3-D preclinical imaging on the cheap
InVivo Analytics Inc. got its start during a conversation in the preclinical imaging facility at Columbia University. In 2012, Neal Paragas, an instructor of medicine at the university, was studying how bacterial cells migrate within a host
animal during an infection.
What Paragas really wanted to do was track the number of bacterial cells in order to quantify the infection’s spread. “I knew it wasn’t feasible,” he recalls. But one day, chatting about one of his experiments with Alexander Klose, who ran the small animal optical imaging core at Columbia, Paragas asked if it was feasible anyway. To his surprise, “Klose answered, ‘Yes.’ At that moment, we forged a partnership to count cells in a living animal,” says Paragas, who now is a scientific advisor to InVivo Analytics.
As it happened, Klose had been working on the problem. His advance relies on a geometrically defined animal bed, a calibration cell, and three-dimensional (3-D) optical image reconstruction software that calculates images of light-emitting cells. In an experiment, an infectious bacteria or tumor cell being studied is engineered to contain a gene that emits light. In principle, an optical imager could measure the increasing intensity of light at the tissue surface as a tumor grows or an infection spreads, but it’s not that simple. Tissues absorb and diffuse light, and each kind of tissue has its own unique effect, making it impossible to accurately determine the initial source of light emission.
Using the InVivo Analytics system, known as InVivoPLOT, an anesthetized animal is placed in the system’s frame, which has a 3-D map laid over it. This allows the image analysis to identify the source tissue. “Our system, when the animal is within this frame, identifies the type of tissue that light is passing through and can make adjustments for the light propagation. We normalize the signal according to the tissue type, thus we’re able to get a quantifiable number,” says Paragas.
