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BACKGROUND: Hepatocellular carcinoma (HCC) is a serious health concern because of its high morbidity and mortality. The prognosis of HCC largely depends on the disease stage at diagnosis. Computed tomography (CT) image textural analysis is an image analysis technique that has emerged in recent years. OBJECTIVE: To probe the feasibility of a CT radiomic model for predicting early (stages 0, A) and intermediate (stage B) HCC using Barcelona Clinic Liver Cancer (BCLC) staging. METHODS: A total of 190 patients with stages 0, A, or B HCC according to CT-enhanced arterial and portal vein phase images were retrospectively assessed. The lesions were delineated manually to construct a region of interest (ROI) consisting of the entire tumor mass. Consequently, the textural profiles of the ROIs were extracted by specific software. Least absolute shrinkage and selection operator dimensionality reduction was used to screen the textural profiles and obtain the area under the receiver operating characteristic curve values. RESULTS: Within the test cohort, the area under the curve (AUC) values associated with arterial-phase images and BCLC stages 0, A, and B disease were 0.99, 0.98, and 0.99, respectively. The overall accuracy rate was 92.7%. The AUC values associated with portal vein phase images and BCLC stages 0, A, and B disease were 0.98, 0.95, and 0.99, respectively, with an overall accuracy of 90.9%. CONCLUSION: The CT radiomic model can be used to predict the BCLC stage of early-stage and intermediate-stage HCC.
Subject(s)
Carcinoma, Hepatocellular , Liver Neoplasms , Neoplasm Staging , Adult , Aged , Female , Humans , Male , Middle Aged , Area Under Curve , Carcinoma, Hepatocellular/diagnostic imaging , Carcinoma, Hepatocellular/pathology , Feasibility Studies , Image Processing, Computer-Assisted/methods , Liver Neoplasms/diagnostic imaging , Liver Neoplasms/pathology , Prognosis , Radiomics , Retrospective Studies , ROC Curve , Tomography, X-Ray Computed/methodsABSTRACT
@#In this study, the conjugate of eicosapentaenoic acid (EPA) and hyaluronic acid (HA) was synthesized and the anti-hepatoma activities in vitro were evaluated.The hyaluronic acid-eicosapentaenoic acid (HA-EPA)nanoparticle was synthesized by linking eicosapentaenoic acid with hyaluronic acid with cystamine.The structure of HA-EPA was characterized by nuclear magnetic resonance (1H NMR) and Fourier transform infrared spectroscopy (FT-IR).Laser particle sizer and Zeta potential analyzer were used to detect the size and potential of HA-EPA.MTT assay was used to detect the anti-proliferative effect of HA-EPA on HepG2, Huh-7 and LX-2 cells in vitro.The effects of HA-EPA nanoparticles on the proliferation and apoptosis of HepG2 cells in vitro were investigated by EdU staining and TUNEL staining. The apoptosis was further confirmed by flow cytometry.The effect of HA-EPA nanoparticles on the migration and invasion of HepG2 cells was demonstrated by transwell and invasion experiments.The results of 1H NMR showed that HA-EPA was successfully synthesized, and the grafting rate of EPA on HA was (40 ± 5) %. The structure of HA-EPA was further confirmed by FT-IR.The particle size was (162.5 ± 10.2) nm, and the potential was -(4.47 ± 0.31) mV.MTT results showed that, with the prolongation of drug treatment time, HA-EPA showed a better inhibitory effect on the activity of HepG2 and Huh-7 cells than EPA under the same EPA content.After treated for 48 hours, the toxicity of HA-EPA to LX-2 cells was less than that of EPA.The results of 24-hour proliferation, apoptosis, migration and invasion of HepG2 showed that, the graft of hyaluronic acid improved the ability of EPA to inhibit proliferation, promote apoptosis, migration and invasion of HepG2 cells (P < 0.001), indicating that grafting of HA can significantly enhance the inhibitory effect of EPA on liver cancer with some role in reducing toxicity.
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OBJECTIVE To prep are folate-targeted miR- 221 antisense oligonucleotide （anti-miR-221）delivery system ，and to preliminarily evaluate its in vitro anti-cancer effect on hepatocellular carcinoma. METHODS Folate-targeted anti-miR- 221 liposomes（FRL）were prepared by thin-film dispersion method ；the particle size ，Zeta potential and encapsulation efficiency were determined. The delivery efficiency of folate-targeted anionic liposome in human hepatoma HepG 2 cells was determined by in vitro cellular uptake experiment using calcein as the model drug. Flow cytometry was used to detect the effects of FRL on the apoptosis and cell cycle of HepG 2 cells. RESULTS The particle size of prepared FRL was （172.70±3.76）nm，Zeta potential was （－1.16± 0.15）mV and encapsulation efficiency was （83.53±1.85）％. In vitro cellular uptake experiments showed that folate-targeted anionic liposome successfully delivered calcein to HepG 2 cells，and the delivery efficiency in targeted group was higher than that of non-targeted liposome group （P＜0.01）. Apoptosis experiment results showed that the apoptotic rate of HepG 2 cells treated with FRL was significantly higher than that of non-targeted liposome （P＜0.01）. In cell cycle experiment ，FRL could shorten the S phase fraction of HepG 2 cells and induced arrest in the G 0/G1 and G 2/M phases. CONCLUSIONS FRL can encapsulate anti-miR-221 well and deliver it to hepatocellular carcinoma HepG 2 cells successfully ，and has a good in vitro anti-hepatoma effect in inducing apoptosis and cell cycle regulation.
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Objective:To investigate the value of ADC map-based radiomics model for identifying the ischemic penumbra (IP) in acute ischemic stroke (AIS).Methods:From January 2014 to October 2019, data of 241 patients with AIS involving the anterior cerebral circulation within 24 h after stroke onset in the First People′s Hospital of Nantong City was analyzed retrospectively. All patients received routine T 1WI, T 2WI, DWI and dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI). Considering the PWI-DWI mismatch model as the gold standard for determining IP, patients were divided into the PWI-DWI mismatch (84 cases) and PWI-DWI non-mismatch (157 cases) groups. The ROI of the low signal area and the surrounding area was drawn by two doctors at the maximum level of the lesions on the ADC maps. Then the images were imported into AK analysis software to extract the features. Firstly, the inter-class correlation coefficient was used to screen out the features with high consistency, then the maximum relevance and minimum redundancy (mRMR) and least absolute shrinkage and selection operator (Lasso) regression analysis were used to screen the features. The selected features were used to construct their own radiomics model. ROC curve was used to evaluate the performance of the models, and Delong test was used to compare the area under the curve (AUC) of the two models. Results:After screening, 12 features (LongRunLowGreyLevelEmphasis_angle135_offset7, LongRunLowGreyLevelEmphasis_AllDirection_offset7, GLCMEntropy_AllDirection_offset4_SD, GLCMEnergy_angle45_offset1, ColGE_W11B25_16, ColGE_W11B25_24, HaraEntropy, SurfaceVolumeRatio, Sphericity, Quantile0.025, uniformity and Percentile75) were used to construct the radiomics model based on the low signal area of the ADC map. The area under the ROC curve in the training set was 0.900, and the sensitivity, specificity and accuracy were 84.5%, 81.4% and 83.4%, respectively. The area under the ROC curve in the validation set was 0.870, and the sensitivity, specificity and accuracy were 80.9%, 84.0% and 81.9%, respectively. Eleven features(RunLengthNonuniformity_AllDirection_offset1_SD, ShortRunLowGreyLevelEmphasis_angle45_offset1, HighGreyLevelRunEmphasis_AllDirection_offset1_SD, ShortRunLowGreyLevelEmphasis_AllDirection_offset7, HaralickCorrelation_AllDirection_offset4_SD, ClusterShade_angle45_offset7, InverseDifferenceMoment_AllDirection_offset7_SD, ColGE_W3B20_0, sumAverage, SurfaceVolumeRatio and VolumeMM) were used to construct the radiomics model based on the surrounding area of ADC map. The area under ROC curve in training set was 0.820, the sensitivity, specificity and accuracy were 80.5%, 80.2% and 80.4%, respectively; the area under ROC curve in validation set was 0.800, the sensitivity, specificity and accuracy were 78.7%, 80.0% and 79.2%, respectively. The AUC of the radiomics model based on the low signal area of the ADC map was larger than that based on the surrounding area of the ADC map (training set: Z=3.017, P=0.003; validation set: Z=0.604, P=0.002). Conclusion:The radiomics model based on ADC map has a good diagnostic efficacyin identifying the IP.
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@#The aim of this study was to study the synthesis of two folate conjugates and their application in the preparation of folate targeted liposome, and to investigate their targeting effect in hepatocellular carcinoma HepG2 cell line in vitro. In this study, Folate-PEG-Cholesteryl hemisuccinate(Folate-PEG2000-CHEMS and Folate-PEG4000-CHEMS)were synthesized by linking folate and cholesterol succinate with two kinds of PEG materials. Structures of Folate-PEG2000-CHEMS and Folate-PEG4000-CHEMS were characterized by 1H NMR and ultra-high resolution mass spectrometry. Calcein was selected as the model drug, and calcein liposomes FA-PEG2000-L and FA-PEG4000-L were prepared by film dispersion method using Folate-PEG2000-CHEMS and Folate-PEG4000-CHEMS, respectively. The particle size and Zeta potential of FA-PEG2000-L and FA-PEG4000-L were measured by laser particle size analyzer. The drug delivery effect of FA-PEG2000-L and FA-PEG4000-L was evaluated by cellular uptake experiment in HepG2 cell line in vitro. Flow cytometry and laser confocal scanning microscope were used to determine fluorescence in HepG2 cells in vitro. The results showed that the average particle size of calcein liposome was (205.8 ± 10.2) nm, and the Zeta potential of calcein liposome was -(1.19 ± 0.31) mV.There was no significant difference in particle size and Zeta potential between FA-PEG2000-L and FA-PEG4000-L. The fluorescence intensity of FA-PEG4000-L liposome group was about 3.6 and 3.1 times higher than that of non-targeted liposome group and FA-PEG2000-L liposome group, with statistically significant difference (P < 0.01). The drug delivery efficiency of FA-PEG4000-L group in HepG2 cells was higher than that in FA-PEG2000-L and non-targeted groups, and the results indicated that Folate-PEG4000-CHEMS can promote the uptake of liposome by HepG2 cells in vitro. All in all, Folate-PEG4000-CHEMS could be applied in the preparation of folate targeted liposome, which could promote the uptake of liposome by HepG2 cells.
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Objective:To investigate the value of CT radiomics mode in differential diagnosis of benign and malignant thyroid nodules.Methods:The clinical and imaging data of 179 patients with thyroid nodules confirmed by pathology from May 2017 to August 2018 were retrospectively analyzed in the Affiliated Huaian First People′s Hospital of Nanjing Medical University. Among the patients, 89 cases were benign nodules and 90 cases were malignant nodules. All patients underwent unenhanced and enhanced CT scan before operation. The stratified random sampling method was used to divide patients into a training group (143 cases) and a testing group (36 cases) according to a ratio of 8∶2. The A.K software was used to extract 378 imaging omics features based on preoperative CT images, and then Spearman correlation analysis and least absolute shrinkage and selection operator regression analysis were used for feature selection and model construction. The receiver operating characteristic (ROC) curve was used to verify the model in the training group and the testing group, and the efficacy of imaging omics features to predict benign and malignant thyroid nodules was evaluated.Results:After feature screening, 16 radiomics features were used to construct an identification model between benign and malignant thyroid nodules. In the training group, the area under the ROC curve (AUC) was 0.92 [95% confidence interval (CI): 0.88-0.97], the sensitivity and specificity were 88.7%, 82.0%, and the diagnostic accuracy of the model was 91.1%. In the testing group, AUC was 0.90 (95 %CI: 0.81-0.98), sensitivity and specificity were 88.5%, 84.6%, and the diagnostic accuracy of the model was 88.2%. Conclusion:The CT radiomics mode has a good diagnostic performance in the identification of benign and malignant thyroid nodules.
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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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Stroke at the acute stage is a major cause of disability in adults, and is associated with dysfunction of brain networks. However, the mechanisms underlying changes in brain connectivity in stroke are far from fully elucidated. In the present study, we investigated brain metabolism and metabolic connectivity in a rat ischemic stroke model of middle cerebral artery occlusion (MCAO) at the acute stage using F-fluorodeoxyglucose positron emission tomography. Voxel-wise analysis showed decreased metabolism mainly in the ipsilesional hemisphere, and increased metabolism mainly in the contralesional cerebellum. We used further metabolic connectivity analysis to explore the brain metabolic network in MCAO. Compared to sham controls, rats with MCAO showed most significantly reduced nodal and local efficiency in the ipsilesional striatum. In addition, the MCAO group showed decreased metabolic central connection of the ipsilesional striatum with the ipsilesional cerebellum, ipsilesional hippocampus, and bilateral hypothalamus. Taken together, the present study demonstrated abnormal metabolic connectivity in rats at the acute stage of ischemic stroke, which might provide insight into clinical research.
Subject(s)
Animals , Male , Acute Disease , Brain , Diagnostic Imaging , Metabolism , Brain Mapping , Disease Models, Animal , Fluorodeoxyglucose F18 , Glucose , Metabolism , Infarction, Middle Cerebral Artery , Diagnostic Imaging , Metabolism , Neural Pathways , Diagnostic Imaging , Metabolism , Positron-Emission Tomography , Radiopharmaceuticals , Random Allocation , Rats, Sprague-DawleyABSTRACT
Positron emission tomography (PET) imaging of functional metabolism has been widely used to investigate functional recovery and to evaluate therapeutic efficacy after stroke. The voxel intensity of a PET image is the most important indicator of cellular activity, but is affected by other factors such as the basal metabolic ratio of each subject. In order to locate dysfunctional regions accurately, intensity normalization by a scale factor is a prerequisite in the data analysis, for which the global mean value is most widely used. However, this is unsuitable for stroke studies. Alternatively, a specified scale factor calculated from a reference region is also used, comprising neither hyper- nor hypo-metabolic voxels. But there is no such recognized reference region for stroke studies. Therefore, we proposed a totally data-driven automatic method for unbiased scale factor generation. This factor was generated iteratively until the residual deviation of two adjacent scale factors was reduced by < 5%. Moreover, both simulated and real stroke data were used for evaluation, and these suggested that our proposed unbiased scale factor has better sensitivity and accuracy for stroke studies.
Subject(s)
Animals , Female , Male , Rats , Computer Simulation , Disease Models, Animal , Fluorodeoxyglucose F18 , Image Processing, Computer-Assisted , Methods , Infarction, Middle Cerebral Artery , Diagnostic Imaging , Positron-Emission Tomography , Methods , Rats, Sprague-Dawley , Stroke , Diagnostic ImagingABSTRACT
Objective: To assess the feasibility of coronary lfow reserve (CFR) detection by SPECT myocardial perfusion imaging using a self developed software with preliminary clinical veriifcation. Methods: CFR calculation software was developed according to Mat lab guide. A total of 16 patients were enrolled including 13 male and 3 female at the mean age of (58±11) years . CAG conifrmed that 25 coronary branches were with stenosis>50% and 23 branches were without stenosis. 2-day ATP/rest99mTc-sestamibi dynamic SPECT myocardial perfusion imaging was conducted to detect CFR. First transit counts were used to sketch the interested pulmonary artery segments and to obtain the arterial input curve of contrast agent as total PAC reached to heart. Reconstructed short-axis images were divided into 3 sections to sketch interested territories (ROI) and to obtain RMC at each territory. Estimated CFR was expressed by the ratio of MBF=RMC/PAC followed by calculating the ratio of MFR=MBFstress/MBFrest. Results: The difference between simulated value and true value could be ignored which conifrmed that our program may accurately measure CFR. The reproducibility by different operators (r=0.986) and the same operator (r=0.983) was good. CFR value in non-stenosis branches were higher than stenosis branches (1.28 ± 0.19) vs (1.10 ± 0.27),P=0.008 and CFR value in stenosis branches was negatively related to stenosis degree (r=-0.5,P=0.02). Conclusion: Our self developed software is reliable for CFR detection by SPECT myocardial perfusion imaging; preliminary study showed good application prospect in clinical practice.
