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PubMed1993

An image analysis workstation for the pathology laboratory.

Computer-based image analysis (IA) is a technology gaining importance in diagnostic pathology. Applications of IA in pathology include DNA ploidy analysis, quantitative immunohistochemistry, three-dimensional reconstruction of tissue sections, motility studies, and chromosomal analysis. Morphometry, the quantitative measurement of size, shape, and textural features of cells and tissues, is another rapidly developing area of IA in pathology. Morphometric IA allows the objective evaluation of subtle histologic and cytologic features to yield useful diagnostic and prognostic information. Research is currently underway to develop diagnostically useful applications of morphometric IA. Several image analysis workstations designed for the pathology laboratory are currently available. However, the high cost and software inflexibility of these instruments are prohibitive to many potential users limiting the practicality of IA and hindering research. We present a relatively inexpensive pathology IA workstation assembled from commercially available hardware and software components. System features and basic image processing methods are described. A variety of practical applications for the surgical pathology laboratory are illustrated, including spatial measurements of tumors, nerve and muscle biopsy evaluation, and nuclear morphometry for classification of lymphoid effusions and hepatocellular carcinoma.

Biopsy↗

PubMed2004

Aerodynamics, voice quality, and laryngeal image analysis of normal and pathologic voices.

PURPOSE OF REVIEW: The purpose of this review is to describe examinations of phonatory function and their relation to image analysis of the unilaterally immobile larynx. Special emphasis was placed on image analysis using three-dimensional endoscopic images produced from CT scans. RECENT FINDINGS: Developments in modern image processing technique have led to the quantification of various aspects of vocal fold vibration. Stroboscopic images of the vocal fold were digitized and, subsequently, the glottal gap area, amplitude, and degree of bowing were analyzed quantitatively in relation to phonatory function. Vocal fold vibration was observed with the aid of videokymography, during which images from a single transverse line can be recorded. Successive line images were shown in real time on a monitor, with the time dimension displayed in the vertical direction. This system enabled the assessment of left-right asymmetries, open quotient, propagation of mucosal waves, and forth. Three-dimensional endoscopic images derived from multislice CT scans provided a novel method for evaluating morphologic characteristics of the laryngeal lumen in relation to phonatory function. The combination of three-dimensional endoscopy and coronal reconstructed images supplemented stroboscopic findings exemplified by differences in vertical position and thickness between the vocal folds. SUMMARY: Depth information about the vocal fold as well as the presence of paradoxic movement of the affected vocal fold and overadduction of the healthy vocal fold during phonation should be taken into account when surgical intervention to improve hoarseness resulting from unilateral vocal fold immobility is performed. Phonatory function tests, videostroboscopy, and laryngeal image analysis are prerequisites to achieving this goal.

Humans↗

PubMed2002

Glucocorticoid induced impairment of lung structure assessed by digital image analysis.

UNLABELLED: Glucocorticoids (GC) are successfully applied in neonatology to improve lung maturation in preterm born babies. Animal studies show that GC can also impair lung development. In this investigation, we used a new approach based on digital image analysis. Microscopic images of lung parenchyma were skeletonised and the geometrical properties of the septal network characterised by analysing the 'skeletal' parameters. Inhibition of the process of alveolarisation after extensive administration of small doses of GC in newborn rats was confirmed by significant changes in the 'skeletal' parameters. The induced structural changes in the lung parenchyma were still present after 60 days in adult rats, clearly indicating a long lasting or even definitive impairment of lung development and maturation caused by GC. CONCLUSION: digital image analysis and skeletonisation proved to be a highly suited approach to assess structural changes in lung parenchyma.

Age Factors↗

PubMed1994

Physical mapping of chromosome 17 cosmids by fluorescence in situ hybridization and digital image analysis.

We used fluorescence in situ hybridization and digital image analysis to localize cosmids along human chromosome 17. Seventy-one cosmids were selected at random from a chromosome 17 library constructed from a partial Sau3AI digest of flow-sorted chromosomes from a mouse-human hybrid cell line. Sixty-three of these (89%) gave a signal only on chromosome 17. The 40 cosmids producing the most distinct hybridization signals in metaphase and interphase cells were precisely mapped using digital image analysis. An additional 20 cosmids, previously mapped by linkage analysis, were also mapped. The order of these probes determined by metaphase mapping was consistent with the order determined by linkage analysis.

Chromosome Mapping↗

PubMed2002

Image analysis and morphometry in the diagnosis of breast cancer.

Image Analysis, a complicated field still in the early stages of application to Pathology, has the capability of rendering major contributions to the diagnosis, prognosis, and management of malignancies of the breast. The present review summarizes the main problems and the general approach to the use of this technique for quantitating immunohistochemical stain results, obtaining DNA histograms, and making de novo diagnoses in routine materials of the Pathology service. In the case of diagnosis, the main steps are sampling, segmentation, and measures of chromatin texture. Currently, the limiting factor for all routine applications of image analysis is probably the absence of a reliable automatic nuclear segmentation.

Breast Neoplasms↗

PubMed2006

[Comparation on Haversian system between human and animal bones by imaging analysis].

OBJECTIVE: To explore the differences in Haversian system between human and animal bones through imaging analysis and morphology description. METHODS: Thirty-five slices grinding from human being as well as dog, pig, cow and sheep bones were observed to compare their structure, then were analysed with the researchful microscope. RESULTS: Plexiform bone or oeston band was not found in human bones; There were significant differences in the shape, size, location, density of Haversian system, between human and animal bones. The amount of Haversian lamella and diameter of central canal in human were the biggest; Significant differences in the central canal diameter and total area percentage between human and animal bones were shown by imaging analysis. CONCLUSION: (1) Plexiform bone and osteon band could be the exclusive index in human bone; (2) There were significant differences in the structure of Haversian system between human and animal bones; (3) The percentage of central canals total area was valuable in species identification through imaging analysis.

Adult↗

PubMed2003

Diagnostic tissue elements in melanocytic skin tumors in automated image analysis.

In tissue counter analysis, digital images are divided into subregions (elements), and the digital information in each element is used for statistical analysis. In this study, we assessed the morphologic details of tissue elements that have turned out to be of diagnostic significance in the discrimination of benign common nevi and malignant melanoma. After creation of a data set based on a total of 12,000 cellular elements obtained from 100 benign common nevi and 100 malignant melanomas, classification and regression tree (CART) analysis was performed to differentiate between cellular elements of nevi and melanoma. In a second step, the slides were re-evaluated by the decision tree; cellular elements suggestive either for benign common nevi or for malignant melanoma were highlighted on zoomed images of the whole sections, and the individual elements were displayed in galleries. Eight groups of elements (so-called terminal nodes) seemed to indicate benign common nevi, whereas seven terminal nodes were suggestive for malignant melanoma. The elements of nodes suggestive for benign nevi largely contained nevus cells with amphiphilic cytoplasm intermingled with fibrillary material, whereas the elements of the nodes suggestive for malignant lesions often showed hyperchromatism, perinuclear halos, heavy pigmentation, or a lymphohistiocytic infiltrate. Tissue counter analysis automatically detects tissue elements that are in accordance with morphologic criteria used in conventional histopathology for diagnostic discrimination.

Biopsy↗

PubMed1997

Quantitation of cell-matrix adhesion using confocal image analysis of focal contact associated proteins and interference reflection microscopy.

We have developed an approach for the quantitation of vinculin, a focal contact associated protein, based on a multimodal confocal microscopy and image analysis. Vinculin spot distribution was imaged in confocal fluorescence microscopy and the corresponding focal contacts were imaged in confocal interference reflection microscopy. These images were analyzed with a SAMBA image cytometer. The image analysis program provided 12 morphometric features describing cellular area, shape, and proportions of vinculin spots as well as six topographical features describing the distribution of vinculin and the relative overlap of vinculin and focal contacts. This approach was applied to the study of rat osteosarcoma cells submitted to mechanical stresses: successions of 2g and 0g accelerations during a series of parabolic flights. The measured features were assessed by means of correlation analysis and stepwise discriminant analysis. After correlation analysis, only ten parameters were retained. Quantitation of cell morphological parameters indicated that cell area was significantly affected by gravitational stresses as well as vinculin distribution. Cell area was reduced by 50% and vinculin spots were restricted to cell periphery. Cell adhesion measured by IRM decreased significantly in the first part of the flight and remained stable at the end of the flight. These results suggest that cell-matrix adhesion is affected by gravitational stresses. Image analysis provides useful tools to investigate focal adhesion re-organization under different physiological stimuli.

Animals↗

PubMed2001

Image analysis and quantification in lung tissue.

On 9-10 September 1999, an international workshop on image analysis and quantification in lung tissue was held at the Leiden University Medical Center, Leiden, The Netherlands. Participants with expertise in pulmonary and/or pathology research discussed the validity and applicability of techniques used for quantitative examination of inflammatory cell patterns and gene expression in bronchial or parenchymal tissue in studies focusing on asthma and chronic obstructive pulmonary disease (COPD). Differences in techniques for tissue sampling and processing, immunohistochemistry, cell counting and densitometry are hampering the comparison of data between various laboratories. The main goals of the workshop were to make an inventory of the techniques that are currently available for each of these aspects, and in particular to address the validity and unresolved problems of using digital image analysis (DIA) as opposed to manual scoring methods for cell counting and assessment of gene and protein expression. Obviously, tissue sampling and handling, fixation and (immunohistochemical) staining, and microscope settings, are having a large impact on any quantitative analysis. In addition, careful choices will have to be made of the commercially available optical and recording systems as well as the application software in order to optimize quantitative DIA. Finally, it appears to be of equal importance to reach consensus on which histological areas are to be analysed. The current proceedings highlight recent advances and state of the art knowledge on digital image analysis for lung tissue, and summarize the established issues and remaining questions raised during the course of the workshop.

Animals↗

PubMed2000

Quantification of angiogenesis by a computerized image analysis system in renal cell carcinoma.

OBJECTIVE: To ascertain whether tumor angiogenesis quantitated by a computerized image analysis system correlates with clinical outcome in renal cell carcinoma. STUDY DESIGN: Microvessels were immunohistochemically labeled with antibodies to CD34 in sections from 62 cases of renal cell carcinoma. Computerized image analysis was used to evaluate the mean microvessel count (MMC) and mean percentage microvessel area (MPMA). RESULTS: MMC ranged from 19.3 to 315.0, while MPMA was 0.6-17.9%. There was a highly significant correlation between MMC and MPMA (r = .867, P < .01). Although MMC and MPMA decreased with increasing nuclear grade and TNM stage, this difference failed to achieve statistical significance. No statistically significant differences in survival were found for MMC or MPMA. CONCLUSION: Our results indicate that computerized image analysis can evaluate accurately tumor angiogenesis, but tumor angiogenesis in renal cell carcinoma does not provide significant prognostic information in renal cell carcinoma.

Adult↗

PubMed1993

A study of hepatocellular carcinoma using morphometric and densitometric image analysis.

Hepatocellular carcinoma is often difficult to diagnose in cytologic material and biopsy specimens. To demonstrate the utility of image analysis in discriminating benign and malignant hepatocytes, 42 malignant cell groups were compared with 26 benign cell groups with a wide range of nuclear morphology in hematoxylin and eosin-stained histologic sections from 42 patients with hepatocellular carcinoma. Nuclear measurements were performed with a relatively inexpensive microcomputer-based image analysis system using a highly flexible imaging software package. Twenty-two nuclear morphometric and densitometric parameters were evaluated. The best single discriminator of benign and malignant cells was the nuclear major axis. Classification of the test samples using optimized linear discriminant functions achieved the following positive predictive values (PV+) and negative predictive values (PV-) for hepatocellular carcinoma: 95.0% PV+ and 85.7% PV- for the major axis; 90.5% PV+ and 84.6% PV- for five densitometric parameters; 100% PV+ and 86.7% PV- for three morphometric parameters; and 95.5% PV+ and 100% PV- for nine combined morphometric/densitometric parameters. These results demonstrate that multivariate linear discriminant functions of nuclear features measured by image analysis can be used to classify benign and malignant hepatocytes accurately.

Adolescent↗

PubMed2003

Quantitative image analysis: software systems in drug development trials.

Multi-dimensional image analysis is being used increasingly to arrive at surrogate end-points for drug development trials. Various imaging modalities such as computed tomography (CT), magnetic resonance imaging (MRI), positron emission tomography (PET) and ultrasound are used to analyze treatments for diseases such as cancer, multiple sclerosis, osteoarthritis, and Alzheimer's disease. However, extracting information from images can be tedious and is prone to high user variability. The medical image analysis community is moving towards advanced software systems specifically designed for drug development trials. These systems can automatically identify the anatomy of interest in medical images (segmentation methods), can compare the anatomy over time or between patients (registration methods) and allow the quantitative extraction of anatomical features and the integration of the data and results into a database management system, automatically tracking the changes made to the data (audit trail generation). In this article, we present a case study using a prototype system that is used for quantifying multiple sclerosis lesions from multivariate MRI.

Clinical Trials as Topic↗

PubMed2002

Computer-assisted image analysis of neovascularization in thyroid neoplasms from dogs.

OBJECTIVE: To develop a computer-assisted image analysis procedure for quantitation of neovascularization in formalin-fixed paraffin-embedded specimens of thyroid gland tissue from dogs with and without thyroid gland neoplasia. SAMPLE POPULATION: 47 thyroid gland carcinomas, 8 thyroid gland adenomas, and 8 specimens of thyroid tissue from dogs without thyroid gland abnormalities (normal). PROCEDURE: Serial tissue sections were prepared and stained with antibodies against human CD31 or factor VIII-related antigen (factor VIII-rag). The areas of highest vascularity were identified in CD31-stained sections, and corresponding areas were then identified in factor VIII-rag-stained sections. Image analysis was used to calculate the total vascular density in each section, and neovascularization, expressed as a percentage, was determined as the absolute value of the total vascular density derived from factor VIII-rag-stained sections minus the vascular density derived from CD31-stained sections. RESULTS: Mean vascular density of thyroid gland carcinomas derived from CD31-stained sections was significantly greater than density derived from factor VII I-rag-stained sections. This incremental difference was presumed to represent degree of neovascularization. However, significant differences were not detected between vascular densities derived from CD31 and factor VIII-rag-stained sections for either normal thyroid gland tissue or thyroid gland adenomas. No significant correlations were found between vascular density in thyroid gland carcinomas and survival time following surgery. CONCLUSION AND CLINICAL RELEVANCE: A computer-assisted image analysis method was developed for quantifying neovascularization in thyroid gland tumors of dogs. This method may allow identification of dogs with tumors that are most likely to respond to treatment with novel antiangiogenesis agents.

Adenoma↗

PubMed1998

Time and space results of dynamic texture feature extraction in MR and CT image analysis.

Texture feature extraction is a fundamental part of texture image analysis. Therefore, the reduction of its computational time and storage requirements should be an aim of continuous research. The Spatial Grey Level Dependence Method (SGLDM) is one of the most important statistical texture description methods, especially in medical image analysis. Co-occurrence matrices are employed for the implementation of this method; however, they are inefficient in terms of computational time and memory space, due to their dependency on the number of gray levels (gray-level range) in the entire image. Since texture is usually measured in a small image region, a large amount of memory is wasted while the computational time of the texture feature extraction operations is unnecessarily raised. Their inefficiency puts up barriers to the wider utilization of SGLDM in a real application environment, such as a clinical environment. In this paper, the memory space and time efficiency of a dynamic approach to texture feature extraction in SGLDM is investigated through a pilot application in the analysis of magnetic resonance (MR) and computed tomography (CT) images.

Image Processing, Computer-Assisted↗

PubMed1998

Automated image analysis system for detecting boundaries of live prostate cancer cells.

Image analysis provides a powerful tool for quantifying cell motility and has been used to correlate motility with metastatic potential in an animal model of prostate cancer. However, widespread use of this image analysis method has been limited because earlier methods of quantitative analysis required time-intensive and subjective manual tracing of cell contours. In this report, we describe a fully automated image segmentation algorithm for detection and morphometric description of prostatic cells. The segmentation system was tested on prostate cell images generated from Hoffman modulation contrast microscopy (47 cells at 64 time points = 3,008 images) and differential interference contrast microscopy (29 cells at 64 times points plus 1 cell at 62 time points = 1,918 images). Morphometric measurements were derived from computer-determined cell boundaries and compared with the same measurements derived from manually traced cell boundaries. Final correlation coefficients for area and perimeter measurements for Hoffman and differential interference contrast microscopy were (0.76, 0.62) and (0.93, 0.93), respectively. Results with our differential interference contrast images demonstrate that our segmentation algorithm reliably and efficiently replaces the need for manually traced cell boundaries in addition to eliminating intraobserver variation. Our automated segmentation process will have immediate utility in our motility analysis system that relates cell motility with metastatic potential of prostate cancer.

Adenocarcinoma↗

PubMed1998

Histopathological evaluation of liver fibrosis: quantitative image analysis vs semi-quantitative scores. Comparison with serum markers.

BACKGROUND/AIMS: Liver fibrosis is mainly evaluated by qualitative histological examination. Although histological semi-quantitative scores and quantitative determination with image analysis are now possible, these methods have not been fully validated and compared. Therefore, we evaluated these two methods prospectively in 243 patients with chronic liver disease. METHODS: The semi-quantitative fibrosis score was evaluated by two independent pathologists, using the Knodell fibrosis score and a 6-grade score derived from the Metavir score; the area of fibrosis was measured by image analysis. The serum levels of hyaluronate, N-terminal peptide of procollagen III, laminin, transforming growth factor-beta1, alpha2-macroglobulin, apolipoprotein A1, PGA score and prothrombin index were measured. RESULTS: There was a good correlation between the semi-quantitative fibrosis score and the area of fibrosis (r=0.84, p<10(-4)). Using multiple regression analysis, the semi-quantitative score was predicted by the 8 serum markers with R2=0.69 (R2=0.59 for hyaluronate at the 1st step) while the area of fibrosis was predicted with R2=0.79 (R2=0.76 for hyaluronate at the 1st step), and the Knodell fibrosis score was predicted with R2=0.65 (R2=0.31 for hyaluronate at the 1st step). CONCLUSIONS: The area of fibrosis, as determined by image analysis, and the semi-quantitative score are well correlated. However, for serum markers the correlation is higher with the area of fibrosis than with the semi-quantitative score. Other characteristics such as reproducibility, rapidity, simplicity, adaptability, and exhaustiveness also favor image analysis.

Biomarkers↗

PubMedDate not supplied

Determination of optimal view angles for quantitative facial image analysis.

In quantitative evaluation of facial skin chromophore content using color imaging, several factors such as view angle and facial curvature affect the accuracy of measured values. To determine the influence of view angle and facial curvature on the accuracy of quantitative image analysis, we acquire cross-polarized diffuse reflectance color images of a white-patched mannequin head model and human subjects while varying the angular position of the head with respect to the image acquisition system. With the mannequin head model, the coefficient of variance (CV) is determined to specify an optimal view angle resulting in a relatively uniform light distribution on the region of interest (ROI). Our results indicate that view angle and facial curvature influence the accuracy of the recorded color information and quantitative image analysis. Moreover, there exists an optimal view angle that minimizes the artifacts in color determination resulting from facial curvature. In a specific ROI, the CV is less in smaller regions than in larger regions, and in relatively flat regions. In clinical application, our results suggest that view angle affects the quantitative assessment of port wine stain (PWS) skin erythema, emphasizing the importance of using the optimal view angle to minimize artifacts caused by nonuniform light distribution on the ROI. From these results, we propose that optimal view angles can be identified using the mannequin head model to image specific regions of interest on the face of human subjects.

Computer Simulation↗

PubMed2006

Object-oriented image analysis for high content screening: detailed quantification of cells and sub cellular structures with the Cellenger software.

BACKGROUND: Detailed image analysis still is a considerable bottleneck for many cellular assays, and automated solutions to the problem are desirable. However, dealing with the complexity and variability of structures in cellular images makes detailed and reliable analysis a nontrivial task. METHODS: Therefore, based on the object-oriented image analysis approach, a novel image analysis technology, a flexible and reliable system for image analysis in cellular assays was developed. It contains a library of predefined, adaptable modules, each of them developed for a specific analysis task. The system can be configured easily by combining appropriate modules and adapting them interactively to the specific image data, if necessary. By representing cells and sub cellular structures within a network of interlinked image objects, a large number of parameters can be derived that describe shape, intensity, and relevant structural and relational aspects of any chosen class of structures. RESULTS: Thus, multi-parameter analysis and multiplexing are supported. A sample application based on this approach demonstrates that GFP signals can be distinguished based on their properties and the relative location within the cell.

Cell Membrane↗