Cytomorphologic spectrum in paraganglioma

OBJECTIVE: To study the detailed cytologic features of paragangliomas (PGs) and delineate features helpful in predicting behavior. STUDY DESIGN: We performed retrospective analysis of 12 cases cytologically suggested as PG over a period of 10 years. Smears were reviewed for cellularity, pattern, shape, cytoplasm, nuclear features and background. Cytologic diagnosis was correlated with clinicoradiologic features, histologic features and immunocytochemistry. RESULTS: Patient age ranged from 12 to 65 years, with male preponderance; they presented with a mass lesion. Sites involved were head and neck (5), retroperitoneum (5) and mediastinum (2). Smears were cellular; cells were round to oval, plasmacytoid and spindled and seen as scattered, in clusters, acinar and perivascular pattern. The most consistent feature was presence of pink granules. Pleomorphism was present in all but 1 case and less prominent in tumors with metastasis. Mitoses were more frequently seen in malignant cases. CONCLUSION: Cytologic features of PG are diverse. Although there are certain main features, they are not diagnostic unless combined with data on site, histology and ancillary studies. Presence of granules, mild pleomorphism, frequent mitoses and necrosis needs careful evaluation for malignancy potential and warrants close follow-up.     

Microevolution in MioceneBrizalina (foraminifera) studied by canonical variate analysis and analysis of landmarks

A stratigraphically oriented series of the Miocene foraminiferal speciesBrizalina mandoroveensis from Ikang, Cameroon, was analyzed both by conventional multivariate morphometric procedures and by the tensor biometric method of Bookstein (1986;Statist. Sci. 1, 181–142), a method which analyzes sets of landmark points rather than specific variables of shape or size. The conventional analysis used five size-measures upon 170 specimens from five stratigraphic levels; the tensor analysis encompassed six landmarks (12 coordinates) upon 50 specimens. Whereas certain features appeared in both analyses, such as the separation between levels one and five, the techniques did not always agree with respect to the interpretation of those findings or about most details in the sequence of mean phenotypes. The canonical variate analysis bases its ordination upon a general size factor (the meaning of which is obscured by the foreshortening of within-group variation which is built into the technique). The tensor analysis locates a similar ordination using mainly features of shape.     

Automatic methods for characterization of sexual dimorphism of adult femora: distal femur

Quantifying sex differences in femoral size and shape has extensive applications in forensics and prosthesis design. By applying strong statistical techniques such as principal component analysis (PCA), certain three-dimensional (3D) morphological variations of adult femora can be quantified over various femoral sizes. Coupling this statistical approach with a novel feature generation and extraction technique, localization of statistically significant (p < 0.05) features are automatically defined and measured. Also, predefined anatomical landmarks and surgical axes have been calculated automatically. In all methods, femoral scale is controlled as a possible parameter of shape. By extensively comparing measurements across 92 male and 74 female femora, the dimorphic characteristics of the distal femur are shown. These differences have not been accounted for in many prosthetic systems and consequently these systems have limited sizing accuracy.     

Image Registration Algorithm Using Mexican Hat Function-Based Operator and Grouped Feature Matching Strategy

Feature detection and matching are crucial for robust and reliable image registration. Although many methods have been developed, they commonly focus on only one class of image features. The methods that combine two or more classes of features are still novel and significant. In this work, methods for feature detection and matching are proposed. A Mexican hat function-based operator is used for image feature detection, including the local area detection and the feature point detection. For the local area detection, we use the Mexican hat operator for image filtering, and then the zero-crossing points are extracted and merged into the area borders. For the feature point detection, the Mexican hat operator is performed in scale space to get the key points. After the feature detection, an image registration is achieved by using the two classes of image features. The feature points are grouped according to a standardized region that contains correspondence to the local area, precise registration is achieved eventually by the grouped points. An image transformation matrix is estimated by the feature points in a region and then the best one is chosen through competition of a set of the transformation matrices. This strategy has been named the Grouped Sample Consensus (GCS). The GCS has also ability for removing the outliers effectively. The experimental results show that the proposed algorithm has high registration accuracy and small computational volume.     

Principles and methods of geometric morphometrics

The basic concepts, notions and methods of geometric morphometrics (GM) are considered. This approach implies multivariate analysis of landmark coordinates located following certain rules on the surface of a morphological object. The aim of GM is to reveal differences between morphological objects by their shapes as such, the "size factor" being excluded. The GM is based on the concept of Kendall's space (KS) defined as a hypersphere with points distributed on its surface. These points are the shapes defined as aligned landmark configurations. KS is a non-Euclidian space, its metrics called Procrustes is defined by landmark configuration of a reference shape relative to which other shapes are aligned and compared. The differences among shapes are measured as Procrustes distances between respective points. For the linear methods of multivariate statistics to be applied to comparison of shapes, the respective points are projected onto the tangent plane (tangent space), the tangent point being defined by the reference. There are two principal methods of shape comparisons in GM: the Procrustes superimposition (a version of the least squares analysis) and thin-plate spline analysis. In the first case, Procrustes residuals are the outcome shape variables which remain after isometric alignment of the shapes being compared. Their summation over all landmarks yields Procrustes distances among these shapes. The Procrustes distances can be used in multivariate analyses just as the Euclidian distances. In the second case, the shapes are fitted to the references by stretching/compressing and shearing until complete identity of their landmark configurations. Eigenvectors of resulting bending energy matrix are defined as new shape variables, principal warps which yield another shape space with the origin defined by the reference. Projections of the shapes being compared onto principal warps yield partial warps, and their covariance matrix decomposition into eigenvectors yields relative warps which are similar to principal components (in particular, they are mutually orthogonal). Both partial and relative warps can be used in many multivariate statistic analyses as quantitative shape variables. Results of thin-plate spline analysis can be represented graphically by transformation grid which displays type, amount and localization of the shape differences. Basis rules of sample composition and landmark positioning to be used in GM are considered. At present, rigid (with minimal degrees of freedom) 2D morphological objects are most suitable for GM applications. It is important to recognize three type of real landmarks, and additionally semi-landmarks and "virtual" landmarks. Some procedures of thin-plate spline analysis are considered exemplified by some study cases, as well as applications of some standard multivariate methods to GM results. They make it possible to evaluate correlation between different shapes, as well as between a shape and some non-shape variables (linear measurements etc); to evaluate the differences among organisms by shape of a morphological structure; to identify landmarks which most accounted for both correlation and differences between the shapes. An annotated list of most popular softwares for GM is provided.     

Image analysis of hyperchromatic crowded cell groups in SurePath cervical cytology

Objective: The discrimination of hyperchromatic crowded cell groups (HCCGs) in cervical cytology is a difficult and error‐prone interpretive task. While the classic features of dyskaryosis are of undoubted value, the contribution of size, shape and colour intensity of HCCGs is less certain. This study employed morphometric analysis to determine whether HCCG area, shape and colour intensity are useful in categorising them. Methods: Seventy‐five digital images from each of six categories of HCCG were subjected to image analysis. Ten variables relating to HCCG size, shape and colour intensity were assessed by discriminant function analysis. A further 28 cases were employed as a test set to determine the classification accuracy of the discriminant model. All samples were SurePath liquid‐based cytology preparations. Results: Nine of the 10 variables contributed significantly to the model (P < 0.001) but no single variable had sufficient discriminative ability. Classification accuracy was highest for abnormal endocervical HCCGs and lowest for squamous metaplastic cells (64.0 vs. 17.3% correct classification rate). The accuracy of the model for distinguishing normal and abnormal HCCGs was 70.0%, which was significantly higher than chance (P < 0.0001), but this reduced to 64.3% for the test cases, which was no better than chance (P > 0.05). Conclusions: The area, shape and colour intensity of HCCGs, either alone or in combination, have little discriminative value. Practitioners and trainers should focus on the well‐established features of dyskaryosis, such as chromatin pattern, nuclear membrane irregularities and group architecture. In terms of morphometric analysis, DNA ploidy and chromatin texture analysis may be more fruitful avenues of investigation.     

Testing the success of palaeontological methods in the delimitation of clam shrimp (Crustacea,Branchiopoda) on extant species

Fossil spinicaudatan taxonomy heavily relies on carapace features (size, shape, ornamentation) and palaeontologists have greatly refined methods to study and describe carapace variability. Whether carapace features alone are sufficient for distinguishing between species of a single genus has remained untested. In our study, we tested common palaeontological methods on 481 individuals of the extant Australian genus Ozestheria that have been previously assigned to ten species based on genetic analysis. All species are morphologically distinct based on geometric morphometrics (p ≤ 0.001), but they occupy overlapping regions in Ozestheria morphospace. Linear discriminant analysis of Fourier shape coefficients reaches a mean model performance of 93.8% correctly classified individuals over all possible 45 pairwise species comparisons. This can be further increased by combining the size and shape datasets. Nine of the ten examined species are clearly sexually dimorphic but male and female morphologies strongly overlap within species with little influence on model performance. Ornamentation is commonly species-diagnostic; seven ornamentation types are distinguished of which six are species-specific while one is shared by four species. A transformation of main ornamental features (e.g. from punctate to smooth) can occur among closely related species suggesting short evolutionary timescales. Our overall results support the taxonomic value of carapace features, which should also receive greater attention in the taxonomy of extant species. The extensive variation in carapace shape and ornamentation is noteworthy and several species would probably have been assigned to different genera or families if these had been fossils, bearing implications for the systematics of fossil Spinicaudata.     

Automatic methods for characterization of sexual dimorphism of adult femora: distal femur

Quantifying sex differences in femoral size and shape has extensive applications in forensics and prosthesis design. By applying strong statistical techniques such as principal component analysis (PCA), certain three-dimensional (3D) morphological variations of adult femora can be quantified over various femoral sizes. Coupling this statistical approach with a novel feature generation and extraction technique, localization of statistically significant (p<0.05) features are automatically defined and measured. Also, predefined anatomical landmarks and surgical axes have been calculated automatically. In all methods, femoral scale is controlled as a possible parameter of shape. By extensively comparing measurements across 92 male and 74 female femora, the dimorphic characteristics of the distal femur are shown. These differences have not been accounted for in many prosthetic systems and consequently these systems have limited sizing accuracy.     

Automated and customizable quantitative image analysis of whole Caenorhabditis elegans germlines

Arranged in a spatial-temporal gradient for germ cell development, the adult germline of Caenorhabditis elegans is an excellent system for understanding the generation, differentiation, function, and maintenance of germ cells. Imaging whole C. elegans germlines along the distal-proximal axis enables powerful cytological analyses of germ cell nuclei as they progress from the pre-meiotic tip through all the stages of meiotic prophase I. To enable high-content image analysis of whole C. elegans gonads, we developed a custom algorithm and pipelines to function with image processing software that enables: (1) quantification of cytological features at single nucleus resolution from immunofluorescence images; and (2) assessment of these individual nuclei based on their position within the germline. We show the capability of our quantitative image analysis approach by analyzing multiple cytological features of meiotic nuclei in whole C. elegans germlines. First, we quantify double-strand DNA breaks (DSBs) per nucleus by analyzing DNA-associated foci of the recombinase RAD-51 at single-nucleus resolution in the context of whole germline progression. Second, we quantify the DSBs that are licensed for crossover repair by analyzing foci of MSH-5 and COSA-1 when they associate with the synaptonemal complex during meiotic prophase progression. Finally, we quantify P-granule composition across the whole germline by analyzing the colocalization of PGL-1 and ZNFX-1 foci. Our image analysis pipeline is an adaptable and useful method for researchers spanning multiple fields using the C. elegans germline as a model system.     

Algorithm to estimate cell biovolume using image analyzed microscopy

This paper describes an algorithm for calculating the biovolume of cells with simple shapes, such as bacteria, flagellates, and simple ciliates, from a 2-dimensional digital image. The method can be adapted to any image analysis system which allows access to the binary cell image--(i.e., the pixels, or (x,y) points, composing the cell. The cell image is rotated to a standard orientation (horizontal), and a solid of revolution is calculated by digital integration. Verification and a critical assessment of the method are presented. The algorithm accounts for irregularities in cell shape that conventional methods based on length, width, and geometrical formulas do not.     

Quantification of immunohistochemistry using an image analyser: correlation with hormone concentrations in pituitary adenomas

Summary The usefulness of immunohistochemistry is usually confined to qualitative analysis. Quantitative evaluation is not performed. At best, the number of immunopositive cells and the immunointensities are recorded as several grades, to which a strict categorization may be applied by individual examiners, but these categorizations are not standardized. We have attempted to quantify immunohistochemical observations using an image analyser. Sections from rat pituitary adenomas secreting prolactin and growth hormone were immunostained for these hormones with either immunogold silver or avidin-biotinylated peroxidase complex (ABC) methods. The number of immunopositive cells were counted by eye on specimens stained with the ABC method. In sections stained by an immunogold-silver technique, an immunopositive area was measured at several immunointensity ranges, to which certain points were allotted. Immunohistochemical values obtained by summing the products of the immunopositive area and intensity points at each range were correlated with concentrations of hormones in adenoma tissues measured by radioimmunoassay. A high correlation between the immunohistochemical values and hormone concentrations were shown for both prolactin and growth hormone, in contrast to a low correlation between the number of immunopositive cells counted by eye and the hormone concentrations. These findings indicate that the immunohistochemical observations can be quantified using the image analyser to the extent that they can be substituted, albeit roughly, for the hormone concentrations measured biochemically.     

Influence of cell cycle synchronization on digital image analysis of HL-60 granulopoiesis.

Retinoic acid (RA)-treated HL-60 cells subjected to density arrest (DA) and double thymidine block (TB) synchronization demonstrated image feature changes associated with cellular proliferation and differentiation. RA-treated TB cells demonstrated an increased level of morphologic differentiation (assessed by differential counts and quantitation of nuclear shape) and more rapid functional differentiation (assessed by superoxide production and expression of complement receptors) than RA-treated DA cells. By comparison to DA cells, TB cells had less variation in virtually all image features values. A Kruskal-Wallis test of image features ranked total optical density (TOD) of Feulgen-stained cells, nuclear area and shape factor as the top three features regardless of synchronization method. Statistically significant changes in image feature values of RA-treated cells were first noted on day 1. The computer-assisted ability to discriminate RA-treated cells on a given day after induction from paired controls by means of an unsupervised learning algorithm increased over a seven-day period for both DA and TB cells. However, in the dichotomous (RA-treated versus untreated) classification scheme employed, which did not account for continuous levels of morphologic differentiation, there was no advantage in the use of the TB over DA procedure.     

An Integrated Approach for Landmark-Based Resistant Shape Analysis in 3D

The study of shape changes in morphology has seen a significant renovation in the last 20 years, particularly as a consequence of the development of geometric morphometric methods based on Cartesian coordinates of points. In order to extract information about shape differences when Cartesian coordinates are used, it is necessary to establish a common reference frame or system for all specimens to be compared. Therefore, a central issue in coordinate-based methods is which criterion should be used to align these configurations of points, since shape differences highly depend on those alignments. This is usually accomplished by aligning the configurations in a way that the sum of squared distances between coordinates of homologous points (landmarks) is minimized: the least-squares superimposition method. However, it is widely recognized that this method has some limitations when shape differences are not homogeneous across landmarks. Here we present an integrated approach for the resistant shape comparison of 3D landmark sets. It includes a new ordinary resistant Procrustes superimposition and its corresponding generalized resistant Procrustes version. In addition, they are combined with existing resistant multivariate statistical techniques for depicting the results. We demonstrate, by using both simulated and real datasets, that resistant Procrustes better detects and measures localized shape variation whenever present in up to half but one of the landmarks. The resistant Procrustes results are highly concordant with a priori biological information, and might dramatically improve the quality of inferences on patterns of shape variation.     

The singularities of the visual mapping

In this article we treat purely metrical properties of the visual image, e.g. the time changes of the relative positions and orientations of image details. Self-induced movements of an observer relative to rigid bodies in his environment generate charactertistic motion parallax fields. The observer may regard those fields as proprioceptive and interprete the geometrical invariants of the fields as indicators of solid shape. In this way his perceptions become object-oriented, which is the normal case as the many constancy-phenomena show. Similar arguments apply to the disparity field of binocular vision. In this paper we treat the qualitative nature of such fields. [In this case the qualitative nature is basic. Compare the case of an equation with a single unknown. Often one is interested primarily in the qualitative solution (are there roots? How many?), and only slightly in the quantitative information (the numerical value of a root).] The qualitative nature of the fields is fixed if their singularities are known. It is shown that the singularities are of two types: isolated points (so-called specular points) and line-singularities (so-called folds, cusps and T-junctions). It is shown that for most vantage points that an observer can occupy, the topological structure of the set of singularities does not change if the observer performs small exploratory movements. That is most vantage points are stable. At an unstable vantage point the set of singularities changes and the observer experiences an event. Because certain properties of the set of singularities are shown to be preserved, only a few simple types of event are possible. A complete list is presented. The occurrence of an event is shown to be simply related to the solid shape of the objects of vision. Our geometrical theory enables us to understand the structure of the observer's internal models of external bodies.     

Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties

Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D imaging and quantification are crucial for proper understanding of mitochondrial shape and topology in non-flat cells. In summary, we here present an integrative method for unbiased 3D quantification of mitochondrial shape and network properties in mammalian cells.     

The Positioning of Ciliary Organelles in Hypotrich Ciliates*†

It is commonly observed in hypotrichs that new ciliary rudiments arise directly from or in close juxtaposition to certain pre-existing ciliary elements. Oral primordia often are initiated near specific cirri, cirral rudiments frequently arise as a result of the disaggregation of certain old cirri, and new dorsal ciliature is formed within pre-existing ciliary rows. In the first 2 situations it has been demonstrated experimentally that neither the old ciliature in question nor the specific cortical site marked by that ciliature is essential for the appearance of the new cirral rudiment. The experimental analysis done thus far suggests that the positions of oral and cirral primordia are determined by interacting gradients established in relation to certain reference points. The nature of the reference points is not fully elucidated; in some cases at least these points appear to be more closely related to topographic features of the cell than to specific pre-existing cortical structures. In the dorsal ciliary rows of Euplotes new ciliary units are formed usually and perhaps invariably in close proximity to old ones, and are generally oriented along the axis of the pre-existing row. The result is a tendency to perpetuate the preexisting row number across cell generations. Changes in row number, however, can occur as a result of occasional formation of new units at right angles to the row, a process that is much enhanced in certain homozygous segregants (basal body deficient). The optimal row number (stability range) as well as the number of ciliary units are under genic control. In addition, the spatial pattern of distribution of ciliary units among rows is invariant in all of the material examined. This pattern is presumed to result from an underlying field whose geometry is independent of both the number of units and the number of rows.     

Body shape variation in the Characid Psalidodon rivularis from São Francisco river,Southeast Brazil (Characiformes: Stethaprioninae)

Psalidodon rivularis is a species of tetra endemic to the São Francisco River basin and, based on cytogenetic and molecular studies, represents a complex of species. The objective of the present work was to identify morphological differences in the body shape of seven populations of P. rivularis from the Upper and Middle São Francisco River basin through geometric morphometry. In all, we photographed 174 individuals on the right side of the body and 17 landmarks were digitized on each image. To study the effects of allometry on the shape, we performed regression analysis and, to study shape modulation at different collection points and sub-basins, the canonical variation analyses. We found differences in shape between collection points and sub-basins associated with relative body height and sub-orbital plate recoil, in addition to a significant influence of size on specimen shape (allometry) associated with the ventral skull, orbits and sub-orbital plate. We do not envision differences in body shape between males and females. Several works with fish relate body height with water velocity, while the sub-orbital plate recoil shows a taxonomic or ecological potential, marking the main difference between the populations of the Upper and Middle São Francisco River.