Chapter 1 – The Basics: Data That Gives Depth to Medical Images
When the term “big data” is used in healthcare and life sciences, there is often an assumption that these millions of petabytes of data are spread fairly evenly across many areas. Yet according to GE Healthcare, 90% of healthcare data is concentrated in one sector: medical imaging. And of that data, 97% goes unused or unanalyzed. Traditionally, when clinical or research radiologists have received images of lesions or tumors to determine the effectiveness of a pharmaceutical or other treatment, their view has been limited to two dimensions – length and width (aka the long/short). As a result, their primary method of evaluation of the progress of that lesion is to use a pair of calipers across the vertical and horizontal axes to determine whether the lesion is growing or changing. That’s like looking at a photo of an iceberg from the top. The reality is lesions and tumors have multiple dimensions, along with thousands of other structural features that define them. Human cancers in particular exhibit strong structural (phenotypic) differences that can be visualized noninvasively by medical imaging. Gaining this view, however, requires seeing below the line.