Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: Correlation with pathological characteristics

Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: Correlation with pathological characteristics | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: Correlation with pathological characteristics Jingwen Bao, Zehua Nie, Quanwen Wang, Yanling Chen, Kun Wang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4627278/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 16 Aug, 2024 Read the published version in Abdominal Radiology → Version 1 posted 11 You are reading this latest preprint version Abstract Objective To explore the factors that influence the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) classification of combined hepatocellular-cholangiocarcinoma (cHCC-ICC). Methods Between September 2014 to July 2020, the CEUS features of 58 patients with pathologically confirmed cHCC-ICC were retrospectively evaluated and assigned according to the CEUS LI-RADS (version 2017). The pathological characteristics of nodules categorizing as different CEUS LI-RADS categories were compared. Multivariate logistic regression analysis was conducted to explore potential factors that may influence the CEUS LI-RADS classification of cHCC-ICC. Results According to CEUS LI-RADS, 32.8% (19/58), 63.8% (37/58), and 3.4% (2/58) were categorized as LR-5, LR-M, and LR-TIV, respectively. There was significant difference between the LR-M and LR-5 groups with regard to the pathological grade, nodule size, and HCC/ICC-component ratio of cHCC-ICC. Multivariate logistic regression analysis identified tumor size and the relative proportions of hepatocellular carcinomas (HCC) and intrahepatic cholangiocarcinomas (ICC) components within cHCC-ICC as the independent influencing factors. Conclusion Tumor size and the relative proportion of HCC and ICC components within the nodule had a significant impact on the CEUS LI-RADS classification of cHCC-ICC. combined hepatocellular-cholangiocarcinoma contrast-enhanced ultrasound Liver Imaging Reporting and Data System influencing factors Figures Figure 1 Figure 2 Figure 3 Key Points Tumor size and the relative proportions of HCC and ICC components were the independent influencing factors for the CEUS LI-RADS classification of cHCC-ICC. The HCC/ICC-component ratio acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern of nodules. Tumor size mainly had an impact on the enhanced pattern and washout features of cHCC-ICCs, thus leading to different CEUS LI-RADS classification Introduction Combined hepatocellular–cholangiocarcinoma (cHCC-ICC) is an uncommon hepatic malignancy accounting for 0.4 ~ 14.2% of primary liver cancers (PLCs)[ 1 ]. According to the 2010 World Health Organization (WHO) classification of tumors of the digestive system, a definite diagnosis of cHCC-ICC requires the coexistence of hepatocytic and cholangiocytic elements on histopathology[ 2 ]. Due to the special constitution, cHCC-ICC shared several risks factors and clinical features of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), while its recommended therapeutic strategy and prognosis were different from the other two malignancies to some extent[ 3 ]. Tumor resection with lymphadenectomy was the only curative option available for patients with cHCC-ICC unfortunately[ 4 ]. Vascular invasion and lymph node metastasis were commonly observed in cHCC-ICC and its prognosis was reported to be poorer than that of HCC and comparable to ICC[ 5 – 8 ]. Therefore, early identification of cHCC-ICC represents a major concern of clinical decision-making as well as prognostic estimation. Nevertheless, the preoperative confirmation of cHCC-ICC so far can only rely on histopathological examination of biopsy specimens from extensive sampling sites. Meanwhile, impaired accuracy of liver biopsy brought by sampling error or tissue insufficiency cannot be neglected[ 9 ]. Evolving imaging techniques have shed light on the preoperative non-invasive diagnosis of PLCs. Contrast-enhanced ultrasound (CEUS) has been applied to the evaluation of hepatic mass for years, with the unique advantage of dynamically presenting the microcirculation within liver lesions. The CEUS Liver Imaging Reporting and Data System (LI-RADS) was developed for the standard classification of focal liver lesions (FLLs) by the American College of Radiology (ACR), which achieved high accuracy in categorizing HCC as LR-5[ 10 – 12 ]. Meanwhile, the LR-M criterion was reported to show satisfying performance in differentiating ICC from HCC, with an accuracy of 92.38%[ 13 ]. However, only a few studies ever investigated the imaging characteristics of cHCC-ICC based on this category, of which either an imaging manifestation of LR-5 or LR-M category was observed in this special tumor[ 14 , 15 ]. This finding might confuse the differential diagnosis and restrict the use of CEUS LI-RADS. Due to the complex components of cHCC-ICC, some researchers were in favor of the explanation that its imaging behavior might be correlated with the HCC/ICC-component ratio. For cHCC-ICC of HCC-predominance, the imaging presentation tended to resemble that of HCC, while for cHCC-ICC with a predominant of ICC component, the ICC-like features were more common[ 9 , 16 , 17 ]. Nonetheless, no research has explicated the influencing factors for CEUS LI-RADS classification in cHCC-ICC. Therefore, the present study attempted to characterize the CEUS manifestation of cHCC-ICC according to the CEUS LI-RADS category and explore its potential influencing factors. Materials and methods Study participants This current study was approved by the ethic committee of our hospital and informed consent from participants was waived. From September 2014 to July 2020, information of patients with pathologically proven cHCC-ICC was reviewed. Those who met the following inclusion criteria were enrolled in the final study: 1) the pathological diagnosis of cHCC-ICC was confirmed according to the 2019 WHO version; 2) CEUS examination was performed within 2 weeks before hepatectomy. 3) patients with high-risk factors for HCC (chronic hepatitis B, liver cirrhosis, etc.); While patients were excluded if they fulfilled any of the following criteria: 1) underwent anti-cancer treatment prior to surgery (local regional therapy, systematic therapy, etc.); 2) preoperative clinical indicators and pathological data were missing; 3) unsatisfying image quality. The process of patient recruitment was presented in Fig. 1 . CEUS images acquisition CEUS examinations were performed using the IU 22 (Philips Bothell, Washington, United States) or LOGIQ E9 (GE Healthcare, Milwaukee, WI, United States) ultrasonic system equipped with a C5-1 and C1-6 multi-frequency convex array probe, respectively. All examinations were independently carried out by experienced sonographers with more than 10 years of experience in liver CEUS according to the World Federation for Ultrasound in Medicine and Biology and the European Federation of Societies for Ultrasound in Medicine and Biology (WFUMB-EFSUMB). After carefully scanning the whole liver and locating the hepatic nodule, the contrast-specific mode was switched for the CEUS test. A bolus of Sonovue (Bracco, Milan, Italy) was injected into the antecubital vein with a volume of 2.4 ml, followed by a flush of 5 ml 0.9% saline. Timing started immediately after contrast agent administration. The target lesion and its surrounding liver parenchyma were observed and recorded continuously for at least 3 minutes, then stored as digital cine clips for further evaluation. Patients were required to breathe peacefully during the whole process. CEUS images assessment Without knowing other imaging results, clinical indicators or pathological findings, two skilled ultrasound physicians with at least 5-year experience using CEUS reviewed the CEUS images independently. Any discrepancy was resolved by discussing with a third more experienced sonographer. Only the single dominant nodule with complete pathological test results was brought into analysis when patients with multiple lesions. The CEUS scanning process was classified as arterial phase (10-20s ~ 30-45s), portal venous phase (30-45s ~ 120s), and late phases (120s ~ 4-6mins) according to the WFUMB-EFSUMB guidelines and ACR CEUS LI-RADS (2017 version)[ 18 , 19 ]. By compared with the enhanced degree of adjacent liver parenchyma, the following diagnostic features of each lesion were recorded for CEUS LI-RADS classification: tumor size, contrast-enhanced intensity in the arterial phase (hyper/iso-/hypo-enhancement) and its enhanced patterns (homogenous/heterogeneous/rim-like enhancement), onset time of washout (within 60s or not), degree of washout within 2 minutes after contrast injection (marked/mild /no washout) and tumor in vein. An LI-RADS category was assigned for each hepatic observation, of which if the lesions presented one of the three CEUS characteristics: rim hyperenhancement, early washout ( 60 seconds) and mild washout were classified as LR-5 (tumor size ≥ 10 cm) or LR-4 (tumor size < 10 cm); And nodules with imaging manifestation of macrovascular invasion was categorized as LR-TIV[ 19 ]. Clinical information and histopathology analysis After reviewing the included patients’ medical records, the following baseline clinical information was collected: demographic characteristics (age, gender), risk factors (cirrhosis, chronic hepatitis status), and serum tumor marker levels [alpha fetoprotein (AFP), carbohydrate antigen 19 − 9 (CA19-9), carcinoembryonic antigen (CEA)]. The diagnosis of cHCC-ICC was confirmed by histopathological assessment according to the 2010 WHO classification of tumors of the digestive system, using hematoxylin-eosin stain and immunohistochemistry. The relative proportion of HCC and ICC was estimated according to their areas observed microscopically. Based on it, the cHCC-ICC nodules were classified as HCC-predominant, ICC-predominant and equal proportion, with the cut-off value as 50%. Meanwhile, the condition of necrosis within the cHCC-ICC nodule was also evaluated. The histologic grade of tumor was judged based on the Edmondson-Steiner (ES) grading system[ 20 , 21 ]. For individual nodule containing components of different histologic grades, grading was established according to the pathological grade of the main component. Those with ES grade I, I-II, and II were considered as Low grade, and ES grade II-III, III, III-IV, and IV were identified as high-grade[ 22 ]. The steatosis stage of the surrounding non-tumorous liver parenchyma was evaluated using and Nonalcoholic fatty liver disease activity score (NAS)[ 23 ]. If more than 5% of hepatocytes had fat vesicles, a diagnosis of hepatic steatosis would be generated. The liver fibrosis stage was judged on the basis of the Scheuer system, of which stages 4 was considered to be liver cirrhosis[ 24 ]. Microvascular invasion (MVI) was defined as small peritumoral vessels being invaded by tumor cells[ 14 ]. The MVI status of tumor was documented as MVI-negative and positive statuses. All histopathological examinations were conducted by experienced pathologists who were blinded to patients’ clinical and imaging information. Any divergences were settled down by consensus. Statistical analysis Continuous variables with skewed distributions were presented as medians (25%, 75%), and categorical variables was reported as frequencies (%). Parameters between cHCC-ICC nodules of different CEUS categories were compared using Mann-Whitney U-test, Pearson’s chi-square test or Fisher’s exact test. Multivariate logistic regression analysis was carried out for the identification of potential influencing factors for CEUS LI-RADS classification in cHCC-ICC. Only the parameters with P <0.05 at univariable analysis were brought into the later multivariate analysis, with the odds ratios (OR) and 95% confidence intervals (CI) being computed. Correlation between the consequent independent influencing factors and the major imaging features of CEUS LI-RADS categories was further investigated to figure out the exact mechanism, using Pearson’s chi-square test or Fisher’s exact test. The kappa (κ) value was calculated to determine the interobserver agreement on CEUS LI-RADS categories among readers, which was classified as poor (0 < κ < 0.20), fair (0.20 < κ < 0.40), moderate (0.40 < κ < 0.60), substantial (0.60 < κ < 0.80) as well as perfect (0.80 < κ < 1). All statistical calculation was conducted with the help of SPSS 20.0 (version 20.0, IBM, Armonk, NY, United States) and medcalc (version 16.8.4, Mariakerke, Belgium). P < 0.05 indicated a statistically significant difference. Results Imaging features and the CEUS LI-RADS classification A total of 58 patients (median age, 54 years; range 34–87 years) with 58 pathological confirmed cHCC-ICC nodules (median size, 24.5 mm, range: 10.0–104.0 mm) were included in the current study. All cHCC-ICC nodules displayed arterial phase hyperenhancement (APHE), of which 44.8% (26/58) showed homogeneous APHE, 31.0% (18/58) exhibited heterogenous APHE, and 24.1% (14/58) presented rim APHE. By comparing with the contrast intensity of adjacent normal hepatic parenchyma, 58.6% (34/58) of cHCC-ICCs appeared to washout within 60s, and 32.8% (19/58) lesions illustrated marked washout as observed during the first 2 mins. According to CEUS LI-RADS (version 2017), 19 nodules (32.8%) were categorized as LR-5 (Fig. 2 ), 37 (63.8%) tumors demonstrated the CEUS features of LR-M (Fig. 3 ), and enhancing thrombus was found in the portal vein of 3.4% cases (2/58), leading to LR-TIV classification (Table 1 ). Table 1 CEUS features of the cHCC-ICC nodules CEUS features Number (%) Arterial phase hyperenhancement 58(100) Enhanced patterns Homogeneous hyperenhancement 26(44.8) Heterogeneous hyperenhancement 18(31.0) Rim-like hyperenhancement 14(24.1) Early washout(≤ 60s) 34(58.6) Washout degree (as observed within the first 120s) Marked washout 19(32.8) Mild washout 35(60.3) No washout 4(6.9) Tumor thrombus 2(3.4) CEUS LI-RADS Category LR-5 19(32.8) LR-M 37(63.8) LR-IV 2(3.4) Data are presented as number (percentage); CEUS : contrast-enhanced ultrasound; cHCC-ICC : combined hepatocellular-cholangiocarcinoma; LI-RADS : liver imaging reporting and data system. The clinical and pathological characteristics between patients with LR-5 or LR-M lesions were compared was and displayed in Table 2 . There was significant difference between the LR-5 and LR-M groups with regard to the tumor size [18.0(14.0,25.0) mm vs . 29.0(20.5,45.0) mm, P = 0.004], pathological grade ( P = 0.047) and HCC/ICC-component ratio within nodules ( P = 0.015). The remaining parameters did not differ between the two groups, including age, gender, tumor location, hepatitis, cirrhosis, steatosis, necrosis and MVI status (all P > 0.05). In the LR-5 group, 57.9% (11/19) lesions showed HCC-predominance on histopathology. By contrast, 64.9% (24/37) of LR-M nodules were identified as ICC-predominance. The percentage of low-grade cHCC-ICC in the LR-5 group was 47.4% (9/19), higher than that of the LR-M group (21.6%, 8/37). Substantial or excellent agreement was achieved between the two radiologists concerning the interpretation of CEUS images and classification of CEUS LI-RADS categories, with the κ coefficients ranging from 0.788 to 0.890 (Supplementary Table 1). Table 2 Comparison of clinical and pathological characteristics among nodules classified as different CEUS LI-RADS categories. Clinical parameters LR-5(n = 19) LR-M(n = 37) P Age (years) 59.0(48.0,65.0) 54.0(48.0,63.5) 0.634 Sex (male: female) 11/8 29/8 0.108 Tumor number(single/multiple) 13/6 23/14 0.644 Location (right/left/caudate lobe) 13/6/0 25/11/1 1.000 Tumor size(mm) 18.0(14.0,25.0) 29.0(20.5,45.0) 0.004* ≥30mm 2(10.5) 17(45.9) 0.008* <30mm 17(89.5) 20(54.1) Etiology Hepatitis B virus 18(94.7) 35(94.6) 1.000 Hepatitis C virus 1(5.3) 0 0.339 Pathological findings Tumor components 0.015* HCC-predominant 11(57.9) 11(29.7) ICC-predominant 5(26.3) 24(64.9) Equal proportion 3(15.8) 2(5.4) Cirrhosis 14(73.7) 24(64.9) 0.503 Steatosis 5(26.3) 12(32.4) 0.637 Necrosis 1(5.3) 7(18.9) 0.327 Microscopic vascular invasion 6(31.6) 15(40.5) 0.512 Pathological grade 0.047* Low grade (ES grade I, I-II and II) 9(47.4) 8(21.6) High grade (ES grade II–III, III, III-IV and IV) 10(52.6) 29(78.4) Tumor markers AFP ≥ 20, 37 (U/ml) 0 8(21.6) 0.074 CEA > 5 (ng/ml) 4(21.1) 5(13.5) 0.732 cHCC-ICC : combined hepatocellular-cholangiocarcinoma; CEUS : contrast-enhanced ultrasound; LI-RADS : liver imaging reporting and data system; HCC : hepatocellular carcinoma; ICC : intrahepatic cholangiocarcinoma; AFP : alpha-fetoprotein; CA199 : cancer antigen 199; CEA : carcinoembryonic antigen Multivariate analysis Base on the univariate analysis results presented in Table 2 , significant parameters with a P-value<0.05 were brought into multivariate logistic regression analysis, including tumor size, pathological grade and HCC/ICC-component ratio within the nodule. Two independent influencing factors of CEUS LI-RADS classification were identified: nodule size (OR, 1.075; 95% CI, 1.008,1.147; P = 0.028) and tumor component (OR, 4.118; 95% CI, 1.007,16.838; P = 0.049) (Table 3 ). Further analysis about the correlation between tumor components and the major imaging features of CEUS LI-RADS indicated that rim-like APHE were more common in cHCC-ICCs containing mainly ICC component than those of HCC-predominance (37.9% vs. 9.1%, P = 0.039). The mechanism by which nodule size affected CEUS LI-RADS classification of cHCC-ICCs was investigated in the same way, which showed that rim-like and heterogeneous enhancement were more frequently observed in cHCC-ICCs with a diameter larger than 30mm, while lesions smaller than 30mm tended to show homogeneous enhancement (all P <0.05). In addition, both early (<60s) and marked washout were more common in tumors with a diameter larger than 3 cm (all P <0.05) (Supplementary Tables 2 and 3). Table 3 Multivariate logistic regression analyses of potential influencing factors for the CEUS LI-RADS classification of cHCC-ICC Risk factors Wals Odds ratio (95%CI) P-value Pathological grade 1.669(0.421,6.623) 0.466 Tumor components 4.032 Equal proportion 0.026 0.494(0.053,4.606) 0.536 ICC-predominant 3.869 4.118(1.007,16.838) 0.049* HCC-predominant / / / Tumor size 6.233 1.075(1.008,1.147) 0.028* CEU S: contrast-enhanced ultrasound; LI-RADS : liver imaging reporting and data system; cHCC-ICC : combined hepatocellular-cholangiocarcinoma; CI : confidence interval; HCC : hepatocellular carcinoma; ICC : intrahepatic cholangiocarcinoma Discussion CEUS LI-RADS was developed by the ACR aiming at improving the diagnostic accuracy of HCC. Nodules in patients with a high risk of HCC were classified into 5 categories (LR-1 to LR-5) based on their CEUS manifestation. A higher grade means a higher possibility of HCC. Moreover, an LR-M category was set up for lesions that showed malignant characteristics but not HCC specific, and LR-TIV for nodules with portal cancerous thrombus[ 10 ]. Theoretically, as a non-HCC malignant tumor, cHCC-ICC was supposed to present CEUS features of LR-M category. However, imaging characteristics of both LR-5 and LR-M classification were observed in cHCC-ICC nodules according to several previous studies[ 14 , 15 ]. Similarly, the current study also found that a majority of cHCC-ICC nodules were categorized as LR-M (63.8%), and a relatively small proportion of tumors were classified as LR-5(32.8%). In order to find out the significant factors that influence the CEUD LR-RADS classification of cHCC-ICC nodules, clinical and pathological data between cHCC-ICC patients with LR-5 and LR-M nodules were compared in the present study. Our results indicated that the CEUS LI-RADS classification of cHCC-ICC nodules might be associated with its maximum diameter, pathological grade and HCC/ICC-component ratio. While multivariate analysis identified tumor size and the relative proportions of HCC and ICC components within cHCC-ICC as the independent influencing factors. cHCC-ICC was characterized as the coexistence of HCC and ICC components. The proportion of HCC and ICC components within the cHCC-ICC nodule was widely considered to be associated with its imaging presentation[ 16 , 25 ]. In the current study, we found that 57.9% of LR-5 nodules were HCC-predominant on histopathology. By contrast, 64.9% of LR-M nodules were found as ICC-predominance. Our study results were partly agreed with that of Yang et al.[ 14 ], in which all ICC-predominant cHCC-ICCs were categorized as LR-M (5 cases) and a high proportion of LR-5 lesions (100%) were HCC-predominant. However, a majority of LR-M nodules (81.5%) were also found as HCC-predominance in their research. The reason for the discrepancy could be attributed to tumor size and sample number. By further analyzing the correlation between tumor components and the specific imaging features of CEUS LI-RADS categories, we found that the HCC/ICC-component ratio within cHCC-ICC nodule acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern. There was 37.9% of ICC-predominant lesions displayed rim-like enhancement, significantly higher than that of nodules in HCC-predominance (9.1%, P = 0.039). Ye et al.[ 16 ] also reported this phenomenon, 84.6% of ICC-predominant cHCC-ICCs in their study manifested as rim-like enhancement, and merely 15.4% HCC-predominant nodules showed this characteristic in comparison. Notably, rim-like enhancement is one of the most prominent characteristics of LR-M classification[ 26 ]. It was reasonable to speculate that when ICC turned to be the major constituent of cHCC-ICC, the blood supply of the tumor was not as rich as HCC and often leaded to necrosis in the central region. In addition, the hyper-enhancing regions of the tumor indicated a high density of malignant cells[ 27 ]. Pathological research about ICC suggested that there was large amount of malignant cells proliferated in the peripheral area while abundant fibrous stroma was located in the center of tumor[ 28 ]. On the other hand, the rich blood supply from neovascularization and capillarized sinusoids inside the HCC component tended to result in homogeneous or heterogeneous enhancement on cHCC-ICCs with HCC-predominance, depending on the degree of blood supply and presence of necrosis in each lesion[ 28 , 29 ]. As reported, tumor size might contribute to the CEUS presentation of primary liver cancers[ 30 , 31 ]. Consistently, CEUS LI-RADS classification of cHCC-ICC showed size-dependent characteristic in our study. Apart from serving as one of the classification bases of CEUS LI-RADS, tumor size was also found to have an impact on the enhanced pattern and washout features of cHCC-ICCs, thus leading to different CEUS LI-RADS classification. In our study, both rim-like and heterogeneous enhancement were more frequently observed in cHCC-ICCs with a diameter larger than 30mm, while lesions smaller than 30mm tended to show homogeneous enhancement. The study of Ye et al.[ 16 ] revealed a connection between tumor size and enhancement pattern as well. Such phenomenon might due to the intra-tumoral necrosis and liquefaction caused by insufficient blood flow of large tumor, and necrosis inside tumor was known to manifest as non-enhanced area on CEUS[ 30 ]. In the present study, a higher proportion of necrosis was observed in cHCC-ICCs classifying as LR-M compared to those categorizing as LR-5, which echoed this hypothesis. In addition, both early (<60s) and marked washout (as observed within the first 2 mins) were more common in tumors with a diameter larger than 3 cm in the current study. Association between tumor diameter and washout features of cHCC-ICC haven’t been discussed up to now. By reviewing and referring to the correlational research of HCC and ICC, a hypothesis was proposed that the washout features might be related to the cellular differentiation of cHCC-ICCs with different sizes. It was believed that tumor became increasingly dedifferentiated with the growth of nodule size[ 32 , 33 ]. And the drainage vessels switched from hepatic veins to portal veins during this process, which resulted in rapid washout on CEUS[ 34 ]. On the other hand, the rich sinusoids and trabecular pattern of cell cords inside tumors might lead to stagnation and slow clearing of ultrasound contrast agents. While such structures were scarce in poorly differentiated tumors [ 35 , 36 ]. Tumor presented high-grade on pathology also implied poorly differentiated. Univariate analysis in our study indicated that pathological grade played a role in the CEUS LI-RADS classification of cHCC-ICCs. The proportion of cHCC-ICCs manifested as high-grade tumors were higher in the LR-M group than the LR-5 nodules (P<0.05). However, this parameter was not recognized as an independent influencing factor of CEUS LI-RADS classification in cHCC-ICC, which in agreement with the conclusion of Herbay et al.[ 37 ] and Yang et al.[ 35 ]. Their studies denied the correlation between histologic grade and tumor size of HCC. Therefore, the mechanism by which tumor size affects washout features of cHCC-ICCs as well as the relationship between pathological grade and CEUS LI-RADS classification of cHCC-ICCs warrant further exploration. Preoperative differentiation of HCC from the non-HCC malignancies including ICC and cHCC-ICC was necessary since they have different preferred treatment options and prognosis. However, a good proportion of cHCC-ICCs were still miscategorized as definite HCCs (the LR-5 category) by CEUS LI-RADS, raising concern over the potential false positive diagnosis of HCC. Nonetheless, the consolation was that such misclassification of the LI-RADS category might cause small impact to the management of patients at risk of HCC due to the low incidence of cHCC-ICC. In addition, the survival outcome of cHCC-ICC manifesting imaging features of LR-5 category was reported to superior than that of nodules in LR-M category[ 14 ]. Stratification of cHCC-CCA according to the CEUS LI-RADS categories (LR-5 or LR-M) might play a role in prognosis prediction. Our study had some limitations. First, as a retrospective study performed in a single center, patient selection bias was inevitable, and the generalizability might be affected. Second, due to the uncommon of cHCC-ICC, the number of cases enrolled in our study was relatively small, of which tumors in ES grade I and IV were scarce. This might affect the reliability of our study results, such as the relationship between histologic grade and the CEUS LI-RADS classification of cHCC-ICC. What’s more, the number of nodules in the LR-TIV category was too small to make a statistical comparison, and the influence that cancer embolus caused on the CEUS LI-RADS classification of cHCC-ICC was undetermined. Therefore, a multicenter study based on a large sample size is further expected. Conclusion In summary, CEUS LI-RADS classification of cHCC-ICC was significantly affected by tumor size and the relative proportion of HCC and ICC components within the lesion. The HCC/ICC-component ratio within the cHCC-ICC nodule acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern. Tumor size was significantly associated with the enhancement patterns and washout features. Abbreviations cHCC-ICC combined hepatocellular- cholangiocarcinoma HCC hepatocellular carcinoma ICC intrahepatic cholangiocarcinoma PLC primary liver cancer FLLs focal liver lesions CEUS contrast-enhanced ultrasound LI-RADS liver imaging reporting and data system EFSUMB European Federation of Societies for Ultrasound in Medicine and Biology MVI microvascular invasion ACR American College of Radiology HBV hepatitis B virus AFP alpha-fetoprotein CA19-9 carbohydrate antigen 19 − 9 CEA carcinoembryonic antigen Declarations Author Contribution Jingwen Bao and Zehua Nie have contributed equally to this work References Beaufrère A, Calderaro J, Paradis V. Combined hepatocellular-cholangiocarcinoma: An update. J Hepatol 2021;74:1212-1224. Akiba J, Nakashima O, Hattori S, Tanikawa K, Takenaka M, Nakayama M, et al.Clinicopathologic analysis of combined hepatocellular-cholangiocarcinoma according to the latest WHO classification. Am J Surg Pathol 2013;37:496-505. 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Claudon M, Dietrich CF, Choi BI, Cosgrove DO, Kudo M, Nolsøe CP, et al. Guidelines and good clinical practice recommendations for Contrast Enhanced Ultrasound (CEUS) in the liver - update 2012: A WFUMB-EFSUMB initiative in cooperation with representatives of AFSUMB, AIUM, ASUM, FLAUS and ICUS. Ultrasound Med Biol 2013;39:187-210. Bartolotta TV, Terranova MC, Gagliardo C, Taibbi A. CEUS LI-RADS: a pictorial review. Insights Imaging 2020;11:9. Edmondson HA, Steiner PE. Primary carcinoma of the liver: a study of 100 cases among 48,900 necropsies. Cancer 1954;7:462-503. Martins-Filho SN, Paiva C, Azevedo RS, Alves VAF. Histological Grading of Hepatocellular Carcinoma-A Systematic Review of Literature. Front Med (Lausanne) 2017;4:193. Wu M, Tan H, Gao F, Hai J, Ning P, Chen J, et al. Predicting the grade of hepatocellular carcinoma based on non-contrast-enhanced MRI radiomics signature. Eur Radiol 2019;29:2802-2811. Kleiner DE, Brunt EM, Van Natta M, Behling C, Contos MJ, Cummings OW, et al. Design and validation of a histological scoring system for nonalcoholic fatty liver disease. Hepatology 2005;41:1313-1321. Desmet VJ, Gerber M, Hoofnagle JH, Manns M, Scheuer PJ. Classification of chronic hepatitis: diagnosis, grading and staging. Hepatology 1994;19:1513-1520. Choi SH, Jeon SK, Lee SS, Lee JM, Hur BY, Kang HJ, et al. Radio-pathologic correlation of biphenotypic primary liver cancer (combined hepatocellular cholangiocarcinoma): changes in the 2019 WHO classification and impact on LI-RADS classification at liver MRI. Eur Radiol 2021;31:9479-9488. Galassi M, Iavarone M, Rossi S, Bota S, Vavassori S, Rosa L, et al. Patterns of appearance and risk of misdiagnosis of intrahepatic cholangiocarcinoma in cirrhosis at contrast enhanced ultrasound. Liver Int 2013;33:771-779. Xu HX, Chen LD, Liu LN, Zhang YF, Guo LH, Liu C. Contrast-enhanced ultrasound of intrahepatic cholangiocarcinoma: correlation with pathological examination. Br J Radiol 2012;85:1029-1037. Liu GJ, Wang W, Lu MD, Xie XY, Xu HX, Xu ZF, et al. Contrast-Enhanced Ultrasound for the Characterization of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma. Liver Cancer 2015;4:241-252. Park HJ, Choi BI, Lee ES, Park SB, Lee JB. How to Differentiate Borderline Hepatic Nodules in Hepatocarcinogenesis: Emphasis on Imaging Diagnosis. Liver Cancer 2017;6:189-203. Yuan MX, Li R, Zhang XH, Tang CL, Guo YL, Guo DY, et al. Factors Affecting the Enhancement Patterns of Intrahepatic Cholangiocarcinoma (ICC) on Contrast-Enhanced Ultrasound (CEUS) and their Pathological Correlations in Patients with a Single Lesion. Ultraschall Med 2016;37:609-618. Fan PL, Ding H, Mao F, Chen LL, Dong Y, Wang WP. Enhancement patterns of small hepatocellular carcinoma (≤ 30 mm) on contrast-enhanced ultrasound: Correlation with clinicopathologic characteristics. Eur J Radiol 2020;132:109341. Lu Q, Zhang XL, Han H, Huang BJ, Ding H, Wang WP. Value of Perfusion Parameters for Differentiating Hepatocellular Carcinoma and Liver Metastasis With Hypervascularity and a Normal Hepatic Background on Contrast-Enhanced Ultrasound Imaging. J Ultrasound Med 2019;38:2601-2608. Fan ZH, Chen MH, Dai Y, Wang YB, Yan K, Wu W, et al. Evaluation of primary malignancies of the liver using contrast-enhanced sonography: correlation with pathology. AJR Am J Roentgenol 2006;186:1512-1519. Kitao A, Zen Y, Matsui O, Gabata T, Nakanuma Y. Hepatocarcinogenesis: multistep changes of drainage vessels at CT during arterial portography and hepatic arteriography--radiologic-pathologic correlation. Radiology 2009;252:605-614. Yang D, Li R, Zhang XH, Tang CL, Ma KS, Guo DY, et al. Perfusion Characteristics of Hepatocellular Carcinoma at Contrast-enhanced Ultrasound: Influence of the Cellular differentiation, the Tumor Size and the Underlying Hepatic Condition. Sci Rep 2018;8:4713. Honda H, Tajima T, Kajiyama K, Kuroiwa T, Yoshimitsu K, Irie H, et al. Vascular changes in hepatocellular carcinoma: correlation of radiologic and pathologic findings. AJR Am J Roentgenol 1999;173:1213-1217. von Herbay A, Vogt C, Westendorff J, Häussinger D, Gregor M. Correlation between SonoVue enhancement in CEUS, HCC differentiation and HCC diameter: analysis of 130 patients with hepatocellular carcinoma (HCC). Ultraschall Med 2009;30:544-550. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Published Journal Publication published 16 Aug, 2024 Read the published version in Abdominal Radiology → Version 1 posted Editorial decision: Revision requested 22 Jul, 2024 Reviews received at journal 21 Jul, 2024 Reviews received at journal 14 Jul, 2024 Reviewers agreed at journal 12 Jul, 2024 Reviewers agreed at journal 11 Jul, 2024 Reviewers agreed at journal 11 Jul, 2024 Reviewers agreed at journal 09 Jul, 2024 Reviewers invited by journal 25 Jun, 2024 Editor assigned by journal 25 Jun, 2024 Submission checks completed at journal 25 Jun, 2024 First submitted to journal 23 Jun, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4627278","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":327078876,"identity":"3c4eb3ec-1709-462e-8f2a-8ec6a51ec394","order_by":0,"name":"Jingwen Bao","email":"","orcid":"","institution":"Hexi University","correspondingAuthor":false,"prefix":"","firstName":"Jingwen","middleName":"","lastName":"Bao","suffix":""},{"id":327078877,"identity":"f70fa8ee-6752-4db1-9129-401d4377096b","order_by":1,"name":"Zehua Nie","email":"","orcid":"","institution":"Hexi University","correspondingAuthor":false,"prefix":"","firstName":"Zehua","middleName":"","lastName":"Nie","suffix":""},{"id":327078878,"identity":"6d7822b0-58ba-4376-a2d7-e4ca12282ad6","order_by":2,"name":"Quanwen Wang","email":"","orcid":"","institution":"Hexi University","correspondingAuthor":false,"prefix":"","firstName":"Quanwen","middleName":"","lastName":"Wang","suffix":""},{"id":327078879,"identity":"ffb106a8-61fb-4f69-b02a-6ccd8f226103","order_by":3,"name":"Yanling Chen","email":"","orcid":"","institution":"First Affiliated Hospital of Sun Yat-sen University","correspondingAuthor":false,"prefix":"","firstName":"Yanling","middleName":"","lastName":"Chen","suffix":""},{"id":327078880,"identity":"9eb6d168-4d71-4aab-af8a-81c2d5958448","order_by":4,"name":"Kun Wang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAwUlEQVRIiWNgGAWjYBACeWbmgw8+8EjY8bM3EKnFsL0t2XCGjE2yZM8BYq05c8ZMmMcmjXHDjQQidTDOSEtjnJFzmJnh5uONNxhqbKIJamGXSD724MOZw3yMs9OKLRiOpeU2EGFLuuHMnsPMzNI5ZhKMDYcJa2G4kWMmzfvvMGOb5BlitQC9L83Dk8bYI8FDpBZIIPPYJEvwAP2SQIxf4FFpf/zwxhsfamyIcBgSMJBIIEU5RAupOkbBKBgFo2BkAAB6/kDWRUW/gAAAAABJRU5ErkJggg==","orcid":"","institution":"Binzhou Medical College Hospital","correspondingAuthor":true,"prefix":"","firstName":"Kun","middleName":"","lastName":"Wang","suffix":""},{"id":327078881,"identity":"2020aca6-0c97-4fa6-a463-faa2cf3587a3","order_by":5,"name":"Xinjiang Liu","email":"","orcid":"","institution":"pudong hospital, fudan university","correspondingAuthor":false,"prefix":"","firstName":"Xinjiang","middleName":"","lastName":"Liu","suffix":""}],"badges":[],"createdAt":"2024-06-24 03:56:54","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4627278/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4627278/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00261-024-04519-x","type":"published","date":"2024-08-16T15:57:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60530237,"identity":"50fe748e-3115-4514-aac9-d9b25de60e86","added_by":"auto","created_at":"2024-07-17 20:04:24","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":204202,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart shows participant inclusion. \u003cem\u003ecHCC-ICC\u003c/em\u003e: combined hepatocellular-cholangiocarcinoma; \u003cem\u003eCEUS\u003c/em\u003e: contrast-enhanced ultrasound; \u003cem\u003eHCC\u003c/em\u003e: hepatocellular carcinoma\u003c/p\u003e","description":"","filename":"Figure1flowchart.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4627278/v1/b49e38b58d542474d6bfaec2.jpg"},{"id":60530896,"identity":"de537502-43c2-47ff-9b2e-5a40946c0a37","added_by":"auto","created_at":"2024-07-17 20:12:24","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1709293,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLR-5 nodule in a 71-year-old female with chronic hepatitis B.\u003c/strong\u003e a. A 12×11mm nodules locating in the left hepatic liver is found to present homogeneously hyperenhancement (arrow) in the arterial phase on CEUS (28s post-injection). b. The lesion displays slightly hypo-enhancement during the portal venous phase (94s). c. Mild washout is observed (arrow) in the late phase (186s). d. Histopathological examination confirms the diagnosis of cHCC-ICC, with the ratio of HCC to ICC components at 7:3 (H\u0026amp;E, × 10). CEUS: contrast-enhanced ultrasound; cHCC-ICC: combined hepatocellular-cholangiocarcinoma; HCC: hepatocellular carcinoma; ICC: intrahepatic cholangiocarcinoma\u003c/p\u003e","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4627278/v1/86365ce55673ceb084deaf9d.jpg"},{"id":60530240,"identity":"4871d05d-129f-4b88-a95d-5ab67a3b3454","added_by":"auto","created_at":"2024-07-17 20:04:24","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1313724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eLR-M nodule in a 45-year-old male with chronic hepatitis B.\u003c/strong\u003e a. A 32×26 mm hepatic mass (arrow) in the right liver lobe shows heterogeneous hyperenhancement (arrow) during the arterial phase on CEUS (19s post-injection). b. The lesion exhibits early (washout onset time, 37 s) and marked washout (arrow, 97s) during the portal venous phase. c. The nodule shows markedly hypo-enhancement during the late phase (240s) and a “punched-out” appearance is observed (arrow). d. Histopathological examination confirms the diagnosis of cHCC-ICC, which shows a predominance of ICC component (80%) (H\u0026amp;E, ×10). CEUS: contrast-enhanced ultrasound; cHCC-ICC: combined hepatocellular-cholangiocarcinoma; ICC: intrahepatic cholangiocarcinoma\u003c/p\u003e","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4627278/v1/9225c6e5b751b4d88c767c77.jpg"},{"id":63071021,"identity":"de505d9f-63d1-4743-aa5f-33be86cffef9","added_by":"auto","created_at":"2024-08-22 20:02:45","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3810918,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4627278/v1/2bec39ee-8073-4c0d-9559-9cd8bec3cfe7.pdf"},{"id":60530238,"identity":"62615aa5-0d0a-4c26-b03c-39cf102ad7d3","added_by":"auto","created_at":"2024-07-17 20:04:24","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":13637,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-4627278/v1/c71e474ad751f5bdbec3377b.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: Correlation with pathological characteristics","fulltext":[{"header":"Key Points","content":"\u003cp\u003eTumor size and the relative proportions of HCC and ICC components were the independent influencing factors for the CEUS LI-RADS classification of cHCC-ICC. The HCC/ICC-component ratio acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern of nodules. Tumor size mainly had an impact on the enhanced pattern and washout features of cHCC-ICCs, thus leading to different CEUS LI-RADS classification\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eCombined hepatocellular\u0026ndash;cholangiocarcinoma (cHCC-ICC) is an uncommon hepatic malignancy accounting for 0.4\u0026thinsp;~\u0026thinsp;14.2% of primary liver cancers (PLCs)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. According to the 2010 World Health Organization (WHO) classification of tumors of the digestive system, a definite diagnosis of cHCC-ICC requires the coexistence of hepatocytic and cholangiocytic elements on histopathology[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Due to the special constitution, cHCC-ICC shared several risks factors and clinical features of both hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC), while its recommended therapeutic strategy and prognosis were different from the other two malignancies to some extent[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Tumor resection with lymphadenectomy was the only curative option available for patients with cHCC-ICC unfortunately[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Vascular invasion and lymph node metastasis were commonly observed in cHCC-ICC and its prognosis was reported to be poorer than that of HCC and comparable to ICC[\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, early identification of cHCC-ICC represents a major concern of clinical decision-making as well as prognostic estimation. Nevertheless, the preoperative confirmation of cHCC-ICC so far can only rely on histopathological examination of biopsy specimens from extensive sampling sites. Meanwhile, impaired accuracy of liver biopsy brought by sampling error or tissue insufficiency cannot be neglected[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEvolving imaging techniques have shed light on the preoperative non-invasive diagnosis of PLCs. Contrast-enhanced ultrasound (CEUS) has been applied to the evaluation of hepatic mass for years, with the unique advantage of dynamically presenting the microcirculation within liver lesions. The CEUS Liver Imaging Reporting and Data System (LI-RADS) was developed for the standard classification of focal liver lesions (FLLs) by the American College of Radiology (ACR), which achieved high accuracy in categorizing HCC as LR-5[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Meanwhile, the LR-M criterion was reported to show satisfying performance in differentiating ICC from HCC, with an accuracy of 92.38%[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. However, only a few studies ever investigated the imaging characteristics of cHCC-ICC based on this category, of which either an imaging manifestation of LR-5 or LR-M category was observed in this special tumor[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This finding might confuse the differential diagnosis and restrict the use of CEUS LI-RADS. Due to the complex components of cHCC-ICC, some researchers were in favor of the explanation that its imaging behavior might be correlated with the HCC/ICC-component ratio. For cHCC-ICC of HCC-predominance, the imaging presentation tended to resemble that of HCC, while for cHCC-ICC with a predominant of ICC component, the ICC-like features were more common[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Nonetheless, no research has explicated the influencing factors for CEUS LI-RADS classification in cHCC-ICC. Therefore, the present study attempted to characterize the CEUS manifestation of cHCC-ICC according to the CEUS LI-RADS category and explore its potential influencing factors.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy participants\u003c/h2\u003e \u003cp\u003e This current study was approved by the ethic committee of our hospital and informed consent from participants was waived. From September 2014 to July 2020, information of patients with pathologically proven cHCC-ICC was reviewed. Those who met the following inclusion criteria were enrolled in the final study: 1) the pathological diagnosis of cHCC-ICC was confirmed according to the 2019 WHO version; 2) CEUS examination was performed within 2 weeks before hepatectomy. 3) patients with high-risk factors for HCC (chronic hepatitis B, liver cirrhosis, etc.); While patients were excluded if they fulfilled any of the following criteria: 1) underwent anti-cancer treatment prior to surgery (local regional therapy, systematic therapy, etc.); 2) preoperative clinical indicators and pathological data were missing; 3) unsatisfying image quality. The process of patient recruitment was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eCEUS images acquisition\u003c/h2\u003e \u003cp\u003eCEUS examinations were performed using the IU 22 (Philips Bothell, Washington, United States) or LOGIQ E9 (GE Healthcare, Milwaukee, WI, United States) ultrasonic system equipped with a C5-1 and C1-6 multi-frequency convex array probe, respectively. All examinations were independently carried out by experienced sonographers with more than 10 years of experience in liver CEUS according to the World Federation for Ultrasound in Medicine and Biology and the European Federation of Societies for Ultrasound in Medicine and Biology (WFUMB-EFSUMB). After carefully scanning the whole liver and locating the hepatic nodule, the contrast-specific mode was switched for the CEUS test. A bolus of Sonovue (Bracco, Milan, Italy) was injected into the antecubital vein with a volume of 2.4 ml, followed by a flush of 5 ml 0.9% saline. Timing started immediately after contrast agent administration. The target lesion and its surrounding liver parenchyma were observed and recorded continuously for at least 3 minutes, then stored as digital cine clips for further evaluation. Patients were required to breathe peacefully during the whole process.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eCEUS images assessment\u003c/h2\u003e \u003cp\u003eWithout knowing other imaging results, clinical indicators or pathological findings, two skilled ultrasound physicians with at least 5-year experience using CEUS reviewed the CEUS images independently. Any discrepancy was resolved by discussing with a third more experienced sonographer. Only the single dominant nodule with complete pathological test results was brought into analysis when patients with multiple lesions. The CEUS scanning process was classified as arterial phase (10-20s\u0026thinsp;~\u0026thinsp;30-45s), portal venous phase (30-45s\u0026thinsp;~\u0026thinsp;120s), and late phases (120s\u0026thinsp;~\u0026thinsp;4-6mins) according to the WFUMB-EFSUMB guidelines and ACR CEUS LI-RADS (2017 version)[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. By compared with the enhanced degree of adjacent liver parenchyma, the following diagnostic features of each lesion were recorded for CEUS LI-RADS classification: tumor size, contrast-enhanced intensity in the arterial phase (hyper/iso-/hypo-enhancement) and its enhanced patterns (homogenous/heterogeneous/rim-like enhancement), onset time of washout (within 60s or not), degree of washout within 2 minutes after contrast injection (marked/mild /no washout) and tumor in vein. An LI-RADS category was assigned for each hepatic observation, of which if the lesions presented one of the three CEUS characteristics: rim hyperenhancement, early washout (\u0026lt;\u0026thinsp;60 seconds) or marked washout, it would be assigned as LR-M; while those showed arterial phase hyperenhancement followed by late (\u0026gt;\u0026thinsp;60 seconds) and mild washout were classified as LR-5 (tumor size\u0026thinsp;\u0026ge;\u0026thinsp;10 cm) or LR-4 (tumor size\u0026thinsp;\u0026lt;\u0026thinsp;10 cm); And nodules with imaging manifestation of macrovascular invasion was categorized as LR-TIV[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eClinical information and histopathology analysis\u003c/h2\u003e \u003cp\u003eAfter reviewing the included patients\u0026rsquo; medical records, the following baseline clinical information was collected: demographic characteristics (age, gender), risk factors (cirrhosis, chronic hepatitis status), and serum tumor marker levels [alpha fetoprotein (AFP), carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9 (CA19-9), carcinoembryonic antigen (CEA)].\u003c/p\u003e \u003cp\u003eThe diagnosis of cHCC-ICC was confirmed by histopathological assessment according to the 2010 WHO classification of tumors of the digestive system, using hematoxylin-eosin stain and immunohistochemistry. The relative proportion of HCC and ICC was estimated according to their areas observed microscopically. Based on it, the cHCC-ICC nodules were classified as HCC-predominant, ICC-predominant and equal proportion, with the cut-off value as 50%. Meanwhile, the condition of necrosis within the cHCC-ICC nodule was also evaluated. The histologic grade of tumor was judged based on the Edmondson-Steiner (ES) grading system[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For individual nodule containing components of different histologic grades, grading was established according to the pathological grade of the main component. Those with ES grade I, I-II, and II were considered as Low grade, and ES grade II-III, III, III-IV, and IV were identified as high-grade[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. The steatosis stage of the surrounding non-tumorous liver parenchyma was evaluated using and Nonalcoholic fatty liver disease activity score (NAS)[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. If more than 5% of hepatocytes had fat vesicles, a diagnosis of hepatic steatosis would be generated. The liver fibrosis stage was judged on the basis of the Scheuer system, of which stages 4 was considered to be liver cirrhosis[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Microvascular invasion (MVI) was defined as small peritumoral vessels being invaded by tumor cells[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The MVI status of tumor was documented as MVI-negative and positive statuses. All histopathological examinations were conducted by experienced pathologists who were blinded to patients\u0026rsquo; clinical and imaging information. Any divergences were settled down by consensus.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables with skewed distributions were presented as medians (25%, 75%), and categorical variables was reported as frequencies (%). Parameters between cHCC-ICC nodules of different CEUS categories were compared using Mann-Whitney U-test, Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test. Multivariate logistic regression analysis was carried out for the identification of potential influencing factors for CEUS LI-RADS classification in cHCC-ICC. Only the parameters with \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05 at univariable analysis were brought into the later multivariate analysis, with the odds ratios (OR) and 95% confidence intervals (CI) being computed. Correlation between the consequent independent influencing factors and the major imaging features of CEUS LI-RADS categories was further investigated to figure out the exact mechanism, using Pearson\u0026rsquo;s chi-square test or Fisher\u0026rsquo;s exact test. The kappa (κ) value was calculated to determine the interobserver agreement on CEUS LI-RADS categories among readers, which was classified as poor (0\u0026thinsp;\u0026lt;\u0026thinsp;κ\u0026thinsp;\u0026lt;\u0026thinsp;0.20), fair (0.20\u0026thinsp;\u0026lt;\u0026thinsp;κ\u0026thinsp;\u0026lt;\u0026thinsp;0.40), moderate (0.40\u0026thinsp;\u0026lt;\u0026thinsp;κ\u0026thinsp;\u0026lt;\u0026thinsp;0.60), substantial (0.60\u0026thinsp;\u0026lt;\u0026thinsp;κ\u0026thinsp;\u0026lt;\u0026thinsp;0.80) as well as perfect (0.80\u0026thinsp;\u0026lt;\u0026thinsp;κ\u0026thinsp;\u0026lt;\u0026thinsp;1). All statistical calculation was conducted with the help of SPSS 20.0 (version 20.0, IBM, Armonk, NY, United States) and medcalc (version 16.8.4, Mariakerke, Belgium). \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05 indicated a statistically significant difference.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eImaging features and the CEUS LI-RADS classification\u003c/h2\u003e \u003cp\u003eA total of 58 patients (median age, 54 years; range 34\u0026ndash;87 years) with 58 pathological confirmed cHCC-ICC nodules (median size, 24.5 mm, range: 10.0\u0026ndash;104.0 mm) were included in the current study. All cHCC-ICC nodules displayed arterial phase hyperenhancement (APHE), of which 44.8% (26/58) showed homogeneous APHE, 31.0% (18/58) exhibited heterogenous APHE, and 24.1% (14/58) presented rim APHE. By comparing with the contrast intensity of adjacent normal hepatic parenchyma, 58.6% (34/58) of cHCC-ICCs appeared to washout within 60s, and 32.8% (19/58) lesions illustrated marked washout as observed during the first 2 mins. According to CEUS LI-RADS (version 2017), 19 nodules (32.8%) were categorized as LR-5 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), 37 (63.8%) tumors demonstrated the CEUS features of LR-M (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), and enhancing thrombus was found in the portal vein of 3.4% cases (2/58), leading to LR-TIV classification (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCEUS features of the cHCC-ICC nodules\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEUS features\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eArterial phase hyperenhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58(100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnhanced patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomogeneous hyperenhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e26(44.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterogeneous hyperenhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(31.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRim-like hyperenhancement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(24.1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEarly washout(\u0026le;\u0026thinsp;60s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34(58.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWashout degree (as observed within the first 120s)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarked washout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(32.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMild washout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35(60.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo washout\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(6.9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor thrombus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEUS LI-RADS Category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLR-5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e19(32.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLR-M\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37(63.8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLR-IV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(3.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eData are presented as number (percentage); \u003cem\u003eCEUS\u003c/em\u003e: contrast-enhanced ultrasound; \u003cem\u003ecHCC-ICC\u003c/em\u003e: combined hepatocellular-cholangiocarcinoma; \u003cem\u003eLI-RADS\u003c/em\u003e: liver imaging reporting and data system.\u003c/p\u003e \u003cp\u003eThe clinical and pathological characteristics between patients with LR-5 or LR-M lesions were compared was and displayed in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. There was significant difference between the LR-5 and LR-M groups with regard to the tumor size [18.0(14.0,25.0) mm \u003cem\u003evs\u003c/em\u003e. 29.0(20.5,45.0) mm, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004], pathological grade (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.047) and HCC/ICC-component ratio within nodules (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.015). The remaining parameters did not differ between the two groups, including age, gender, tumor location, hepatitis, cirrhosis, steatosis, necrosis and MVI status (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In the LR-5 group, 57.9% (11/19) lesions showed HCC-predominance on histopathology. By contrast, 64.9% (24/37) of LR-M nodules were identified as ICC-predominance. The percentage of low-grade cHCC-ICC in the LR-5 group was 47.4% (9/19), higher than that of the LR-M group (21.6%, 8/37). Substantial or excellent agreement was achieved between the two radiologists concerning the interpretation of CEUS images and classification of CEUS LI-RADS categories, with the κ coefficients ranging from 0.788 to 0.890 (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of clinical and pathological characteristics among nodules classified as different CEUS LI-RADS categories.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClinical parameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLR-5(n\u0026thinsp;=\u0026thinsp;19)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLR-M(n\u0026thinsp;=\u0026thinsp;37)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e59.0(48.0,65.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54.0(48.0,63.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.634\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSex (male: female)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29/8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.108\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor number(single/multiple)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13/6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23/14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.644\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLocation (right/left/caudate lobe)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13/6/0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25/11/1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size(mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.0(14.0,25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29.0(20.5,45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.004*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;30mm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2(10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17(45.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.008*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;30mm\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e17(89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20(54.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEtiology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis B virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18(94.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35(94.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHepatitis C virus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.339\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePathological findings\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.015*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC-predominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11(57.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(29.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICC-predominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(64.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEqual proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3(15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2(5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCirrhosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14(73.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24(64.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.503\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSteatosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5(26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12(32.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.637\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNecrosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7(18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.327\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMicroscopic vascular invasion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6(31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.512\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.047*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow grade (ES grade I, I-II and II)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9(47.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh grade (ES grade II\u0026ndash;III, III, III-IV and IV)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10(52.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29(78.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTumor markers\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP\u0026thinsp;\u0026ge;\u0026thinsp;20, \u0026lt;400(ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8(42.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15(40.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.910\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAFP\u0026thinsp;\u0026ge;\u0026thinsp;400 (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4(10.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.846\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCA199\u0026thinsp;\u0026gt;\u0026thinsp;37 (U/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(21.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCEA\u0026thinsp;\u0026gt;\u0026thinsp;5 (ng/ml)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4(21.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5(13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.732\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003ecHCC-ICC\u003c/em\u003e: combined hepatocellular-cholangiocarcinoma; \u003cem\u003eCEUS\u003c/em\u003e: contrast-enhanced ultrasound; \u003cem\u003eLI-RADS\u003c/em\u003e: liver imaging reporting and data system; \u003cem\u003eHCC\u003c/em\u003e: hepatocellular carcinoma; \u003cem\u003eICC\u003c/em\u003e: intrahepatic cholangiocarcinoma; \u003cem\u003eAFP\u003c/em\u003e: alpha-fetoprotein; \u003cem\u003eCA199\u003c/em\u003e: cancer antigen 199; \u003cem\u003eCEA\u003c/em\u003e: carcinoembryonic antigen\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eMultivariate analysis\u003c/h2\u003e \u003cp\u003eBase on the univariate analysis results presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, significant parameters with a P-value\u0026lt;0.05 were brought into multivariate logistic regression analysis, including tumor size, pathological grade and HCC/ICC-component ratio within the nodule. Two independent influencing factors of CEUS LI-RADS classification were identified: nodule size (OR, 1.075; 95% CI, 1.008,1.147; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.028) and tumor component (OR, 4.118; 95% CI, 1.007,16.838; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.049) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Further analysis about the correlation between tumor components and the major imaging features of CEUS LI-RADS indicated that rim-like APHE were more common in cHCC-ICCs containing mainly ICC component than those of HCC-predominance (37.9% \u003cem\u003evs.\u003c/em\u003e 9.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039). The mechanism by which nodule size affected CEUS LI-RADS classification of cHCC-ICCs was investigated in the same way, which showed that rim-like and heterogeneous enhancement were more frequently observed in cHCC-ICCs with a diameter larger than 30mm, while lesions smaller than 30mm tended to show homogeneous enhancement (all \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05). In addition, both early (\u0026lt;60s) and marked washout were more common in tumors with a diameter larger than 3 cm (all \u003cem\u003eP\u003c/em\u003e\u0026lt;0.05) (Supplementary Tables\u0026nbsp;2 and 3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariate logistic regression analyses of potential influencing factors for the CEUS LI-RADS classification of cHCC-ICC\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk factors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWals\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eOdds ratio (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathological grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.669(0.421,6.623)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.466\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor components\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEqual proportion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.494(0.053,4.606)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.536\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eICC-predominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.118(1.007,16.838)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.049*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCC-predominant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e/\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTumor size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.233\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.075(1.008,1.147)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cem\u003eCEU\u003c/em\u003eS: contrast-enhanced ultrasound; \u003cem\u003eLI-RADS\u003c/em\u003e: liver imaging reporting and data system; \u003cem\u003ecHCC-ICC\u003c/em\u003e: combined hepatocellular-cholangiocarcinoma; \u003cem\u003eCI\u003c/em\u003e: confidence interval; \u003cem\u003eHCC\u003c/em\u003e: hepatocellular carcinoma; \u003cem\u003eICC\u003c/em\u003e: intrahepatic cholangiocarcinoma\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCEUS LI-RADS was developed by the ACR aiming at improving the diagnostic accuracy of HCC. Nodules in patients with a high risk of HCC were classified into 5 categories (LR-1 to LR-5) based on their CEUS manifestation. A higher grade means a higher possibility of HCC. Moreover, an LR-M category was set up for lesions that showed malignant characteristics but not HCC specific, and LR-TIV for nodules with portal cancerous thrombus[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Theoretically, as a non-HCC malignant tumor, cHCC-ICC was supposed to present CEUS features of LR-M category. However, imaging characteristics of both LR-5 and LR-M classification were observed in cHCC-ICC nodules according to several previous studies[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Similarly, the current study also found that a majority of cHCC-ICC nodules were categorized as LR-M (63.8%), and a relatively small proportion of tumors were classified as LR-5(32.8%). In order to find out the significant factors that influence the CEUD LR-RADS classification of cHCC-ICC nodules, clinical and pathological data between cHCC-ICC patients with LR-5 and LR-M nodules were compared in the present study. Our results indicated that the CEUS LI-RADS classification of cHCC-ICC nodules might be associated with its maximum diameter, pathological grade and HCC/ICC-component ratio. While multivariate analysis identified tumor size and the relative proportions of HCC and ICC components within cHCC-ICC as the independent influencing factors.\u003c/p\u003e \u003cp\u003ecHCC-ICC was characterized as the coexistence of HCC and ICC components. The proportion of HCC and ICC components within the cHCC-ICC nodule was widely considered to be associated with its imaging presentation[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. In the current study, we found that 57.9% of LR-5 nodules were HCC-predominant on histopathology. By contrast, 64.9% of LR-M nodules were found as ICC-predominance. Our study results were partly agreed with that of Yang et al.[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], in which all ICC-predominant cHCC-ICCs were categorized as LR-M (5 cases) and a high proportion of LR-5 lesions (100%) were HCC-predominant. However, a majority of LR-M nodules (81.5%) were also found as HCC-predominance in their research. The reason for the discrepancy could be attributed to tumor size and sample number. By further analyzing the correlation between tumor components and the specific imaging features of CEUS LI-RADS categories, we found that the HCC/ICC-component ratio within cHCC-ICC nodule acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern. There was 37.9% of ICC-predominant lesions displayed rim-like enhancement, significantly higher than that of nodules in HCC-predominance (9.1%, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.039). Ye et al.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] also reported this phenomenon, 84.6% of ICC-predominant cHCC-ICCs in their study manifested as rim-like enhancement, and merely 15.4% HCC-predominant nodules showed this characteristic in comparison. Notably, rim-like enhancement is one of the most prominent characteristics of LR-M classification[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. It was reasonable to speculate that when ICC turned to be the major constituent of cHCC-ICC, the blood supply of the tumor was not as rich as HCC and often leaded to necrosis in the central region. In addition, the hyper-enhancing regions of the tumor indicated a high density of malignant cells[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Pathological research about ICC suggested that there was large amount of malignant cells proliferated in the peripheral area while abundant fibrous stroma was located in the center of tumor[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. On the other hand, the rich blood supply from neovascularization and capillarized sinusoids inside the HCC component tended to result in homogeneous or heterogeneous enhancement on cHCC-ICCs with HCC-predominance, depending on the degree of blood supply and presence of necrosis in each lesion[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAs reported, tumor size might contribute to the CEUS presentation of primary liver cancers[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Consistently, CEUS LI-RADS classification of cHCC-ICC showed size-dependent characteristic in our study. Apart from serving as one of the classification bases of CEUS LI-RADS, tumor size was also found to have an impact on the enhanced pattern and washout features of cHCC-ICCs, thus leading to different CEUS LI-RADS classification. In our study, both rim-like and heterogeneous enhancement were more frequently observed in cHCC-ICCs with a diameter larger than 30mm, while lesions smaller than 30mm tended to show homogeneous enhancement. The study of Ye et al.[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] revealed a connection between tumor size and enhancement pattern as well. Such phenomenon might due to the intra-tumoral necrosis and liquefaction caused by insufficient blood flow of large tumor, and necrosis inside tumor was known to manifest as non-enhanced area on CEUS[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In the present study, a higher proportion of necrosis was observed in cHCC-ICCs classifying as LR-M compared to those categorizing as LR-5, which echoed this hypothesis. In addition, both early (\u0026lt;60s) and marked washout (as observed within the first 2 mins) were more common in tumors with a diameter larger than 3 cm in the current study. Association between tumor diameter and washout features of cHCC-ICC haven\u0026rsquo;t been discussed up to now. By reviewing and referring to the correlational research of HCC and ICC, a hypothesis was proposed that the washout features might be related to the cellular differentiation of cHCC-ICCs with different sizes. It was believed that tumor became increasingly dedifferentiated with the growth of nodule size[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. And the drainage vessels switched from hepatic veins to portal veins during this process, which resulted in rapid washout on CEUS[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. On the other hand, the rich sinusoids and trabecular pattern of cell cords inside tumors might lead to stagnation and slow clearing of ultrasound contrast agents. While such structures were scarce in poorly differentiated tumors [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Tumor presented high-grade on pathology also implied poorly differentiated. Univariate analysis in our study indicated that pathological grade played a role in the CEUS LI-RADS classification of cHCC-ICCs. The proportion of cHCC-ICCs manifested as high-grade tumors were higher in the LR-M group than the LR-5 nodules (P\u0026lt;0.05). However, this parameter was not recognized as an independent influencing factor of CEUS LI-RADS classification in cHCC-ICC, which in agreement with the conclusion of Herbay et al.[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e] and Yang et al.[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Their studies denied the correlation between histologic grade and tumor size of HCC. Therefore, the mechanism by which tumor size affects washout features of cHCC-ICCs as well as the relationship between pathological grade and CEUS LI-RADS classification of cHCC-ICCs warrant further exploration.\u003c/p\u003e \u003cp\u003ePreoperative differentiation of HCC from the non-HCC malignancies including ICC and cHCC-ICC was necessary since they have different preferred treatment options and prognosis. However, a good proportion of cHCC-ICCs were still miscategorized as definite HCCs (the LR-5 category) by CEUS LI-RADS, raising concern over the potential false positive diagnosis of HCC. Nonetheless, the consolation was that such misclassification of the LI-RADS category might cause small impact to the management of patients at risk of HCC due to the low incidence of cHCC-ICC. In addition, the survival outcome of cHCC-ICC manifesting imaging features of LR-5 category was reported to superior than that of nodules in LR-M category[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Stratification of cHCC-CCA according to the CEUS LI-RADS categories (LR-5 or LR-M) might play a role in prognosis prediction.\u003c/p\u003e \u003cp\u003eOur study had some limitations. First, as a retrospective study performed in a single center, patient selection bias was inevitable, and the generalizability might be affected. Second, due to the uncommon of cHCC-ICC, the number of cases enrolled in our study was relatively small, of which tumors in ES grade I and IV were scarce. This might affect the reliability of our study results, such as the relationship between histologic grade and the CEUS LI-RADS classification of cHCC-ICC. What\u0026rsquo;s more, the number of nodules in the LR-TIV category was too small to make a statistical comparison, and the influence that cancer embolus caused on the CEUS LI-RADS classification of cHCC-ICC was undetermined. Therefore, a multicenter study based on a large sample size is further expected.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, CEUS LI-RADS classification of cHCC-ICC was significantly affected by tumor size and the relative proportion of HCC and ICC components within the lesion. The HCC/ICC-component ratio within the cHCC-ICC nodule acted on the CEUS LI-RADS classification mainly through influencing the enhanced pattern. Tumor size was significantly associated with the enhancement patterns and washout features.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ecHCC-ICC \u0026nbsp;combined hepatocellular- cholangiocarcinoma\u003c/p\u003e\n\u003cp\u003eHCC hepatocellular carcinoma\u003c/p\u003e\u003cp\u003eICC intrahepatic cholangiocarcinoma\u003c/p\u003e\u003cp\u003ePLC primary liver cancer\u003c/p\u003e\u003cp\u003eFLLs focal liver lesions\u003c/p\u003e\u003cp\u003eCEUS contrast-enhanced ultrasound\u003c/p\u003e\u003cp\u003eLI-RADS liver imaging reporting and data system\u003c/p\u003e\u003cp\u003eEFSUMB European Federation of Societies for Ultrasound in Medicine and Biology\u003c/p\u003e\u003cp\u003eMVI microvascular invasion\u003c/p\u003e\u003cp\u003eACR American College of Radiology\u003c/p\u003e\u003cp\u003eHBV hepatitis B virus\u003c/p\u003e\u003cp\u003eAFP alpha-fetoprotein\u003c/p\u003e\u003cp\u003eCA19-9 carbohydrate antigen 19\u0026thinsp;\u0026minus;\u0026thinsp;9\u003c/p\u003e\u003cp\u003eCEA carcinoembryonic antigen\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJingwen Bao and Zehua Nie have contributed equally to this work\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBeaufr\u0026egrave;re A, Calderaro J, Paradis V. 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Hepatocarcinogenesis: multistep changes of drainage vessels at CT during arterial portography and hepatic arteriography--radiologic-pathologic correlation. Radiology 2009;252:605-614.\u003c/li\u003e\n\u003cli\u003eYang D, Li R, Zhang XH, Tang CL, Ma KS, Guo DY, et al. Perfusion Characteristics of Hepatocellular Carcinoma at Contrast-enhanced Ultrasound: Influence of the Cellular differentiation, the Tumor Size and the Underlying Hepatic Condition. Sci Rep 2018;8:4713.\u003c/li\u003e\n\u003cli\u003eHonda H, Tajima T, Kajiyama K, Kuroiwa T, Yoshimitsu K, Irie H, et al. Vascular changes in hepatocellular carcinoma: correlation of radiologic and pathologic findings. AJR Am J Roentgenol 1999;173:1213-1217.\u003c/li\u003e\n\u003cli\u003evon Herbay A, Vogt C, Westendorff J, H\u0026auml;ussinger D, Gregor M. Correlation between SonoVue enhancement in CEUS, HCC differentiation and HCC diameter: analysis of 130 patients with hepatocellular carcinoma (HCC). Ultraschall Med 2009;30:544-550.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"abdominal-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aima","sideBox":"Learn more about [Abdominal Radiology](http://link.springer.com/journal/261)","snPcode":"261","submissionUrl":"https://submission.springernature.com/new-submission/261/3","title":"Abdominal Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"combined hepatocellular-cholangiocarcinoma, contrast-enhanced ultrasound, Liver Imaging Reporting and Data System, influencing factors","lastPublishedDoi":"10.21203/rs.3.rs-4627278/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4627278/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e \u003cp\u003eTo explore the factors that influence the contrast-enhanced ultrasound (CEUS) Liver Imaging Reporting and Data System (LI-RADS) classification of combined hepatocellular-cholangiocarcinoma (cHCC-ICC).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eBetween September 2014 to July 2020, the CEUS features of 58 patients with pathologically confirmed cHCC-ICC were retrospectively evaluated and assigned according to the CEUS LI-RADS (version 2017). The pathological characteristics of nodules categorizing as different CEUS LI-RADS categories were compared. Multivariate logistic regression analysis was conducted to explore potential factors that may influence the CEUS LI-RADS classification of cHCC-ICC.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAccording to CEUS LI-RADS, 32.8% (19/58), 63.8% (37/58), and 3.4% (2/58) were categorized as LR-5, LR-M, and LR-TIV, respectively. There was significant difference between the LR-M and LR-5 groups with regard to the pathological grade, nodule size, and HCC/ICC-component ratio of cHCC-ICC. Multivariate logistic regression analysis identified tumor size and the relative proportions of hepatocellular carcinomas (HCC) and intrahepatic cholangiocarcinomas (ICC) components within cHCC-ICC as the independent influencing factors.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTumor size and the relative proportion of HCC and ICC components within the nodule had a significant impact on the CEUS LI-RADS classification of cHCC-ICC.\u003c/p\u003e","manuscriptTitle":"Evaluation of combined hepatocellular-cholangiocarcinoma using CEUS LI-RADS: Correlation with pathological characteristics","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-17 20:04:19","doi":"10.21203/rs.3.rs-4627278/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-22T20:26:51+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-21T19:55:04+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-14T09:26:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"325775953978544839450782157033954759389","date":"2024-07-12T08:41:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"256984151185806273999419870201715820754","date":"2024-07-12T02:56:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"323944108968623283627108341765858811272","date":"2024-07-12T01:23:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"176532197044842012721346488256853699460","date":"2024-07-09T21:15:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-25T16:44:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-25T14:24:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-25T14:23:12+00:00","index":"","fulltext":""},{"type":"submitted","content":"Abdominal Radiology","date":"2024-06-24T03:55:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"abdominal-radiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aima","sideBox":"Learn more about [Abdominal Radiology](http://link.springer.com/journal/261)","snPcode":"261","submissionUrl":"https://submission.springernature.com/new-submission/261/3","title":"Abdominal Radiology","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"4ecc417b-235d-4e83-a4c8-14c93afbdb4a","owner":[],"postedDate":"July 17th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-22T19:31:23+00:00","versionOfRecord":{"articleIdentity":"rs-4627278","link":"https://doi.org/10.1007/s00261-024-04519-x","journal":{"identity":"abdominal-radiology","isVorOnly":false,"title":"Abdominal Radiology"},"publishedOn":"2024-08-16 15:57:15","publishedOnDateReadable":"August 16th, 2024"},"versionCreatedAt":"2024-07-17 20:04:19","video":"","vorDoi":"10.1007/s00261-024-04519-x","vorDoiUrl":"https://doi.org/10.1007/s00261-024-04519-x","workflowStages":[]},"version":"v1","identity":"rs-4627278","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4627278","identity":"rs-4627278","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}