title: Automatic delineation for replanning in nasopharynx radiotherapy: what is the agreement among experts to be considered as benchmark?
abstract: OBJECTIVE
  Anatomic changes during head and neck radiotherapy require replanning. The primary aim of this study is the definition of the agreement among experts in the head and neck automatic delineation frame to use as benchmark. The secondary goal is to assess the reliability of automatic delineation for nasopharynx radiotherapy and time saving.
  
  
  METHODS
  A computed tomography (CT) scan was acquired in 10 nasopharynx patients along intensity-modulated radiotherapy (IMRT) treatment for replanning. Deformable registration with replanning autocontouring of the structures was performed using VelocityAI 2.3© software defining Structure Set A. The optimization of these contours was obtained through revision by a skilled operator, drawing Structure Set B. An ex novo Structure Set C was segmented on the replanning CT-scan by an expert delineation team. The mean Dice's Similarity Index (mDSI) was calculated between Structure Set A and B, A and C, and between B and C for each volume. All segmentation times for organs at risk (OARs) and clinical target volume (CTV) were recorded and compared.
  
  
  RESULTS
  We validated the replanning autocontoured Structure Sets for 10 patients. For volumetric analysis we observed mDSI values of 0.87 for the OARs, 0.70 for nodes, 0.90 for CTV in the Structure Set A-B comparison and respectively of 0.74, 0.63 and 0.78 for the Structure Set A-C one, and 0.78, 0.78 and 0.85 for Structure Set B-C, which represents the existing expert based benchmark. We calculated a mean saved time in Structure Set B of 30 minutes.
  
  
  CONCLUSIONS
  Autocontouring procedures offer considerable segmentation time saving with acceptable reliability of the contours, even if an independent check procedure for their optimization is still required to increase their adherence to referential benchmark gold standard among experts, which stands at a 0.80 DSI value.
authors: Radiation Oncology Department, Università Cattolica del Sacro Cuore , Rome , Italy.
authors: Gian Carlo
authors: GC
authors: Mattiucci
authors: Luca
authors: L
authors: Boldrini
authors: Giuditta
authors: G
authors: Chiloiro
authors: Giuseppe Roberto
authors: GR
authors: D'Agostino
authors: Silvia
authors: S
authors: Chiesa
authors: Fiorenza
authors: F
authors: De Rose
authors: Luigi
authors: L
authors: Azario
authors: Danilo
authors: D
authors: Pasini
authors: Maria Antonietta
authors: MA
authors: Gambacorta
authors: Mario
authors: M
authors: Balducci
authors: Vincenzo
authors: V
authors: Valentini
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000465:Algorithms; D001331:Automation; D005260:Female; D006258:Head and Neck Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D058958:Organs at Risk / Q000528:radiation effects; D011379:Prognosis; D011856:Radiographic Image Enhancement; D011880:Radiotherapy Planning, Computer-Assisted; D061089:Radiotherapy, Image-Guided; D050397:Radiotherapy, Intensity-Modulated; D014057:Tomography, X-Ray Computed