Abstract
Purpose
To develop a nomogram using clinical features and the MRI parameters for preoperatively predicting the expression of Ki-67 in patients with hepatocellular carcinoma (HCC).
Methods
One hundred and forty patients (training cohorts: n = 108; validation cohorts: n = 32) with confirmed HCC were investigated. Mann–Whitney U test, independent sample t-test, and chi-squared test were used to analyze the continuous and categorical variables. Univariate and multivariate logistic regression analyses were performed to examine the clinical variables and parameters from MRI associated with Ki-67 expression. As a result, a nomogram was developed based on these associations in patients with HCC. The performance of the nomogram was evaluated using the area under the receiver operating characteristic curve (AUC) and calibration curves.
Results
In the training set, multivariable logistic regression analysis revealed that lens culinaris agglutinin-reactive fraction of alpha-fetoprotein (AFP-L3) levels, protein induced by vitamin K absence or antagonist-II (PIVKA-II) levels, and tumor shape were independent predictors for Ki-67 expression (p < 0.05). These three variables and the apparent diffusion coefficient (ADC) value were used to establish a nomogram, while the ADC value was found to be a marginal significant predictor. The model demonstrated a strong ability to discriminate Ki-67 expression in both the training and validation cohorts (AUC = 0.862, 0.877).
Conclusion
A non-invasive preoperative prediction method, which incorporates MRI variables and clinical features was developed, and showed effectiveness in evaluating Ki-67 expression in HCC patients.
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12029-024-01051-5/MediaObjects/12029_2024_1051_Fig1_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12029-024-01051-5/MediaObjects/12029_2024_1051_Fig2_HTML.jpg)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12029-024-01051-5/MediaObjects/12029_2024_1051_Fig3_HTML.png)
![](http://media.springernature.com/m312/springer-static/image/art%3A10.1007%2Fs12029-024-01051-5/MediaObjects/12029_2024_1051_Fig4_HTML.png)
Similar content being viewed by others
Availability of Data and Materials
The datasets generated and/or analyzed during the current study are not publicly available due to our next research involving some data, but are available from the corresponding author on reasonable request.
References
EASL clinical practice guidelines. management of hepatocellular carcinoma. J Hepatol. 2018;69(1):182–236.
Xu J. Trends in liver cancer mortality among adults aged 25 and over in the United States, 2000–2016. NCHS Data Brief. 2018;314:1–8.
Schobert IT, Savic LJ, Chapiro J, Bousabarah K, Chen E, Laage-Gaupp F, Tefera J, Nezami N, Lin M, Pollak J, Schlachter T. Neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios as predictors of tumor response in hepatocellular carcinoma after DEB-TACE. Eur Radiol. 2020;30(10):5663–73.
Heimbach JK, Kulik LM, Finn RS, Sirlin CB, Abecassis MM, Roberts LR, Zhu AX, Murad MH, Marrero JA. AASLD guidelines for the treatment of hepatocellular carcinoma. Hepatology. 2018;67(1):358–80.
Chen B, Wu JX, Cheng SH, Wang LM, Rong WQ, Wu F, Wang SL, ** J, Liu YP, Song YW, Ren H, Fang H, Tang Y, Li N, Li YX, Wang WH. Phase 2 study of adjuvant radiotherapy following narrow-margin hepatectomy in patients with HCC. Hepatology. 2021;74(5):2595–604.
Olsen SK, Brown RS, Siegel AB. Hepatocellular carcinoma: review of current treatment with a focus on targeted molecular therapies. Therap Adv Gastroenterol. 2010;3(1):55–66.
Chen YD, Zhang L, Zhou ZP, Lin B, Jiang ZJ, Tang C, Dang YW, **a YW, Song B, Long LL. Radiomics and nomogram of magnetic resonance imaging for preoperative prediction of microvascular invasion in small hepatocellular carcinoma. World J Gastroenterol. 2022;28(31):4399–416.
Cao Y, Ke R, Wang S, Zhu X, Chen J, Huang C, Jiang Y, Lv L. DNA topoisomerase IIα and Ki67 are prognostic factors in patients with hepatocellular carcinoma. Oncol Lett. 2017;13(6):4109–16.
Scholzen T, Gerdes J. The Ki-67 protein: from the known and the unknown. J Cell Physiol. 2000;182(3):311–22.
Fleming GF, Pagani O, Regan MM, Walley BA, Francis PA. Adjuvant abemaciclib combined with endocrine therapy for high-risk early breast cancer: updated efficacy and Ki-67 analysis from the monarchE study. Ann Oncol. 2022;33(6):658.
Li Z, Li F, Pan C, He Z, Pan X, Zhu Q, Wu W, Chen L. Tumor cell proliferation (Ki-67) expression and its prognostic significance in histological subtypes of lung adenocarcinoma. Lung cancer (Amsterdam, Netherlands). 2021;154:69–75.
Ye Z, Jiang H, Chen J, Liu X, Wei Y, **a C, Duan T, Cao L, Zhang Z, Song B. Texture analysis on gadoxetic acid enhanced-MRI for predicting Ki-67 status in hepatocellular carcinoma: a prospective study. Chin J Cancer Res. 2019;31(5):806–17.
Zhang X, Wu Z, Peng Y, Li D, Jiang Y, Pan F, Li Y, Lai Y, Cui Z, Zhang K. Correlationship between Ki67, VEGF, and p53 and hepatocellular carcinoma recurrence in liver transplant patients. Biomed Res Int. 2021;2021:6651397.
Li Y, Yan C, Weng S, Shi Z, Sun H, Chen J, Xu X, Ye R, Hong J. Texture analysis of multi-phase MRI images to detect expression of Ki67 in hepatocellular carcinoma. Clin Radiol. 2019;74(10):813.e19-813.e27.
Fan Y, Yu Y, Wang X, Hu M, Hu C. Radiomic analysis of Gd-EOB-DTPA-enhanced MRI predicts Ki-67 expression in hepatocellular carcinoma. BMC Med Imaging. 2021;21(1):100.
Chen Y, Qin X, Long L, Zhang L, Huang Z, Jiang Z, Li C. Diagnostic value of Gd-EOB-DTPA-enhanced MRI for the expression of Ki67 and microvascular density in hepatocellular carcinoma. J Magn Reson Imaging. 2020;51(6):1755–63.
Hu XX, Yang ZX, Liang HY, Ding Y, Grimm R, Fu CX, Liu H, Yan X, Ji Y, Zeng MS, Rao SX. Whole-tumor MRI histogram analyses of hepatocellular carcinoma: correlations with Ki-67 labeling index. J Magn Reson Imaging. 2017;46(2):383–92.
Liu Z, Yang S, Chen X, Luo C, Feng J, Chen H, Ouyang F, Zhang R, Li X, Liu W, Guo B, Hu Q. Nomogram development and validation to predict Ki-67 expression of hepatocellular carcinoma derived from Gd-EOB-DTPA-enhanced MRI combined with T1 map**. Front Oncol. 2022;12:954445.
Wu C, Chen J, Fan Y, Zhao M, He X, Wei Y, Ge W, Liu Y. Nomogram based on CT radiomics features combined with clinical factors to predict Ki-67 expression in hepatocellular carcinoma. Front Oncol. 2022;12:943942.
Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA. Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol. 2010;11(2):174–83.
Klöppel G, La Rosa S. Ki67 labeling index: assessment and prognostic role in gastroenteropancreatic neuroendocrine neoplasms. Virchows Arch. 2018;472(3):341–9.
Tu Y, Jiang P, Zhang J, Jiang S, Yi Q, Yuan R. The positive threshold of the immunohistochemical parameter Ki67 for predicting the recurrence of cervical cancer. Int J Gynaecol Obstet. 2022;158(2):330–7.
Zhang YF, Guo RP, Zou RH, Shen JX, Wei W, Li SH, OuYang HY, Zhu HB, Xu L, Lao XM, Shi M. Efficacy and safety of preoperative chemoembolization for resectable hepatocellular carcinoma with portal vein invasion: a prospective comparative study. Eur Radiol. 2016;26(7):2078–88.
Yang C, Zhang J, Ding M, Xu K, Li L, Mao L, Zheng J. Ki67 targeted strategies for cancer therapy. Clin Transl Oncol. 2018;20(5):570–5.
Hu X, Zhou J, Li Y, Wang Y, Guo J, Sack I, Chen W, Yan F, Li R, Wang C. Added value of viscoelasticity for MRI-based prediction of Ki-67 expression of hepatocellular carcinoma using a deep learning combined radiomics (DLCR) model. Cancers (Basel). 2022;14(11):2575.
Wen L, Weng S, Yan C, Ye R, Zhu Y, Zhou L, Gao L, Li Y. A radiomics nomogram for preoperative prediction of early recurrence of small hepatocellular carcinoma after surgical resection or radiofrequency ablation. Front Oncol. 2021;11:657039.
Aktas S, Karakayali H, Moray G, Ozdemir H, Haberal M. Effects of risk factors and Ki-67 on rates of recurrence on patients who have undergone liver transplant for hepatocellular carcinoma. Transplant Proc. 2011;43(10):3807–12.
Ahmed AA, Elmohr MM, Fuentes D, Habra MA, Fisher SB, Perrier ND, Zhang M, Elsayes KM. Radiomic map** model for prediction of Ki-67 expression in adrenocortical carcinoma. Clin Radiol. 2020;75(6):479.e17-479.e22.
Wang Q, Li B, Liu Z, Shang H, **g H, Shao H, Chen K, Liang X, Cheng W. Prediction model of axillary lymph node status using automated breast ultrasound (ABUS) and ki-67 status in early-stage breast cancer. BMC Cancer. 2022;22(1):929.
Zhang S, Duan C, Zhou X, Liu F, Wang X, Shao Q, Gao Y, Duan F, Zhao R, Wang G. Radiomics nomogram for prediction of microvascular invasion in hepatocellular carcinoma based on MR imaging with Gd-EOB-DTPA. Front Oncol. 2022;12:1034519.
Park SJ, Jang JY, Jeong SW, Cho YK, Lee SH, Kim SG, Cha SW, Kim YS, Cho YD, Kim HS, Kim BS, Park S, Bang HI. Usefulness of AFP, AFP-L3, and PIVKA-II, and their combinations in diagnosing hepatocellular carcinoma. Medicine (Baltimore). 2017;96(11):e5811.
Kumada T, Toyoda H, Kiriyama S, Tanikawa M, Hisanaga Y, Kanamori A, Tada T, Tanaka J, Yoshizawa H. Predictive value of tumor markers for hepatocarcinogenesis in patients with hepatitis C virus. J Gastroenterol. 2011;46(4):536–44.
Force M, Park G, Chalikonda D, Roth C, Cohen M, Halegoua-DeMarzio D, Hann HW. Alpha-fetoprotein (AFP) and AFP-L3 is most useful in detection of recurrence of hepatocellular carcinoma in patients after tumor ablation and with low AFP level. Viruses. 2022;14(4):775.
Tzartzeva K, Obi J, Rich NE, Parikh ND, Marrero JA, Yopp A, Waljee AK, Singal AG. Surveillance imaging and alpha fetoprotein for early detection of hepatocellular carcinoma in patients with cirrhosis: a meta-analysis. Gastroenterology. 2018;154(6):1706–1718.e1.
Tian S, Chen Y, Zhang Y, Xu X. Clinical value of serum AFP and PIVKA-II for diagnosis, treatment and prognosis of hepatocellular carcinoma. J Clin Lab Anal. 2023;37(1):e24823.
Sun X, Mei J, Lin W, Yang Z, Peng W, Chen J, Zhang Y, Xu L, Chen M. Reductions in AFP and PIVKA-II can predict the efficiency of anti-PD-1 immunotherapy in HCC patients. BMC Cancer. 2021;21(1):775.
Cho IJ, Jeong JU, Nam TK, Joo YE, Cho SB, Kim YH, Song JY, Yoon MS, Ahn SJ, Chung WK. PIVKA-II as a surrogate marker for prognosis in patients with localized hepatocellular carcinoma receiving stereotactic body radiotherapy. Radiat Oncol J. 2022;40(1):20–8.
Feng H, Li B, Li Z, Wei Q, Ren L. PIVKA-II serves as a potential biomarker that complements AFP for the diagnosis of hepatocellular carcinoma. BMC Cancer. 2021;21(1):401.
Tamano M, Sugaya H, Oguma M, Iijima M, Yoneda M, Murohisa T, Kojima K, Kuniyoshi T, Majima Y, Hashimoto T, Terano A. Serum and tissue PIVKA-II expression reflect the biological malignant potential of small hepatocellular carcinoma. Hepatol Res. 2002;22(4):261–9.
Author information
Authors and Affiliations
Contributions
L.MG. wrote the main manuscript text, L.SB. and L.HL. prepared data, and H.YY. and L.L. prepared figures 2. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Ethics Approval and Consent to Participate
This retrospective study was approved by the Institutional Ethics Committee of the Shengli Oilfield Central Hospital, which waived the requirement for written informed consent.
Consent for Publication
Not applicable.
Competing Interests
The authors declare no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Li, Mg., Luo, Sb., Hu, Yy. et al. Role of the Clinical Features and MRI Parameters on Ki-67 Expression in Hepatocellular Carcinoma Patients: Development of a Predictive Nomogram. J Gastrointest Canc (2024). https://doi.org/10.1007/s12029-024-01051-5
Accepted:
Published:
DOI: https://doi.org/10.1007/s12029-024-01051-5