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Background The application value of T(2)mapping in evaluating cervical cancer (CC) features remains unclear. Purpose To investigate the role of T(2)values in evaluating CC classification, grade, and lymphovascular space invasion (LVSI) in comparison to apparent diffusion coefficient (ADC), and to compare synthetic T-2-weighted (T2W) images calculated from T(2)values to conventional T2W images for CC staging. Study Type Retrospective. Population Sixty-three patients with histopathologically confirmed CC. Field Strength/Sequence 3T, conventional T2W turbo spin-echo, diffusion-weighted echo-planar, and accelerated T(2)mapping sequence. Assessment T(2)and ADC values between different pathological features of CC were compared. The diagnostic accuracies of conventional and synthetic T2W images in staging were also compared. Statistical Tests Parameters were compared using an independentt-test, Wilcoxon signed-rank test, and the chi-square test. Receiver operating characteristic analysis was performed. Results The T(2)values varied significantly between well/moderately differentiated and poorly differentiated tumors ([92.8 +/- 9.5 msec] vs. [83.8 +/- 9.5 msec],P < 0.05) and between LVSI-positive and LVSI-negative CC ([82.2 +/- 8.2 msec] vs. [93.9 +/- 9.1 msec],P < 0.05). The ADC values showed a significant difference for grade ([0.76 +/- 0.10 x 10(-3)mm(2)/s] vs. [0.65 +/- 0.11 x 10(-3)mm(2)/s],P < 0.05) and no difference for LVSI status ([0.71 +/- 0.11x 10(-3)mm(2)/s] vs. [0.73 +/- 0.12x 10(-3)mm(2)/s],P= 0.472). There was no significant difference in T(2)and ADC values between squamous cell carcinoma and adenocarcinoma (P= 0.378 andP= 0.661, respectively). In MRI staging, the conventional and synthetic T2W images resulted in a similar accuracy (71% vs. 68%,P= 0.698). Data Conclusion The accelerated T(2)mapping sequence may facilitate grading and staging of CC by providing quantitative T(2)maps and synthetic T2W images in one acquisition. T(2)values may be superior to ADC in predicting LVSI. Level of Evidence 2 Technical Efficacy Stage 2
Victor Panaretos, Yoav Zemel, Valentina Masarotto