ABSTRACT An estimated 13 million preterm births (PTBs) occur annually worldwide and PTB is the single most significant contributing factor to neonatal morbidity and mortality. The inability to correctly identify patients at risk for PTB limits efficient research progress by preventing assembly of cohorts actually at risk for the disease and leaves major research investments with heterogenous cohorts, modest or conflicting effects of interventions tested, and unclear clinical translation. Current PTB prediction is applied according to two primary risk factors: 1) prior PTB and 2) short cervical length on ultrasound. These two risk criteria are particularly problematic in nulliparous patients because they have no obstetric history to guide risk stratification, and cervical length has poor predictive ability. In fact, in a 2021 American College of Obstetrics and Gynecology practice bulletin on PTB prevention, the authors concluded that “whether and how to screen nulliparous women is a matter of uncertainty and debate.” Cervical tissue elastography is a promising technique to measure cervical remodeling. However, current systems are unable to quantify the pressure applied to the cervix, making the measurement non-quantitative and thereby preventing standardization between examiners, longitudinal within-patient comparisons, and between-patient comparisons. We have overcome this key limitation with a novel, precise, operator-independent, ultrasound- based imaging modality—fully quantitative cervical elastography system (Q-CES). Our preliminary data shows that 1) cervical stiffness, detectable by Q-CES in early pregnancy, is significantly associated with spontaneous PTB, and 2) Q-CES may have stronger predictive utility for spontaneous PTB than cervical length. The aims of this proposal will test the overall hypothesis that Q-CES values of cervical stiffness can more accurately predict spontaneous PTB than cervical length using a multicenter, diverse prospective cohort. In Aim 1 we will, for the first time, quantify normative Q-CES values of cervical stiffness in nulliparous patients who deliver at term versus preterm. In Aim 2 we will use Q-CES to develop a multiparametric risk prediction model for spontaneous PTB compared to existing models based on cervical length. We have an established, multidisciplinary team already performing Q-CES at all three centers in this proposal, with equipment in place and ready to be leveraged for this project. We will enroll 35% Black and Hispanic patients to ensure that our results can explore the persistent racial and ethnic disparities in PTB risk. Completion of these aims will allow us to, for the first time, numerically quantify cervical tissue stiffness longitudinally in pregnancy and to detect softening patterns predictive of spontaneous PTB. This will be directly clinically actionable and address a fundamental roadblock in PTB science by improving the ability to assemble rational research cohorts for more meanin...