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


Journal

BMC medical imaging
ISSN: 1471-2342
Titre abrégé: BMC Med Imaging
Pays: England
ID NLM: 100968553

Informations de publication

Date de publication:
02 09 2022
Historique:
received: 09 09 2021
accepted: 29 08 2022
entrez: 2 9 2022
pubmed: 3 9 2022
medline: 9 9 2022
Statut: epublish

Résumé

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). 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. 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. 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.

Sections du résumé

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.

Identifiants

pubmed: 36056307
doi: 10.1186/s12880-022-00888-1
pii: 10.1186/s12880-022-00888-1
pmc: PMC9438215
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

154

Informations de copyright

© 2022. The Author(s).

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Auteurs

Amrei Welp (A)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany.

Michael Gembicki (M)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany.

Christoph Dracopoulos (C)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany.

Jann Lennard Scharf (JL)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany.

Achim Rody (A)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany.

Jan Weichert (J)

Division of Prenatal Medicine, Department of Obstetrics and Gynecology, University Hospital of Schleswig-Holstein, Campus Luebeck, Ratzeburger Allee 160, 23538, Luebeck, Germany. jan.weichert@uksh.de.

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