TY - JOUR
T1 - Early invasive cervical cancer
T2 - MRI and CT predictors of lymphatic metastases in the ACRIN 6651/GOG 183 intergroup study
AU - Mitchell, Donald G.
AU - Snyder, Bradley
AU - Coakley, Fergus
AU - Reinhold, Caroline
AU - Thomas, Gillian
AU - Amendola, Marco A.
AU - Schwartz, Lawrence H.
AU - Woodward, Paula
AU - Pannu, Harpreet
AU - Atri, Mostafa
AU - Hricak, Hedvig
N1 - Funding Information:
This study was funded by NCI grant # U01 CA079778 and U01 CA080098 and was conducted jointly by the American College of Radiology Imaging Network (ACRIN) and the Gynecologic Oncology Group (GOG). Data were collected, managed and analyzed by the Biostatistics and Data Management Center of ACRIN. Both ACRIN and GOG participated in the study design, the data analysis, the writing of the report, and the decision to submit the paper for publication. The NCI did not participate in the study design, the collection, analysis, or interpretation of the data, the writing of the report, or the decision to submit it for publication.
PY - 2009/1
Y1 - 2009/1
N2 - 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.
AB - 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.
KW - Cervical cancer
KW - Computed tomography
KW - FIGO
KW - Imaging
KW - Magnetic resonance imaging
KW - Staging
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U2 - 10.1016/j.ygyno.2008.10.005
DO - 10.1016/j.ygyno.2008.10.005
M3 - Article
C2 - 19019414
AN - SCOPUS:57649128506
SN - 0090-8258
VL - 112
SP - 95
EP - 103
JO - Gynecologic oncology
JF - Gynecologic oncology
IS - 1
ER -