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Framework for the co-registration of MRI and histology images in prostate cancer patients with radical prostatectomy
Author(s): Mirabela Rusu; Christian Kunder; Richard Fan; Pejman Ghanouni M.D.; Robert West; Geoffrey Sonn; James Brooks M.D.
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Paper Abstract

Prostate magnetic resonance imaging (MRI) allows the detection and treatment planning of clinically significant cancers. However, indolent cancers, e.g., those with Gleason scores 3+3, are not readily distinguishable on MRI. Thus an image-guided biopsy is still required before proceeding with a radical treatment for aggressive tumors or considering active surveillance for indolent disease. The excision of the prostate as part of radical prostatectomy treatments provides a unique opportunity to correlate whole-mount histology slices with MRI. Through a careful spatial alignment of histology slices and MRI, the extent of aggressive and indolent disease can be mapped on MRI which allows one to investigate MRI-derived features that might be able to distinguish aggressive from indolent cancers. Here, we introduce a framework for the 3D spatial integration of radiology and pathology images in the prostate. Our approach, first, uses groupwise-registration methods to reconstruct the histology specimen prior to sectioning, and incorporates the MRI as a spatial constraint, and, then, performs a multi-modal 3D affine and deformable alignment between the reconstructed histology specimen and the MRI. We tested our approach on 15 studies and found a Dice similarity coefficient of 0.94±0.02 and a urethra deviation of 1.11±0.34 mm between the histology reconstruction and the MRI. Our robust framework successfully mapped the extent of disease from histology slices on MRI and created ground truth labels for characterizing aggressive and indolent disease on MRI.

Paper Details

Date Published: 15 March 2019
PDF: 4 pages
Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109491P (15 March 2019); doi: 10.1117/12.2513099
Show Author Affiliations
Mirabela Rusu, Stanford Univ. (United States)
Christian Kunder, Stanford Univ. (United States)
Richard Fan, Stanford Univ. (United States)
Pejman Ghanouni M.D., Stanford Univ. (United States)
Robert West, Stanford Univ. (United States)
Geoffrey Sonn, Stanford Univ. (United States)
James Brooks M.D., Stanford Univ. (United States)

Published in SPIE Proceedings Vol. 10949:
Medical Imaging 2019: Image Processing
Elsa D. Angelini; Bennett A. Landman, Editor(s)

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