MRI quantitative parameters combined with pathological microvascular characteristics predict lymph node metastasis of cervical squamous cell carcinoma.

Abstract

BackgroundLymph 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.PurposeTo 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 MethodsThe 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.ResultsThere 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). K^trans and K_ep were significantly higher, and MPI was significantly lower in patients with LNM. There were negative correlations between K^trans and MPI, and K_ep and MPI. Binary logistic regression analysis showed that a combined prediction model constructed by K^trans, K_ep, and MPI had the highest diagnostic efficacy.ConclusionK^trans and K_ep of CSCC can predict LNM by non-invasively reflecting the maturity of tumor vessels, and the combined K^trans, K_ep, and MPI have promising diagnostic efficiency for LNM.