Automatic segmentation for magnetic resonance imaging guided individual elective lymph node irradiation in head and neck cancer patients.

ABSTRACT:

Background and purpose

In head and neck squamous cell carcinoma (HNSCC) patients, the radiation dose to nearby organs at risk can be reduced by restricting elective neck irradiation from lymph node levels to individual lymph nodes. However, manual delineation of every individual lymph node is time-consuming and error prone. Therefore, automatic magnetic resonance imaging (MRI) segmentation of individual lymph nodes was developed and tested using a convolutional neural network (CNN).

Materials and methods

In 50 HNSCC patients (UMC-Utrecht), individual lymph nodes located in lymph node levels Ib-II-III-IV-V were manually segmented on MRI by consensus of two experts, obtaining ground truth segmentations. A 3D CNN (nnU-Net) was trained on 40 patients and tested on 10. Evaluation

SUBMITTER: Reinders FCJ 

PROVIDER: S-EPMC11536060 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature