Classifying prostate cancer malignancy by quantitative histomorphometry.

PURPOSE: Prostate cancer is routinely graded according to the Gleason grading scheme. This scheme is predominantly based on the textural appearance of aberrant glandular structures. Gleason grade is difficult to standardize and often leads to discussion due to interrater and intrarater disagreement. Thus, we investigated whether digital image based automated quantitative histomorphometry could be used to achieve a more standardized, reproducible classification outcome. MATERIALS AND METHODS: In a proof of principle study we developed a method to evaluate digitized histological images of single prostate cancer regions in hematoxylin and eosin stained sections. Preprocessed color images were subjected to color deconvolution, followed by the binarization of obtained hematoxylin related image channels. Highlighted neoplastic epithelial gland related objects were morphometrically assessed by a classifier based on 2 calculated quantitative and objective geometric measures, that is inverse solidity and inverse compactness. The procedure was then applied to the prostate cancer probes of 125 patients. Each probe was independently classified for Gleason grade 3, 4 or 5 by an experienced pathologist blinded to image analysis outcome. RESULTS: Together inverse compactness and inverse solidity were adequate discriminatory features for a powerful classifier that distinguished Gleason grade 3 from grade 4/5 histology. The classifier was robust on sensitivity analysis. CONCLUSIONS: Results suggest that quantitative and interpretable measures can be obtained from image based analysis, permitting algorithmic differentiation of prostate Gleason grades. The method must be validated in a large independent series of specimens.

Image-processing chain for a three-dimensional reconstruction of basal cell carcinomas.

Basal cell carcinoma (BCC) is the most common malignant skin cancer. For a deeper insight into the specific growth patterns of the tumorous tissue in BCC, we have focused on the development of a novel automated image-processing chain for 3D reconstruction of BCC using histopathological serial sections. For fully automatic delineation of the tumor within the tissue, we apply a fuzzy c-means segmentation method. We used a novel multi-grid form of the non-linear registration introduced by Braumann and Kuska in 2005 effectively suppressing registration runs into local minima (possibly caused by diffuse nature of the tumor). Our method was successfully applied in a proof-of-principle study for automated reconstruction.

Characteristic quantities of microvascular structures in CLSM volume datasets.

A method for fully automated morphological and topological quantification of microvascular structures in confocal laser scanning microscopy (CLSM) volume datasets is presented. Several characteristic morphological and topological quantities are calculated in a series of image-processing steps and can be used to compare single components as well as whole networks of microvascular structures to each other. The effect of the individual image-processing steps is illustrated and characteristic quantities of measured volume datasets are presented and discussed.

Evaluation of the invasion front pattern of squamous cell cervical carcinoma by measuring classical and discrete compactness.

The invasion front pattern of squamous cell carcinoma (SCC) is a conspicuous histological phenomenon, which is assessed without precise criteria. The current study was performed to introduce the classical (C(C)) and discrete compactness (C(D)) as new morphometric parameters for quantification of this pattern. A retrospective analysis of 76 surgically treated patients with cervical carcinoma was conducted and the pattern of invasion was qualitatively classified as closed, finger-like or diffuse, respectively, by two pathologists. After digitization of the histological slides with a field of view of 10.4 mm x 8.3mm, tumor areas were labeled and C(C) and C(D) were computed based on the drawings (binary images). Additionally, intraindividual variation of compactness was evaluated for 12 selected tumors. The qualitative pattern assessment by the pathologists was moderately reproducible with an interobserver agreement of 72% and a kappa coefficient of 0.44. The values of C(C) and C(D) referring to the invasion front patterns assigned by both pathologists were significantly different between the three classified groups (p< or =0.01 and p< or =0.0001), so that, both theoretically and in practice, compactness regards the same morphological feature. In due consideration of the analysis of the area under the ROC (receiver operating characteristic) curves and the variation coefficient of different tumor regions, C(D) is more suitable for practical use than C(C). Tumors with a microscopic invasion into the parametria and with lymph-vascular space invasion were found to have a lower value of C(D), which indicates a more diffuse pattern of invasion (p=0.028 and p=0.033). We conclude that the discrete compactness C(D) is a new and reproducible parameter for a computer assisted quantification of the invasion front pattern and, thus, defines a further phenotypic feature of SCC of the uterine cervix.

Three-dimensional reconstruction and quantification of cervical carcinoma invasion fronts from histological serial sections.

The analysis of the three-dimensional (3-D) structure of tumoral invasion fronts of carcinoma of the uterine cervix is the prerequisite for understanding their architectural-functional relationship. The variation range of the invasion patterns known so far reaches from a smooth tumor-host boundary surface to more diffusely spreading patterns, which all are supposed to have a different prognostic relevance. As a very decisive limitation of previous studies, all morphological assessments just could be done verbally referring to single histological sections. Therefore, the intention of this paper is to get an objective quantification of tumor invasion based on 3-D reconstructed tumoral tissue data. The image processing chain introduced here is capable to reconstruct selected parts of tumor invasion fronts from histological serial sections of remarkable extent (90-500 slices). While potentially gaining good accuracy and reasonably high resolution, microtome cutting of large serial sections especially may induce severe artifacts like distortions, folds, fissures or gaps. Starting from stacks of digitized transmitted light color images, an overall of three registration steps are the main parts of the presented algorithm. By this, we achieved the most detailed 3-D reconstruction of the invasion of solid tumors so far. Once reconstructed, the invasion front of the segmented tumor is quantified using discrete compactness.

Quantitative analysis of astrogliosis in drug-dependent humans.

Drug addiction is a chronic, relapsing disease caused by neurochemical and molecular changes in the brain. In this human autopsy study qualitative and quantitative changes of glial fibrillary acidic protein (GFAP)-positive astrocytes in the hippocampus of 26 lethally intoxicated drug addicts and 35 matched controls are described. The morphological characterization of these cells reflected alterations representative for astrogliosis. But, neither quantification of GFAP-positive cells nor the Western blot analysis indicated statistical significant differences between drug fatalities versus controls. However, by semi-quantitative scoring a significant shift towards higher numbers of activated astrocytes in the drug group was detected. To assess morphological changes quantitatively, graph-based representations of astrocyte morphology were obtained from single cell images captured by confocal laser scanning microscopy. Their underlying structures were used to quantify changes in astroglial fibers in an automated fashion. This morphometric analysis yielded significant differences between the investigated groups for four different measures of fiber characteristics (Euclidean distance, graph distance, number of graph elements, fiber skeleton distance), indicating that, e.g., astrocytes in drug addicts on average exhibit significant elongation of fiber structures as well as two-fold increase in GFAP-positive fibers as compared with those in controls. In conclusion, the present data show characteristic differences in morphology of hippocampal astrocytes in drug addicts versus controls and further supports the involvement of astrocytes in human pathophysiology of drug addiction. The automated quantification of astrocyte morphologies provides a novel, testable way to assess the fiber structures in a quantitative manner as opposed to standard, qualitative descriptions.

Spatial organization of mesenchymal stem cells in vitro--results from a new individual cell-based model with podia.

Therapeutic application of mesenchymal stem cells (MSC) requires their extensive in vitro expansion. MSC in culture typically grow to confluence within a few weeks. They show spindle-shaped fibroblastoid morphology and align to each other in characteristic spatial patterns at high cell density. We present an individual cell-based model (IBM) that is able to quantitatively describe the spatio-temporal organization of MSC in culture. Our model substantially improves on previous models by explicitly representing cell podia and their dynamics. It employs podia-generated forces for cell movement and adjusts cell behavior in response to cell density. At the same time, it is simple enough to simulate thousands of cells with reasonable computational effort. Experimental sheep MSC cultures were monitored under standard conditions. Automated image analysis was used to determine the location and orientation of individual cells. Our simulations quantitatively reproduced the observed growth dynamics and cell-cell alignment assuming cell density-dependent proliferation, migration, and morphology. In addition to cell growth on plain substrates our model captured cell alignment on micro-structured surfaces. We propose a specific surface micro-structure that according to our simulations can substantially enlarge cell culture harvest. The 'tool box' of cell migratory behavior newly introduced in this study significantly enhances the bandwidth of IBM. Our approach is capable of accommodating individual cell behavior and collective cell dynamics of a variety of cell types and tissues in computational systems biology.

PROCESS FLOW FOR CLASSIFICATION AND CLUSTERING OF FRUIT FLY GENE EXPRESSION PATTERNS.

The rapidly growing collection of fruit fly embryo images makes automated Image Segmentation and classification an indispensable requirement for a large-scale analysis of in situ hybridization (ISH) - gene expression patterns (GEP). We present here such an automated process flow for Segmenting, Classification, and Clustering large-scale sets of Drosophila melanogaster GEP that is capable of dealing with most of the complications implicated in the images.

3-D analysis of the invasion front in squamous cell carcinoma of the uterine cervix: histopathologic evidence for collective invasion per continuitatem.

OBJECTIVE: To investigate spatial tumor invasion using ex vivo specimens and pursue a new morphometric approach for a quantitative assessment of the invasion front. STUDY DESIGN: Based on histologic serial sections with up to 500 slices stained with hematoxylin-eosin, volumes of interest of the tumor invasion front were 3-D reconstructed for 13 specimens from patients with squamous cell carcinoma (SCC) of the uterine cervix. Starting from very sensitive automatic tumor segmentation, 404 presumptive loci of isolated tumor islets were detected within the reconstructed volume data sets. These loci were microscopically inspected on the slides utilizing the volume date set's coordinates. RESULTS: A single detached tumor cell cluster within the stroma could be verified and, additionally, 4 tumor emboli within lymph vessels. The main cause of all other suspect islets (false positive segmentations) was peritumoral inflammatory response. Spatial invasion front quantification was done using discrete compactness (3-D C(D)). A comparison with 2-D C(D) values from single slides yielded strong correlation (correlation coefficient: r = 0.94; p < 0.001). CONCLUSION: Collective migration in SCC of the cervix mainly occurs per continuitatem. 2-D C(D) appears adequate and applicable for the morphometry of tumor invasion front phenotypes.

Combined serial section-based 3D reconstruction of cervical carcinoma invasion using H&E/p16INK4a/CD3 alternate staining.

BACKGROUND: Malignant growth and invasiveness of cancers is a function of both intratumoral and stromal factors. The accessibility to nutrients, oxygen and growth factors, the stromal composition, and the interference with the immune system all shape the tumor invasion front. A recent study has shown a prognostic difference with respect to different invasion patterns analyzed on histological specimens of cervical cancers. The present study analyzes the spatial organization of a cervical cancer and the relation of the tumor invasion front and the infiltration with CD3(+) T-cells. METHODS: From a cervical squamous cell carcinoma specimen, 84 serial sections were performed and three interleaving series were stained with hematoxylin/eosin and immunohistochemistry directed against the cervical carcinoma biomarker p16(INK4a) and the T-cell marker CD3. Sections were passed through an image processing chain to obtain a reconstructed and segmented tissue volume. For local tumor invasion front analysis the mean curvature was used, which in turn was related to the respective local minimum tumor to T-cell distance as well to a T-cell originated diffusing substance's concentration at the tumor surface. RESULTS: Spatial models of the tumor tissue and the infiltrating T-cells were computed. The overall discrete compactness of the tumor invasion front was 0.89, corresponding to a pathological assessment of diffuse infiltration. The comparison of the tumor invasion front with the density of T-cell infiltration revealed an increased smoothening in regions with high T-cell infiltration. CONCLUSIONS: We could demonstrate the spatial organization of a cervical cancer and model the interaction between infiltrating T-cells with the tumor invasion front shape. Increased smoothening in regions with high T-cell infiltration suggests that T-cells may have an influence on the shaping of the tumor invasion front, e.g., by attacking tumor cells displaying specific antigens. The applied technique allows visualization of the spatial organization of tissues and could be extended to analyze multiple stains on alternating sections.