title: Ultrasound-based gestational-age estimation in late pregnancy.
abstract: OBJECTIVE
  Accurate gestational-age (GA) estimation, preferably by ultrasound measurement of fetal crown-rump length before 14 weeks' gestation, is an important component of high-quality antenatal care. The objective of this study was to determine how GA can best be estimated by fetal ultrasound for women who present for the first time late in pregnancy with uncertain or unknown menstrual dates.
  
  
  METHODS
  INTERGROWTH-21stwas a large, prospective, multicenter, population-based project performed in eight geographically defined urban populations. One of its principal components, the Fetal Growth Longitudinal Study, aimed to develop international fetal growth standards. Each participant had their certain menstrual dates confirmed by first-trimester ultrasound examination. Fetal head circumference (HC), biparietal diameter (BPD), occipitofrontal diameter (OFD), abdominal circumference (AC) and femur length (FL) were measured every 5 weeks from 14 weeks' gestation until delivery. For each participant, a single, randomly selected ultrasound examination was used to explore all candidate biometric variables and permutations to build models to predict GA. Regression equations were ranked based upon minimization of the mean prediction error, goodness of fit and model complexity. An automated machine learning algorithm, the Genetic Algorithm, was adapted to evaluate > 64 000 potential polynomial equations as predictors.
  
  
  RESULTS
  Of the 4607 eligible women, 4321 (94%) had a pregnancy without major complications and delivered a live singleton without congenital malformations. After other exclusions (missing measurements in GA window and outliers), the final sample comprised 4229 women. Two skeletal measures, HC and FL, produced the best GA prediction, given by the equation loge(GA) = 0.03243 × (loge(HC))2+ 0.001644 × FL × loge(HC) + 3.813. When FL was not available, the best equation based on HC alone was loge(GA) = 0.05970 × (loge(HC))2+ 0.000000006409 × (HC)3+ 3.3258. The estimated uncertainty of GA prediction (half width 95% interval) was 6-7 days at 14 weeks' gestation, 12-14 days at 26 weeks' gestation and > 14 days in the third trimester. The addition of FL to the HC model led to improved prediction intervals compared with using HC alone, but no further improvement in prediction was afforded by adding AC, BPD or OFD. Equations that included other measurements (BPD, OFD and AC) did not perform better.
  
  
  CONCLUSIONS
  Among women initiating antenatal care late in pregnancy, a single set of ultrasound measurements combining HC and FL in the second trimester can be used to estimate GA with reasonable accuracy. We recommend this tool for underserved populations but considerable efforts should be implemented to improve early initiation of antenatal care worldwide. © 2016 Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: A T
authors.initials: AT
authors.lastname: Papageorghiou
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: B
authors.initials: B
authors.lastname: Kemp
authors.affiliation: Faculty of Health Sciences, Aga Khan University, Nairobi, Kenya.|School of Medicine, University of St Andrews, St Andrews, Scotland.
authors.forename: W
authors.initials: W
authors.lastname: Stones
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.|Centre for Statistics in Medicine, Botnar Research Centre, University of Oxford, Oxford, UK.
authors.forename: E O
authors.initials: EO
authors.lastname: Ohuma
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: S H
authors.initials: SH
authors.lastname: Kennedy
authors.affiliation: Nagpur INTERGROWTH-21st Research Centre, Ketkar Hospital, Nagpur, India.
authors.forename: M
authors.initials: M
authors.lastname: Purwar
authors.affiliation: Maternité Necker-Enfants Malades, AP-HP, Université Paris Descartes, Paris, France.
authors.forename: L J
authors.initials: LJ
authors.lastname: Salomon
authors.affiliation: Center for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, Oxford, UK.
authors.forename: D G
authors.initials: DG
authors.lastname: Altman
authors.affiliation: Department of Engineering Science, University of Oxford, Oxford, UK.
authors.forename: J A
authors.initials: JA
authors.lastname: Noble
authors.affiliation: Dipartimento di Scienze Pediatriche e dell'Adolescenza, Cattedra di Neonatologia, Università degli Studi di Torino, Turin, Italy.
authors.forename: E
authors.initials: E
authors.lastname: Bertino
authors.affiliation: Global Alliance to Prevent Prematurity and Stillbirth (GAPPS), Seattle, WA, USA.
authors.forename: M G
authors.initials: MG
authors.lastname: Gravett
authors.affiliation: School of Public Health, Peking University, Beijing, China.
authors.forename: R
authors.initials: R
authors.lastname: Pang
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: L
authors.initials: L
authors.lastname: Cheikh Ismail
authors.affiliation: Programa de Pós-Graduação em Saúde e Comportamento, Universidade Católica de Pelotas, Pelotas, RS, Brazil.|Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil.
authors.forename: F C
authors.initials: FC
authors.lastname: Barros
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: A
authors.initials: A
authors.lastname: Lambert
authors.affiliation: Department of Family & Community Health, Ministry of Health, Muscat, Sultanate of Oman.
authors.forename: Y A
authors.initials: YA
authors.lastname: Jaffer
authors.affiliation: Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil.
authors.forename: C G
authors.initials: CG
authors.lastname: Victora
authors.affiliation: Division of Women & Child Health, The Aga Khan University, Karachi, Pakistan.|Center for Global Health, Hospital for Sick Children, Toronto, ON, Canada.
authors.forename: Z A
authors.initials: ZA
authors.lastname: Bhutta
authors.affiliation: Nuffield Department of Obstetrics & Gynaecology and Oxford Maternal & Perinatal Health Institute, Green Templeton College, University of Oxford, Oxford, UK.
authors.forename: J
authors.initials: J
authors.lastname: Villar
mesh_terms: D000328:Adult; D000886:Anthropometry; D018568:Crown-Rump Length; D005260:Female; D047109:Fetal Development; D005865:Gestational Age; D006257:Head / Q000000981:diagnostic imaging* / Q000196:embryology; D006801:Humans; D008137:Longitudinal Studies; D000069550:Machine Learning; D008423:Maternal Age; D011247:Pregnancy; D011261:Pregnancy Trimester, First; D011446:Prospective Studies; D016216:Ultrasonography, Prenatal / Q000379:methods*
keywords: dating; fetal growth; gestational age