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Segmentation of the placenta and its vascular tree in Doppler ultrasound for fetal surgery planning

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International Journal of Computer Assisted Radiology and Surgery Aims and scope Submit manuscript

Abstract

Purpose

Twin-to-twin transfusion syndrome (TTTS) is a serious condition that occurs in about 10–15% of monochorionic twin pregnancies. In most instances, the blood flow is unevenly distributed throughout the placenta anastomoses leading to the death of both fetuses if no surgical procedure is performed. Fetoscopic laser coagulation is the optimal therapy to considerably improve co-twin prognosis by clogging the abnormal anastomoses. Notwithstanding progress in recent years, TTTS surgery is highly risky. Computer-assisted planning of the intervention can thus improve the outcome.

Methods

In this work, we implement a GPU-accelerated random walker (RW) algorithm to detect the placenta, both umbilical cord insertions and the placental vasculature from Doppler ultrasound (US). Placenta and background seeds are manually initialized in 10–20 slices (out of 245). Vessels are automatically initialized in the same slices by means of Otsu thresholding. The RW finds the boundaries of the placenta and reconstructs the vasculature.

Results

We evaluate our semiautomatic method in 5 monochorionic and 24 singleton pregnancies. Although satisfactory performance is achieved on placenta segmentation (Dice ≥ 84.0%), some vascular connections are still neglected due to the presence of US reverberation artifacts (Dice ≥ 56.9%). We also compared inter-user variability and obtained Dice coefficients of ≥ 76.8% and ≥ 97.42% for placenta and vasculature, respectively. After a 3-min manual initialization, our GPU approach speeds the computation 10.6 times compared to the CPU.

Conclusions

Our semiautomatic method provides a near real-time user experience and requires short training without compromising the segmentation accuracy. A powerful approach is thus presented to rapidly plan the fetoscope insertion point ahead of TTTS surgery.

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Notes

  1. The Insight Segmentation & Registration Toolkit (ITK): https://itk.org.

  2. Eigen3: http://eigen.tuxfamily.org.

  3. CUDA: https://developer.nvidia.com/cuda-toolkit.

  4. The Medical Imaging Interaction Toolkit (MITK): http://mitk.org.

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Acknowledgements

The research leading to these results has received funding by The Cellex Foundation, “LaCaixa” Foundation under Grant Agreements LCF/PR/GN14/10270005 and LCF/PR/GN18/10310003, AGAUR under Grant 2017 SGR nº 1531, the Spanish Ministry of Economy and Competitiveness under the María de Maeztu Units of Excellence Programme [MDM-2015-0502], and the European Commission under the H2020 ATTRACT project MIIFI. Additionally, Enric Perera-Bel has received funding from the Spanish Ministry of Economy and Competitiveness under the Programme for the Formation of Doctors [BES-2017-081164], and Elisenda Eixarch from the Departament de Salut under the Grant SLT008/18/00156.

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Correspondence to Enric Perera-Bel.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards (PIC-39-16, HCB/2016/0138).

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Perera-Bel, E., Ceresa, M., Torrents-Barrena, J. et al. Segmentation of the placenta and its vascular tree in Doppler ultrasound for fetal surgery planning. Int J CARS 15, 1869–1879 (2020). https://doi.org/10.1007/s11548-020-02256-2

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