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On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis.

Weis CA, Grießmann BW, Scharff C, Detzner C, Pfister E, Marx A, Zoellner FG - Diagn Pathol (2015)

Bottom Line: In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor.Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad).Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pathology, University Medical Centre Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany. Cleo-Aron.Weis@medma.uni-heidelberg.de.

ABSTRACT

Background: Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections.

Methods: The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object's centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image.

Results: After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field - were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection.

Conclusions: The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

No MeSH data available.


Related in: MedlinePlus

Direct spatial interaction in a lymphoid follicle. Serial sections of a trephine biopsy from a patient with bone marrow lymphocytosis were stained for CD3, CD3, CD20 and CD20 (a-d). Subsequently, slides were fully digitalized, registered and analysed as described. By segmentation, there are 320 CD3+ and 1,156 CD3−/+ nuclei in a, 392 CD3+ and 1,139 CD3−/+ nuclei in b, 316 CD20+ and 1,176 CD20−/+ nuclei in c and respectively 202 CD20+ and 1,182 CD20−/+ nuclei in d. Overlap readings are calculated for direct interaction (RBFdirect). A + B: Overlap of both images with A (first section stained for CD3) drawn in red and respectively B (second section stained for CD3) drawn in blue. For stained cells, PCC = 0.95, MOC = 0.99 and M1st section CD3+ = 0.98 and M2nd section CD3 = 0.81. B + C: Overlap of both images with B (second section stained for CD3) drawn in red and respectively C (first section stained for CD20) drawn in blue. For stained cells, PCC = 0.97, MOC = 0.99 and M2ndsection CD3+ = 0.83 and M1stsection CD20 = 0.97. C + D: Overlap of both images with C (first section stained for CD20) drawn in red and respectively D (second section stained for CD20) drawn in blue. For stained cells, PCC = 0.67, MOC = 0.92 and M1st section CD20+ = 0.57 and M2nd section CD20 = 0.97
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Fig5: Direct spatial interaction in a lymphoid follicle. Serial sections of a trephine biopsy from a patient with bone marrow lymphocytosis were stained for CD3, CD3, CD20 and CD20 (a-d). Subsequently, slides were fully digitalized, registered and analysed as described. By segmentation, there are 320 CD3+ and 1,156 CD3−/+ nuclei in a, 392 CD3+ and 1,139 CD3−/+ nuclei in b, 316 CD20+ and 1,176 CD20−/+ nuclei in c and respectively 202 CD20+ and 1,182 CD20−/+ nuclei in d. Overlap readings are calculated for direct interaction (RBFdirect). A + B: Overlap of both images with A (first section stained for CD3) drawn in red and respectively B (second section stained for CD3) drawn in blue. For stained cells, PCC = 0.95, MOC = 0.99 and M1st section CD3+ = 0.98 and M2nd section CD3 = 0.81. B + C: Overlap of both images with B (second section stained for CD3) drawn in red and respectively C (first section stained for CD20) drawn in blue. For stained cells, PCC = 0.97, MOC = 0.99 and M2ndsection CD3+ = 0.83 and M1stsection CD20 = 0.97. C + D: Overlap of both images with C (first section stained for CD20) drawn in red and respectively D (second section stained for CD20) drawn in blue. For stained cells, PCC = 0.67, MOC = 0.92 and M1st section CD20+ = 0.57 and M2nd section CD20 = 0.97

Mentions: Analysis of co-localization in serial sections (Fig. 4) stained repeatedly (serially) for CD3 and CD20 (sections CD3 I, CD3 II, CD20 I and CD20 II) showed, that there was a spatial overlap/a co-localization of these markers (Manders coefficients each >0.57). This is against the expectation, since CD3 and CD20 usually are not expressed by one cell. However, a closer look at the images reveals (small insets in Fig. 5), that brown stained areas do co-localize in the images (white arrows in the small insets). Furthermore, from the point of spatial interaction, there is of course an interaction of neighbouring T- and B-cells. Analysing a sketch of a lymphoid follicle composed of B- and T-cells drawn on basis of Fig. 4 carve this point out: In this case there is no overlap of cells but the cells are close neighbours. Therefore MT-cell = 0.34 and MT-cell = 0.67.Fig. 5


On the representation of cells in bone marrow pathology by a scalar field: propagation through serial sections, co-localization and spatial interaction analysis.

Weis CA, Grießmann BW, Scharff C, Detzner C, Pfister E, Marx A, Zoellner FG - Diagn Pathol (2015)

Direct spatial interaction in a lymphoid follicle. Serial sections of a trephine biopsy from a patient with bone marrow lymphocytosis were stained for CD3, CD3, CD20 and CD20 (a-d). Subsequently, slides were fully digitalized, registered and analysed as described. By segmentation, there are 320 CD3+ and 1,156 CD3−/+ nuclei in a, 392 CD3+ and 1,139 CD3−/+ nuclei in b, 316 CD20+ and 1,176 CD20−/+ nuclei in c and respectively 202 CD20+ and 1,182 CD20−/+ nuclei in d. Overlap readings are calculated for direct interaction (RBFdirect). A + B: Overlap of both images with A (first section stained for CD3) drawn in red and respectively B (second section stained for CD3) drawn in blue. For stained cells, PCC = 0.95, MOC = 0.99 and M1st section CD3+ = 0.98 and M2nd section CD3 = 0.81. B + C: Overlap of both images with B (second section stained for CD3) drawn in red and respectively C (first section stained for CD20) drawn in blue. For stained cells, PCC = 0.97, MOC = 0.99 and M2ndsection CD3+ = 0.83 and M1stsection CD20 = 0.97. C + D: Overlap of both images with C (first section stained for CD20) drawn in red and respectively D (second section stained for CD20) drawn in blue. For stained cells, PCC = 0.67, MOC = 0.92 and M1st section CD20+ = 0.57 and M2nd section CD20 = 0.97
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4557224&req=5

Fig5: Direct spatial interaction in a lymphoid follicle. Serial sections of a trephine biopsy from a patient with bone marrow lymphocytosis were stained for CD3, CD3, CD20 and CD20 (a-d). Subsequently, slides were fully digitalized, registered and analysed as described. By segmentation, there are 320 CD3+ and 1,156 CD3−/+ nuclei in a, 392 CD3+ and 1,139 CD3−/+ nuclei in b, 316 CD20+ and 1,176 CD20−/+ nuclei in c and respectively 202 CD20+ and 1,182 CD20−/+ nuclei in d. Overlap readings are calculated for direct interaction (RBFdirect). A + B: Overlap of both images with A (first section stained for CD3) drawn in red and respectively B (second section stained for CD3) drawn in blue. For stained cells, PCC = 0.95, MOC = 0.99 and M1st section CD3+ = 0.98 and M2nd section CD3 = 0.81. B + C: Overlap of both images with B (second section stained for CD3) drawn in red and respectively C (first section stained for CD20) drawn in blue. For stained cells, PCC = 0.97, MOC = 0.99 and M2ndsection CD3+ = 0.83 and M1stsection CD20 = 0.97. C + D: Overlap of both images with C (first section stained for CD20) drawn in red and respectively D (second section stained for CD20) drawn in blue. For stained cells, PCC = 0.67, MOC = 0.92 and M1st section CD20+ = 0.57 and M2nd section CD20 = 0.97
Mentions: Analysis of co-localization in serial sections (Fig. 4) stained repeatedly (serially) for CD3 and CD20 (sections CD3 I, CD3 II, CD20 I and CD20 II) showed, that there was a spatial overlap/a co-localization of these markers (Manders coefficients each >0.57). This is against the expectation, since CD3 and CD20 usually are not expressed by one cell. However, a closer look at the images reveals (small insets in Fig. 5), that brown stained areas do co-localize in the images (white arrows in the small insets). Furthermore, from the point of spatial interaction, there is of course an interaction of neighbouring T- and B-cells. Analysing a sketch of a lymphoid follicle composed of B- and T-cells drawn on basis of Fig. 4 carve this point out: In this case there is no overlap of cells but the cells are close neighbours. Therefore MT-cell = 0.34 and MT-cell = 0.67.Fig. 5

Bottom Line: In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor.Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad).Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

View Article: PubMed Central - PubMed

Affiliation: Institute of Pathology, University Medical Centre Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, 68167, Mannheim, Germany. Cleo-Aron.Weis@medma.uni-heidelberg.de.

ABSTRACT

Background: Immunohistochemical analysis of cellular interactions in the bone marrow in situ is demanding, due to its heterogeneous cellular composition, the poor delineation and overlap of functional compartments and highly complex immunophenotypes of several cell populations (e.g. regulatory T-cells) that require immunohistochemical marker sets for unambiguous characterization. To overcome these difficulties, we herein present an approach to describe objects (e.g. cells, bone trabeculae) by a scalar field that can be propagated through registered images of serial histological sections.

Methods: The transformation of objects within images (e.g. cells) to a scalar field was performed by convolution of the object's centroids with differently formed radial basis function (e.g. for direct or indirect spatial interaction). On the basis of such a scalar field, a summation field described distributed objects within an image.

Results: After image registration i) colocalization analysis could be performed on basis scalar field, which is propagated through registered images, and - due to the shape of the field - were barely prone to matching errors and morphological changes by different cutting levels; ii) furthermore, depending on the field shape the colocalization measurements could also quantify spatial interaction (e.g. direct or paracrine cellular contact); ii) the field-overlap, which represents the spatial distance, of different objects (e.g. two cells) could be calculated by the histogram intersection.

Conclusions: The description of objects (e.g. cells, cell clusters, bone trabeculae etc.) as a field offers several possibilities: First, co-localization of different markers (e.g. by immunohistochemical staining) in serial sections can be performed in an automatic, objective and quantifiable way. In contrast to multicolour staining (e.g. 10-colour immunofluorescence) the financial and technical requirements are fairly minor. Second, the approach allows searching for different types of spatial interactions (e.g. direct and indirect cellular interaction) between objects by taking field shape into account (e.g. thin vs. broad). Third, by describing spatially distributed groups of objects as summation field, it gives cluster definition that relies rather on the bare object distance than on the modelled spatial cellular interaction.

No MeSH data available.


Related in: MedlinePlus