Operator-dependent ultrasound workflows struggle to keep up with rising measurement demands

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BY INSIDE REPRODUCTIVE HEALTH

Manual ultrasound workflows are increasingly constraining IVF clinics as patient volumes rise and stimulation protocols become more measurement-sensitive. Many clinics continue to rely on legacy systems that require clinicians to manually identify, count, and measure follicles at each visit. The result is longer scan times, variability between operators, and workflow strain that compounds across a clinic day.

These pressures are most evident during stimulation cycles with high follicle counts. Irregular follicle shapes, crowding, and anatomical variation complicate two-dimensional assessment, increasing scan duration and dependence on individual interpretation. Clinics report delays, bottlenecks, and reduced confidence in measurements, even as they attempt to standardize protocols and staffing practices.

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2D Imaging Underestimates Follicle Size by 1.6–2.1 mm

Published studies comparing two-dimensional and three-dimensional ultrasound have shown that 2D imaging underestimates follicle size by an average of approximately 1.6–2.1 mm relative to 3D measurement, according to findings indexed on PubMed. Because trigger timing and oocyte retrieval decisions often hinge on millimeter-level thresholds, these discrepancies carry direct operational implications for stimulation management.

Additional IVF studies have found that three-dimensional ultrasound metrics — including antral follicle count, follicle volume, and stromal blood flow — are more predictive of ovarian response and IVF outcomes than older measurement parameters, reinforcing the limitations of manual 2D workflows as protocols become more data-driven.

Observer Variability Reaches ~20% Under High Follicle Load

Operator dependence remains a defining limitation of legacy ultrasound systems. Under conditions where multiple follicles grow simultaneously, inter- and intra-observer variability has been estimated at up to ~20%, driven by differences in experience, fatigue, and subjective interpretation.

For REIs, advanced practice providers, embryologists, and clinical area directors, this variability translates into inconsistent counts, longer scan times, and difficulty managing patient throughput. Clinics have attempted to mitigate these issues through training, protocol alignment, and quality audits, but those measures do not eliminate the manual steps embedded in older equipment.

Automation Shifts Imaging From Interpretation to Measurement

As these pressures intensify, imaging workflows in reproductive medicine are beginning to shift away from manual interpretation toward automated measurement. Reviews of emerging ultrasound technologies point to growing adoption of AI-enabled systems designed to reduce manual measurement time, standardize data capture, and support scalable care as patient volumes increase.

Three-dimensional volumetric follicle assessment and automated uterine measurement are central to this shift. By reducing reliance on operator judgment, these approaches aim to deliver more reproducible measurements across clinicians and visits, addressing variability that training alone cannot resolve.

Replacing Legacy Ultrasound With Reproducible Scanning Workflows

Within this broader transition, Samsung has introduced its V6 ultrasound platform, positioning AI-powered automation as a replacement for manual fertility imaging workflows. The system applies automated 3D volumetric measurement to ovarian follicles and AI-based uterine assessment to reduce scan time and operator dependence.

At the center of the platform is 5D Follicle™, which automates volumetric measurement across multiple follicles to support faster, reproducible assessment. Additional tools automate uterine measurement and endometrial detection aligned with established classification standards. Workflow features such as customizable controls, automated annotations, and streamlined measurement labeling are designed to reduce repetitive manual steps common to legacy systems.

As clinics confront rising patient volumes, tighter treatment timing, and limited staffing flexibility, the move from manual interpretation to automated measurement is emerging as a structural shift in fertility imaging. For practices reassessing legacy ultrasound infrastructure, Samsung is positioning AI-powered automation as a practical alternative to operator-dependent workflows.