Oncology application examples
'DRACCAR' DNA quantization and ploidy analysis
DNA Quantization and Ploidy application for anticancer research
ADCIS and the Francois Baclesse Cancer Centre in Caen jointly developed a turn-key system to perform DNA quantization and Ploidy analysis. These two tests are performed routinely by laboratories involved in cytopathology in oncology. Starting from image processing algorithms on an existing UNIX system 1, ADCIS ported all the image processing algorithms into the Aphelion™ environment on a PC running Windows. Porting this application to the PC with Aphelion improved the system performance and ease-of-use, while dramatically reducing the cost of the system by using the standard PC environment.
The system includes an optical microscope equipped with an automatic stage able to move in the X, Y and Z directions, a black and white camera mounted on the microscope, and a PC running Windows with a standard frame grabber board.
The image processing techniques involved in the system are rather complex, and can be described in the following steps:
During the development of the software, all results were matched against the results obtained with a flow cytometry system, pointing out the main benefits of image analysis: identification and elimination of debris and unwanted stromal cells, analysis of fixed formalin and paraffin embedded samples.
The following screen captures present two of the windows in the analysis.
The custom engineering work performed by ADCIS engineers included the definition of the GUI, the implementation of the image segmentation algorithms, the full control of the stage of the microscope, and the development of the classification module, which is now available as an ActiveX component. The stand-alone application was developed using Visual Basic, calling for the Aphelion ActiveX components and Toolkits.
Future development on the product will include more advanced statistical analysis, such as dispersion and dynamic clustering.
This application demonstrates the power of the Aphelion's ActiveX components in use. The system was developed quickly and is easy to maintain and expand as needed.
ADCIS and the GRECAN (bioticla) at Francois Baclesse Cancer Centre are also currently working together on related biology projects such as the immuno-marker analysis, and other original tools dedicated to experimental and clinical pathology.
'ImagePath' DNA quantization and ploidy analysis
DNA Ploidy analysis sample
DNA quantization: ImagePath Application for Ploidy Analysis
The ImagePath Systems provides vertically integrated imaging products and reagents for the anatomic pathology laboratory.
Current offerings include ImagePath's remarkable integration of reagents, microscope, camera, high-speed computer and propriety imaging algorithms to permit ploidy analysis (DNA measurements in individual, Feulgen stained, cell nuclei) of a thousand or more nuclei in a few minutes, speeds never before thought possible.
This system also is optimized for full color image capture at resolutions of 1315 x 1024 pixels - which provides detail approaching the lens resolution of the microscope. These full color images can be annotated and saved, as well as exported to other graphics programs.
The ImagePath 300 consists of a vertically integrated system for performing rapid image-based DNA Ploidy Analysis with simple, intuitive, menu driven instructions, standardizing these procedures for improved accuracy and repeatability. Full user interaction with measurement results is provided via linked displays. Mouse actions in any image, graph or table causes corresponding data to be highlighted in the other windows.
RAMIS: Discover innovative compounds inhibiting cell division
RAMIS: A software product to discover innovative compounds inhibiting cell division
Goal of the project
Use multi-parametric and high resolution imaging techniques to characterize and select innovative compounds and/or protein targets involved in cell division.
Over the past few years, new strategies have emerged that allow one to discover new molecules on the basis of their activity in a given cellular context (cell-based assays), rather than at the molecular level. The most recent form of such strategies is the concept of image-based phenotypic screening or High Content Screening (HCS).
This type of screening aids in the direct selection of compounds that are able to penetrate a cell and induce a phenotypic change of interest. This screening is based on the combined use of:
The analysis of complex phenotypic changesinvolving multiple probes, multiple parameters computed from these probes, and multiple treatment conditionshelps to generate a new phenotype and/or new phenotypic profiles characteristic of the pharmacological effects and of the mechanism of action of a given molecule. The comparison of phenotypic profiles may then allow the discovery of molecules having unique mechanisms of action and/or that affect new targets.
To get better results, high content phenotypic screenings require the use of advanced technologies adapted to the detection, quantification, and analysis of the observed changes.
Ramis project partners are developing an innovative screening strategy based on high resolution imaging techniques to characterize phenotypes of new molecules and new targets interfering with the division of human tumor cells, in particular with mitosis.
The project includes two very distinct but complementary axes:
Image Database Generation
Automatic identification of new phenotypes
Users of the Ramis software product will appreciate its ease of use and its capability to identify original molecules and/or targets. In addition, users can add new entries in the database and thereby enrich the knowledge of experts.
When completed, Ramis will be a unique and efficient image-based, high content screening system for the identification of original molecules as well as new targets in the area of cell division.
Ramis is being designed as a flexible system that can be enhanced in the future to:
The marketing and sale of the Ramis software will be the responsibility of ADCIS SA, a commercial partner in the Ramis consortium.
The Research Institute Pierre Fabre (IRPF), located in Toulouse, France, is in charge of all R&D activities within the Pierre Fabre Laboratories. It brings to the project its expertise in the discovery of anti-cancerous agents in the field of onco-pharmacology. IRPF is also involved in automated image acquisition using fluorescence microscopy and in software development.
The Centre National de la Recherche Scientifique (CNRS), a French public research center in Toulouse, brings its expertise in the field of fundamental cell biology and its comprehensive knowledge in the field of cell division and associated phenotypes.
ARMINES, the research institute of the School of Mines ParisTech, brings its renowned expertise in the field of image processing and analysis to develop methods for quantitative description of cells, its experience in the field of data classification, and statistics. During the project, ARMINES will develop new techniques for the training and modeling of biological systems and phenotypes classification.
ADCIS S.A., a commercial company located in Normandy, France, brings its expertise in the development of advanced software products for image processing and analysis. ADCIS is the prime contractor in the development of the Ramis software environment, the image database generation, the graphical user interface, the image annotation software to formalize the biology expert knowledge, and the integration of the various image processing and classification algorithms developed by the other Ramis partners.
Stereology Analyzer: Stereological analysis of 3D structures using 2D section or projection images
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Stereology Analyzer is a simple to use software tool for reliably estimating quantifications of important 3D structures. This tool is general in its implementation, but has applicability to various scientific domains, most commonly in medicine, materials science, and geology.
The common factors in these fields are the need to characterize and quantify microscopic structures of interest ("SOI") and the use of very large images (i.e., virtual slides or composite images).
Where automated processes don't exist or fail to compute SOI parameters reliably, stereology is the method of choice to estimate these parameters. In fact, stereology is also frequently used to validate the proper performance of complex, automated algorithms. Stereology Analyzer is a faithful implementation of long-accepted stereological and statistical methods in the context of today's software technology.
Image courtesy of Paulette Herlin
The term stereology was first introduced in 1961 when the International Society for Stereology (ISS) was founded by a small group of scientists, although the basis of stereology theory was defined more than 300 years ago. By definition, stereology is the science that studies the geometric relationship between a structure that exists in 3D space and a set of images of the same structure that are fundamentally defined in 2D space (images of slices, sections, or projections). Note that standard 2D image processing techniques will hardly provide 3D information from sections, except for the volume fraction value.
Stereology Analyzer Presentation
Stereology Analyzer implements long-standing and accepted stereology techniques that employ an interactive grid overlaid on regions of interest ("ROI") in a 2D image. Stereology Analyzer enables the user to optionally define one or more ROIs and a grid that overlays the ROIs or the whole image. The type and spacing of the grid can be adjusted by the user to achieve the best estimates of the SOI parameters contained within the ROIs. The types of grids are characterized by the geometric element that displays at the grid's nodes. Grid element alternatives include points, lines, frames, squares, and circles.
After the grid and ROIs are defined, the user manually highlights SOIs that are intersected by the grid elements. The number of grid elements contained within the ROIs and the number of highlighted SOIs are then automatically counted and used to compute SOI parameters. The automatic computations are based on classical stereological and statistical analyses. These computational results are then displayed on the computer's screen and can be exported into third party environments (e.g., Excel, Word) for display and further analysis specific to the applicable field.
Image Processing Algorithm Validation
Experts in the applicable field can use Stereology Analyzer to quickly compute unbiased estimates of SOI parameters on virtual slides. If used properly, Stereology Analyzer is an effective alternative for image processing developers to validate a sequence of complex image processing algorithms. In addition, while complex algorithms require careful validation of their results, stereology results require no validation since results are derived from a standard statistical analysis of grid elements and user-highlighted SOIs.
In the field of medicine, when the SOIs cannot be highlighted by a specific staining (e.g., histochemical or immunohistochemical stainings), or when staining is not optimal or tissue is heterogeneous, then the techniques of stereology are the best alternative for estimating the parameter values of SOIs.
When specific staining is effective, different image processing and analysis algorithms can be developed that vary in their complexity, accuracy, and efficiency. Stereology Analyzer is a powerful tool for establishing the quantification accuracy that an algorithm sequence should achieve to be relied on. The statistical sampling process used in stereology science diminishes the difficult problem resulting from tissue heterogeneity. The special strength of stereology is that it always provides unbiased estimates of SOI parameters for any complexity of sample tissue. When combining stereology and image processing in pathology and scanning microscopy fields, the user has a broad set of powerful tools to characterize SOIs on virtual slides.
The Stereology Toolkit has the following capabilities:
The concept of this module is derived from the Stereology expertise of Paulette Herlin and her original development works at the Centre François Baclesse Cancer Center. The expertise of Dr Dragos Vasilescu, PhD, in the field of stereology and the use of combined grids, University of British Columbia, Vancouver, V6Z 1Y6, Canada, helped ADCIS to develop the latest version of the Stereology Analyzer Software product.
Main benefits of Image Quality Extension: