Two statistical approaches to nuclei shape and size in a morphometric description of lymph node sections in non‐Hodgkin's lymphoma

Lesty, Claude; Raphaël, Martine; Nonnenmacher, L.; Binet, Jacques‐Louis

doi:10.1002/cyto.990100106

Cited by 12 publications

(7 citation statements)

References 9 publications

(11 reference statements)

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“…Amongst many other interesting topics, image‐based analysis of nuclear morphometry is a key problem due to the important roles that the cell nucleus plays in biology. Nuclear morphology, and associated changes, have been studied in conjunction with cellular movements (7), cancer (8, 9), Hutchinson‐Gilford progeria (10), as well as gene expression and protein synthesis (11), to name a few.…”

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confidence: 99%

Deformation‐based nuclear morphometry: Capturing nuclear shape variation in HeLa cells

et al. 2007

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The empirical characterization of nuclear shape distributions is an important unsolved problem with many applications in biology and medicine. Numerous genetic diseases and cancers have alterations in nuclear morphology, and methods for characterization of morphology could aid in both diagnoses and fundamental understanding of these disorders. Automated approaches have been used to measure features related to the size and shape of the cell nucleus, and statistical analysis of these features has often been performed assuming an underlying Euclidean (linear) vector space. We discuss the difficulties associated with the analysis of nuclear shape in light of the fact that shape spaces are nonlinear, and demonstrate methods for characterizing nuclear shapes and shape distributions based on spatial transformations that map one nucleus to another. By combining large deformation metric mapping with multidimensional scaling we offer a flexible approach for elucidating the intrinsic nonlinear degrees of freedom of a distribution of nuclear shapes. More specifically, we demonstrate approaches for nuclear shape interpolation and computation of mean nuclear shape. We also provide a method for estimating the number of free parameters that contribute to shape as well as an approach for visualizing most representative shape variations within a distribution of nuclei. The proposed methodology can be completely automated, is independent of the dimensionality of the images, and can handle complex shapes. Results obtained by analyzing two sets of images of HeLa cells are shown. In addition to identifying the modes of variation in normal HeLa nuclei, the effects of lamin A/C on nuclear morphology are quantitatively described. ' 2007 International Society for Analytical Cytology Key terms nuclear morphometry; shape statistics; shape models; image registration COMPUTATIONAL analysis of cellular and subcellular structures aims to provide quantitative information (such as the measurement of physical quantities) that can be used to generate and test hypotheses related to normal and pathological eukaryotic cell characterization. Such studies have long been a major topic of biomedical research (see, for example (1,2)) and advances in microscope image acquisition systems and sophisticated image processing algorithms over the past decade have established computational analysis of cell images as a important component of cell biology research (3-6). Amongst many other interesting topics, image-based analysis of nuclear morphometry is a key problem due to the important roles that the cell nucleus plays in biology. Nuclear morphology, and associated changes, have been studied in conjunction with cellular movements (7), cancer (8,9), Hutchinson-Gilford progeria (10), as well as gene expression and protein synthesis (11), to name a few.Both visual and computational approaches have been applied in characterizing nuclear morphology. For example, nuclear morphology can be visually rated on an objective scale of ''normal'' and ''dysmorphic'' ...

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confidence: 99%

Deformation‐based nuclear morphometry: Capturing nuclear shape variation in HeLa cells

et al. 2007

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“…The acquisition and the recording of GC images were performed when perfect juxtaposition of images from different parts was obtained. Different sizes were obtained: 512 x 512 pixels (4 square images) in 3 cases, 768 x 768 pixels (9 square images) in 13 cases, and 1,024 x 1,024 pixels (16 square images) in 1 case.…”

Section: Methodsmentioning

confidence: 99%

“…Most morphometric analyses have been devoted to cell or nuclei characterization of follicular center cells in reactive FH and SCCFL (13,14,20,21). In contrast to a precise quantitative morphologic description of GCs that individualized a zonal structure, only a few studies have been carried out about quantitative architectural analysis of lymph nodes (4,5).…”

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Germinal center analysis with the tools of mathematical morphology on graphs

et al. 1993

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Only few studies devoted to quantitative analysis of tissue architecture have been performed. The analysis of neighborhood relationships between cells, using graphs and mathematical morphology (MM), constitutes one approach. We propose to analyse quantitatively the architecture of a tissue with the tools of MM on graphs. The use of graphs seems best suited to take into account the neighborhood relationships between cells, independently from their mutual distances: two cells are considered as neighbors if no interfering cell is placed in a given sense between them. Such neighboring cells are linked by an arc in a graph. On such a graph, all tools of MM may be applied. We investigate two of them in the present work: (1) the distance transforms permits to analyse the repartition of a cellular population A relative to population B, (2) the size distribution permits to analyse the tendancy of a cell population to form clusters. We have applied this method using Gabriel's graph, derived from the Voronoï diagram, to determine the “zone of influence” of a cell.We have analysed the neighborhood relationships between cells in germinal centers (GC) from lymph rodes. Twelve hyperplastic GCs from follicular hyperplasia (FH) and 5 neoplastic GCs from small cleaved cell follicular lymphoma (SCCFL) have been studied; 2 m̈m hematoxylin‐eosin plastic embedded sections have been analysed. Cell nuclei have been identified manually by the observer by giving a numerical and image color code. Gabriel's graphs have been constructed with all centrofollicular cells. Subgraphs with only lymphoïd cells, large cells or small cleaved cells have also been studied.The application of MM transformations on the graphs using software package Morphograph has allowed a quantitative description of cell distribution in the tissue. The distances of centrofollicular lymphoïd cells from the periphery of the GCs (mantle zone), from nonlymphoïd cells as macrophages located within the GCs and between large lymphoïd cells and small lymphoïd cells have been determined in FH and SCCFL. Using iterative closings and openings, we have detected aggregates of small and large cells and characterized their size and distribution in the GCs. The application of this method on lymph node biopsy has allowed a quantitative description and comparison of GCs in different pathological conditions. © 1993 Wiley‐Liss, Inc.

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“…Such a computer-assisted assessment of nuclear shapes was previously used on lymphocytes to detect lymphoid neoplasms and on prostatic cells to detect malignant cells (13)(14)(15). Such a computer-assisted assessment of nuclear shapes was previously used on lymphocytes to detect lymphoid neoplasms and on prostatic cells to detect malignant cells (13)(14)(15).…”

Section: Introductionmentioning

confidence: 99%

“…We, therefore, applied a more objective method to characterize neutrophil nuclear lobulation by measuring the perimeter of the nucleus (as an indicator of lobulation) in relation to the nuclear area; the "circularity index." Such a computer-assisted assessment of nuclear shapes was previously used on lymphocytes to detect lymphoid neoplasms and on prostatic cells to detect malignant cells (13)(14)(15). Thus, we compared the two conventional optical classifications of neutrophils with a computer-assisted, morphometric analysis of the nuclear shape.…”

Section: Introductionmentioning

confidence: 99%

Image analysis of neutrophil nuclear morphology: Learning about phenotypic range and its reliable analysis from patients with pelger‐Huët‐anomaly and treated with colchicine

Schnipper

Stassen

Kallinich

et al. 2017

Cytometry Part B Clinical

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The nuclear morphology of neutrophils depends on different endogenous and exogenous factors, which can lead to hypo- or hypersegmentation of the normally 2-4 segmented nucleus. Hyposegmentation can be due to mutations in the LBR-gene (Pelger-Huët-Anomaly) or can be induced, for example, by colchicine treatment. The range of this phenotypic variation is known as "norm of reaction," which can be of major relevance for clinical diagnosis and therapeutic intervention. In this project, we studied the norm of reaction in 26 subjects with 0-3 wild type LBR alleles. In addition, the phenotypic variation was analyzed in 3 patients with Familial Mediterranean Fever (FMF), before and after colchicine treatment. We measured the phenotype nuclear segmentation of neutrophils based on two conventional qualitative methods, the "rule of threads" and the "rule of thirds." In addition, we tested a morphometric quantitative approach, the "circularity index." The circularity index was superior in cases with hyposegmentation; the rule of thirds with respect to hypersegmentation. Approximately 65% of the observed phenotypic variance was explainable by the number of LBR wild type alleles. The gene-dosage effect followed a non-additive, hysteresis-like characteristic with lower and upper plateaus. Colchicine treatment had a clear, although minor phenotypic effect compared to the number of LBR wild type genes or the mutation type. Thus, the nuclear morphology of granulocytes and its norm of reaction can be regarded as an excellent model both for detailing the interplay between endogenous and exogenous factors and for clinical diagnostic purposes. © 2016 International Clinical Cytometry Society.

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Two statistical approaches to nuclei shape and size in a morphometric description of lymph node sections in non‐Hodgkin's lymphoma

Cited by 12 publications

References 9 publications

Deformation‐based nuclear morphometry: Capturing nuclear shape variation in HeLa cells

Deformation‐based nuclear morphometry: Capturing nuclear shape variation in HeLa cells

Germinal center analysis with the tools of mathematical morphology on graphs

Image analysis of neutrophil nuclear morphology: Learning about phenotypic range and its reliable analysis from patients with pelger‐Huët‐anomaly and treated with colchicine

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