MIT
MGH
HMS
LCLN

LABORATORY FOR COMPUTATIONAL LONGITUDINAL NEUROIMAGING (LCLN)

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Image Acquisition

Head Motion and Online Correction
We have demonstrated in [1] that head motion during structural MRI acquisition biases down-stream processing and anatomical measurements, resulting in significant gray matter volume loss with increased motion, even when motion is too small to produce noticeable image artifacts. In view of these results, the interpretation of reported morphometric effects of movement disorders or other conditions with increased motion tendency may need to be revisited: effects may be overestimated when not controlling for head motion. Furthermore, drug studies with hypnotic, sedative, tranquilizing, or neuromuscular-blocking substances may contain spurious effects of reduced atrophy or brain growth simply because they affect motion distinct from true effects of the disease or therapeutic process.
vNavs (short EPI volume navigators, introduced in [2]) provide an estimate of the subject's location in the scanner during acquisition and permit online motion-correction with no extra time requirements. We were able to show in [3] that this approach significantly reduces the motion-induced bias and variance in brain morphometry estimates. It therefore provides an invaluable tool when studying motion disorders and, really, in any situations where the control group exhibits different behaviors in the scanner compared to the experimental group.
Prospective Slice Prescription
In collaboration with industrial partners, we currently develop a tool for prospective slice prescription in longitudinal studies. This will allow acquisition of exactly the same slices (same position and orientation) as in a previous session of the same individual and is expected to greatly increase reliability of, e.g., clinical tumor size estimates as well as reduce partial voluming effects. See, for example, our work in [4] on the effect of different head placement on tumor size estimates, which is especially problematic in thick-sliced clinical images.
Selected Publications (full list):
clustrmaps.com
Martin Reuter - MIT - Cambridge, MA, USA - EMail: reu...@mit.edu
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