Ignite Creation Date:
2024-05-06 @ 4:41 PM
Last Modification Date:
2024-10-26 @ 2:14 PM
Study NCT ID:
NCT05059093
Status:
COMPLETED
Last Update Posted:
2022-07-27
First Post:
2021-09-07
Brief Title:
Developing and Testing AI Models for Fetal Biometry and Amniotic Volume Assessment in Fetal Ultrasound Scans
Sponsor:
Deepecho
Organization:
Deepecho
Study Overview
Official Title:
Developing and Testing Deep Learning Models for Fetal Biometry and Amniotic Volume Assessment in Routine Fetal Ultrasound Scans
Status:
COMPLETED
Status Verified Date:
2022-07
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Routine fetal ultrasound scan during the second trimester of the pregnancy is a low-cost noninvasive screening modality that has been proven to lower fetal mortality by up to 20 One of the critical elements of this exam is the measurement of fetal biometric parameters which are the head circumference HC biparietal diameter BPD abdominal circumference AC and femur length FL measured on biometry standard planes Those standard planes are taken according to quality standards first described by Salomon et al and used as the guidelines of the International Society of Ultrasound in Obstetrics and Gynecology ISUOG The biometric parameters extracted from them are essential to diagnose fetal growth restriction FGR the worlds first cause of perinatal fetal mortality
Such measurements and image quality assessment are time-consuming tasks that are prone to inter and intraobserver variability depending on the level of skill of the sonographer or the physician performing the exam
Amniotic fluid AF volume assessment is also an essential step in routine screening scans allowing the diagnosis of oligo or hydramnios both associated with increased fetal mortality rates
The AF is measured by two main semi-quantitative techniques Amniotic Fluid Index AFI and the single deepest pocket SDP The latter is more specific as it lowers the overdiagnosis of oligo-amnios without any impact on mortality or morbidity and is easier to perform for the sonographer only one measurement versus four in the case of the AFI technique However AF assessment remains a time-consuming and poorly reproducible task
Attempts to automate such biometric measurements and AF volume assessment have been made using Artificial Intelligence AI and deep learning DL tools Studies showed excellent results in silico reaching up to 98 95 93 dice score coefficients for HC AC and FL measurements and 89 DSC for AFI measurements However they were all conducted retrospectively without validation on prospectively acquired images
Reviews and experts have stressed the need for quality peer-reviewed prospective studies to assess AI tools performance with real-world data Their performance is expected to be worse and to reflect better their use in the clinical workflow
This study aims to develop DL models to automate HC BPD AC and FL measurements and AF volume assessment from retrospectively acquired data and test their performances to those of clinicians and experts on prospective real-world fetal US scans
Such measurements and image quality assessment are time-consuming tasks that are prone to inter and intraobserver variability depending on the level of skill of the sonographer or the physician performing the exam
Amniotic fluid AF volume assessment is also an essential step in routine screening scans allowing the diagnosis of oligo or hydramnios both associated with increased fetal mortality rates
The AF is measured by two main semi-quantitative techniques Amniotic Fluid Index AFI and the single deepest pocket SDP The latter is more specific as it lowers the overdiagnosis of oligo-amnios without any impact on mortality or morbidity and is easier to perform for the sonographer only one measurement versus four in the case of the AFI technique However AF assessment remains a time-consuming and poorly reproducible task
Attempts to automate such biometric measurements and AF volume assessment have been made using Artificial Intelligence AI and deep learning DL tools Studies showed excellent results in silico reaching up to 98 95 93 dice score coefficients for HC AC and FL measurements and 89 DSC for AFI measurements However they were all conducted retrospectively without validation on prospectively acquired images
Reviews and experts have stressed the need for quality peer-reviewed prospective studies to assess AI tools performance with real-world data Their performance is expected to be worse and to reflect better their use in the clinical workflow
This study aims to develop DL models to automate HC BPD AC and FL measurements and AF volume assessment from retrospectively acquired data and test their performances to those of clinicians and experts on prospective real-world fetal US scans
Detailed Description:
The DL models will be trained validated and tested on the retrospectively acquired data first This data will consist of fetal US images gathered in the participating medical centers after patient-level anonymization The ground truth for the models will consist of annotations made by radiologists and obstetricians for classification and segmentation purposes The DL models will be trained to perform the following tasks
Detection of the following standard planes as described in the ISUOG guidelines transthalamic transventricular transcerebellar abdominal and femoral planes on video loops
Image quality scoring according to the ISUOG guidelines of the transthalamic abdominal and femoral planes
Fetal cranium abdomen and femur segmentation to measure HC BPD AC and FL
Detection of AF pockets
Segmentation of AF pockets and extraction of pockets depth in order to evaluate the SDP measurement
Physicians will be asked to save additional images and video loops additional to their routine screening in the prospective examinations
Eight images transthalamic abdominal and femoral standard planes with and without calipers SDP with and without calipers
Four video loops up to five seconds each
A cephalic loop encompassing the transcerebellar transthalamic and transventricular planes
An abdominal loop going from the four-chamber view of the heart to a cross-section of the kidneys and back
A femoral loop with the probe parallel to the sagittal axis of the femur sweeping from side to side
A whole amniotic cavity loop with the probe perpendicular to the ground applying as little pressure as possible on the patients abdomen sweeping from the uterine fundus to the cervix once or twice depending on the volume of the amniotic cavity
The clinicians performing the exam in real-timeRT clinicians the panel of experts and the DL models will review the prospective examinations
The SDP measurement extracted by the AF pocket detection and segmentation models will be directly compared to the value measured by the RT clinicians
Then the image quality of planes selected by the RT clinicians and the model will be scored by the panel of experts
The segmentation task will be evaluated in a tripartite fashion the model the RT clinicians and the panel will all segment the same images
To assess inter-observer agreement 10 of the images will be randomly selected and reviewed by two independent reviewers from the panel
Detection of the following standard planes as described in the ISUOG guidelines transthalamic transventricular transcerebellar abdominal and femoral planes on video loops
Image quality scoring according to the ISUOG guidelines of the transthalamic abdominal and femoral planes
Fetal cranium abdomen and femur segmentation to measure HC BPD AC and FL
Detection of AF pockets
Segmentation of AF pockets and extraction of pockets depth in order to evaluate the SDP measurement
Physicians will be asked to save additional images and video loops additional to their routine screening in the prospective examinations
Eight images transthalamic abdominal and femoral standard planes with and without calipers SDP with and without calipers
Four video loops up to five seconds each
A cephalic loop encompassing the transcerebellar transthalamic and transventricular planes
An abdominal loop going from the four-chamber view of the heart to a cross-section of the kidneys and back
A femoral loop with the probe parallel to the sagittal axis of the femur sweeping from side to side
A whole amniotic cavity loop with the probe perpendicular to the ground applying as little pressure as possible on the patients abdomen sweeping from the uterine fundus to the cervix once or twice depending on the volume of the amniotic cavity
The clinicians performing the exam in real-timeRT clinicians the panel of experts and the DL models will review the prospective examinations
The SDP measurement extracted by the AF pocket detection and segmentation models will be directly compared to the value measured by the RT clinicians
Then the image quality of planes selected by the RT clinicians and the model will be scored by the panel of experts
The segmentation task will be evaluated in a tripartite fashion the model the RT clinicians and the panel will all segment the same images
To assess inter-observer agreement 10 of the images will be randomly selected and reviewed by two independent reviewers from the panel
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None