There is a critical gap in the reliability of anisotropic diffusion magnetic resonance imaging (AdMRI). This gap can be filled by using a ground truth measurement capability that allows for the necessary parametric control of water filled geometries of tubes at the micron scale that can produce paths representative of the millions of axons across centimeters in brain tract trajectories. Diffusion Tensor Imaging (DTI) publications report clinically significant systematic error that confounds accurate quantitative assessments across instruments and time. Reference phantoms that provide exact error metrics will advance MRI biophysics science and clinical quantitative accuracy. Correction algorithms using reference data can reduce systematic measurement error, enabling accurate reproducible measurement and provide cross scanner norms for AdMRI pathology. This project will deliver the first viable AdMRI phantom ?ground truth? using ?Taxons?? (textile axon shaped nanotubes), invented by this team, and apply advanced bi-component polymer nanoscale production methods to create structures matched to human tissue histology. In doing this we will deliver axon scale taxons at 800 nanometer diameter, with a packing density of one million taxons per mm2, matched to actual human corpus callosum axon measurements. In Phase I we proposed and delivered taxons with 12 micron inner diameter tubes with a packing density of 1241 per mm2 that could be filled with water and produce FA measurement in the human tissue range. We actually ?over- delivered?, exceeding a packing density of 1,000,000 per mm2 covering the human axonal tissue range. We can now precisely parametrically control the diameters, packing density, restricted/hindered, and isotropic water fractions to test and improve leading compartmental models of diffusion. We created a fasciculus routing machine that can, at viable cost, create human scale fasciculus routes matched to human tissue, such as the optic system eye to LGN, of 20 million routed taxons. The 1 to 1 scale taxonal network phantoms quantify dMRI measurement accuracy for each taxon path with 100 micron path precision along the trajectory. We scanned the phase I phantoms at ten sites. We established in empirical studies that there is substantial systematic, cross instrument and measurement error (e.g., 5x the TBI effect size), that the error is stable, and can be corrected for (removed 94% of systematic error). Phase II of this project will: 1) provide the first AdMRI phantom for ground truth measurement to quantify dMRI biophysics, spatial homogeneity, and routing precision; 2) provide fully automated quantification of accuracy and repeatability of measurement; 3) assess AdMRI precision of 20+ sites, quantifying measurement error at 1.5, 3, 7, 9.4 and 14T field strength; and4) develop a set of routing phantoms (Eye>LGN> V1, spinal cord and cortical tracts). These phantoms and/or subcomponents will be measured with non-MRI methods (confocal & electron microscope) using NIST traceable measurements. Researchers and center directors involved in Phase I scanning and reviewing of the results were very positive, with 30+ sites offering free scanning time to use the phantom, and to utilize the resulting quality assurance reports. Radiology has had phantom based pivotal successes (i.e., CT Hounsfield phantoms in the 1990s). This project will deliver a quantitative AdMRI phantom, enabling MRI metrics to become accurate across vendors and time implementing quantitative quality assurance (QQA).
With no standard for accuracy, the field of MRI imaging has serious concerns about the accuracy of diffusion imaging precision to produce anatomically correct maps of known anatomy. This project will advance the quality and speed of MRI diffusion imaging to provide an anatomically accurate map of brain connectivity, providing quantitative calibration of MRI scans for white matter pathology impacting over 10 million US residents annually for disorders including brain trauma, tumors, developmental disorders, and neurodegenerative disorders at an economic cost of over $80 billion. It will also provide the first viable ground truth calibration of anisotropic diffusion to calibrate US connectome-based imaging with over $316 million dollars of research effort supported by current NIH and Department of Defense research programs.
