Guest Editorial to the Special Letters Issue on Emerging Technologies in Multiparameter Biomedical Optical Imaging and Image Analysis

The past two decades have witnessed revolutionary advances in biomedical imaging modalities capable of providing biological and physiological information from the cellular scale to the organ level. Recent advances have also been focused on cost-effective, noninvasive, portable, and molecularimaging technologies for imaging at microscopic, mesoscopic, and macroscopic levels. These technologies have significant potential to advance biomedical research and clinical practice. They can also provide a better understanding and monitoring of physiological and functional disorders, which could lead to mainstream diagnostic technologies of the future

An Interactive Java Statistical Image Segmentation System: GemIdent

Supervised learning can be used to segment/identify regions of interest in images using both color and morphological information. A novel object identification algorithm was developed in Java to locate immune and cancer cells in images of immunohistochemically-stained lymph node tissue from a recent study published by Kohrt et al. (2005). The algorithms are also showing promise in other domains. The success of the method depends heavily on the use of color, the relative homogeneity of object appearance and on interactivity. As is often the case in segmentation, an algorithm specifically tailored to the application works better than using broader methods that work passably well on any problem. Our main innovation is the interactive feature extraction from color images. We also enable the user to improve the classification with an interactive visualization system. This is then coupled with the statistical learning algorithms and intensive feedback from the user over many classification-correction iterations, resulting in a highly accurate and user-friendly solution. The system ultimately provides the locations of every cell recognized in the entire tissue in a text file tailored to be easily imported into R (Ihaka and Gentleman 1996; R Development Core Team 2009) for further statistical analyses. This data is invaluable in the study of spatial and multidimensional relationships between cell populations and tumor structure. This system is available at http://www.GemIdent.com together with three demonstration videos and a manual. The code is now open-sourced and available on github at: https://github.com/kapelner/GemIden

A Fiber-Optic Fluorescence Microscope Using a Consumer-Grade Digital Camera for In Vivo Cellular Imaging

BACKGROUND: Early detection is an essential component of cancer management. Unfortunately, visual examination can often be unreliable, and many settings lack the financial capital and infrastructure to operate PET, CT, and MRI systems. Moreover, the infrastructure and expense associated with surgical biopsy and microscopy are a challenge to establishing cancer screening/early detection programs in low-resource settings. Improvements in performance and declining costs have led to the availability of optoelectronic components, which can be used to develop low-cost diagnostic imaging devices for use at the point-of-care. Here, we demonstrate a fiber-optic fluorescence microscope using a consumer-grade camera for in vivo cellular imaging. METHODS: The fiber-optic fluorescence microscope includes an LED light, an objective lens, a fiber-optic bundle, and a consumer-grade digital camera. The system was used to image an oral cancer cell line labeled with 0.01% proflavine. A human tissue specimen was imaged following surgical resection, enabling dysplastic and cancerous regions to be evaluated. The oral mucosa of a healthy human subject was imaged in vivo, following topical application of 0.01% proflavine. FINDINGS: The fiber-optic microscope resolved individual nuclei in all specimens and tissues imaged. This capability allowed qualitative and quantitative differences between normal and precancerous or cancerous tissues to be identified. The optical efficiency of the system permitted imaging of the human oral mucosa in real time. CONCLUSION: Our results indicate this device as a useful tool to assist in the identification of early neoplastic changes in epithelial tissues. This portable, inexpensive unit may be particularly appropriate for use at the point-of-care in low-resource settings

Automatic Tumor-Stroma Separation in Fluorescence TMAs Enables the Quantitative High-Throughput Analysis of Multiple Cancer Biomarkers

The upcoming quantification and automation in biomarker based histological tumor evaluation will require computational methods capable of automatically identifying tumor areas and differentiating them from the stroma. As no single generally applicable tumor biomarker is available, pathology routinely uses morphological criteria as a spatial reference system. We here present and evaluate a method capable of performing the classification in immunofluorescence histological slides solely using a DAPI background stain. Due to the restriction to a single color channel this is inherently challenging. We formed cell graphs based on the topological distribution of the tissue cell nuclei and extracted the corresponding graph features. By using topological, morphological and intensity based features we could systematically quantify and compare the discrimination capability individual features contribute to the overall algorithm. We here show that when classifying fluorescence tissue slides in the DAPI channel, morphological and intensity based features clearly outpace topological ones which have been used exclusively in related previous approaches. We assembled the 15 best features to train a support vector machine based on Keratin stained tumor areas. On a test set of TMAs with 210 cores of triple negative breast cancers our classifier was able to distinguish between tumor and stroma tissue with a total overall accuracy of 88%. Our method yields first results on the discrimination capability of features groups which is essential for an automated tumor diagnostics. Also, it provides an objective spatial reference system for the multiplex analysis of biomarkers in fluorescence immunohistochemistry

Effect of elevated PCO2 on optical properties of the coccolithophorid Emiliania huxleyi grown under nitrate limitation

Side scatter and red fluorescence properties of the coccolithophore Emiliania huxleyi were investigated by flow cytometry when NO3-limited continuous cultures were submitted to a CO2 partial pressure (pCO2) increase from 400 to 700 ppm. Cultures renewed at the rate of 0.5 d-1 and were submitted to saturating light level. pCO2 was controlled by bubbling CO2-rich or CO2- free air in the cultures. Most of the analyses were repeated 5 times and the average SD were < 1.6%, 0.1 and 0.2% for counting, fluorescence and side scatter respectively. Considering the possible decalcification induced by the increase of CO2 in the chemostat atmosphere, the maximum variation that can be expected for side scatter is that provided by the coccolith depletion upon acidification of the cell suspension. The acidification induced a large (36%) decrease of the side scatter signal but had no detectable effect on the red fluorescence. A control was run with a non-calcifying species, Dunaliella tertiolecta, where acidification induced no detectable change, both on fluorescence and side scatter. During the time of the experiment, the decline of side scatter in chemostat 1 never approached the potential 36% change observed when coccoliths are fully dissolved. Interestingly, the specific chl a fluorescence of E. huxleyi slightly increased during the period of high CO2 level. At the end of the experiment this increase amounted to a significant 2.8% of the initial signal. Furthermore, it progressed linearly with time over the period of observation. However, the experiment did not last enough to know if the fluorescence increase had already reached its maximum value. The acidification experiment supported the use of side scatter as a relevant parameter to trace potential changes in calcification. Since the estimated 25% decrease in calcification induced by the rise in CO2 atmosphere did not result in dramatic changes in side scatter values, we can conclude that the number of cocoliths and the overall shape and granulosity of cells was not significantly affected by this decrease. Changes must have only affected tiny structure details of the coccoliths which is supported by scanning electron microscopy observations. The small but significant increase of the fluorescence signal can be considered as a physiological response to the CO2 rise. This suggests a more dynamic photosynthetic process that would result in a higher rate of organic matter production providing that the system is not nutrient limited as in the present situation