Validation of a semiautomated volumetric approach for fetal neurosonography using 5DCNS+ in clinical data from > 1100 consecutive pregnancies

Abstract

Objective The aim of this study was to evaluate the validity of a semiautomated volumetric approach (5DCNS+) for the detailed assessment of the fetal brain in a clinical setting. Methods Stored 3D volumes of > 1100 consecutive 2nd and 3rd trimester pregnancies (range 15-36 gestational weeks) were analyzed using a workflow-based volumetric approach 5DCNS+, enabling semiautomated reconstruction of diagnostic planes of the fetal central nervous system (CNS). All 3D data sets were examined for plane accuracy, the need for manual adjustment, and fetal-maternal characteristics affecting successful plane reconstruction. We also examined the potential of these standardized views to give additional information on proper gyration and sulci formation with advancing gestation. Results Based on our data, we were able to show that gestational age with an OR of 1.085 (95% CI 1.041-1.132) and maternal BMI with an OR of 1.022 (95% CI 1.041-1.054) only had a slight impact on the number of manual adjustments needed to reconstruct the complete volume, while maternal age and fetal position during acquisition (p = 0.260) did not have a significant effect. For the vast majority (958/1019; 94%) of volumes, using 5DCNS+ resulted in proper reconstruction of all nine diagnostic planes. In less than 1% (89/9171 planes) of volumes, the program failed to give sufficient information. 5DCNS+ was able to show the onset and changing appearance of CNS folding in a detailed and timely manner (lateral/parietooccipital sulcus formation seen in < 65% at 16-17 gestational weeks vs. 94.6% at 19 weeks). Conclusions The 5DCNS+ method provides a reliable algorithm to produce detailed, 3D volume-based assessments of fetal CNS integrity through a standardized reconstruction of the orthogonal diagnostic planes. The method further gives valid and reproducible information regarding ongoing cortical development retrieved from these volume sets that might aid in earlier in utero recognition of subtle structural CNS anomalies.

The Use of Artificial Intelligence in Automation in the Fields of Gynaecology and Obstetrics – an Assessment of the State of Play

“…The latter working group documented successful visualisation rates of 97.7 – 99.4% for axial, 94.4 – 97.7% for sagittal and 92.2 – 97.2% for coronal planes in a prospective follow-up study using the 5DCNS+ modified algorithm 67 . A retrospective clinical validation study of more than 1100 pregnant women yielded similar results 68 . In contrast to the data of Pluym et al, the authors were able to show in their study, among other things, that this standardised approach could be used to collect biometric parameters that, in comparison, were similarly valid and reproducible to those obtained manually 69 .…”

“…Letztere Arbeitsgruppe konnte in einer prospektiven Folgestudie mit der Programmerweiterung 5DCNS+ erfolgreiche Visualisierungsraten von 97,7 bis 99,4% für axiale, 94,4 bis 97,7% für sagittale und 92,2 bis 97,2% für koronale Ebenen dokumentieren 67 . Zu ähnlichen Ergebnissen kam auch eine retrospektive klinische Validierungsstudie an mehr als 1100 Schwangeren 68 . Im Gegensatz zu den Daten von Pluym et al konnten die Autoren in ihrer Studie u. a. zeigen, dass mit diesem standardisierten Ansatz vergleichbar valide und reproduzierbare biometrische Parameter wie im Vergleich zu manuellem Vorgehen erhoben werden können 69 .…”

Computational methods for the analysis of early-pregnancy brain ultrasonography: a systematic review

“…3 gives an overview of the detection accuracy and the GA range. 23 , 28 , 33 , 34 , 37 , 59 , 60 , 61 , 62 , 63 , 64 The best results for the TT plane were achieved by Kong et al. and the best results for the TC and TV plane were achieved by Sridar et al.…”

Applicability of a Semiautomated Volumetric Approach (5D CNS+™) for Detailed Antenatal Reconstruction of Abnormal Fetal CNS Anatomy

“…28 Qualitative and quantitative studies of cortical development evaluation using volume data sets clearly showed the potential of multiplanar assessment and con rmed 3D US as a robust diagnostic method. 14,29,30 Detailed prenatal judgment of even subtle changes in terms of cortical grading and sulci shape and depth is feasible [31][32][33][34] , but it necessitates exact image alignment and, more strikingly, an awareness of the adequacy of planar image adjustment based on anatomical landmarks, as described in the current literature. 29,35 In fact, quite a number of the studies analyzed volume information derived from transvaginally acquired 3D datasets, as these showed a higher image resolution (through US propagation via the sagittal suture and subsequent volume postprocessing).…”

“…It has recently been shown that automated volumetric approaches e ciently enable rapid and standardized evaluation of the fetal brain in terms of basic examination [41][42][43] or reconstruction of an entire neurosonogram. [12][13][14] By simplifying the evaluation process of basic and/or advanced CNS examination, these algorithms might aid in earlier detection of abnormal CNS anatomy in utero. However, it remains widely unclear how these automatic techniques are of clinical use in delineating different CNS lesions by means of proper plane reconstruction and visualization of structural defects in detail.…”