title: Simulated required accuracy of image registration tools for targeting high-grade cancer components with prostate biopsies.
abstract: OBJECTIVE
  To estimate the required spatial alignment accuracy for correctly grading 95 % of peripheral zone (PZ) prostate cancers using a system for multiparametric magnetic resonance (MR)-guided ultrasound (US) biopsies.
  
  
  METHODS
  PZ prostate tumours were retrospectively annotated on multiparametric MR series using prostatectomy specimens as reference standard. Tumours were grouped based on homogeneous and heterogeneous apparent diffusion coefficient (ADC) values using an automated ADC texture analysis method. The proportion of heterogeneous tumours containing a distinct, high Gleason grade tumour focus yielding low ADC values was determined. Both overall tumour and high-grade focal volumes were calculated. All high-grade target volumes were then used in a simulated US biopsy system with adjustable accuracy to determine the hit rate.
  
  
  RESULTS
  An ADC-determined high-grade tumour focus was found in 63 % of the PZ prostate tumours. The focal volumes were significantly smaller than the total tumour volumes (median volume of 0.3 ml and 1.1 ml respectively). To correctly grade 95 % of the aggressive tumour components the target registration error (TRE) should be smaller than 1.9 mm.
  
  
  CONCLUSIONS
  To enable finding the high Gleason grade component in 95 % of PZ prostate tumours with MR-guided US biopsies, a technical registration accuracy of 1.9 mm is required.
  
  
  CONCLUSIONS
  • MRI can identify foci of prostatic cancer with reduced apparent diffusion coefficients • Sixty-three per cent of prostatic peripheral zone tumours contain high-grade tumour low ADC foci • The median volume of such foci is 0.3 ml • Biopsy targets are significantly smaller than whole tumour volumes • Simulated registration accuracy is 1.9 mm for correctly grading 95 % of tumours.
authors.affiliation: Department of Radiology, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, The Netherlands. W.vandeVen@rad.umcn.nl
authors.forename: Wendy J M
authors.initials: WJ
authors.lastname: van de Ven
authors.forename: Christina A
authors.initials: CA
authors.lastname: Hulsbergen-van de Kaa
authors.forename: Thomas
authors.initials: T
authors.lastname: Hambrock
authors.forename: Jelle O
authors.initials: JO
authors.lastname: Barentsz
authors.forename: Henkjan J
authors.initials: HJ
authors.lastname: Huisman
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D061705:Image-Guided Biopsy / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008954:Models, Biological; D060787:Neoplasm Grading; D011471:Prostatic Neoplasms / Q000473:pathology*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique