Prediction of Anastomotic Leakage in Esophageal Cancer Surgery: A Multimodal Machine Learning Model Integrating Imaging and Clinical Data.

Journal: Academic radiology
PMID: 38955594

Abstract

RATIONALE AND OBJECTIVES: Surgery in combination with chemo/radiotherapy is the standard treatment for locally advanced esophageal cancer. Even after the introduction of minimally invasive techniques, esophagectomy carries significant morbidity and mortality. One of the most common and feared complications of esophagectomy is anastomotic leakage (AL). Our work aimed to develop a multimodal machine-learning model combining CT-derived and clinical data for predicting AL following esophagectomy for esophageal cancer.

Authors

  • Michail E Klontzas
    Department of Medical Imaging, Heraklion University Hospital, Crete, 70110, Greece; Advanced Hybrid Imaging Systems, Institute of Computer Science, Foundation for Research and Technology (FORTH), N. Plastira 100, Vassilika Vouton 70013, Heraklion, Crete, Greece. Electronic address: miklontzas@ics.forth.gr.
  • Motonari Ri
    Department of Gastrointestinal Surgery, Graduate School of Medicine, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan.
  • Emmanouil Koltsakis
    Department for Clinical Science, Intervention and Technology (CLINTEC), Division of Radiology, Karolinska Institutet, Stockholm, Sweden; Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm, Sweden.
  • Erik Stenqvist
    Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm, Sweden.
  • Georgios Kalarakis
    Department for Clinical Science, Intervention and Technology (CLINTEC), Division of Radiology, Karolinska Institutet, Stockholm, Sweden; Department of Radiology, School of Medicine, University of Crete, Voutes Campus, Heraklion, Greece; Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm, Sweden.
  • Erik Boström
    Department of Diagnostic Radiology, Karolinska University Hospital, Stockholm, Sweden.
  • Aristotelis Kechagias
    Department of Digestive Surgery, Kanta-Häme Central Hospital, Hämeenlinna 13530, Finland.
  • Dimitrios Schizas
    1st Department of Surgery, Laikon General Hospital, Medical School, National and Kapodistrian University of Athens, Athens, Greece.
  • Ioannis Rouvelas
    Department of Clinical Science, Intervention and Technology (CLINTEC), Division of Surgery and Oncology, Karolinska Institutet, Solna, Sweden; Department of Upper Abdominal Diseases, Karolinska University Hospital, Huddinge, Stockholm, Sweden.
  • Antonios Tzortzakakis
    Department for Clinical Science, Intervention and Technology (CLINTEC), Division of Radiology, Karolinska Institutet, Stockholm, Sweden; Medical Radiation Physics and Nuclear Medicine, Section for Nuclear Medicine, Karolinska University Hospital, Huddinge, Stockholm, Sweden. Electronic address: antonios.tzortzakakis@ki.se.

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