Cited by 25Surgical Simulation and TrainingAnatomy and Medical TechnologyMedical Image Segmentation Techniques

TTTS-GPS: Patient-specific preoperative planning and simulation platform for twin-to-twin transfusion syndrome fetal surgery

Torrents-Barrena, Jordina, López-Velazco, Rocío, Piella, Gemma, Masoller, Narcís, Valenzuela-Alcaraz, Brenda, Gratacós, Eduard, Eixarch, Elisenda, Ceresa, Mario +1 more·2019·Computer Methods and Programs in Biomedicine

Abstract

Twin-to-twin transfusion syndrome (TTTS) is a serious condition that may occur in pregnancies when two or more fetuses share the same placenta. It is characterized by abnormal vascular connections in the placenta that cause blood to flow unevenly between the babies. If left untreated, perinatal mortality occurs in 90% of cases, whilst neurological injuries are still present in TTTS survivors. Minimally invasive fetoscopic laser surgery is the standard and optimal treatment for this condition, but is technically challenging and can lead to complications. Acquiring and maintaining the required surgical skills need consistent practice, and a steep learning curve. An accurate preoperative planning is thus vital for complex TTTS cases. To this end, we propose the first TTTS fetal surgery planning and simulation platform. The soft tissue of the mother, the uterus, the umbilical cords, the placenta and its vascular tree are segmented and registered automatically from magnetic resonance imaging and 3D ultrasound using computer vision and deep learning techniques. The proposed state-of-the-art technology is integrated into a flexible C++ and MITK-based application to provide a full exploration of the intrauterine environment by simulating the fetoscope camera as well as the laser ablation, determining the correct entry point, training doctors' movements and trajectory ahead of operation, which allows improving upon current practice. A comprehensive usability study is reported. Experienced surgeons rated highly our TTTS planner and simulator, thus being a potential tool to be implemented in real and complex TTTS surgeries.

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Crossref · 10.1016/j.cmpb.2019.104993

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References 26 · Cited by 25

Authors
Torrents-Barrena, J., López-Velazco, R., Piella, G., Masoller, N., Valenzuela-Alcaraz, B., Gratacós, E., Eixarch, E., Ceresa, M., & Ángel González Ballester, M.
Affiliations
  • Universitat Pompeu Fabra (ES)
  • Universitat de Barcelona (ES)
Venue
Computer Methods and Programs in Biomedicine
Publisher
Elsevier BV
Published
2019-10
Volume
179
Pages
104993
ISSN
0169-2607 (ISSN-L)
OpenAlex
W2963569911
Cited by
25
References
26
Citations by year
2026: 1 · 2025: 5 · 2024: 1 · 2023: 3 · 2022: 7 · 2021: 1 · 2020: 5 · 2019: 2
FWCI
3.58
Type
journal article
Language
en
Open access
closed
Locations
  • Computer Methods and Programs in Biomedicine (publishedVersion)
  • PubMed (publishedVersion)
Funders
Ministry of Economy and Competitiveness (MDM-2015-0502)
Topics
  • Health Sciences › Medicine › Surgery › Surgical Simulation and Training
  • Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Keywords
twin-twin transfusion syndrome, fetoscopic laser surgery, surgical planning, surgical simulation, fetal surgery, 3D ultrasound, magnetic resonance imaging, deep learning segmentation, image registration, surgical training, MITK, usability testing
MeSH terms
Algorithms, Computer Graphics, Computer Simulation, Female, Fetofetal Transfusion, Fetoscopy, Humans, Infant, Newborn, Magnetic Resonance Imaging, Models, Anatomic, Placenta, Pregnancy, User-Computer Interface, Uterus, Imaging, Three-Dimensional, Laser Therapy, Patient-Specific Modeling

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