Standardized visual reading of F18-FDG-PET in patients with non-small cell lung cancer scheduled for preoperative thoracic lymph node staging

  • Julian M M Rogasch
  • Ivayla Apostolova
  • Ingo G Steffen
  • Ferdinand L G A Steinkrüger
  • Philipp Genseke
  • Sandra Riedel
  • Heinz Wertzel
  • H Jost Achenbach
  • Thomas Kalinski
  • Meinald Schultz
  • Jens Schreiber
  • Holger Amthauer
  • Christian Furth

Abstract

OBJECTIVES: Routine visual assessment of positron emission tomography (PET) for thoracic lymph node (LN) staging in patients with non-small cell lung cancer (NSCLC) is limited by a lack of reliable assessment criteria. This study evaluates the accuracy and inter-rater agreement of a standardized approach with unified windowing and a PET-based visual score.

MATERIALS AND METHODS: This retrospective analysis included pretherapeutic FDG-PET data of 86 patients with NSCLC. After standardized windowing (threshold: 2×liver SUVmean) the LN uptake was assessed visually by three independent readers with varying levels of experience using a 4-step score (1, LN uptake≤mediastinal blood pool structures (MBPS); 2, MBPS<LN<liver; 3, liver≤LN<'black'; 4, LN appears 'black'). ROC analyses and respective areas under the curve (AUC) based on histology/cytology as standard of reference. Agreement was analyzed with Cohen's kappa (κ, pairwise) and Fleiss' κ (overall). Subgroup analyses separated between hilar vs. mediastinal LNs, adenocarcinoma vs. squamous cell carcinoma and grading G1/2 vs. G3/4.

RESULTS: Fifty-four of the 278LNs (19.4%) were malignant (optimal cut-off to differentiate benign vs. malignant, score >3). The inexperienced (n=1), advanced (n=1), and expert readers (n=1) achieved similar accuracies of 93.5%, 91.4% and 92.1%, respectively (P>0.05 each). Cohen's κ ranged from 0.92 to 0.96 and Fleiss' κ was 0.93. ROC-analyses showed no significant differences between attendant readers within any subgroup (AUC, 0.92-0.96).

CONCLUSION: Applying unified windowing, the introduced PET-score achieved highly accurate and robust LN assessment. This approach may shorten learning curves of inexperienced readers, facilitate multicenter trials, and improve comparability of future studies.

Bibliographical data

Original languageEnglish
ISSN0720-048X
DOIs
Publication statusPublished - 08.2016
PubMed 27423672