FiBar: A tool for analyzing fiber diameters in complex drug delivery systems from scanning electron microscopy images.

Journal: European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Published Date:

Abstract

Electrospinning increases opportunities to facilitate the production of drug delivery systems (DDSs), such as complex biomaterials. However, the manual measurement of fiber diameters remains a critical bottleneck, hindering efficiency and scalability. While existing tools like SIMPoly, ImageJ/FIJI plugins (e.g., DiameterJ, GIFT) aim to address this challenge, they fall short in accessibility and flexibility - none provide a seamless, browser-based experience or robust handling of measurement errors. To address these gaps, we introduce FiBar, an online platform for automated analysis of fibrous DDSs. FiBar is designed with the focus on user-friendliness, reducing setup time and complexity compared to existing alternatives. Additionally, FiBar incorporates advanced features to correct erroneous measurements. This combination makes FiBar a transformative tool for researchers seeking efficiency, accuracy, and versatility in DDSs characterization. We evaluated FiBar's performance against ImageJ's DiameterJ plugin and GIFT macro, SIMPoly, and manual measurements for the analysis of both synthetic datasets and scanning electron microscopy (SEM) images of electrospun drug-loaded fibers. Our results demonstrated that FiBar consistently delivered more reliable measurements, particularly in cases involving faulty segmentations, where other tools faltered. Additionally, FiBar significantly improved efficiency, achieving an average 2.2x reduction in processing time compared to measuring manually. FiBar enables users to easily and quickly measure, edit, and collect diameters of nano- and microfibers, which is important for the characterization and understanding of DDSs and other biomaterials. This is achieved by employing both classical and artificial intelligence (AI) based solutions to enhance its generalizability. The tool is accessible online at https://fibar.elixir.ut.ee/.

Authors

  • Marilin Moor
    Institute of Computer Science, University of Tartu, Narva mnt 18, Tartu, 51009, Tartumaa, Estonia; Institute of Pharmacy, University of Tartu, Nooruse 1, Tartu, 50411, Tartumaa, Estonia.
  • Laura Männaste
    Institute of Pharmacy, University of Tartu, Nooruse 1, Tartu, 50411, Tartumaa, Estonia.
  • Marta Putrinš
    Institute of Pharmacy, University of Tartu, Nooruse 1, Tartu, 50411, Tartumaa, Estonia.
  • Dmytro Fishman
    Department of Computer Science, University of Tartu, Tartu, Estonia.
  • Karin Kogermann
    Institute of Pharmacy, University of Tartu, Nooruse 1, Tartu, 50411, Tartumaa, Estonia. Electronic address: karin.kogermann@ut.ee.