SBIR/STTR Research Award

Advancing and calibrating anisotropic diffusion MR imaging brain connectome with Taxon brain network diffusion phantoms

Award identifier 2ff335ffea10dd225dd85888aecbea4c4c77d6f0ae4fde4faf6c1bb084218276Awarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$1,386,637

Program and phase

SBIR · Phase II

Award year

2019

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Psychology Software Tools, Inc.
Proposal award date
2019-03-15
Contract end date
2021-02-28
UEI
MJEJGMLW3RN6
Solicitation number
PAR18-501
Topic code
106

Research abstract

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 (Eyeandgt;LGNandgt; V1, spinal cord and cortical tracts). These phantoms and/or subcomponents will be measured with non-MRI methods (confocal andamp; 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.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

28 SBIR/STTR records share this UEI (1993–2019). Reported award amounts total $12,487,807. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Health and Human Services, Department of Defense, National Science Foundation

Agency intelligence

Department of Health and Human Services

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.