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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=201807</link>
<language>zh-cn</language>
<copyright>An RSS feed for Chinese Journal of Magnetic Resonance Imaging</copyright>
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<title><![CDATA[Changes of local brain neural function activity in subjective tinnitus based on resting-state functional MRI]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.001</link>
<description><![CDATA[Objective: To explore the alterations of local spontaneous brain function activity in patients with subjective tinnitus (ST) using regional homogeneity (ReHo) and fractional amplitude of low-frequency fluctuations (fALFF) approaches. Materials and Methods: Twenty-five patients with ST and 25 age-, sex-, and education-matched normal controls were included in the study. All participants underwent resting-state functional magnetic resonance imaging (fMRI) scans. Both ReHo and fALFF values were calculated to represent local spontaneous brain activity and were compared between groups. Correlational analyses were then conducted to investigate the relationship between these two methods and clinical scale data in ST patients. Results: Compared with normal controls, ST patients showed significantly increased ReHo and fALFF values in the right middle temporal gyrus (MTG) and cuneus, while decreased ReHo values were found in the right middle frontal gyrus (MFG) and left anterior lobe of the cerebellum (P＜0.05, GRF correction). In the ST group, ReHo values of the right MTG were positively correlated with the tinnitus handicap inventory (THI) score (r=0.576, P=0.003). Conclusions: ST patients showed abnormal spontaneous brain activity in some auditory and non-auditory brain regions, mainly involving the default mode network and audio-visual network, which could confirm that ST exists the aberrant changes of local spontaneous brain neural function activity.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[The effect of leucine on feeding center and reward system in T2DM patients and healthy control subjects: a resting-state fMRI study]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.002</link>
<description><![CDATA[Objective: To study the functional connectivity of the reward system and feeding center after oral leucine in type 2 diabetes mellitus by resting-state fMRI, and analyze the relationships between the changes and related metabolic indicators of T2DM during this test. Materials and Methods: This study included several T2DM patients (T2DM, n=9) whose age, sex, education match up with healthy control subjects (HC, n=8). Resting-state fMRI data were collected by blood oxygen level dependent sequence (BOLD). Brain regions involving in feeding center and reward system were selected as seeds, and functional connection values between these seeds and other voxels in the brain were calculated after oral leucine, the resulted values of both groups were compared using two-sample t-test to locate the regions with significant change. Then correlation analysis was conducted between clinical indexes and values of functional connection extracted from significant difference between groups. Results: After oral leucine, HC group people showed significantly increased functional connectivity between left orbitofrontal cortex and right cerebellum posterior lobe (P＜0.05). The functional connection values between the prefrontal cortex, the anterior cingulum cortex, orbitofrontal cortex, limbic lobe and left putamen increased significantly (P＜0.05),however there were no significant differences in T2DM group (P＞0.05). Moreover, negative correlations were found between the changes of functional connection values of brain function and fasting serum insulin, HOMA2-IR in T2DM group (P＜0.05). Positively correlations were found between the changes of functional connection values of brain function and plasma leucine level in HC group (P＜0.05). Conclusions: T2DM damage the functional connectivity of reward-associated brain regions, and the functional connectivity between left OFC and cerebellar tonsils was correlates with the degree of HOMA2-IR and fasting serum insulin. Moreover, this study indicated that central insulin resistance may damage the leucine sensing pathway.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Investigation of automated glioma grading using DCE-MRI quantitative parameters]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.003</link>
<description><![CDATA[Objective: To develop a non-invasive and automated preoperative glioma grading system based on quantitative parameters derived from dynamic contrast-enhanced MRI (DCE-MRI) data. Materials and Methods: A total of 98 histologically confirmed glioma patients were recruited in this study, including 28 low-grade gliomas (LGGs) and 70 high-grade gliomas (HGGs), who underwent preoperative conventional MRI and DCE-MRI scans. Parametric maps such as AUCAIF, Ktrans, Kep, Ve and Vp were derived using the NordicICE software. Statistically histogram indices of the whole tumor region were calculated from each parametric map and formed the corresponding parametric feature dataset. Support vector machine recursive feature elimination (SVM-RFE) feature selection strategy and SVM classifier were jointly used to train the glioma grade discrimination models. The classification performance of each parametric model was evaluated by 10-fold cross-validation method. Results: The AUCAIF, Ktrans, Kep and Ve parametric classification model achieved relatively high accuracy and area under the curve (AUC) values (all of them≥0.75), except for Vp. When all of the parametric features were combined, the accuracy and AUC values of the trained grading model both increased to 0.864, obviously higher than each independent parametric features. Conclusions: Utilizing the quantitative parameters provided by DCE-MRI and high-efficiency machine learning techniques, it is possible to establish a non-invasive and automated preoperative glioma grading model with high efficiency. This study will provide valuable reference for making treatment plans and increasing prognosis in the future.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Effects of KIBRA polymorphism on the volume of hippocampus subfield in healthy young volunteers]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.004</link>
<description><![CDATA[Objective: To investigate the effect of kidney and brain expressed protein (KIBRA) rs17070145 gene polymorphism on the volume of hippocampus subfield in healthy young volunteers by using the MR automatic segmentation method. Materials and Methods: A total of 60 healthy young volunteers were recruited in the study according to volunteer recruitment process criterion. Subjects were divided into two groups according to the genotype test: one group was the C allele carriers (CC+CT) and another group was the TT homozygous carriers. All subjects underwent the head magnetic resonance imaging, 23 subjects of who were assessed by the neuropsychological scale. The volume of the hippocampal subfields were segmented and calculated by FreeSurfer V5.3.0 software from the 3D-T1 weighted imaging sequence. The differece of each hippocampal subfield volume was compared between the two groups by using the linear regression analysis, controlling for eTIV (estimated total intracranial volume). The eTIV was used as the covariate in this analysis to remove the difference of hippocampal volume caused by the size of each subject. The Pearson correlation test was used between the volume of the hippocampus subfield and the neuropsychological scale. Results: Compared with TT homozygote carriers, the volume of the left CA1 region volume of the C allele group was significantly increased (P=0.032). No significant differences were found between the two groups in other hippocampal subfields. And there was a significant positive correlation between the volume of the left CA1 region volume and the complete time of digital connection test-B (NCT-B) (r=0.459, P=0.028) in 23 volunteers. Conclusions: In the young healthy volunteers, the volume of the left CA1 region is affected by the KIBRA gene polymorphism. The increased volume of left CA1 region in the C allele carriers may be a compensatory effect on the reduction of spatial memory and execution function, which will be helpful to study the neural mechanisms of KIBRA gene polymorphism and spatial memory and execution function on healthy young people.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Value of Gd-EOB-DTPA enhanced MRI in differentlly diagnosing malignant neoplasms from benign nodules of focal liver lesions]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.005</link>
<description><![CDATA[Objective: To evaluate the values of unenhanced MRI, high-b-value diffusion-weighted imaging (DWI) and Gd-EOB-DTPA enhanced MRI in diagnosis of focal liver lesions. Materials and Methods: Sixty-eight patients with 96 focal hepatic lesions were enrolled in this study. The images were analyzed by three methods: method A included the combined reading of unenhanced, DWI images, method B considered unenhanced, dynamic enhanced phase images, method C considered unenhanced, DWI, dynamic enhanced phase and hepatobiliary phase images. Two experienced abdominal radiologists who were independent reviewed the images. Sensitivity and specificity were cmpared by χ2 test. Results: Histopathology of the lesions,there were hepatocellular carcinoma (HCC, n=47), dysplastic nodule (DN, n=12), hemangioma (n=10), intrahepatic cholangiocarcinoma (ICC, n=8), intrahepatocellular carcinoma-cholangiocarcinoma (HCC-ICC, n=6), regenerative nodule (RN, n=7), malignant lymphoma (n=2) and metastases, lymphoid follicular hyperplasia, abscess, adenoma for one case each. 61, 61, 64 malignant neoplasms were characterized by methods A, B and C, respectively. The sensitivity, specificity was 87.5% (56/64), 50.0% (16/32), 71.9% (46/64), 75.0% (24/32), 96.9% (62/64), 75.0% (24/32) respectively. The sensitivity and specificity of diagnosing malignant lesions of liver in three groups were statistically different (P＜0.05) except for the difference in the specificity between group B and group C (P=1). Conclusions: Gd-EOB-DTPA enhanced MRI, unenhanced MRI and high-b-value diffusion-weighted imagings (DWI) showed typical imaging features, which were best sanning methods in diagnosis of focal liver lesions.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Preliminary application of gadolinium-based capsule in MR colon transit times]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.006</link>
<description><![CDATA[Objective: Radio-opaque markers (ROMs) is a commonly used traditional method for colon dynamics. As the limitation of ionizing radiation of ROMs in clinical use, we proposed a method of gadolinium-based capsules in the measurement of colon dynamics. It can be used in semi-quantitative analysis of digestive tract transmitting ability in a non-invasive way and free of ionizing radiation. Materials and Methods: Twenty healthy volunteers without acute or chronic gastrointestinal function disorders and 5 slow transit constipation patients consumed 5 gadolinium-based capsules simultaneously. Gadolinium-based capsules contained gadolinium/0.9% normal saline (concentration ratio is 1:10). After ingestion of capsules, T1WI LAVA sequences using a 1.5 Tesla MR system is obtained at certain time point until all capsules were emptied completely. The location of capsules is analyzed via these imaging data. Results: All of the twenty healthy volunteers (average age: 33 years) and five slow transit constipation patients (average age: 34 years) successfully underwent MRI colonic transit tests without any discomfort. In healthy volunteers group, the mean transit time is (32.3±18.9) hour. For slow transit constipation patients, the mean transit time is (64.8±9.6) hour, and it is obviously longer than it in healthy group. The best sequence in MR imaging is defined in T1WI sequence. Conclusions: MRI colon transit times is capable of duplicating the result of X-ray colon transit times accurately. Meanwhile, MR colon transit times is free of ionizing radiation with abundant imaging information. It can clearly demonstrate the morphology of colon, location and semi-quantify the remaining markers in the colon. In future, it can be possible dynamic evaluation of the digestive tract transit time and applied to clinical routine.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Texture features derived from intravoxel incoherent motion diffusion-weighted imaging for predicting the pathological response to chemoradiotherapy in rectal cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.007</link>
<description><![CDATA[Objective: To investigate the performance of texture features based on intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) on identifying pathological complete response (pCR) to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC). Materials and Methods: Pretreatment IVIM-DWI was performed on 38 LARC patients receiving nCRT. Nine first-order texture features (TFs) and eleven gray level co-occurrence matrix (GLCM) TFs were derived from four IVIM-DWI parameter maps (ADC, D, D* and f) respectively. The first-order TFs included Mean, Kurtosis, Skewness, Variance, Perc01%, Perc10%, Perc50%, Perc90% and Perc99%, and the GLCM features included Angular Second Moment (AngScMom), Contrast, Correlat, Difference Entropy (DifEntrp), Difference Variance (DifVarnc), Entropy, Inverse Difference Moment (InvDfMom), Sum Average (SumAverg), Sum Entropy (SumEntrp), Sum of Squares (SumOfSqs) and Sum Variance (SumVarnc). The values of first-order and GLCM TFs were compared between the pCR (n=8) and non-pathological responder (non-pCR, n=30) groups, which was classified according to tumor regression grade system. Receiver operating characteristic (ROC) curve in univariate and multivariate Logistic regression analysis was generated to determine the efficiency for identifying pCR. Results: The pCR group had lower AngScMomD, AngScMomD*, AngScMomf, DifVarncADC, DifVarncD, ContrastADC and ContrastD* values. Higher Perc10%ADC, Perc10%D, Perc99%D*, CorrelatD*, Correlatf, DifEntrpADC, InvDfMomADC, SumAvergD, SumVarncD* and SumOfSqsD* values were observed in the pCR group. The area under the ROC curve (AUC) values for the predictors in univariate analysis ranged from 0.662 to 0.829, with sensitivities from 33.33% to 100.00% and specificities from 37.50% to 100.00%. In multivariate Logistic regression analysis based on the first-order TFs, Perc10%ADC (P=0.032) and Perc10%D (P=0.028) were the independent predictors to pCR, with an AUC value of 0.754 (95% confidence interval, 0.588—0.879), a sensitivity of 50% and a specificity of 100.00%. DifVarncD (P=0.003) and SumVarncD* (P=0.002) were the independent predictors to pCR in the multivariate models that were based on either the GLCM TFs or the combination of the first-order and GLCM TFs, with an AUC of 0.929 (95% confidence interval, 0.797—0.987), a sensitivity of 83.33% and a specificity of 100.00%. Conclusions: GLCM analysis based on IVIM-DWI may be a potential approach to identify the pathological response of LARC before starting chemoradiotherapy.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[The value of MRI intravoxel incoherent motion imaging (IVIM) and diffusion kurtosis imaging (DKI) in the differential diagnosis of benign and malignant bone and soft tissue tumors of lower extremity]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.008</link>
<description><![CDATA[Objective: To evaluate the value of magnetic resonance intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging in the differential diagnosis of benign and malignant bone and soft tissue tumors of lower extremity. Materials and Methods: We collected 54 patients who underwent lower extremity MRI examination found bone or soft tissue masses in the radiology department of our hospital in November 2016 to January 2018.All patients underwent IVIM scan with 14 b values (0, 10, 20, 30, 40, 50, 75, 100, 150, 200, 400, 800, 1000, 1500 s/mm2) and DKI scan with 5 b values (0, 100, 700, 1400, 2100 s/mm2) and routine MRI examination with a 3.0 T MR scanner. IVIM and DKI parameters including ADC, D, D*, f, MK, MD values were measured at a workstation. Patients were divided into benign and malignant bone and soft tissue tumors according to pathological results. Independent two-samples t test was used to evaluate those parameters in differentiating benign and malignant bone and soft tissue tumors. ROC curves were used to evaluate the diagnostic performance of these parameters. Logistic analysis was used to evaluate the diagnostic performance when combinating the parameters of IVIM and DKI. Results: The ADC (1.23±0.27)× 10-3 mm2/s), D (1.12±0.22)×10-3 mm2/s, MD (1.26±0.46)×10-3 mm2/s values of malignant bone tumors were statistically lower than that of benign bone tumors (1.95±0.39)×10-3 mm2/s, (1.78±0.42)×10-3 mm2/s, (1.91±0.53)×10-3 mm2/s (P＜0.05). The f value of malignant tumors (10.0%±3.98%) was statistically higher than that of benign tumors (3.43%±2.99%) (P＜0.05). The MK value [(0.76±0.45)×10-3 mm2/s] was statistically higher than that of benign tumors [(0.36±0.22)×10-3 mm2/s], (P＜0.05). There were no significant difference between D* value of benign and malignant tumors (P＞0.05). The area under the ROC curves of ADC, D, f, D*, MK, MD were 0.935, 0.939, 0.891, 0.701, 0.840, 0.844. When the optimal threshold of ADC, D, MK and MD was 1.64× 10-3 mm2/s, 1.45×10-3 mm2/s, 0.56×10-3 mm2/s, 1.86×10-3 mm2/s, the corresponding diagnostic sensitivity and specificity were 85.7% & 95.2%, 85.7% & 95.2%, 71.4% & 100%, 71.4% & 95.2%. Similiarly, the ADC [(1.27±0.38)×10-3 mm2/s], D [(1.04±0.35)×10-3 mm2/s], MD [(1.53±0.55)×10-3 mm2/s] values of malignant soft tissue tumors were statistically lower than that of benign soft tissue tumors (1.90±0.43)×10-3 mm2/s, (1.71±0.45)×10-3 mm2/s, (2.24±0.60)×10-3 mm2/s (P＜0.05). The f value of malignant tumors (8.20%±3.84%) was lower than that of benign tumors (9.62%±4.47%) (P＞0.05). The MK value [(0.82±0.56)×10-3 mm2/s] was statistically higher than that of benign tumors [(0.45±0.97)×10-3 mm2/s] (P＜0.05). There were no significant difference between D* value of benign and malignant tumors (P＞0.05). The area under the ROC curves of ADC, D, f, D*, MK, MD were 0.876, 0.885, 0.633, 0.552, 0.894, 0.812. When the optimal threshold of ADC, D, MK and MD was 1.33×10-3 mm2/s, 1.42×10-3 mm2/s, 0.60×10-3 mm2/s, 1.71×10-3 mm2/s, the corresponding diagnostic sensitivity and specificity were 100% & 60%, 72.7% & 93.3%, 60.0% & 100%, 90.9% & 66.7%. Conclusions: IVIM parameters ADC, D and DKI parameters MK, MD can help to distinguish benign and malignant bone and soft tissue tumors of lower extremity. The combination of parameters of IVIM and DKI can improve the accuracy of the diagnosis of lower extremity tumors.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Implement of radiomics flow based on the YAP pipeline]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.009</link>
<description><![CDATA[Objective: To support radiomics studies based YAP (Yet Another Pipeline), which is originally a framework for magnetic resonance image reconstruction and post-processing. Materials and Methods: We introduced support of Python into YAP pipeline, so that processors in the pipeline can be programmed in Python. Then we implemented a radiomics pipeline with PyRadiomics package. Finally, the pipeline was used to study brain tumor grading problem with BRATS2017 open datasets. Results: A complete radiomics pipeline was built, which involved hybrid programming of C++ and Python. Best results for BRATS2017 tumor grading were achieved when 12 features were selected, with the best accuracy of 94.5% and AUC (Area Under Curve) for receiver operating characteristic curve of 0.9650. Conclusions: Hybrid programming of Python and C++, together with the facilities provided by YAP framework, may facilitate radiomics studies.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progresses of MRI in white matter hyperintensity]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.010</link>
<description><![CDATA[White matter hyperintensity (WMH) is a common imaging manifestations of cerebral small vessel disease. The occurrence of WMH is mainly related with impaired dynamic cerebral autoregulation, collagen vascular diseases, blood–brain barrier dysfunction and genes, and the incidence of WMH is positively related to age. But the clinical information provided by WMH was still limited. However, a large number of new technologies have been applied to researches about WMH, when radiology represented by MRI made great progresses in recent years. In this paper, the latest clinical applications of revolutionary MRI technologies in WMH were primarily reviewed, and the limitations of current researches and relevant prospects were stated at last.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[The role of metal ions in AD pathogenesis and its imaging evaluation]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.011</link>
<description><![CDATA[The main pathogenesis of Alzheimer's disease is the abnormal accumulation of beta-amyloid and the abnormal phosphorylation of Tau protein causes neurofibrillary tangles. Metal ions play an important role in the formation of β beta plaque. With the development of imaging technology, it is possible to evaluate the abnormal deposition of beta-amyloid and tangles of neurofibrillary fibers. This paper reviews the mechanism of metal ions and the status of imaging evaluation.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances of MRI new technology in clinical application for rectal cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.012</link>
<description><![CDATA[Rectal cancer is the most common gastrointestinal malignant tumors in China. At present, MRI is the most accurate method for rectal cancer staging. MRI new technology which is used on gastrointestinal, such as high-resolution magnetic resonance imaging, intravoxel incoherent motion diffusion weighted imaging and dynamic contrast-enhanced magnetic resonance imaging, have improved the diagnostic accuracy which can reduce recurrence and improve outcome. We in this article reviewed the clinical application of the above MRI new technology.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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<title><![CDATA[Application of different diffusion models in the diagnosis of endometrial cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2018.07.013</link>
<description><![CDATA[Endometrial cancer is a common malignant tumor in postmenopausal women. The differential diagnosis, preoperative staging, pathological classification and pathological grading are the keys to treatment and prognosis. Conventional MRI is mainly confined to morphological imaging. Different diffusion models include diffusion weighted imaging (DWI), diffusion tensor imaging (DTI), diffusion kurtosis imaging (DKI), intracorporeal incoherent motion imaging (IVIM), be able to provide more clinical information through a series of quantitative and semi-quantitative data analysis. Combined with domestic and foreign literature, this article reviews the application of these four diffusion models in the diagnosis of endometrial cancer.]]></description>
<pubDate>Fri,20 Jul 2018 00:00:00  GMT</pubDate>
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