Automated Prediction of Kidney Failure in IgA Nephropathy with Deep Learning from Biopsy Images.

Journal: Clinical journal of the American Society of Nephrology : CJASN
PMID: 35882505

Abstract

BACKGROUND AND OBJECTIVES: Digital pathology and artificial intelligence offer new opportunities for automatic histologic scoring. We applied a deep learning approach to IgA nephropathy biopsy images to develop an automatic histologic prognostic score, assessed against ground truth (kidney failure) among patients with IgA nephropathy who were treated over 39 years. We assessed noninferiority in comparison with the histologic component of currently validated predictive tools. We correlated additional histologic features with our deep learning predictive score to identify potential additional predictive features.

Authors

  • Francesca Testa
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Francesco Fontana
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Federico Pollastri
    Department of Engineering "Enzo Ferrari," University of Modena and Reggio Emilia, Modena, Italy.
  • Johanna Chester
    Dermatology Department, University of Modena and Reggio Emilia, Modena, Italy.
  • Marco Leonelli
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Francesco Giaroni
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Fabio Gualtieri
    Department of Surgery, Medicine, Dental Medicine and Morphological Sciences, University of Modena and Reggio Emilia, Modena, Italy.
  • Federico Bolelli
    Department of Engineering "Enzo Ferrari," University of Modena and Reggio Emilia, Modena, Italy.
  • Elena Mancini
    U.O. Nefrologia, Dialisi, Ipertensione, Istituto di Ricovero e Cura a Carattere Scientifico (IRCCS) Azienda Ospedaliero-Universitaria di Bologna, Bologna, Italy.
  • Maurizio Nordio
    Nephrology and Dialysis Unit, Unità Locale Socio Sanitaria 15 (ULSS 15), Camposampiero-Cittadella, Padua, Italy.
  • Paolo Sacco
    Nephrology and Dialysis Unit, Azienda Sanitaria Locale 3 (ASL 3), Genoa, Italy.
  • Giulia Ligabue
    Department of Surgery, Medicine, Dental Medicine and Morphological Sciences, University of Modena and Reggio Emilia, Modena, Italy.
  • Silvia Giovanella
    Department of Surgery, Medicine, Dental Medicine and Morphological Sciences, University of Modena and Reggio Emilia, Modena, Italy.
  • Maria Ferri
    Department of Surgery, Medicine, Dental Medicine and Morphological Sciences, University of Modena and Reggio Emilia, Modena, Italy.
  • Gaetano Alfano
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Loreto Gesualdo
    Department of Diagnostic Pathology, Bioimages and Public Health, Policlinic University Hospital, Bari, Italy.
  • Simonetta Cimino
    Nephrology and Dialysis, Azienda Unità Sanitaria Locale (AUSL) Modena, Modena, Italy.
  • Gabriele Donati
    Division of Nephrology, Dialysis and Renal Transplantation, Azienda Ospedaliera Universitaria Policlinico di Modena, Modena, Italy.
  • Costantino Grana
    Department of Engineering "Enzo Ferrari," University of Modena and Reggio Emilia, Modena, Italy.
  • Riccardo Magistroni
    Department of Surgery, Medicine, Dental Medicine and Morphological Sciences, University of Modena and Reggio Emilia, Modena, Italy.

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