Projects

The organization of the institute is project-directed and the following projects have special relevance for Centre for Cancer Biomedicine.

DNA Ploidy

Ploidy is a cytogenetic term used to describe the number of chromosome sets, or deviation from the normal number of chromosomes in a cell. In cytometry, the expression DNA ploidy is used either to describe the DNA content in a cell or the total DNA distribution in a cell population.

We have developed an image analysis system for DNA ploidy analyses based on the Feulgen technique, which is a widely used staining method in biology. The Schiff or Shiff-related reagent is used to bind to aldehyde groups which are yielded after hydrolysis with HCl. This allows for DNA staining in situ. The color intensity is proportional to the DNA concentration and the amount of DNA in the nucleus is an expression of light absorbed by the Feulgen stain in the entire nucleus. The Feulgen reaction is used to quantify the DNA ploidy distribution in tumor nuclei.
The picture of the nuclei is transferred from a microscope to a computer, via a high resolution digital camera. The computer measures the absorbed amount of light, which provides an expression of the amount of DNA in each nucleus:

Nucleotyping

The Nucleotyping project is based on the concept of genome instability in cancer, in line with todays understanding and theories of cancer development. Nucleotyping classifies a tumor based on qualitative and quantitative analyses of DNA and chromatin structure in the tumor cell nuclei using advanced high-resolution digital image analysis.
Nucleotyping represents among other features an objective assessment of nuclear atypia, one of the most important features of histopathological diagnosis and prognosis. In parallel with the qualitative assessment of chromatin structure, the total amount of chromatin or DNA (dependent on the applied staining) are also measured, thus giving the DNA ploidy as well as more traditional nuclear morphometry. The method is also sensitive for larger chromosomal aberrations. Of even greater importance is the methods ability to map and quantify functional changes in DNA organization. Such changes are, to a large extent, sub-visual, and are therefor not detected by traditional microscopy. Nucleotyping might be described as interphase cytogenetics, or an interphase version of karyotyping, where organisational and functional domains of DNA are mapped and described.

The project has two main goals:

• Contribute to the understanding of epigenetic changes in cancer development, especially with emphasis on changes in DNA organization and chromatin structure.
• Develop new prognostic and predictive markers for diagnosis and treatment of cancer.

Tissue Micro Array

Tissue Micro Array (TMA) is an application that digitalizes and interprets/scores TMA specimens. The applications were completed in 2007 for PC and made available for our own projects and collaborators.

Tissue Micro Array (TMA) is an application that digitalizes and interprets/scores TMA specimens. The applications were completed in 2007 for PC and made available for our own projects and collaborators. Phase 2 of the project is underway and will result in a web-based version where the users can impart and analyse TMA specimens over the Internet. In phase 3, the solution will be integrated in the project Nucleotyping.

Collection is done from morphologically representative areas in regular formalin fixed, paraffin-embedded blocks. The desired tissue in the block is localized with the help of HE-stained sections. The cylinder formed biopsies are removed from the donor block using a core needle and place in a “punch” in the recipient paraffin block. One can therefore gather hundreds of biopsies in a recipient block. The finished block is then sectioned and stained with HE or immunostaining. The finished stained TMA section is scanned in the NanoZoomer for further analysis by the pathologist/researcher.

Micro Tracker

Micro Tracker is a method we established for visualizing results from different analysis methods in a traditional histopathological specimen.

We would like to be able to directly correlate results from methods such as Nucleotyping and DNA ploidy to histopathological classification and grading – a comparative cell-by-cell analysis.

The method is developed and implemented into RUST. Histological sections stained with standard Hematoxilin-Eosin (HE) are scanned in the NanoZoomer before they are de-stained and re-stained with Feulgen-Schiff and scanned with high resolution on Z1 (image cytometry system). The individual nuclei are then segmented and analyzed, before each nuclei is retrieved in the original HE-scan aided by Micro Tracker. The result from the nuclei measurements are then classified and defined groups can be chosen and given a clear markation (with different colors, for example) which are drawn around the same nuclei in the original HE-scan. The method also works on parallel sections.

Path Tool

Promising results from the technical development image analysis and segmenting algorithms for Nucleotyping, have now made it possible to assess automatic methods for classifying cells and tissue in routine pathology sections.

Combined with traditional graph theory and some of our own ideas, we believe it should be possible to develop a system for making some types of histopathological classification automatic.
We have demonstrated that we are able to identify nuclei in HE stained routine specimens from prostate cancer, and achieved promising classification results related to Gleason grading.

3D Imaging

Capturing about 200 scans with 0.1 µm intervals from a semi-thick histological section, we can build 3-dimensional images of the nuclei in the section.

Confocal laser scan microscopy has traditionally been used to create 3D images of cell and tissue specimens, but the method is limited to fluorescence. Our approach is to test a high resolution light microscope with penetrating light, combined with deconvolution and other image analysis techniques. We capture about 200 scans with 0.1 µm intervals, from a semi-thick histological section stained with the Feulgen-Schiff technique. Based on a section from the middle of the series, we segment and classify the nucleus and build 3-dimensional images based on the nucleus profile from all of the sections the nucleus is represented in. We have demonstrated that the technique works and have successfully produced several 3-dimensional images of nuclei.

MEDinsight

MEDinsight is a tool intended for use in the clinical and research groups at Rikshospitalet. The MEDinsight concept is based on developing customized databases on a modern platform, which collect information from other systems. MEDinsight can provide better data management, data security, and data quality.

MEDinsight is used today as a quality register in the clinic and replaces in many cases quality registers which are no longer functional. Data from old registers are converted to MEDinsight databases (SQL), which contribute to secure data access for historical data.

MEDinsight makes it possible to register self-defined parameters, gather information from other systems, cross-check information, as well as retrieve relevant parameters from other systems were it is necessary. This is in conjunction with securing good data quality and data security.
MEDinsight has a role filter enabling the user to only see data they have legal access to.

A patient explorer is the base structure in the application. Here the patients are in focus and the information is shown resembling an explorer in MS-Windows. The explorer provides health personnel and researchers an overview of the logical connection between patient data for the different databases. A timeline shows patient progress in chronological order with both historical and planned events. Together, this provides a comprehensive and more complete picture of a patient’s illness history and development. Data from the individual patient is used as a template to define reports for groups of patients. The reporting function is a primary function in MEDinsight. It is used, among other things, in the generation of data for quality indicators.