NAEOTOM Alpha Photon-Counting CT Scanner

NIH Pandemic-Era Grants

Pandemic Era Grants

2024

Document text

Principal Investigator: ERIC Alfred HOFFMAN
Organization: UNIVERSITY OF IOWA
Fiscal Year: 2024
Award: $2,000,000
Funding agency: NIH Office of the Director

Project Summary/Abstract
This is a request to upgrade our current Siemens SOMATOM Force research energy integrating
CT scanner to a newly released photon-counting CT scanner (Siemens NAEOTOM Alpha). While
we have made great progress in the use of quantitative CT imaging to sub-phenotype lung
disease there are limitations which this new scanner design will eliminate. Beam hardening is a
scanning artifact which makes the lung appear less dense than it actually is. Because the new
scanner directly counts every photon passing through the body and bins them into energy ranges,
by reconstructing the lungs with a narrower photon range (selected for the kV range which best
maximizes tissue contrast) will essentiall eliminate this error. Additionally, because the detection
of photons is a digital process, the noise associated with analogue to digital conversion of light
signals is eliminated, significantly reducing electronic noise. The spatial resolution is considerably
higher and there is a choice of keeping similar dose as previous protocols (which have already
been reduced nearly 10 fold) while taking advantage of the improved spatial resolution, or
significanlty reducing the dose further and keep the same resolution. Because the photons are
captured along with their energy characteristics, the photon count at each location can be binned
into energy ranges, allowing for the seperation of multiple materials such as krypton and
gadolinium for the simultaneous assessment of ventilation and perfusion. Additional contrast
agents are under development to also, simultaneously, tag inflammation. Because of the
improved contrast resolution, we will be able to further reduce the amount of contrast agent used
by as much as 40%. We propose 9 major projects, all associated with either multi-center studies
seeking new phenotypes of lung disease (COPD, Asthma, IPF, PASC (long COVID) etc. , or local
investigations into lung pathologies. The scanner promises to improve the ability to assess airway
wall thickness further into the lung periphery and to make possible the identification and
seperation of arteries and veins.with similar abilities to extend to the lung periphery. Through
deep learning and transfer learning, we propose that these improvement will help advance utility
of existing scanner images as well. Because we are the radiology Center, the scanner not only
allows us to take advantage of the advanced methodology locally, but we will be able to continue
to disseminate newer protocols, keeping the lung community at imaging state-of-the-art. There
are already 7 such scanners delivered to cinical centers within the US and this is expected to
rapidly expand. Thus, the opportunity for research translation.

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