Theory of sampling and its application in tissue based diagnosis

<p>Abstract</p> <p>Background</p> <p>A general theory of sampling and its application in tissue based diagnosis is presented. Sampling is defined as extraction of information from certain limited spaces and its transformation into a statement or measure that is valid for the entire (reference) space. The procedure should be reproducible in time and space, i.e. give the same results when applied under similar circumstances. Sampling includes two different aspects, the procedure of sample selection and the efficiency of its performance. The practical performance of sample selection focuses on search for localization of specific compartments within the basic space, and search for presence of specific compartments.</p> <p>Methods</p> <p>When a sampling procedure is applied in diagnostic processes two different procedures can be distinguished: I) the evaluation of a diagnostic significance of a certain object, which is the probability that the object can be grouped into a certain diagnosis, and II) the probability to detect these basic units. Sampling can be performed without or with external knowledge, such as size of searched objects, neighbourhood conditions, spatial distribution of objects, etc. If the sample size is much larger than the object size, the application of a translation invariant transformation results in Kriege's formula, which is widely used in search for ores. Usually, sampling is performed in a series of area (space) selections of identical size. The size can be defined in relation to the reference space or according to interspatial relationship. The first method is called random sampling, the second stratified sampling.</p> <p>Results</p> <p>Random sampling does not require knowledge about the reference space, and is used to estimate the number and size of objects. Estimated features include area (volume) fraction, numerical, boundary and surface densities. Stratified sampling requires the knowledge of objects (and their features) and evaluates spatial features in relation to the detected objects (for example grey value distribution around an object). It serves also for the definition of parameters of the probability function in so – called active segmentation.</p> <p>Conclusion</p> <p>The method is useful in standardization of images derived from immunohistochemically stained slides, and implemented in the EAMUS™ system <url>http://www.diagnomX.de</url>. It can also be applied for the search of "objects possessing an amplification function", i.e. a rare event with "steering function". A formula to calculate the efficiency and potential error rate of the described sampling procedures is given.</p

TKTL1 is overexpressed in a large portion of non-small cell lung cancer specimens

In several tumors the transketolase activity, controlled inter alia by enzymes of the pentose phosphate pathway which is an alternative, energy generating reaction-cascade to glycolysis, has been correlated with proliferation. The increase of thiamine-dependant transketolase enzyme reactions is induced especially through upregulated transketolase-like enzyme 1 (TKTL1)-activity; that shows TKTL1 to be a causative enzyme for tumors enhanced, anaerobic glucose degradation. We investigated TKTL1-expression in 88 human, formalin-fixed non-small cell lung cancer tissues and 24 carcinomas of the breast by immunohistochemical stainings applying a 0 to 3 staining-score system (3 = strongest expression). For means of validation we additionally stained 40 NSCLC fixed and paraffin-embedded utilizing the HOPE-technique; showing comparable results to the formalin-fixed, paraffin-embedded specimens (not shown). Potential correlations with age, sex, TNM-classification parameters and tumor grading as well as tumor transcription factor 1 (TTF1) and surfactant protein A (SPA) expression were investigated. 40.9% of the analyzed lung tumors expressed TKTL1 weakly (Score 1), 38.6% moderately (score 2) and 17.1% strongly (score 3). 3 tumors were diagnosed TKTL1-negative (3.4%; score 0). All Breast cancer specimen stainings were positive and scored 1: 32%; scored 2: 36%; scored 3: 32%. Alveolar macrophages and Alveolar Epithelial Cells Type II were also found to be TKTL1-positive

Image standards in Tissue-Based Diagnosis (Diagnostic Surgical Pathology)

© 2008 Kayser et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution Licens

AI (artificial intelligence) in histopathology--from image analysis to automated diagnosis.

The technological progress in digitalization of complete histological glass slides has opened a new door in tissue--based diagnosis. The presentation of microscopic images as a whole in a digital matrix is called virtual slide. A virtual slide allows calculation and related presentation of image information that otherwise can only be seen by individual human performance. The digital world permits attachments of several (if not all) fields of view and the contemporary visualization on a screen. The presentation of all microscopic magnifications is possible if the basic pixel resolution is less than 0.25 microns. To introduce digital tissue--based diagnosis into the daily routine work of a surgical pathologist requires a new setup of workflow arrangement and procedures. The quality of digitized images is sufficient for diagnostic purposes; however, the time needed for viewing virtual slides exceeds that of viewing original glass slides by far. The reason lies in a slower and more difficult sampling procedure, which is the selection of information containing fields of view. By application of artificial intelligence, tissue--based diagnosis in routine work can be managed automatically in steps as follows: 1. The individual image quality has to be measured, and corrected, if necessary. 2. A diagnostic algorithm has to be applied. An algorithm has be developed, that includes both object based (object features, structures) and pixel based (texture) measures. 3. These measures serve for diagnosis classification and feedback to order additional information, for example in virtual immunohistochemical slides. 4. The measures can serve for automated image classification and detection of relevant image information by themselves without any labeling. 5. The pathologists' duty will not be released by such a system; to the contrary, it will manage and supervise the system, i.e., just working at a "higher level". Virtual slides are already in use for teaching and continuous education in anatomy and pathology. First attempts to introduce them into routine work have been reported. Application of AI has been established by automated immunohistochemical measurement systems (EAMUS, www.diagnomX.eu). The performance of automated diagnosis has been reported for a broad variety of organs at sensitivity and specificity levels >85%). The implementation of a complete connected AI supported system is in its childhood. Application of AI in digital tissue--based diagnosis will allow the pathologists to work as supervisors and no longer as primary "water carriers". Its accurate use will give them the time needed to concentrating on difficult cases for the benefit of their patients

LED-FISH: Fluorescence microscopy based on light emitting diodes for the molecular analysis of Her-2/neu oncogene amplification

Light emitting diodes (LED), which are available as small monochromatic light sources with characteristic features such as maximum illumination power combined with minimum energy consumption and extremely long lifespan have already proved as a highly potential low-cost alternative for specific diagnostic applications in clinical medicine such as tuberculosis fluorescence microscopy. Likewise, the most reliable evaluation of Her-2/neu (c-erbB2) gene amplification, which has been established in the last few years for routine diagnosis in clinical pathology as determinant towards Herceptin-based treatment of patients with breast cancer, is based on fluorescence in situ hybridization (FISH) and corresponding high priced fluorescence equipment. In order to test the possibility to utilize the advantages of low-cost LED technology on FISH analysis of c-erbB2 gene expression for routine diagnostic purposes, the applicability of a standard bright field Carl Zeiss Axiostar Plus microscope equipped with a Fraen AFTER* LED Fluorescence Microscope Kit for the detection of Her-2/neu gene signals was compared to an advanced Nikon Eclipse 80i fluorescence microscope in combination with a conventional 100W mercury vapor lamp. Both microscopes were fitted with the same Quicam FAST CCD digital camera to unequivocally compare the quality of the captured images. C-erbB2 gene expression was analyzed in 30 different human tissue samples of primary invasive breast cancer, following formalin fixation and subsequent paraffin-embedding. The Her2/neu gene signals (green) were identifiable in the tumor cells in all cases and images of equal quality were captured under almost identical conditions by 480 nm (blue) LED module equipped standard Axiostar microscope as compared to conventional fluorescence microscopy. In this first attempt, these monochromatic LED elements proved in principle to be suitable for the detection of Her-2/neu gene expression by FISH. Thus, our own experiences emphasize the high potential of this technology to provide a serious alternative to conventional fluorescence microscopy in routine pathology; representing a sustainable technological progress, this low-cost technology will clearly give direction also to the growing field of molecular pathology

On the significance of Surfactant Protein-A within the human lungs

Surfactant Protein-A (SP-A) is the most prominent among four proteins in the pulmonary surfactant-system. SP-A is expressed by alveolar epithelial cells type II as well as by a portion of non small cell lung carcinomas (NSCLC)

Enhanced molecular analyses by combination of the HOPE-technique and laser microdissection

As part of an investigation aimed at illuminating the possibilities and limits of the HOPE-fixation and paraffin-embedding technique we here describe a novel procedure which was developed in order to combine the benefits of the HOPE-technique with the capabilities of laser microdissection. The presented procedure avoids the need for amplification of template-RNA thus facilitating reliable and reproducible results. The excellent preservation of nucleic acids, proteins, and morphology in HOPE-fixed, paraffin-embedded tissues enhances the molecular applications available to date with materials acquired by laser microdissection when compared to formalin fixed, paraffin-embedded tissues, thus substantially extending the methodological panel in tissue based research

Correlation of EGFR expression, gene copy number and clinicopathological status in NSCLC

Background: Epidermal Growth Factor Receptor (EGFR) targeting therapies are currently of great relevance for the treatment of lung cancer. For this reason, in addition to mutational analysis immunohistochemistry (IHC) of EGFR in lung cancer has been discussed for the decision making of according therapeutic strategies. The aim of this study was to obtain standardization of EGFR-expression methods for the selection of patients who might benefit of EGFR targeting therapies. Methods: As a starting point of a broad investigation, aimed at elucidating the expression of EGFR on different biological levels, four EGFR specific antibodies were analyzed concerning potential differences in expression levels by Immunohistochemistry (IHC) and correlated with fluorescence in situ hybridization (FISH) analysis and clinicopathological data. 206 tumor tissues were analyzed in a tissue microarray format employing immunohistochemistry with four different antibodies including Dako PharmDx kit (clone 2-18C9), clone 31G7, clone 2.1E1 and clone SP84 using three different scoring methods. Protein expression was compared to FISH utilizing two different probes. Results: EGFR protein expression determined by IHC with Dako PharmDx kit, clone 31G7 and clone 2.1E1 (≤ 0.05) correlated significantly with both FISH probes independently of the three scoring methods; best correlation is shown for 31G7 using the scoring method that defined EGFR positivity when ≥ 10% of the tumor cells show membranous staining of moderate and severe intensity (p = 0.001). Conclusion: Overall, our data show differences in EGFR expression determined by IHC, due to the applied antibody. Highest concordance with FISH is shown for antibody clone 31G7, evaluated with score B (p = 0.001). On this account, this antibody clone might by utilized for standard evaluation of EGFR expression by IHC