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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=202309</link>
<language>zh-cn</language>
<copyright>An RSS feed for Chinese Journal of Magnetic Resonance Imaging</copyright>
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<title><![CDATA[Correlation between low-frequency amplitude and serum inflammatory factors in resting-state functional magnetic resonance imaging in mild to moderate depression]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.001</link>
<description><![CDATA[<b>Objective</b>To explore the correlation between the brain functional amplitude of low-frequency fluctuation (ALFF) and serum inflammatory factors in mild to moderate depression (MMD). <b>Materials and Methods</b>A total of 48 MMD patients and 51 healthy controls were included. All participants underwent functional MRI (fMRI) resting-state brain functional scans, and the levels of serum tumor necrosis factor alpha (TNF-α), interleukin 6 (IL-6), interleukin 2 (IL-2), and high-sensitivity C-reactive protein (HsCRP) were measured. The 17-item Hamilton Depression Rating Scale (HAMD-17) and 14-item Hamilton Anxiety Rating Scale (HAMA-14) were used to assess the participants<sup><sup>,</sup></sup> clinical symptoms. The DPABI software was used for preprocessing and statistical analysis of fMRI data to obtain the ALFF values of different brain regions between the two groups. Spearman rank correlation analysis was conducted to explore the relationships between ALFF values, clinical scales, and inflammatory factor levels. <b>Results</b>The MMD group had significantly higher scores on HAMD-17 and HAMA-14 compared to the healthy control group (<i>P</i>＜0.05). The levels of IL-2, IL-6, TNF-α and HsCRP were elevated in the MMD group. Compared to the healthy control group, the MMD group showed increased ALFF values in the left temporal subregion and decreased values in the right temporal pole, left triangular part of the inferior frontal gyrus, and right dorsolateral prefrontal cortex. The correlation analysis revealed a positive correlation between the left temporal subregion and HAMD-17, HAMA-14, and HsCRP (<i>r</i>=0.591, <i>P</i>＜0.001; <i>r</i>=0.549, <i>P</i>＜0.001;<i> r</i>=0.479, <i>P</i>＜0.001), a negative correlation between the right dorsolateral prefrontal cortex and TNF-α (<i>r</i>=-0.285, <i>P</i>=0.004), and a positive correlation between HsCRP and HAMD-17, HAMA-14 (<i>r</i>=0.723, <i>P</i>＜0.001; <i>r</i>=0.667, <i>P</i>＜0.001). <b>Conclusions</b>MMD patients exhibit abnormal immune-inflammatory factors, and there are ALFF differences in specific brain regions, mainly involving the limbic and default mode networks. The left temporal subregion and right dorsolateral prefrontal cortex are abnormal brain regions associated with peripheral inflammatory factors, suggesting the involvement of more complex neuroimmune pathological mechanisms in MMD. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[A study of regional homogeneity altered of brain function and cognitive dysfunction in patients with ischemic stroke]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.002</link>
<description><![CDATA[<b>Objective</b>To explore the changes of regional homogeneity (ReHo) of resting-state brain activity in patients with ischemic stroke (IS) and its relationship with cognitive dysfunction. <b>Materials and Methods</b>Twenty patients with IS and 27 age- and sex- matched healthy controls were prospectively enrolled. All subjects underwent resting-state functional magnetic resonance imaging (rs-fMRI) scan and ReHo analysis. The group differences were compared by using two-sample <i>t</i> test. Person correlation analysis was used to analyze the correlation between the abnormal ReHo values and the scores of mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) scale in IS patient group. <b>Results</b>Compared with the healthy control group, the IS patient group showed reduced in ReHo values in the right middle frontal gyrus, postcentral gyrus, middle temporal gyrus and the left inferior frontal gyrus, triangular part. The increased in ReHo values were found in the bilateral supplementary motor area, median cingulate and paracingulate gyri, the left superior parietal gyrus, precuneus and paracentral lobule. The group differences were statistically significant (<i>P</i>＜0.001, AlphaSim corrected). In addition, the increased ReHo value in the bilateral supplementary motor area and left superior parietal gyrus showed a significant negative correlation with MMSE score (<i>r</i>=-0.640, <i>P</i>=0.014; <i>r</i>=-0.541, <i>P</i>=0.046; <i>r</i>=-0.563, <i>P</i>=0.036). <b>Conclusions</b>The spontaneous ReHo changes exist in multiple brain regions in patients with IS, which may be related to cognitive dysfunction. ReHo values in abnormal brain regions may be an important biomarker of IS. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Abnormal changes of brain function in patients with OSAHS: VMHC-based rs-fMRI study]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.003</link>
<description><![CDATA[<b>Objective</b>To explore the alterations of voxel-mirrored homotopic connectivity (VMHC) in obstructive sleep apnea-hypopnea syndrome (OSAHS) patients and the correlations with clinical indicators. <b>Materials and Methods</b>In this study, apnea hypopnea index (AHI) 15 was taken as the cut-off value, and the subjects were divided into moderate or severe group (OSAHS group,<i> n</i>=68), normal or mild group (control group, <i>n</i>=47). All subjects were male, and underwent polysomnography (PSG) monitoring, cambridge neuropsychological test automated battery assessment, structural and resting-state functional MRI scans. Compared the differences in VMHC between the two groups, and the VMHC values of the abnormal brain regions were extracted to perform the partial correlation analysis with PSG and Cambridge cognitive indicators. <b>Results</b>Compared with the control group, the OSAHS group showed significantly increased VMHC in bilateral posterior cingulate gyrus, insula and superior temporal gyrus (GRF corrected, voxel level<i> P</i>＜0.001, cluster level<i> P</i>＜0.05, two tailed). The VMHC value of bilateral posterior cingulate gyrus and insula were positively correlated with the selection time of spatial recognition memory (SRM) (<i>r</i>=0.318, <i>P</i>=0.010; <i>r</i>=0.437, <i>P</i>＜0.001). <b>Conclusions</b>Patients with OSAHS presente increased VMHC in specific brain regions, suggesting the compensatory mechanism of brain function, and there are certain correlations between the abnormal brain changes and cognitive impairment. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Changes in spontaneous brain activity in patients with postherpetic neuralgia: An ALE Meta-analysis based on rs-fMRI data]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.004</link>
<description><![CDATA[<b>Objective</b>To explore the characteristics of spontaneous brain activity changes in patients with postherpetic neuralgia (PHN), so as to reveal the possible neural mechanism of PHN, and lay a foundation for the objective evaluation of the therapeutic effect of PHN through the changes of spontaneous brain activity in the later stage. <b>Materials and Methods</b>PubMed, The Cochrane Library, EMBase, Medine, and Web of Science, CNKI, CBM, VIP database and Wanfang Data Knowledge service Platform were searched for literatures, which study the changes of brain basal activity in patients with PHN using regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) /fractional amplitude of low-frequency fluctuation (fALFF) analysis methods. Activation likelihood estimation (ALE) was used to perform a Meta-analysis of the brain regions with spontaneous brain activity changes in PHN patients compared with healthy controls (HCs). <b>Results</b>A total of 16 studies from 11 articles were included, including 5 ReHo studies, 4 ALFF studies and 7 fALFF studies, with a total of 200 PHN patients and 236 HCs. Combined with the data from the ALFF/fALFF and ReHo studies, the Meta-analysis results showed that compared with HCs, PHN patients had increased spontaneous brain activity in the right middle frontal gyrus, right thalamus, left striatum and right cuneus, while decreased spontaneous brain activity in the right temporal lobe and right parahippocampal gyrus. Meta-analysis using ALFF/fALFF data alone showed that compared with HCs, PHN patients had increased spontaneous brain activity in the right middle frontal gyrus, right thalamus and left striatum, but no decreased spontaneous brain activity was found. Meta-analysis using data from ReHo study alone showed that there were no regions with increased or decreased spontaneous brain activity in PHN patients compared with HCs. <b>Conclusions</b>In this paper, through the ALE Meta-analysis method, based on the data of reported rs-fMRI whole brain studies, we find that PHN patients have spontaneous brain activity changes in the right middle frontal gyrus, right thalamus, left striatum, right cuneus, right temporal lobe and right parahippocampal gyrus. This provides an important basis for objective evaluation of PHN treatment efficacy through changes in spontaneous brain activity. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application of three-dimensional pseudo-continuous arterial spin labeling combined with automatic segmentation technology in hippocampal sclerotic medial temporal lobe epilepsy]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.005</link>
<description><![CDATA[<b>Objective</b>To study the application value of three-dimensional pseudo-continuous arterial spin labeling (3D-pCASL) combined with automatic hippocampal segmentation technology in hippocampal sclerotic medial temporal lobe epilepsy (MTLE-HS). <b>Materials and Methods</b>A retrospective analysis was made of 40 cases of patients with unilateral MTLE-HS diagnosed with hippocampal sclerosis (HS) by pathology or MRI from January 2021 to December 2022, and 30 healthy volunteers matched with sex and age were included as the control group. All patients were scanned with axial T1 weighted three-dimensional magnetization intensity preparation gradient echo (3D-T1WI-MPRAGE) sequence and 3D-pCASL sequence on 3.0 T MRI. We used FreeSurfer software to segment the hippocampal subregions of 3D-T1WI images. By fusing the segmented hippocampal subregions with perfusion quantitative maps, we registered and measured the subarea cerebral blood flow (CBF). Compare the differences in CBF values in the hippocampus subregion between the left and right sides of the control group, and the affected and contralateral sides of the MTLE-HS group through paired <i>t</i>-tests. Independent samples <i>t</i>-test was used to compare the variability of CBF values in hippocampal subregions between the control group and the affected side of the MTLE-HS group, and between the control group and the contralateral side of the MTLE-HS group. The diagnostic efficacy of CBF value in each subregion in detecting MTLE-HS was evaluated by using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). <b>Results</b>There was no significant difference in the CBF values of the left and right hippocampal subregions CA1, CA2-3, CA4, granular cell layer of dentate gyrus (GC-DG) in the control group (<i>P</i>＞0.05). In the MTLE-HS group, there was no statistical difference in CBF values between the affected and contralateral CA1 (<i>t</i>=1.075, <i>P</i>=0.289), but there were significant differences in other subregions (all <i>P</i>＜0.001). The CBF values of the affected and contralateral sides of MTLE-HS group were significantly different from those of the control group (<i>P</i>＜0.001). ROC curve analysis results showed that the AUC of CBF values in hippocampal CA1, CA2-3, CA4 and GC-DG subregions were 0.746, 0.831, 0.837 and 0.830. <b>Conclusions</b>For patients with focal medial temporal lobe epilepsy, the measurement of blood perfusion in the hippocampal subregion is of certain significance to accurately locate the epileptogenic zone and its affected area before surgery, and provide imaging basis for understanding the blood perfusion changes in the MTLE-HS subregion before surgery. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Changes of cerebrospinal fluid capacity in patients with lung cancer with or without chemotherapy and its clinical significance]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.006</link>
<description><![CDATA[<b>Objective</b>To explore the effects of lung cancer (LC) and chemotherapy on the total amount of intracranial cerebrospinal fluid (CSF) and the volume of CSF in various subregions in patients with LC by using both horizontal and vertical analysis methods. <b>Materials and Methods</b>In the horizontal study, 151 cases of patient with LC admitted to our hospital from May 2019 to December 2021 were retrospectively analyzed, of which 38 receivied chemotherapy. Meanwhile, 39 healthy controls (HC) were recruited. The differences of total CSF volume and CSF capacity in each subregion were compared among the three groups by one-way ANOVA. Then the correlations between the significantly different indicators and cancer-related clinical data in each group were carried out. In the longitudinal study, an additional 20 cases of LC patients admitted to our hospital between July 2020 and January 2022 were then retrospectively analyzed. The paired <i>t</i>-test method was used to compare the changes in CSF volume between the two times, and then, the correlation analyses were performed between the significantly different indexes and the follow-up interval. <b>Results</b>In the transverse study, the CSF volume in the third ventricle and right lateral ventricle of LC patients with chemotherapy and without chemotherapy were significantly higher than that of the HC group (<i>P</i>＜0.05). And in the chemotherapy group, the tumor size was positively correlated with the CSF in the third ventricle (<i>P</i>＜0.05). The longitudinal study showed that compared with the first brain scan, the volume of intracranial, peripheral and left lateral ventricle CSF in LC patients increased significantly after the second follow-up (<i>P</i>＜0.05). And the CSF differences above were positively associated with the follow-up interval (<i>P</i>＜0.05). <b>Conclusions</b>LC and chemotherapy lead to aberrant CSF volume in multiple ventricles,which may provide a new neuroimaging marker for LC diagnosis and assist in guiding cancer chemotherapy. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[White matter microstructural changes shortly after acute stress: A DTI study]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.007</link>
<description><![CDATA[<b>Objective</b>To investigate the changes of white matter microstructure shortly after acute stress using diffusion tensor imaging (DTI) and discuss the clinical significance of these changes. <b>Materials and Methods</b>Thirty motor vehicle accident (MVA) survivors and 26 gender, age and education degree matched healthy subjects were recruited. Along with MRI scan, clinical assessments were also evaluated in both groups. MVA survivors got trauma-specific clinical assessments including Hamilton Anxiety Scale (HAMA) score and received MRI scan within 1week from the MVA. Tract-based spatial statistics (TBSS) was carried out to investigate difference in white matter integrity between 2 groups. White matter integrity was measured using fractional anisotropy (FA), axial diffusivity (AD) and radical diffusivity (RD). A correlation between HAMA score and regional FA value was examined using correlation analysis. <b>Results</b>Significantly lower FA (<i>P</i>＜0.05) values with higher RD (<i>P</i>＜0.05) values were found in areas including the left external capsule, posterior limb of internal capsule, superior longitudinal fasciculus and posterior thalamic radiations (including optic radiation) in MVA survivors as compared with those in control group (<i>P</i>＜0.05). No AD changes were noted (<i>P</i>＞0.05). HAMA score was negatively correlated with FA in the left posterior thalamic radiations (including optic radiation)( <i>r</i>=-0.40, <i>P</i>=0.03 ). <b>Conclusions</b>These results indicate changes in white matter microstructure integrity shortly after acute stress which may be related to anxiety symptom. Therefore, highlight the need for early evaluation and intervention for trauma survivors. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Value of detecting changes in white matter fiber integrity in patinets with amyotrophic lateral sclerosis based on automatic fiber quantification]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.008</link>
<description><![CDATA[<b>Objective</b>To analyze the changes of white matter fiber integrity in patients with amyotrophic lateral sclerosis (ALS) by automatic fiber quantification (AFQ) technology, and explore the feasibility of combining it with support vector machine (SVM) to identify ALS disease. <b>Materials and Methods</b>Clinical and MRI data of 29 patients with ALS (ALS group) and 29 matched healthy controls (HCs group) were prospectively included. Diffusion tensor imaging (DTI) data from all subjects were analyzed using the AFQ software package, and 20 white matter fiber bundles in the whole brain were tracked. Then each fiber bundle was divided into 100 equal parts to acquire quantitative parameter values such as fraction anisotropy (FA), mean diffusion (MD), radial diffusion (RD) and axial diffusion (AD). Partial correlation was further used to explore the relationships between DTI parameters and clinical indicators. Extracting the classification features with white matter fiber difference between two subjects. SVM was used to distinguish them and estimated the accuracy rate. <b>Results</b>The AFQ results showed that, compared with the HCs, the ALS patients had decreased FA values and AD values in the left corticospinal tract, higher AD values in the left inferior fronto-occipital fasciculus and the right superior longitudinal fasciculus, higher MD and RD values of the bilateral corticospinal tract. The average FA value of the left corticospinal tract was positively correlated with Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised (ALSFRS-R) fine functional domain score (<i>r</i>=0.386, <i>P</i>=0.046) and the average AD value of the right superior longitudinal fasciculus was positively correlated with ALSFRS-R bulbar functional domain score (<i>r</i>=0.422, <i>P</i>=0.028). Both the average MD and RD values of the right corticospinal tract were negatively associated with the Edinburgh Cognitive and Behavioural ALS Screen (ECAS) score (<i>r</i>=-0.428, <i>P</i>=0.026; <i>r</i>=-0.416, <i>P</i>=0.031). All the selected nodes with inter-group differences in damaged fiber tracts were used as feature values to achieve a good classification effect. The identification accuracy rate for the ALS and HCs groups was 81.00%, and the maximum area under the curve (AUC) value for the receiver operating characteristic (ROC) was 0.90. <b>Conclusions</b>The white matter microarchitectural damage in ALS is mainly related to the corticospinal tract, and these abnormalities detected by AFQ analysis can be used as a valid biomarker, which can improve the diagnostic evaluation of ALS patients when combined with the SVM method. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Machine learning models based on radiomics in differentiating solitary fibrous tumor from angiomatous meningioma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.009</link>
<description><![CDATA[<b>Objective</b>To investigate the value of machine learning models based on MRI radiomics features in differentiating solitary fibrous tumor (SFT) from angiomatous meningioma (AM). <b>Materials and Methods</b>A total of 68 patients with SFT and 41 patients with AM confirmed by pathology from the Affiliated Hospital of Qingdao University and the First Affiliated Hospital of Guangxi Medical University were retrospectively enrolled. The pre-processing, delineation of the region of interest (ROI), and feature extraction of the T1-weighted images (T1WI), fluid-attenuated inversion recovery (FLAIR), and contrast-enhanced T1WI were performed in the 3D slicer software. The optimal feature set was selected by independent-samples<i> t</i> test and least absolute shrinkage and selection operator (LASSO). The optimal features of multi-parameter MRI were selected based on T1WI, FLAIR and contrast-enhanced T1WI. All patients were randomly divided into the training group (<i>n</i>=76) and the test group (<i>n</i>=33) at a ratio of 7∶3. The models were established by logistic regression (LR), random forest (RF), and support vector machine (SVM). Receiver operating characteristic (ROC) curves were drawn, respectively, and accuracy, sensitivity, specificity, and area under the curve (AUC) were calculated. The DeLong<i> </i>test was used to compare the differences in AUCs among different models. <b>Results</b>The average age of the AM group was higher than that of the SFT group (<i>P</i>＜0.001). There was no significant difference in gender composition between AM group and SFT group (<i>P</i>＞0.05). Twenty-two, twelve, twelve and sixty-five radiomics features were extracted from T1WI, FLAIR, contrast-enhanced T1WI and multi-parameter MRI, respectively. The differentiation efficiency of models based on multi-parameter MRI between intracranial SFT and AM was better than that of models based on a single sequence. The SVM model based on multi-parameter MRI reached the highest performance of all models, and the AUC was 0.99. Among models based on a single sequence, differentiation efficiency of models based on T1WI or FLAIR was better than that of models based on contrast-enhanced T1WI. The AUCs of LR models were all greater than 0.9. <b>Conclusions</b>Machine learning models based on MRI radiomics features can effectively discriminate SFT from AM. The differentiation efficiency of models based on multi-parameter MRI is higher, and the SVM model has the highest efficiency among these models. LR models have good efficiency and stability. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Radiomics analysis based on IVIM-DWI quantitative parameters to predict the short-term therapeutic effect of nasopharyngeal carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.010</link>
<description><![CDATA[<b>Objective</b>To establish a predictive model based on quantitative characteristics of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) radiomics to predict short-term treatment efficacy of nasopharyngeal carcinoma before treatment. <b>Materials and Methods</b>A retrospective study was conducted to collect 80 patients with nasopharyngeal carcinoma diagnosed pathologically at the first visit who were treated in the Radiotherapy Department of Hainan Provincial People<sup><sup>,</sup></sup>s Hospital from January 2019 to August 2021. Before treatment, all subjects underwent MRI plain scan + enhanced examination and 11 b-value (interval 0-800 s/mm<sup>2</sup>) IVIM-DWI examination. After receiving comprehensive treatment based on radiotherapy, routine MRI follow-up of head and neck was conducted every 3 months. Use MRI follow-up images taken 6 months after the end of treatment for efficacy evaluation. According to respond evaluation criteriain solid tumors, version 1.1 standard, the patients were divided into complete remission group (<i>n</i>=62) and incomplete remission group (<i>n</i>=18). The real diffusion coefficient (D), perfusion related diffusion coefficient (D<sup>*</sup>) and perfusion fraction (f) were obtained by post-processing IVIM-DWI with a double exponential model. Itk-snap was used to delineate the region of interest (ROI) of the lesion layer by layer on the S<sub>0</sub> image of IVIM-DWI, and the conventional and enhanced MRI images of nasopharyngeal carcinoma were used as the positioning reference. 3D slicer software was used to extract radiomics features, including histogram features, texture features and morphology features, from the corresponding ROI regions of D, D<sup>*</sup> and f quantitative parameter images. The least absolute shrinkage and selection operator algorithm was used to screen out the radiomics features that were highly correlated with the treatment effect. Logistic regression was used to construct radiomics prediction models based on D, D<sup>*</sup>, f, and joint parameters, and predictive performance was evaluated using ROC curves, area under the curve (AUC), and calibration curves. Decision curve analysis (DCA) was used to evaluate the clinical utility of the prediction models. A 10-fold cross-validation was used for internal model validation, and the average sensitivity and specificity were calculated. <b>Results</b>A total of 851 radiomics features were extracted, and after feature selection, two D-value features were selected to construct a radiomics model with a sensitivity of 60.0%, specificity of 79.6%, and an AUC value of 0.734. Two f-value features were selected to construct a radiomics model, with a sensitivity of 66.1%, specificity of 76.3%, and an AUC value of 0.747. One D<sup>*</sup>-value feature was selected to construct a radiomics model, with a sensitivity of 76.1%, specificity of 75.9%, and an AUC value of 0.726. The sensitivity, specificity and AUC of the radiomics model based on the three types of IVIM-DWI radiomics features were 81.7%, 80.6% and 0.827 respectively. The calibration curves showed good goodness-of-fit for all models, and the DCA demonstrated good clinical utility for all four models, with the IVIM joint model showing the highest clinical benefit. <b>Conclusions</b>The radiomics model based on IVIM-DWI parameters can predict the therapeutic response of nasopharyngeal carcinoma patients before treatment. Among them, the most effective model is the IVIM-DWI combined parameter model, which can assist in clinical decision-making for patients. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application value of mono- and bi-exponential model diffusion weighted imaging and arterial spin labeling in predicting short-term curative effect of recurrent nasopharyngeal carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.011</link>
<description><![CDATA[<b>Objective</b>To investigate the potential value of mono- and bi-exponential model diffusion weighted imaging (DWI) and three dimensional pseudo-continuous arterial spin labeling (3DpCASL) in predicting the short-term curative effect of recurrent nasopharyngeal carcinoma. <b>Materials and Methods</b>A total of 34 patients with recurrent nasopharyngeal carcinoma who were treated in our hospital were prospectively enrolled. Before treatment, all patients underwent conventional MRI, traditional mono-exponential model DWI (b=0, 800 s/mm<sup>2</sup>) and intravoxel incoherent motion imaging (IVIM) bi-exponential model multi-b-value DWI and 3DpCASL examination, routine MRI examination after treatment. According to Response Evaluation Criteria in Solid Tumors (version 1.1), patients were divided into response group (complete response and partial response) and non-response group (stable disease and progression disease). The differences in apparent diffusion coefficient (ADC), slow diffusion coefficient (D<sub>slow</sub>), fast diffusion coefficient (D<sub>fast</sub>), perfusion fraction (f), tumor blood flow (TBF), and relative tumor blood flow (rTBF) values were compared between the two groups. Then, the tumor regression rate was calculated according to the regression of the target lesion before and after treatment, and the correlation between each parameter and the tumor regression rate was explored by Spearman correlation analysis. The area under curve of ROC was used to evaluate the diagnostic value of each parameter. <b>Results</b>The baseline ADC and D<sub>slow</sub> value of the response group were significantly lower than those of the non-response group (<i>P</i>＜0.001). The baseline TBF and rTBF values of the response group were significantly higher than those of the non-response group (<i>P</i>＜0.001). The ADC and D<sub>slow</sub> values before treatment were negatively correlated with the tumor regression rate, and the TBF and rTBF values before treatment were positively correlated with the tumor regression rate. ROC analysis showed that the AUC values of ADC, D<sub>slow</sub>, TBF and rTBF for predicting the short-term curative effect of recurrent nasopharyngeal carcinoma were 0.944, 0.940, 0.765 and 0.779, respectively. <b>Conclusions</b>The mono- and bi-exponential model DWI and 3DpCASL parameters could accurately predict the short-term curative effect of recurrent nasopharyngeal carcinoma, especially ADC and D<sub>slow</sub> have the best predictive performance, providing non-invasive technical means and effective quantification for the early and accurate prediction of the short-term curative effect of recurrent nasopharyngeal carcinoma index. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Clinical value of intravoxel incoherent motion diffusion-weighted imaging in the diagnosis of small metastatic axillary lymph nodes in breast cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.012</link>
<description><![CDATA[<b>Objective</b>To investigate the clinical value of quantitative parameters of intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) in axillary small metastatic lymph nodes (SMLN) of breast cancer. <b>Materials and Methods</b>Eighty patients with pathologically confirmed breast cancer with axillary SMLN (SMLN group) and 55 patients with benign lymph nodes (BLN) (BLN group) were collected. Conventional MRI and IVIM-DWI sequence scans of bilateral breast and axilla were perform for all patients. The differences in IVIM-DWI parameters true diffusion coefficient (D), perfusion related diffusion coefficient (D<sup>*</sup>), perfusion fraction (f) and apparent diffusion coefficient (ADC) value between SMLN group and BLN group were analyzed and measured accurately. The double exponential nonlinear model parameters (D, D<sup>*</sup> and f values) and ADC values were drawn to distinguish the ROC curve between the SMLN group and the BLN group with benign breast lesions. The diagnostic effects of axillary SMLN group and axillary BLN in breast cancer were analyzed by area under curve (AUC). <b>Results</b>The D value (<i>F</i>=6.975, <i>P</i>＜0.01), D<sup>*</sup> value (<i>F</i>=3.206, <i>P</i>＜0.01) and ADC value (<i>F</i>=5.117, <i>P</i>＜0.01) were significantly different, while the f value (<i>F</i>=-0.171, <i>P</i>＞0.05) showed no significant difference between SMLN group and BLN group. D value and ADC value were significantly lower in SMLN group than that in BLN group (<i>P</i>＜0.001), and D<sup>*</sup> value was significantly higher in SMLN group than that in BLN group (<i>P</i>=0.002). The AUC values of D, D<sup>*</sup>, ADC value and the ADC and D combined prediction probability were 0.817, 0.643, 0.734 and 0.833 for differentiating axillary SMLN of breast cancer from BLN of benign breast lesions, respectively. The diagnostic thresholds of D, D<sup>*</sup> and ADC value were 0.750×10<sup>-3</sup> mm<sup>2</sup>/s, 17.500×10<sup>-3</sup> mm<sup>2</sup>/s, and 0.836×10<sup>-3</sup> mm<sup>2</sup>/s, respectively. The sensitivities were 81.8%, 52.7%, 78.2%, and the specificities were 80.0%, 75.0% and 61.3%, respectively. <b>Conclusions</b>The D value in the diagnosis of breast cancer axillary SMLN has a better diagnostic efficiency and is obviously better than ADC value, which has certain significance for the diagnosis of axillary SMLN. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Correlation between radiomics features on T2WI sequences and clinical features of recurrent acute pancreatitis]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.013</link>
<description><![CDATA[<b>Objective</b>To explore the correlation between radiomics features on T2WI sequences and clinical features of recurrent acute pancreatitis (RAP). <b>Materials and Methods</b>This retrospective study collected T2WI images of 200 patients with acute pancreatitis (AP), including 127 cases of primary AP and 73 cases of RAP. The patients were randomly divided into a training group (<i>n</i>=139) and a validation group (<i>n</i>=61) in a 7∶3 ratio. Clinical characteristics of both groups were collected. Feature selection was performed using univariate analysis and the least absolute shrinkage and selection operator (LASSO) algorithm. Spearman correlation analysis was used to analyze the correlation between the optimal radiomics features and clinical characteristics, with <i>P</i>＜0.05 indicating statistical significance. <b>Results</b>Nine statistically significant features were retained, including cluster tendency, variance, two correlations, short run low gray-level emphasis, range, total mean, surface area density, and quartile. Complications were strong positively correlated with range (<i>r</i>=0.606, 95% <i>CI</i>: 0.508-0.690; <i>P</i>＜0.01), total mean (<i>r</i>=0.606, 95% <i>CI</i>: 0.508-0.690; <i>P</i>＜0.01), and quartile (<i>r</i>=0.606, 95% <i>CI</i>: 0.508-0.690; <i>P</i>＜0.01), while gallstone were strong positively correlated with short run low gray-level emphasis (<i>r</i>=0.575, 95%<i> CI</i>: 0.470-0.663; <i>P</i>＜0.01). Hyperlipidemia was strong positively correlated with total mean (<i>r</i>=0.501, 95%<i> CI</i>: 0.386-0.601; <i>P</i>＜0.01) and quartile (<i>r</i>=0.575, 95%<i> CI</i>: 0.470-0.663; <i>P</i>＜0.01), and alcoholism was strong positively correlated with range (<i>r</i>=0.699, 95%<i> CI</i>: 0.618-0.765; <i>P</i>＜0.01), total mean (<i>r</i>=0.822, 95%<i> CI</i>: 0.770-0.864; <i>P</i>＜0.01), and quartile (<i>r</i>=0.699, 95%<i> CI</i>: 0.618-0.765; <i>P</i>＜0.01). <b>Conclusions</b>Complications, stones, hyperlipidemia, and alcoholism are potential biological explanations for the radiomics features of RAP. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Noninvasively evaluate pancreatic exocrine function using 2D cine-dynamic MRCP under physiological conditions: A preliminary study]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.014</link>
<description><![CDATA[<b>Objective</b>To explore the feasibility of using two-dimensional magnetic resonance cholangiopancreatography (2D-MRCP) dynamic cine imaging sequence to quantitatively detect changes in physiological pancreatic juice secretion in the main pancreatic duct of healthy volunteers after consuming a fat meal. <b>Materials and Methods</b>Thirty-six healthy volunteers were recruited, all of whom underwent 2D-MRCP film sequence scanning. Each movie sequence selects the pancreatic head layer and applies a 20 mm wide spatial selection inversion pulse (IR) saturation band at the pancreatic head position. Single layer breath-holding scan, with a breath-holding duration of 5 s and a breath-holding interval of 15 s. Collect and measure the frequency and length of pancreatic juice secretion (basic state frequency and length) of the volunteer 20 times before the fat meal, and hold the breath 60 times after the fat meal to observe the dynamic changes in pancreatic juice secretion after the fat meal. Compare the changes in pancreatic secretion length before and after a fat meal using paired <i>t</i>-tests, and compare the percentage increase in pancreatic secretion frequency after a fat meal compared to the base frequency. Volunteers were divided into three groups based on age. The first group was ≤ 30 years old, the second group was ＞ 30 years old and ≤ 60 years old, and the third group was ＞ 60 years old. The Kruskal Wallis method was used to compare the average frequency of pancreatic juice secretion after a fat meal, and the relationship between the average length and age. <b>Results</b>The frequency of pancreatic juice secretion before fat meal was 21.32%±1.20%, and the frequency of pancreatic juice secretion after fat meal was 29.82%±1.11%, an increase of 8.50%, with a statistical difference of <i>P</i>＜0.001. The length of pancreatic juice secretion before the fat meal was (11.06±7.27) mm, and the length of pancreatic juice secretion after the fat meal was (15.34±4.61) mm, with an average increase of 4.28 mm, showing a statistical difference of <i>P</i>=0.004. According to age group, there were statistical differences in the average frequency and length of pancreatic juice between the first group and the second and third groups, <i>P</i>＜0.001; There was no statistically significant difference in the average frequency and length of pancreatic juice between the second and third groups, with <i>P</i>-values of 0.477 and 0.316, respectively. <b>Conclusions</b>The 2D-MRCP dynamic movie sequence can quantitatively detect changes in pancreatic juice secretion flow after a fat meal, and this sequence has clinical value for non-invasive evaluation of pancreatic exocrine function under physiological conditions. The secretion function of pancreatic juice after fat meal may decrease with age. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Quantitative measurement of renal fat in patients with type 2 diabetes mellitus: Comparison between Dixon and HISTO MRS techniques]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.015</link>
<description><![CDATA[<b>Objective</b>To compare the concordance of renal fat quantification measures based on the six-echo water-fat separation (Dixon) and high-speed T2-corrected multiecho magnetic resonance spectroscopic (HISTO MRS) techniques, and to investigate their predictive ability for renal function impairment. Provide a basis for determining the extent of renal lipotoxicity in patients with type 2 diabetes mellitus (T2DM) and for monitoring treatment efficacy. <b>Materials and Methods</b>This prospective study enrolled 172 patients with T2DM and 55 healthy subjects. Renal proton density fat fraction (PDFF) was obtained through abdominal 3 T MRI using Dixon and HISTO MRS techniques, recorded as D-PDFF and H-PDFF. The intraclass correlation coefficient was used to evaluate the consistency between the two techniques within the same group. The subjects were divided into healthy subjects, normal renal function group in T2DM patients (N-T2DM), mild to moderate renal function impairment group in T2DM patients (M-T2DM), and severe renal function impairment group in T2DM patients (S-T2DM) based on the presence or absence of T2DM and estimated glomerular filtration rate (eGFR), and inter-group differences were compared. Pearson correlation and multiple linear regression analyses were performed to investigate whether D-PDFF and H-PDFF are independent risk factors for decreased eGFR. <b>Results</b>The interclass correlation coefficient was 0.185 for D-PDFF and H-PDFF. After adjusting for confounding factors, the difference in D-PDFF between healthy participants and T2DM patients was statistically significant (<i>P</i>＜0.001), while the difference in H-PDFF was not statistically significant (<i>P</i>＞0.05). After adjustment, the differences in D-PDFF between the healthy participant group and the N-T2DM group, the healthy participant group and the M-T2DM group, and the N-T2DM group and the M-T2DM group were all statistically significant (all <i>P</i>≤0.001). The differences in H-PDFF among the groups were not statistically significant (all <i>P</i>＞0.05). D-PDFF was independently and negatively associated with increased eGFR (<i>β</i>=-0.168, <i>P</i>=0.016) after correction for confounders and was identified as an independent risk factor for renal impairment. H-PDFF values did not correlate with eGFR (<i>β</i>=-0.008, <i>P</i>=0.918). <b>Conclusions</b>The two magnetic resonance fat quantification techniques are poorly concordant in the kidney. Dixon-based PDFF is more responsive to increased renal ectopic fat accumulation (RELA) and renal function impairment in patients with T2DM than HISTO MRS-based PDFF. Therefore, Dixon-based PDFF may be a more suitable method for monitoring RELA in patients with T2DM. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application of magnetic resonance image compilation in the diagnosis of dermatomyositis/polymyositis and quantitative assessment of activity]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.016</link>
<description><![CDATA[<b>Objective</b>To investigate the quantitative parameters of MR compilation on dermatomyositis (DM) / polymyositis (PM) the diagnostic value of activity, and the correlation between quantitative parameters and clinical indicators was analyzed. <b>Materials and Methods</b>The imaging data and clinical data of 68 patients with DM/PM confirmed by clinical and pathological methods in General Hospital of Ningxia Medical University were retrospectively collected, and the case group was divided into an active group (28 cases) and an inactive group (40 cases) according to the electromyogram and myositis disease activity tool. Another 24 normal volunteers matching the age, gender and body mass index (BMI) of the case group were also collected. SIGNA Architect 3.0 T MRI scanner was used to perform MAGiC sequence and conventional T1WI, T2WI and T2Flex sequence scanning on both thighs. The T2 and T1 values of the three thigh muscle groups were measured twice by two radiologists on the MAGiC sequence. One-way analysis of variance or Kruskal-Wallis <i>H</i>-test was used to compare the T2 and T1 values of different groups. Receiver operating characteristic (ROC) curves were plotted and the area under the curve (AUC) was calculated to analyze the diagnostic efficacy of T2 values for DM and its activity. Spearman correlation was used to analyze the correlation between DM/PM quantitative parameters and creatine kinase (CK) value. <b>Results</b>(1) The T2 values of anterolateral, medial and posterior muscles in DM/PM active group were higher than those in inactive group and control group (<i>F</i> values were 48.17, 94.60, 79.11,<i> P</i>＜0.05). The T1 value of the active group was higher than that of the inactive group and higher than that of the control group (<i>F</i>=16.13, <i>P</i>＜0.05). There was no significant difference between medial muscle group and posterior muscle group (<i>P</i>＞0.05). (2) The AUC value of T2 value of muscle groups in case group and control group was 0.939; the Youden index, sensitivity and specificity were 0.726, 81.5% and 91.0%, respectively. The AUC value of active and inactive muscle T2 values was 0.722, and the Youden index, sensitivity and specificity were 0.389, 57.1% and 81.8%, respectively. (3) The T2 value of the posterior muscle group was significantly positively correlated with CK (<i>r</i>=0.48, <i>P</i>＜0.05). <b>Conclusions</b>T2 value of MAGiC quantitative mapping technique can quantitatively analyze muscle involvement in DM/PM patients, which is highly correlated with clinical indicators of CK. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application of fMRI in the study of central mechanism of acupuncture and moxibustion in the treatment of depression]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.019</link>
<description><![CDATA[Depression is a kind of affective disorder caused by various reasons, which is mainly characterized by significant and lasting depression. It belongs to the category of "depression syndrome" in traditional medicine. Acupuncture is effective in the treatment of depression in clinic, and there are many studies on its central mechanism at home and abroad, but due to the differences in research design methods, a unified standard has not been formed. The emergence of functional MRI (fMRI) has a place in the field of brain functional localization, which provides reliable technical support for the study of the central mechanism of acupuncture in the treatment of depression. This article reviews the application of fMRI, the research progress of abnormal brain function network related to depression and the improvement of brain function network in patients with depression after acupuncture treatment, in order to provide new ideas for studying the potential mechanism of acupuncture treatment of depression. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress on neuroimaging biomarkers of cognitive impairment in patients with type 2 diabetes]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.020</link>
<description><![CDATA[The onset of cognitive dysfunction associated with type 2 diabetes mellitus (T2DM) is insidious, and the specific mechanism remains unclear. Structural MRI can objectively measure brain volume and cortical morphological changes; diffusion weighted imaging can accurately track nerve fibers; quantitative susceptibility mapping can quantify the abnormal iron deposition in living tissues. Graph theory analysis can reflect the information processing efficiency of brain network; neurovascular coupling analysis can detect neurovascular injury; machine learning can build reliable diagnostic or predictive models. At present, the combination of multimodal MRI and advanced neuroimaging analysis theory has gradually become a powerful tool for clinical research on the mechanism of cognitive impairment in T2DM. The article reviewed the progress of multimodal MRI in the study of neuroimaging biomarkers of cognitive dysfunction in T2DM, in order to provide imaging evidence for revealing its neurophysiological mechanism and early diagnosis. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of quantitative susceptibility mapping in cognitive impairment]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.021</link>
<description><![CDATA[Cognitive impairment is caused by various diseases, and previous studies have shown a certain correlation between abnormal iron deposition in the brain and cognitive impairment. Quantitative susceptibility mapping (QSM) is a new imaging technique that can quantitatively detect magnetic substances in tissues, providing a feasible method for studying the correlation between cognitive impairment and iron deposition in the brain caused by Alzheimer<sup><sup>,</sup></sup>s disease, Parkinson<sup><sup>,</sup></sup>s disease, Diabetes mellitus type 2, vascular cognitive impairment and other diseases. This article provided a review of the latest research progress on QSM technology and cognitive impairment in recent years. It analyzed the application value of QSM technology in the study of cognitive impairment from the aspects of the etiology of cognitive impairment, corresponding brain iron deposition sites, and imaging related manifestations. The aim is to provide objective imaging basis for non-invasive assessment of patient progress and formulation of treatment plans in the early stage. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Implications of habitat imaging-based multisequence MRI in adult-type diffuse glioma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.022</link>
<description><![CDATA[Adult-type diffuse glioma is the most common malignancy among central nervous system tumors, and although surgical resection combined with radiotherapy and chemotherapy prolongs patient survival, its 5-year survival rate remains low. The genetic heterogeneity, epigenetic heterogeneity and environmental heterogeneity encompassed by gliomas greatly affect the effectiveness of patient treatment options. Habitat imaging based on Darwinian evolutionary dynamics can be combined with quantitative MRI to reflect the spatial and temporal heterogeneity of tumors more clearly. The subregions generated by the habitat analysis are expressions of different environmental selective forces and cellular adaptation differences within the tumor. In this review, we first describe the importance of tumor microenvironment heterogeneity studies and the advantages of habitat imaging. Different clustering methods for building habitat maps and their advantages and disadvantages were explored. The application of this technology in the areas of predicting patient survival cycles, assessing tumor genetic subtypes, and monitoring post-treatment response is then summarized. Finally, the technical difficulties faced in this research direction and the future development trend are given in-depth consideration and forward-looking outlook. This will help in genotyping, prognosis prediction, targeted puncture and individualized treatment of adult-type diffuse glioma patients. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of magnetic resonance imaging in the assessment of TAO activity]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.023</link>
<description><![CDATA[Thyroid-associated ophthalmopathy (TAO) is an autoimmune orbital disease. TAO affects the patient<sup><sup>,</sup></sup>s appearance and even causes blindness, which reduces the patient<sup><sup>,</sup></sup>s quality of life. The assessment of its disease activity and symptom severity is the basis for formulating treatment plans. Clinical activity score is mainly used to evaluate the stage of TAO. The imaging manifestations of TAO patients are mainly exophthalmos, extraocular myoedema thickening and orbital lipopedema, and other manifestations may be combined with enlarged tear gland volume, eyelid and optic nerve edema. Multi-modal MRI techniques such as T2WI fat suppression sequence, dynamic enhanced MRI, diffusion magnetic resonance imaging, mapping, magnetization transfer imaging and artificial intelligence analysis based on MRI images can provide more objective information for the activity staging of TAO from a variety of perspectives. In this paper, we summarized the application of these techniques in the extraocular muscle, orbital fat, lacrimal gland and optic nerve of TAO patients, and combined with the measured parameter values to determine the stage of TAO. It is of great significance to guide clinical decision-making, and is expected to provide reference direction for future research. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application and research progress of extracellular volume based on MRI and CT in malignant tumor]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.024</link>
<description><![CDATA[Extracellular volume (ECV) is a quantitative factor of intravascular and extravascular-extracellular space. With the further study of tumor microenvironment, ECV can quantify the decisive components of malignant tumors and provide more quantitative analysis indicators non-invasively, and has a wide application prospect in tumor-related diseases. We reviewed the application of ECV based on MRI and CT in the diagnosis, differential diagnosis, pathological grading and prognosis of malignant tumors in this paper to enable clinicians and radiologists to understand the application of ECV in malignant tumors, in order to promote the application of ECV in cancer research and development. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application progress of MRI radiomics in predicting the prognosis of breast cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.025</link>
<description><![CDATA[Breast cancer is the most common cancer among women worldwide and is characterized by intra- and inter-tumor heterogeneity that strongly contributes towards its poor prognosis. With more and more high-precision diagnosis and treatment data, breast Magnetic resonance imaging (MRI) radiomics shows great potential. MRI is the most sensitive imaging method for breast cancer as it provides a comprehensive assessment of the overall tumor information by observing the morphological and hemodynamic characteristics of the lesion. As a new research field for high-throughput extraction and quantitative analysis of image features, radiomics has received extensive attention and been applied in the field of tumors in recent years. We summarized the steps of the work flow of radiomics, and according to the published literature to study the application of MRI radiomics in predicting the prognosis of breast cancer, as well as the limitations and challenges of radiomics in this paper, so as to provide ideas for clinical accurate diagnosis and treatment and improve the level of prognosis evaluation of breast cancer in female population. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Summary of mammography of breast MRI and progress in its prognostic application]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.026</link>
<description><![CDATA[Breast cancer is the most prevalent malignant tumor in women. MRI has played a great role in the diagnosis, treatment, and prognosis of breast cancer due to its good tissue resolution and absence of radiation, and a lot of research has been conducted. With the increasing availability of high-precision diagnosis and treatment data, breast MRI imaging histology has shown the potential to be used more and more. The study searched PubMed, China Knowledge Network, and Wanfang database for literature on MRI imaging histology in breast cancer prognosis research, and summarized and analyzed the software used, the research process, and the research results. This paper focuses on the research methods, such as platform selection, image segmentation, feature extraction, verification queue selection, and image selection, used in MRI imaging histology in breast cancer prognosis and the prognostic application of combined models, to provide valuable imaging information to clinicians focusing on the prognosis of breast cancer patients and to assist in the precision treatment of breast cancer. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of artificial intelligence measurement technology for three-dimensional volume of breast cancer based on dynamic contrast-enhanced magnetic resonance imaging]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.027</link>
<description><![CDATA[As one of the important imaging methods for breast diseases, MRI is of great significance in the early detection of breast cancer and prediction of outcome. At present, the assessment of breast cancer tumor size is mainly based on the information of tumor diameter and morphology contained in two-dimensional images, which has certain limitations and low reproducibility, and the prediction accuracy needs to be further improved. Based on dynamic contrast enhanced MRI measurement of tumor volume and other three-dimensional information can provide an important basis for determining the course of breast cancer and evaluating the efficacy of neoadjuvant chemotherapy. However, the measurement of 3D information of breast cancer tumors relies on the experience of the physicians and takes a long time. To improve the measurement accuracy and reduce the time cost, artificial intelligence technology has a promising research prospect in the field of breast MRI. In view of this, we compared the research and applications of artificial intelligence, especially deep learning techniques, in automated breast cancer tumor volume measurement, mainly in the areas of image segmentation, morphological 3D reconstruction, visualization and volume measurement. This paper provides precise material for clinicians to gain insight into how AI techniques can help in automated and high-precision measurement of breast tumors, and provides ideas for information technology personnel to understand how AI techniques can be applied to breast tumor measurement. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of MRI radiomics in the evaluation of curative effect of hepatocellular carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.028</link>
<description><![CDATA[Hepatocellular carcinoma (HCC) is the sixth most common malignant tumor and the fourth leading cause of cancer-related mortality worldwide. Early and accurate prediction of therapeutic effect is very important for the prognosis of patients, but most indexes for evaluating therapeutic effect are based on postoperative pathological puncture, which is not helpful for preoperative decision-making. MRI radiomics can quantify tumor heterogeneity through the spatial distribution and relationship of gray levels in medical images and quantitatively extract the microscopic characteristics of images in order to clarify the degree of tumor pathological remission, predict the therapeutic effect of tumors before operations, and meet the needs of subsequent individualized treatment plan formulation. This paper reviews the research progress of MRI imaging in the evaluation of the therapeutic effect of HCC in order to expand the application value of MRI imaging in predicting recurrence and evaluating the therapeutic effect of HCC and to provide new ideas for formulating the best clinical treatment plan. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances in artificial intelligence-based research on microvascular invasion in primary hepatocellular carcinoma]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.029</link>
<description><![CDATA[Hepatocellular carcinoma (HCC) is one of the most common malignant tumors of the digestive system with a high degree of malignancy and poor prognosis. Microvascular invasion (MVI) usually refers to a cluster of cancer cells in the vascular cavity covered by endocrine cells under the microscope. Currently, MVI is generally considered to correlate closely with the recurrence and metastasis of HCC. Therefore, it is essential to predict MVI accurately before surgery. However, there is still no accepted and effective method to accurately predict MVI. With the rise and development of artificial intelligence, radiomics and deep learning are increasingly used to develop individualized predictive models. Radiomics and deep learning technologies can enable deep mining of imaging information to provide more objective and comprehensive information, which can be combined with clinical information to build comprehensive models. These models can accurately assess of HCC MVI risk and help doctors develop individualized treatment strategies. This paper aims to make a comprehensive analysis of relevant studies on MVI assessment by radiomics techniques at home and abroad to enhance the understanding and attention of radiologists and clinicians on MVI and to provide helpful guidance for the accurate assessment and treatment planning of clinical MVI, as well as the prognosis judgment of HCC patients, to improve the diagnosis and treatment results of HCC patients, increase the survival rate, and provide a basis for the realization of the big data medical environment guided by this will provide a basis for individualized and precise treatment under the guidance of big data medical environment. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances and applications of artificial intelligence in liver transplantation]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.030</link>
<description><![CDATA[Liver transplantation (LT) is the primary treatment for end-stage liver disease, which mainly includes hepatocellular carcinoma (HCC) and end-stage cirrhosis. Radiomics and deep learning (DL), which identify subtle features invisible to the human eye from medical imaging images routinely used, which are increasingly being used to predict tumor recurrence after LT. Previous studies mainly focused on the preoperative prediction of tumor recurrence based on radiomics and DL images. It is hoped that more studies will be conducted to predict various complications after LT in the future. This paper mainly analyzes the research progress of radiomics and DL in the prognosis of LT from four aspects: ultrasound, CT, MRI and positron emission computed tomography (PET), including the similarities and differences of previous studies, the advantages and disadvantages of the four imaging methods in the evaluation of postoperative complications of LT. Finally, based on previous studies, the limitations and future development direction of radiomics and DL are summarized. The purpose of this paper is to improve readers<sup><sup>,</sup></sup> understanding of LT, enhance the awareness of imaging physicians and clinicians on the prevention, early diagnosis and early treatment of complications in patients after LT, helping the accurate and individualized treatment of patients after LT, improving the survival rate of patients after LT and improving the prognosis of patients. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[The progress of magnetic resonance imaging in predicting biomarkers of ovarian cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.031</link>
<description><![CDATA[Ovarian cancer has an insidious onset, low early diagnosis rate and poor prognosis. The discovery of biomarkers is increasingly important for the treatment monitoring and guidance of targeted drug use in ovarian cancer, but most of them are invasive. MRI technology, such as diffusion weighted imaging (DWI), dynamic contrast-enhanced MRI (DCE-MRI), and molecular MRI, can be used to non-invasive prediction of biomarkers of ovarian cancer and targeted monitoring of therapeutic efficacy in order to provide new diagnostic and ideas for clinical treatment decisions and reduce invasive damage to patients. In addition, due to the rapid development of the pathogenesis and targeted drug research of ovarian cancer, targeted molecular imaging is becoming increasingly important for the clinical diagnosis and treatment of ovarian cancer. Therefore, it is necessary and urgent to develop and use targeted molecular imaging technology and targeted molecular probes in the future. We reviewed the research progress of different MRI techniques, including DWI, DCE-MRI, molecular MRI, imaging omics and artificial intelligence in predicting the biomarkers of ovarian cancer, providing new ideas for monitoring clinical treatment response and guiding the use of targeted drugs of ovarian cancer. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Application progress of MRI based artificial intelligence in rectal cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.032</link>
<description><![CDATA[High resolution MRI of rectum is the preferred imaging method for evaluating rectal cancer (RC) because of its high soft tissue resolution and its ability to clearly display the rectal wall, mesocenteric fascia, peritoneal reflow and invasion of adjacent organs. However, the semantic features of conventional MRI are still insufficient to assist clinicians in making diagnosis and treatment decisions. Therefore, in the treatment and follow-up process of RC patients, new non-invasive imaging markers are needed to quantitatively describe tumor characteristics, guide clinical development of treatment strategies, and realize individualized diagnosis and treatment. With the development and wide application of artificial intelligence in medicine, it provides an objective reference basis for colorectal cancer evaluation based on high-resolution MRI, which can better assist clinicians to make accurate diagnosis and treatment decisions. This paper summarizes the application of AI in RC lesion segmentation, T stage evaluation, lymph node metastasis prediction, efficacy evaluation after neoadjuvant therapy, and prognosis prediction in recent years, and makes a summary and prospect, aiming to help readers better understand the application progress of MRI-based AI in RC, and provide some reference direction for future research. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research progress of multimodal magnetic resonance imaging in evaluating preoperative staging, restaging after chemoradiotherapy and efficacy of chemoradiotherapy in rectal cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.033</link>
<description><![CDATA[Rectal cancer (RC) is a malignant tumor with high incidence in China and even in the world. In recent years, the application of conventional MRI and functional MRI in RC has developed rapidly. This paper summarized domestic and foreign literatures on high-resolution MRI, dynamic contrast enhanced MRI, diffuse-weighted imaging, intravoxel incoherent motion MRI in evaluating the preoperative staging, restaging after chemoradiation, and the efficacy of chemoradiation in RC, hoping to integrate the advantages and disadvantages of each mode of MRI and provide more reliable imaging basis for clinical diagnosis and treatment. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances in deep learning and Radiomics for precision diagnosis and treatment of bladder cancer]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.034</link>
<description><![CDATA[In recent years, the incidence of bladder cancer (BCa) has been increasing year by year and has become one of the important factors threatening the health of middle-aged and elderly people, and the early detection and prognosis monitoring of BCa has increasingly become a hot spot of current research. Radiomics is a high-throughput quantitative feature extraction method that mines the information contained in multimodal medical images, then synthesises these massive images to extract phenotypic features and explores the relationship between patient prognosis and these extracted features. Deep learning is a representation learning approach in which complex multilayer neural network architectures automatically learn data representations by transforming input information into multi-level abstractions. This paper reviews the research progress of radiomics and deep learning in precision diagnosis and treatment of BCa from the perspective of urological clinicians, including pathological grading and staging prediction, tumour lymph node metastasis prediction and efficacy assessment, and provides an outlook on future research directions. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Research status and progress in the application of MRI quantitative techniques in osteoporosis]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.035</link>
<description><![CDATA[Osteoporosis, as a systemic skeletal metabolic disease, is characterized by low bone mass and deterioration of microstructure, which makes an individual more likely to fracture. Bone mineral density (BMD) has been the gold standard for clinically diagnosing osteoporosis and predicting the risk of fracture. However, MRI techniques are becoming increasingly important in the study of etiology, diagnosis and fracture risk of osteoporosis because of the higher tissue resolution, non-invasive and non-radiation, and the availability of information on bone quality except BMD. Compared with BMD alone, magnetic resonance spectroscopy and water-lipid separation techniques can accurately quantify the bone marrow adipose, diffusion-weighted imaging reflects the pathophysiological changes of bone marrow by assessing the diffusion properties of bone marrow tissue, high-resolution MRI can better predict osteoporotic fractures by microstructural analysis of proximal femoral trabeculae, and ultrashort echo time MRI reflects bone strength by detecting the binding water and pore water content of cortical bone. The paper reviews the application of MRI quantitative techniques in the diagnosis of osteoporosis, summarises their principles and application value, and analyses their advantages and disadvantages, with a view to providing a reference for future applications and studies related to the quantitative assessment of bone quality by MRI and the comprehensive assessment of osteoporosis progression by combined bone mineral density. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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<title><![CDATA[Advances in diffusion MRI based on oscillating gradient spin echo]]></title>
<link>http://med-sci.cn/cgzcx/en/en_articlexml.asp?doi=10.12015/issn.1674-8034.2023.09.036</link>
<description><![CDATA[Diffusion magnetic resonance imaging (dMRI) is one of the most promising methods for microstructural imaging of biological tissues, which has made great progress in tumor and neuroimaging. Oscillating gradient spin echo (OGSE) sequence is a new dMRI technique, which shortens the measurable effective diffusion time of water molecules by applying oscillating gradients. By establishing a mathematical model, the microstructure characteristics such as cell diameter, extracellular water molecular diffusion coefficient, intracellular water molecular volume fraction and cellularity can be measured. It shows the prospect of clinical application in tumor cell diameter measurement, tumor heterogeneity evaluation and nerve axon diameter measurement. This paper reviewed the imaging principle of OGSE, the research status of OGSE in tumors and nerve axons, and the current limitations of OGSE, aiming to provide reference for scholars interested in this technology, promote further research on OGSE, and accelerate the application of OGSE in clinical diagnosis and treatment. ]]></description>
<pubDate>Wed,20 Sep 2023 00:00:00  GMT</pubDate>
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