title: Prostate tumour volumes: evaluation of the agreement between magnetic resonance imaging and histology using novel co-registration software.
abstract: OBJECTIVE
  To evaluate the agreement between prostate tumour volume determined using multiparametric magnetic resonance imaging (MRI) and that determined by histological assessment, using detailed software-assisted co-registration.
  
  
  METHODS
  A total of 37 patients who underwent 3T multiparametric MRI (T2-weighted imaging [T2WI], diffusion-weighted imaging [DWI]/apparent diffusion coefficient [ADC], dynamic contrast-enhanced [DCE] imaging) were included. A radiologist traced the borders of suspicious lesions on T2WI and ADC and assigned a suspicion score of between 2 and 5, while a uropathologist traced the borders of tumours on histopathological photographs. Software was used to co-register MRI and three-dimensional digital reconstructions of radical prostatectomy specimens and to compute imaging and histopathological volumes. Agreement in volumes between MRI and histology was assessed using Bland-Altman plots and stratified by tumour characteristics.
  
  
  RESULTS
  Among 50 tumours, the mean differences (95% limits of agreement) in MRI relative to histology were -32% (-128 to +65%) on T2WI and -47% (-143 to +49%) on ADC. For all tumour subsets, volume underestimation was more marked on ADC maps (mean difference ranging from -57 to -16%) than on T2WI (mean difference ranging from -45 to +2%). The 95% limits of agreement were wide for all comparisons, with the lower 95% limit ranging between -77 and -143% across assessments. Volume underestimation was more marked for tumours with a Gleason score ≥7 or a MRI suspicion score 4 or 5.
  
  
  CONCLUSIONS
  Volume estimates of prostate cancer using MRI tended to substantially underestimate histopathological volumes, with a wide variability in extent of underestimation across cases. These findings have implications for efforts to use MRI to guide risk assessment.
authors.affiliation: Department of Urology, Division of Urological Oncology, New York University Langone Medical Center, New York, NY, USA.|Department of Urology, University Hospital of Lille, Lille, France.
authors.forename: Julien
authors.initials: J
authors.lastname: Le Nobin
authors.affiliation: Department of Urology, Division of Urological Oncology, New York University Langone Medical Center, New York, NY, USA.|Department of Urology and Renal Transplantation/UMR 6301-Cervoxy Group, University Hospital of Caen, Caen, France.
authors.forename: Clément
authors.identifier: http://orcid.org/0000-0003-3067-2409
authors.initials: C
authors.lastname: Orczyk
authors.affiliation: Department of Pathology, New York University Langone Medical Center, New York, NY, USA.
authors.forename: Fang-Ming
authors.initials: FM
authors.lastname: Deng
authors.affiliation: Department of Pathology, New York University Langone Medical Center, New York, NY, USA.
authors.forename: Jonathan
authors.initials: J
authors.lastname: Melamed
authors.affiliation: Department of Radiology, New York University Langone Medical Center, New York, NY, USA.
authors.forename: Henry
authors.initials: H
authors.lastname: Rusinek
authors.affiliation: Department of Urology, Division of Urological Oncology, New York University Langone Medical Center, New York, NY, USA.
authors.forename: Samir S
authors.initials: SS
authors.lastname: Taneja
authors.affiliation: Department of Radiology, New York University Langone Medical Center, New York, NY, USA.
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Rosenkrantz
mesh_terms: D000368:Aged; D038524:Diffusion Magnetic Resonance Imaging; D006801:Humans; D021621:Imaging, Three-Dimensional; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D011468:Prostatectomy; D011471:Prostatic Neoplasms / Q000473:pathology* / Q000601:surgery; D012189:Retrospective Studies; D018570:Risk Assessment / Q000379:methods; D012984:Software; D047368:Tumor Burden
keywords: computer-assisted; diffusion-weighted MRI; histology; image processing; prostate cancer; tumour volume