Applicability of a semiautomated volumetric approach (5D CNS+™) for detailed antenatal reconstruction of abnormal fetal CNS anatomy

Abstract

BACKGROUND: The aim of this study was to evaluate the accuracy and reliability of a semiautomated volumetric approach (5D CNS+™) when examining fetuses with an apparent abnormal anatomy of the central nervous system (CNS).

METHODS: Stored 3D volumes extracted from a cohort of > 1.400 consecutive 2nd and 3rd trimester pregnancies (range 15-36 gestational weeks) were analyzed using the semiautomatic software tool 5D CNS+™, enabling detailed reconstruction of nine diagnostic planes of the fetal brain. All 3D data sets were examined and judged for plane accuracy, the need for manual adjustment, and fetal CNS anomalies affecting successful plane reconstruction.

RESULTS: Based on our data of 91 fetuses with structural cerebral anomalies, we were able to reveal details of a wide range of CNS anomalies with application of the 5D CNS+™ technique. The corresponding anatomical features and consecutive changes of neighboring structures could be clearly demonstrated. Thus, a profound assessment of the entire altered CNS anatomy could be achieved in nearly all cases. The comparison with matched controls showed a significant difference in volume acquisition (p < 0.001) and in need for manual adjustment (p < 0.001) but not in the drop-out rates (p = 0.677) of both groups.

CONCLUSION: 5D CNS+™ is applicable in the majority of cases with brain lesions and constitutes a reliable tool even if the integrity of the fetal CNS is compromised by structural anomalies. Using volume data that were acquired in identical cutting sections needed for conventional biometry allows for detailed anatomic surveys grossly independent of the examiner's experience.

Original languageEnglish
JournalBMC medical imaging
Volume22
Issue number1
Pages (from-to)154
ISSN1471-2342
DOIs
Publication statusPublished - 02.09.2022

Research Areas and Centers

  • Research Area: Luebeck Integrated Oncology Network (LION)
  • Centers: University Cancer Center Schleswig-Holstein (UCCSH)
  • Centers: Center for Rare Diseases (ZSE)

DFG Research Classification Scheme

  • 205-21 Gynaecology and Obstetrics
  • 205-32 Medical Physics, Biomedical Engineering

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