title: Robust alignment of prostate histology slices with quantified accuracy.
abstract: No current imaging technique is capable of detecting with precision tumors in the prostate. To evaluate each technique, the histology data must be precisely mapped to the imaged data. As the histology slices cannot be assumed to be cut along the same plane as the imaged data were acquired, the registration must be considered as a 3-D problem. This requires the prior alignment of the histology slices. We propose a protocol in which three needles are inserted into the fresh prostate, creating internal fiducial markers visible in the histology slices. Our algorithm then automatically detects and identifies these markers, enabling the automatic rigid alignment of each slice. The accuracy of the algorithm was quantified in simulated images, a beef liver sample in which a validation marker had been created, and ten prostate specimens. The simulated images showed that the algorithm has no associated residual error for a situation where there is no deformation. In the beef liver images, the average accuracy of the alignment was 0.12 ± 0.09 mm at the fiducial markers, and 0.62 ± 0.46 mm at a validation marker positioned approximately 20 mm from the fiducial markers. Concerning the ten prostates, there were 19.2 histology slices on average per specimen. On average, 93.7% of the fiducial markers created were visible in the slices, of which 96.1% were then automatically and correctly detected and identified, enabling an alignment of average accuracy 0.18 ± 0.13 mm at the fiducial markers. As a cancer of volume <0.5 cm(3) is classified as clinically insignificant, the accuracy achieved justified the choice of a rigid registration. An attractive feature of this method is the time required, less than 6 min on average per prostate specimen.
authors.affiliation: Department of Electrical Engineering, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA. pashaie@uwm.edu
authors.forename: Cecilia
authors.initials: C
authors.lastname: Hughes
authors.forename: Olivier
authors.initials: O
authors.lastname: Rouvière
authors.forename: Florence
authors.initials: F
authors.lastname: Mege-Lechevallier
authors.forename: Rémi
authors.initials: R
authors.lastname: Souchon
authors.forename: Rémy
authors.initials: R
authors.lastname: Prost
mesh_terms: D000465:Algorithms; D000818:Animals; D002417:Cattle; D003198:Computer Simulation; D057918:Fiducial Markers; D006651:Histocytochemistry / Q000379:methods*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008954:Models, Biological; D011467:Prostate / Q000737:chemistry / Q000473:pathology*; D011471:Prostatic Neoplasms / Q000737:chemistry / Q000473:pathology*