Outside the world or radiology data compression is just about as common as daylight. Look around you. Are you listening to an MP3 player? The files contained on it are compressed music files that contain but a fraction of the electronic information that is available on a compact disc. Yet, compressed music files such as those found on MP3s are the way the world has gone. Can your ears really tell the difference? Some audiophiles think so, but others doubt it. And it really doesn’t matter if there is a difference. It’s just music, no one’s life or career is on the line.
But that’s not so in radiology. Though introduced years ago to combat the rising problem of transferring large imaging datasets throughout a healthcare enterprise, and also to combat mounting storage problems, compression has remained a controversial subject. The first controversy arose from a generally, and perhaps understandably, nervous physician community – comprised of radiologists and radiology informatics specialists, as well as other specialties – that wanted nothing to do with compressed images for fear that they’d get sued if some mistake was made. Compression, they believed, was an easy target for hungry lawyers looking to nail a doctor.
The varying types of compression causing the stir basically break down into two forms. There’s “lossless” compression which decreases the size of a file by 2:1 to 4:1. This level of compression is not that substantial, but the benefit is that the image is then restored to full fidelity once decompressed. The more common form, known as “lossy,” is able to compress data far more but it does not restore images back to the original form and depending on the severity, a large amount of data can be lost. The old debate hinges on how much information can be lost so that an image is still considered diagnostic quality?
More recently, other types of solutions have come forward, called “just-in-time” delivery by some, which send large data sets a tiny bit at a time as they are needed at a workstation so a network is not bogged down all at once. This is a highly dynamic sort of technology that might lead some to wonder whether compression is even relevant anymore.
In fact, compression is becoming top of mind because at the SIIM 2007 meeting in Providence, R.I., in June, the organization announced the launch of an accelerated research project to evaluate compression’s uses in radiology. Results of the study are expected by early next year. The SIIM study will focus especially on what level of compression can be applied to 3D data sets.
Health Imaging & IT sat down with one of the SIIM study participants Eliot Siegel, MD, professor and vice chair of info systems, University of Maryland Dept. of Diagnostic Radiology, and director of imaging at VA Maryland Healthcare Systems. Siegel is a well known advocate for compression in radiology.
The common compression level, generally considered to be of suitable diagnostic quality for interpreting images, is a ratio of 10:1. Yet, that reduction in file size has caused an inflated amount of trouble, you could say.
Image compression has been discussed, Siegel believes, more than any other subject in diagnostic imaging that he is aware of. An enormous amount of space has been given to the subject in journal articles regarding how and when to do it, and despite all of that, it’s surprising how little it is taken advantage of and how much fear there is out there regarding the issue, Siegel says.
He goes so far as to say that “compression is a tiny, tiny drop in the ocean in comparison to lots of things who people don’t question at all [in radiology].” Yet facilities with PACS today that make the decision to use compression must go through piles of paperwork, which must go through legal, just to have the functionality switched on by a PACS vendor.
The fears are simply not justified, according to Siegel. The human visual system is “pretty resilient” when viewing compressed images, which VA Maryland studies have proven, and in instances of 10:1 compression, the human eye cannot tell a difference.
However, the same cannot be said for computer systems such as computer-aided detection (CAD) that need to look at the pixel information in images to work effectively. So, it’s not yet clear what impact compression would have on those systems, according to the research at VA Maryland.
Yet, despite all of the research understandings that still abound. “The thing that most people don’t