title: Effects of image characteristics on performance of tumor delineation methods: a test-retest assessment.
abstract: PET can be used to monitor response during chemotherapy and assess biologic target volumes for radiotherapy. Previous simulation studies have shown that the performance of various automatic or semiautomatic tumor delineation methods depends on image characteristics. The purpose of this study was to assess test-retest variability of tumor delineation methods, with emphasis on the effects of several image characteristics (e.g., resolution and contrast).
  
  
  METHODS
  Baseline test-retest data from 19 non-small cell lung cancer patients were obtained using (18)F-FDG (n = 10) and 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) (n = 9). Images were reconstructed with varying spatial resolution and contrast. Six different types of tumor delineation methods, based on various thresholds or on a gradient, were applied to all datasets. Test-retest variability of metabolic volume and standardized uptake value (SUV) was determined.
  
  
  RESULTS
  For both tracers, size of metabolic volume and test-retest variability of both metabolic volume and SUV were affected by the image characteristics and tumor delineation method used. The median volume test-retest variability ranged from 8.3% to 23% and from 7.4% to 29% for (18)F-FDG and (18)F-FLT, respectively. For all image characteristics studied, larger differences (≤10-fold higher) were seen in test-retest variability of metabolic volume than in SUV.
  
  
  CONCLUSIONS
  Test-retest variability of both metabolic volume and SUV varied with tumor delineation method, radiotracer, and image characteristics. The results indicate that a careful optimization of imaging and delineation method parameters is needed when metabolic volume is used, for example, as a response assessment parameter.
authors.affiliation: Department of Nuclear Medicine and PET Research, VU University Medical Center, Amsterdam, The Netherlands.
authors.forename: Patsuree
authors.initials: P
authors.lastname: Cheebsumon
authors.forename: Floris H P
authors.initials: FH
authors.lastname: van Velden
authors.forename: Maqsood
authors.initials: M
authors.lastname: Yaqub
authors.forename: Virginie
authors.initials: V
authors.lastname: Frings
authors.forename: Adrianus J
authors.initials: AJ
authors.lastname: de Langen
authors.forename: Otto S
authors.initials: OS
authors.lastname: Hoekstra
authors.forename: Adriaan A
authors.initials: AA
authors.lastname: Lammertsma
authors.forename: Ronald
authors.initials: R
authors.lastname: Boellaard
mesh_terms: D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000378:metabolism; D015224:Dideoxynucleosides; D005260:Female; D005462:Fluorine Radioisotopes; D019788:Fluorodeoxyglucose F18; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000378:metabolism; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000706:statistics & numerical data*; D019275:Radiopharmaceuticals; D012189:Retrospective Studies
chemical_list: D015224:Dideoxynucleosides; D005462:Fluorine Radioisotopes; D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18; C002854:alovudine