Post-Concussion Neuroimaging Advances, DTI, SWI
Post-Concussion Neuroimaging and Other Thingomometers
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Absence of evidence is not evidence of the absence. It is an old cliché that applies to all logic and science, but is axiomatic in utitlizing evolving post-concussion neuroimaging.. Surprisingly, the old cliché even applies to severe brain injury, not just post-concussion neuroimaging. The percentage of severe brain injuries with negative neuroimaging is getting smaller with each new generation of scanners. Yet, despite each new application of those scanners, there is still a significant minority of coma patients with negative imaging.
The story of one attending neuroradiologist’s dismissal of the junior resident’s argument on this point is a classic:
Resident: How do we know they have brain injury? The CT was negative.
Attending: They are in a coma.
Loss of consciousness is the ultimate footprint of pathology of brain injury, because it tells us the most about how the brain is functioning. The resident who waves the negative CT in the comatose patients face, will enlighten himself no more than the patient.
With that preface, post-concussion neuroimaging advances are moving forward as computer based technologies advance. The reason: post-concussion neuroimaging is computer based. Sadly, neuroimaging is advancing far slower than the computer. Generational shifts (doubling of capacity and speed) in neuroimaging are still decade long. In most other computer based technology, a generation is closer to a 18 months. In the semi-conductor industry there is an axiom called “Moore’s law.” Moore’s law can be reduced to the theory that the capacity of our computing power will double every 2 years. Eric Schmidt the CEO of Google had shortened that to a generation every 18 months. He also claimed that the power of our cellular phones will be 100 times more in 10 years than today. But that prediction was two years ago, so who knows where it is all at now. 
In contrast the 3T scanner for MRI was accepted for clinical use more than half a decade after the 1.5 T scanner. Advances in resolution and a reduction in the “signal to noise” of MRI represent our biggest hope for post-concussion neuroimaging, because the size of the pathology is far smaller than what is seen on CT. Part of the lag in medical innovations in post-concussion neuroimaging is the huge cost of such devices.MRI scanners cost millions of dollars and most of our other electronic devices under a thousand. Part of the justification is that most such devices have to be FDA approved. Still, the medical community has been unacceptably slow to take advantage of the huge leaps of processing capacity that each new generation of computing allows.
- MRI files are still measured in Megabytes not Gibabytes.
- MRI images are still read in black and white not color.
- Post processing is necessary to tease out the most useful of data on a scan, yet the volume of work in the clinical practice of radiology is growing exponentially to the point that less time is spent on the average patient, not more.
An additional fundamental flaw in technological advances in post-concussion neuroimaging is that the careers of radiologists span 40 years. Yet, only a fraction of the radiologist training comes after the finish of residency. That means for 3/4ths of a radiologist career, he will be technologically behind the potential of the machines he uses. Thus, even with the best of our new brain imaging techniques, it will be difficult to find radiologists who understand the technology. This phenomenon gets so bad that often times the old doctors get together and publish guidelines casting doubt on the remarkable advances that are being made. The would be mentors tend to be far behind the best students ability to comprehend. Thus, the clinical judgment to apply the technology, is negatively correlated to the technical understanding of the technology.
Last decade ushered in an exciting time for post-concussion neuroimaging because of the entry of 3 Tesla MRI scanners. Beginning about 2004, 3 Tesla MRI began to be used for clinical diagnosis of mild brain injury. This seemed to offer an exponential increase in the number of abnormal scans post-concussion. But increased field strength did little to change the relative value of scanning in the clinical diagnosis of mild traumatic brain injury. What abnormalities that were found were small. Once the elation at finding any abnormality in a concussion case wore off, the probative value of that small spot, was far less than expected. When an abnormality on a scan is too small to be appreciated in a well lit room, it will not likely change the skeptical decision maker.
As I look forward, I still have hope that technology will force the medical community to acknowledge the existence of the post-concussion syndrome. Yet, if the radiologists can’t take more time to look for the hallmark abnormalities, there will be countless people with identifiable brain damage, who have their scans called “normal.” It isn’t enough to bring in to focus, what has been thought of as an invisible injury. The person looking at that image must slow down the eyes, to see. Post-concussion neuroimaging requires an image by image inquiry. At the pace that we demand of radiologists, that isn’t going to happen.
 The law is named after Intel co-founder Gordon E. Moore, who introduced the concept in a 1965 paper. It has since been used in the semiconductor industry to guide long term planning and to set targets for research and development.
 A moderately priced MRI today can generate 250 shades of grey, many more than MRIs of the previous decade. The interpretation of the scan – the potential for detection of abnormalities – is improved by higher resolution. Thus, with further improvement in technology the ability of doctors to detect abnormalities is improved, right? There are two answers to this question.
No. The average middle-aged radiologist can see 17 shades of grey, 25 at the absolute maximum. Making more and more subtle distinctions in the computer-produced image is pointless if they cannot be seen by the MD interpreting the scan.
Yes. The underlying data is used to create images on MRI, CT, PET and SPECT are all computer animation. The images are based on numeric data generated by the scanner’s detection device in numeric form and then, like a paint by numbers kit, different values of the numbers generate different colors. This technology offers the great advantages if one looks at the numeric data, which provides a highly accurate measure of cell activity in various areas. Sticking with the numbers, one can find subtle differences in the metabolic activity of a healthy area vs. one with a malfunction…say 80% vs. 100%. This difference will be obvious through the analysis of numeric data, but produces only subtle differences in hue, invisible to the eye of the radiologist. Thus, numeric analysis provides greater sensitivity* and greater reliability.
*Varney and Bushnell (1992) found that this type of numeric analysis revealed three times as many abnormalities as did visual interpretation in post-concussion neuroimaging.