Preoperative assessment of Ki-67 expression in hepatocellular carcinoma using a multi-parametric spectral CT approach

Introduction

Hepatocellular carcinoma (HCC) represented the sixth most common cancer and the third leading cause of cancer-related deaths worldwide in 2022 (1). The 5-year survival rate for HCC is approximately 18% (2,3), with a median overall survival of only 20–30 months (4). A significant factor contributing to this poor prognosis is the high recurrence rate following curative liver resection, which has been reported to exceed 70% within 5 years (3,5).

Ki-67 is a biomarker for cell proliferation and is associated with the prognosis of malignant tumors. The Ki-67 proliferation index reflects the level of proliferative activity and demonstrates a significant correlation with tumor grading (6). In HCC, Ki-67 expression serves as an independent prognostic indicator for disease-free survival and overall survival (7). High Ki-67 expression is a significant risk factor contributing to the elevated recurrence rate and poor prognosis following curative resection of HCC (8,9). Unfortunately, Ki-67 assessment is typically performed pathologically, necessitating careful identification across multiple regions of resected specimens. Thus, accurate preoperative detection of Ki-67 status in HCC patients could provide critical clinical insights to improve survival rates and outcomes.

Compared to conventional computed tomography (CT), spectral CT offers multi-parametric imaging, quantitative analysis, and spectral evaluation (10). Previous studies have indicated that quantitative parameters from spectral CT can predict Ki-67 expression in lung, breast, and colorectal cancers (11-14). However, there are limited reports on the correlation between spectral CT and Ki-67 expression in liver cancer, with only two studies demonstrating a positive correlation between the quantitative parameters of intratumoral tissue and Ki-67 levels (15,16). Furthermore, recurrence or metastasis of liver cancer predominantly occurs within the liver, highlighting the significant role of peritumoral tissues in the dissemination of cancer cells (17), which is crucial for prognostic prediction (18). Nevertheless, no studies have evaluated the qualitative and quantitative parameters of spectral CT in both intratumoral and peritumoral regions to predict Ki-67 expression in HCC. Thus, the objective of this study was to determine whether assessments based on spectral CT imaging of intratumoral and peritumoral regions can yield valuable insights into Ki-67 expression status in liver cancer. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2313/rc).

Methods

Patients

This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. This prospective study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (approval No. 2024-E691-01) and written informed consent was provided by all patients prior to participation. Between February 2023 and February 2024, a total of 163 patients with suspected HCC based on ultrasound or magnetic resonance imaging (MRI) underwent preoperative spectral CT imaging. The inclusion criteria were as follows: (I) pathologically confirmed primary HCC; (II) spectral CT examination within one week prior to surgery; and (III) availability of complete clinical and imaging data. The exclusion criteria were as follows: (I) preoperative anticancer treatment; and (II) images that failed to meet quality control standards. The patient selection flowchart for the study is shown in Figure 1.

Figure 1 Flowchart illustrating the patient selection process in this study. CT, computed tomography; HCC, hepatocellular carcinoma.

Ki-67 assessment

The Ki-67 proliferation index was determined by two pathologists (with 5 and 15 years of experience, respectively) using high-power microscopy (×400). They randomly selected 10 fields on each slide and recorded a total of 1,000 cells. The percentage of positively stained Ki-67 nuclei was calculated semi-quantitatively. The Ki-67 index was initially assessed by the junior physician and ultimately determined by the senior physician. The Ki-67 index was defined as the percentage of Ki-67-positive nuclei. Based on the median Ki-67 expression index in this study, patients were classified into two groups: a high Ki-67 expression group (more than 20% positive cells) and a low Ki-67 expression group (20% or fewer positive cells).

Spectral CT protocol

All examinations were conducted using a GE Revolution CT scanner (GE Healthcare, Chicago, IL, USA), with patients positioned supine and head-first. A conventional non-contrast scan of the upper abdomen was performed at a tube voltage of 120 kV, with automatic selection of tube current, covering from the diaphragm to the lower poles of the kidneys. A high-pressure injector administered the contrast medium via the antecubital vein, at a dosage of 1.5 mL/kg body weight at a rate of 4.5 mL/s, followed by a 30-mL saline flush at the same rate. Three-phase spectral enhanced scans were conducted approximately at 33, 65, and 127 seconds post-contrast injection to obtain arterial, portal venous, and delayed phase images, respectively. Gemstone spectral imaging (GSI) utilized spiral scanning with instantaneous switching between 80 and 140 kVp, with tube current automatically selected by GSI Assist and 60% adaptive statistical iterative reconstruction-V (ASiR-V). Image reconstruction involved combining the non-contrast and three-phase spectral enhanced data with 50% ASIR-V, resulting in a slice thickness and interval of 1.25 mm.

Image analysis and data collection

Using the spectral reconstruction algorithm on an Advantage Windows server (version 4.7, GE Medical Systems), images of 40 keV virtual monochromatic imaging (VMI), 70 keV VMI, and iodine concentration map (IC Map) were generated. Two radiologists (a senior physician and a junior physician) independently analyzed the spectral CT images of 42 lesions, blinded to clinical and pathological data. Thereafter, the junior radiologist delineated the remaining 52 lesions.

Initially, tumor margins were identified on the 70 keV VMI images from the arterial (AP) and portal venous phase (PVP). Regions of interest (ROIs) with a diameter of 8 mm were manually outlined as follows: (I) tumor: three ROIs were delineated in the solid portion of the tumor, avoiding vascular areas, necrotic regions, and tumor edges, based on the maximum diameter; if the short diameter of the solid portion was less than 8 mm, the largest possible ROI was selected; (II) peritumoral: draw three ROIs within 10 mm of the tumor margin; draw three ROIs across the tumor margin (with approximately half inside and half outside the tumor); (III) abdominal aorta: an ROI was drawn at the same slice level as the lesion, avoiding vessel edges and calcifications. The ROIs were then copied to the corresponding slices of other spectral parameter images (40 keV VMI, 70 keV VMI, and IC Map) to measure the respective values.

During the equilibrium phase, ROIs were delineated solely on the IC Map: (I) tumor: three ROIs were placed within the solid portion of the tumor, avoiding areas of necrosis; (II) abdominal aorta: one ROI was delineated on the abdominal aorta at the same slice level as the lesion, avoiding the vessel margins and calcifications (Figure 2).

Figure 2 Flowchart for region of interest delineation in arterial and portal venous phase. IC Map, iodine concentration map; ROI, region of interest; VMI, virtual monochromatic imaging.

The normalized iodine concentration (NIC) for both AP and PVP was calculated using the formula: NIC = IC lesion/IC abdominal aorta. Additionally, the slope of the spectral curve (λHU) was calculated using: λHU = (CT40 keV − CT70 keV)/(70 keV − 40 keV), representing the difference in CT values at two energy levels divided by the energy difference. The extracellular volume (ECV) fraction was computed as follows: ECV = (1 − hematocrit) × (iodine concentration of the lesion during the equilibrium phase/iodine concentration of the abdominal aorta at the same level during the equilibrium phase).

Quality control of ROI delineation

In the 70 keV VMI mode, the liver is initially evaluated to identify slices where tumor margins are clearly delineated and there is adequate surrounding tissue for ROI placement. The selected slices should also contain relatively high-density solid components within the tumor and exhibit the largest possible diameter. If delineating tumor margins proves challenging in the 70 keV VMI, the IC map can be consulted. Should it still be difficult to identify a suitable slice that meets these criteria, a senior radiologist will be consulted to determine the appropriate slice or exclude the patient from the study. The system is configured to generate ROIs with a diameter of 8 mm. During ROI placement, care must be taken to avoid vascular regions, areas of tumor necrosis, and calcifications. Since the 40 keV VMI, 70 keV VMI, and IC map are displayed simultaneously, the 10 ROIs identified in the 70 keV VMI can be readily copied to corresponding slices in the other two images with a single click. If the measured data between the two observers show significant discrepancies, the ROIs will be redrawn. When delineating ROIs on PVP images, the placement of the 10 ROIs should be as similar as possible to their counterparts in the AP. This allows for verification of the correctness of the AP ROIs outlined in the previous step. Should any discrepancies be identified, the AP ROIs should be redrawn (Figure 3).

Figure 3 Imaging examination of a 54-year-old female patient with a 9.1-cm single hepatocellular carcinoma. ROI123 outlines the solid part within the tumor, ROI456 is within 10 mm of the tumor margin, ROI789 spans across the tumor margin, and ROI10 delineates the abdominal aorta at the same level. The first row (A-D) represents the delineations by Reader 1, whereas the second row (E-H) represents those by Reader 2. (A,E) Arterial phase 70-keV VMI; (B,F) arterial phase iodine maps, showing intratumoral NIC-AP of 0.22 and 0.18, peritumoral NIC-AP (<1 cm) of 0.09 and 0.09, and transtumoral NIC-AP of 0.15 and 0.14, respectively; (C,G) portal venous phase 70-keV VMI; (D,H) portal venous phase iodine maps, showing intratumoral NIC-PVP of 0.50 and 0.49, peritumoral NIC-PVP (<1 cm) of 0.67 and 0.65, and transtumoral NIC-PVP of 0.64 and 0.63, respectively. AP, arterial phase; IC Map, iodine concentration map; NIC, normalized iodine concentration; ROI, region of interest; VMI, virtual monochromatic imaging; PVP, portal venous phase.

Statistical analysis

Statistical analyses were conducted using the software SPSS 23.0 (IBM Corp., Armonk, NY, USA). The reliability of the spectral parameter assessments of 42 lesions by two observers was measured using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Clinical and imaging data from patients meeting the inclusion and exclusion criteria were collected, and differences in spectral CT parameters among groups based on Ki-67 expression levels were analyzed. Both Pearson and Spearman correlation analyses were employed to assess the relationship between spectral CT parameters and Ki-67 indices.

Results

In this study, a total of 163 patients underwent scanning. Cases were excluded based on the following criteria: 18 cases with postoperative pathology indicating non-HCC, 12 cases with incomplete clinical and pathological data, 21 cases with poor image quality, 21 cases with a history of preoperative antitumor treatment, and 2 cases where the scanning time was more than one week apart from surgery. This resulted in a final cohort of 89 patients, encompassing 94 lesions.

Patient clinical characteristics

A total of 94 eligible lesions were included in this study. The clinical characteristics of the participants are summarized in Table 1. Significant differences were observed between the low and high Ki-67 expression groups in terms of age and alpha-fetoprotein (AFP) levels (P<0.05).

Inter-observer consistency of quantitative parameters

The measurements of spectral CT quantitative parameters demonstrated good inter-observer consistency, with an ICC >0.8 (Table 2). Furthermore, Bland-Altman analysis was conducted, with the majority of data points falling between +1.96 standard deviation (SD) and −1.96 SD (Figure 4).

Figure 4 Bland-Altman analysis of the measurement data by two radiologists. AP, arterial phase; ECV, extracellular volume; NIC, normalized iodine concentration; SD, standard deviation; PVP, portal venous phase; λHU, slope of the spectral Hounsfield unit curve.

Value of spectral CT imaging features in evaluating Ki-67 expression

Imaging features of HCC assessed by CT included tumor size, presence of cirrhosis, number of tumors, tumor margins, peritumoral enhancement in the AP, capsule integrity, and large vessel invasion. Notably, a significant difference in capsule integrity was observed between the low and high Ki-67 expression groups (P<0.05) (Table 3).

Value of spectral CT quantitative parameters in evaluating Ki-67 expression

Significant differences were observed between the low and high Ki-67 expression groups regarding intratumoral NIC during the arterial phase (NIC-AP), intratumoral NIC during the portal venous phase (NIC-PVP), AP slope, PVP slope, and ECV fraction (P<0.05) (Table 4). Additionally, Ki-67 expression in HCC exhibited negative correlations with intratumoral NIC-AP, intratumoral NIC-PVP, AP slope, PVP slope, and ECV (P<0.05), as detailed in Table 5.

Discussion

In this study, patients within the high Ki-67 expression group were generally younger, exhibited higher AFP levels, and presented with incomplete or absent capsules. These findings are consistent with the observations made by Wu et al. (19) and Xu et al. (15). Elevated AFP levels and incomplete capsules have been associated with increased invasiveness in HCC (20,21).

Among the quantitative parameters derived from spectral CT, significant differences were observed between the low and high Ki-67 expression groups in intratumoral NIC-AP, NIC-PVP, AP slope, PVP slope, and ECV, all of which demonstrated negative correlations.

Regarding the slopes, these findings align with the results from Chen et al. (14) and Wang et al. (22), suggesting that variations in the chemical molecular structures of different substances result in distinct energy attenuation curves (23). This underscores the significant correlation observed between Ki-67 expression and slopes in HCC.

Intratumoral NIC-AP and NIC-PVP also serve to differentiate Ki-67 expression status, aligning with the findings of Xu et al. (15), which suggest that standardized ICs may reflect Ki-67 levels. Iodine maps can provide preliminary evaluations of tumor blood supply and hemodynamics based on ICs (24).

Meanwhile, Xu et al. (15) reported a positive correlation between intratumoral NIC-AP, NIC-PVP, and Ki-67, which contrasts with our findings. Emerging evidence suggests that in HCC, a high tumor proliferation rate is frequently associated with the development of a hypoxic microenvironment (25). Although hypoxia induces the expression of pro-angiogenic factors such as erythropoietin and vascular endothelial growth factor (VEGF), the resulting angiogenesis is often compromised by disorganized endothelial cell alignment, leading to the formation of non-functional or abnormal vessels (26). Furthermore, the rapid proliferation of cancer cells generates significant solid stress, which can compress intratumoral blood vessels and subsequently impair blood flow (27). Consequently, high Ki-67 expression, a marker of robust cell proliferation, may paradoxically result in reduced intratumoral blood supply.

Additionally, we hypothesize that this phenomenon may be associated with the placement of the ROI. In our study, establishing a one-to-one correspondence between the ROIs delineated on CT images and those on histopathological sections posed significant challenges. Prior research has suggested that in poorly differentiated HCC, the hepatic cancer tissue surrounding the tumor may necessitate an increased blood supply due to its invasive proliferative characteristics (28,29), leading to relatively higher ICs.

Regarding ECV, Wang et al. (30) showed a positive correlation between ECV derived from spectral CT and pathological immunohistochemistry in breast tumors, which also contradicts our findings. The ECV indicates that iodine more freely distributes in the plasma and extracellular space during measurement, with the tumor-to-aorta ratio representing the interstitial proportion (31). A previous study demonstrated an association between ECV and the degree of liver fibrosis (32). The accumulation of extracellular matrix is accompanied by an expansion of extracellular water, which serves as the distribution space for contrast agents. However, ECV can also be influenced by other factors. For example, hepatocyte swelling due to hepatic steatosis can compress the extracellular space and reduce ECV, whereas inflammation and venous congestion can induce edema, leading to an increase in ECV (33). To date, no studies have explored the potential of ECV to predict Ki-67 expression in HCC. Future research may focus on elucidating the impact of these confounding factors on liver ECV, thereby providing a more comprehensive understanding of its role in tumor biology.

In this study, the quantitative parameters of the peritumoral region were unable to differentiate between the high and low Ki-67 expression groups. Previous studies have shown that as liver fibrosis progresses, there is a reduction in liver parenchymal volume and microcirculatory changes, leading to increased hepatic resistance, reduced portal venous flow, and compensatory increases in hepatic arterial flow (34,35), all of which are correlated with the severity of fibrosis (36). Although no significant difference in the presence of cirrhosis was observed between the high and low Ki-67 expression groups in this study, the heterogeneity in fibrosis severity may have influenced the quantitative analysis of the peritumoral region. Currently, the quantitative analysis of the peritumoral region is predominantly conducted using radiomics. Studies have demonstrated that a 2-mm and a 5-mm peritumoral margin offer robust diagnostic performance for predicting microvascular invasion (MVI) in HCC and Ki-67 expression in breast cancer, respectively (37-39). However, manual delineation of ROIs poses challenges in achieving such precise margins and introduces inherent subjectivity, potentially impacting experimental outcomes. Future research should investigate the application of radiomics to further elucidate the relationship between peritumoral margins and Ki-67 expression in HCC.

In conclusion, multiple factors affect quantitative tumor analysis, including the tumor microenvironment, scanning techniques, and physiological changes linked to comorbidities. Further investigation is warranted to elucidate the specific mechanisms underlying these influences. Currently, no guidelines define the criteria for stratifying HCC patients into high and low Ki-67 expression groups. Therefore, large-scale, multicenter studies with more standardized protocols are necessary to further elucidate the relationship between quantitative spectral CT parameters and Ki-67 expression in HCC.

Conclusions

The qualitative and quantitative parameters derived from intratumoral spectral CT offer valuable insights for distinguishing between low and high Ki-67 expression in HCC.

Acknowledgments

None.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-24-2313/rc

Funding: This study was supported by the National Natural Science Foundation of China (No. 82060310).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-24-2313/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in 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 and its subsequent amendments. This study was approved by the Medical Ethics Committee of the First Affiliated Hospital of Guangxi Medical University (approval No. 2024-E691-01). Written informed consent was provided by all patients prior to participation.

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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