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Histopathological analysis is crucial for the diagnosis of a large number of cancer types. A lot of progress has been made in the development of molecular based assays, but many of the cases still require the careful analysis of the stained tissue under a bright-field microscope and its analysis. This procedure is costly and time-consuming. We present a novel method for classification of cancer cells in lymph node images. It is based on the measurement of the spectral image of hematoxylin and eosin stained sample under the microscope and the analysis of the acquired data using state of the art machine learning techniques. The method is based on the analysis of the spectral information of the cells as well as their morphological properties. A large number of descriptors is extracted for each cell location, which are used to train a supervised classifier which discriminates between normal and cancer cells. We show that a reliable analysis can be made with detection rate (recall) of 81%-100% for the cancer class.

Telomeres, the end of chromosomes, are organized in a nonoverlapping fashion and form microterritories in nuclei of normal cells. Previous studies have shown that normal and tumor cell nuclei differ in their 3D telomeric organization. The differences include a change in the spatial organization of the telomeres, in telomere numbers and sizes and in the presence of telomeric aggregates. Previous attempts to identify the above parameters of 3D telomere organization were semi-automated. Here we describe the automation of 3D scanning for telomere signatures in interphase nuclei based on three-dimensional fluorescent in situ hybridization (3D-FISH) and, for the first time, define its sensitivity in tumor cell detection. The data were acquired with a high-throughput scanning/acquisition system that allows to measure cells and acquire 3D images of nuclei at high resolution with 40 × or 60 × oil and at a speed of 10,000-15,000 cells h(-1) , depending on the cell density on the slides. The automated scanning, TeloScan, is suitable for large series of samples and sample sizes. We define the sensitivity of this automation for tumor cell detection. The data output includes 3D telomere positions, numbers of telomeric aggregates, telomere numbers, and telomere signal intensities. We were able to detect one aberrant cell in 1,000 normal cells. In conclusions, we are able to detect tumor cells based on 3D architectural profiles of the genome. This new tool could, in the future, assist in patient diagnosis, in the detection of minimal residual disease, in the analysis of treatment response and in treatment decisions., (Copyright © 2010 International Society for Advancement of Cytometry.)

Hyperspectral microscopy grants the ability to characterize unique properties of tissues based on their spectral fingerprint. The ability to label and measure multiple molecular probes simultaneously provides pathologists and oncologists with a powerful tool to enhance accurate diagnostic and prognostic decisions. As the pathological workload grows, having an objective tool that provides companion diagnostics is of immense importance. Therefore, fast whole-slide spectral imaging systems are of immense importance for automated cancer prognostics that meet current and future needs. We aim to develop a fast and accurate hyperspectral microscopy system that can be easily integrated with existing microscopes and provide flexibility for optimizing measurement time versus spectral resolution. The method employs compressive sensing (CS) and a spectrally encoded illumination device integrated into the illumination path of a standard microscope. The spectral encoding is obtained using a compact liquid crystal cell that is operated in a fast mode. It provides time-efficient measurements of the spectral information, is modular and versatile, and can also be used for other applications that require rapid acquisition of hyperspectral images. We demonstrated the acquisition of breast cancer biopsies hyperspectral data of the whole camera area within ∼1 s. This means that a typical 1 × 1 cm2 biopsy can be measured in ∼10 min. The hyperspectral images with 250 spectral bands are reconstructed from 47 spectrally encoded images in the spectral range of 450 to 700 nm. CS hyperspectral microscopy was successfully demonstrated on a common lab microscope for measuring biopsies stained with the most common stains, such as hematoxylin and eosin. The high spectral resolution demonstrated here in a rather short time indicates the ability to use it further for coping with the highly demanding needs of pathological diagnostics, both for cancer diagnostics and prognostics. [ABSTRACT FROM AUTHOR]

Improving the spatial resolution of optical microscopes is important for a vast number of applications in the life sciences. Optical microscopy allows intact samples and living cells to be studied in their natural environment, tasks that are not possible with other microscopy methods (e.g. electron microscopy). Major advances in the past two decades have significantly improved microscope resolution. By using interference and structured light methods microscope resolution has been improved to ∼100nm, and with non-linear methods a ten times improvement has been demonstrated to a current resolution limit of ∼30nm. These methods bring together old theoretical concepts such as interference with novel non-linear methods that improve spatial resolution beyond the limits that were previously assumed to be unreachable. [Copyright &y& Elsevier]

Classical Hodgkin's lymphoma (cHL) is a B-Cell lymphoma comprised of mononuclear Hodgkin cells (H) and bi- to multi-nucleated Reed-Sternberg (RS) cells. Previous studies revealed that H and RS cells express lamin A/C, a component of the lamina of the nuclear matrix. Since no information was available about the three-dimensional (3D) expression patterns of lamin A/C in H and RS cells, we analyzed the 3D spatial organization of lamin in such cells, using 3D fluorescent microscopy. H and RS cells from cHL derived cell lines stained positive for lamin A/C, in contrast to peripheral blood lymphocytes (PBLs), in which the lamin A/C protein was not detected or weak, although its presence could be transiently increased with lymphocyte activation by lipopolysaccharide (LPS). Most importantly, in H and RS cells, the regular homogeneous and spherically shaped lamin A/C pattern, identified in activated lymphocytes, was absent. Instead, in H and RS cells, lamin staining showed internal lamin A/C structures, subdividing the nuclei into two or more smaller compartments. Analysis of pre-treatment cHL patients' samples replicated the lamin patterns identified in cHL cell lines. We conclude that the investigation of lamin A/C protein could be a useful tool for understanding nuclear remodeling in cHL. [ABSTRACT FROM AUTHOR]

Abstract: We present a novel concept for microscopic imaging. The proposed microscope-like device does not include an objective lens neither a condenser. Instead, a metallic plate of sub-wavelength hole-array with a varying pitch is used to illuminate the inspected object that is mounted very close to it. As a result, the transmitted spectrum through each hole differs from the others and therefore, each spot of the detected object is illuminated with a unique spectrum. By measuring a single spectrum that is the sum of all the spectra that are transmitted through the sample and by using spectral decomposition algorithms, the spatial transmission pattern of the object can be extracted. [Copyright &y& Elsevier]