A Trial on the Use of Point-of-care Ultrasound in the Assessment of Breast Symptoms

NCT06932133 | Active Not Recruiting FDA Device

• 1 other identifier: CIV-ID 24-10-049596
• Study Type: interventional
• Target: 600
• Locations: 1 country
• Sites: 1

Brief Summary

The high cost of diagnostic equipment, limited expertise, and inadequate infrastructure are major barriers to early breast cancer diagnosis in low- and middle-income countries. Point-of-care ultrasound (POCUS) offers a relatively low-cost, portable solution that, when combined with artificial intelligence (AI)-driven image analysis, has the potential to significantly expand access to breast assessment in these settings. The purpose of this study is to evaluate the performance of POCUS for women with focal breast symptoms and to assess the performance of AI to analyze POCUS images. The study will be divided in two parts: a prospective interventional study and a retrospective multicase multireader study.

Conditions

Breast Cancer

Keywords

artificial intelligence, point-of-care ultrasound

Outcome Measures

Primary Outcomes (1)

• The area under the receiver operating characteristic curve (AUC) for the intervention, compared to that of the comparator

  1. The AUC of POCUS compared to SoC 2. The AUC of AI compared to average radiologists on POCUS

  From the last enrolled participant to the end of one-year follow up

Secondary Outcomes (1)

• The performance of POCUS and POCUS AI

  From the last enrolled participants to the end of one year follow up

Study Arms (1)

Intervention

EXPERIMENTAL

Diagnostic Test: Point-of-care ultrasound

Interventions

Point-of-care ultrasound DIAGNOSTIC_TEST

Point-of-care ultrasound will be performed on symptomatic breast patients. The images will be analysed by AI

Intervention

Eligibility Criteria

• Age: 18 Years+
• Sex: female
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Women (≥18 years of age) referred to diagnostic imaging with a suspicion on malignancy

You may not qualify if:

• Individuals unable to comprehend the study information due to language barriers or cognitive impairments.

Sponsors & Collaborators

• Region Skane: lead

Study Sites (1)

Unilabs Mammography Unit, Skane University Hospital

Malmo, 20502, Sweden

Location

Related Publications (3)

• Karlsson J, Arvidsson I, Sahlin F, Astrom K, Overgaard NC, Lang K, Heyden A. Breast cancer classification in point-of-care ultrasound imaging-the impact of training data. J Med Imaging (Bellingham). 2025 Jan;12(1):014502. doi: 10.1117/1.JMI.12.1.014502. Epub 2025 Jan 17.

  PMID: 39830074 BACKGROUND

• Karlsson, J, Wodrich, M, Overgaard, NC, Sahlin, F, Lång, K, Heyden, A & Arvidsson, I 2025, Towards Out-of-Distribution Detection for Breast Cancer Classification in Point-of-Care Ultrasound Imaging. in, Pattern Recognition - 27th International Conference, ICPR 2024, Proceedings, Part XIII. Lecture Notes in Computer Science

  BACKGROUND

• Wodrich, M, Karlsson, J, Lång, K & Arvidsson, I 2025, Trustworthiness for Deep Learning Based Breast Cancer Detection Using Point-of-Care Ultrasound Imaging in Low-Resource Settings. in Medical Information Computing: MICCAI Meets Africa Workshop, https://doi.org/10.1007/978-3-031-79103-1_5.

  BACKGROUND

Related Links

• Official webpage of Lund University research portal and the webpage of the PI

MeSH Terms

Conditions

Breast Neoplasms

Condition Hierarchy (Ancestors)

Neoplasms by Site; Neoplasms; Breast Diseases; Skin Diseases; Skin and Connective Tissue Diseases

Study Officials

• Kristina Lång, MD PhD

  Lund University, Unilabs Mammography

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 10, 2025
• First Posted: April 17, 2025
• Study Start: April 7, 2025
• Primary Completion: February 12, 2026
• Study Completion (Estimated): February 12, 2027
• Last Updated: March 30, 2026

Record last verified: 2026-02

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL, SAP
• Time Frame: Supporting information will be available from study start and up to 10 years after study completion. IPD will be available at the publication of results, if conditions are met.
• Access Criteria: See plan description

Locations

SE (1)