Performance of a point-of-care ultrasound platform for artificial intelligence-enabled assessment of pulmonary B-lines.

Journal: Cardiovascular ultrasound
PMID: 40025516

Abstract

BACKGROUND: The incorporation of artificial intelligence (AI) into point-of-care ultrasound (POCUS) platforms has rapidly increased. The number of B-lines present on lung ultrasound (LUS) serve as a useful tool for the assessment of pulmonary congestion. Interpretation, however, requires experience and therefore AI automation has been pursued. This study aimed to test the agreement between the AI software embedded in a major vendor POCUS system and visual expert assessment.

Authors

  • Ashkan Labaf
    Department of Clinical Sciences Lund, Cardiology, Section for Heart Failure and Valvular Disease, Lund University, Skåne University Hospital, Klinikgatan 15, Lund, 221 85, Sweden. ashkan.labaf@med.lu.se.
  • Linda Åhman-Persson
    Department of Internal and Emergency Medicine, Skåne University Hospital, Malmö, Sweden.
  • Leo Silvén Husu
    Department of Internal and Emergency Medicine, Skåne University Hospital, Malmö, Sweden.
  • J Gustav Smith
    Department of Clinical Sciences Lund, Cardiology, Section for Heart Failure and Valvular Disease, Lund University, Skåne University Hospital, Klinikgatan 15, Lund, 221 85, Sweden.
  • Annika Ingvarsson
    Department of Clinical Sciences Lund, Cardiology, Section for Heart Failure and Valvular Disease, Lund University, Skåne University Hospital, Klinikgatan 15, Lund, 221 85, Sweden.
  • Anna Werther Evaldsson
    Department of Clinical Sciences Lund, Cardiology, Section for Heart Failure and Valvular Disease, Lund University, Skåne University Hospital, Klinikgatan 15, Lund, 221 85, Sweden.

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