Pathology-based validation of FDG PET segmentation tools for volume assessment of lymph node metastases from head and neck cancer

D. Schinagl, P. Span, F. van den Hoogen, M. Merkx, P. Slootweg, W. Oyen and J. Kaanders

Department of Radiation Oncology, Radboud University Nijmegen Medical Centre, Nijmegen, The Netherlands,
Dec, 2013



FDG PET is increasingly incorporated into radiation treatment planning of head and neck cancer. However, there are only limited data on the accuracy of radiotherapy target volume delineation by FDG PET. The purpose of this study was to validate FDG PET segmentation tools for volume assessment of lymph node metastases from head and neck cancer against the pathological method as the standard.Twelve patients with head and neck cancer and 28 metastatic lymph nodes eligible for therapeutic neck dissection underwent preoperative FDG PET/CT. The metastatic lymph nodes were delineated on CT (NodeCT) and ten PET segmentation tools were used to assess FDG PET-based nodal volumes: interpreting FDG PET visually (PETVIS), applying an isocontour at a standardized uptake value (SUV) of 2.5 (PETSUV), two segmentation tools with a fixed threshold of 40\% and 50\%, and two adaptive threshold based methods. The latter four tools were applied with the primary tumour as reference and also with the lymph node itself as reference. Nodal volumes were compared with the true volume as determined by pathological examination.Both NodeCT and PETVIS showed good correlations with the pathological volume. PET segmentation tools using the metastatic node as reference all performed well but not better than PETVIS. The tools using the primary tumour as reference correlated poorly with pathology. PETSUV was unsatisfactory in 35\% of the patients due to merging of the contours of adjacent nodes.FDG PET accurately estimates metastatic lymph node volume, but beyond the detection of lymph node metastases (staging), it has no added value over CT alone for the delineation of routine radiotherapy target volumes. If FDG PET is used in radiotherapy planning, treatment adaptation or response assessment, we recommend an automated segmentation method for purposes of reproducibility and interinstitutional comparison.