Study design and setting
This was a diagnostic accuracy cross sectional study that was conducted in accordance to Standards for Reporting of Diagnostic Accuracy Studies (STARD) guidelines . It was conducted at hepatology unit of internal medicine department and hepatoma unit of diagnostic and interventional radiology department at our university hospitals. All our participants were consecutively selected in the period from October, 2019 to October, 2021.
Participants and data collection
Eighty nine cirrhotic patients proved to be complicated with HCC and associated with PVT (either benign or malignant), were consecutively referred to our hepatology unit for clinical assessment. All patients were evaluated for the study eligibility criteria before enrollment that were fulfilled in 78 cirrhotic patients after exclusion of 11 patients; 4 cirrhotic patients were excluded due to presence of tense ascites, 3 patients were excluded due to morbid obesity, 3 patients were excluded due to concomitant hepatic encephalopathy, and one uncooperative patient. All included patients were firstly evaluated accurately using history, clinical evaluation, demographic criteria (age and gender), laboratory parameters [alanine aminotransferase (ALT), aspartate aminotranferase (AST), serum albumin, serum bilirubin, international normalized ratio (INR), Child–Pugh grade, hemoglobin, white blood cells, platelets, serum creatinine and alpha fetoprotein (AFP)] and the imaging criteria [HCC focality, HCC size, portal vein diameter (PVD), and nature of PVT]. Then, all participants were blindly referred to diagnostic radiology department for assessment of PVT using P-SWE by a highly experienced operator. All these are illustrated in the participant’s flowchart (Fig. 1).
Assessment of malignant criteria of portal vein thrombosis
The malignant criteria of HCC and PVT were assessed using triphasic computed tomography (used in 68 patients) or dynamic magnetic resonance imaging (used only in 10 patients). The malignant PVT was proved if it revealed arterial hyper-enhancement with delayed and venous washout [1, 6, 7].
Assessment of shear wave elastography of portal vein thrombosis
Assessment of SWE of portal vein thrombi were performed using iU22 US system (iU22, Philips Medical systems, Bothell, WA, USA), which can assess stiffness by p-SWE. It was done using a convex transducer C5-1 (1–5 MHz; C5-1, Philips Healthcare) through intercostal route in a supine position with the corresponding arm maximally abducted to widen intercostal space for better examination. Some patients underwent p-SWE in left or right lateral position for better access to liver or portal vein with holding their breath during time of examination for about 5 s. The maximum penetration depth of ElastPQ was 8 cm and the ROI was presented as a rectangular area measured 5 × 15 mm. The measures were taken from the main trunk, right and left branches of thrombosed portal veins. We considered the value of an average of 5–8 valid successful measurements. The velocity of the propagated shear wave in the ROI was automatically translated to stiffness in kilopascals (kPa) for PVT. As shown in Figs. 2 and 3.
Statistical analysis methods
We used IBM SPSS; version 23 statistic software (IBM, NY, USA) for description and statistical analysis of our collected data. The median with (IQR) was calculated for all our quantitative data (abnormally distributed), all our qualitative data were tabulated as frequency and relative frequency. We used Mann–Whitney U test for two group comparisons of our quantitative data. Chi-Square test was performed to conduct group comparisons for categorical data. The logistic regression analysis was performed for our candidate predictors; participants’ demographic criteria (age and sex), laboratory criteria (AST, ALT, Child–Pugh scores, platelets count, hemoglobin levels, white blood cells, serum creatinine, and AFP), imaging criteria related to HCC (HCC size and focality) and PVT-related criteria (PVD and SWE). Univariate logistic regression analysis was done first for each predictor to identify the significant predictors, and then the most independent significant predictors were identified using the multivariable logistic regression analysis by entering all the previously identified significant predictors simultaneously with a stepwise backward strategy. Receiver operating characteristics (ROC) were calculated for SWE values of PVT, and area under the ROC curve (AUC) was computed. Two cutoff values of SWE were calculated; the 1st cutoff point was selected to rule in malignant PVT with the highest specificity and highest LR+, the 2nd cutoff point was selected to rule out the malignant PVT with the highest sensitivity and lowest LR-. P-values less than 0.05 were considered statistically significant (Fig. 4).
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