“Virtual flow cytometry” of immunostained lymphocytes on microscopic tissue slides:iHCFlow™ tissue cytometry

QUANTITATIVE MORPHOLOGICAL AND MOLECULAR PATHOLOGY OF THE HUMAN THYMUS CORRELATE WITH INFANT CAUSE OF DEATH

The objective of this study was to investigate and quantify the morphological and molecular changes in the thymus for common causes of human infant death. Thymic architecture and molecular changes apparent in human infant head trauma victims were assessed by microscopy and quantified by image analysis of digital whole slide images. Thymuses from victims of SIDS and suffocated infants displaying normal thymus architecture were used for comparison. Molecular expression of proliferation and serotonin receptor and transporter protein markers was evaluated. Duplicate morphological and molecular studies of rodent thymuses were completed with both mouse and rat models. Quantification of novel parameters of digital images of thymuses from human infants suffering mortal head trauma revealed a disruption of the corticomedullary organization of the thymus, particularly involving dissolution of the corticomedullary border. A similar result was obtained for related mouse and rat models. The human thymuses from head trauma cases also displayed a higher percentage of Ki-67-positive thymocytes. Finally, we determined that thymus expression of the human serotonin receptor, and the serotonin transporter, occur almost exclusively in the thymic medulla. Head trauma leads to a disruption of the thymic, corticomedullary border, and molecular expression patterns in a robust and quantifiable manner.

Developments in the immunophenotypic analysis of haematological malignancies

Immunophenotyping is the method by which antibodies are used to detect cellular antigens in clinical samples. Although the major role is in the diagnosis and classification of haematological malignancies, applications have expanded over the past decade. Immunophenotyping is now used extensively for disease staging and monitoring, to detect surrogate markers of genetic aberrations, to identify potential immuno-therapeutic targets and to aid prognostic prediction. This expansion in applications has resulted from developments in antibodies, methodology, automation and data handling. In this review we describe recent advances in both the technology and applications for the analysis of haematological malignancies. We highlight the importance of the expanding repertoire of testing capability for diagnostic, prognostic and therapeutic applications. The impact and significance of immunophenotyping in the assessment of haematological neoplasms are evident.

Multispectral imaging and pathology: seeing and doing more

BACKGROUND

The current appreciation of the biological complexity of disease has led to increasing demands on pathologists to provide clinically relevant, quantitative morphological and molecular information while preserving cellular and tissue context. This can be technically challenging, especially when signals of interest are colocalized. With fluorescence-based methods, sensitivity and quantitative reliability may be compromised by spectral cross-talk between labels and by autofluorescence. In brightfield microscopy, overlapping chromogenic signals pose similar imaging difficulties.

APPROACH

These challenges can be addressed using commercially available multispectral imaging technologies attached to standard microscope platforms, or alternatively, integrated into whole-slide scanning instruments.

ASSESSMENT

Multispectral techniques, along with other developments in digital analysis, will allow pathologists to deliver appropriate quantitative and multiplexed analyses in a reproducible and timely manner. Caveats apply - as the complexity of the sample preparation and analysis components increases, commensurate attention must be paid to the use of appropriate controls for all stages of the process.

Automated segmentation of tissue images for computerized IHC analysis

This paper presents two automated methods for the segmentation of immunohistochemical tissue images that overcome the limitations of the manual approach as well as of the existing computerized techniques. The first independent method, based on unsupervised color clustering, recognizes automatically the target cancerous areas in the specimen and disregards the stroma; the second method, based on colors separation and morphological processing, exploits automated segmentation of the nuclear membranes of the cancerous cells. Extensive experimental results on real tissue images demonstrate the accuracy of our techniques compared to manual segmentations; additional experiments show that our techniques are more effective in immunohistochemical images than popular approaches based on supervised learning or active contours. The proposed procedure can be exploited for any applications that require tissues and cells exploration and to perform reliable and standardized measures of the activity of specific proteins involved in multi-factorial genetic pathologies.