The mean apparent diffusion coefficient value (ADCmean) on primary cervical cancer is a predictive marker for disease recurrence

Gynecol Oncol. 2012 Dec;127(3):478-83. doi: 10.1016/j.ygyno.2012.07.123. Epub 2012 Aug 11.


Objective: The purpose of this study is to investigate the correlation of the max, mean and minimal apparent diffusion coefficient values (ADCmax, ADCmean, and ADCmin) on diffusion weighted imaging findings with prognostic factors in cervical cancer.

Methods: A cohort of 80 cervical cancer patients underwent pelvic magnetic resonance imaging (MRI) within the 2 to 4 weeks prior to radical hysterectomy. The optimal cutoff value for segregating disease free survival (DFS) was determined by receiver operating characteristic (ROC) curve analysis. We used ROC curve analyses to evaluate whether preoperative ADCmax, ADCmean, ADCmin on MRI predicted the risk group of recurrence.

Results: Analyses of ROC curves identified an optimal The ROC curves identified an optimal ADCmax, ADCmean, and ADCmin cutoff values of 1.122 × 10(-3)mm(2)/s, 0.852 × 10(-3)mm(2)/s, 0.670 × 10(-3)mm(2)/s and for predicting the recurrence of cervical cancer. The patients categorized into the lower ADCmean or ADCmin groups showed the shorter disease free survivals compared with the higher ADCmean or ADCmin, respectively (P<0.0001 or P=0.0210). In particular, the ADCmean of primary cervical cancer was an independent predictive factor for disease recurrence by a multivariate analysis (P=0.0133).

Conclusions: The ADCmean of primary cervical cancer calculated by MRI could be an important factor for identifying patients with a risk of disease recurrence.

MeSH terms

  • Adult
  • Aged
  • Cohort Studies
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Humans
  • Middle Aged
  • Neoplasm Recurrence, Local / diagnosis*
  • ROC Curve
  • Uterine Cervical Neoplasms / pathology*