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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.
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Hepatocellular carcinoma (HCC) is the most common primary liver malignancy, and represents a significant global health burden with rising incidence rates, despite a more thorough understanding of the etiology and biology of HCC, as well as advancements in diagnosis and treatment modalities. According to emerging evidence, imaging features related to tumor aggressiveness can offer relevant prognostic information, hence validation of imaging prognostic features may allow for better noninvasive outcomes prediction and inform the selection of tailored therapies, ultimately improving survival outcomes for patients with HCC.
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Objective To explore the diagnostic performance of the most recent 2018 version of liver reporting and data system (LI?RADS) on gadolinium?ethoxybenzyl?diethylenetriamine pentaacetic acid (Gd?EOB?DTPA) enhanced MRI to diagnose hepatocellular carcinoma (HCC) in high?risk patients. Methods From July 2015 to September 2018, 130 consecutive high?risk patients with 134 focal liver lesions were retrospectively enrolled in our center and underwent Gd?EOB?DTPA?enhanced MRI and subsequent hepatectomy within 1 month. Two independent radiologists blindly reviewed the preoperative MR images of all patients, and determined the presence of major features, ancillary features and the LI?RADS categories according to the version 2018 LI?RADS of each liver observation. The sensitivity, specificity, positive predictive value, negative predictive value, Youden index and accuracy of the 2018 version of LI?RADS were evaluated with postoperative histopathological results as references. The inter?observer agreement between the two radiologists was tested by Kappa analysis. Results The Kappa value of the LI?RADS categories between two radiologists was 0.628 (95%CI: 0.565 to 0.691). The sensitivity, specificity, Youden index values and accuracy of LR?5 by the two reviewers were 80.4% (78/97), 87.6% (85/97); 75.7% (28/37), 73.0% (27/37); 0.560 8, 0.605 9; 79.1% (106/134), 83.6% (112/136), respectively. These measures of LR?4+LR?5 were 91.8% (85/97), 96.9% (94/97); 67.6% (25/37), 67.6% (25/37); 0.605 9, 0.644 6; 82.1% (110/134), 88.8% (119/134), respectively. Conclusion Version 2018 LI?RADS demonstrated high sensitivity and accuracy to diagnosis HCC in high?risk patients on Gd?EOB?DTPA enhanced MRI.
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Objective@#To explore the diagnostic performance of the most recent 2018 version of liver reporting and data system (LI-RADS) on gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced MRI to diagnose hepatocellular carcinoma (HCC) in high-risk patients.@*Methods@#From July 2015 to September 2018, 130 consecutive high-risk patients with 134 focal liver lesions were retrospectively enrolled in our center and underwent Gd-EOB-DTPA-enhanced MRI and subsequent hepatectomy within 1 month. Two independent radiologists blindly reviewed the preoperative MR images of all patients, and determined the presence of major features, ancillary features and the LI-RADS categories according to the version 2018 LI-RADS of each liver observation. The sensitivity, specificity, positive predictive value, negative predictive value, Youden index and accuracy of the 2018 version of LI-RADS were evaluated with postoperative histopathological results as references. The inter-observer agreement between the two radiologists was tested by Kappa analysis.@*Results@#The Kappa value of the LI-RADS categories between two radiologists was 0.628 (95%CI: 0.565 to 0.691). The sensitivity, specificity, Youden index values and accuracy of LR-5 by the two reviewers were 80.4% (78/97), 87.6% (85/97); 75.7% (28/37), 73.0% (27/37); 0.560 8, 0.605 9; 79.1% (106/134), 83.6% (112/136), respectively. These measures of LR-4+LR-5 were 91.8% (85/97), 96.9% (94/97); 67.6% (25/37), 67.6% (25/37); 0.605 9, 0.644 6; 82.1% (110/134), 88.8% (119/134), respectively.@*Conclusion@#Version 2018 LI-RADS demonstrated high sensitivity and accuracy to diagnosis HCC in high-risk patients on Gd-EOB-DTPA enhanced MRI.
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<p><b>OBJECTIVE</b>To study the karyotype of four Ephedra plants in order to provide the cytologic evidence for the genetic diversity and identification genetic resources of Ephedra.</p><p><b>METHOD</b>The roots of germinating seeds were used to study the karyotype of four Ephedra plants by staining and slide-preparing technique of mitotic chromosomes.</p><p><b>RESULT</b>the optimal root-sampling time was about 10: 20 - 10:40 am. Using 0.002 mol x L(-1) 8-Hydroxyquinoline to pretreating the intravital root tips, the optimal pretreatment time for E. Sinica, E. intermedina, E. equisetina and E. przewalskii was 4, 5, 4.5 and 3.5 h, respectively. E. przewalskii and E. equisetina were diploid, E. Sinica and E. intermedina were belonged quadruple. The karyotype formulae of the four species were 2n = 2x = 14 = 2M + 8m + 4sm, 2n = 2x = 14 = 10m + 4st, 2n = 4x = 28 = 20m (2SAT) +8st, and 2n = 4x = 28 = 20m (SAT) + 6st + 2sm, respectively.</p><p><b>CONCLUSION</b>All the karyotypes of four Ephedra species were 2A type, which was the symmetric karyotype.</p>