A Method for Quantifying Cervical Elasticity During Pregnancy Based on Transvaginal Ultrasound and Pressure Measurement

Background and Motivation

Preterm birth (delivery before 37 weeks of gestation) is a major cause of neonatal morbidity and mortality. Due to the high risks associated with preterm birth, many pregnant women with preterm symptoms need hospital treatment, but more than half of the hospitalized women eventually deliver at full term. The current methods for predicting cervical softening (such as the Bishop score) have limited efficacy in predicting preterm birth, indicating the need for more accurate tools to predict preterm birth.

Research Question

Currently, two commonly used methods for cervical elasticity imaging are strain elastography and shear wave elastography. However, strain elastography lacks stress information and does not support comparison between different imaging sessions; shear wave elastography’s robustness is affected by the highly heterogeneous nature of cervical tissue.

Objectives and Methods

The objective of this study is to develop a quantitative cervical elasticity imaging system that overcomes the above limitations by adding a stress sensor to the transvaginal ultrasound imaging system. This system is safe, accurate, and highly repeatable, allowing for long-term monitoring and comparison between different examiners.

Source

This paper is authored by Peng Hu, Peinan Zhao, Molly J. Stout, among others, and published in the IEEE Transactions on Biomedical Engineering (2024, Volume xx, Issue xx). The research is funded by the March of Dimes Prematurity Research Center.

Research Details

Experimental Procedure

Research Design and Experimental Methods

The experimental procedure includes the following main steps:

1. Image Acquisition and Stress Measurement

   • Record cervical deformation using a transvaginal ultrasound system in B-mode imaging, while recording the stress on the probe surface using a stress sensor.

2. Deformation and Strain Quantification

   • An automatic feature tracking algorithm quantifies deformation and calculates strain. Then, the Young’s modulus of the cervix is estimated through stress-strain linear regression.

3. Stress Sensor Calibration

   • Use a calibration system to calibrate the stress sensor to ensure the accuracy of the measurements.

4. Data Analysis and Regression

   • Use linear regression to analyze stress and strain to estimate the cervical Young’s modulus.

Sample Selection

The study includes pregnant women from a prospective longitudinal cohort study conducted by the Washington University School of Medicine in St. Louis from January 2017 to January 2020. Participants underwent regular examinations from the first trimester to delivery, with 22 women included who had at least three imaging sessions, with the last session beyond 34 weeks of gestation.

Research Results

System Accuracy, Repeatability, and Reproducibility

1. Phantom Experiments

   • Prepared four gelatin phantoms with concentrations of 70 g/l, 90 g/l, 110 g/l, and 130 g/l. Two operators performed multiple quantitative elasticity imaging sessions on each phantom using two stress sensors, showing no significant difference between the operators and methods (P-value = 0.369 > 0.05).
   • The coefficient of variation (CV) was low, indicating high repeatability of the system.

2. Impact of Contact Angle

   • Used stress sensors with contact angles of 60° and 90° to measure the phantoms, showing that the contact angle had no significant impact on measurements (P-value = 0.638 > 0.05).

3. Clinical Experiments

   • In experiments with 19 pregnant participants, two ultrasound physicians performed multiple quantitative elasticity imaging sessions on each participant, showing high repeatability and reproducibility. Measurement differences between the two physicians were within acceptable ranges, with a Pearson correlation coefficient (PCC) of 0.981.

Long-term Monitoring Results

The system successfully quantified the softening process of the cervix during pregnancy. Long-term monitoring of 22 participants showed a gradual decrease in cervical Young’s modulus during pregnancy. The geometric mean Young’s modulus values for the first, second, and third trimesters were 13.07 kPa, 7.59 kPa, and 4.40 kPa, respectively.

Conclusion and Significance

The quantitative cervical elasticity imaging system developed in this study is accurate, robust, and safe, suitable for long-term monitoring and comparison between different examiners. Its quantification of cervical softening at different stages of pregnancy provides important evidence for predicting preterm birth. This system is not only suitable for clinical research on cervical softening but also applicable in clinical practice to assess obstetric issues related to abnormal cervical physiology, improving the efficiency of preterm birth management.

Technical Highlights and Future Prospects

1. Technical Highlights

   • The unique feature of this system is its combination of stress and strain measurements, making comparisons within and between patients more reliable.
   • Automated strain quantification algorithms and a real-time GUI interface enable efficient data analysis and visualization.

2. Future Prospects

   • Improve the accuracy of local strain quantification to further detail the softening conditions of different cervical regions.
   • Enhance stress distribution estimation accuracy through multi-sensor and finite element mechanical modeling.
   • Improve the sensitivity, calibration system, and automated image/signal processing of the stress sensor to increase system efficiency and scalability.