A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models.

Journal: Scientific data
Published Date:

Abstract

Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, when Sophie Spitz first described them, the diagnostic uncertainty remains until now, especially in the intermediate category known as Spitz tumor of unknown malignant potential (STUMP) or atypical Spitz tumor. Studies developing deep learning (DL) models to diagnose melanocytic tumors using whole slide imaging (WSI) are scarce, and few used ST for analysis, excluding STUMP. To address this gap, we introduce SOPHIE: the first ST dataset with WSIs, including labels as benign, malignant, and atypical tumors, along with the clinical information of each patient. Additionally, we explain two DL models implemented as validation examples using this database.

Authors

  • Andrés Mosquera-Zamudio
    Pathology Department Hospital Clínico Universitario de Valencia, Universidad de Valencia, Valencia, Spain. amosquera@incliva.es.
  • Laëtitia Launet
    Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano, HUMAN-tech Universitat Politècnica de València, Valencia, Spain.
  • Rocío Del Amor
    Instituto Universitario de Investigación en Tecnología Centrada en el Ser Humano (HUMAN-Tech), Universitat Politècnica de València, 46022, Spain.
  • Anaïs Moscardó
    Pathology Department Hospital Clínico Universitario de Valencia, Universidad de Valencia, Valencia, Spain.
  • Adrian Colomer
  • Valery Naranjo
    Instituto de Investigación e Innovación en Bioingeniería, I3B, Universitat Politècnica de València, Camino de Vera s/n, 46022, Valencia, Spain.
  • Carlos Monteagudo
    Pathology Department Hospital Clínico Universitario de Valencia, Universidad de Valencia, Valencia, Spain. carlos.monteagudo@uv.es.