AUTHOR=Wan Shang , Wei Yi , Zhang Xin , Yang Caiwei , Hu Fubi , Song Bin
TITLE=Computed Tomography-Based Texture Features for the Risk Stratification of Portal Hypertension and Prediction of Survival in Patients With Cirrhosis: A Preliminary Study
JOURNAL=Frontiers in Medicine
VOLUME=9
YEAR=2022
URL=https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2022.863596
DOI=10.3389/fmed.2022.863596
ISSN=2296-858X
ABSTRACT=ObjectiveClinical evidence suggests that the risk stratification of portal hypertension (PH) plays a vital role in disease progression and patient outcomes. However, the gold standard for stratifying PH [portal vein pressure (PVP) measurement] is invasive and therefore not suitable for routine clinical practice. This study is aimed to stratify PH and predict patient outcomes using liver or spleen texture features based on computed tomography (CT) images non-invasively.
MethodsA total of 114 patients with PH were included in this retrospective study and divided into high-risk PH (PVP ≥ 20 mm Hg, n = 57) or low-risk PH (PVP < 20 mm Hg, n = 57), a progression-free survival (PFS) group (n = 14), or a non-PFS group (n = 51) based on patients with rebleeding or death after the transjugular intrahepatic portosystemic shunt (TIPS) procedure. All patients underwent contrast-enhanced CT, and the laboratory data were recorded. Texture features of the liver or spleen were obtained by a manual drawing of the region of interest (ROI) and were performed in the portal venous phase. Logistic regression analysis was applied to select the significant features related to high-risk PH, and PFS-related features were determined by the Cox proportional hazards model and Kaplan-Meier analysis. Receiver operating characteristic (ROC) curves were used to test the diagnostic capacity of each feature.
ResultsFive texture features (one first-order feature from the liver and four wavelet features from the spleen) and the international normalized ratio (INR) were identified as statistically significant for stratifying PH (p < 0.05). The best performance was achieved by the spleen-derived feature of wavelet.LLH_ngtdm_Busyness, with an AUC of 0.72. The only log.sigma.3.0.mm.3D_firstorder_RobustMeanAbsoluteDeviation feature from the liver was associated with PFS with a C-index of 0.72 (95% CI 0.566–0.885), which could stratify patients with PH into high- or low-risk groups. The 1-, 2-, and 3-year survival probabilities were 66.7, 50, and 33.3% for the high-risk group and 93.2, 91.5, and 84.4% for the low-risk group, respectively (p < 0.05).
ConclusionCT-based texture features from the liver or spleen may have the potential to stratify PH and predict patient survival.