Abstract
Objectives: Endometrial peristalsis (EP) in non-pregnant uterine can be assessed by visual assessment of transvaginal ultrasound (TVUS). However, visual assessment is subjective, and the outcome depends on the sonographers and video analysts. This study aimed to create a newly developed automatic analysis algorithm for measuring the EP compared to visual assessment. Methods: A retrospective analysis was performed using the datasets from in vitro fertilization and embryo transfer (IVF-ET), who underwent the evaluation of EP by TVUS within 5 days prior to transplantation. 158 cine TVUS images were used to develop the automated analysis algorithm, and 37 cine TVUS images were evaluated by both visual and automated analysis algorithms. The algorithm was developed by applying the optical flow technology and enabled objective analysis of the number, direction, and intensity of EP. Results: The number of peristaltic waves counted by visual assessment was 4.2 ± 2.3 (mean ± standard deviation) and 4.1 ± 2.1 for doctors one and two, respectively. The number of waves counted with the algorithm was 3.6 ± 2.1 at first evaluation and 3.7 ± 2.0 at repeated evaluation. A significant difference was found between the algorithm count and visual assessment (p = 0.001, 0.002, 0.003, 0.008). The ICC values for algorithm versus manuals ranged from 0.84 to 0.96 and 0.87 to 0.96. The numbers of the cervix-to-fundus (CF), fundus-to-cervix (FC), and both cervix-to-fundal and fundus-to-cervix (CF + FC) directions of EP counted by the algorithm were 50, 52, and 32, respectively. The numbers counted by visual assessment were 43, 45, and 46, respectively. The number of EP was the same in 87% of the two algorithm counts. The number was lower between the algorithm and visual analysis (79% with complete agreement). The EP intensity assessed by the algorithm was 2.6 ± 1.1, and the peristalsis velocity was 0.147 (0.07) mm/s. Conclusion: The fully automated analysis algorithm can be used to quantify uterine peristalsis comparable to visual assessment.
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