Convolutional Neural Network in Ovarian Follicle Identification

Infertility, Female Clinical Trial

Official title:

Assessing a Mask Region-based Convolutional Neural Network in Follicle Identification and Measurement During Ovarian Stimulation

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04545918
• Other study ID #: CC2020-001
• Status: Recruiting
• Start date: February 1, 2021
• Est. completion date: May 20, 2021

Study information

• Verified date: May 2021
• Source: Cycle Clarity
• Contact: John A Schnorr, MD
• Phone: 843-883-6200
• Email: john.schnorr[@]cycleclarity.com
• Is FDA regulated: No
• Study type: Observational

Clinical Trial 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.

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.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 80
• Est. completion date: May 20, 2021
• Est. primary completion date: May 10, 2021
• Gender: Female
• Age group: 21 Years to 42 Years

Eligibility

Inclusion Criteria:

• Infertile women ages 21-42 years old undergoing ovarian hyperstimulation as part of the treatment care.

Women with at least one ovary visible with transvaginal ultrasound. Women with at least one follicle 10 mm or greater in average diameter.

Exclusion Criteria:

• Women less than 21 years of age or greater than 42 years of age. Women without a visible ovary by transvaginal ultrasound. Women without a follicle at least 10 mm in average diameter

Related Conditions & MeSH terms

• Infertility
• Infertility, Female
• Ovarian Follicular Cyst

Intervention

Device:
• Follicle Clarity
Mask Region-based Convolutional Neural Network in Ultrasound Follicle Identification

Locations

Country	Name	City	State
United States	Coastal Fertility Specialists	Mount Pleasant	South Carolina

Sponsors (1)

Lead Sponsor	Collaborator
Cycle Clarity

Country where clinical trial is conducted

United States, 

References & Publications (2)

Al-Inany HG, Youssef MA, Ayeleke RO, Brown J, Lam WS, Broekmans FJ. Gonadotrophin-releasing hormone antagonists for assisted reproductive technology. Cochrane Database Syst Rev. 2016 Apr 29;4:CD001750. doi: 10.1002/14651858.CD001750.pub4. Review. — View Citation

Gordon K, Hodgen GD. GnRH analogues in ovarian stimulation. Ann N Y Acad Sci. 1991;626:238-49. Review. — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Median size (mm) of ovarian follicles in CCAI compared to SonoAVC	Comparison of the mean size in mm of Cycle Clarity's Artificial Intelligence software (CCAI) compared with GE SonoAVC	1 month
Secondary	Number of ovarian follicles in CCAI compared to Sono	Comparison of the number of ovarian follicles with Cycle Clarity's Artificial Intelligence software (CCAI) compared with GE SonoAVC	1 month