Automated breast lesion detection and characterization with the wavelia microwave breast imaging system: Methodological proof-of-concept on first-in-human patient data

  • Angie Fasoula
  • , Luc Duchesne
  • , Julio Daniel Gil Cano
  • , Brian M. Moloney
  • , Sami M.Abd Elwahab
  • , Michael J. Kerin

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

22 Citations (Scopus)

Abstract

Microwave Breast Imaging (MBI) is an emerging non-ionizing imaging modality, with the potential to support breast diagnosis and management. Wavelia is an MBI system prototype, of 1st generation, which has recently completed a First-In-Human (FiH) clinical investigation on a 25-symptomatic patient cohort, to explore the capacity of the technology to detect and characterize malignant (invasive carcinoma) and benign (fibroadenoma, cyst) breast disease. Two recent publications presented promising results demonstrated by the device in this FiH study in detecting and localizing, as well as delineating size and malignancy risk, of malignant and benign palpable breast lesions. In this paper, the methodology that has been employed in the Wavelia semi-automated Quantitative Imaging Function (QIF), to support breast lesion detection and characterization in the FiH clinical investigation of the device, is presented and the critical design parameters are highlighted.

Original languageEnglish
Article number9998
JournalApplied Sciences (Switzerland)
Volume11
Issue number21
DOIs
Publication statusPublished - 1 Nov 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Breast cancer detection
  • Computer-aided diagnosis (CAD)
  • First-in-human (FiH) study
  • Microwave breast imaging

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