Use of FDG-PET in Radiation Treatment Planning for Thoracic Cancers

Table 1

Target volume delineation in NSCLC.

Author	Year	Patients	Methods of delineation	Conclusion
Nestle et al. [14]	2005	25	Visual 40% of SUV max ≧ 2.5 SUV Phantom algorithm	Visual, SUV of 2.5, and phantom algorithm were associated with GTV delineated by CT.
Biehl et al. [17]	2006	20	20%–40% of SUV max	No single threshold delineating PET provides accurate volume definition, compared with that provided by CT.
Hong et al. [18]	2007	19	SUV ≧ 2.5 40% of SUV max	This study recommended using SUV ≧ 2.5 for radiotherapy planning in non-small-cell lung cancer.
van Baardwijk [19]	2007	23	Source-to-background ratio	Source-to-background ratio-based autodelineation was strongly correlated microscopic diameter of primary tumor (correlation coefficient = 0.90).
Visser et al. [20]	2008	13	50% of SUV max 50% of glucose metabolic rate	Tumor volumes from glucose metabolic rate were significantly smaller than SUV-based volumes.
Rodríguez et al. [21]	2010	40	40% of SUV max	Lymph nodes could be delineated in accordance with tumor uptake when lymph nodes/tumor SUV max ratio was ≤25%.
Devic et al. [22]	2010	31	Visual 15%, 40% of SUV max	Not dependent on the thresholding method used.
Vinod et al. [23]	2010	5	Visual	Effects of FDG-PET on normal tissue complication and tumor control cannot be predicted.
Wanet et al. [15]	2011	10	Gradient-based method Source-to-background ratio 40%, 50% of SUV max	Gradient-based method best estimated true tumor volume.
Warner-Wasik et al. [16]	2011	Phantom	Gradient-based method	Gradient-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	32	Source-to-background ratio	FDG-PET confined target volume definition was associated with low risk of isolated nodal recurrences.
Lin et al. [25]	2011	37	Visual	There was correlation between GTV based on FDG-PET and excised surgical specimen.