A 3-dimensional histology computer model of malignant melanoma and its implications for digital pathology

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Alexander Kurz - , Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)
  • Dieter Krahl - , MVZ DermatoHistoPathologie Heidelberg GmbH (Autor:in)
  • Heinz Kutzner - , Medizinisches Versorgungszentrum (MVZ) Dermapathologie Friedrichshafen/Bodensee PartG (Autor:in)
  • Raymond Barnhill - , Institut Curie (Autor:in)
  • Antonio Perasole - , Cerba Healthcare S.r.l. Rete Diagnostica Italiana (Autor:in)
  • Maria Teresa Fernandez Figueras - , UIC Barcelona International University of Catalonia (Autor:in)
  • Gerardo Ferrara - , IRCCS Istituto nazionale tumori Fondazione Giovanni Pascale - Napoli (Autor:in)
  • Stephan A. Braun - , Westfälische Wilhelms-Universität Münster, Heinrich Heine Universität Düsseldorf (Autor:in)
  • Hans Starz - , DERMPATH München (Autor:in)
  • Mar Llamas-Velasco - , Hospital Universitario de la Princesa (Autor:in)
  • Jochen Sven Utikal - , Universität Heidelberg, Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)
  • Stefan Fröhling - , Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)
  • Christof von Kalle - , Charité – Universitätsmedizin Berlin (Autor:in)
  • Jakob Nikolas Kather - , Else Kröner Fresenius Zentrum für Digitale Gesundheit (Autor:in)
  • Lucas Schneider - , Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)
  • Titus J. Brinker - , Deutsches Krebsforschungszentrum (DKFZ) (Autor:in)

Abstract

Background: Historically, cancer diagnoses have been made by pathologists using two-dimensional histological slides. However, with the advent of digital pathology and artificial intelligence, slides are being digitised, providing new opportunities to integrate their information. Since nature is 3-dimensional (3D), it seems intuitive to digitally reassemble the 3D structure for diagnosis. Objective: To develop the first human-3D-melanoma-histology-model with full data and code availability. Further, to evaluate the 3D-simulation together with experienced pathologists in the field and discuss the implications of digital 3D-models for the future of digital pathology. Methods: A malignant melanoma of the skin was digitised via 3 µm cuts by a slide scanner; an open-source software was then leveraged to construct the 3D model. A total of nine pathologists from four different countries with at least 10 years of experience in the histologic diagnosis of melanoma tested the model and discussed their experiences as well as implications for future pathology. Results: We successfully constructed and tested the first 3D-model of human melanoma. Based on testing, 88.9% of pathologists believe that the technology is likely to enter routine pathology within the next 10 years; advantages include a better reflectance of anatomy, 3D assessment of symmetry and the opportunity to simultaneously evaluate different tissue levels at the same time; limitations include the high consumption of tissue and a yet inferior resolution due to computational limitations. Conclusions: 3D-histology-models are promising for digital pathology of cancer and melanoma specifically, however, there are yet limitations which need to be carefully addressed.

Details

OriginalspracheEnglisch
Aufsatznummer113294
FachzeitschriftEuropean journal of cancer
Jahrgang193
PublikationsstatusVeröffentlicht - Nov. 2023
Peer-Review-StatusJa

Externe IDs

PubMed 37690178

Schlagworte

Ziele für nachhaltige Entwicklung

ASJC Scopus Sachgebiete

Schlagwörter

  • Artificial intelligence, Deep learning, Dermatology, Dermatopathology, Digital pathology, Melanoma