Abstract Introduction and objectives: Breast cancer remains the leading cause of cancer-related deaths among women globally, underscoring the importance of early detectionfor effective treatment. Traditional screening methods, including mammography, ultrasound, and MRI, are predominantly clinic-based and have notable limitations. Asthe healthcare landscape shifts towards remote care, innovative technologies are beingexplored to overcome these constraints. Advances in artificial intelligence are enhancing diagnostic precision, highlighting the need for accessible remote screeningsolutions. This study aims to identify and map breast pathologies using a wearable disposable breast patch which integrates infrared and bioimpedance sensors. Thus, addressing the need for more versatile and remote screening options. Methods This prospective, non-interventional, validation study evaluated 100 womenaged 25-75 undergoing breast cancer screening at the “Merav” Clinic, Tel Hashomer Hospital. Participants completed a medical questionnaire to assess their risk for breastcancer and were subsequently scanned with the FeminaiTM patch: a wearabledisposable breast patch incorporating thermometry and impedance sensors. Allparticipants underwent mammography or breast ultrasound, with several also receivingadditional breast MRI. A subset of 51 participants underwent biopsies. The data from thermal and impedance sensors, combined with questionnaire responses, wereanalysed using AI algorithms and compared against radiological interpretations(BIRADS scores) and biopsy results, enabling a comprehensive evaluation of thedevice’s efficacy in distinguishing between normal and abnormal breast conditions. Results A total of 100 women, with a mean age of 49, were examined using the Feminaibreast examination kit. Among the participants, 9 underwent ultrasound, 7 receivedMRI, and the remaining had mammograms. Of the cohort, 51 had a BI-RADS score of 3or higher, indicating abnormal findings, while 49 had a BI-RADS score of 1 or 2,indicating normal findings. Compared to imaging results, the device exhibited a sensitivity of 96%, specificity of 76%, and a negative predictive value (NPV) of 98%,accurately identifying all but one BIRADS 4 case, which biopsy results confirmed as normal tissue. 51 Biopsies were preformed for patients with BIRADS 4 and 5, 38 hadabnormal tissue findings (12 malignant, 26 benign). The device correctly identified all 38 cases with abnormal tissue findings. Notably, variations in infrared and impedance thresholds suggest potential for distinguishing between malignant and benign cases, ascompared to tissue biopsy results. Conclusions This validation study indicates that the Feminai breast examination kit achieved high sensitivity and NPV in this cohort. These promising results suggest the need for further validation to explore its potential as a valuable and cost-effective screening tool. The device’s performance suggests it could enhance early detection and improveaccessibility to breast cancer diagnostics, especially in remote and cost-sensitivesettings. Citation Format: K. Ilan, J. Mostafa, T. Menes, M. Sklair-Levy. Identification of breast abnormalities using remote self-test Feminai - Breast Examination Kit™: a validation study abstract. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS1-06-14.
Ilan et al. (Tue,) studied this question.