A new AI-powered software has been developed to assist in childbirth by providing real-time guidance on the baby’s head position during labor. This software, which can be integrated with ultrasound devices, helps operators determine whether to proceed with a natural birth, use a vacuum extractor, or perform an emergency cesarean. It uses a traffic light system to display clear instructions: red means a cesarean may be needed, green indicates the vacuum extractor can be used, and yellow suggests uncertainty.
This tool, expected to be available in delivery rooms by 2028, was created as part of a study published in The European Journal of Obstetrics & Gynecology and Reproductive Biology. The project was led by Professor Tullio Ghi, a gynecology and obstetrics expert at the Catholic University of Rome. The study received support from the Clinical Physiology Institute of the Italian National Research Council (CNR) in Lecce and the Obstetrics Clinic at the University of Parma. The research is part of the ISLANDS international study group, founded by Professor Ghi, and will continue with a new study funded by the Italian Ministry of Health with €200,000.
Labor can be complicated when the fetus faces difficulties during its descent through the birth canal. One common issue is fetal malposition, where the baby’s head is turned incorrectly. This can cause slow or halted labor, requiring interventions like a vacuum extractor or, in severe cases, an emergency cesarean to ensure the safety of both mother and child.
Evaluating the baby’s head position is often tricky, even for experienced practitioners. Professor Ghi notes that manual assessments carry a 20% error rate, which could lead to improper use of the vacuum extractor, failed extractions, or delayed delivery in stressful situations. While ultrasound is useful for accurate assessments, not all medical staff are skilled in interpreting the images.
The AI software addresses this issue by analyzing ultrasound images and offering immediate feedback. The results are displayed as a traffic light system: red signals the need for a cesarean, green means it’s safe to proceed with the vacuum, and yellow indicates uncertainty.
In a multicenter study, the software was tested with 2,154 ultrasound images from 16 centers worldwide. The results showed a 94.5% accuracy rate and a 95.6% sensitivity in detecting head malposition, which is considered excellent by Professor Ghi. The next step will involve validating the software with larger patient groups, but if results remain positive, it could be part of standard clinical practice within the next 3 to 4 years.
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