Literature DB >> 22255771

Spatially weighted mutual information (SWMI) for registration of digitally reconstructed ex vivo whole mount histology and in vivo prostate MRI.

Pratik Patel1, Jonathan Chappelow, John Tomaszewski, Michael D Feldman, Mark Rosen, Natalie Shih, Anant Madabhushi.   

Abstract

In this work, we present a scheme for the registration of digitally reconstructed whole mount histology (WMH) to pre-operative in vivo multiprotocol prostate MR imagery (T2w and DCE) using spatially weighted mutual information (SWMI). Spatial alignment of ex vivo histological sections to pre-operative in vivo MRI for prostate cancer (CaP) patients undergoing radical prostatectomy is a necessary first step in the discovery of quantitative multiprotocol MRI signatures for CaP. This may be done by spatially mapping delineated extent of disease on ex vivo histopathology onto pre-operative in vivo MRI via image registration. Apart from the challenges in spatially registering multi-modal data (histology and MRI) on account of (a) modality specific differences, (b) deformation due to the endorectal coil and tissue loss on histology, another complication is that the ex vivo histological sections, in the lab, are usually obtained as quadrants. This means they need to be reconstituted as a pseudo-whole mount histologic section (WMHS) prior to registration with MRI. An additional challenge is that most registration techniques rely on availability of the pre-segmented prostate capsule on T2w MRI. The novel contribution of this paper is that it leverages a spatially weighted mutual information (SWMI) scheme to automatically register and map CaP extent from WMHS onto pre-operative, multiprotocol MRI. The SWMI scheme obviates the need for pre-segmentation of the prostate capsule on MRI. Additionally, we leverage a program developed by our group, Histostitcher©, for interactive stitching of individual histology quadrants to digitally reconstruct the pseudo WMHS. Our registration methodology comprises the following main steps, (1) affine registration of T2w and DCE MRI, (2) affine registration of stitched WMHS to multiprotocol T2w and DCE MRI, and (3) multimodal image registration of WMHS to multiprotocol T2w and DCE MRI using SWMI. We quantitatively and qualitatively evaluated all aspects of our methodology in the multimodal registration of a total of 7 corresponding histology and MRI sections from 2 different patients. For the 7 studies, we obtained an average Hausdorff distance of 1.85 mm, mean absolute distance of 0.99 mm, RMS of 1.65 mm, and DICE of 0.83, when comparing the capsular alignment on MRI to histology.

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Year:  2011        PMID: 22255771     DOI: 10.1109/IEMBS.2011.6091547

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  8 in total

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Journal:  Acad Radiol       Date:  2017-11-06       Impact factor: 3.173

Review 2.  Computer-aided Detection of Prostate Cancer with MRI: Technology and Applications.

Authors:  Lizhi Liu; Zhiqiang Tian; Zhenfeng Zhang; Baowei Fei
Journal:  Acad Radiol       Date:  2016-04-25       Impact factor: 3.173

3.  Registration of in vivo prostate MRI and pseudo-whole mount histology using Local Affine Transformations guided by Internal Structures (LATIS).

Authors:  Chaitanya Kalavagunta; Xiangmin Zhou; Stephen C Schmechel; Gregory J Metzger
Journal:  J Magn Reson Imaging       Date:  2014-04-04       Impact factor: 4.813

4.  Semiautomatic registration of digital histopathology images to in vivo MR images in molded and unmolded prostates.

Authors:  Olga Starobinets; Richard Guo; Jeffry P Simko; Kyle Kuchinsky; John Kurhanewicz; Peter R Carroll; Kirsten L Greene; Susan M Noworolski
Journal:  J Magn Reson Imaging       Date:  2013-10-17       Impact factor: 4.813

5.  3D Registration of pre-surgical prostate MRI and histopathology images via super-resolution volume reconstruction.

Authors:  Rewa R Sood; Wei Shao; Christian Kunder; Nikola C Teslovich; Jeffrey B Wang; Simon J C Soerensen; Nikhil Madhuripan; Anugayathri Jawahar; James D Brooks; Pejman Ghanouni; Richard E Fan; Geoffrey A Sonn; Mirabela Rusu
Journal:  Med Image Anal       Date:  2021-01-23       Impact factor: 8.545

6.  Building of a composite virtual slide from contiguous tissue samples.

Authors:  Benoît Plancoulaine; Myriam Oger; Nicolas Elie; Philippe Belhomme; Paulette Herlin; Abir Nasri; Célia Augé; Mylène Brécin; Jacques Marnay; Catherine Bor-Angelier
Journal:  Diagn Pathol       Date:  2014-12-19       Impact factor: 2.644

Review 7.  Accurate validation of ultrasound imaging of prostate cancer: a review of challenges in registration of imaging and histopathology.

Authors:  Rogier R Wildeboer; Ruud J G van Sloun; Arnoud W Postema; Christophe K Mannaerts; Maudy Gayet; Harrie P Beerlage; Hessel Wijkstra; Massimo Mischi
Journal:  J Ultrasound       Date:  2018-07-30

8.  Weighted mutual information analysis substantially improves domain-based functional network models.

Authors:  Jung Eun Shim; Insuk Lee
Journal:  Bioinformatics       Date:  2016-05-20       Impact factor: 6.937

  8 in total

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