Publications by authors named "Lizhi Xie"

31 Publications

Value of multiple models of diffusion-weighted imaging for improving the nodal staging of preoperatively node-negative rectal cancer.

Abdom Radiol (NY) 2021 Jun 14. Epub 2021 Jun 14.

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China.

Objective: To investigate the parameters of multiple diffusion-weighted imaging (DWI) models for improving nodal staging of preoperatively node-negative rectal cancer.

Materials And Methods: A total of 74 rectal cancer patients without suspected metastatic lymph nodes on conventional MRI who underwent direct surgical resection between November 2018 and January 2020 were enrolled in this prospective study. DWI parameters of mono-exponential model (ADC), intravoxel incoherent motion (D, D* and f), stretched exponential model (DDC and α), and diffusion kurtosis imaging (MD and MK) within the whole tumor were measured to predict the nodal staging in rectal cancer patients.

Results: The D*, DDC, and MK values were significantly different in patients with pN0 and pN1-2 (all P < 0.001). The D*, DDC, and MK showed good diagnostic performance with the area under the receiver operating characteristic (AUC) of 0.788, 0.827 and 0.799. Multivariate analysis indicated D* (odds ratio, OR = 1.163, P = 0.003) and DDC (OR = 0.007, P = 0.019) as significant predictors of nodal staging. The combination of DDC and D* demonstrated superior diagnostic performance with the AUC, sensitivity, specificity and accuracy of 0.872, 0.800, 0.932 and 0.878, respectively.

Conclusion: Multiple functional DWI parameters were potential to identify the rectal cancer patients with micro-nodal involvement for accurate treatment.
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http://dx.doi.org/10.1007/s00261-021-03125-5DOI Listing
June 2021

Preoperative volumetric synthetic magnetic resonance imaging of the primary tumor for a more accurate prediction of lymph node metastasis in rectal cancer.

Quant Imaging Med Surg 2021 May;11(5):1805-1816

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

Background: An accurate assessment of lymph node (LN) status in patients with rectal cancer is important for treatment planning and an essential factor for predicting local recurrence and overall survival. In this study, we explored the potential value of histogram parameters of synthetic magnetic resonance imaging (SyMRI) in predicting LN metastasis in rectal cancer and compared their predictive performance with traditional morphological characteristics and chemical shift effect (CSE).

Methods: A total of 70 patients with pathologically proven rectal adenocarcinoma who received direct surgical resection were enrolled in this prospective study. Preoperative rectal MRI, including SyMRI, were performed, and morphological characteristics and CSE of LN were assessed. Histogram parameters were extracted on a T1 map, T2 map, and proton density (PD) map, including mean, variance, maximum, minimum, 10th percentile, median, 90th percentile, energy, kurtosis, entropy, and skewness. Receiver operating characteristic (ROC) curves were used to explore their predictive performance for assessing LN status.

Results: Significant differences in the energy of the T1, T2, and PD maps were observed between LN-negative and LN-positive groups [all P<0.001; the area under the ROC curve (AUC) was 0.838, 0.858, and 0.823, respectively]. The maximum and kurtosis of the T2 map, maximum, and variance of PD map could also predict LN metastasis with moderate diagnostic power (P=0.032, 0.045, 0.016, and 0.047, respectively). Energy of the T1 map [odds ratio (OR) =1.683, 95% confidence interval (CI): 1.207-2.346, P=0.002] and extramural venous invasion on MRI (mrEMVI) (OR =10.853, 95% CI: 2.339-50.364, P=0.002) were significant predictors of LN metastasis. Moreover, the T1 map energy significantly improved the predictive performance compared to morphological features and CSE (P=0.0002 and 0.0485).

Conclusions: The histogram parameters derived from SyMRI of the primary tumor were associated with LN metastasis in rectal cancer and could significantly improve the predictive performance compared with morphological features and CSE.
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http://dx.doi.org/10.21037/qims-20-659DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8047345PMC
May 2021

Prediction of pathological prognostic factors of rectal cancer by relaxation maps from synthetic magnetic resonance imaging.

Eur J Radiol 2021 May 15;138:109658. Epub 2021 Mar 15.

Department of Diagnostic Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No.17, Panjiayuan Nanli, Chaoyang District, Beijing, 100021, China. Electronic address:

Purpose: To explore the feasibility of relaxation maps from synthetic MRI for predicting pathological prognostic factors of rectal cancer (RC) and to compare the predictive performance of quantitative values and conventional subjective evaluation.

Material And Methods: A total of 94 patients with pathologically proven RC who underwent direct surgical resection were enrolled in this prospective study. Preoperative rectal MRI including synthetic MRI was performed. The mean T, T, and PD value of the whole tumor was obtained to preoperatively assess the pathological T stage, N stage, extramural venous invasion (EMVI), differentiation, and perineural invasion. Receiver operating characteristic curves were used to explore the predictive performance for assessing the prognostic factors. The T stage, N stage and EMVI status on conventional T2WI were evaluated and compared with the quantitative values.

Results: The T value decreased significantly in patients with positive perineural invasion, lymph node metastasis (LNM), EMVI, and higher T stage RC (p =  0.007 and < 0.001). The T value of LNM and EMVI positive groups was significantly lower than those of the negative groups (p =  0.034 and 0.011). For predicting N stage and EMVI, the T value demonstrated good performance with an AUC of 0.883 (95 % confidence interval, CI, 0.801-0.940) and 0.821 (95 % CI, 0.729-0.893); the T value was superior to the T value and subjective evaluation of radiologists (all p < 0.05).

Conclusion: Synthetic MRI is a promising tool for noninvasive evaluation of prognostic factors of RC by generating relaxation maps.
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http://dx.doi.org/10.1016/j.ejrad.2021.109658DOI Listing
May 2021

To Explore MR Imaging Radiomics for the Differentiation of Orbital Lymphoma and IgG4-Related Ophthalmic Disease.

Biomed Res Int 2021 4;2021:6668510. Epub 2021 Feb 4.

Department of Radiology, The Second Hospital of Jilin University, Changchun 130041, China.

Among orbital lymphoproliferative disorders, about 55% of diagnosed cancerous tumors are orbital lymphomas, and nearly 50% of benign cases are immunoglobulin G4-related ophthalmic disease (IgG4-ROD). However, due to nonspecific characteristics, the differentiation of the two diseases is challenging. In this study, conventional magnetic resonance imaging-based radiomics approaches were explored for clinical recognition of orbital lymphomas and IgG4-ROD. We investigated the value of radiomics features of axial T1- (T1WI-) and T2-weighted (T2WI), contrast-enhanced T1WI in axial (CE-T1WI) and coronal (CE-T1WI-cor) planes, and 78 patients (orbital lymphoma, 36; IgG4-ROD, 42) were retrospectively reviewed. The mass lesions were manually annotated and represented with 99 features. The performance of elastic net-based radiomics models using single or multiple modalities with or without feature selection was compared. The demographic features showed orbital lymphoma patients were significantly older than IgG4-ROD patients ( < 0.01), and most of the patients were male (72% in the orbital lymphoma group vs. 23% in the IgG4-ROD group; = 0.03). The MR imaging findings revealed orbital lymphomas were mostly unilateral (81%, = 0.02) and wrapped eyeballs or optic nerves frequently (78%, = 0.02). In addition, orbital lymphomas showed isointense in T1WI (100%, < 0.01), and IgG4-ROD was isointense (60%, < 0.01) or hyperintense (40%, < 0.01) in T1WI with well-defined shape (64%, < 0.01). The experimental comparison indicated that using CE-T1WI radiomics features achieved superior results, and the features in combination with CE-T1WI-cor features and the feature preselection method could further improve the classification performance. In conclusion, this study comparatively analyzed orbital lymphoma and IgG4-ROD from demographic features, MR imaging findings, and radiomics features. It might deepen our understanding and benefit disease management.
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http://dx.doi.org/10.1155/2021/6668510DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7884128PMC
May 2021

Correlation Between Cerebral Venous Oxygen Level and Cognitive Status in Patients With Alzheimer's Disease Using Quantitative Susceptibility Mapping.

Front Neurosci 2020 18;14:570848. Epub 2021 Jan 18.

Department of Radiology, First Affiliated Hospital of Dalian Medical University, Dalian, China.

Purpose: To quantitatively assess the blood oxygen levels of the cerebral vein using quantitative susceptibility mapping (QSM), and to analyze the correlation between magnetic susceptibility value (MSV) and clinical laboratory indicators/cognitive scores in patients with Alzheimer's disease (AD).

Materials And Methods: Fifty-nine patients (21 males and 38 females) with clinically confirmed AD (AD group) and 22 control subjects (12 males, 10 females; CON group) were recruited. Clinical data and laboratory examination indexes were collected. All patients underwent Mini-mental State Examination, Montreal Cognitive Assessment, Clock Drawing Task, and Activity of Daily Living Scale test, as well as a routine MRI and enhanced gradient echo T2 star weighted angiography (ESWAN).

Results: Higher cerebral venous MSV was observed in AD group compared to CON group, significant differences were observed for bilateral thalamus veins and left dentate nucleus veins. The MSV of bilateral thalamus veins, bilateral internal cerebral veins, and bilateral dentate nucleus veins had significant negative correlation with Mini-mental State Examination score; the MSV of bilateral thalamus veins, bilateral dentate nucleus veins, right septal vein had a significant negative correlation with Montreal Cognitive Assessment scores; a significant negative correlation between the MSV of bilateral thalamus veins, left dentate nucleus vein, right septal vein and the Clock Drawing Task score; the MSV of bilateral thalamus veins, left dentate nucleus vein had a significant negative correlation with Activity of Daily Living Scale score. The MSV of left dentate nucleus vein was positively correlated with the course of the disease, the MSV of bilateral septal vein were positively correlated with the total cholesterol, and the MSV of left septal vein had a positive correlation with LDL.

Conclusion: Decreasing cerebral venous oxygen level in AD patients may affect cognitive status, and associated with the deterioration of the disease in AD patients.
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http://dx.doi.org/10.3389/fnins.2020.570848DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848136PMC
January 2021

Whole-tumor texture model based on diffusion kurtosis imaging for assessing cervical cancer: a preliminary study.

Eur Radiol 2021 Aug 19;31(8):5576-5585. Epub 2021 Jan 19.

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Objectives: To evaluate the diagnostic potential of diffusion kurtosis imaging (DKI) functional maps with whole-tumor texture analysis in differentiating cervical cancer (CC) subtype and grade.

Methods: Seventy-six patients with CC were enrolled. First-order texture features of the whole tumor were extracted from DKI and DWI functional maps, including apparent kurtosis coefficient averaged over all directions (MK), kurtosis along the axial direction (Ka), kurtosis along the radial direction (Kr), mean diffusivity (MD), fractional anisotropy (FA), and ADC maps, respectively. The Mann-Whitney U test and ROC curve were used to select the most representative texture features. Models based on each individual and combined functional maps were established using multivariate logistic regression analysis. Conventional parameters-the average values of ADC and DKI parameters derived from the conventional ROI method-were also evaluated.

Results: The combined model based on Ka, Kr, MD, and FA maps yielded the best diagnostic performance in discrimination of cervical squamous cell cancer (SCC) and cervical adenocarcinoma (CAC) with the highest AUC (0.932). Among individual functional map derived models, Kr map-derived model showed the best performance when differentiating tumor subtypes (AUC = 0.828). MK_90th percentile was useful for distinguishing high-grade and low-grade in SCC tumors with an AUC of 0.701. The average values of MD, FA, and ADC were significantly different between SCC and CAC, but no conventional parameters were useful for tumor grading.

Conclusions: The whole-tumor texture analysis applied to DKI functional maps can be used for differential diagnosis of cervical cancer subtypes and grading SCC.

Key Points: • The whole-tumor texture analysis applied to DKI functional maps allows accurate differential diagnosis of CC subtype and grade. • The combined model derived from multiple functional maps performs significantly better than the single models when differentiating tumor subtypes. • MK_90th percentile was useful for distinguishing poorly and well-/moderately differentiated SCC tumors with an AUC of 0.701.
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http://dx.doi.org/10.1007/s00330-020-07612-zDOI Listing
August 2021

Differential Diagnosis of Solitary Fibrous Tumor/Hemangiopericytoma and Angiomatous Meningioma Using Three-Dimensional Magnetic Resonance Imaging Texture Feature Model.

Biomed Res Int 2020 1;2020:5042356. Epub 2020 Dec 1.

GE Healthcare, MR Research China, Beijing, China.

Background: Intracranial solitary fibrous tumor(SFT)/hemangiopericytoma (HPC) is an aggressive malignant tumor originating from the intracranial vasculature. Angiomatous meningioma (AM) is a benign tumor with a good prognosis. The imaging manifestations of the two are very similar. Thus, novel noninvasive diagnostic method is urgently needed in clinical practice. Texture analysis and model building through machine learning may have good prospects.

Aim: To evaluate whether a 3D-MRI texture feature model could be used to differentiate malignant intracranial SFT/HPC from AM.

Method: A total of 97 patients with SFT/HPC and 95 with AM were included in this study. Patients from each group were randomly divided into the train (70%) and test (30%) sets. ROIs were drawn along the edge of the tumor on each section of T1WI, T2WI, and contrasted T1WI using ITK-SNAP software. The segmented image was imported into the AK software for texture feature extraction, and the 3D ROI signal intensity histograms of T1WI, T2WI, and contrasted T1WI were automatically obtained along with all the parameters. Modeling was performed using the language R. Confusion matrix was used to analyze the accuracy of the model. ROC curve was constructed to assess the grading ability of the logistic regression model.

Results: After Lasso dimension reduction, 5, 9, and 7 texture features were extracted from T1WI, T2WI, and contrasted T1WI, respectively; additional 8 texture features were extracted from the combined sequence for modeling. The ROC analyses on four models resulted in an area under the curve (AUC) of 0.885 (sensitivity 76.1%, specificity 87.9%) for T1WI model, 0.918 (73.1%, 95.5%) for T2WI model, 0.815 (55.2%, 93.9%) for contrasted T1WI model, and 0.959 (92.5%, 84.8%) for the combined sequence model and were enough to correctly distinguish the two groups in 71.2%, 81.4%, 69.5%, and 83.1% of cases in test set, respectively.

Conclusions: The radiological model based on texture features could be used to differentiate SFT/HPC from AM.
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http://dx.doi.org/10.1155/2020/5042356DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725548PMC
June 2021

Quantification of Hepatic Fat Fraction in Patients With Nonalcoholic Fatty Liver Disease: Comparison of Multimaterial Decomposition Algorithm and Fat (Water)-Based Material Decomposition Algorithm Using Single-Source Dual-Energy Computed Tomography.

J Comput Assist Tomogr 2021 Jan-Feb 01;45(1):12-17

From the Department of Radiology, The First Affiliated Hospital of Dalian Medical University.

Methods: Hepatic fat fractions were quantified by noncontrast (HFFnon-CE) and contrast-enhanced single-source dual-energy computed tomography in arterial phase (HFFAP), portal venous phase (HFFPVP) and equilibrium phase (HFFEP) using MMD in 19 nonalcoholic fatty liver disease patients. The fat concentration was measured on fat (water)-based images. As the standard of reference, magnetic resonance iterative decomposition of water and fat with echo asymmetry and least-squares estimation-iron quantification images were reconstructed to obtain HFF (HFFIDEAL-IQ).

Results: There was a strong correlation between HFFnon-CE, HFFAP, HFFPVP, HFFEP, fat concentration and HFFIDEAL-IQ (r = 0.943, 0.923, 0.942, 0.952, and 0.726) with HFFs having better correlation with HFFIDEAL-IQ. Hepatic fat fractions did not significantly differ across scanning phases. The HFFs of 3-phase contrast-enhanced computed tomography had a good consistency with HFFnon-CE.

Conclusions: Hepatic fat fraction using MMD has excellent correlation with that of magnetic resonance imaging, is independent of the computed tomography scanning phases, and may be used as a routine technique for quantitative assessment of HFF.
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http://dx.doi.org/10.1097/RCT.0000000000001112DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7834908PMC
January 2021

Investigating the value of arterial spin labeling and intravoxel incoherent motion imaging on diagnosing nasopharyngeal carcinoma in T1 stage.

Cancer Imaging 2020 Aug 28;20(1):62. Epub 2020 Aug 28.

Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, CT06510, USA.

Background: To investigate the diagnostic value of arterial spin labeling (ASL) and intravoxel incoherent motion (IVIM) imaging in distinguishing nasopharyngeal carcinoma (NPC) in T1 stage from healthy controls (HC).

Methods: Forty-five newly diagnosed NPC patients in the T1 stage and thirty-one healthy volunteers who underwent MR examinations for both 3D pseudo-continuous ASL (pCASL) and IVIM were enrolled in this study. The Mann-Whitney test was used to compare the mean values of blood flow (BF) derived from pCASL and IVIM derived parameters, including apparent diffusion coefficient (ADC), pure molecular diffusion (D), pseudo-diffusion coefficient (D*) and perfusion fraction (f) between NPC tumor and benign nasopharyngeal mucosa of HC. Receiver Operating Characteristic (ROC) was performed to determine diagnostic cutoff and efficiency. The correlation coefficients among parameters were investigated using Spearman's test.

Results: The NPC in the T1 stage showed higher mean BF, lower ADC, D, and f compared to benign nasopharyngeal mucosa (P < 0.001) with the area under curve of ROC of 0.742-0.996 (highest by BF). BF cutoff was set at > 36 mL/100 g/min; the corresponding sensitivity, specificity, and accuracy in differentiating NPC stage T1 from benign nasopharyngeal mucosa were 95.56% (43/45), 100% (31/31) and 97.37% (74/76), respectively. BF demonstrated moderate negative correlation with D* on HC (ρ [Spearman correlation coefficients] = - 0.426, P = 0.017).

Conclusions: ASL and IVIM could reflect the difference in perfusion and diffusion between tumor and benign nasopharyngeal mucosa, indicating a potential for accessing early diagnosis of NPC. Notably, BF, with a specificity of 100%, demonstrated better performance compared to IVIM in distinguishing malignant lesions from healthy tissue.
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http://dx.doi.org/10.1186/s40644-020-00339-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7456064PMC
August 2020

Improving diagnostic performance of differentiating ocular adnexal lymphoma and idiopathic orbital inflammation using intravoxel incoherent motion diffusion-weighted MRI.

Eur J Radiol 2020 Sep 25;130:109191. Epub 2020 Jul 25.

Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China; Clinical Center for Eye Tumors, Capital Medical University, Beijing 100730, China. Electronic address:

Purpose: To investigate the utility of intravoxel incoherent motion diffusion-weighted MRI (IVIM-DWI) derived diffusion and perfusion parameters in differentiating ocular adnexal lymphoma (OAL) from idiopathic orbital inflammation (IOI), and to assess whether IVIM-DWI provides improved diagnostic performance for the distinction.

Method: Twenty-one patients with OAL and 24 patients with IOI underwent IVIM-DWI. Apparent diffusion coefficient (ADC) and IVIM-DWI parameters including true diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f) were measured in lesions by two independent radiologists. The MRI parameter differences between OAL and IOI were tested using two-sample t-test. The receiver operating characteristic (ROC) analysis curves were used to determine the diagnostic performance of significant parameters for differentiation between OAL and IOI.

Results: The ADC, D, and f were lower in OAL than those in IOI (ADC = 0.78 ± 0.12 vs. 0.99 ± 0.16 × 10 mm/s, P < 0.001; D = 0.34 ± 0.15 vs. 0.76 ± 0.25 × 10 mm/s, P < 0.001; f = 0.31 ± 0.06 vs. 0.41 ± 0.08 × 100 %, P < 0.001). There was no significant difference in D* between OAL and IOI (P = 0.235). The optimal cut-off values of ADC, D, and f in differentiating OAL from IOI were 0.83 × 10 mm/s, 0.56 × 10 mm/s, and 0.36 × 100 %, respectively. No significant differences were found in areas under the curve (AUCs) among ADC, D and f (all P > 0.05). The combination of D and f provided significantly higher AUC than ADC (AUC = 0.984 vs. 0.838, Z = 2.128, P = 0.033), and had higher sensitivity of 95.24 %, specificity of 95.83 %, and accuracy of 95.56 %.

Conclusions: IVIM-DWI is valuable in differentiating OAL from IOI, and D combined f can improve the performance of differential diagnosis.
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http://dx.doi.org/10.1016/j.ejrad.2020.109191DOI Listing
September 2020

Differentiation of endometrial adenocarcinoma from adenocarcinoma of cervix using kinetic parameters derived from DCE-MRI.

Eur J Radiol 2020 Sep 24;130:109190. Epub 2020 Jul 24.

Department of Chronic Disease Epidemiology, Yale School of Public Health, Yale University, New Haven, CT, CT06510, USA.

Purpose: This prospective study aimed to investigate the value of kinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in differentiating uterine endometrioid adenocarcinoma (EAC) from adenocarcinoma of cervix (AdC).

Methods: Seventy-five newly diagnosed patients with distinctive pathology underwent DCE-MRI. Observers independently calculated the tumor diameters and DCE-MRI parameters using both population and individual-based arterial input function (AIF). Inter-observer consistency was evaluated, and a comparative analysis between EAC (n = 47) and AdC (n = 28) was performed. Regression analysis was used to select parameters that best distinguished EAC from AdC, and to generate predictive models. Receiver operating characteristic curve (ROC) was applied to calculate the diagnostic efficiency of single parameter and the predictive models.

Results: Inter-observer consistency was excellent (intra-class correlation [ICC] = 0.902-0.981), especially when calculated via population AIF with relatively higher ICC and smaller SD on Bland-Altman plot. Tumor diameters were not correlated with tumor types. All the DCE-MRI parameters were lower in EAC compared to AdC, except K by population AIF and TTP by both sets of AIFs. The statistical parameters were V, Maxslop, and Maxconc by population AIF, and Maxslop and K by individual AIF included in the predictive models, respectively. The two predictive models with combined parameters showed improved diagnostic efficiency in differentiating these two diseases compared with a single parameter.

Conclusion: DCE-MRI can quantitatively evaluate the perfusion difference between EAC and AdC, thus improving the identification of uterine adenocarcinoma with uncertain biopsy pathology.
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http://dx.doi.org/10.1016/j.ejrad.2020.109190DOI Listing
September 2020

Multiple mathematical models of diffusion-weighted imaging for endometrial cancer characterization: Correlation with prognosis-related risk factors.

Eur J Radiol 2020 Sep 31;130:109102. Epub 2020 May 31.

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. Electronic address:

Purpose: To investigate mono-exponential, bi-exponential, and stretched-exponential models of diffusion-weighted imaging (DWI) for evaluation of prognosis-related risk factors of endometrial cancer (EC).

Method: Sixty-one consecutive patients with EC who preoperatively underwent pelvic MRI with multiple b value DWI between September 2016 and May 2018 were enrolled. The apparent-diffusion-coefficient (ADC), bi-exponential model parameters (D, D* and f) and stretched-exponential model parameters (DDC and α) were measured and compared to analyze the following prognosis-related risk factors confirmed by pathology: histological grade, depth of myometrial invasion, cervical stromal infiltration (CSI) and lymphovascular invasion (LVSI). A stepwise multilvariate logistic regression and the receiver operating characteristic (ROC) curves were performed for further statistical analysis.

Results: Lower ADC, D, f, and DDC were observed in tumor with high grade compared with a low-grade group, and the largest area under curve (AUC) was obtained when combining f and DDC values. ADC, D, f, DDC, and α were significantly different in patients with deep myometrial invasion (DMI) compared to those without DMI; the combination of f, DDC and α showed the highest AUC. Significantly different ADC and f were found between patients' presence and absence CSI; the f values showed the highest diagnostic performance with an AUC of 0.825. Regarding the LVSI, ADC, D*, f, and DDC were significantly lower in tumors with LVSI compared to those without LVSI; the combination of f and DDC showed the largest AUC.

Conclusion: Multiple mathematical DWI models are a useful approach for the prediction of prognosis-related risk factors in EC.
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http://dx.doi.org/10.1016/j.ejrad.2020.109102DOI Listing
September 2020

Feasibility of intravoxel incoherent motion diffusion-weighted imaging in distinguishing adenocarcinoma originated from uterine corpus or cervix.

Abdom Radiol (NY) 2021 02;46(2):732-744

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, China Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China.

Purpose: To prospectively assess the incremental value of intravoxel incoherent motion (IVIM) DWI in determining whether the adenocarcinoma originated from the uterine corpus or cervix.

Methods: Eighty consecutive uterine adenocarcinomas from the cervix or endometrium confirmed by histopathology underwent IVIM DWI acquisition on a 3.0T MR scanner before treatment. Five morphologic features were analyzed using Fisher exact test; IVIM DWI-derived parameters, including apparent diffusion coefficient (ADC), true coefficient diffusivity (D), perfusion-related diffusivity (D), and perfusion fraction (f) were compared using two-sample independent t-test or Mann-Whitney U test. Logistic regression analysis was used to develop different diagnosis model. The ROCs of these variables and diagnostic models were compared to evaluate the diagnostic efficiency.

Results: Among single morphologic features, tumor location yielded the highest AUC of 0.891 in distinguishing endometrial adenocarcinoma (EAC) from cervical adenocarcinoma (CAC). Among single IVIM DWI-derived parameters, f values showed the best diagnostic performance (AUC: 0.837) at the optimal cut-off value of 0.261. Additionally, the combined diagnostic model, which consisted of tumor location, ADC and f showed the largest AUC of 0.967 with the highest sensitivity of 88.14%, highest specificity of 100.00%, and highest accuracy of 91.25%.

Conclusion: IVIM DWI-derived parameters add additional diagnostic value to conventional morphologic features. A combined diagnosis model is a promising imaging tool for predicting the origin of uterine adenocarcinoma, further contributing to therapeutic decision-making.
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http://dx.doi.org/10.1007/s00261-020-02586-4DOI Listing
February 2021

Diffusion Kurtosis Imaging of Microstructural Changes in Gray Matter Nucleus in Parkinson Disease.

Front Neurol 2020 17;11:252. Epub 2020 Apr 17.

GE Healthcare, MR Research, Beijing, China.

To explore the microstructural damage of extrapyramidal system gray matter nuclei in Parkinson disease (PD) using diffusion kurtosis imaging (DKI). We enrolled 35 clinically confirmed PD patients and 23 healthy volunteers. All patients underwent MR examination with conventional MRI scan sequences and an additional DKI sequence. We subsequently reconstructed the DKI raw images and analyzed the data. A radiologist in our hospital collected the Mini-Mental State Examination (MMSE) score of all subjects. In the PD group, the mean kurtosis and axial kurtosis level decreased in the red nucleus (RN) and thalamus; the radial kurtosis increased in the substantia nigra (SN) and globus pallidus (GP). Fractional anisotropy decreased in the putamen. The largest area under the ROC curve of mean diffusion in GP was 0.811. Most kurtosis parameters demonstrated a positive correlation with the MMSE score, while several diffusion parameters showed a negative correlation with the same. DKI can qualitatively distinguish PD from healthy controls; furthermore, DKI-derived parameters can quantitatively evaluate the modifications of microstructures in extrapyramidal system gray matter nucleus in PD.
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http://dx.doi.org/10.3389/fneur.2020.00252DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7180218PMC
April 2020

Multi-b-value diffusion weighted imaging for preoperative evaluation of risk stratification in early-stage endometrial cancer.

Eur J Radiol 2019 Oct 12;119:108637. Epub 2019 Aug 12.

Department of Radiology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, China. Electronic address:

Purpose: To investigate the application of multi-b-value DWI parameters for the assessment of risk stratification in early-stage endometrial cancer (EC).

Material And Methods: Fifty-three patients with early-stage EC who preoperatively underwent multi-b-value DWI with 13 b values (from 0 to 2000s/mm²) were included in this study. Multi-b-value DWI derived parameters, including apparent diffusion coefficient (ADC), true diffusivity (D), perfusion-related diffusivity (D*) and perfusion fraction (f) were measured independently by two radiologists. In addition, binary logical regression model was used to calculate predicative probability of combined parameters indicating statistical significance in differentiating risk stratification of early-stage endometrial cancer. Receiver operating characteristic analysis was performed for all single and combined parameters.

Results: The ADC and D values were significantly lower in intermedium-risk compared with low-risk (P = 0.000 and 0.011), as well as high-risk compared with low-risk of early-stage EC (P = 0.001 and 0.013), while f values only showed significant differences between low-risk and intermedium-risk groups (P = 0.011). Among the single parameters, the ADC values had the highest area under the ROC curve (AUC) in the identification of the low-risk of early-stage EC (AUC=0.892). Moreover, the combination of ADC and f value had the best diagnostic performance with the AUC of 0.912, the sensitivity of 81.1% and the specificity of 87.5%.

Conclusion: The multi-b-value DWI parameters provide valuable imaging biomarkers for the assessment of risk stratification in early-stage endometrial cancer. This approach might facilitate the selection of the optimal therapeutic approach and lead to the greater personalization of cancer care.
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http://dx.doi.org/10.1016/j.ejrad.2019.08.006DOI Listing
October 2019

The enhanced T star weighted angiography (ESWAN) value for differentiating borderline from malignant epithelial ovarian tumors.

Eur J Radiol 2019 Sep 13;118:187-193. Epub 2019 Jul 13.

Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China. Electronic address:

Purpose: To investigate the potential of ESWAN in differentiating borderline epithelial ovarian tumors (BEOTs) from malignant epithelial ovarian tumors (MEOTs).

Method: Thirty-four patients with 37 lesions were enrolled, including 14 BEOTs and 23 MEOTs. The magnitude, phase, R* and T* maps were analyzed by two observers. The regions of interest were drawn along the boundaries of tumors on the slice with maximal solid area, according to fat suppression TWI and TWI. The consistency among the three measurements taken by two observers was tested by intra-class correlation coefficients. Agreement of average values measured by two observers was evaluated by Bland-Altman plots. All the data of BEOTs and MEOTs were compared using the independent-sample t test. The receiver operating characteristic curve was used to evaluate the diagnostic performance.

Results: No statistical differences were observed in the magnitude and phase values between two tumor groups. The R* value of BEOTs was lower than that of MEOTs (P < 0.001), whereas the T* value of BEOTs was higher than that of MEOTs (P = 0.01). The area under the curve of R* values was 0.894 and the corresponding cutoff value was 7.50 Hz, with the sensitivity, specificity and accuracy of 85.7%, 82.6% and 86.5%, respectively. The AUC of T* values was 0.776 and the corresponding cutoff value was 143.73 ms with the sensitivity, specificity and accuracy of 71.4%, 82.6% and 78.4%, respectively.

Conclusions: R* and T* values can be used for quantificationally differentiating BEOTs from MEOTs and the R* has better diagnostic performance.
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http://dx.doi.org/10.1016/j.ejrad.2019.07.011DOI Listing
September 2019

Blood Oxygen Level-Dependent Imaging and Intravoxel Incoherent Motion MRI of Early Contrast-Induced Acute Kidney Injury in a Rabbit Model.

Kidney Blood Press Res 2019 28;44(4):496-512. Epub 2019 Jun 28.

Department of Radiology, Xiang'an Hospital of Xiamen University, Xiamen, China,

Background: To evaluate the application of blood oxygenation level-dependent (BOLD)imaging and intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) on assessing early contrast-induced acute kidney injury (CIAKI).

Materials: Sixty rabbits were randomly chosen to undergo iohexol (1.0, 2.5, and 5.0 [gI/kg], respectively; n = 15 for each group) or saline injection (n = 15). In each group, 6 rabbits underwent MRI at 24 h before injection and after injection of iohexol or saline (1 h and 1, 2, 3, and 4 days); meanwhile, out of the remaining 9 rabbits, 3 were chosen for MRI acquisition, and then they were killed at specific time points (1 h, 1 day, and 3 days, respectively).

Results: The strong attenuation of pure molecular diffusion (D), apparent diffusion coefficient (ADC), and perfusion fraction (f) was observed at 1 day, while pseudodiffusion coefficient (D*) showed a significant decrease at 1 h after iohexol injection. A distinct elevation of apparent transverse relaxation rate (R2*) reached the maximum levels on day 1, which was consistent with the expression of hypoxia-inducible factor-1α and vascular endothelial growth factor. ADC, D, and R2* correlated well with histopathological parameters and biochemical parameters.

Conclusion: BOLD combined with IVIM is effective to monitor renal pathophysiology associated with CIAKI.
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http://dx.doi.org/10.1159/000500052DOI Listing
January 2020

Radiomics-based classification of hepatocellular carcinoma and hepatic haemangioma on precontrast magnetic resonance images.

BMC Med Imaging 2019 03 11;19(1):23. Epub 2019 Mar 11.

GE Healthcare, MR Research, Beijing, China.

Background: To evaluate the feasibility of using radiomics with precontrast magnetic resonance imaging for classifying hepatocellular carcinoma (HCC) and hepatic haemangioma (HH).

Methods: This study enrolled 369 consecutive patients with 446 lesions (a total of 222 HCCs and 224 HHs). A training set was constituted by randomly selecting 80% of the samples and the remaining samples were used to test. On magnetic resonance (MR) images of HCC and HH obtained with in-phase, out-phase, T2-weighted imaging (T2WI), and diffusion-weighted imaging (DWI) sequences, we outlined the target lesions and extracted 1029 radiomics features, which were classified as first-, second-, higher-order statistics and shape features. Then, the variance threshold, select k best, and least absolute shrinkage and selection operator algorithms were explored for dimensionality reduction of the features. We used four classifiers (decision tree, random forest, K nearest neighbours, and logistic regression) to identify HCC and HH on the basis of radiomics features. Two abdominal radiologists also performed the conventional qualitative analysis for classification of HCC and HH. Diagnostic performances of radiomics and radiologists were evaluated by receiver operating characteristic (ROC) analysis.

Results: Valuable radiomics features for building a radiomics signature were extracted from in-phase (n = 22), out-phase (n = 24), T2WI (n = 34) and DWI (n = 24) sequences. In comparison, the logistic regression classifier showed better predictive ability by combining four sequences. In the training set, the area under the ROC curve (AUC) was 0.86 (sensitivity: 0.76; specificity: 0.78), and in the testing set, the AUC was 0.89 (sensitivity: 0.822; specificity: 0.714). The diagnostic performance for the optimal radiomics-based combined model was significantly higher than that for the less experienced radiologist (2-years experience) (AUC = 0.702, p < 0.05), and had no statistic difference with the experienced radiologist (10-years experience) (AUC = 0.908, p>0.05).

Conclusions: We developed and validated a radiomics signature as an adjunct tool to distinguish HCC and HH by combining in-phase, out-phase, T2W, and DW MR images, which outperformed the less experienced radiologist (2-years experience), and was nearly equal to the experienced radiologist (10-years experience).
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http://dx.doi.org/10.1186/s12880-019-0321-9DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6417028PMC
March 2019

MRI texture analysis based on 3D tumor measurement reflects the IDH1 mutations in gliomas - A preliminary study.

Eur J Radiol 2019 Mar 24;112:169-179. Epub 2019 Jan 24.

Department of Radiology, The First Affiliated Hospital of Dalian Medical University, Dalian 116000, China.

Objective: To evaluate the differentiation efficiency of texture analysis of T1WI, T2WI and contrasted-enhanced T1WI MRI sequences in gliomas with and without IDH1 mutation based on entire tumor region.

Materials And Methods: A total of 42 patients with histopathologically confirmed gliomas, including 21 patients carrying IDH1 mutation (IDH1 group) and 21 with wild-type IDH1 (IDH1 group) were included in this study. The preoperative MRI and clinical data were collected. The regions of interest (ROIs) covering the entire tumor and edema were manually delineated on axial slices using O.K. (Omni Kinetics, GE Healthcare, China) software; and the histogram and GLCM features based on T1WI, T2WI and contrasted-enhanced T1WI sequences were automatically generated.

Results: Based on contrasted-enhanced T1WI features, the inertia resulted as the best feature for diagnosis, with the AUC of 0.844. Furthermore, the AUC for gliomas prediction with IDH1 was 0.800 for cluster prominence. IDH1-mutation was differentiated on T2WI with the highest AUC of 0.848, which corresponded to GLCM Entropy. After modeling, the accuracy of the contrasted-enhanced T1WI, T1WI, and T2WI features model was 0.952, 0.857, and 0.738, respectively. The AUC of Joint Variable for predicting IDH1 was 0.984, while the AUC of Joint Variable for predicting the same mutation was 0.927. The diagnostic efficiency of Joint Variable was also desirable.

Conclusion: MRI texture analysis could be used as a new noninvasive method for identification of gliomas with IDH1 mutation. The present results show that the Joint Variable derived from conventional MR imaging histogram and GLCM features is suitable for precise detection of IDH1-mutated gliomas.
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http://dx.doi.org/10.1016/j.ejrad.2019.01.025DOI Listing
March 2019

Intravoxel Incoherent Motion Combined With Dynamic Contrast-Enhanced Perfusion MRI of Early Cervical Carcinoma: Correlations Between Multimodal Parameters and HIF-1α Expression.

J Magn Reson Imaging 2019 09 16;50(3):918-929. Epub 2019 Jan 16.

Department of MR Research, GE Healthcare, Beijing, China.

Background: The identification of hypoxia inducible factor (HIF-1α) expression is helpful for the quantitative assessment of tumor hypoxia. The application of multimodal imaging techniques may play a part in the assessment of HIF-1α expression of cervical carcinoma.

Purpose: To investigate the correlations between multiple imaging parameters and HIF-1α expression of early cervical carcinoma and to determine whether tumor hypoxia can be predicted using multisequence imaging parameters.

Study Type: Prospective observational.

Population: One hundred patients with early cervical carcinoma.

Field Strength/sequences: 3.0 T MRI including intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE) perfusion MRI sequences.

Assessment: DCE-MRI and IVIM DWI were performed for all patients. The imaging parameters included volume transfer constant (K ), rate constant (K ), extravascular extracellular volume fraction (V ), D, D*, and f.

Statistical Tests: The comparisons of imaging parameters between two independent groups were performed using the Mann-Whitney U-test. Multiple linear regression analysis was performed to determine the correlation between multiple imaging parameters and HIF-1α expression. The diagnostic ability of DCE-MRI, IVIM DWI, and the combination of two techniques for discriminating high-expression and low-expression groups were analyzed.

Results: The high-expression group had a lower K or K value than the low-expression group (P = 0.03; 0.02), while the high-expression group had a higher V value than the low-expression group (P = 0.03). The high-expression group had a higher D or f value than the low-expression group (P = 0.02; 0.02). K , K , D, V , and f values were independently correlated with HIF-1α expression. The sensitivity or accuracy of a combined method was higher than that of DCE-MRI or IVIM DWI individually (P = 0.03, 0.02; 0.04, 0.03).

Data Conclusion: The combination of DCE-MRI and IVIM DWI can improve the diagnostic ability of discriminating different HIF-1α expression levels for early cervical tumors.

Level Of Evidence: 1 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019;50:918-929.
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http://dx.doi.org/10.1002/jmri.26604DOI Listing
September 2019

Meningioma grading using conventional MRI histogram analysis based on 3D tumor measurement.

Eur J Radiol 2019 Jan 22;110:45-53. Epub 2018 Nov 22.

Department of Radiology, the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, China.

Purpose: To evaluate the application of conventional MRI histogram analysis based on the whole tumor measurement on assessing meningioma grading.

Materials And Methods: This retrospective study was approved by the institutional review board. A total amount of 90 patients with meningioma were enrolled and the preoperative MRI of them were analyzed. To be specific, the patient group were consisted of 45 patients with grade I, 38 with grade II, and 7 with grade III meningioma. Grade I meningioma is classified as low grade meningioma (LGM), whereas Grade II and III meningioma were combined and classified as high grade meningioma (HGM). ROIs were drawn along the edge of the tumor on each section of T1WI, T2WI, and contrasted T1WI. 3D ROI signal intensity histogram and all its parameters were obtained. Independent t-test and Kruskal-Wallis test were used for comparison between two groups. Univariate logistic regression analysis and Spearman's correlation analysis were used to screen for the parameters with high predictive efficiency, while multivariate logistic regression analysis was used to determine the optimal model for the classification of meningioma.

Results: There were significant differences observed between HGM and LGM groups regarding to histogram volume count, uniformity of three sequences, range of T1WI and T2WI, kurtosis, standard deviation, variance, max intensity of T2WI, skewness, mean deviation, minimum intensity, mean value, the 5 percentile, the 10 percentile, the 25 percentile, the 50 percentile, the 75 percentile, and the 90 percentile of contrasted T1WI. Volume count and uniformity were high predictive parameters in distinguishing HGM from LGM. Logistic regression model included contrasted T1WI histogram parameters (i.e. minimum intensity, volume count, skewness, uniformity, and the 75 percentile) showed the best diagnostic efficiency for meningioma grade, with a sensitivity and specificity of 83.9% and 77.4% (AUC = 0.834, cutoff value = 0.413), respectively. The optimal model was achieved with a sensitivity of 71.4% and a specificity of 78.6% in the test set (AUC = 0.791, cutoff value = 0.413).

Conclusions: Histogram analysis of conventional MRI based on 3D tumor measurement can be applied in the assessment of meningioma grading in clinical.
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http://dx.doi.org/10.1016/j.ejrad.2018.11.016DOI Listing
January 2019

Apparent Diffusion Coefficient Histogram Analysis for Assessing Tumor Staging and Detection of Lymph Node Metastasis in Epithelial Ovarian Cancer: Correlation with p53 and Ki-67 Expression.

Mol Imaging Biol 2019 08;21(4):731-739

Department of Radiology, Peking University Third Hospital, 49 North Garden Street, Haidian District, Beijing, 100191, China.

Purpose: To investigate the potential of apparent diffusion coefficient (ADC) histogram parameters in epithelial ovarian cancer (EOC) for distinguishing different tumor stages and determining lymph node status and correlations between ADC values and p53 and Ki-67 expression.

Procedures: Forty-nine EOC patients underwent preoperative magnetic resonance imaging. Staging and lymph node status were determined postoperatively. ADC values were measured using histogram analysis and compared between groups. Relationships between ADCs and Ki-67 and p53 expression were explored.

Results: DC parameters differed significantly between stage I vs II, I vs III, and I vs IV. The parameters were significantly lower in the lymph node-positive group than in the lymph node-negative group, were significantly negatively correlated with Ki-67 labeling index, and were all significantly lower in the mutation-type p53 group than in the wild-type p53 group.

Conclusions: ADC histogram analysis can help discriminate stage I from advanced-stage EOC and predict lymph node metastasis. ADC parameters were correlated with Ki-67 labeling index; the parameters may help indicate p53 expression.
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http://dx.doi.org/10.1007/s11307-018-1295-7DOI Listing
August 2019

Investigating the correlation of arterial spin labeling and dynamic contrast enhanced perfusion in primary tumor of nasopharyngeal carcinoma.

Eur J Radiol 2018 Nov 2;108:222-229. Epub 2018 Oct 2.

Department of Diagnostic Radiology, National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No17, panjiayuannanli, chaoyang district, Beijing, 100021, China. Electronic address:

Purpose: This prospective study aimed to investigate the correlation between two perfusion methods: arterial spin labeling (ASL) and dynamic contrast enhanced (DCE) technique in patients with nasopharyngeal carcinoma (NPC) and to optimize ASL protocol.

Materials And Methods: Forty-five newly diagnosed NPC patients underwent MR examinations with both 3D pseudo-continuous ASL (pCASL) and DCE-MRI sequences. Tumor blood flow (TBF) derived in pCASL with three post-labeling delay (PLD) times (i.e. 1.0 s, 1.5 s, and 2.0 s) and DCE derived parameters including MaxSlop, contrast enhancement ratio (CER), Initial area under the gadolinium curve (IAUGC), K, K and V were measured by two independent observers, and their correlation coefficients were investigated using Spearman test.

Results: Inter-observer reproducibility (ICC = 0.931-0.998) was observed to be excellent. Positive correlations between mean, maximum and minimum value of TBFs with different PLDs and DCE-MRI parameters (except V) were respectively observed (r = 0.308-0.688, P = 0.000-0.040).

Conclusion: pCASL may be an alternative method for DCE-MRI in assessing the perfusion level in NPC in the future.
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http://dx.doi.org/10.1016/j.ejrad.2018.09.034DOI Listing
November 2018

Effect of Repeated Injection of Iodixanol on Renal Function in Healthy Wistar Rats Using Functional MRI.

Biomed Res Int 2018 4;2018:7272485. Epub 2018 Apr 4.

Department of Radiology, First Affiliated Hospital of China Medical University, Shenyang 110001, China.

Purpose: To determine the optimal time interval of repeated intravenous injections of iodixanol in rat model and to identify the injury location and causes of renal damage .

Materials And Methods: Rats were randomly divided into Control group, Group 1 with one iodixanol injection, and Group 2 with two iodixanol injections. Group 2 was subdivided into 3 cohorts according to the interval between the first and second iodixanol injections as 1, 3, and 5 days, respectively. Blood oxygen level-dependent (BOLD) imaging and diffusion weighted imaging (DWI) were performed at 1 hour, 1 day, 3 days, 5 days, and 10 days after the application of solutions.

Results: Compared with Group 1 (7.2%), Group 2 produced a remarkable R2 increment at the inner stripe of the renal outer medulla by 15.37% ( = 0.012), 14.83% ( = 0.046), and 13.53% ( > 0.05), respectively, at 1 hour after repeated injection of iodixanol. The severity of BOLD MRI to detect renal hypoxia was consistent with the expression of HIF-1 and R2 was well correlated with HIF-1 expression ( = 0.704). The acute tubular injury was associated with urinary NGAL and increased significantly at 1 day.

Conclusions: Repetitive injection of iodixanol within a short time window can induce acute kidney injury, the impact of which on renal damage in rats disappears gradually 3-5 days after the injections.
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http://dx.doi.org/10.1155/2018/7272485DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5904815PMC
October 2018

Increased Iron Deposition on Brain Quantitative Susceptibility Mapping Correlates with Decreased Cognitive Function in Alzheimer's Disease.

ACS Chem Neurosci 2018 07 15;9(7):1849-1857. Epub 2018 May 15.

Department of Radiology , China-Japan Friendship Hospital , Beijing 100029 , China.

The excessive accumulation of iron in deep gray structures is an important pathological characteristic in patients with Alzheimer's disease (AD). Quantitative susceptibility mapping (QSM) is more specific than other imaging-based iron measurement modalities and allows noninvasive assessment of tissue magnetic susceptibility, which has been shown to correlate well with brain iron levels. This study aimed to investigate the correlations between the magnetic susceptibility values of deep gray matter nuclei and the cognitive functions assessed by mini-mental state examination (MMSE) and Montreal cognitive assessment (MoCA) in patients with mild and moderate AD. Thirty subjects with mild and moderate AD and 30 age- and sex-matched healthy controls were scanned with a 3.0 T magnetic resonance imaging (MRI) scanner. The magnetic susceptibilities of the regions of interest (ROIs), including caudate nucleus (Cd), putamen (Pt), globus pallidus (Gp), thalamus (Th), red nucleus (Rn), substantia nigra (Sn), and dentate nucleus (Dn), were quantified by QSM. We found that the susceptibility values of the bilateral Cd and Pt were significantly higher in AD patients than the controls ( P < 0.05). In contrast, bilateral Rn had significantly lower susceptibility values in AD than the controls. Regardless of gender and age, the increase of magnetic susceptibility in the left Cd was significantly correlated with the decrease of MMSE scores and MoCA scores ( P < 0.05). Our study indicated that magnetic susceptibility value of left Cd could be potentially used as a biomarker of disease severity in mild and moderate AD.
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http://dx.doi.org/10.1021/acschemneuro.8b00194DOI Listing
July 2018

Intravoxel incoherent motion MR imaging of early cervical carcinoma: correlation between imaging parameters and tumor-stroma ratio.

Eur Radiol 2018 May 8;28(5):1875-1883. Epub 2017 Dec 8.

Department of Medical Imaging, Cancer Hospital of China Medical University & Liaoning Cancer Hospital & Institute, No.44 Xiaoheyan Road, Dadong District, Shenyang, 110042, Liaoning Province, People's Republic of China.

Objectives: To investigate if intravoxel incoherent motion (IVIM) MR imaging can predict the tumour-stroma ratio (TSR) in patients with early cervical carcinoma.

Methods: Fifty-four patients with early cervical carcinoma were prospectively enrolled into this study. All patients underwent IVIM imaging and parameters including D, D* and f value were measured. The tumours were classified into stroma-rich and stroma-poor group according to TSR, and comparisons of IVIM parameters between two groups were performed. The relationships between IVIM parameters and TSR were analysed by using a multivariate multi-regression analysis.

Results: D and f values were significantly lower in stroma-poor tumours than in stroma-rich tumours (p=0.02, 0.04), while the difference in D* value between two groups didn't achieve statistical significance (p=0.09). The areas under ROC curves of D and f values in discriminating stroma-rich and stroma-poor tumours were 0.835 (95%CI=0.616~0.905) and 0.686 (95%CI=0.575~0.798). In multiple linear regression analysis, D value, pathologic type, histologic grade, tumour size and f value were independently correlated with TSR of cervical carcinoma.

Conclusions: D and f values are independently correlated with TSR of cervical carcinoma and have the potential for quantitative measurement of TSR.

Key Points: • TSR is a recognized independent prognostic factor in many solid tumours. • D and f values measured by IVIM MRI are independently correlated with TSR while D* is not. • IVIM offers the potential to predict TSR.
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http://dx.doi.org/10.1007/s00330-017-5183-3DOI Listing
May 2018

Comparison between types I and II epithelial ovarian cancer using histogram analysis of monoexponential, biexponential, and stretched-exponential diffusion models.

J Magn Reson Imaging 2017 12 5;46(6):1797-1809. Epub 2017 Apr 5.

Department of Radiology, Peking University Third Hospital, Haidian District, Beijing, P.R. China.

Purpose: To evaluate the utility of histogram analysis of monoexponential, biexponential, and stretched-exponential models to a dualistic model of epithelial ovarian cancer (EOC).

Materials And Methods: Fifty-two patients with histopathologically proven EOC underwent preoperative magnetic resonance imaging (MRI) (including diffusion-weighted imaging [DWI] with 11 b-values) using a 3.0T system and were divided into two groups: types I and II. Apparent diffusion coefficient (ADC), true diffusion coefficient (D), pseudodiffusion coefficient (D*), perfusion fraction (f), distributed diffusion coefficient (DDC), and intravoxel water diffusion heterogeneity (α) histograms were obtained based on solid components of the entire tumor. The following metrics of each histogram were compared between two types: 1) mean; 2) median; 3) 10th percentile and 90th percentile. Conventional MRI morphological features were also recorded.

Results: Significant morphological features for predicting EOC type were maximum diameter (P = 0.007), texture of lesion (P = 0.001), and peritoneal implants (P = 0.001). For ADC, D, f, DDC, and α, all metrics were significantly lower in type II than type I (P < 0.05). Mean, median, 10th, and 90th percentile of D* were not significantly different (P = 0.336, 0.154, 0.779, and 0.203, respectively). Most histogram metrics of ADC, D, and DDC had significantly higher area under the receiver operating characteristic curve values than those of f and α (P < 0.05) CONCLUSION: It is feasible to grade EOC by morphological features and three models with histogram analysis. ADC, D, and DDC have better performance than f and α; f and α may provide additional information.

Level Of Evidence: 4 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1797-1809.
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http://dx.doi.org/10.1002/jmri.25722DOI Listing
December 2017

Intravoxel incoherent motion diffusion weighted MRI of cervical cancer - Correlated with tumor differentiation and perfusion.

Magn Reson Imaging 2016 Oct 28;34(8):1050-6. Epub 2016 Apr 28.

Department of Radiology, Peking University Third Hospital, 49 North Garden Road, Haidian, Beijing 100191, China.

Objectives: To investigate the value of parameters derived from IVIM model in grading of uterine cervical cancer and the relationship between perfusion parameters derived from IVIM and that from DCE-MRI.

Methods: Parameters of DWI (ADC, D, f, D*) and semi-quantitative parameters of DCE-MRI (Slop, Maxslop, CER, Washout, AUC90) were assessed in 24 female with cervical cancers. Except for ROIs encompassed all of the area of tumors in axial plane (A_all), ROIs on tumor edge (A_peri) and tumor center (A_central) were drawn. All of the parameters were compared among three pathology grades. Perfusion parameters derived from IVIM were correlated with that from DCE-MRI.

Results: For G1, G2 and G3 tumors, on tumor edge ADC=(1.03±0.11), (1.05±0.10), (0.90±0.05)×10(-3)mm(2)/s, D=(0.80±0.11), (0.78±0.07), (0.69±0.06)×10(-3)mm(2)/s, and f=(0.19±0.03), (0.22±0.02), (0.24±0.03). The differences among groups were significant (P<0.05). On tumor center, ADC=(0.90±0.10), (0.85±0.03), (0.80±0.07)×10(-3)mm(2)/s with significant differences (P=0.027). The other parameter, D and f of tumor center, as well as D* of all tumor areas, were of no statistic significance. Most of the DCE-MRI parameters negatively correlated with tumor volume. Although the correlation between f and slop was statistic significant, R=0.277 meant a negligible correlation. f had week correlation with Maxslop, CER and AUC90 (R=0.361, 0.400 and 0.405; P<0.001). D* showed no statistic significant correlation with all of the DCE parameters.

Conclusion: IVIM model could possibly be used to evaluate tumor differentiation and perfusion, providing an alternative for DCE-MRI.
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http://dx.doi.org/10.1016/j.mri.2016.04.009DOI Listing
October 2016

DTI Study of Cerebral Normal-Appearing White Matter in Hereditary Neuropathy With Liability to Pressure Palsies (HNPP).

Medicine (Baltimore) 2015 Oct;94(43):e1909

From the Radiology Department of the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, PR China (WWW, SQW, WQ, MYW); Neurology Department of the First Affiliated Hospital of Dalian Medical University, Dalian, Liaoning, PR China (SCL, HL, LZH); Department of Radiology, Wayne State University, Detroit, Michigan, USA (HJN); and GE Healthcare China, Beijing, PR China (WB, XLZ).

The majority of previous studies on hereditary neuropathy with liability to pressure palsies (HNPP) were focused on peripheral nerves, whereas cerebral alterations in HNPP have been less attended to. In this work, Diffusion tensor imaging (DTI) was used to detect the changes in WM, especially in the normal-appearing white matter (NAWM) in HNPP patients for its sensitivity in probing the microstructure of WM, the sensitive metric was searched for probing cerebral alterations and the regional distribution of cerebral abnormalities was identified. Twelve HNPP patients and 12 age- and gender-matched healthy controls underwent the conventional MRI, DTI scan, and electrophysiological examination. The conventional MRI images were first analyzed to identify abnormal intense regions and the NAWM regions. NAWM refers to the white matter regions that do not include the lesions on conventional MRI. The apparent diffusion coefficient and fractional anisotropy (FA) values of the NAWM were then measured and compared between patient and control groups. The sensitivity and specificity of 3 methods and the cerebral regional distribution of MR signal abnormalities were further analyzed. Hyperintense foci were observed on T2 weighted image and fluid attenuated inversion recovery images in 6 patients. Compared to the controls, FA values of the patients were significantly lower in bilateral frontal, orbitofrontal, and temporal NAWMs; whereas the electrophysiological examination results of patients and controls exhibited no statistically significant difference. The sensitivity of FA value was higher than that of electrophysiological examination and conventional MRI. The majority of abnormal signals on conventional MRI images and abnormal FA values were located in the frontal and temporal lobes. The results of our study show cerebral WM changes in HNPP patients. FA value in DTI has been shown to be sensitive to the cerebral microstructural changes in HNPP. The frontal lobe is the predilection site that is most involved in HNPP.
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http://dx.doi.org/10.1097/MD.0000000000001909DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4985427PMC
October 2015

Effects of ambient PM2.5 on pathological injury, inflammation, oxidative stress, metabolic enzyme activity, and expression of c-fos and c-jun in lungs of rats.

Environ Sci Pollut Res Int 2015 Dec 26;22(24):20167-76. Epub 2015 Aug 26.

Institute of Environmental Science, Shanxi University, 92 Wucheng Road, Taiyuan, 030006, Shanxi Province, People's Republic of China.

Fine particulate matter (PM2.5) exposure is associated with morbidity and mortality induced by respiratory diseases and increases the lung cancer risk. However, the mechanisms therein involved are not yet fully clarified. In this study, the PM2.5 suspensions at different dosages (0.375, 1.5, 6.0, and 24.0 mg/kg body weight) were respectively given to rats by the intratracheal instillation. The results showed that PM2.5 exposure induced inflammatory cell infiltration and hyperemia in the lung tissues and increased the inflammatory cell numbers in bronchoalveolar lavage fluid. Furthermore, PM2.5 significantly elevated the levels of pro-inflammatory mediators including tumor necrosis factor-α (TNF-α), interleukin (IL)-6, IL-1β, and intercellular adhesion molecule 1 (ICAM-1) and the expression of c-fos and c-jun in rat lungs exposed to higher dose of PM2.5. These changes were accompanied by decreases of activities of superoxide dismutase and increases of levels of malondialdehyde, inducible nitric oxide synthase, nitric oxide, cytochrome P450s, and glutathione S-transferase. The results implicated that acute exposure to PM2.5 induced pathologically pulmonary changes, unchained inflammatory and oxidative stress processes, activated metabolic enzyme activity, and enhanced proto-oncogene expression, which might be one of the possible mechanisms by which PM2.5 pollution induces lung injury and may be the important determinants for the susceptibility to respiratory diseases.
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http://dx.doi.org/10.1007/s11356-015-5222-zDOI Listing
December 2015
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