Literature DB >> 23144026

Robust alignment of prostate histology slices with quantified accuracy.

Cecilia Hughes1, Olivier Rouvière, Florence Mege-Lechevallier, Rémi Souchon, Rémy Prost.   

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.

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Year:  2012        PMID: 23144026     DOI: 10.1109/TBME.2012.2225835

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  7 in total

1.  Mri-based cancer lesion analysis with 3d printed patient specific prostate cutting guides.

Authors:  David R Rutkowski; Shane A Wells; Brian Johnson; Wei Huang; David F Jarrard; Joshua M Lang; Steve Cho; Alejandro Roldán-Alzate
Journal:  Am J Clin Exp Urol       Date:  2019-08-15

2.  Influence of imaging and histological factors on prostate cancer detection and localisation on multiparametric MRI: a prospective study.

Authors:  Flavie Bratan; Emilie Niaf; Christelle Melodelima; Anne Laure Chesnais; Rémi Souchon; Florence Mège-Lechevallier; Marc Colombel; Olivier Rouvière
Journal:  Eur Radiol       Date:  2013-03-15       Impact factor: 5.315

3.  A Method for 3D Histopathology Reconstruction Supporting Mouse Microvasculature Analysis.

Authors:  Yiwen Xu; J Geoffrey Pickering; Zengxuan Nong; Eli Gibson; John-Michael Arpino; Hao Yin; Aaron D Ward
Journal:  PLoS One       Date:  2015-05-29       Impact factor: 3.240

4.  3D prostate histology image reconstruction: Quantifying the impact of tissue deformation and histology section location.

Authors:  Eli Gibson; Mena Gaed; José A Gómez; Madeleine Moussa; Stephen Pautler; Joseph L Chin; Cathie Crukley; Glenn S Bauman; Aaron Fenster; Aaron D Ward
Journal:  J Pathol Inform       Date:  2013-10-31

Review 5.  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

6.  Comparative analysis of tissue reconstruction algorithms for 3D histology.

Authors:  Kimmo Kartasalo; Leena Latonen; Jorma Vihinen; Tapio Visakorpi; Matti Nykter; Pekka Ruusuvuori
Journal:  Bioinformatics       Date:  2018-09-01       Impact factor: 6.937

7.  A method for accurate spatial registration of PET images and histopathology slices.

Authors:  Tanuj Puri; Anastasia Chalkidou; Rhonda Henley-Smith; Arunabha Roy; Paul R Barber; Teresa Guerrero-Urbano; Richard Oakley; Ricard Simo; Jean-Pierre Jeannon; Mark McGurk; Edward W Odell; Michael J O'Doherty; Paul K Marsden
Journal:  EJNMMI Res       Date:  2015-11-14       Impact factor: 3.138

  7 in total

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