Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.730596
Title: Antenatal characterisation and postnatal validation of fetal nutritional status using novel fetal imaging methods, neonatal body composition data, and anthropometry
Author: Knight, Caroline L.
ISNI:       0000 0004 6498 511X
Awarding Body: University of Oxford
Current Institution: University of Oxford
Date of Award: 2014
Availability of Full Text:
Access from EThOS:
Full text unavailable from EThOS. Restricted access.
Access from Institution:
Abstract:
Background: Fetal growth restricted (FGR) infants have increased perinatal morbidity and mortality risks. Standard fetal biometry may identify some FGR babies; amniotic fluid measurement and Doppler assessment of blood vessels provide additional, functional assessments, but are often normal in babies with late-onset FGR who are difficult to diagnose. A marker reflecting nutritional status should help to identify FGR fetuses, enabling effective intervention: increased monitoring or delivery and neonatal management. Arm and/or thigh measurements have previously shown potential in 2D and 3D. Limb fat volume has never been measured and could provide an in utero marker of fetal nutritional status. Aims: 1. To develop an ultrasound scanning protocol to acquire 2D images and 3D volumes of fetal arms and thighs. 2. To develop method(s), suitable for use in clinical practice, to measure fat in these images and volumes. 3. To assess the reproducibility of these methods. 4. To assess the validity of these methods by comparing them with MRI images of fetal limb fat. 5. To use these methods in a healthy population to develop reference ranges. 6. To correlate these methods with validated neonatal measurements, to assess whether the antenatal methods reflect neonatal body composition. 7. To apply these methods to longitudinal prospective ultrasound images from multiple countries to assess SGA fetuses. Method: Ultrasound imaging protocols were developed to obtain accurate images and volumes of fetal arms and thighs. Segmentation tools were designed with biomedical engineers to measure fat, lean and limb compartments, and applied to 2D images and 3D volumes (n=500), with calculation of reference centiles in optimally healthy women (INTERGROWTH-21st study) and MRI validation of the ultrasound measurements. Additional methods were assessed: a two-ellipse method, and a three-thickness Fetal Fat Index (FFI). Reproducibility was assessed using Bland-Altman plots and ICCs. Fetal measurements were correlated with neonatal body composition data and anthropometry. Third trimester fetal thigh fat volumes were compared in sub-cohorts of AGA and SGA fetuses. Results: Reference centiles were calculated for novel fractional arm and leg volumes (fat and lean), from 16 to 41 weeks. 2D reference ranges were also calculated. The FFI technique - quick, simple, 2D - correlated well with fat area and fat volume. DXA analyses showed a strong correlation between neonatal limb and whole body fat. Correlation analyses showed that infants with above- and below-average arm circumferences have significantly different amounts of arm fat as early as 30-35 weeks. The strength of correlation between antenatal limb fat and neonatal PEA POD whole body fat increased with increasing gestational age. Scans at 30-34 weeks showed a significant difference in fractional thigh fat between those who would be born SGA compared with AGA. Conclusion: This thesis explores, in detail, the measurement of fetal arm and thigh fat using 2D and 3D ultrasound, and demonstrates that it is correlated to neonatal body composition thus allowing 'fetal body composition' to be established as a research tool; the ultimate aim is to be able to distinguish growth-restricted fetuses from those of normal nutritional status. Novel measurements have been developed, acquisition protocols described, reproducibility assessed, and reference centiles calculated in an optimally healthy population: 2D Fetal Fat Index, 3D fractional limb fat and lean volumes, and limb fat (2D and 3D) as a percentage.
Supervisor: Papageorghiou, Aris T. Sponsor: Wellcome Trust ; EPSRC ; Bill and Melinda Gates Foundation
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.730596  DOI: Not available
Keywords: Obstetrics ; Ultrasound ; Magnetic resonance imaging ; Fat ; Body composition ; Fetal growth
Share: