Limitations on the number of unique protein and DNA molecules that can be characterized microscopically in a single tissue specimen impede advances in understanding the biological basis of health and disease. Here we present a multiplexed fluorescence microscopy method (MxIF) for quantitative, single-cell, and subcellular characterization of multiple analytes in formalin-fixed paraffinembedded tissue. Chemical inactivation of fluorescent dyes after each image acquisition round allows reuse of common dyes in iterative staining and imaging cycles. The mild inactivation chemistry is compatible with total and phosphoprotein detection, as well as DNA FISH. Accurate computational registration of sequential images is achieved by aligning nuclear counterstain-derived fiducial points. Individual cells, plasma membrane, cytoplasm, nucleus, tumor, and stromal regions are segmented to achieve cellular and subcellular quantification of multiplexed targets. In a comparison of pathologist scoring of diaminobenzidine staining of serial sections and automated MxIF scoring of a single section, human epidermal growth factor receptor 2, estrogen receptor, p53, and androgen receptor staining by diaminobenzidine and MxIF methods yielded similar results. Single-cell staining patterns of 61 protein antigens by MxIF in 747 colorectal cancer subjects reveals extensive tumor heterogeneity, and cluster analysis of divergent signaling through ERK1/2, S6 kinase 1, and 4E binding protein 1 provides insights into the spatial organization of mechanistic target of rapamycin and MAPK signal transduction. Our results suggest MxIF should be broadly applicable to problems in the fields of basic biological research, drug discovery and development, and clinical diagnostics.cancer diagnostics | high-content cellular analysis | image analysis | mTOR | multiplexing

A simple image-based autofocusing scheme for digital microscopy is demonstrated that uses as few as two intermediate images to bring the sample into focus. The algorithm is adapted to a commercial inverted microscope and used to automate brightfield and fluorescence imaging of histopathology tissue sections.

Accurate focusing is a critical challenge of whole slide imaging, primarily due to inherent tissue topography variability. Traditional line scanning and tile-based scanning systems are limited in their ability to acquire a high degree of focus points while still maintaining high throughput. This review examines limitations with first-generation whole slide scanning systems and explores a novel approach that employs continuous autofocus, referred to as independent dual sensor scanning. This “second-generation” concept decouples image acquisition from focusing, allowing for rapid scanning while maintaining continuous accurate focus. The technical concepts, merits, and limitations of this method are explained and compared to that of a traditional whole slide scanning system.

Many pathology laboratories are implementing digital pathology systems. The image resolution and scanning (digitization) magnification can vary greatly between these digital pathology systems. In addition, when digital images are compared with viewing images using a microscope, the cellular features can vary in size. This article highlights differences in magnification and resolution between the conventional microscopes and the digital pathology systems. As more pathologists adopt digital pathology, it is important that they understand these differences and how they ultimately translate into what the pathologist can see and how this may impact their overall viewing experience.

We have described a novel platform for evaluating biomarker co-localization. Expression in multiplexed images is consistent with conventional immunohistochemistry. Automation reduces inconsistencies in staining and positional shifts, while the fluorescent dye cycling approach dramatically expands the number of biomarkers which can be visualized and quantified on a single tissue section.

SummaryThe purpose of this study is to investigate how to scale pixel intensity acquired from one exposure time to another. This is required when comparing grayscale images acquired at different exposure times and other image processing such as autofluorescence removal. Pixel intensity is linear to exposure time as long as images are acquired at the linear range of a camera, but importantly there exists an intercept, which is set by the camera. We termed this intercept as dark pixel intensity, as it is the pixel intensity under conditions of no light and zero exposure time. Dark pixel intensity is determined by camera's readout noise (electron/pixel), gain, and DC offset. Knowing dark pixel intensity, image acquired from one exposure time can be linearly scaled to an image at a different exposure time. Dark pixel intensity can be directly measured by obtaining an image at no light and zero (or minimum) exposure time. It can be also indirectly calculated by capturing images at a series of exposure times. Finally, the prestained and poststained images were acquired at their optimal exposures and autofluorescence was completely removed by normalizing images with the exposure time ratio and dark pixel intensity followed by subtraction.

Purpose: The association hepatocyte growth factor receptor (Met) tyrosine kinase with prognosis and survival in colon cancer is unclear, due in part to the limitation of detection methods used. In particular, conventional chromagenic immunohistochemistry (IHC) has several limitations including the inability to separate compartmental measurements. Measurement of membrane, cytoplasm, and nuclear levels of Met could offer a superior approach to traditional IHC. Experimental Design: Fluorescent-based IHC for Met was done in 583 colon cancer patients in a tissue microarray format. Using curvature and intensity-based image analysis, the membrane, nuclear, and cytoplasm were segmented. Probability distributions of Met within each compartment were determined, and an automated scoring algorithm was generated. An optimal score cutpoint was calculated using 500-fold crossvalidation of a training and test data set. For comparison with conventional IHC, a second array from the same tissue microarray block was 3,3 ¶-diaminobenzidine immunostained for Met. Results: In crossvalidated and univariate Cox analysis, the membrane relative to cytoplasm Met score was a significant predictor of survival in stage I (hazard ratio, 0.16; P = 0.006) and in stage II patients (hazard ratio, 0.34; P V 0.0005). Similar results were found with multivariate analysis. Met in the membrane alone was not a significant predictor of outcome in all patients or within stage. In the 3,3 ¶-diaminobenzidine^stained array, no associations were found with Met expression and survival. Conclusions: These data indicate that the relative subcellular distribution of Met, as measured by novel automated image analysis, may be a valuable biomarker for estimating colon cancer prognosis.

Abstract. We propose a scanning method utilizing dual-cone beams of x-rays to induce luminescence from nanophosphors and reconstruct the three-dimensional distribution of these particles in a biological sample or a small animal. For this purpose, x-rays are focused through a polycapillary lens onto a spot of a few micrometers in size. Such x-ray scanning can be point-wise performed to acquire photon emission data on an object surface. The x-ray-induced luminescence data allow for reliable image reconstruction with high spatial resolution and large imaging depth. We describe several numerical simulation studies to demonstrate the feasibility and merits of the proposed approach.