Artificial Intelligence-based Segmentation of Residual Pancreatic Cancer in Resection Specimens Following Neoadjuvant Treatment (ISGPP-2): International Improvement and Validation Study.

Journal: The American journal of surgical pathology
PMID: 38985503

Abstract

Neoadjuvant therapy (NAT) has become routine in patients with borderline resectable pancreatic cancer. Pathologists examine pancreatic cancer resection specimens to evaluate the effect of NAT. However, an automated scoring system to objectively quantify residual pancreatic cancer (RPC) is currently lacking. Herein, we developed and validated the first automated segmentation model using artificial intelligence techniques to objectively quantify RPC. Digitized histopathological tissue slides were included from resected pancreatic cancer specimens from 14 centers in 7 countries in Europe, North America, Australia, and Asia. Four different scanner types were used: Philips (56%), Hamamatsu (27%), 3DHistech (10%), and Leica (7%). Regions of interest were annotated and classified as cancer, non-neoplastic pancreatic ducts, and others. A U-Net model was trained to detect RPC. Validation consisted of by-scanner internal-external cross-validation. Overall, 528 unique hematoxylin and eosin (H & E) slides from 528 patients were included. In the individual Philips, Hamamatsu, 3DHistech, and Leica scanner cross-validations, mean F1 scores of 0.81 (95% CI, 0.77-0.84), 0.80 (0.78-0.83), 0.76 (0.65-0.78), and 0.71 (0.65-0.78) were achieved, respectively. In the meta-analysis of the cross-validations, the mean F1 score was 0.78 (0.71-0.84). A final model was trained on the entire data set. This ISGPP model is the first segmentation model using artificial intelligence techniques to objectively quantify RPC following NAT. The internally-externally cross-validated model in this study demonstrated robust performance in detecting RPC in specimens. The ISGPP model, now made publically available, enables automated RPC segmentation and forms the basis for objective NAT response evaluation in pancreatic cancer.

Authors

  • Boris V Janssen
    Department of Surgery, Amsterdam UMC, University of Amsterdam, Cancer Center Amsterdam, Amsterdam, The Netherlands.
  • Bart Oteman
    Departments of Surgery.
  • Mahsoem Ali
    Department of Surgery, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
  • Pieter A Valkema
    Pathology, Amsterdam UMC, location University of Amsterdam.
  • Volkan Adsay
    Department of Pathology, Koc University and KUTTAM Research Center, Istanbul, Turkey.
  • Olca Basturk
    Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY.
  • Deyali Chatterjee
    MD Anderson Cancer Center, Houston, TX, USA.
  • Angela Chou
    Royal North Shore Hospital and Northern Clinical School, Sydney Medical School, University of Sydney, Sydney, Australia.
  • Stijn Crobach
    Departments of Pathology.
  • Michael Doukas
    Department of Pathology, Erasmus Medical Center.
  • Paul Drillenburg
    Department of Pathology, OLVG, Amsterdam.
  • Irene Esposito
    Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, Duesseldorf, Germany.
  • Anthony J Gill
    Royal North Shore Hospital, Cancer Diagnosis and Pathology Group, Kolling Institute of Medical Research, Sydney, Australia.
  • Seung-Mo Hong
    Department of Pathology, Asan Medical Center, Seoul, Republic of Korea.
  • Casper Jansen
    Laboratorium Pathologie Oost-Nederland, Hengelo.
  • Mike Kliffen
    Department of Pathology, Maasstad ziekenhuis, Rotterdam.
  • Anubhav Mittal
    Department of Surgery of Medical Research, Royal North Shore Hospital, St Leonards, NSW, Australia.
  • Jas Samra
    University of Sydney, Sydney, NSW, Australia.
  • Marie-Louise F van Velthuysen
    Department of Pathology, Erasmus Medical Center.
  • Aslihan Yavas
    Institute of Pathology, Heinrich-Heine-University and University Hospital of Duesseldorf, Duesseldorf, Germany.
  • Geert Kazemier
    Department of Surgery, VU University Medical Center, Cancer Center Amsterdam, De Boelelaan 1117, 1081 HV Amsterdam, the Netherlands.
  • Joanne Verheij
    Pathology, Amsterdam UMC, location University of Amsterdam.
  • Ewout Steyerberg
    Biomedical Data Sciences, Leiden University Medical Center, Leiden.
  • Marc G Besselink
    Department of Surgery, Cancer Center Amsterdam, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands. m.g.besselink@amsterdamumc.nl.
  • Huamin Wang
    Department of Mathematics, Luoyang Normal University, Luoyang, Henan 471934, China.
  • Caroline Verbeke
    Department of Pathology, Institute of Clinical Medicine, University of Oslo.
  • Arantza Fariña
    Pathology, Amsterdam UMC, location University of Amsterdam.
  • Onno J de Boer
    Department of Pathology, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.

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