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Dataset Information

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.


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 HN

SUBMITTER: Santer M 

PROVIDER: S-EPMC11512899 | biostudies-literature | 2024 Nov

REPOSITORIES: biostudies-literature