Ultra-fast deep-learned CNS tumour classification during surgery

Abstract Central nervous system tumours represent one of the most lethal cancer types, particularly among children 1 . Primary treatment includes neurosurgical resection of the tumour, in which a delicate balance must be struck between maximizing the extent of resection and minimizing risk of neurological damage and comorbidity 2,3 . However, surgeons have limited knowledge of the precise tumour type prior to surgery. Current standard practice relies on preoperative imaging and intraoperative histological analysis, but these are not always conclusive and occasionally wrong. Using rapid nanopore sequencing, a sparse methylation profile can be obtained during surgery 4 . Here we developed Sturgeon, a…

• NO
  Nederlandse Organisatie voor Wetenschappelijk Onderzoek

  Award: 184.034.019
• UM
  Universitair Medisch Centrum Utrecht
• SK
  Stichting Kinderen Kankervrij

  Award: 184.034.019
• OI
  Oncode Institute