Contrast-to-noise ratio comparison between X-ray fluorescence emission tomography and computed tomography

We provide a comparison of X-ray fluorescence emission tomography (XFET) and computed tomography (CT) for detecting low concentrations of gold nanoparticles (GNPs) in soft tissue and characterize the conditions under which XFET outperforms energy-integrating CT (EICT) and photon-counting CT (PCCT).

We compared dose-matched Monte Carlo XFET simulations and analytical fan-beam EICT and PCCT simulations. Each modality was used to image a numerical mouse phantom and contrast-depth phantom containing GNPs ranging from 0.05% to 4% by weight in soft tissue. Contrast-to-noise ratios (CNRs) of gold regions were compared among the three modalities, and XFET's detection limit was quantified based on the Rose criterion. A partial field-of-view (FOV) image was acquired for the phantom region containing 0.05% GNPs.

For the mouse phantom, XFET produced superior CNR values ( $\mathrm{CNRs}=24.5$ , 21.6, and 3.4) compared with CT images obtained with both energy-integrating ( $\mathrm{CNR}=4.4$ , 4.6, and 1.5) and photon-counting ( $\mathrm{CNR}=6.5$ , 7.7, and 2.0) detection systems. More generally, XFET outperformed CT for superficial imaging depths ( $<28.75\mathrm{mm}$ ) for gold concentrations at and above 0.5%. XFET's surface detection limit was quantified as 0.44% for an average phantom dose of 16 mGy compatible with in vivo imaging. XFET's ability to image partial FOVs was demonstrated, and 0.05% gold was easily detected with an estimated dose of $\sim 81.6\mathrm{cGy}$ to a localized region of interest.

We demonstrate a proof of XFET's benefit for imaging low concentrations of gold at superficial depths and the feasibility of XFET for in vivo metal mapping in preclinical imaging tasks.