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Objective:To explore the predictive value of deep learning (DL)-based coronary artery calcification score (CACS) for obstructive coronary artery disease (CAD) and noncalcified plaque/mixed plaque in type 2 diabetes mellitus (T2DM).Methods:Forty hundred and twenty-four consecutive T2DM patients who accepted CACS scan and coronary CT angiography (CCTA) from December 2012 to December 2019 were included retrospectively, with clinical risk factors and plaque features collected. Plaque composition was classified as calcified, non-calcified or mixed plaque. Obstructive CAD was defined as maximum diameter stenosis≥50%. CACS was calculated with a fully automated method based on DL. Univariate and multivariate logistic regressions were applied to select statistically significant factors and the odds ratios(ORs) were measured. Receiver operating characteristic (ROC) curve was evaluated to assess the predictive performance.Results:Increased CACS was associated with a significantly higher odds of obstructive CAD in CCTA (adjusted ORs were 2.22, 6.18 and 16.98 for CACS=1-99, 100-299, 300-999 vs. CACS=0, and P values were 0.009,<0.001,<0.001 respectively). The area under ROC curve (AUC) of CACS to predict obstructive CAD was 0.764. Compared with 0, increased CACS was associated with increased risk of non-calcified/mixed plaque (adjusted ORs were 2.75, 4.76, 5.29 for CACS=1-99, 100-299, 300-999 respectively and P values were 0.001,<0.001,<0.001 respectively). The AUC of CACS to predict non-calcified/mixed plaque was 0.688. It took 1.17 min to perform automated measurement of CACS based on DL in total, which was significantly less than manual measurement of 1.73 min ( P<0.001). Conclusion:DL-based CACS can predict obstructive CAD and non-calcified plaque/mixed plaque in T2DM, which is economical and efficient, and has important value for clinical diagnosis and treatment.
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Objective:To investigate the predictive value of thrombus enhancement (TE) and thrombus permeability in cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.Methods:The clinical and image data of 93 patients with acute middle cerebral artery occlusion who were admitted to the First Affiliated Hospital of Soochow University within 12 hours after onset from January 2020 to July 2022 were retrospectively analyzed. According to the TOAST criteria, the patients were divided into the cardioembolism (CE) group (43 cases) and the large artery atherosclerosis (LAA) group (50 cases). All patients received noncontrast CT and CT angiography, and then thrombus permeability [thrombus attenuation increase (TAI), void fraction (ε)] and TE were assessed. Independent sample t-test, Mann-Whitney U test and χ2 test were used in univariable analysis between two groups. Multivariable logistic regression analysis was used to explore the independent influencing factors for cardioembolic stroke and establish a logistic model. The receiver operating characteristic (ROC) curve and the area under the curve (AUC) were used to evaluate the predictive value of TAI, ε, TE and the logistic model in cardioembolic thrombus with acute middle cerebral artery occlusion. Results:There were statistically significant differences in sex, atrial fibrillation, hypertension, diabetes mellitus, smoking, baseline National Institutes of health stroke scale (NIHSS), TAI, ε and TE between the CE group and the LAA group ( P<0.05). Binary logistics regression analysis showed that TAI (OR=1.300, 95%CI 1.147-1.473, P<0.001), hypertension (OR=0.116, 95%CI 0.025-0.535, P=0.006) and baseline NIHSS (OR=1.165, 95%CI 1.040-1.304, P=0.008) were independent influencing factors for cardioembolic thrombus. The ROC curve indicated that the logistic model predicted cardioembolic thrombus with the highest AUC of 0.907 (95%CI 0.848-0.966). TE predicted cardioembolic thrombus with the highest sensitivity of 90.7%. Conclusion:TE and thrombus permeability have application value for predicting cardioembolic thrombus with acute middle cerebral artery occlusion based on CT.
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Lung cancer is the most lethal malignancy around the world and non-small cell lung cancer (NSCLC) accounts for 80% of all cases. Most of the NSCLC patients has "driver gene mutations" and targeted therapy achieved a relatively good efficacy, but some patients progressed or relapsed after treatment. Previous studies demonstrated that immune checkpoint inhibitor could improve the prognosis of advanced-stage NSCLC and prolong the survival time. However, the efficacy of immune therapy varies in NSCLC patients with different immune and molecular features. The efficacy of immune therapy was controversial in NSCLC patients with driver gene mutation. The present review will summarize the immune characteristics of NSCLC patients with driver mutation and the directions of immunotherapy for patients with driver mutation. .
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Humans , Carcinoma, Non-Small-Cell Lung/therapy , Immunotherapy , Lung Neoplasms/therapy , Molecular Targeted Therapy , MutationABSTRACT
Objective:To investigate the difference in the peri-coronary fat attenuation index (FAI) between using coronary calcium score (CCS) images and coronary CT angiography (CCTA) images, and to explore the feasibility and befitting threshold of FAI measured on CCS images.Methods:The clinical and imaging data of patients who underwent CCTA examination from August 2019 to August 2020 were retrospectively analyzed in the First Affiliated Hospital of Soochow University. According to the inclusion and exclusion criteria, there were 122 cases in non-calcified plaque group (144 coronary arteries) and 97 cases in none-plaque group (186 coronary arteries). The coronary arteries were delineated both on CCS and CCTA images with Perivascular Fat Analysis Tool; the regions of interest of peri-coronary adipose tissue were generated automatically after setting the threshold of fat tissue. Then the FAI value was calculated. The thresholds were set in four levels (-190--30, -185--25, -180--20 and -175--15 HU) for CCS images and one level (-190--30 HU) for CCTA images. The intra-class correlation coefficient (ICC) was used to evaluate the consistency of the measurements of FAI values on CCS and CCTA images between the two physicians. Paired t test was used to compare the differences of FAI values between CCS and CCTA images, and Pearson correlation coefficient was used to evaluate the correlation between CCS-FAI and CCTA-FAI. Results:(1) FAI values measured on CCS and CCTA images by 2 physicians showed good consistency; (2) At the threshold of -185--25 HU, there was no significant difference in FAI values between the CCS and CCTA images for non-calcified plaque group [(-84.15±5.99)HU vs. (-83.83±5.98)HU, t=0.79, P=0.429], as well as for the none-plaque group [(-83.41±5.75)HU vs.(-83.84±6.25)HU, t=-1.08, P=0.280]; (3) There were significant differences on FAI values between the CCS images and CCTA images at the threshold of -190--30、-180--20 and -175--15 HU (all P<0.05); (4) There were moderate correlations on FAI values between the CCS images and CCTA images under different thresholds both in non-calcified plaque group and none-plaque group. Conclusion:It is feasible to measure FAI on CCS images, and the befitting threshold is -185--25 HU.
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Objective:To explore the value of different machine learning models based on Gd-EOB-DTPA enhanced MRI hepatobiliary phase radiomics features in preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC).Methods:The data of 132 patients with HCC confirmed by pathology in the First Affiliated Hospital of Soochow University from January 2015 to May 2020 were retrospectively analyzed, including 72 cases of positive MVI and 60 cases of negative MVI. According to the proportion of 7∶3, the cases were randomly divided into training set and validation set. The radiomics features of hepatobiliary phase images for HCC were extracted by PyRadiomics software. The clinical and radiomics features of the training set were screened by the least absolute shrinkage and selection operator (LASSO) regression with 5 fold cross-validation, and then the optimal feature subset was obtained. Six machine learning algorithms, including decision tree, extreme gradient boosting, random forest, support vector machine (SVM), generalized linear model (GLM) and neural network, were used to build the prediction models, and the ROC curves were used to evaluate the prediction ability of the models. DeLong test was used to compare the differences of area under the curve (AUC) for 6 machine learning algorithms.Results:Totally 14 features selected by LASSO regression were obtained to form the optimal feature subset, including 2 clinical features (maximum tumor diameter and alpha-fetoprotein) and 12 radiomics features. The AUCs of decision tree, extreme gradient boosting, random forest, SVM, GLM and neural network based on the optimal feature subset were 0.969, 1.000, 1.000, 0.991, 0.966, 1.000 in the training set and 0.781, 0.890, 0.920, 0.806, 0.684, 0.703 in the validation set, respectively. There were significant differences in the AUCs between extreme gradient boosting and GLM or neural network ( Z=2.857, 3.220, P=0.004, 0.001). The differences in AUCs between random forest and SVM, GLM, or neural network were significant ( Z=2.371, 3.190, 3.967, P=0.018, 0.001,<0.001). The difference in AUCs between SVM and GLM was statistically significant ( Z=2.621 , P=0.009). There were no significant differences in the AUCs among the other machine learning models ( P>0.05). Conclusion:Machine learning models based on Gd-EOB-DTPA enhanced MRI hepatobiliary phase radiomics features can be used to preoperatively predict MVI of HCC, particularly the extreme gradient boosting and random forest models have high prediction efficiency.
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Objective:To develop a radiomics nomogram model based on CT to distinguish arteriovenous malformation(AVM) intracerebral hemorrhage from primary intracerebral hemorrhage.Methods:One hundred and thirty-five patients with cerebral hemorrhage confirmed by operation in the First Affiliated Hospital of Soochow University were analyzed retrospectively, including 52 patients with AVM cerebral hemorrhage and 83 patients with primary cerebral hemorrhage. Radiomics features were extracted from baseline CT, radiomics score (Radscore) was calculated and radiomic labels were constructed. Multiple logistic regression analysis was used for clinical features combined with CT signs to establish a clinical model. And then the nomogram model was generated according to the Radscore and the clinical model. The ROC curve and decision curve analysis (DCA) were used to evaluate the discrimination performance of the model.Results:Six features were selected and used to establish radiomic labels. The clinical model consisted of age (OR: 4.739, 95%CI 1.382-16.250) and hematoma location (OR: 0.111, 95%CI 0.032-0.385), while the nomogram model consisted of age, hematoma location and Radscore. In the training group, there was a significant difference between the nomogram model [area under curve (AUC) 0.912] and the clinical model (AUC 0.816), the radiomics model (AUC 0.857) ( Z=2.776, 2.034, P=0.006, 0.042, respectively); While in the validation group, there was no significant difference between the nomogram model (AUC 0.919) and the clinical model (AUC 0.788), the radiomics model (AUC 0.810) ( Z=1.796, 1.788, P=0.073, 0.074, respectively). DCA analysis showed that the clinical value of the nomogram model was superior to the clinical model and radiomic model. Conclusion:The radiomics nomogram can effectively distinguish AVM-related cerebral hemorrhage from primary cerebral hemorrhage, which is helpful for clinical decision-making.
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Objective:To investigate the predictive value of measurement parameters of left atrial appendage by coronary CTA (CCTA) for the risk of cardiogenic stroke (CS) in patients with nonvalvular atrial fibrillation (NVAF).Methods:The clinical and examination data of 179 patients with NVAF who underwent CCTA examination were retrospectively analyzed. The selected patients were grouped according to the outbreak of acute ischemic stroke and TIA within 2 years after CCTA examination. Patients who met the criteria for CS were selected as cases (87 patients), and those with neither stroke nor TIA as controls (92 patients). The diameter and area of left atrial appendage (LAA) orifice, the LAA depth, and the LAA volume were measured by using dedicated software. The parameter was corrected using the body surface area (BSA) to obtain the correction index of corresponding parameter. The independent samples t test, Mann-Whitney U test, and Chi-square test were used to compare the differences in various indicators between the two groups. Binary logistic regression was used to analyze the impacts of body mass index (BMI), hyperlipidemia, the duration years of atrial fibrillation, left atrial appendage area index (LAAOA Index), and the left atrial appendage emptying fraction (LAAEF) on the risk of CS. The ROC curve was used to evaluate the predictive value of LAAOA Index and LAAEF for the onset of CS. Results:The correction index of the left atrial appendage orifice maximum and minimum diameter, the left atrial appendage orifice area, and the maximum & minimum left atrial appendage volume and the LAAEF in the case group were (1.80±0.21) cm/m 2, (1.19±0.17) cm/m 2, (3.20±0.71) cm 2/m 2, (7.91±1.92) ml/m 2, (5.03±1.40) ml/m 2, (36.20±10.54)%, and those value in the control group were (1.64±0.24) cm/m 2, (1.06±0.19) cm/m 2, (2.65±0.64) cm 2/m 2, (6.61±1.68) ml/m 2, (3.67±1.28) ml/m 2, (45.25±10.07)%, the differences were statistically significant ( t= 4.783, 4.647, 5.481, 4.826, 6.823, and -5.875, all P<0.001). Binary logistic regression analysis showed that the increase in LAAOA Index ( P= 0.005) and the decrease in LAAEF ( P<0.001) were independent risk factors for CS in NVAF patients. The area under the ROC curve (AUC) of LAAOA Index was 0.712 (95%CI 0.639-0.777), and the best diagnostic cut-off was 3.16 cm 2/m 2; the AUC of LAAEF was 0.734 (95%CI 0.663-0.797), the cut-off was 38.71%; the AUC of LAAOA Index-LAAEF was 0.786 (95%CI 0.718-0.843). The difference of AUC value between LAAOA Index and LAAEF was not statistically significant ( Z= 0.448, P= 0.654). The difference of AUC between the LAAOA Index-LAAEF and LAAOA Index ( Z=2.667, P=0.008) and between the LAAOA Index-LAAEF and LAAEF ( Z=2.061, P=0.039) were statistically significant. Conclusions:CCTA can provide a one-stop and relatively accurate evaluation of the size and function of the left atrial appendage by post-processing the coronary vascular scan data. Left atrial appendage measurement parameters from CCTA can be used as a supplement to the CHA2DS2-VASc score, and provide quantitative indicators for the risk assessment of CS in patients with NVAF.
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Objective:To explore the value of gadolinium-ethoxybenzyl- diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI nomogram model for preoperative prediction of Ki-67 expression in hepatocellular carcinoma (HCC).Methods:Data of 85 patients of HCC confirmed by postoperative pathology, who underwent preoperative Gd-EOB-DTPA enhanced MRI between September 2016 and August 2019 in the First Affiliated Hospital of Soochow University were retrospectively evaluated. According to postoperative immunohistochemistry Ki-67 index, the 85 patients were divided into Ki-67 low expression group(Ki-67 index ≤10%, n=20) and Ki-67 high expression group (Ki-67 index >10%, n=65). Clinical data (hepatitis, cirrhosis, etc.), qualitative imaging parameters (tumor margin, capsule, etc.) were compared by χ 2 test and quantitative parameters [lesion-to-normal parenchyma ratio-arterial phase (LNR-AP), lesion-to-normal parenchyma ratio-portal phase (LNR-PP), lesion-to-normal parenchyma ratio-equilibrium phase (LNR-EP) and lesion-to-normal parenchyma ratio-hepatobiliary phase (LNR-HBP)] were compared by independent sample t test. The above statistically significant parameters were included in multivariate logistic regression to identify the independent predictors of Ki-67 high expression and then the nomogram model for predicting Ki-67 expression of HCC was established. Results:alpha-fetoprotein (AFP) tumor margin, arterial rim enhancement between the Ki-67 low expression group and the Ki-67 high expression group had significant differences (χ 2 were 8.196, 10.538 and 4.717, respectively, P<0.05). LNR-AP, LNR-PP, LNR-EP and LNR-HBP between the two groups had significant differences ( t were 2.929, 2.773, 2.890 and 3.437, respectively, P<0.05).The result of multivariate logistic regression revealed that AFP≥20 μg/L, non-smooth tumor margin and low LNR-HBP were the independent predictors of Ki-67 high expression (odds ratio were 4.090, 3.509 and 0.042, respectively, P<0.05).The Gd-EOB-DTPA enhanced MRI nomogram model for predicting Ki-67 expression of HCC was established successfully. The Area under the receiver operating characteristic curve of the nomogram was 0.837 and the corrected predictive curve fitted the ideal curve, which suggested the model had a good predictive efficiency. Conclusion:Gd-EOB-DTPA enhanced MRI nomogram model has great value in preoperative prediction of Ki-67 expression of HCC, which provided a personalized prediction method for Ki-67 expression in patient with HCC.
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Objective:To explore the value of spectral CT radiomics quantitative features on differentiating lung cancer nodule from inflammatory nodule.Methods:The spectral CT imaging data of 96 lung cancer nodules and 45 inflammatory nodules from the First Affiliated Hospital of Soochow University were analyzed retrospectively. According to a ratio of two to one, patients were randomly assigned to the training group and validation group, including 64 lung cancer nodules and 30 inflammatory nodules in the training group, 32 lung cancer nodules and 15 inflammatory nodules in the validation group. MaZda software was used for radiomic feature extraction from the 70 keV monochromatic images in arterial phase and venous phase for lung cancer nodules and inflammatory nodules in the training group. Fisher coefficients (Fisher), classification error probability combined average correlation coefficients (POE+ACC) and mutual information (MI) were used to select 10 optimal features for the optimal feature subsets. The optimal feature subsets were analyzed by using linear discriminant analysis (LDA) and nonlinear discriminant analysis (NDA) to calculate the area under the receiver operating characteristic (ROC) curve (AUC), accuracy, sensitivity, specificity, precise and F1 score in differentiating lung cancer nodule from inflammatory nodule. The prediction model was established using the optimal feature subsets in the training group with artificial neural network (ANN). Then the established prediction model was used to differentiate lung cancer nodule from inflammatory nodule in the validation group. Delong test was used to compare the differences in the AUC of different optimal feature subsets.Results:In arterial phase, the optimal feature subset obtained from MI-NDA had the highest AUC of 0.888 [95% confidence interval (CI) 0.806-0.943], accuracy rate of 88.3%, sensitivity of 87.5% and specificity of 90.0%, on the differential diagnosis of lung cancer nodule and inflammatory nodule in the training group. There was no significant difference in AUC between MI-NDA and Fisher-NDA or (POE+ACC)-NDA method ( Z=1.941, P=0.052; Z=1.683, P=0.092). In venous phase, the optimal feature subset obtained from (POE+ACC)-NDA had the highest AUC of 0.846 (95%CI 0.757-0.912), accuracy rate of 87.2%, sensitivity of 92.2% and specificity of 76.7%, on the differential diagnosis of lung cancer nodule and inflammatory nodule in the training group. There was no significant difference in AUC between(POE+ACC)-NDA and MI-NDA method ( Z=1.354, P=0.18), but significant difference between (POE+ACC)-NDA and Fisher-NDA method ( Z=2.423, P=0.015). In the validation group and training group, the optimal feature subset selected by MI-NDA method had the highest AUC of 0.888(95%CI 0.806-0.943) and 0.871(95%CI 0.741-0.951). Conclusion:Spectral CT radiomics quantitative features have great value on the differential diagnosis of lung cancer nodule and inflammatory nodule.
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Objective:To evaluate the application of multiparametric MRI (mpMRI)-transrectal ultrasound (TRUS) fusion guided biopsy in the diagnosis of clinical significant prostate cancer (PCa).Methods:A prospective analysis was performed in 168 patients with suspected PCa from September 2015 to June 2017 in the First Affiliated Hospital of Soochow University. Suspicious areas on mpMRl were defined and graded using prostate imaging reporting and data system version 2 (PI-RADS V2) score. All the patients had the TRUS-guided systematic biopsy, 108 patients with PI-RAD V2 scores ≥ 3 had additional MRI-TRUS targeted biopsies. Taking pathologic results as golden standard, the detection rates were compared between the 2 methods using χ 2 test. Results:Initially, all of the 168 patients underwent TRUS biopsy. PCa was detected in 86 (101 niduses) of 168 patients (51.19%, 86/168), 82 (91 niduses) (48.81%, 82/168) were not prostate cancer. Seventy eight (46.43%, 78/168) cases of PCa were detected by TRUS biopsy, and 63 (58.33%, 63/168) cases of PCa were detected by MRI-TRUS fusion guided biopsy, the difference was statistically significant between TRUS biopsy and MRI-TRUS fusion guided biopsy (χ 2=3.73, P=0.035). The 168 patients were biopsied with a total of 2 300 cores, including TRUS biopsy 2 016 cores and MRI-TRUS fusion targeted biopsy 284 cores. Additionally, the detection rate for per cores for MRI-TRUS fusion targeted biopsy (51.76%, 147/284) was significantly higher than that for TRUS biopsy cores (19.64%, 396/2 016) (χ 2=142.38, P<0.05). Among patients with a positive biopsy for PCa, the biopsy cores for conventional TRUS biopsy was 1 032 comparing to 214 cores for MRI-TRUS biopsy. The suspicious MRI-TRUS fusion targeted biopsy (68.69%, 147/214) detected more PCa compared with TRUS biopsy (38.37%, 396/1 032) (χ 2=66.27, P<0.05). Among patients with a positive biopsy for PCa, MRI-TRUS fusion targeted biopsy [69.74% (106/152)] detected more significant cancer cores than TRUS biopsy [54.50% (351/644) ] (χ 2=11.67, P<0.05). Conclusion:MRI-TRUS fusion biopsy combined with PI-RADS V2 increases positive rate markedly and improves the detection rate of clinical significant PCa.
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Objective:To investigate the value of pericoronary adipose tissue histogram parameters based on coronary CT angiography (CTA) images for the differentiation of acute coronary syndrome and stable coronary artery disease.Methods:The clinical data and CTA images of 93 patients with coronary CTA examination in Suzhou Kowloon Hospital from 2013 to 2018 were analyzed retrospectively. There were 39 patients with acute coronary syndrome (acute coronary syndrome group) and 54 patients with stable coronary artery disease (stable coronary artery disease group). A region of interest (ROI) was drawn around the stenosis of the coronary arteries, with CT attenuation ranging from-190 to -30 HU to exclude non-adipose tissue. The CT attenuation of ROI excluding non-adipose were measured and histogram analysis was performed. The obtained parameters included the mean value, median value and the 5th, 10th, 45th, 55th, 70th and 95th percentiles. The differences in histogram parameters between the two groups were compared, and then the value of each parameter in differentiating acute coronary syndrome and stable coronary artery disease was evaluated based on receiver operating characteristic (ROC) analysis. The stepwise regression of multivariate logistic regression analysis was used to identify the useful features and establish the final prediction model. The ROC curve of the final model was calculated and its value was analyzed.Results:The mean, median and the 5th, 10th, 45th, 55th,70th and 95th percentile differences between the acute coronary syndrome group and the stable coronary artery disease group were statistically significant (all P<0.05). The ROC curve for the median and the 95th percentile had the same area under curve (AUC) of 0.73. The sensitivity, specificity and AUC of the diagnostic model established by multiple logistic regression were 82.1%, 89.1% and 0.90 respectively. Conclusion:CT attenuation histogram of pericoronary adipose tissue is of high value in differentiating acute coronary syndrome from stable coronary artery disease.
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Non-small cell lung cancer (NSCLC) is the most common pathological type of lung cancer. In recent years, immunotherapy has developed rapidly. Immune checkpoint inhibitors, especially programmed death-1 (PD-1)/programmed death-ligand 1 (PD-L1) inhibitors have made a breakthrough in the treatment of NSCLC and changed the treatment pattern for NSCLC. Immunological checkpoint inhibitors targeting PD-1/PD-L1 are beneficial to patients, both in the first-line and second-line treatment of advanced NSCLC, in the adjuvant treatment of locally-advanced NSCLC, and in the neoadjuvant therapy of early NSCLC, which show an important role in the comprehensive treatment of NSCLC. This article reviews the clinical research progress of immunological checkpoint inhibitors targeting PD-1/PD-L1 in NSCLC. .
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Objective@#To observe distribution and morphological characteristics of symptomatic atherosclerotic plaques in the middle cerebral artery (MCA) using high-resolution magnetic resonance imaging (HR-MRI), and to investigate HR-MRI characteristics of atherosclerotic plaques in the MCA in patients with acute cerebral infarction.@*Methods@#A total of 57 symptomatic patients with MCA atherosclerotic plaques recruited in the Affiliated Hospital of Yangzhou University from January 2014 to January 2016 were imaged with diffusion weighted imaging (DWI), three dimensional time of flight magnetic resonance angiography (3D TOF-MRA) and HR-MRI scanning for plaque on a 3.0 T MRI scanner. According to the results of DWI examination, the 57 patients were divided into transient ischemic attack (TIA) group (27 cases) and acute cerebral infarction group (30 cases). The distribution of the narrowest lumen plaque was evaluated by cross-section division into four equal arcs (superior, inferior, ventral, dorsal arcs). For quantitative analysis, lumen area (LAMLN), vessel area (VAMLN) at maximal lumen narrow (MLN) and LAreference, VAreference were measured, then wall area (WA), plaque area (PA), percentage of plaque burden, rate of lumen stenosis and remodeling index (RI) were calculated. The data of each group were compared and analyzed.@*Results@#The location and morphological analysis of the 57 patients with symptomatic MCA atherosclerotic plaques revealed that plaques were located in the ventral wall in 19 cases (33.3%), the upper wall in 15 cases (26.3%), the dorsal wall in 10 cases (17.5%), and the lower wall in 13 cases (22.8%). For the location variations in ventral wall, upper wall, dorsal wall and lower wall, the TIA group was shown as six cases (22.2%), five cases (18.5%), seven cases (25.9%) and nine cases (33.3%), and the acute cerebral infarction group was shown as 13 cases (43.3%), 10 cases (33.3%), three cases (10.0%) and four cases (13.3%), respectively. There was no statistically significant difference in the distribution of each side wall between the two groups (P>0.05). VAreference, LAreference, VAMLN and RI of the TIA group and the acute cerebral infarction group were (19.89±1.34) mm2, (15.19±2.04) mm2, (20.78±1.78) mm2, 1.09±0.11 and (19.70±1.34) mm2, (14.60±2.33) mm2, (21.53±2.34) mm2, 1.10±0.11, respectively. There was no statistically significant difference between the two groups (P>0.05). The remodeling patterns of both groups were mainly positive remodeling, with a total of 44 cases (77.2%). In the TIA group and the acute cerebral infarction group, the WAMLN, PA, stenosis rate and plaque load percentages were (8.85±1.92) mm2, (4.00±3.00) mm2, 20.92%±9.18%, 19.05%±14.93% and (11.10±1.88) mm2, (6.00±2.25) mm2, 28.56%±8.67%, 27.30%±7.69%, respectively. The differences between the two groups were statistically significant (t=-4.466, t=-2.865, t=-3.231, t=-2.580, P<0.01). There were eight patients (29.6%) with unsmooth plaque surface in the TIA group and 19 patients (63.3%) in the acute cerebral infarction group. The differences between the two groups were statistically significant (χ2=6.475, P<0.05). LAMLN in the TIA group and the acute cerebral infarction group was (11.93±1.59) mm2 and (10.43±2.08) mm2 respectively, and the difference between the two groups was statistically significant (t=3.033, P<0.01).@*Conclusions@#Symptomatic atherosclerotic plaques in MCA in the acute cerebral infarction group have higher plaque load, thicker vascular wall at the maximum stenosis and more unsmooth plaque surface. This indicates the characteristics of high-risk plaques to a certain extent.
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Objective@#To evaluate the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters in diagnosing prostate cancer(PCa) in transition zone (TZ) and stratifying pathologic Gleason grade of prostate cancer.@*Methods@#A total of 55 patients who were undergoing preoperative muti-parameters MRI of T2WI, DWI, IVIM and DKI model for the exploration of prostate cancer (January 2015 to June 2017) with pathologically confirmed by MRI-transrectal ultrasound (TRUS) targeted fusion biopsy were retrospectively included. Parameters were postprocessed by IVIM models including quantitation of perfusion fraction (f), diffusivity (D) and pseudo-diffusivity (D*) and DKI models including the mean diffusivity (MD), mean kurtosis (MK) and fractional anisotropy (FA) by outlining the 3D VOI. Independent sample t-test was used to compare the differences in lesion parameters between prostate cancer and BPH, low-risk (BPH+Gleason score 6 points) and medium-high-risk lesions (Gleason score ≥7 points). Correlation between ADC values, IVIM and DKI parameters and Gleason scores were assessed with Spearman analysis. Receiver operating characteristic curve analysis was used to evaluate the efficacy of various parameters in the differential diagnosis of prostate cancer and BPH with low-risk or high-risk.@*Results@#27 (36 focus) cases of PCa and 28 (40 focus) cases of benign prostatic hyperplasia (BPH) in PZ were included, meanwhile, the cases of GS ≥7 and and BPH+(GS=6) were 33,43,respectively. There were significant differences in ADC, D, MD, MK, and FA between patients in PCa-BHP group and high-low risk group in TZ (P<0.05), D* and f had no significant differences (P>0.05). ADC and MD showed relatively higher negativity correlations (r were -0.585 and -0.489, P<0.05) with GS of PCa in TZ. ADC exhibited a higher area under the curve (AUC 0.864) compared with D with area under the curve (AUC 0.853), however, the difference is not significant (P>0.05). Of model DKI in diagnose of PCa and BPH, the highest classification accuracy was MD(AUC 0.796). The AUC derived from multiple model parameters in different combination of ADC+D value, ADC+MD value, and ADC+MD+D value were 0.892, 0.884, and 0.897, respectively. ADC and D of IVIM model showed a significance difference between GS ≥7 and BPH+(GS=6) with a higher AUC of 0.826 and 0.743. The AUC was 0.851 of the combination of mean ADC and D, 0.846 of combination of mean ADC and MD, the AUC (0.856) of the combination of ADC, D and MD significant higher than any two combined parameters (P>0.05).@*Conclusions@#IVIM and DKI models may help to discriminate prostate cancer from BPH, and predict mid-higher GS PCa in TZ. But there is no significant advantage compared with ADC values. It is feasible to stratify the pathological grade of prostate cancer in TZ by mean ADC and MD.
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Objective To evaluate the diagnostic value of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters in diagnosing prostate cancer(PCa) in transition zone (TZ) and stratifying pathologic Gleason grade of prostate cancer. Methods A total of 55 patients who were undergoing preoperative muti?parameters MRI of T2WI, DWI, IVIM and DKI model for the exploration of prostate cancer (January 2015 to June 2017) with pathologically confirmed by MRI?transrectal ultrasound (TRUS) targeted fusion biopsy were retrospectively included. Parameters were postprocessed by IVIM models including quantitation of perfusion fraction (f), diffusivity (D) and pseudo?diffusivity (D*) and DKI models including the mean diffusivity (MD), mean kurtosis (MK) and fractional anisotropy (FA) by outlining the 3D VOI. Independent sample t?test was used to compare the differences in lesion parameters between prostate cancer and BPH, low?risk (BPH+Gleason score 6 points) and medium?high?risk lesions (Gleason score ≥7 points). Correlation between ADC values, IVIM and DKI parameters and Gleason scores were assessed with Spearman analysis.Receiver operating characteristic curve analysis was used to evaluate the efficacy of various parameters in the differential diagnosis of prostate cancer and BPH with low?risk or high?risk. Results 27 (36 focus) cases of PCa and 28 (40 focus) cases of benign prostatic hyperplasia(BPH) in PZ were included, meanwhile, the cases of GS≥7 and and BPH+(GS=6) were 33,43,respectively. There were significant differences in ADC, D, MD, MK, and FA between patients in PCa?BHP group and high?low risk group in TZ (P<0.05), D*and f had no significant differences (P>0.05). ADC and MD showed relatively higher negativity correlations (r were－0.585 and－0.489, P<0.05) with GS of PCa in TZ. ADC exhibited a higher area under the curve (AUC 0.864) compared with D with area under the curve (AUC 0.853), however, the difference is not significant (P>0.05). Of model DKI in diagnose of PCa and BPH, the highest classification accuracy was MD(AUC 0.796). The AUC derived from multiple model parameters in different combination of ADC+D value, ADC+MD value, and ADC+MD+D value were 0.892, 0.884, and 0.897, respectively. ADC and D of IVIM model showed a significance difference between GS≥7 and BPH+(GS=6) with a higher AUC of 0.826 and 0.743. The AUC was 0.851 of the combination of mean ADC and D, 0.846 of combination of mean ADC and MD, the AUC (0.856) of the combination of ADC, D and MD significant higher than any two combined parameters (P>0.05). Conclusions IVIM and DKI models may help to discriminate prostate cancer from BPH, and predict mid?higher GS PCa in TZ. But there is no significant advantage compared with ADC values. It is feasible to stratify the pathological grade of prostate cancer in TZ by mean ADC and MD.
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Objective To retrospectively analyze and compare the clinical application value of core-needle biopsy (CNB) histology and fine needle aspiration (FNA) cytology in diagnosing malignant thyroid nodules. Methods A total of 134 patients with 137 thyroid nodules (93 malignant nodules and 44 benign nodules) were included in this study. Under ultrasound guidance, successive use of 22 G fine needle and18 G core-needle to puncture each nodule was performed for sampling of thyroid nodule. Surgical findings and pathological manifestations were compared with clinical follow-up results. The success rate of sampling and the diagnostic accuracy, sensitivity as well as specificity for malignant thyroid nodules were compared among FNA, CNB, and CNB/FNA. Results The success rate of puncture sampling with FNA, CNB and FNA/CNB for thyroid nodules was 89.1％, 97.8％ and 100％ respectively. For malignant thyroid nodules, the diagnostic accuracy of FNA, CNB and FNA/CNB was 79.6％, 91.9％ and 96.4％ respectively, the sensitivity was 81.7％, 94.6％ and 97.8％ respectively, and the specificity was 75.0％, 86.4％ and 93.2％ respectively. The success rate of puncture sampling by using CNB or FNA/CNB was significantly higher than that by using FNA (P<0.01), moreover, the diagnostic accuracy and sensitivity for malignant thyroid nodules by using CNB or FNA/CNB was also remarkably higher than those by using FNA (P<0.01) . Conclusion In making diagnosis of malignant thyroid nodules, CNB is accurate, safe and reliable. CNB can be used as a complementary or alternative technique to FNA in clinical practice.
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Objective To observe distribution and morphological characteristics of symptomatic atherosclerotic plaques in the middle cerebral artery (MCA) using high?resolution magnetic resonance imaging (HR?MRI), and to investigate HR?MRI characteristics of atherosclerotic plaques in the MCA in patients with acute cerebral infarction. Methods A total of 57 symptomatic patients with MCA atherosclerotic plaques recruited in the Affiliated Hospital of Yangzhou University from January 2014 to January 2016 were imaged with diffusion weighted imaging (DWI), three dimensional time of flight magnetic resonance angiography (3D TOF?MRA) and HR?MRI scanning for plaque on a 3.0 T MRI scanner. According to the results of DWI examination, the 57 patients were divided into transient ischemic attack (TIA) group (27 cases) and acute cerebral infarction group (30 cases). The distribution of the narrowest lumen plaque was evaluated by cross?section division into four equal arcs (superior, inferior, ventral, dorsal arcs). For quantitative analysis, lumen area (LAMLN), vessel area (VAMLN) at maximal lumen narrow (MLN) and LAreference, VAreference were measured, then wall area (WA), plaque area (PA), percentage of plaque burden, rate of lumen stenosis and remodeling index (RI) were calculated. The data of each group were compared and analyzed. Results The location and morphological analysis of the 57 patients with symptomatic MCA atherosclerotic plaques revealed that plaques were located in the ventral wall in 19 cases (33.3%), the upper wall in 15 cases (26.3%), the dorsal wall in 10 cases (17.5%), and the lower wall in 13 cases (22.8%). For the location variations in ventral wall, upper wall, dorsal wall and lower wall, the TIA group was shown as six cases (22.2%), five cases (18.5%), seven cases (25.9%) and nine cases (33.3%), and the acute cerebral infarction group was shown as 13 cases (43.3%), 10 cases (33.3%), three cases (10.0%) and four cases (13.3%), respectively. There was no statistically significant difference in the distribution of each side wall between the two groups (P>0.05). VAreference, LAreference, VAMLN and RI of the TIA group and the acute cerebral infarction group were (19.89 ± 1.34) mm2, (15.19 ± 2.04) mm2, (20.78 ± 1.78) mm2, 1.09 ± 0.11 and (19.70 ± 1.34) mm2, (14.60 ± 2.33) mm2, (21.53 ± 2.34) mm2, 1.10 ± 0.11, respectively. There was no statistically significant difference between the two groups (P>0.05). The remodeling patterns of both groups were mainly positive remodeling, with a total of 44 cases (77.2%). In the TIA group and the acute cerebral infarction group, the WAMLN, PA, stenosis rate and plaque load percentages were (8.85±1.92) mm2, (4.00±3.00) mm2, 20.92%± 9.18%, 19.05% ± 14.93% and (11.10 ± 1.88) mm2, (6.00 ± 2.25) mm2, 28.56% ± 8.67%, 27.30% ± 7.69%, respectively. The differences between the two groups were statistically significant (t=-4.466, t=-2.865, t=-3.231, t=-2.580, P<0.01). There were eight patients (29.6%) with unsmooth plaque surface in the TIA group and 19 patients (63.3%) in the acute cerebral infarction group. The differences between the two groups were statistically significant (χ2=6.475, P<0.05). LAMLN in the TIA group and the acute cerebral infarction group was (11.93±1.59) mm2 and (10.43±2.08) mm2 respectively, and the difference between the two groups was statistically significant (t=3.033, P<0.01). Conclusions Symptomatic atherosclerotic plaques in MCA in the acute cerebral infarction group have higher plaque load, thicker vascular wall at the maximum stenosis and more unsmooth plaque surface. This indicates the characteristics of high?risk plaques to a certain extent.
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Objective@#To assess the enhancement characteristics of plaques in patients with intracranial atherosclerotic stenosis using three-dimensional high-resolution magnetic resonance imaging (3D HR MRI), and to analyze the correlation between the enhancement characteristics of plaques and the time from onset of stroke symptoms to MRI examination.@*Methods@#The enhancement characteristics of plaques were retrospectively analyzed in 61 patients with cerebral infarction who were scanned in MRI room of the Affiliated Hospital of Yangzhou University from January 2014 to January 2016. According to the elapsed time between symptom onset and MR examination, 61 patients were classified into early stage group (<4 weeks, n=26), middle stage group (4-12 weeks, n=20) and late stage group (>12 weeks, n=15). All cases underwent three-dimensional sampling perfection with application optimized contrast using different angle evolutions (3D-SPACE) T1WI and enhanced 3D-SPACE T1WI sequence scans, as well as routine head MRI examinations. The signal intensities of plaques before and after enhancement scanning were compared on the 3D-SPACE T1WI sequence. The degrees of plaque enhancement were qualitatively analyzed, and the enhancement rates of plaques were quantitatively calculated. The correlation between the enhancement characteristics of plaques and time of symptom onset of stroke was analyzed.@*Results@#Sixty-one intracranial atherosclerotic plaques on the 3D HR MRI showed eccentric thickening or annular thickening of the vessel wall, and slightly higher signals on the T1WI. They showed different degrees of enhancement or no enhancement after enhancement scans. The characteristics of plaque enhancement in 61 patients with cerebral infarction were analyzed. The results showed that 26 plaques in the early stage group were obviously enhanced for 21 cases (80.8%), mildly enhanced for 4 cases (15.4%), no enhancement for 1 case (3.8%), and the enhancement rate was 80.49%±18.64%. Twenty plaques in the middle stage group were obviously enhanced for 2 cases (10.0%), mildly enhanced for 14 cases (70.0%), no enhancement for 4 cases (20.0%), and the enhancement rate was 52.09%±18.17%. Fifteen plaques in the late stage group were mildly enhanced for 2 cases (2/15), no enhancement for 13 cases (13/15), and the enhancement rate was 12.16%±10.44%. There were statistically significant differences in the degrees of plaque enhancement and plaque enhancement rates among the three groups (χ2=22.834, P<0.01; F=78.403, P<0.01). Further analysis showed that there was a statistically significant difference in the degree of enhancement and enhancement rate of plaques between the early stage group and the middle stage group (χ2=-4.177, P<0.01; t=5.179, P<0.01), and there was a statistically significant difference between the middle stage group and the late stage group (χ2=-2.484, P<0.05; t′=8.189, P<0.01), and the difference between the early stage group and the late stage group was also statistically significant (χ2=-3.796, P<0.01; t′=15.044, P<0.01). There was a significant negative correlation between the time from onset of stroke symptoms to MRI examination and the enhancement rate of plaques (r=-0.903, P<0.01).@*Conclusions@#Enhanced HR MRI scanning can clearly show the enhancement of intracranial atherosclerotic plaques. With the prolongation of the onset time interval, the enhancement of intracranial atherosclerotic plaques gradually weakens, which can assess the vulnerability of plaques and has important guiding significance for secondary prevention of ischemic stroke.
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Objective To explore the diagnostic value of MR elastography and diffusion?weighted imaging in patients with liver fibrosis in the context of chronic hepatitis B. Methods Twenty?four patients with chronic hepatitis B, whose course of liver disease was more than 6 months and hepatitis B surface antigen was positive, were prospectively enrolled in the First Affiliated Hospital of Soochow University from July to December 2017. All of the patients underwent abdominal transient elastography (TE), routine MRI, magnetic resonance elastography (MRE) and DWI examination, TE and MRI were performed within one week. TE liver stiffness was measured, the MRE liver stiffness and ADC value were measured on MR imagings. All patients were divided into three groups: mild and non fibrosis (F0 to 1), significant fibrosis(F2 to 3) and cirrhosis (F4), according to the recommended standard of FibroTouch. Correlation between TE liver stiffness, MRE liver stiffness and ADC values were identified by using Spearman correlation test. The difference of the MRE liver stiffness and ADC value among the three groups was tested using independent sample t test. The overall predictive ability of MRE and DWI in assessment of liver fibrosis and cirrhosis was analyzed by constructing ROC curve. Results TE and MRI were successfully performed in all subjects, and the image quality was good. The MRE liver stiffness in mild and non fibrosis, significant fibrosis and cirrhosis was (2.32±0.31),(3.43±1.05),(4.77±0.68) kPa with statistically significant difference(F=61.690, P<0.01). The ADC values in three groups were (1.31 ± 0.14)×10-3, (1.23 ± 0.15)×10-3,(1.22±0.12)×10-3mm2/s without significant difference(F=1.074,P=0.360). The TE liver stiffness in three groups was (5.61±1.05),(9.56±0.57),(17.25±3.55)kPa, respectively, there was significant correlation between the MRE liver stiffness and the TE liver stiffness(t=0.858, P<0.01), but no significant correlation between the TE liver stiffness and the ADC value was found (r=-0.326,P=0.120). The area under ROC of MRE liver stiffness in diagnosing liver fibrosis grade (≥F2 and F4) was 0.96 and 1.00 respectively, while the AUC of ADC value was less than 0.70, which were 0.67 and 0.62 respectively. Conclusion MRE is a non?invasive promising tool for assessing liver fibrosis with chronic hepatitis B, while DWI has limited role.
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To explore the effect of down-regulation of growth arrest and DNA damage inducible protein 45β (GADD45β) on the PC9 lung adenocarcinoma cells. Methods: GADD45β gene siRNA sequence was designed and synthesized, which was transfected into PC9 lung adenocarcinoma cells through lentivirus transfection. Quantitative real-time PCR (qRT-PCR) and Western blot are used to examine the mRNA and protein levels of GADD45β in PC9 cells before and after the transfection. Annexin V-allophycocyanin (APC) double-staining flow cytometry was used to detect the apoptosis level after the transfection. The intracellular DNA content after transfection was detected by flow cytometry. The percentage of the cells at each period of cell cycle was calculated, and the effect of RNA interference on the cell growth were analyzed. The effects of RNA interference on the tumor-formation ability of cells were tested by counting the number of clones. MTT assay was used to test the half maximal inhibitory concentration (IC50) of PC9 cells for gefitinib. Results: The 5'-AAATCCACTTCACGCTCAT-3' sequence was identified as the effective sequence for GADD45β gene RNA interference. The mRNA and protein expression levels of GADD45β were markedly decreased (both P<0.05) at 48 h after transfection of GADD45β-siRNA, which resulted in the increased apoptosis rate (P<0.05), decreased tumor clone number (P<0.05) and increased percentage of PC9 cell at the S stage and G2/M stage (P<0.05). The IC50 for gefitinib was decreased obviously (P<0.05). Conclusion: Down-regulation of GADD45β can reduce the colony-forming ability of PC9 cells, promote the cell apoptosis, and enhance the sensitivity of PC9 cells to gefitinib.