Registration of histopathology to magnetic resonance imaging of prostate cancer

Abstract

Background and purpose: The diagnostic accuracy of new imaging techniques requires validation, preferably by histopathological verification. The aim of this study was to develop and present a registration procedure between histopathology and in-vivo magnetic resonance imaging (MRI) of the prostate, to estimate its uncertainty and to evaluate the benefit of adding a contour-correcting registration. Materials and methods: For twenty-five prostate cancer patients, planned for radical prostatectomy, a 3D-printed prostate mold based on in-vivo MRI was created and an ex-vivo MRI of the specimen, placed inside the mold, was performed. Each histopathology slice was registered to its corresponding ex-vivo MRI slice using a 2D-affine registration. The ex-vivo MRI was rigidly registered to the in-vivo MRI and the resulting transform was applied to the histopathology stack. A 2D deformable registration was used to correct for specimen distortion concerning the specimen's fit inside the mold. We estimated the spatial uncertainty by comparing positions of landmarks in the in-vivo MRI and the corresponding registered histopathology stack. Results: Eighty-four landmarks were identified, located in the urethra (62%), prostatic cysts (33%), and the ejaculatory ducts (5%). The median number of landmarks was 3 per patient. We showed a median in-plane error of 1.8 mm before and 1.7 mm after the contour-correcting deformable registration. In patients with extraprostatic margins, the median in-plane error improved from 2.1 mm to 1.8 mm after the contour-correcting deformable registration. Conclusions: Our registration procedure accurately registers histopathology to in-vivo MRI, with low uncertainty. The contour-correcting registration was beneficial in patients with extraprostatic surgical margins.

Multiparametric magnetic resonance imaging for radiation therapy response monitoring in soft tissue sarcomas: a histology and MRI co-registration algorithm

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Spatial correlation of 2D hard-tissue histology with 3D microCT scans through 3D printed phantoms

“…The application was further limited by a dedicated preparation step, in which the pins are inserted into holes drilled using a computer numerically controlled (CNC) mill. Other researchers suggest the use of individual 3D-printed slicer-molds to aid and guide the cutting process 22 . Here the specimens were scanned, segmented, and loaded into a CAD Software.…”

A statistical, voxelised model of prostate cancer for biologically optimised radiotherapy

“…Validation of computational models to predict biological characteristics using patient imaging data, however, remains challenging. Ground truth is difficult to ascertain; histopathological analysis of surgically removed prostates is considered the gold standard, but accurate correlation of histology and mpMRI is hampered by significant differences in features between these modalities and physical deformation of the prostate following removal [27][28][29][30]. We previously reported a novel approach, using ex vivo MRI, to minimise uncertainties during co-registration, however, quantifying the accuracy of this process is difficult [31].…”