Clinical trial NCT03002246: Automated Fetal Weight Estimation: A Multicenter Validation Using Fractional Limb Volume
Official title: Automated Fetal Weight Estimation: A Multicenter Validation Using Fractional Limb Volume
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Birth Weight
Fetal Growth Retardation
Fetal Weight
Fetal Macrosomia
Lead sponsor: Baylor College of Medicine
Sponsor class: OTHER
Collaborators: name: Samsung Medison Co., Ltd.
name: Beijing Obstetrics and Gynecology Hospital
name: Frauenklinik der Diakonischen Dienste Hannover
name: University of Pittsburgh
First posted: 2016-12-23
Enrollment: 330
Sex: FEMALE
Minimum age (years): 18
Maximum age (years): 64
Standard ages: ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Pregnant women between 28-42 weeks gestation. Fetuses will be either small for gestational age (estimated fetal weight \< 10%), average for gestational age, or large for gestational age (estimated fetal weight \> 90%).

Brief summary: This trial is a collaborative study between 4 sites worldwide. A total of 600 research subjects will be enrolled. We will investigate the validity of using 5D Limb Volume software to improve on estimated fetal weight predictions over a broad range of gestational ages. The purpose is to compare the accuracy and precision of birth weight predictions based on this new technology as compared to the current 2D birth weight prediction models.

Detailed description: Ultrasound has been used for over 20 years to estimate fetal weight prior to birth. Sometimes this estimation is not always similar to what the baby actually weighs. In addition to the regular measurements taken at routine ultrasound exams, 3D ultrasound of the baby's arm and leg soft tissue may give us more precise information on how much the baby weighs. This measurement is called fractional limb volume. Fractional limb volume (FLV) is a soft tissue measurement of the arm or thigh that can be used to evaluate body composition. This measurement mostly reflects the fat and muscle development with a small amount of bone.

The recent introduction of 5D Limb Volume software (Samsung, Seoul, Korea) now makes it possible to efficiently and reproducibly measure semi-automated FLV using a computer guided technique.

Subjects will receive one ultrasound scan 4-7 days before their delivery. Both 2D and 3D measurements will be taken. These measurements will then be used to estimate fetal weight. We will compare estimated weight to actual birth weight in order to determine the accuracy and precision of the 5D Limb Volume technology. This data may also be used to develop new weight estimation models that could provide better accuracy and/or precision than what is currently provided using published methods.

Eligibility criteria: Inclusion Criteria:

1. Pregnant women (28-42 weeks) within 4-7 days of delivery
2. Planned delivery at the collaborating hospital where the fetal US scan was performed
3. Body mass index at first official prenatal appointment below 35.0 kg/M2
4. Firm US dating criteria (early crown-rump length \< 14 weeks gestational age)

Exclusion Criteria:

1. Presence of technical factors (e.g. obesity) that make it difficult to visualize fetal structures
2. Oligohydramnios determined by amniotic fluid index less than 5cm
3. Fetal distress or unstable maternal condition
4. Structural or chromosomal fetal anomalies

Primary outcomes:
measure: Comparison Between 5D Limb Vol and 2D Birth weight Prediction
timeFrame: Feb 2017 -Feb 2018
Secondary outcomes:
measure: Birth weight Predictions in Suspected Growth Abnormalities
timeFrame: Feb 2017 - Feb 2018
Other outcomes:
Locations:
Study officials:
affiliation: Baylor College of Medicine
name: Wesley Lee, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Kang L, Wu QQ, Sun LJ, Gao FY, Wang JJ. Predicting fetal weight by three-dimensional limb volume ultrasound (AVol/TVol) and abdominal circumference. Chin Med J (Engl). 2021 Apr 20;134(9):1070-1078. doi: 10.1097/CM9.0000000000001413.