Fetal nuchal skin-fold thickness during the 2nd trimester of pregnancy

Enhancing Small-for-Gestational-Age Prediction: Multi-Country Validation of Nuchal Thickness, Estimated Fetal Weight, and Machine Learning Models

OBJECTIVE

The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants.

METHOD

This retrospective study involved singleton pregnancies at University Malaya Medical Centre, Malaysia, developed a nuchal thickness chart and evaluated its predictive value for small-for-gestational-age using Malaysian and Singapore cohorts. Predictive performance using conjunctive (AND)/disjunctive (OR) rule-based algorithms was assessed. Seven machine learning models were trained on Malaysia data and evaluated on both Malaysia and Singapore cohorts.

RESULTS

5519 samples were collected from the University Malaya Medical Centre. Small-for-gestational-age infants exhibit significantly lower nuchal thickness (small-for-gestational-age: 4.57 [1.04] mm, appropriate-for-gestational-age: 4.86 [1.06] mm, p < 0.001). Implementing disjunctive rule (nuchal thickness < 10th centile or estimated fetal weight < 10th centile) significantly improved small-for-gestational-age prediction across all growth charts, with balanced accuracy gains of 5.83% in Malaysia (p < 0.05) and 7.75% in Singapore. The best model for predicting small-for-gestational-age was: logistic regression with five variables (abdominal circumference, femur length, nuchal thickness, maternal age, and ultrasound-confirmed gestational age), which achieved an area under the curve of 0.75 for Malaysia cohorts; support vector machine with all variables, achieved area under the curve of 0.81 for Singapore cohorts.

CONCLUSIONS

Small-for-gestational-age infants demonstrate significantly reduced second-trimester nuchal thickness. Employing the disjunctive rule enhanced small-for-gestational-age prediction. Logistic regression and support vector machines show superior performance among all models, highlighting the advantages of machine learning. Larger prospective studies are needed to assess clinical utility.

Fetal head and neck tumors

Imaging plays a leading role in detection and diagnosis of fetal head and neck lesions. These lesions comprise a heterogeneous group of congenital tumors and malformations. Complementary imaging modalities that can be used in prenatal medicine are ultrasound and MRI. The authors discuss imaging characteristics of fetal lesions, assessment of potential complications and pregnancy management options for the most common pathology of the fetal head and neck.

Reference values of nuchal fold thickness in an Iranian population sample

Background:

Considering that ethnicity and gestational age (GA) could affect the value of nuchal fold thickness (NFT) in mid-trimester, we aimed to determine the reference intervals of NFT values for each gestational week from 16 to 24 weeks of pregnancy among a group of Iranian pregnant women.

Materials and Methods:

In this cross-sectional study, medical files of pregnant women who underwent fetal anomaly scanning at 16–24 weeks of gestation were reviewed and the following data were extracted: GA, value of NFT, value of nuchal translucency (NT) in their previous ultrasound study, if available, and head circumference (HC). The 5^th, 25^th, 50^th, 75^th, and 95^th percentiles of NFT for each gestational week were determined. The association between NFT and HC, GA, and NT were also determined.

Results:

Medical files of 882 pregnant women were studied. The expected 95^th percentile value of NFT between 16^th and 24^th weeks of gestation ranged from 4 mm to 5.9 mm. The mean (standard deviation) of NFT increased with GA from 2.67 (0.90) mm at 16^th weeks to 4.69 (0.71) mm at 24^th weeks. There was a significant positive association between NFT and GA (β = 1.11, p < 0.001), HC (β = 0.21, p < 0.001), and NT (β = 0.351, p < 0.001).

Conclusion:

The findings of this study revealed that before the 20^th week of gestation, the appropriate cutoff value of NFT is 5 mm, and for 21^st to 24^th weeks, the proper cutoff is 6 mm. However, for providing more conclusive results, further studies with larger sample size and considering the impact of other influencing variables are recommended.