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We present an interpretable approach for automated lymph node station (LNS) classification and N-staging on PET/CT and CT only by extending two established segmentation algorithms with probabilistic atlas-based LNS mapping. Our results show that a probabilistic approach for LNS mapping improves the detection accuracy by over 40 percentage points. The proposed method yields an accuracy of 0.74 for LNS classification and 0.68 for N-staging on PET/CT, representing a significant improvement toward human-level performance compared with the baseline approach. A performance drop for CT only evaluation indicates the PET scan adds valuable information to lymph node assessment, which is in alignment with according literature.

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Interpretable Mediastinal Lymph Node Station Classification and N-staging on CT and PET/CT Images

  • 会议论文

  • 发表日期：

    2026年

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  • Sofija Engelson,
  • Jan Ehrhardt,
  • Yannic Elser,
  • Malte M. Sieren,
  • Julia Andresen,
  • Stefanie Schierholz,
  • Tobias Keck,
  • Daniel Drömann,
  • Jörg Barkhausen,
  • Heinz Handels

摘要

We present an interpretable approach for automated lymph node station (LNS) classification and N-staging on PET/CT and CT only by extending two established segmentation algorithms with probabilistic atlas-based LNS mapping. Our results show that a probabilistic approach for LNS mapping improves the detection accuracy by over 40 percentage points. The proposed method yields an accuracy of 0.74 for LNS classification and 0.68 for N-staging on PET/CT, representing a significant improvement toward human-level performance compared with the baseline approach. A performance drop for CT only evaluation indicates the PET scan adds valuable information to lymph node assessment, which is in alignment with according literature.