Facilitating tumor functional assessment by spatially relating 3D tumor histology and In Vivo MRI: Image registration approach

Lejla Alic, Joost C. Haeck, Karin Bol, Stefan Klein, Sandra T. van Tiel, Piotr A. Wielepolski, Marion de Jong, Wiro J. Niessen, Monique Bernsen, Jifke F. Veenland

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Background: Magnetic resonance imaging (MRI), together with histology, is widely used to diagnose and to monitor treatment in oncology. Spatial correspondence between these modalities provides information about the ability of MRI to characterize cancerous tissue. However, registration is complicated by deformations during pathological processing, and differences in scale and information content. Methodology/Principal Findings: This study proposes a methodology for establishing an accurate 3D relation between histological sections and high resolution in vivo MRI tumor data. The key features of the methodology are: 1) standardized acquisition and processing, 2) use of an intermediate ex vivo MRI, 3) use of a reference cutting plane, 4) dense histological sampling, 5) elastic registration, and 6) use of complete 3D data sets. Five rat pancreatic tumors imaged by T2*-w MRI were used to evaluate the proposed methodology. The registration accuracy was assessed by root mean squared (RMS) distances between manually annotated landmark points in both modalities. After elastic registration the average RMS distance decreased from 1.4 to 0.7 mm. The intermediate ex vivo MRI and the reference cutting plane shared by all three 3D images (in vivo MRI, ex vivo MRI, and 3D histology data) were found to be crucial for the accurate co-registration between the 3D histological data set and in vivo MRI. The MR intensity in necrotic regions, as manually annotated in 3D histology, was significantly different from other histologically confirmed regions (i.e., viable and hemorrhagic). However, the viable and the hemorrhagic regions showed a large overlap in T2*-w MRI signal intensity. Conclusions: The established 3D correspondence between tumor histology and in vivo MRI enables extraction of MRI characteristics for histologically confirmed regions. The proposed methodology allows the creation of a tumor database of spatially registered multi-spectral MR images and multi-stained 3D histology.

Original languageEnglish
Article numbere22835
JournalPLoS One
Volume6
Issue number8
DOIs
Publication statusPublished - 29 Aug 2011
Externally publishedYes

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Functional assessment
Histology
Image registration
magnetic resonance imaging
Magnetic resonance imaging
histology
Tumors
Magnetic Resonance Imaging
neoplasms
Neoplasms
methodology
Oncology
Processing

ASJC Scopus subject areas

  • Medicine(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Facilitating tumor functional assessment by spatially relating 3D tumor histology and In Vivo MRI : Image registration approach. / Alic, Lejla; Haeck, Joost C.; Bol, Karin; Klein, Stefan; van Tiel, Sandra T.; Wielepolski, Piotr A.; de Jong, Marion; Niessen, Wiro J.; Bernsen, Monique; Veenland, Jifke F.

In: PLoS One, Vol. 6, No. 8, e22835, 29.08.2011.

Research output: Contribution to journalArticle

Alic, L, Haeck, JC, Bol, K, Klein, S, van Tiel, ST, Wielepolski, PA, de Jong, M, Niessen, WJ, Bernsen, M & Veenland, JF 2011, 'Facilitating tumor functional assessment by spatially relating 3D tumor histology and In Vivo MRI: Image registration approach', PLoS One, vol. 6, no. 8, e22835. https://doi.org/10.1371/journal.pone.0022835
Alic, Lejla ; Haeck, Joost C. ; Bol, Karin ; Klein, Stefan ; van Tiel, Sandra T. ; Wielepolski, Piotr A. ; de Jong, Marion ; Niessen, Wiro J. ; Bernsen, Monique ; Veenland, Jifke F. / Facilitating tumor functional assessment by spatially relating 3D tumor histology and In Vivo MRI : Image registration approach. In: PLoS One. 2011 ; Vol. 6, No. 8.
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abstract = "Background: Magnetic resonance imaging (MRI), together with histology, is widely used to diagnose and to monitor treatment in oncology. Spatial correspondence between these modalities provides information about the ability of MRI to characterize cancerous tissue. However, registration is complicated by deformations during pathological processing, and differences in scale and information content. Methodology/Principal Findings: This study proposes a methodology for establishing an accurate 3D relation between histological sections and high resolution in vivo MRI tumor data. The key features of the methodology are: 1) standardized acquisition and processing, 2) use of an intermediate ex vivo MRI, 3) use of a reference cutting plane, 4) dense histological sampling, 5) elastic registration, and 6) use of complete 3D data sets. Five rat pancreatic tumors imaged by T2*-w MRI were used to evaluate the proposed methodology. The registration accuracy was assessed by root mean squared (RMS) distances between manually annotated landmark points in both modalities. After elastic registration the average RMS distance decreased from 1.4 to 0.7 mm. The intermediate ex vivo MRI and the reference cutting plane shared by all three 3D images (in vivo MRI, ex vivo MRI, and 3D histology data) were found to be crucial for the accurate co-registration between the 3D histological data set and in vivo MRI. The MR intensity in necrotic regions, as manually annotated in 3D histology, was significantly different from other histologically confirmed regions (i.e., viable and hemorrhagic). However, the viable and the hemorrhagic regions showed a large overlap in T2*-w MRI signal intensity. Conclusions: The established 3D correspondence between tumor histology and in vivo MRI enables extraction of MRI characteristics for histologically confirmed regions. The proposed methodology allows the creation of a tumor database of spatially registered multi-spectral MR images and multi-stained 3D histology.",
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AU - Klein, Stefan

AU - van Tiel, Sandra T.

AU - Wielepolski, Piotr A.

AU - de Jong, Marion

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AB - Background: Magnetic resonance imaging (MRI), together with histology, is widely used to diagnose and to monitor treatment in oncology. Spatial correspondence between these modalities provides information about the ability of MRI to characterize cancerous tissue. However, registration is complicated by deformations during pathological processing, and differences in scale and information content. Methodology/Principal Findings: This study proposes a methodology for establishing an accurate 3D relation between histological sections and high resolution in vivo MRI tumor data. The key features of the methodology are: 1) standardized acquisition and processing, 2) use of an intermediate ex vivo MRI, 3) use of a reference cutting plane, 4) dense histological sampling, 5) elastic registration, and 6) use of complete 3D data sets. Five rat pancreatic tumors imaged by T2*-w MRI were used to evaluate the proposed methodology. The registration accuracy was assessed by root mean squared (RMS) distances between manually annotated landmark points in both modalities. After elastic registration the average RMS distance decreased from 1.4 to 0.7 mm. The intermediate ex vivo MRI and the reference cutting plane shared by all three 3D images (in vivo MRI, ex vivo MRI, and 3D histology data) were found to be crucial for the accurate co-registration between the 3D histological data set and in vivo MRI. The MR intensity in necrotic regions, as manually annotated in 3D histology, was significantly different from other histologically confirmed regions (i.e., viable and hemorrhagic). However, the viable and the hemorrhagic regions showed a large overlap in T2*-w MRI signal intensity. Conclusions: The established 3D correspondence between tumor histology and in vivo MRI enables extraction of MRI characteristics for histologically confirmed regions. The proposed methodology allows the creation of a tumor database of spatially registered multi-spectral MR images and multi-stained 3D histology.

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