• Xiaolong Qi, Weimin An, Fuquan Liu, Ruizhao Qi, Lei Wang, Yanna Liu, Chuan Liu, Yi Xiang, Jialiang Hui, Zhao Liu, Xingshun Qi, Changchun Liu, Baogang Peng, Huiguo Ding, Yongping Yang, Xiaoshun He, Jinlin Hou, Jie Tian, and Zhiwei Li.
• From the Chinese Portal Hypertension Diagnosis and Monitoring Study Group (CHESS), CHESS Frontier Center, Lanzhou University, Lanzhou, China (Xiaolong Qi); Hepatic Hemodynamic Laboratory, Institute of Hepatology, Nanfang Hospital, Southern Medical University, Guangzhou, China (Xiaolong Qi, Y.L., Chuan Liu, Y.X., J. Hui, Z. Liu, J. Hou); Department of Radiology (W.A., Changchun Liu), Department of General Surgery (R.Q., Z. Li), and Center for Therapeutic Research of Hepatocarcinoma (Y.Y.), 302 Hospital of PLA, Beijing, China; Department of Interventional Therapy, Beijing Shijitan Hospital, Capital Medical University, Beijing, China (F.L., L.W.); Department of Gastroenterology, General Hospital of Shenyang Military Area, Shenyang, China (Xingshun Qi); Department of Hepatobiliary Surgery (B.P.) and Organ Transplant Center (X.H.), The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China; Department of Gastroenterology and Hepatology, Beijing You'an Hospital, Capital Medical University, Beijing, China (H.D.); Key Laboratory of Molecular Imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing, China (J.T.); and Department of Hepatobiliary Surgery, The Third People's Hospital of Shenzhen, Shenzhen, China (Z. Li).
• Radiology. 2019 Feb 1; 290 (2): 370-377.

AbstractPurpose To develop and validate a computational model for estimating hepatic venous pressure gradient (HVPG) based on CT angiographic images, termed virtual HVPG, to enable the noninvasive diagnosis of portal hypertension in patients with cirrhosis. Materials and Methods In this prospective multicenter diagnostic trial (ClinicalTrials.gov identifier: NCT02842697), 102 consecutive eligible participants (mean age, 47 years [range, 21-75 years]; 68 men with a mean age of 44 years [range, 21-73 years] and 34 women with a mean age of 52 years [range, 24-75 years]) were recruited from three high-volume liver centers between August 2016 and April 2017. All participants with cirrhosis of various causes underwent transjugular HVPG measurement, Doppler US, and CT angiography. Virtual HVPG was developed with a three-dimensional reconstructed model and computational fluid dynamics. Results In the training cohort (n = 29), the area under the receiver operating characteristic curve (AUC) of virtual HVPG in the prediction of clinically significant portal hypertension (CSPH) was 0.83 (95% confidence interval [CI]: 0.58, 1.00). The diagnostic performance was prospectively confirmed in the validation cohort (n = 73), with an AUC of 0.89 (95% CI: 0.81, 0.96). Inter- and intraobserver agreement was 0.88 and 0.96, respectively, suggesting the good reproducibility of virtual HVPG measurements. There was good correlation between virtual HVPG and invasive HVPG (R = 0.61, P < .001), with a satisfactory performance to rule out (7.3 mm Hg) and rule in (13.0 mm Hg) CSPH. Conclusion The accuracy of a computational model of virtual hepatic venous pressure gradient (HVPG) shows significant correlation with invasive HVPG. The virtual HVPG also showed a good performance in the noninvasive diagnosis of clinically significant portal hypertension in cirrhosis. © RSNA, 2018 Online supplemental material is available for this article. See also the editorial by Malayeri in this issue.

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