Lymph node metastasis (LNM) greatly affects the prognosis and treatment of cervical squamous cell carcinoma (CSCC). Non-invasive imaging biomarkers that reflect tumor angiogenesis and vascular maturity may help predict LNM.
Purpose
To determine whether the magnetic resonance imaging (MRI) quantitative parameters combined with microvascular characteristics predict the potential of LNM by reflecting angiogenesis or vascular maturation in CSCC.
Material and Methods
The clinicopathological characteristics, microvascular characteristics and MRI quantitative parameters of the LNM group (43 cases) and the non-LNM group (42 cases) were analyzed. The correlation between microvascular and MRI quantitative parameters and the ability of combined diagnosis of LNM were analyzed.
Results
There were significant differences in the FIGO stage and the short diameter of the largest lymph node between patients with or without LNM. There was no significant difference in the apparent diffusion coefficient (ADC) value of the primary tumor between the LNM group and the non-LNM group (P >0.05). Spearman’s correlation analysis showed that there was no correlation between ADC and MVD or microvessel pericyte coverage index (MPI) (all P >0.05). Ktrans and Kep were significantly higher, and MPI was significantly lower in patients with LNM. There were negative correlations between Ktrans and MPI, and Kep and MPI. Binary logistic regression analysis showed that a combined prediction model constructed by Ktrans, Kep, and MPI had the highest diagnostic efficacy.
Conclusion
Ktrans and Kep of CSCC can predict LNM by non-invasively reflecting the maturity of tumor vessels, and the combined Ktrans, Kep, and MPI have promising diagnostic efficiency for LNM.
SungHFerlayJSiegelRL, et al.Global Cancer Statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin2021;71:209–249.
2.
LiKXuHWangS, et al.Disparities in the increases of cervical cancer incidence rates: observations from a city-wide population-based study. BMC Cancer2022;22:419.
3.
LinSGaoKGuS, et al.Worldwide trends in cervical cancer incidence and mortality, with predictions for the next 15 years. Cancer2021;127:4030–4039.
4.
JeongSYParkHKimMS, et al.Pretreatment lymph node metastasis as a prognostic significance in cervical cancer: comparison between disease Status. Cancer Res Treat2020;52:516–523.
5.
XuMXieXCaiL, et al.Risk factor assessment of lymph node metastasis in patients with FIGO stage IB1 cervical cancer. Front Oncol2022;12:809159.
6.
SalehMVirarkarMJavadiS, et al.Cervical cancer: 2018 revised international federation of gynecology and obstetrics staging system and the role of imaging. AJR Am J Roentgenol2020;214:1182–1195.
7.
KohWJAbu-RustumNRBeanS, et al.Cervical cancer, version 3.2019, NCCN clinical practice guidelines in oncology. J Natl Compr Canc Netw2019;17:64–84.
8.
LuganoRRamachandranMDimbergA. Tumor angiogenesis: causes, consequences, challenges and opportunities. Cell Mol Life Sci2020;77:1745–1770.
9.
QinYZhaoW. The modeling analysis and effect of CHI3L1 and CD31-marked microvessel density in the occurrence and development of cervical squamous cell carcinoma. Comput Math Methods Med2022;2022:3516335.
10.
FathyAAbdelrahmanAE. EZH2, endothelin-1, and CD34 as biomarkers of aggressive cervical squamous cell carcinoma: an immunohistochemical study. Turk Patoloji Derg2018;34:150–157.
11.
TriratanachatSNiruthisardSTrivijitsilpP, et al.Angiogenesis in cervical intraepithelial neoplasia and early-staged uterine cervical squamous cell carcinoma: clinical significance. Int J Gynecol Cancer2006;16:575–580.
12.
QiYLiWKangS, et al.Expression of BDNF, TrkB, VEGF and CD105 is associated with pelvic lymph node metastasis and prognosis in IB2-stage squamous cell carcinoma. Exp Ther Med2019;18:4221–4230.
13.
ZhangZSZhouHNHeSS, et al.Research advances in pericyte function and their roles in diseases. Chin J Traumatol2020;23:89–95.
14.
Alarcon-MartinezLYemisciMDalkaraT. Pericyte morphology and function. Histol Histopathol2021;36:633–643.
15.
ViallardCLarrivéeB. Tumor angiogenesis and vascular normalization: alternative therapeutic targets. Angiogenesis2017;20:409–426.
16.
TeleanuRIChircovCGrumezescuAM, et al.Tumor angiogenesis and anti-angiogenic strategies for cancer treatment. J Clin Med2019;9:84.
17.
ZhangYCedervallJHamidiA, et al.Platelet-Specific PDGFB ablation impairs tumor vessel integrity and promotes metastasis. Cancer Res2020;80:3345–3358.
18.
YinLHeJXueJ, et al.PDGFR-β inhibitor slows tumor growth but increases metastasis in combined radiotherapy and endostar therapy. Biomed Pharmacother2018;99:615–621.
19.
RofstadEKGalappathiKMathiesenBS. Tumor interstitial fluid pressure-a link between tumor hypoxia, microvascular density, and lymph node metastasis. Neoplasia2014;16:586–594.
20.
EllingsenCWalentaSHomplandT, et al.The microenvironment of cervical carcinoma Xenografts: associations with lymph node metastasis and its assessment by DCE-MRI. Transl Oncol2013;6:607–617.
21.
BhardwajRBoruahDKGogoiBB, et al.Added-value of diffusion-weighted imaging (DWI) and dynamic contrast-enhanced (DCE-MRI) magnetic resonance imaging in the preoperative assessment of cervical cancer. J Obstet Gynaecol India2022;72:330–340.
22.
MeyerHJHamerlaGLeifelsL, et al.Whole-lesion ADC histogram analysis is not able to reflect microvessel density in HNSCC. Medicine (Baltimore)2019;98:e15520.
23.
LiuYYeZSunH, et al.Grading of uterine cervical cancer by using the ADC difference value and its correlation with microvascular density and vascular endothelial growth factor. Eur Radiol2013;23:757–765.
24.
YangCQuanXHuangX, et al.Factors influencing apparent diffusion coefficient value in extrahepatic cholangiocarcinoma: a retrospective study. Eur J Radiol2022;157:110603.
25.
LiuLWangSYuT, et al.Value of diffusion-weighted imaging in preoperative evaluation and prediction of postoperative supplementary therapy for patients with cervical cancer. Ann Transl Med2022;10:120.
26.
KhalifaFSolimanAEl-BazA, et al.Models and methods for analyzing DCE-MRI: a review. Med Phys2014;41:124301.
27.
BaiZShiJYangZ, et al.Quantitative kinetic parameters of primary tumor can be used to predict pelvic lymph node metastasis in early-stage cervical cancer. Abdom Radiol (NY)2021;4:1129–1136.
28.
MeyerHJWienkeASurovA. Correlation between K(trans) and microvessel density in different tumors: a meta-analysis. Anticancer Res2018;38:2945–2950.
29.
HaugeAGaustadJVHuangR, et al.DCE-MRI and quantitative histology reveal enhanced vessel maturation but impaired perfusion and increased hypoxia in bevacizumab-treated cervical carcinoma. Int J Radiat Oncol Biol Phys2019;104:666–676.
30.
ChenYLJiangYChenTW, et al.Assessing microcirculation in resectable oesophageal squamous cell carcinoma with dynamic contrast-enhanced MRI for identifying primary tumour and lymphatic metastasis. Sci Rep2019;9:124.
31.
ZhangXDongYSongQ, et al.The role of multiparametric magnetic resonance imaging in the study of primary tumor and pelvic lymph node metastasis in stage IB1-IIA1 cervical cancer. J Comput Assist Tomogr2020;44:750–758.
32.
QinFPangHMaJ, et al.Combined dynamic contrast enhanced MRI parameter with clinical factors predict the survival of concurrent chemo-radiotherapy in patients with 2018 FIGO IIICr stage cervical cancer. Eur J Radiol2021;141:109787.
33.
SujlanaPSkrokJFayadLM. Review of dynamic contrast-enhanced MRI: technical aspects and applications in the musculoskeletal system. J Magn Reson Imaging2018;47:875–890.
34.
SongQGuoYYaoX, et al.Comparative study of evaluating the microcirculatory function status of primary small HCC between the CE (DCE-MRI). and non-CE (IVIM-DWI) MR perfusion imaging. Abdom Radiol (NY)2021;46:2575–2583.
35.
ShrivastavSBalASinghG, et al.Tumor angiogenesis in breast cancer: pericytes and maturation does not correlate with lymph node metastasis and molecular subtypes. Clin Breast Cancer2016;16:131–138.
36.
KimSHChoSH. Assessment of pelvic lymph node metastasis in FIGO IB and IIA cervical cancer using quantitative dynamic contrast-enhanced MRI parameters. Diagn Interv Radiol2020;26:382–389.
37.
DengYRChenXJXuCQ, et al.A preoperative nomogram predicting risk of lymph node metastasis for early-stage cervical cancer. BMC Womens Health2023;23:568.
38.
DingSLiCLinS, et al.Comparative evaluation of microvessel density determined by CD34 or CD105 in benign and malignant gastric lesions. Hum Pathol2006;37:861–866.
39.
HuangBXFangF. Progress in the study of lymph node metastasis in early-stage cervical cancer. Curr Med Sci2018;38:567–574.
40.
TantariMBoglioloSMorottiM, et al.Lymph node involvement in early-stage cervical cancer: is lymphangiogenesis a risk factor? Results from the MICROCOL study. Cancers (Basel)2022;14:212.
41.
RofstadEKHuangRGalappathiK, et al.Functional intratumoral lymphatics in patient-derived xenograft models of squamous cell carcinoma of the uterine cervix: implications for lymph node metastasis. Oncotarget2016;7:56986–56997.
42.
HuangTSunHLuoX, et al.Correlation study between flash dual source CT perfusion imaging and regional lymph node metastasis of non-small cell lung cancer. BMC Cancer2020;20:547.
43.
MelincoviciCSBoşcaABŞuşmanS, et al.Vascular endothelial growth factor (VEGF) - key factor in normal and pathological angiogenesis. Rom J Morphol Embryol2018;59:455–467.
44.
MiHLSuoSTChengJJ, et al.The invasion status of lymphovascular space and lymph nodes in cervical cancer assessed by mono-exponential and bi-exponential DWI-related parameters. Clin Radiol2020;75:763–771.
45.
LiBXuDZhouJ, et al.Monitoring bevacizumab-induced tumor vascular normalization by intravoxel incoherent motion diffusion-weighted MRI. J Magn Reson Imaging2022;56:427–439.
46.
HaugeAWegnerCSGaustadJV, et al.DCE-MRI of patient-derived xenograft models of uterine cervix carcinoma: associations with parameters of the tumor microenvironment. J Transl Med2017;15:225.
47.
AhnSJAnCSKoomWS, et al.Correlations of 3 T DCE-MRI quantitative parameters with microvessel density in a human-colorectal-cancer xenograft mouse model. Korean J Radiol2011;12:722–730.
48.
DiNYaoCChengW, et al.Correlation of dynamic contrast-enhanced MRI derived volume transfer constant with histological angiogenic markers in high-grade gliomas. J Med Imaging Radiat Oncol2018;62:464–470.
49.
XuJMaYMeiH, et al.Diagnostic value of multimodal magnetic resonance imaging in discriminating between metastatic and non-metastatic pelvic lymph nodes in cervical cancer. Int J Gen Med2022;15:6279–6288.
