Technical note on the validation of a semi-automated image analysis software application for estrogen and progesterone receptor detection in breast cancer.

Background: The immunohistochemical detection of estrogen (ER) and progesterone (PR) receptors in breast cancer is routinely used for prognostic and predictive testing. Whole slide digitalization supported by dedicated software tools allows quantization of the image objects (e.g.

Digital microscopy for boosting database integration and analysis in TMA studies.

The enormous amount of clinical, pathological, and staining data to be linked, analyzed, and correlated in a tissue microarray (TMA) project makes digital slides ideal to be integrated into TMA database systems. With the help of a computer and dedicated software tools, digital slides offer dynamic access to microscopic information at any magnification with easy navigation, annotation, measurement, and archiving features. Advanced slide scanners work both in transmitted light and fluorescent modes to support biomarker testing with immunohistochemistry, immunofluorescence or fluorescence in situ hybridization (FISH).

Automated multichannel fluorescent whole slide imaging and its application for cytometry.

Slide-based image cytometry (SBC) has several advantages over flow cytometry but it is not widely used because of its low throughput, complicated workflow, and high price. Fully automated microscopes became affordable with the advent of whole slide imaging (WSI) and they can be transformed into a cytometer. A MIRAX MIDI automated whole slide imager was used with metal-halide and light emitting diode (LED)-based fluorescent illumination, filter block changer, and a cooled monochrome charge coupled device camera.

Collagen XVII/BP180 protein expression in squamous cell carcinoma of the skin detected with novel monoclonal antibodies in archived tissues using tissue microarrays and digital microscopy.

Collagen XVII/BP180, a hemidesmosomal adhesion protein, is lost during normal keratinocyte maturation; however, it may be reexpressed upon malignant transformation. In this work, highly sensitive monoclonal antibodies 6D1 and 9G2 were produced, characterized, and used for the detection of collagen XVII in a tissue microarray series of archived samples of nonmelanocytic epithelial neoplasias, including 5 verruca vulgaris, 14 seborrheic keratosis, 38 actinic keratosis, 38 basal cell carcinoma (BCC), 15 basosquamous carcinoma, 58 squamous cell carcinoma (SCC), and 9 normal skin. Digital microscopy and a new tissue microarray software linking image and patient data allowed easy and validated evaluation and quality archiving of stained samples.

Automated classification of inflammation in colon histological sections based on digital microscopy and advanced image analysis.

Automated and quantitative histological analysis can improve diagnostic efficacy in colon sections. Our objective was to develop a parameter set for automated classification of aspecific colitis, ulcerative colitis, and Crohn's disease using digital slides, tissue cytometric parameters, and virtual microscopy. Routinely processed hematoxylin-and-eosin-stained histological sections from specimens that showed normal mucosa (24 cases), aspecific colitis (11 cases), ulcerative colitis (25 cases), and Crohn's disease (9 cases) diagnosed by conventional optical microscopy were scanned and digitized in high resolution (0.

Automated virtual microscopy of gastric biopsies.

Background: Automated virtual microscopy of specimens from gastrointestinal biopsies is based on cytometric parameters of digitized histological sections. To our knowledge, cytometric parameters of gastritis and of adenocarcinoma have yet to be fully characterized. Our objective was to classify gastritis and adenocarcinoma based on cytometric parameters.

Three-dimensional virtual microscopy of colorectal biopsies.

Conventional optical microscopy of specimens from colorectal biopsies commonly produces diagnostic errors due to incomplete sampling or poor orientation. Obtaining additional sections or re-embedding may help avoid these errors, but can prolong turnaround time. We describe new technology, which incorporates exhaustive sectioning, 3-dimensional reconstruction, and virtual microscopy, that may eliminate these problems by enabling pathologists to rapidly examine entire specimens and convert poorly oriented mucosa to well-oriented mucosa.