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Completed

NCT Number: NCT07287111

Effectiveness of CadAI-B Dx for Decision Support in Breast Ultrasound

This is a retrospective, fully-crossed, multi-reader, multi-case (MRMC) study to evaluate the effectiveness of 'CadAI-B Dx' (CadAI-B) for decision support in breast ultrasound. The study compares the diagnostic performance of readers interpreting breast ultrasound images with and without the aid of CadAI-B. A total of 797 patient cases will be included, comprising 350 cases with a confirmed diagnosis of malignancy and 447 cases with a confirmed benign diagnosis. Sixteen readers will participate in the study to evaluate the device.

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Key information

Age range

22 year and older

Sex eligibility

Female

Study type

Interventional

Phase

Not applicable

Primary location

Yonsei University Severance Hospital

Seoul, 03722, South Korea

About this study

The study utilizes a crossover design where all readers independently review all cases. The control arm consists of a reading session where participating readers independently review cases without the assistance of the CadAI-B device (unaided reading). The experimental arm involves reading with CadAI-B assistance (AI-aided reading). To minimize potential bias, a washout period of four weeks will be maintained between the unassisted and assisted reading sessions for each reader. The primary hypothesis is that CadAI-B assistance significantly improves overall reader performance in breast ultrasound interpretation, as measured by the area under the Localization Receiver Operating Characteristic (LROC) curve (AULROC).

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Women aged 22 years or older at the time of the breast ultrasound examination.
  • Standard B-mode breast ultrasound images available for analysis.
  • Lesions must have a confirmed diagnosis based on one of the following reference standards:

3-1. Malignant Cases: Diagnosis of breast cancer confirmed through biopsy or surgery.

3-2. Benign Cases: Confirmed as benign through biopsy or surgical excision, or confirmed as having no evidence of malignancy for at least 2 years of follow-up.

Exclusion criteria

  • mages containing modes other than standard B-mode ultrasound, such as Doppler, elastography, or other annotations/overlays.
  • Patients who have breast implant(s).
  • Patients suffering from significant breast trauma or mastitis at the time of the breast ultrasound examination.
  • Images of post-surgical resection sites.
  • Images where multiple lesions are present within a single 2D ultrasound image

Treatment and study plan

CadAI-B Dx

Device

CadAI-B Dx is a Software as a Medical Device (SaMD) designed to assist physicians by providing Computer-Aided Detection (CADe) and Diagnosis (CADx) capabilities in breast ultrasound interpretation. The software automatically processes the image to identify suspicious regions (Lesion Detection) and provides a quantitative malignancy score (CadAI-Score) mapped to a corresponding BI-RADS Category. It also analyzes lesion size and BI-RADS lexicon descriptors.

Primary outcomes

  1. Area Under the Localization Receiver Operating Characteristic (LROC) Curve (AULROC)

    Time frame: Through study completion, approximately 2 months

    The difference in reader performance between the unaided and AI-aided sessions in breast ultrasound interpretation. LROC reflects both detection accuracy and localization precision. The primary hypothesis is that the mean AULROC of all readers for the AI-aided reading mode is greater than that for the unaided reading mode.

Secondary outcomes

  1. Sensitivity

    Time frame: Through study completion, approximately 2 months

    Comparison of the average sensitivity of the readers between the unaided and AI-aided sessions.

  2. Positive Predictive Value (PPV)

    Time frame: Through study completion, approximately 2 months

    Comparison of PPV between unaided and AI-aided sessions. The PPV will be adjusted for disease prevalence in the target population to reflect real-world clinical practice.

  3. Negative Predictive Value (NPV)

    Time frame: Through study completion, approximately 2 months

    Comparison of NPV between unaided and AI-aided sessions. The NPV will be adjusted for disease prevalence in the target population.

  4. Inter-reader Agreement

    Time frame: Through study completion, approximately 2 months

    Evaluation of the consistency of interpretations among different readers. Inter-reader agreement for BI-RADS category and descriptors assignments will be compared between sessions using Kappa statistics.

  5. Reading Time

    Time frame: Through study completion, approximately 2 months

    Comparison of the average reading time per case between the unaided and AI-aided sessions to assess if the AI system improves the efficiency of interpretation.

  6. AI-Ground Truth Agreement

    Time frame: Through study completion, approximately 2 months

    Assessment of the agreement between the AI system's outputs and the ground truth. This includes agreement on BI-RADS categories and descriptors (using Kappa statistics) and lesion size measurements (using Intraclass Correlation Coefficient).

Sponsors and collaborators

Lead sponsor

BeamWorks Inc.

Industry

Registry information

Official study title

Multi-Reader Multi-Case, Cross-Over, Retrospective Study to Evaluate the Effectiveness of CadAI-B Dx for Decision Support in Breast Ultrasound

Important dates

Study start
2025
Primary completion
2025
Study completion
2025
First posted
Dec 17, 2025
Registry last updated
Dec 17, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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