The Neck-Persistency-Net: a three-dimensional, convolution, deep neural network aids in distinguishing vital from non-vital persistent cervical lymph nodes in advanced head and neck squamous cell carcinoma after primary concurrent radiochemotherapy

Eur Arch Otorhinolaryngol. 2024 Nov;281(11):5971-5982. doi: 10.1007/s00405-024-08842-3. Epub 2024 Jul 30.

Abstract

Purpose: To evaluate the diagnostic performance (DP) of the high-resolution contrast computed tomography (HR-contrast-CT) based Neck-Persistency-Net in distinguishing vital from non-vital persistent cervical lymph nodes (pcLNs) in patients with advanced head and neck squamous cell carcinoma (HNSCC) following primary concurrent chemoradiotherapy (CRT) with [18F]-fluorodeoxyglucose positron emission tomography and high-resolution contrast-enhanced computed tomography ([18F]FDG-PET-CT). Furthermore, the Neck-Persistency-Net's potential to justify omitting post-CRT neck dissection (ND) without risking treatment delays or preventing unnecessary surgery was explored.

Methods: All HNSCC patients undergoing primary CRT followed by post-CRT-ND for pcLNs recorded in the institutional HNSCC registry were analyzed. The Neck-Persistency-Net DP was explored for three scenarios: balanced performance (BalPerf), optimized sensitivity (OptSens), and optimized specificity (OptSpec). Histopathology of post-CRT-ND served as a reference.

Results: Among 68 included patients, 11 were female and 32 had vital pcLNs. The Neck-Persistency-Net demonstrated good DP with an area under the curve of 0.82. For BalPerf, both sensitivity and specificity were 78%; for OptSens (90%), specificity was 62%; for OptSpec (95%), sensitivity was 54%. Limiting post-CRT-ND to negative results would have delayed treatment in 27%, 40%, and 7% for BalPerf, OptSens and OptSpec, respectively, versus 23% for [18F]FDG-PET-CT. Conversely, restricting post-CRT-ND to positive results would have prevented unnecessary post-CRT-ND in 78%, 60%, and 95% for BalPerf, OptSens and OptSpec, respectively, versus 55% for [18F]FDG-PET-CT.

Conclusion: The DP of the Neck-Persistency-Net was comparable to [18F]-FDG-PET-CT. Depending on the chosen decision boundary, the potential to justify the omission of post-CRT-ND without risking treatment delays in false negative findings or reliably prevent unnecessary surgery in false positive findings outperforms the [18F]-FDG-PET-CT.

Keywords: Artificial intelligence; HNSCC; Machine learning; PET/CT; Radiomics; Salvage surgery.

MeSH terms

  • Adult
  • Aged
  • Chemoradiotherapy* / methods
  • Deep Learning
  • Female
  • Fluorodeoxyglucose F18
  • Head and Neck Neoplasms* / diagnostic imaging
  • Head and Neck Neoplasms* / pathology
  • Head and Neck Neoplasms* / therapy
  • Humans
  • Imaging, Three-Dimensional
  • Lymph Nodes* / diagnostic imaging
  • Lymph Nodes* / pathology
  • Lymphatic Metastasis* / diagnostic imaging
  • Male
  • Middle Aged
  • Neck / diagnostic imaging
  • Neck Dissection
  • Neural Networks, Computer
  • Positron Emission Tomography Computed Tomography* / methods
  • Radiopharmaceuticals
  • Retrospective Studies
  • Sensitivity and Specificity
  • Squamous Cell Carcinoma of Head and Neck* / diagnostic imaging
  • Squamous Cell Carcinoma of Head and Neck* / pathology
  • Squamous Cell Carcinoma of Head and Neck* / therapy
  • Tomography, X-Ray Computed / methods

Substances

  • Fluorodeoxyglucose F18
  • Radiopharmaceuticals