 0.874 respectively, which were better than 0.832, 0.885, 0.852 and 0.696 of mammography, and the corresponding values of the combined diagnosis of the two were 0.988, 0.860, 0.940 and 0.869 respectively. Conclusions: The benign and malignant lesions of small breast nodules under DCE-MRI are significantly different in morphology, TIC classification and related parameters. The diagnostic efficacy of DCE-MRI on small breast cancer with diameter≤2 cm is better than that of mammography, and the combination of the two has higher diagnostic value.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[The value of IVIM-DWI combined with Gd-EOB-DTPA enhanced MRI in prediction of hepatocellular carcinoma microvascular invasion]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.015</link>
<description><![CDATA[Objective: To explore the predictive value of intravoxel incoherent motion diffusion weighted imaging (IVIM-DWI) combined with Gd-EOB-DTPA enhanced MRI images for hepatocellular carcinoma (HCC) microvascular invasion (MVI). Materials and Methods: The MRI images and clinical data of 57 patients with HCC confirmed by pathology were analyzed retrospectively. Standard ADC value, D value, D* value, f value, relative enhancement (RE) rate and imaging characteristics were analyzed. Chi-square test, t test, and U test were used in the comparison between groups. Multivariate logistic regression analysis was performed on the variables with differences. ROC curves were used to compare the diagnostic efficacy of predicting significant indicators of MVI. Results: There were significant differences in tumor size, margin, peritumor enhancement in arterial phase and D value between MVI positive group and negative group (P＜0.05), among which D value had the best diagnostic efficacy (AUC 0.849, sensitivity 75.0%and specificity 81.1%). Multivariate Logistic regression analysis showed that tumor size, arterial peritumor enhancement and D value were independent risk factors for MVI. ROC curve analysis showed that the combination of D value and arterial tumor enhancement had the highest diagnostic efficacy in predicting MVI (AUC 0.879, sensitivity 86.5% and specificity 80.0%). Conclusions: The combination of D value and arterial periodical enhancement can improve the accuracy of predicting MVI. The smaller the D value is, the more likely the HCC with periodical enhancement is to have MVI.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[The value of Gd-EOB-DTPA enhanced MRI in predicting microvascular invasion of hepatocellular carcinoma and its grade]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.016</link>
<description><![CDATA[Objective: To evaluate the predictive value of Gd-EOB-DTP-enhanced MRI in the occurrence and grading of microvascular invasion of (MVI) in hepatocellular carcinoma (HCC). Materials and Methods: Sixty-seven patients with primary HCC confirmed by postoperative pathology were retrospectively studied. All cases were divided into MVI positive group and MVI negative group according to whether there was microvascular invasion or not. The general data and laboratory examination, Gd-EOB-DTPA enhanced MRI imaging data and postoperative tumor histopathological grading data were analyzed, and the independent risk factors affecting microvascular invasion in patients with hepatocellular carcinoma were obtained. ROC curve was drawn to evaluate the diagnostic efficacy of independent risk factors. Furthermore, according to the histological characteristics of microvascular invasion, all patients with hepatocellular carcinoma were divided into M0 group, M1 group and M2 group. The effect of P＜0.05 in univariate analysis on MVI grade was studied. Results: Univariate analysis showed that there were significant differences in tumor margin、 rim enhancement、 peritumoral enhancement in arterial phase and peritumoral hypointensity in the hepatobiliary phase between MVI positive group and MVI negative group. Further multivariate Logistic regression analysis showed that peritumoral enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were independent risk factors for the occurrence of MVI in hepatocellular carcinoma. The results of diagnostic effectiveness analysis of independent risk factors showed that the area under the curve (AUC) of peritumoral enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase were 0.669 and 0.636, respectively. The sensitivity and specificity of peritumoral enhancement in the arterial phase were 93.8% and 40.0%, respectively, and the sensitivity and specificity of peritumoral hypointensity in the hepatobiliary phase were 84.4% and 42.9%, respectively. Furthermore, all patients with hepatocellular carcinoma were divided into M0 group, M1 group and M2 group according to MVI grade. The results showed that there were significant differences in peritumor rim enhancement in arterial phase, low signal intensity in hepatobiliary phase and tumor margin among different MVI grades, and it can be seen from the data that the higher the MVI grade, the greater the proportion of peritumoral enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase. Conclusions: In Gd-EOB-DTPA enhanced MRI, peritumoral enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase can be used as effective indexes to predict microvascular invasion of HCC before operation, while peritumoral enhancement in the arterial phase and peritumoral hypointensity in the hepatobiliary phase and tumor margin can be used to predict MVI grade of HCC.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[A comparative study of UTE and T2* mapping imaging technology in quantitative assessment of rotator cuff tear]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.017</link>
<description><![CDATA[Objective: To explore the ability of ultra-short echo time (UTE) and T2* mapping imaging technology to quantitatively assess rotator cuff tears. Materials and Methods: Thirty-nine patients with rotator cuff injury were collected and underwent UTE and T2* mapping sequence scan. The supraspinatus tendon was divided into three sub-regions, and the R value of the deltoid muscle (the reciprocal of the T2* value) was used as a reference to obtain the relative R value of each sub-region. Two radiologists performed the Zlatkin type in different sub-regions on the rotator cuff images, which were divided into three types. Type Ⅰ was defined as tendinitis; Type Ⅱ was defined as a small tear; Type Ⅲ was defined as a large tear. Tendons were divided into continuous group (type Ⅰ) and tear group (type Ⅱ and type Ⅲ). The Kappa consistency test was used between different observers, the Kruskal-Wallis H test was used to compare the Zlatkin classification of the two sequences, the LSD pairwise multiple comparisons were used between the groups, and the diagnostic efficacy of the two techniques was compared by the receiver operating characteristic (ROC) curve. Results: There is almost complete agreement between the two observers (Kappa=0.821). In the UTE sequence, there are statistical differences between type Ⅰ and type Ⅲ, type Ⅱ and type Ⅲ in the outer and middle subregions (P＜0.05); T2* mapping is only statistically different between type Ⅱ and type Ⅲ (P＜0.05) ). Using UTE sequence to measure the middle subregion to judge whether the tendon is torn is 3.0755, the AUC is 0.782, the sensitivity is 0.75, the specificity is 0.645, the other subregions are not statistically significant (P＞0.05), all none of the sub-regions of the T2* mapping sequence is statistically significant (P＞0.05). Conclusions: UTE technology is helpful to judge the rotator cuff tear and quantitatively distinguish the rotator cuff tear in the middle sub-regions. It has good diagnostic efficiency, guides further clinical treatment, and provides a new idea for clinical work.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Dynamic changes of necrotizing pancreatitis: "Transmural pancreatic necrosis-Pancreatic duct disruption-Walled-off necrosis" trilogy]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.022</link>
<description><![CDATA[Necrotizing pancreatitis is a critically pathological type of acute pancreatitis (AP). Initially, the pancreatic necrosis is solid or semi-solid state. And then, the necrotic lesion would gradually become soften, thereafter followed by liquefied necrosis. Classically, the CT severity index or MRI severity index can be usually regarded as a favorite imaging marker for predicting the prognosis of AP. In fact, like the clinical significance of necrotic areas, the depth of pancreatic necrosis also influences the outcome of patients. Indeed, dynamic processes of necrotizing pancreatitis can be tracked clearly on CT or MRI. This article mainly introduces the values of imaging on the AP dynamic followings. And a novel academic opinion is given as "Transmural pancreatic necrosis-Pancreatic duct disruption-Walled-off necrosis" trilogy.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of magnetic resonance imaging in predicting postoperative recurrence patterns of high-grade gliomas]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.023</link>
<description><![CDATA[Glioma is the most common central nervous system malignant tumor. High-grade glioma (HGG) is prone to high recurrence rate and poor prognosis after surgery due to complex biological behaviors. Gliomas that recur after surgery are often more malignant and more aggressive. The survival prognosis of HGG patients with different recurrence patterns is also very different. Therefore, early and accurate prediction of HGG recurrence patterns is of great significance for patients to choose the best treatment plan. In predicting the recurrence pattern of HGG, MRI can use different MRI sequences to evaluate the tumor factors of the patient through preoperative location, volume, morphology and other indicators, and combine clinical factors to make more accurate prediction of recurrence patterns.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of machine learning for predicting breast cancer response to neoadjuvant chemotherapy based on MRI]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.024</link>
<description><![CDATA[Neoadjuvant chemotherapy (NAC) is the essential component of breast cancer treatment plan. Breast cancer will show varying degrees of remission after NAC. An accurate method of efficacy prognosis can help in the adjustment of treatment plan and the selection of surgical modality that can benefit patients to the maximum extent. Machine learning (ML) can extract high-throughput information from MR images to reflect tumor heterogeneity and predict tumor response early in NAC or even before therapy. This article reviews the progress of research on ML combined with breast MRI to predict the efficacy of NAC.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Progress of radiomics in diagnosis and treatment of hepatocellular carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.025</link>
<description><![CDATA[The incidence of hepatocellular carcinoma has been high in recent years. Today, with the emphasis on the concept of "precision medicine", accurate information is needed to provide efficient and individualized diagnosis and treatment for patients. Radiomics is of great significance for improving the individualization and precision of medical strategies because it can obtain the information of the overall heterogeneity of tumor noninvasively. This paper mainly discusses the radiomics research progress in diagnosis and treatment of hepatocellular carcinoma, including the diagnosis and differential diagnosis of hepatocellular carcinoma, prediction of gene phenotypes and molecular markers, efficacy monitoring and prognosis prediction , and based on the research achievements of deep learning applications. The demerits of radiomics technology and its future development direction were also summarized at the end of article.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Application progress of intravoxel incoherent motion imaging in clinical diagnosis and treatment of rectal cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.026</link>
<description><![CDATA[Imaging evaluation of rectal cancer mainly focuses on diagnosis, preoperative staging and prediction of treatment response. Accurate preoperative staging and prediction of therapeutic response after neoadjuvant chemoradiotherapy (NCRT) can provide a basis for clinical selection of appropriate treatment . Intravoxel incoherent motion (IVIM) is a new technology derived from diffusion weighted imaging (DWI). It applies multi-b value scanning without intravenous injection of gadolinium contrast agent. It can quantify the perfusion and diffusion information in tissues and cover more comprehensive informations than DWI. It is useful in the diagnosis and treatment of rectal cancer. It has certain value in the diagnosis, staging and curative effect evaluation. This paper mainly reviews the application status and development trend of IVIM in rectal cancer.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of magnetic resonance elastography in the quantitative diagnosis and staging of liver fibrosis]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.027</link>
<description><![CDATA[Liver fibrosis (LF) refers to the abnormal accumulation of liver extracellular matrix, especially collagen fibers. LF can progress to cirrhosis or even liver cancer without intervention or insufficient intervention. Early LF is histologically reversible. Magnetic resonance elastography (MRE) is a robust technique for evaluating the mechanical properties of tissues, and it is also the most accurate non-invasive imaging method for evaluating LF. The purpose of liver MRE is to observe histological changes as early as possible before the morphology is visible, and to provide a basis for clinical interventions to prevent the further development of fibrosis as early as possible. With the continuous advancement of magnetic resonance technology, non-invasive quantitative diagnosis and staging of LF have made great progress. This article summarizes the research progress of MRE in the quantitative diagnosis and staging of LF.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of Wallerian degeneration in the central nervous system diffusion magnetic resonance imaging]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.028</link>
<description><![CDATA[Wallerian degeneration refers to the process of demyelination and disintegration of distal axons due to injury to the cell body or proximal axons. Wallerian degeneration of the pyramidal tract of the central nervous system will affect the recovery of the patient<sup><sup>,</sup></sup>s motor function. More advanced MRI techniques can not only provide relevant information of early wallerian degeneration in pyramidal tract, but also predict the long-term recovery of motor function of patients, which will provide help for early intervention and treatment of patients in the future.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances in functional magnetic resonance imaging for renal function assessment]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.029</link>
<description><![CDATA[Various diseases can cause abnormal renal function. Early and accurate evaluation of renal function is the focus of clinical diagnosis and treatment. Currently available clinical biomarkers cannot accurately detect renal insufficiency early and assess its severity and progression. With the rapid development of functional magnetic resonance imaging (fMRI) technology, fMRI techniques such as blood oxygen level-dependence imaging, diffusion-weighted imaging, intravoxel incoherent motion imaging, diffusion tensor imaging, and arterial spin labeling can noninvasively assess renal function from oxygenation, diffusion and perfusion, providing more information for the early diagnosis, progression and prognosis of renal disease. In this paper, the principle of fMRI and its evaluation of renal function are described.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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<title><![CDATA[Radiological research progress on the adherence and invasion of adjacent brain tissue caused by craniopharyngioma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2021.12.030</link>
<description><![CDATA[Some important brain tissues are around craniopharyngioma, including hypothalamus. Although craniopharyngioma is WHOⅠ grade tumor, it presents complicated effect on the adjacent brain tissues, including adherence and invasion. This behavior shows an important influence on the tumor treatment and patient prognosis. It is clinically important to identify the effect on the peritumoral brain tissues caused by the tumor in radiology. This paper is to briefly overview the radiological research status on the tumor behavior.]]></description>
<pubDate>Mon,20 Dec 2021 00:00:00  GMT</pubDate>
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