Ignite Creation Date:
2025-12-25 @ 4:46 AM
Ignite Modification Date:
2025-12-26 @ 3:48 AM
Study NCT ID:
NCT04545918
Status:
UNKNOWN
Last Update Posted:
2021-05-07
First Post:
2020-09-04
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Convolutional Neural Network in Ovarian Follicle Identification
Sponsor:
Cycle Clarity
Organization:
Study Overview
Official Title:
Assessing a Mask Region-based Convolutional Neural Network in Follicle Identification and Measurement During Ovarian Stimulation
Status:
UNKNOWN
Status Verified Date:
2021-05
Last Known Status:
RECRUITING
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:
A prospective cohort trial studying patients with infertility undergoing an ovarian stimulation with exogenous gonadotropins. Ovarian monitoring will be performed with a combination of transvaginal ultrasound and 2 dimensional human measurements of the follicle development on the right and left ovaries along with SonoAVC. Human and SonoAVC measurements will then be compared to mask region-based convolutional neural network in follicle identification and measurement during during the ovarian stimulation.
Detailed Description:
This is a prospective cohort trial in which a total of 80 female subjects with infertility between the ages of 21 and 42 years of age undergoing ovarian stimulation will be recruited. After giving informed written consent the subject to undergo standard ovarian ultrasound monitoring with transvaginal ultrasounds during the ovarian stimulation. Monitoring will be performed with two-dimensional measurements of each follicle greater than 10 mm in size by the ultrasonographer. SonoAVC will then be applied to both ovaries for automated counting and measurement of the follicles within the ovaries. The patient will then undergo two 6-second ultrasounds of the right and left ovaries which will then be transmitted in a DICOM format to mask regional based recurrent neural network which is been trained and validated for follicle detection and quantification using curated transvaginal ultrasound images.
Study Oversight
Has Oversight DMC:
False
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
True
Is an Unapproved Device?:
True
Is a PPSD?:
None
Is a US Export?:
False
Is an FDA AA801 Violation?: