The article in Nature shows how imaging of the growth and progression of cancer cells can be accomplished.
As they state:
First used by cancer biologists in the late 1990s, intravital imaging
involves focusing powerful microscopes directly onto exposed tissue in a
live, anaesthetized mouse. More labs have adopted intravital imaging as
technological improvements have made it possible to peer further into
tissue — now as many as 20 cells deep — and to tease out fainter
signals. A growing library of molecular markers has given researchers
the ability to visualize up to eight different kinds of cells and
structures, including various immune-system cells and the endothelial
cells that line blood vessels.
They then state:
As intravital imaging of cancer has matured, the field has moved
beyond eye-catching films and has begun to generate quantitative data
detailing, for example, the speed and direction of moving cells. Such
data allow researchers to construct and refine mathematical models of
cell behaviour. These could predict, for example, how tumour cells
invade tissues, says Friedl.But generating
such quantitative data is difficult and time-consuming: analysing the
movies can take up to 15 times longer than making them...
We have argued that such data collection could best be accomplished in the context of having a model and then estimating the model parameters and also modifying the model accordingly.
It will be of significant interest to see this area progress. Yet with so many data collection projects having a data analysis methodology is essential.