Early invasive cervical cancer: MRI and CT predictors of lymphatic metastases in the ACRIN 6651/GOG 183 intergroup study. Academic Article uri icon

Overview

abstract

  • PURPOSE: To compare MRI, CT, clinical exam and histopathological analysis for predicting lymph node involvement in women with cervical carcinoma, verified by lymphadenectomy. METHODS: A 25-center ACRIN/GOG study enrolled 208 patients with biopsy-proven invasive cervical cancer for MRI and CT prior to attempted curative radical hysterectomy. Each imaging study was interpreted prospectively by one onsite radiologist, and retrospectively by 4 independent offsite radiologists, all blinded to surgical, histopathological and other imaging findings. Likelihood of parametrial and uterine body involvement was rated on a 5-point scale. Tumor size measurements were attempted in 3 axes. Association with histologic lymph node involvement, scored as absent, pelvic only and common iliac or paraaortic, was evaluated using Cochran-Mantel Haenszel statistics, univariate and multivariate logistic regression, generalized estimating equations, accuracy statistics and ROC analysis. RESULTS: Lymphatic metastases were found in 34% of women; 13% had common iliac nodal metastases, and 9% had paraortic nodal metastases. Based on the retrospective multi-observer re-reads, the average AUC for predicting histologic lymph node involvement based on tumor size was higher for MRI versus CT, although formal statistic comparisons could not be conducted. Multivariate analysis showed improved model fit incorporating predictors from MRI, but not from CT, over and above the initial clinical and biopsy predictors, although the increase in discriminatory ability was not statistically significant. CONCLUSION: MRI findings may help predict the presence of histologic lymph node involvement in women with early invasive cervical carcinoma, thus providing important prognostic information.

publication date

  • November 20, 2008

Research

keywords

  • Lymph Nodes
  • Magnetic Resonance Imaging
  • Tomography, X-Ray Computed
  • Uterine Cervical Neoplasms

Identity

PubMed Central ID

  • PMC2606919

Scopus Document Identifier

  • 57649128506

Digital Object Identifier (DOI)

  • 10.1016/j.ygyno.2008.10.005

PubMed ID

  • 19019414

Additional Document Info

volume

  • 112

issue

  • 1