title: Understanding the pathological implications of MRI: application to focal therapy planning.
abstract: OBJECTIVE
  The current challenge in prostate cancer (PCa) focal therapy indication and planning is how to accurately estimate tumor parameters such as volume, extent and grade. In addition to biopsy results, MRI provides an estimation of PCa contour, volume and histopathological characteristics such as presence of high Gleason grade. Among MRI sequences, diffusion-weighted imaging with apparent diffusion coefficient map is the sequence that showed the best results for cancer aggressiveness characterization.
  
  
  RESULTS
  It was shown that the higher the Gleason score, the lower the apparent diffusion coefficient value. However, accuracy is not sufficient for peripheral zone cancers to be validated for clinical decision and it was not enough investigated for transition zone cancers. Analysis of tumor extent showed a significant underestimation of tumor volume by imaging and this finding should be taken into consideration when planning focal therapy procedures.
  
  
  CONCLUSIONS
  Pathological implications of MRI for focal therapy planning are significant but not mature enough to be validated. Future research should aim to quantify cellularity and architectural patterns of PCa Gleason system in correlation with signal abnormalities for better assessment of tumor aggressiveness and extent, and to compare the boundaries of tumors between MRI and histopathological evaluation in order to define an optimal treatment margin.
authors.affiliation: aDepartment of Urology bDepartment of Radiology, CHU Lille cInserm U1189 - ONCO-THAI, CHRU Lille, Université de Lille, Loos, France.
authors.forename: Adil
authors.initials: A
authors.lastname: Ouzzane
authors.forename: Olivier
authors.initials: O
authors.lastname: Helfrich
authors.forename: Julien
authors.initials: J
authors.lastname: Le Nobin
authors.forename: Philippe
authors.initials: P
authors.lastname: Puech
authors.forename: Nacim
authors.initials: N
authors.lastname: Betrouni
authors.forename: Arnauld
authors.initials: A
authors.lastname: Villers
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D060787:Neoplasm Grading; D009361:Neoplasm Invasiveness / Q000473:pathology; D011379:Prognosis; D011468:Prostatectomy / Q000379:methods*; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D012680:Sensitivity and Specificity; D047368:Tumor Burden