Objective:Analyze the clinicopatholocical and imaging characteristics of hepatic epithelioid hemangioendothelioma (HEHE) and the related factors of survival prognosis.Methods:Clinical data of 32 patients diagnosed with HEHE at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023 retrospectively analyzed, including 11 males and 21 females, aged (46.8±3.6) years. The clinical manifestations, pathological findings, CT and MRI features of the patients were analyzed and the living conditions of the patients were followed up. Kaplan-Meier method was used for survival analysis, and log-rank test was used for survival rate comparison.Results:Among the 32 patients, 17 (53.1%) had no obvious symptoms, 10 (31.3%) had abdominal pain, 6 (18.8%) had abdominal distension, and 4 (12.5%) had lost weight. Under the microscope, HEHE was composed of mucous matrix and epithelioid endothelial cells, with dense surrounding cells and relatively sparse center. Small blood vessels can be seen invading the junction with normal liver tissue. The positive rates of endothelial marker CD34 in immunohistochemically staining was 100%(32/32), the positive rates of CD31 were 100% (32/32). The positive rates of erythroblast transformation specific related gene were 100% (28/28), and the positive rates of Friend leukemia virus integration protein 1 (22/22) were 100%. CT and MRI scan showed that the lesion were mainly multiple nodules and in diffuse formality. In arterial phase, the lesion showed slight homogeneous or ring-like enhancement, while in portal phase, the lesion showed progressive enhancement. Some lesions may exhibit more specific "lollipop sign" ( n=9) and "target ring sign" ( n=15). The median overall survival time of the 32 patients was 47 months, and the cumulative 1-, 3-, and 5-year survival were 100%, 95.0% and 72.7%, respectively. The cumulative survival rate of patients with "target ring sign" ( n=15), extrahepatic organ involvement or metastasis ( n=8) and Ki-67 positive rate >5% ( n=10) were lower than those without the above characteristics (all P<0.05). Conclusion:The clinical manifestations of HEHE were not typical, and the tumor was rich in mucus matrix and epithelioid endothelial cells, expressing endothelial markers. CT and MRI scan mainly showed multiple nodules or diffused lesion, and the "lollipop sign" and "target ring sign" were helpful for diagnosis. HEHE patients with Ki-67 positivity rate >5%, "target ring sign", and extrahepatic organs involvement or metastasis had a poor prognosis.

Objective To investigate the effect of drug-eluting bead DACE(DEB-TACE)combined with systemic treatment for hepatocellular carcinoma(HCC)in different locations.Methods A total of 204 HCC patients who underwent DEB-TACE combined with systemic therapy(targeted and immunotherapy)were retrospectively collected.According to the anatomical location of HCC,86 cases with lesions located at the main trunk of portal vein(PV)or within 1 cm of the first PV branch were classified into central type group,while 118 cases with lesions located at the other areas were classified as peripheral type group.Follow-up was regularly performed after DEB-TACE until August,2024.The objective response rate(ORR)and disease control rate(DCR)at 1,3,6 and 12 months after DEB-TACE,also patients'progression-free survival(PFS)and overall survival(OS)were compared between groups.Results All patients were followed up for a median of 32.6 months,during which 164 cases died.Significant differences of ORR at 1 and 3 months after DEB-TACE(77.91％[67/86]vs.89.83％[106/118],34.88％[30/86]vs.54.24％[64/118])and DCR at 3 and 6 months after DEB-TACE(51.16％[44/86]vs.66.95％[79/118],34.88％[30/86]vs.50.00％[59/118])were found between groups(all P＜0.05).Patients'PFS(30.18[9.12,48.54]months)and OS(37.36[17.79,56.68])in peripheral type group were better than those in central type group(20.11[11.35,28.87]months and 23.24[3.11,43.47]months,x2=3.971,4.162,P=0.048,0.041).Conclusion The effect of DEB-TACE combined with systemic treatment for peripheral type HCC was better than for central type HCC.

Objective To investigate the effect of drug-eluting bead DACE(DEB-TACE)combined with systemic treatment for hepatocellular carcinoma(HCC)in different locations.Methods A total of 204 HCC patients who underwent DEB-TACE combined with systemic therapy(targeted and immunotherapy)were retrospectively collected.According to the anatomical location of HCC,86 cases with lesions located at the main trunk of portal vein(PV)or within 1 cm of the first PV branch were classified into central type group,while 118 cases with lesions located at the other areas were classified as peripheral type group.Follow-up was regularly performed after DEB-TACE until August,2024.The objective response rate(ORR)and disease control rate(DCR)at 1,3,6 and 12 months after DEB-TACE,also patients'progression-free survival(PFS)and overall survival(OS)were compared between groups.Results All patients were followed up for a median of 32.6 months,during which 164 cases died.Significant differences of ORR at 1 and 3 months after DEB-TACE(77.91％[67/86]vs.89.83％[106/118],34.88％[30/86]vs.54.24％[64/118])and DCR at 3 and 6 months after DEB-TACE(51.16％[44/86]vs.66.95％[79/118],34.88％[30/86]vs.50.00％[59/118])were found between groups(all P＜0.05).Patients'PFS(30.18[9.12,48.54]months)and OS(37.36[17.79,56.68])in peripheral type group were better than those in central type group(20.11[11.35,28.87]months and 23.24[3.11,43.47]months,x2=3.971,4.162,P=0.048,0.041).Conclusion The effect of DEB-TACE combined with systemic treatment for peripheral type HCC was better than for central type HCC.

Objective:Analyze the clinicopatholocical and imaging characteristics of hepatic epithelioid hemangioendothelioma (HEHE) and the related factors of survival prognosis.Methods:Clinical data of 32 patients diagnosed with HEHE at the First Affiliated Hospital of Zhengzhou University from January 2013 to December 2023 retrospectively analyzed, including 11 males and 21 females, aged (46.8±3.6) years. The clinical manifestations, pathological findings, CT and MRI features of the patients were analyzed and the living conditions of the patients were followed up. Kaplan-Meier method was used for survival analysis, and log-rank test was used for survival rate comparison.Results:Among the 32 patients, 17 (53.1%) had no obvious symptoms, 10 (31.3%) had abdominal pain, 6 (18.8%) had abdominal distension, and 4 (12.5%) had lost weight. Under the microscope, HEHE was composed of mucous matrix and epithelioid endothelial cells, with dense surrounding cells and relatively sparse center. Small blood vessels can be seen invading the junction with normal liver tissue. The positive rates of endothelial marker CD34 in immunohistochemically staining was 100%(32/32), the positive rates of CD31 were 100% (32/32). The positive rates of erythroblast transformation specific related gene were 100% (28/28), and the positive rates of Friend leukemia virus integration protein 1 (22/22) were 100%. CT and MRI scan showed that the lesion were mainly multiple nodules and in diffuse formality. In arterial phase, the lesion showed slight homogeneous or ring-like enhancement, while in portal phase, the lesion showed progressive enhancement. Some lesions may exhibit more specific "lollipop sign" ( n=9) and "target ring sign" ( n=15). The median overall survival time of the 32 patients was 47 months, and the cumulative 1-, 3-, and 5-year survival were 100%, 95.0% and 72.7%, respectively. The cumulative survival rate of patients with "target ring sign" ( n=15), extrahepatic organ involvement or metastasis ( n=8) and Ki-67 positive rate >5% ( n=10) were lower than those without the above characteristics (all P<0.05). Conclusion:The clinical manifestations of HEHE were not typical, and the tumor was rich in mucus matrix and epithelioid endothelial cells, expressing endothelial markers. CT and MRI scan mainly showed multiple nodules or diffused lesion, and the "lollipop sign" and "target ring sign" were helpful for diagnosis. HEHE patients with Ki-67 positivity rate >5%, "target ring sign", and extrahepatic organs involvement or metastasis had a poor prognosis.

Objective:To establish and validate a clinical and CT radiomics combined model for predicting lymph node metastasis (LNM) risk in patients with hilar cholangiocarcinoma (HCCA).Methods:This was a case-control study. Data from 158 pathologically confirmed HCCA patients between January 2016 and January 2022 at the First Affiliated Hospital of Zhengzhou University were retrospectively analyzed. Using stratified random sampling, the patients were randomly divided into a training set ( n=95) and an internal validation set ( n=63) at a 6∶4 ratio. According to postoperative pathology, 31 LNM-positive cases and 64 LNM-negative cases were in the training set, and 22 LNM-positive cases and 41 LNM-negative cases were in the internal validation set. A cohort of 50 HCCA patients was retrospectively collected from West China Hospital of Sichuan University between October 2018 and June 2021 as an external validation set, including 21 LNM-positive and 29 LNM-negative cases. Clinical features were selected by multivariate logistic regression analysis to establish a clinical model. Radiomics features were extracted from portal venous phase CT images using 3D Slicer software. A radiomics model was developed using the least absolute shrinkage and selection operator regression algorithm. A clinical-radiomics model was constructed by integrating clinical features and Radscore, and a nomogram was developed. The prediction performance of models was evaluated by the area under the receiver operating characteristic curve (AUC). The AUC values were compared using the DeLong test. Calibration curves and decision curves were plotted to assess calibration and clinical net benefit. Results:Clinical N (cN) staging was an independent risk factor for LNM ( OR=6.86, 95% CI 2.70-18.49, P<0.001). Totally 12 optimal features were selected to construct the radiomics model, and the clinical-radiomics nomogram model was constructed by combining cN staging and Radscore. In the external validation set, the AUC (95% CI) of the clinical model, radiomics model, and clinical-radiomics nomogram were 0.706 (0.576-0.836), 0.768 (0.637-0.899), and 0.803 (0.680-0.926), respectively. The nomogram achieved higher AUC than clinical and radiomics models with statistical significance ( Z=2.01, 2.21; P=0.044, 0.027). The calibration and decision curves demonstrated good model fit, providing clinical net benefits for patients. Conclusion:The clinical-radiomics nomogram model combining cN staging and CT radiomics features can effectively predict LNM risk in HCCA patients.

Objective To observe the reproducibility of radiomics feature(RF)extracted from virtual monoenergetic image(VMI)of rabbit VX2 hepatoma models obtained with 3 different dual-energy CT(DECT)systems,and to explore relationship of reproducibility and diagnostic performance of RF.Methods Fifteen rabbits with VX2 hepatoma were randomly divided into 3 groups(each n=5).Contrast-enhanced abdominal CT scanning under volume CT dose index(CTDIvol)levels of 6,9 and 12 mGy were performed with dual-source DECT(dsDECT),rapid kV switching DECT(rsDECT)and dual-layer detector DECT(dlDECT),respectively.VMI were reconstructed at 10 keV increments from 40 to 140 keV.RF were extracted from VMI,the reproducibility was assessed using intra-class correlation coefficient(ICC),and those with ICC≥0.8 were considered as reproducible RF.The percentage of reproducible features(denoted by R)were compared among different scanner pairings and different CTDIvol levels.Within each CTDIvol group,the reconstruction energy levels yielding the maximum number(denoted by N)of common RF across different scanner pairings were identified.The receiver operating characteristic(ROC)curve was drawn,the area under the curve(AUC)was calculated,and the diagnostic efficacies of reproducible RF and other RF were compared under optimal reproducible conditions.Spearman correlation coefficient between ICC and the corresponding AUC of RF were calculated.Results RrsDECT-dsDECT(6.45％,95％CI[2.36％,8.87％])was higher than RdlDECT-dsDECT(0.72％,95％CI[0.15％,1.79％])and RrsDECT-dlDECT(1.43％,95％CI[0.60％,4.06％])(all adjusted P＜0.05),R9mGy(3.70％,95％CI[1.31％,5.73％])and R12mGy(2.63％,95％CI[0.60％,6.69％])were higher than R6mGy(1.31％,95％CI[0.12％,1.55％])(all adjusted P＜0.05).The optimal reproducible reconstruction energy levels of RF under CTDIvol of 6,9 and 12 mGy concentrated at 50-70 keV.AUC of reproducible RFs were higher than of other RF(all adjusted P＜0.05)and had certain correlation with the reproducibility(rs=0.102-0.516,P＜0.05).Conclusion The reproducibility of RF extracted from contrast-enhanced VMI CT images of rabbit VX2 hepatoma models associated with DECT scanner,CTDIvol level and reconstruction energy level.RF with higher reproducibility might have better diagnostic performance.

Objective To investigate the value of CT radiomics combined with CT and preoperative pathological features for predicting postoperative early recurrence(ER)of local advanced esophageal squamous cell carcinoma(LAESCC).Methods Data of 334 patients with LAESCC were retrospectively analyzed.The patients were divided into training set(n=234)and verification set(n=100)at the ratio of 7:3 and were followed up to observe ER(recurrence within 12 months after surgery)or not.Univariate and multivariate logistic regression were used to analyze clinical,CT and preoperative pathological features of LAESCC in patients with or without ER in training set.The independent risk factors of ER were screened,and a CT-preoperative pathology model was constructed.Based on venous phase CT in training set,the radiomics features of lesions were extracted and screened to establish radiomics model,and finally a combined model was established based on radiomics model and the independent risk factors.Receiver operating characteristic(ROC)curves were drawn,and the area under the curve(AUC)was calculated to evaluate the diagnostic efficacy of each model.Results Among 334 cases,168 were found with but 166 without ER.In training set,117 cases were found with while the rest 117 without ER,while in verification set,51 were found with but 49 without ER.The length of lesions,cT stage and cN stage shown on CT and tumor differentiation degree displayed with preoperative pathology were all independent risk factors for ER of LAESCC(all P＜0.05).The AUC of CT-preoperative pathology model in training set and validation set was 0.759 and 0.783,respectively.Ten best radiomics features of LAESCC were selected,and AUC of the established radiomics model in training set and validation set was 0.770 and 0.730,respectively.The AUC of combined model in training and validation set was 0.838 and 0.826,respectively.The AUC of CT radiomics combined with CT and preoperative pathological features in training set was higher than that of CT-preoperative pathologymodel and radiomics model(both P＜0.01).Conclusion CT radiomics combined with CT and preoperative pathological features could effectively predict postoperative ER of LAESCC.

Objective:To investigate the predictive model construction of anastomotic thickening character after radical surgery of esophageal cancer based on computed tomogralphy(CT) radiomics and its application value.Methods:The retrospective cohort study was conducted. The clinicopathological data of 202 patients with esophageal squamous cell carcinoma (ESCC) who were admitted to The First Affiliated Hospital of Zhengzhou University from January 2013 to June 2021 were collected. There were 147 males and 55 females, aged (63±8) years. Based on random number table, 202 patients were assigned into training dataset and validation dataset at a ratio of 7:3, including 141 cases and 61 cases respectively. Patients underwent radical resection of ESCC and enhanced CT examination. Observation indicators: (1) influencing factor analysis of malignant anas-tomotic thickening; (2) construction and evaluation of predictive model; (3) performance comparison of 3 predictive models. The normality of continuous variables was tested by Kolmogorov-Smirnov method. Measurement data with normal distribution were represented as Mean± SD, and comparison between groups was analyzed using the t test. Measurement data with skewed distribution were represented as M( Q1, Q3), and comparison between groups was analyzed using the Mann-Whintney U test. Count data were represented as absolute numbers, and comparison between groups was analyzed using the chi-square test or Fisher's exact probability. The consistency between subjective CT features by two doctors and measured CT numeric variables was analyzed by Kappa test and intraclass correlation coefficient (ICC), with Kappa >0.6 and ICC >0.6 as good consistency. Univariate analysis was conducted by corresponding statistic methods. Multivariate analysis was conducted by Logistics stepwise regression model. The receiver operating characteristic (ROC) curve was drawn, and area under curve (AUC), Delong test, decision curve were used to evaluate the diagnostic efficiency and clinical applicability of model. Results:(1) Influencing factor analysis of malignant anastomotic thickening. Of the 202 ESCC patients, 97 cases had malignant anastomotic thickening and 105 cases had inflammatory anastomotic thickening. The consistency between subjective CT features by two doctors and measured CT numeric variables showed Kappa and ICC values >0.6. Results of multivariate analysis showed that the maximum thickness of anastomosis and CT enhancement pattern were independent influencing factors for malignant anastomotic thickening[ hazard ratio=1.46, 3.09, 95% confidence interval ( CI) as 1.26-1.71,1.18-8.12, P<0.05]. (2) Construction and evaluation of predictive model. ① Clinical predictive model. The maximum thickness of anasto-mosis and CT enhancement pattern were used to construct a clinical predictive model. ROC curve of the clinical predictive model showed an AUC, accuracy, sensitivity, specificity as 0.86 (95% CI as 0.80-0.92),0.77, 0.77, 0.80 for the training dataset, and 0.78 (95% CI as 0.65-0.89), 0.77, 0.77, 0.80 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=1.22, P>0.05). ② Radiomics predictive model. A total of 854 radiomics features were extracted and 2 radiomics features (wavelet-LL_first order_ Maximum and original_shape_VoxelVolume) were finally screened out to construct a radiomics predictive model. ROC curve of the radiomics predictive model showed an AUC, accuracy, sensitivity, specificity as 0.87 (95% CI as 0.81-0.93), 0.80, 0.75, 0.86 for the training dataset, and 0.73 (95% CI as 0.63-0.83), 0.80, 0.76, 0.94 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=-0.25, P>0.05). ③ Combined predictive model. Results of multivariate analysis and radiomics features were used to construct a combined predictive model. ROC curve of the combined predictive model showed an AUC, accuracy, sensitivity, specificity as 0.93 (95% CI as 0.89-0.97),0.84, 0.90, 0.84 for the training dataset, and 0.79 (95% CI as 0.70-0.88), 0.89, 0.86, 0.91 for the validation dataset, respectively. Results of Delong test showed no significant difference in AUC between the training dataset and validation dataset ( Z=0.22, P>0.05). (3) Performance comparison of 3 predictive models. Results of Hosmer-Lemeshow goodness-of-fit test showed that the clinical predictive model, radiomics predictive model and combined predictive model had a good fitting degree ( χ2=4.88, 7.95, 4.85, P>0.05). Delong test showed a significant difference in AUC between the combined predictive model and clinical predictive model, also between the combined predictive model and radiomics predictive model ( Z=2.88, 2.51, P<0.05 ). There was no significant difference in AUC between the clinical predictive model and radiomics predictive model ( Z=-0.32, P>0.05). The calibration curve showed a good predictive performance in the combined predictive model. The decision curve showed a higher distinguishing performance for anastomotic thickening character in the combined predictive model than in the clinical predictive model or radiomics predictive model. Conclusions:The maximum thickness of anastomosis and CT enhancement pattern are independent influencing factors for malignant anastomotic thickening. Radiomics predictive model can distinguish the benign from malignant thickening of anastomosis. Combined predictive model has the best diagnostic efficacy.

Objective:To explore the value of multiphasic CT-based radiomics signature in predicting the invasive behavior of pancreatic solid pseudopapillary neoplasm (pSPN).Methods:The multiphasic CT images of patients with pSPN confirmed by postoperative pathology in the First Affiliated Hospital of Zhengzhou University from January 2012 to January 2021 were analyzed retrospectively. There were 23 cases of invasiveness and 59 cases of non-invasiveness. The region of interest(ROI) was artificially delineated layer by layer in the plain scan, arterial-phase and venous-phase images, respectively. The 1 316 image features were extracted from each ROI. The data set was divided into training and validation sets with a ratio of 7∶3 by stratified random sampling, and synthetic minority oversampling technique (SMOTE) algorithm was used for oversampling in the training set to generate invasive and non-invasive balanced data for building the training model. The constructed model was validated in the validation set. The receiver operating characteristic(ROC) analysis was used to evaluate model performance and the Delong′s test was applied to compare the area under the ROC curve (AUC) of different predict models. The improvement for classification efficiency of each independent model or their combinations were also assessed by net reclassification improvement (NRI) and integrated discrimination improvement (IDI) indices.Results:After feature extraction, 2, 6 and 3 features were retained to construct plain-scanned model, arterial-phase and venous-phase models, respectively. Seven independent-phase and combined-phase models were established. Except the plain-scanned model, the AUC values of other models were greater than 0.800. The arterial-phase model had the best efficiency for classification among all independent-phase models. The AUC values of arterial-phase model in the SMOTE training and validation sets were 0.913 and 0.873, respectively. By combining the radiomics signature of the arterial-phase and venous-phase models, the AUC values of training and validation sets increased to 0.934 and 0.913 respectively. There were no significant differences of the AUC values between the scan-arterial venous-phase model and arterial venous-phase model in both training and validation sets (both P>0.05). The NRI and IDI indexes showed that the combined form of plain-scan model and arterial-venous-phase model could not significantly improve the classification efficiency in the validation set (both NRI and IDI<0). Conclusions:The arterial-phase CT-based radiomics model has a good predictive performance in the invasive behavior of pSPN, and the combination with a venous-phase radiomics model can further improve the model performance.

Objective:To investigate the efficiency of deep learning image reconstruction (DLIR) algorithm in the image quality and detection of hypovascular hepatic metastases under low radiation doses in comparison with adaptive statistical iterative construction-V (ASiR-V).Methods:Fifty-six patients with suspected hypovascular hepatic metastases who needed abdominal enhanced CT scans were collected prospectively in the First Affiliated Hospital of Zhengzhou University from January to April 2021. The patients received conventional radiation dose with tube current-time products of 400 mA CT scans in the first venous phase, low-dose CT scans in the second venous phase, which were set as tube current-time products of 280 mA for group A (19 cases), 200 mA for group B (19 cases) and 120 mA for group C (18 case), respectively. The images of first venous phase and 3 groups of second venous phase were both reconstructed with ASiR-V60% and high-DLIR (DLIR-H). Quantitative parameters [image noise, liver and portal vein signal to noise ratio (SNR), contrast to noise ratio (CNR)] and qualitative parameters (overall image quality, lesion conspicuity, diagnostic confidence) were compared between ASiR-V60% and DLIR-H images, and the effective radiation dose (ED) and the lesion detectability of each group was recorded. The paired t test was used to compare quantitative parameters, whereas the Wilcoxon signed-rank test of paired data was used to compare qualitative parameters. Results:In the second venous phase, ED was (5.56±0.35) mSv in group A, (3.88±0.23) mSv in group B, and (2.42±0.23) mSv in group C, with a decrease of 30%, 50% and 70% compared with the first venous phase, respectively. Moreover, with the decrease of radiation dose, the noise gradually increased, and the CNR lesions, SNR liver and SNR portal vein all gradually decreased. DLIR-H images had statistically better quantitative scores than ASiR-V60% images when the same radiation dose was applied (all P<0.001). Furthermore, the qualitative parameters of each group decreased with the decrease of radiation dose. Under the same radiation dose, the overall image quality, lesion conspicuity and diagnostic confidence of DLIR-H were higher than those of ASiR-V60% (all P<0.001). All lesions [100% (84/84)] were detected by ASIR-V60% and DLIR-H in group A, 92.0% (75/81) in group B, and 88.0% (79/89) in group C. Conclusions:Compared with ASiR-V60%, DLIR-H could reduce image noise, improve overall image quality and lesion conspicuity of hypovascular hepatic metastases as well as increase diagnostic confidence under different radiation doses.