BACKGROUND: Ovarian response to gonadotrophin stimulation is monitored with serial ultrasound (US) examinations. Sonography-based Automated Volume Count (SonoAVC) is a relatively new three-dimensional (3D) US technology, which automatically generates a set of measurements including the mean follicular diameter (MFD) and a volume-based diameter (d(V)) for each follicle in the ovaries. The present study aimed to assess the applicability and reproducibility of this automated follicle measurement method in an IVF programme. METHODS: For this prospective method comparison study, 100 women undergoing US monitoring of a controlled ovarian stimulation cycle were recruited. Each follicle was manually measured by taking the mean of maximal diameters on three orthogonal planes with two-dimensional (2D) US. A 3D volume of each ovary was then captured. The ovarian volumes were later analysed using SonoAVC. The agreement between the two methods for the numbers of follicles and the size of the leading follicle was assessed with the Bland-Altman method. The reproducibility of SonoAVC measurements was assessed with the intraclass correlation coefficient (ICC). RESULTS: Both SonoAVC-generated MFD and d(V)-based follicle counts, as well as the leading follicle diameter, had good agreement with conventional 2D US measurements. SonoAVC measurements had very good reproducibility, with ICC ≥0.8 for most evaluations. CONCLUSIONS: Automated follicle monitoring with SonoAVC can replace or be used interchangeably with conventional 2D measurements. Automated follicle monitoring can save time, provide a method of quality control and create opportunities for developing HCG criteria based on follicular volume or for monitoring patients from a distance.
BACKGROUND: Ovarian response to gonadotrophin stimulation is monitored with serial ultrasound (US) examinations. Sonography-based Automated Volume Count (SonoAVC) is a relatively new three-dimensional (3D) US technology, which automatically generates a set of measurements including the mean follicular diameter (MFD) and a volume-based diameter (d(V)) for each follicle in the ovaries. The present study aimed to assess the applicability and reproducibility of this automated follicle measurement method in an IVF programme. METHODS: For this prospective method comparison study, 100 women undergoing US monitoring of a controlled ovarian stimulation cycle were recruited. Each follicle was manually measured by taking the mean of maximal diameters on three orthogonal planes with two-dimensional (2D) US. A 3D volume of each ovary was then captured. The ovarian volumes were later analysed using SonoAVC. The agreement between the two methods for the numbers of follicles and the size of the leading follicle was assessed with the Bland-Altman method. The reproducibility of SonoAVC measurements was assessed with the intraclass correlation coefficient (ICC). RESULTS: Both SonoAVC-generated MFD and d(V)-based follicle counts, as well as the leading follicle diameter, had good agreement with conventional 2D US measurements. SonoAVC measurements had very good reproducibility, with ICC ≥0.8 for most evaluations. CONCLUSIONS: Automated follicle monitoring with SonoAVC can replace or be used interchangeably with conventional 2D measurements. Automated follicle monitoring can save time, provide a method of quality control and create opportunities for developing HCG criteria based on follicular volume or for monitoring patients from a distance.