title: What is the best way to contour lung tumors on PET scans? Multiobserver validation of a gradient-based method using a NSCLC digital PET phantom.
abstract: OBJECTIVE
  To evaluate the accuracy and consistency of a gradient-based positron emission tomography (PET) segmentation method, GRADIENT, compared with manual (MANUAL) and constant threshold (THRESHOLD) methods.
  
  
  METHODS
  Contouring accuracy was evaluated with sphere phantoms and clinically realistic Monte Carlo PET phantoms of the thorax. The sphere phantoms were 10-37 mm in diameter and were acquired at five institutions emulating clinical conditions. One institution also acquired a sphere phantom with multiple source-to-background ratios of 2:1, 5:1, 10:1, 20:1, and 70:1. One observer segmented (contoured) each sphere with GRADIENT and THRESHOLD from 25% to 50% at 5% increments. Subsequently, seven physicians segmented 31 lesions (7-264 mL) from 25 digital thorax phantoms using GRADIENT, THRESHOLD, and MANUAL.
  
  
  RESULTS
  For spheres <20 mm in diameter, GRADIENT was the most accurate with a mean absolute % error in diameter of 8.15% (10.2% SD) compared with 49.2% (51.1% SD) for 45% THRESHOLD (p < 0.005). For larger spheres, the methods were statistically equivalent. For varying source-to-background ratios, GRADIENT was the most accurate for spheres >20 mm (p < 0.065) and <20 mm (p < 0.015). For digital thorax phantoms, GRADIENT was the most accurate (p < 0.01), with a mean absolute % error in volume of 10.99% (11.9% SD), followed by 25% THRESHOLD at 17.5% (29.4% SD), and MANUAL at 19.5% (17.2% SD). GRADIENT had the least systematic bias, with a mean % error in volume of -0.05% (16.2% SD) compared with 25% THRESHOLD at -2.1% (34.2% SD) and MANUAL at -16.3% (20.2% SD; p value <0.01). Interobserver variability was reduced using GRADIENT compared with both 25% THRESHOLD and MANUAL (p value <0.01, Levene's test).
  
  
  CONCLUSIONS
  GRADIENT was the most accurate and consistent technique for target volume contouring. GRADIENT was also the most robust for varying imaging conditions. GRADIENT has the potential to play an important role for tumor delineation in radiation therapy planning and response assessment.
authors.affiliation: Department of Radiation Oncology, Thomas Jefferson University Hospital, Philadelphia, PA 19107, USA. Maria.Wernerwasik@jeffersonhospital.org
authors.forename: Maria
authors.initials: M
authors.lastname: Werner-Wasik
authors.forename: Arden D
authors.initials: AD
authors.lastname: Nelson
authors.forename: Walter
authors.initials: W
authors.lastname: Choi
authors.forename: Yoshio
authors.initials: Y
authors.lastname: Arai
authors.forename: Peter F
authors.initials: PF
authors.lastname: Faulhaber
authors.forename: Patrick
authors.initials: P
authors.lastname: Kang
authors.forename: Fabio D
authors.initials: FD
authors.lastname: Almeida
authors.forename: Ying
authors.initials: Y
authors.lastname: Xiao
authors.forename: Nitin
authors.initials: N
authors.lastname: Ohri
authors.forename: Kristin D
authors.initials: KD
authors.lastname: Brockway
authors.forename: Jonathan W
authors.initials: JW
authors.lastname: Piper
authors.forename: Aaron S
authors.initials: AS
authors.lastname: Nelson
mesh_terms: D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging*; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008198:Lymph Nodes / Q000000981:diagnostic imaging; D009010:Monte Carlo Method; D015588:Observer Variation; D019047:Phantoms, Imaging; D049268:Positron-Emission Tomography / Q000295:instrumentation / Q000379:methods*