Bioconjugated quantum dots (QDs) provide a new class of biological labels for evaluating biomolecular signatures (biomarkers) on intact cells and tissue specimens. In particular, the use of multicolor QD probes in immunohistochemistry is considered one of the most important and clinically relevant applications. At present, however, clinical applications of QD-based immunohistochemistry have achieved only limited success. A major bottleneck is the lack of robust protocols to define the key parameters and steps. Here, we describe our recent experience, preliminary results and detailed protocols for QD-antibody conjugation, tissue specimen preparation, multicolor QD staining, image processing and biomarker quantification. The results demonstrate that bioconjugated QDs can be used for multiplexed profiling of molecular biomarkers, and ultimately for correlation with disease progression and response to therapy. In general, QD bioconjugation is completed within 1 day, and multiplexed molecular profiling takes 1-3 days depending on the number of biomarkers and QD probes used.

Abstract. We present a novel method to track a guidewire in cardiac x-ray video. Using variational calculus, we derive differential equations that deform a spline, subject to intrinsic and extrinsic forces, so that it matches the image data, remains smooth, and preserves an a priori length. We analytically derive these equations from first principles, and show how they include tangential terms, which we include in our model. To address the poor contrast often observed in x-ray video, we propose using phase congruency as an image-based feature. Experimental results demonstrate the success of the method in tracking guidewires in low contrast x-ray video.

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Colorectal cancer, the second leading cause of cancer deaths in the United States, is a molecular disease that is largely lifestyle determined and preventable. While heart disease has been sharply declining, in large part from widespread use of biological measurements that indicate risk ("biomarkers of risk"), such as blood cholesterol, to motivate and guide preventive treatment, colorectal cancer is a disease for which mortality rates have changed little and for which there have been no biomarkers of risk. Based on new knowledge about the molecular basis of colorectal cancer we developed and validated a panel of treatable biomarkers of risk that can be measured in rectal biopsies using automated immunohistochemistry and semi-automated image analysis. The methodology is now being made practical for clinical application through the use of 1) quantum dots, so that all of the biomarkers can be detected simultaneously on the same histologic sections (i.e., multiplexed), and 2) novel, automated image analysis algorithms to measure the quantities and tissue distributions of the biomarkers. Herein we summarize our methods, results, current directions, and progress.

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We present an LED light source for use with standard clinical endoscopes to enable visualization of tissues labeled with quantum dots (QDs). QD-assisted endoscopy may improve the outcome of surgical endoscopic procedures by identifying specific tissue types. QDs offer several advantages over current fluorescent stains due to their high target selectivity, long-lasting fluorescence, large excitation and narrow emission bands, and multiplexing capabilities. The prototype presented is compact, modular in design, and was built at low cost making it competitive with commercially available light sources. The device's efficiency is evaluated by measuring light intensity at discreet locations and by successfully illuminating a chicken tissue sample non-specifically labeled with a 250nM or 500nM QD solution. Ultimately, this device serves as a step towards incorporating QDs into real time, image-guided surgical procedures.

Microtubules are dynamic polymers that rapidly transition between states of growth, shortening, and pause. These dynamic events are critical for basic cellular processes, especially cell division. Typically, these events are quantified by imaging microtubule movements over time, which results in large data sets that require rigorous quantitative analysis. In most cases, these analyses are performed manually by the researcher. This process is both tedious and prone to error; thus an efficient and reliable computer-assisted quantification system would provide a rapid approach, suitable for high-throughput data analysis. In this paper, we describe methods to automatically segment and track microtubule movements. Our method is a snake based method [1]. Instead of a closed contour, we use an open contour to track individual microtubule. We redefine some of the internal energy terms specifically for open snake. A new external energy term for locating the end points of a microtubule is also defined. Testing is done using simulated images and untreated MCF-7 breast cancer cell lines as well as cells treated with the microtubule-targeting chemotherapeutic agent, Taxol.