Deep learning identifies inflamed fat as a risk factor for lymph node metastasis in early colorectal cancer
The Journal of Pathology, vol. 256, pp. 269–281
Abstract
The spread of early-stage (T1 and T2) adenocarcinomas to locoregional lymph nodes is a key event in disease progression of colorectal cancer (CRC). The cellular mechanisms behind this event are not completely understood and existing predictive biomarkers are imperfect. Here, we used an end-to-end deep learning algorithm to identify risk factors for lymph node metastasis (LNM) status in digitized histopathology slides of the primary CRC and its surrounding tissue. In two large population-based cohorts, we show that this system can predict the presence of more than one LNM in pT2 CRC patients with an area under the receiver operating curve (AUROC) of 0.733 (0.67-0.758) and patients with any LNM with an AUROC of 0.711 (0.597-0.797). Similarly, in pT1 CRC patients, the presence of more than one LNM or any LNM was predictable with an AUROC of 0.733 (0.644-0.778) and 0.567 (0.542-0.597), respectively. Based on these findings, we used the deep learning system to guide human pathology experts towards highly predictive regions for LNM in the whole slide images. This hybrid human observer and deep learning approach identified inflamed adipose tissue as the highest predictive feature for LNM presence. Our study is a first proof of concept that artificial intelligence (AI) systems may be able to discover potentially new biological mechanisms in cancer progression. Our deep learning algorithm is publicly available and can be used for biomarker discovery in any disease setting. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
Authors 17
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Scarlet Fiona Brockmoeller corresponding
Affiliation as printed
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Medicine III University Hospital RWTH Aachen Aachen Germany
Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Medicine III University Hospital RWTH Aachen Aachen Germany
Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany
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University of Copenhagen · Zealand University Hospital
Affiliation as printed
Department of Pathology Zealand University Hospital, University of Copenhagen Roskilde Denmark
Department of Pathology, Zealand University Hospital, University of Copenhagen, Roskilde, Denmark
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Affiliation as printed
Department of Surgery Nordsjællands Hospital Hillerod Denmark
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Herlev Hospital · Copenhagen University Hospital
Affiliation as printed
Department of Pathology Herlev University Hospital Copenhagen Denmark
Department of Pathology, Herlev University Hospital, Copenhagen, Denmark
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Herlev Hospital · Copenhagen University Hospital
Affiliation as printed
Department of Surgery Herlev University Hospital Copenhagen Denmark
Department of Surgery, Herlev University Hospital, Copenhagen, Denmark
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University of Leeds · Maastricht University Medical Centre · Maastricht University
Affiliation as printed
Department of Pathology, GROW School for Oncology and Developmental Biology Maastricht University Medical Center+ Maastricht The Netherlands
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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Affiliation as printed
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Medicine III University Hospital RWTH Aachen Aachen Germany
Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany
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Affiliation as printed
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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Affiliation as printed
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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Maastricht University Medical Centre · Maastricht University · Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Pathology, GROW School for Oncology and Developmental Biology Maastricht University Medical Center+ Maastricht The Netherlands
Department of Surgery and Transplantation University Hospital RWTH Aachen Aachen Germany
Institute of Pathology University Hospital RWTH Aachen Aachen Germany
Department of Pathology, GROW School for Oncology and Developmental Biology, Maastricht University Medical Center+, Maastricht, The Netherlands
Department of Surgery and Transplantation, University Hospital RWTH Aachen, Aachen, Germany
Institute of Pathology, University Hospital RWTH Aachen, Aachen, Germany
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German Cancer Research Center · National Center for Tumor Diseases
Affiliation as printed
Digital Biomarkers for Oncology Group, National Center for Tumour Diseases (NCT) German Cancer Research Center (DKFZ) Heidelberg Germany
Digital Biomarkers for Oncology Group, National Center for Tumour Diseases (NCT), German Cancer Research Center (DKFZ), Heidelberg, Germany
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University of Copenhagen · Hvidovre Hospital · Copenhagen University Hospital · Zealand University Hospital · Zealand University Hospital Køge
Affiliation as printed
Department of Surgery Zealand University Hospital, University of Copenhagen Køge Denmark
Gastrounit – Surgical Division, Center for Surgical Research Copenhagen University Hospital Hvidovre Copenhagen Denmark
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Affiliation as printed
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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University of Leeds · Heidelberg University · University Hospital Heidelberg · National Center for Tumor Diseases · Universitätsklinikum Aachen · RWTH Aachen University
Affiliation as printed
Department of Medicine III University Hospital RWTH Aachen Aachen Germany
Medical Oncology, National Center of Tumour Diseases (NCT) University Hospital Heidelberg Heidelberg Germany
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
Department of Medicine III, University Hospital RWTH Aachen, Aachen, Germany
Medical Oncology, National Center of Tumour Diseases (NCT), University Hospital Heidelberg, Heidelberg, Germany
Pathology & Data Analytics, Leeds Institute of Medical Research at St James's University of Leeds Leeds UK
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