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.

In this trial we want to understand if the use of POCUS is non-inferior to Standard of Care (SoC) and if the combination of POCUS AI can reach non-inferior performance to that of breast radiologists. There is a need for breast diagnostic tools in underserved countries since late-stage diagnosis is a major cause of the high breast-cancer mortality in low-and middle-income countries. Showing that POCUS can be sufficient for an assessment of focal breast symptoms can provide evidence for a broader use. Also, enabling automated interpretation using AI can add to the value of this low-cost and accessible solution. The first part of the trial is a prospective open-label accuracy study with paired design. The intervention of POCUS as a targeted diagnostic method for women with focal breast complaints will be compared with SoC. We will also be able to compare POCUS with the individual components of SoC (mammography and standard ultrasound) and retrospectively with POCUS AI. The second part of the trial is a single-blinded retrospective paired mulitcase multireader study. In this part we can directly assess POCUS and POCUS AI without the influence of mammography and benchmark to a larger group of radiologists and in addition compare with standard ultrasound

Inclusion Criteria:

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

Exclusion Criteria:

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

De-identified data will be made available upon reasonable request, with investigator support and a signed data access agreement. A proposal should be submitted to be reviewed by the study steering committee. Individual data are not publicly available due to data protection regulations. The Clinical Investigator Plan is available online at https://portal.research.lu.se/sv/projects/breast-point-of-care-examination-trial

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.

See plan description