Spectral computed tomography parameters for predicting vessels encapsulating tumor clusters (VETC) pattern in hepatocellular carcinoma: a pilot study

Introduction

Hepatocellular carcinoma (HCC) constitutes 75–85% of primary liver cancer cases (1) and ranks as the third most prevalent malignant tumor globally (2). Despite the application of surgical resection, the primary treatment modality for HCC, the 5-year rates of metastasis and recurrence remain high (2,3). Vessels encapsulating tumor clusters (VETC), characterized by endothelial cells surrounding tumor cell nests, are a prevalent and recently identified microvascular pattern in HCC (4,5). Unlike metastasis mediated by the conventional epithelial-mesenchymal transition (EMT), VETC exhibits enhanced metastatic potential, leading to significantly reduced overall and recurrence-free survival (RFS) rates and thus poorer outcomes in patients with HCC (6). However, VETC detection primarily relies on postoperative immunohistochemical examinations, which are constrained by invasive tissue acquisition requirements. These inherent drawbacks—including limitations in pathology sampling and delayed diagnostic availability—frequently compromise assessment completeness. Consequently, there is an urgent need to develop a preoperative, noninvasive, and precise approach for predicting VETC patterns in HCC, which would aid in personalized therapeutic strategies and prognostic evaluation prior to surgical intervention. Spectral computed tomography (CT) offers multiparameter functional imaging capabilities, allowing for the noninvasive and quantitative assessment of tumor pathology (7,8). The relationship between multiparameter spectral CT and VETC patterns has not been extensively investigated. This study thus aimed to assess the value of multiparameter spectral CT in predicting VETC patterns in HCC and develop a novel preoperative noninvasive prediction method integrating multiparametric spectral CT biomarkers. We present this article in accordance with the STARD reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2077/rc).

Methods

Study design and patient population

This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and received ethical approval from the Ethics Committees of Weihai Central Hospital Affiliated to Qingdao University (approval No. 2022-121-01). The requirement for individual consent was waived due to the retrospective nature of the analysis. This retrospective cohort study consecutively enrolled 50 patients with HCC who were admitted to Weihai Central Hospital Affiliated to Qingdao University between May 2020 and May 2023. The inclusion criteria were as follows: (I) primary HCC confirmed by postoperative pathology and CD34 immunohistochemistry; (II) liver contrast-enhanced spectral CT conducted ≤7 days before resection; and (III) complete serum biomarkers tests [alpha-fetoprotein (AFP), protein-induced by vitamin K absence or antagonist-II (PIVKA-II), carcinoembryonic antigen (CEA)] completed ≤7 days before resection. Meanwhile, the exclusion criteria were as follows: (I) a history of HCC recurrence; (II) administration of preoperative anticancer treatment; (III) significant respiratory motion artifacts in the images; and (IV) biopsy-proven diagnosis. VETC(+) was defined according to a previous publication (9) as CD34⁺ vascular encapsulation occupying ≥5% of the tumor area as confirmed by CD34 immunostaining; otherwise, a VETC(−) status was confirmed. The flow diagram depicting the patient selection process is shown in Figure 1.

Figure 1 Flowchart of participant enrollment. AFP, alpha-fetoprotein; CEA, carcinoembryonic antigen; CT, computed tomography; HCC, hepatocellular carcinoma; PIVKA-II, protein-induced by vitamin K absence or antagonist-II; VETC, vessels encapsulating tumor clusters.

CT image acquisition

All imaging examinations were conducted using a dual-layer detector spectral CT device (IQon, Philips Healthcare, Best, the Netherlands). Scanning sequences included unenhanced phase (UP), arterial phase (AP), portal phase (PP), and equilibrium phase (EP). The technical parameters were as follows: a tube voltage of 120 kVp, a tube current automatically adjusted by tube current modulation (TCM), a detector collimation of 0.625 mm × 64 mm, a rotation speed of 0.5 s, and a pitch factor of 1.234. For contrast-enhanced imaging, ioversol (320 mgI/mL) was administered intravenously via an antecubital vein using a dual-barrel high-pressure syringe at a dose of 1.5 mL/kg body weight and a flow rate of 3.0 mL/s. SmartPrep dynamic monitoring technology was used to synchronize scanning initiation. The AP scan was automatically triggered once the region of interest (ROI) reached a predefined threshold of 100 Hounsfield units (HU). Subsequent phases were acquired with fixed delays: the PP was triggered at 40 s after AP initiation and the EP at 120 s after AP initiation.

Image processing and analysis

Spectral-based image (SBI) data were uploaded to the postprocessing software (Philips IntelliSpace Portal, Philips Healthcare; version 9.0) on a dedicated workstation for spectral CT, and the morphological features of the HCC were evaluated on 40-keV virtual monoenergetic images (VMIs). Uneven or nonsignificant enhancement of the tumor in the AP can affect the accuracy of the selected ROI. Therefore, quantitative spectral parameters, including iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff), and energy spectrum curve slope (λ), in the PP and EP were analyzed. NIC was calculated as the ratio of lesion IC to aortic IC (NIC = IC_lesion/IC_aorta) at the same section. λ was defined as the difference in CT numbers at 40 and 90 keV, divided by the energy difference: λ = [CT number (40 keV) − CT number (90 keV)]/(90−40) keV. The 40-keV energy level was selected as it typically shows the greatest enhancement; for the higher energy level, values between 70 and 150 keV are commonly reported. The selection of 90 keV as the upper energy threshold was based on preliminary observations that CT values of lesions show minimal change at energy levels above 90 keV. Qualitative and quantitative assessments of the lesions were performed by two radiologists with more than 8 years of experience in abdominal radiology. Following previous literature (10) and Liver Imaging Reporting and Data System (LI-RADS) v.2018 (11), we selected the following key features for assessment: (I) tumor size (maximum radial length of the main lesion in axial position); (II) intratumor vascularity (persistent vascular within the tumor in AP); (III) nonrim AP hyperenhancement; (IV) nonperipheral PP washout; (V) a well-defined capsule (most or all of the tumor clearly demarcated from the surrounding hepatic parenchyma, with circumferential enhancement visible in the PP or the EP); (VI) a nonsmooth tumor margin (bud-like projections protruding from the tumor margins or local infiltration); (VII) intratumor necrosis (at the level of the largest radial dimension of the tumor in the axial plane and ≥20% of the nonenhanced area across phases); and (VIII) intratumor AP hypovascular component (IAPHC; ≥20% hypoenhanced viable tumor during the AP).

Multiple ROIs were selected from the same lesion, and the final values were averaged across all measurements, with necrotic, calcified, and vascular areas being excluded.

Follow-up after surgery

Patients underwent regular follow-up visits at 2- to 3-month intervals after surgery. RFS was as defined as the interval from surgical resection to radiologically confirmed tumor recurrence. Recurrence was confirmed through at least two radiological examinations [CT, magnetic resonance imaging (MRI), or ultrasound]. Follow-up was terminated upon confirmed local recurrence or distant metastasis, with the date of recurrence or metastasis recorded as the termination point for RFS; for nonrecurrent cases, the end of the follow-up period was June 1, 2024.

Statistical analysis

All statistical analyses were performed using SPSS 23.0 (IBM Corp., Armonk, NY, USA), MedCalc version 22.0 (MedCalc Software Ltd., Ostend, Belgium), and GraphPad Prism version 9.0 (Dotmatics, Boston, MA, USA). Quantitative data with a normal distribution are presented as the mean ± standard deviation (SD), and the independent samples t-test was employed to compare the data between the two groups. Clinical data and qualitative parameters of spectral CT for the two groups were compared using the Chi-squared test. Variables with statistical significance underwent multivariate logistic regression so that the independent VETC predictors could be identified. Finally, the receiver operating characteristic (ROC) curve was used to evaluate the predictive performance of each single parameter that had a significant difference and the combined model. The related 95% confidence interval (CI), sensitivity, and specificity were evaluated with area under the curve (AUC) comparisons performed with the DeLong test. Statistical significance was defined as a P value ≤0.05. Survival curves were generated with the Kaplan-Meier method and compared via the log-rank test.

Results

Clinical characteristics

The VETC(+) (n=21) and VETC(−) (n=29) cohorts demonstrated comparable demographic profiles, with mean ages of 61.43±7.78 and 60.69±9.39 years, respectively (P>0.05). The AFP levels were significantly elevated in VETC(+) patients (P<0.05) (Table 1), while CEA and PIVKA-II showed no intergroup differences (P>0.05) (Table 1).

Qualitative spectral parameters in predicting VETC

As compared to VETC(−) tumors, VETC(+) HCC tumors demonstrated a significantly higher prevalence of IAPHC (P<0.05) (Table 2). However, no significant intergroup differences were observed regarding tumor size, nonrim AP hyperenhancement, nonperipheral PP washout, nonsmooth tumor margin, well-defined capsule, intratumor necrosis, or intratumor vascularity (all P values >0.05) (Table 2). Cases of HCC with VETC(+) and VETC(−) are shown in Figure 2.

Figure 2 Comparison of AP CT_Convention and CT_40keV-VMI images in VETC-positive/negative HCCs (red boxes indicate lesions). (A,B) In VETC-positive HCC, the tumor exhibited uneven and diffuse enhancement in the AP. The CT_40keV-VMI image revealed an IAPHC and necrotic regions within the tumor, which were more prominent as compared to the CT_Convention image. (C,D) In VETC-negative HCC, the tumor showed mild and homogeneous enhancement in the AP. The lesion appeared less distinct on the CT_Convention image, whereas it was clearly depicted on the CT_40keV-VMI image. AP, arterial phase; CT, computed tomography; CT_40keV-VMI, 40-keV virtual monoenergetic images CT; CT_Convention, conventional CT; HCC, hepatocellular carcinoma; IAPHC, intratumor arterial phase hypovascular component; VETC, vessels encapsulating tumor clusters.

Quantitative spectral parameters in predicting VETC

The results showed that patients with VETC(+) HCC exhibited elevated spectral parameters in the PP (IC: P=0.012; Zeff: P=0.031; λ: P=0.034) and in the EP (IC: P=0.002; Zeff: P=0.023; λ; P=0.028) (Table 3 and Figure 3). However, there were no significant differences in NIC between the two groups in either the PP or EP (P>0.05) (Table 3 and Figure 3). Cases of HCC with VETC(+) and VETC(−) are shown in Figure 4 and Figure 5, respectively.

Figure 3 Column charts showing the IC-PP (A), NIC-PP (B), Zeff-PP (C), λ-PP (D), IC-EP (E), NIC-EP (F), Zeff-EP (G), and λ-EP (H) of VETC(+) and VETC(−) HCCs. *, P<0.05; ns, not significant (P>0.05). HCC, hepatocellular carcinoma; IC-EP, iodine concentration in the equilibrium phase; IC-PP, iodine concentration in the portal phase; λ-EP, energy spectrum curve slope of the equilibrium phase; λ-PP, energy spectrum curve slope of the portal phase; NIC-EP, normalized iodine concentration in the equilibrium phase; NIC-PP, normalized iodine concentration in the portal phase; VETC, vessels encapsulating tumor clusters; Zeff-EP, effective atomic number in the equilibrium phase; Zeff-PP, effective atomic number in the portal phase.

Figure 4 Representative histopathological and radiological images of an HCC case with VETC (59-year-old female). (A-D) Conventional image, IC map, Zeff map, and spectral curve of the PP (red arrows indicate the lesions), respectively. (E-H) Conventional image, IC map, Zeff map, and spectral curve of the EP (red arrows indicate the lesions), respectively. (I,J) Typical VETC pattern tumor cluster captured by a web-like vascular network [(I) hematoxylin and eosin staining, magnification 100×; (J) CD34 immunohistochemical staining, magnification 100×]. AP, arterial phase; EP, equilibrium phase; HCC, hepatocellular carcinoma; HU, Hounsfield units; IC, iodine concentration; ROI, region of interest; VETC, vessels encapsulating tumor clusters; Zeff, effective atomic number.

Figure 5 Representative histopathological and radiological images of an HCC case without VETC (67-year-old male). (A-D) Conventional image, IC map, Zeff map, and spectral curve of the PP (red arrows indicate the lesions), respectively. (E-H) Conventional image, IC map, Zeff map, and spectral curve of the EP (red arrows indicate the lesions), respectively. (I,J) A classical capillary vascular pattern [(I) hematoxylin and eosin staining, magnification 100×; (J) CD34 immunohistochemical staining, magnification 100×]. AP, arterial phase; EP, equilibrium phase; HCC, hepatocellular carcinoma; HU, Hounsfield units; IC, iodine concentration; ROI, region of interest; VETC, vessels encapsulating tumor clusters; Zeff, effective atomic number.

Risk factors of predicting VETC and ROC analysis

Multivariate logistic regression identified two independent predictors of VETC positivity: IAPHC and IC-EP (Table 4). A combined model was constructed, and the ROC curve showed that the AUC of IAPHC, IC-EP, and the combined model were 0.672, 0.766, and 0.810, respectively (Table 5, Table S1, Figure 6, and Figure S1). The AUC of the combined model for predicting VETC(+) HCC was greater than that of IAPHC and IC-EP. The difference in AUC value between the combined model and IAPHC was statistically significant (Z=2.34; P=0.02), while the difference between the combined model and IC-EP was not (Z=0.98; P=0.33).

Figure 6 ROC curves of the IAPHC, IC-EP, and the combined model for predicting the VETC pattern. IC-EP, iodine concentration in the equilibrium phase; IAPHC, intratumor arterial phase hypovascular component; ROC, receiver operating characteristic; VETC, vessels encapsulating tumor clusters.

Prognostic evaluation

Recurrence was detected in 15 of 50 patients (30%) during follow-up, and the RFS rates had significantly different between groups. Patients in the VETC(+) group had significantly poor RFS rates than did those in the VETC(−) group at 1-year (75.2% vs. 86.2%), 2-year (44.5% vs. 79.6%), and 3-year follow-up (44.5% vs. 79.6%). The Kaplan-Meier curves for RFS were significantly different between the two groups (log-rank χ²=5.31; P=0.02) (Figure 7).

Figure 7 Kaplan-Meier curve for postoperative RFS according to the histological VETC pattern. Patients in the VETC(+) group exhibited poorer RFS than did those in the VETC(−) group (P=0.02). RFS, recurrence-free survival; VETC, vessels encapsulating tumor clusters.

Discussion

VETC is a recently discovered HCC metastatic pattern, and the research related to its radiology-based preoperative prediction remains in the exploratory stage. In this study, we employed spectral CT multiparameter features to predict the VETC pattern for noninvasive VETC detection, which may offer valuable guidance for treatment planning and prognosis assessment.

In this study, AP 40-keV VMI was used to visualize intratumor hypoenhanced areas, and the results showed that IAPHC was significantly correlated with VETC(+) HCC. These findings are consistent with previous work on contrast-enhanced MRI. For instance, Fan et al. (12) identified AP tumors with diffuse and heterogeneous enhancement as independent predictive factors for VETC(+) HCC; Chen et al. (13) noted a significant correlation between tumor heterogeneous enhancement patterns (uneven enhancement with septa and irregular ring-like structures) and VETC(+) HCC. In our study, we found inhomogeneous and heterogenous intratumoral enhancement. We speculate that this may be related to the unique vascular structure of VETC. VETC is composed of functional blood vessels with blood perfusion, and these functional sinusoidal vessels, arranged in cobweb-like networks, can compress the adjacent vasculature, leading to insufficient local blood supply (4); moreover, this cobweb-like vascular structure may also impede the flow of blood, slowing down the inflow and outflow of the iodine contrast agent, which manifests as a hypointensified area inside the tumor in the AP. The above speculation was also consistent with the Lan et al. (14), who found that ultrasonography of VETC(+) HCC first revealed circumferential hyperenhancement around the periphery of the tumor and then filling in the center in the form of stripes and fissures, with a prolonged filling time per unit diameter compared with that of VETC(−) HCC. In their study, Rhee et al. (15) reported that 50.8% of macrotrabecular-massive (MTM)-HCC specimens exhibited VETC positivity, with a correlation between IAPHC and MTM-HCC. Approximately 77% of MTM-HCCs showed intra-arterial stage tumors or diffuse areas of hypoenhancement with peripheral or speckled areas of hyperenhancement. This radiopathological correlation was attributed to two distinct mechanisms: intratumor necrosis and abundant fibrotic mesenchyme within the tumor (which is enriched with VETC patterns in MTM-HCC). Therefore, we speculate that the abundant fibrotic mesenchyme within the tumor is a key determinant of IAPHC manifestation in VETC(+) HCC.

Our quantitative analysis demonstrated significantly elevated IC-PP and IC-EP in the VETC(+) HCC group as compared to the VETC(−) HCC groups. While angiogenesis is central to tumor growth and metastasis, quantitative analysis of angiogenesis in vivo remains challenging. Microvessel density (MVD) within tumors has shown promise as a biomarker. High MVD within tumors may be associated with angiogenesis and tumor invasiveness (16). Huang et al. (17) found increased intratumoral MVD in VETC(+) HCC, whereas in nontumor areas, MVD was not significantly different between the VETC(+) and VETC(−) groups, suggesting that VETC(+) HCC has increased vascularity within the tumor and is highly invasive. However, another study found that hypovascularity in VETC-HCC may arise from sinusoidal-pattern HCC due to low MVD (18). Similarly, Li et al. found a positive correlation between IC and NIC measured by spectral CT with MVD among patients with lung cancer (19); moreover, venous-phase IC had the strongest correlation with MVD and was also associated lung cancer pathological classification, tumor differentiation, tumor size, and intratumoral necrosis status. In our HCC study, we also found statistical differences in the IC in the EP between the two groups. Wang et al. examined the relationship between tumor angiogenesis and dynamic enhanced MRI features in HCC (20). Their analysis revealed that the MVD in the group with PP enhancement was higher than that of the group without enhancement. Meanwhile, delayed-phase ring-enhancement patterns correlated with increased MVD as compared the nonring enhancement patterns. High-MVD HCC maintained persistent enhancement of tumor in the PP and delayed phase. Despite the different enhancement mechanisms of MRI and CT, both may be related to tumor angiogenesis (20). Our results are similar to those of Li et al. (19) and Wang et al. (20), and our IC findings may be explained by the following three pathophysiological mechanisms. First, in VETC(+) HCC, elevated MVD increases intratumoral vascularity and blood perfusion, augmenting intratumoral iodine contrast agent content and IC. Second, the unique reticular vascular pattern of VETC may delay the outflow of contrast agent, resulting in iodine contrast agent retention and elevation of IC during the PP and EP (4). Third, the abundant fibrotic stroma within the tumor tissue manifests as delayed enhancement, and fibrotic components during the EP increase the iodine content within the lesion, thereby increasing IC (15). This may explain why the IC in the PP and EP was higher in the VETC(+) group than in the VETC(−) group in our study.

The results regarding IC and NIC are of particular interest and initially difficult to explain, as they deviate from the conclusions of many previous studies. Specifically, in research on gastric and lung cancers using spectral CT, NIC has often demonstrated superior diagnostic and predictive value as compared to IC (21,22). We believe this discrepancy may be attributed to two factors: patient characteristics and sample size limitations. Most patients included in this study had coexisting liver cirrhosis, and some were in the decompensated stage. The hemodynamic disturbances caused by complications of liver cirrhosis or concurrent heart failure could lead to differences between the IC within the lesion and the IC of the abdominal aorta (23). Additionally, the liver’s dual blood supply and potential presence of arteriovenous shunts in some HCC cases might have also contributed to this (24). Additionally, our relatively small sample size might have influenced the overall findings, particularly given the inclusion of a significant proportion of cases with decompensated liver cirrhosis combined with HCC.

This study further integrated IAPHC and IC-EP to construct a combined prediction model. The results showed that compared to single risk factors, the combined model demonstrated a significantly superior ability to predict VETC(+) HCC. This suggests that the combined model has better preoperative diagnostic efficacy and can provide useful auxiliary indicators for clinical treatment selection. Histologic VETC has been reported to be associated with a poor prognosis in patients with HCC in a number of studies (25,26), with which our results are consistent. This may be related to the VETC pattern, in which tumor nests form at the primary site and then actively protrude from the tumor mass as a whole, floating within the vascular lumen of the tumor stroma. Through migration and invasion, tumor cells traverse the vascular wall. During circulation, endothelial cell encapsulation protects the cancer cells from hypoxia and immune attacks, thus preventing tumor cells from being killed during the metastatic process (12,27).

This study involved certain limitations that should be acknowledged. First, the single-center retrospective design might have introduced selection bias. Second, the sample size of this study is small. Future studies with larger cohorts are warranted to verify these preliminary findings.

Conclusions

IAPHC and IC-EP may have significant application value in predicting VETC(+) HCC. Additionally, the combination of these two factors demonstrated improved diagnostic performance compared to IAPHC or IC-EP alone and may be an effective approach for the preoperative, noninvasive, and quantitative prediction of the VETC pattern.

Acknowledgments

The authors would like to thank the Weihai Key Laboratory of Interventional Minimally Invasive Technology based on Radiology, the Weihai Clinical Research Center for Radiology, and the Shandong Provincial Key Medical and Health Laboratory of Iron Metabolism Clinical Research for their support of this study.

Footnote

Reporting Checklist: The authors have completed the STARD reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-2077/rc

Funding: This work was supported by the Shandong Province Medical and Health Science & Technology Project (No. 202209010213).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2077/coif). X.C. is an employee of Philips Healthcare, the manufacturer of the CT system used in this study. The other authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work by ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki (as revised in 2013) and was approved by the Ethics Committees of Weihai Central Hospital Affiliated to Qingdao University (approval No. 2022-121-01). The requirement for individual consent was waived due to the retrospective nature of the analysis.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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