Optical coherence tomography and convolutional neural networks can differentiate colorectal liver metastases from liver parenchyma ex vivo.

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Abstract

Abstract Purpose:Optical coherence tomography (OCT) is an imaging technology based on low-coherence interferometry, which provides noninvasive, high-resolution cross-sectional images of biological tissues. A potential clinical application is the intraoperative examination of resection margins, as a real-time adjunct to histological examination. In this ex vivo study, we investigated the ability of OCT to differentiate colorectal liver metastases (CRLM) from healthy liver parenchyma, when combined with convolutional neural networks (CNN).Methods:Between June and August 2020, consecutive adult patients undergoing elective liver resections for CRLM were included in this study. Fresh resection specimens were scanned ex vivo, before fixation in formalin, using a table-top OCT device at 1310nm wavelength. Scanned areas were marked and histologically examined. A pre-trained CNN (Xception) was used to match OCT scans to their corresponding histological diagnoses. To validate the results, a stratified k-fold cross-validation (CV) was carried out.Results:A total of 26 scans (containing approx. 26,500 images in total) were obtained from 15 patients. Of these, 13 were of normal liver parenchyma and 13 of CRLM. The CNN distinguished CRLM from healthy liver parenchyma with an F1-score of 0.93 (0.03), and a sensitivity and specificity of 0.94 (0.04) and 0.93 (0.04), respectively.Conclusion: Optical coherence tomography combined with CNN can distinguish between healthy liver and CRLM with great accuracy ex vivo. Further studies are needed to improve upon these results and develop in vivo diagnostic technologies, such as intraoperative scanning of resection margins.

Authors 15

1. Iakovos Amygdalos Aachen

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   University Hospital RWTH Aachen

2. Enno Hachgenei Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT

3. Luisa Burkl Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT

4. Paul Goßmann Aachen

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   University Hospital RWTH Aachen

5. Laura I. Wolff Aachen

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   University Hospital RWTH Aachen

6. Mariia Druzenko Aachen

   Universitätsklinikum Aachen · RWTH Aachen University

   Affiliation as printed

   University Hospital RWTH Aachen

7. Maik Frye Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT

8. Robert Heinrich Schmitt Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT

9. Niels König Aachen Fraunhofer Institute for Production Technology IPT

   Fraunhofer Institute for Production Technology IPT

   Affiliation as printed

   Fraunhofer Institute for Production Technology IPT

10. Alexandros Chrysos Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen

11. K. Jöchle Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen

12. Tom Florian Ulmer Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen

13. Ruth Knüchel‐Clarke Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen

14. Ulf P. Neumann Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen

15. Sven Arke Lang Aachen

    Universitätsklinikum Aachen · RWTH Aachen University

    Affiliation as printed

    University Hospital RWTH Aachen