Magnetic Resonance Imaging-Based Nomogram to Antenatal Predict Cesarean Delivery for Cephalopelvic Disproportion in Primiparous Women

Background: Cephalopelvic disproportion (CPD)-related obstructed labor is associated with maternal and neonatal morbidity and mortality. Accurate prediction of whether a primiparous woman is at high risk of an unplanned cesarean delivery would be a major advance in obstetrics.

Purpose: To develop and validate a predictive model assessing the risk of cesarean delivery in primiparous women based on MRI findings.

Study type: Prospective.

Population: A total of 150 primiparous women with clinical findings suggestive of CPD.

Field strength/sequence: T1-weighted fast spin-echo sequences, single-shot fast spin-echo (SSFSE) T2-weighted sequences at 1.5 T.

Assessment: Pelvimetry and fetal biometry were assessed independently by two radiologists. A nomogram model combined that the clinical and MRI characteristics was constructed.

Statistical tests: Univariable and multivariable logistic regression analyses were applied to select independent variables. Receiver operating characteristic (ROC) analysis was performed, and the discrimination of the model was assessed by the area under the curve (AUC). Calibration was assessed by calibration plots. Decision curve analysis was applied to evaluate the net clinical benefit. A P value below 0.05 was considered to be statistically significant.

Results: In multivariable modeling, the maternal body mass index (BMI) before delivery, bilateral femoral head distance, obstetric conjugate, fetal head circumference, and fetal abdominal circumference was significantly associated with the likelihood of cesarean delivery. The discrimination calculated as the AUC was 0.838 (95% confidence interval [CI]: 0.774-0.902). The sensitivity and specificity of the nomogram model were 0.787 and 0.764, and the positive predictive and negative predictive values were 0.696 and 0.840, respectively. The model demonstrated satisfactory calibration (calibration slope = 0.945). Moreover, the decision curve analysis proved the superior net benefit of the model compared with each factor included.

Data conclusion: Our study might provide a nomogram model that could identify primiparous women at risk of cesarean delivery caused by CPD based on MRI measurements.

Evidence level: 2 TECHNICAL EFFICACY: Stage 2.