Automatic microtubule tracking for QD-Based in vivo cell imaging and drug efficacy study

Microtubules (MT) are dynamic polymers that rapidly transition between states of growth, shortening, and pause. These dynamic events are critical for many microtubule functions such as intracellular trafficking and signaling. In addition, cancer chemotherapy drugs that target microtubules, such as the taxanes and the vinca alkaloids, are known to suppress microtubule dynamics at low doses, leading to mitotic arrest and cell death. Quantification of microtubule dynamics can be used as a read-out of anticancer-drug activity and can be a surrogate marker of drug sensitivity/resistance. The emerging nanotechnology such as quantum dots has provided properties such as less photo bleaching, higher probe imaging intensity, better specificity and sensitivity, which finally makes visualizing subcellular events over long enough time a possibility. But it also results in big increase in data acquisition. The traditional way of annotating MT manually is becoming a daunting task. Thus, the goal is to research and develop an efficient, reliable, and rapid MT tracking. In this paper, we describe active contour-based [1] tracking methods to automatically track MT. We redefine the internal energy terms specifically for open snake, and examine different external energy terms for locating the end tips of a microtubule. This algorithm has been validated using simulated images, images of untreated MCF-7 breast cancer cells, and image of cells treated with the microtubule-targeting chemotherapeutic agent, Taxol.