Cód. SSPA: IBiS-CS-18
The CS-18 research group “Maternal–Fetal Medicine and Gynecological Health (Fetalginsalud)” was established as a clinical-translational team, serving as a direct bridge between the healthcare work of the Virgen de Valme University Hospital and the research conducted at the University of Seville.
Our mission is to address the major challenges of obstetric and gynecological pathology that affect women’s health, from the fetal stage through the postpartum period. We apply an innovative approach in which applied research is driven by the most advanced imaging-based diagnostic technologies.
We have solid experience in advanced ultrasound (3D/4D, sonoelastography, Doppler-SMI), a capability now strengthened by the development of our own Artificial Intelligence (AI) and deep-learning models. The goal is clear: to create diagnostic and therapeutic tools that enhance the quality of care, reduce inter-observer variability, and enable highly precise, personalized medicine.
Our lines of work range from prenatal diagnosis and fetal pathology to the impact of childbirth on the pelvic floor, advanced gynecological pathology, placental complications, and the integration of AI into the clinical workflow.
Research lines
The CS-18 group (Fetalginsalud) structures its scientific-technical activity into five main lines of research, all of them interconnected and with a strong component of technological innovation and clinical translation:
- Prenatal Diagnosis and Fetal Pathology
Our work has historically focused on optimizing combined screening for chromosomal abnormalities and structural malformations, both in the first and second trimesters. We aim to redefine screening strategies by incorporating secondary ultrasound markers, contingent methodology, and the use of cell-free fetal DNA in maternal blood. The cornerstone of this line is the study of early morphological ultrasound (11–14 weeks) as a fundamental diagnostic tool for structural anomalies.
Since 2010, the group has led the implementation and evaluation of these programs with a direct impact on the prenatal screening system in the Southern Seville Area and Andalusia. This work has generated more than 25 articles—most of them in high-impact journals—as well as several specialized books, strengthening the establishment of innovative methodologies for detecting Down syndrome and other conditions.
- Labour, Postpartum, and Pelvic Floor Trauma
This line addresses a critical moment: childbirth and its impact on women’s health. We specialize in the use of intrapartum translabial ultrasound as a predictive tool in complex instrumented deliveries, aiming to improve neonatal outcomes. We focus on studying the morphology and recovery of the levator ani muscle after vaginal delivery, characterizing ultrasound markers of avulsion and their functional impact. We also evaluate intensive physiotherapy strategies and telerehabilitation for personalized recovery protocols.
This work has positioned us as an international reference in the use of translabial ultrasound. Key milestones include the development of ultrasound-based models to predict difficulties in instrumented births (with a registered patent), the pioneering application of elastography to predict induction-of-labour success, and the publication of the first Spanish-language books on Peripartum Ultrasound and Transperineal Pelvic Floor Ultrasound, with more than 20 high-impact papers.
- Gynecological Pathology and Pelvic Floor Dysfunction
One of our most productive lines, devoted to advanced ultrasound diagnosis of pelvic floor dysfunctions such as pelvic organ prolapse (POP) and urinary incontinence. We promote the development of image-based diagnostic software, evaluate tension-free vaginal tapes, and identify ultrasound predictors of surgical recurrence. Additionally, we apply transperineal ultrasound to study the anorectal angle and use elastography to improve the detection of cervical lesions.
With more than 30 JCR-indexed articles published, this line has generated three registered clinical software tools for automated POP diagnosis. This leadership is reflected in our coordination of SEGO’s first clinical guideline on pelvic floor dysfunction. We have also developed a predictive software tool for lymph-node metastasis in breast cancer (registered), which is already in use.
- Placental Pathology and Fetal Growth Restriction (FGR)
This is a cutting-edge line exploring the role of placental microcirculation in fetal development. The challenge is to characterize normal placental vascularization using the innovative Doppler-SMI technique as a diagnostic basis for placental pathology. The main focus is evaluating Doppler-SMI for differentiating between small-for-gestational-age fetuses and those with late-onset FGR, seeking to apply microvascular imaging to improve neonatal prognosis and risk stratification.
The primary achievement of this emerging line lies in this evaluation and in participation in studies on preeclampsia markers in collaboration with Vall d’Hebron Hospital.
- Artificial Intelligence Applied to Diagnosis in Gynecology and Obstetrics
This line represents the convergence of all previous ones and our leap into the future. It is a cross-cutting axis with high technological impact, focused on developing artificial-intelligence models for dynamic and automatic identification of pelvic-floor structures in ultrasound imaging. We apply deep-learning neural networks for image-assisted diagnosis of prolapse, aiming to drastically reduce inter-observer variability and integrate AI into clinical workflows.
The group has been a pioneer in integrating deep learning and convolutional neural networks (CNNs) for automated diagnosis. We have developed three registered AI models for automatic organ identification, midsagittal-plane determination, and POP diagnosis. Especially noteworthy is the registered patent of our CNN (Registration No. 04 / 2024 / 851), a tool with clear utility for real-world clinical application.
