title: A Workflow to Improve the Alignment of Prostate Imaging with Whole-mount Histopathology.
abstract: OBJECTIVE
  Evaluation of prostate imaging tests against whole-mount histology specimens requires accurate alignment between radiologic and histologic data sets. Misalignment results in false-positive and -negative zones as assessed by imaging. We describe a workflow for three-dimensional alignment of prostate imaging data against whole-mount prostatectomy reference specimens and assess its performance against a standard workflow.
  
  
  METHODS
  Ethical approval was granted. Patients underwent motorized transrectal ultrasound (Prostate Histoscanning) to generate a three-dimensional image of the prostate before radical prostatectomy. The test workflow incorporated steps for axial alignment between imaging and histology, size adjustments following formalin fixation, and use of custom-made parallel cutters and digital caliper instruments. The control workflow comprised freehand cutting and assumed homogeneous block thicknesses at the same relative angles between pathology and imaging sections.
  
  
  RESULTS
  Thirty radical prostatectomy specimens were histologically and radiologically processed, either by an alignment-optimized workflow (n = 20) or a control workflow (n = 10). The optimized workflow generated tissue blocks of heterogeneous thicknesses but with no significant drifting in the cutting plane. The control workflow resulted in significantly nonparallel blocks, accurately matching only one out of four histology blocks to their respective imaging data. The image-to-histology alignment accuracy was 20% greater in the optimized workflow (P < .0001), with higher sensitivity (85% vs. 69%) and specificity (94% vs. 73%) for margin prediction in a 5 × 5-mm grid analysis.
  
  
  CONCLUSIONS
  A significantly better alignment was observed in the optimized workflow. Evaluation of prostate imaging biomarkers using whole-mount histology references should include a test-to-reference spatial alignment workflow.
authors.forename: Hidekazu
authors.initials: H
authors.lastname: Yamamoto
authors.forename: Dror
authors.initials: D
authors.lastname: Nir
authors.forename: Lona
authors.initials: L
authors.lastname: Vyas
authors.forename: Richard T
authors.initials: RT
authors.lastname: Chang
authors.forename: Rick
authors.initials: R
authors.lastname: Popert
authors.forename: Declan
authors.initials: D
authors.lastname: Cahill
authors.forename: Ben
authors.initials: B
authors.lastname: Challacombe
authors.forename: Prokar
authors.initials: P
authors.lastname: Dasgupta
authors.forename: Ashish
authors.initials: A
authors.lastname: Chandra
mesh_terms: D000368:Aged; D000465:Algorithms; D006801:Humans; D061705:Image-Guided Biopsy / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008867:Microtomy / Q000379:methods*; D008875:Middle Aged; D011467:Prostate / Q000000981:diagnostic imaging* / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000175:diagnosis*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013194:Staining and Labeling / Q000379:methods; D013382:Subtraction Technique; D014463:Ultrasonography; D057188:Workflow
keywords: Prostate cancer; histoscanning; image alignment; image registration; whole-mount histopathology