Table 1: Target volume delineation in NSCLC.

AuthorYearPatientsMethods of delineationConclusion

Nestle et al. [14]2005 25Visual 40% of SUV max ≧ 2.5 SUV Phantom algorithmVisual, SUV of 2.5, and phantom algorithm were associated with GTV delineated by CT.
Biehl et al. [17]2006 2020%–40% of SUV maxNo single threshold delineating PET provides accurate volume definition, compared with that provided by CT.
Hong et al. [18]2007 19SUV ≧ 2.5 40% of SUV maxThis study recommended using SUV ≧ 2.5 for radiotherapy planning in non-small-cell lung cancer.
van Baardwijk [19]2007 23Source-to-background ratioSource-to-background ratio-based autodelineation was strongly correlated microscopic diameter of primary tumor (correlation coefficient = 0.90).
Visser et al. [20]2008 1350% of SUV max 50% of glucose metabolic rateTumor volumes from glucose metabolic rate were significantly smaller than SUV-based volumes.
Rodríguez et al. [21]2010 4040% of SUV maxLymph nodes could be delineated in accordance with tumor uptake when lymph nodes/tumor SUV max ratio was ≤25%.
Devic et al. [22]2010 31Visual 15%, 40% of SUV maxNot dependent on the thresholding method used.
Vinod et al. [23]2010 5VisualEffects of FDG-PET on normal tissue complication and tumor control cannot be predicted.
Wanet et al. [15]2011 10Gradient-based method Source-to-background ratio 40%, 50% of SUV maxGradient-based method best estimated true tumor volume.
Warner-Wasik et al. [16]2011PhantomGradient-based methodGradient-based method was most accurate and consistent technique for target volume contouring.
Visual ≧2.5 SUV
Source-to-background ratio
Fleckenstein et al. [24]2011 32Source-to-background ratioFDG-PET confined target volume definition was associated with low risk of isolated nodal recurrences.
Lin et al. [25]2011 37VisualThere was correlation between GTV based on FDG-PET and excised surgical specimen.