Evaluation of quantitative ultrasound tissue characterization of the cervix and cervical length in the prediction of premature delivery for patients with spontaneous preterm labor

OBJECTIVE: This study was to evaluate the predictive value of the uterine cervix tissue with the use of quantitative ultrasound gray level analysis for preterm delivery. STUDY DESIGN: Sixty-eight patients with preterm labor between 20 and 35 weeks of gestation were included. When two-dimensional transvaginal ultrasound measurement of cervical length was completed, a region of interest of constant size was defined in the midsection of the posterior wall, and the tissue-specific gray scale was determined. Preterm delivery of <37 weeks of gestation was sought. RESULTS: Twenty-eight patients (41.2%) were delivered preterm. The risk for preterm delivery was increased significantly in patients with cervical length of ≤2.5 cm (odds ratio, 7.67; 95% CI, 2.4-24.45), with Bishop score of ≥4 (odds ratio, 3.44; 95% CI, 1.21-9.75), and with decreased mean gray scale value (odds ratio, 12.13; 95% CI, 3.69-39.88). Parity and uterine contractions were not significant as predictors for preterm delivery, although the risk for preterm delivery increased with higher parity (odds ratio, 1.8; 95% CI, 0.68-4.79). The risk for preterm delivery remained nearly the same by uterine contractions (odds ratio, 0.92; 95% CI, 0.28-3.01). A mean scale value of ≤6.54 had the best cutoff value for the prediction of preterm delivery. For preterm delivery, a mean gray value ≤6.54 had a sensitivity of 82.1%, a specificity of 72.5%, a positive predictive value of 67.6%, and a negative predictive value 85.3%. Multiple logistic regression analysis indicated that, even when other variables are considered simultaneously, the mean gray scale value is the single best predictor of preterm delivery. CONCLUSION: Quantitative ultrasound tissue characterization of the uterine cervix predicts premature delivery and provides additional information in the prediction of potential premature delivery.