Automated follicular assessment using a novel two-dimensional ultrasound-based solution
Celine Firtion1, Ganesan Ramachandran2, Sindhu P Nellur Prakash1, Sujitkumar Hiwale1, Pallavi Vajinepalli1, Indira Manyam3, Devika Gunasheela3
1 Philips Research India, Philips Innovation Campus, Manyata Tech-Park, Bengaluru, Karnataka, India
2 Philips Research India, Philips Innovation Campus, Manyata Tech-Park, Bengaluru, Karnataka; KLA Corporation, Chennai, Tamil Nadu, India
3 Gunasheela Surgical and Maternity Hospital, Bengaluru, Karnataka, India
Philips Research India, Philips Innovation Campus, Manyata Tech-Park, Bengaluru, Karnataka
Source of Support: None, Conflict of Interest: None
Background: High intra- and interobserver variability in the follicular assessment using two-dimensional (2D) ultrasound (US) is still a concern. To solve this issue, we have developed a novel software solution, which automatically provides follicles' count and their diameters using 2D US images obtained by a manual sweep of an ovary. The primary objective of this study was to compare the result of the automated solution with a manual 2D US-based assessment. Methods: In the first phase, multiple follicular US sweeps were collected from 54 subjects; these sweeps were used to develop the software. In the second phase, data from 10 subjects were collected for validation of the developed solution. During each phase, for follicles ≥5 mm, their count and diameters were recorded by the sonologist using 2D US. Results: For the total follicle count, a high correlation (0.787) was observed between the solution and manual assessment. The 95% limits of agreement between the two methods were in the range of 4.232 to −4.258. The two methods had an excellent correlation (0.817) for the measurement of mean follicular diameter. However, the solution had a tendency to underestimate the mean diameter by an average of 1.725 mm (±2.16 mm). The limits of agreement between the two methods for mean diameter measurement were from 2.508 to −5.960 mm. Conclusion: This study validates the feasibility of our solution for automatic assessment of follicle count and diameter with accuracy comparable to the 2D US-based manual assessment. We further observed that the solution's performance is better than known intra- and interobserver variability of the manual assessment. We recommend further validation of the solution to confirm these initial results and potential time gain with an automated assessment.