Spatial resolution, noise properties, and detectability index of a deep learning reconstruction algorithm for dual‐energy CT of the abdomen

Abstract Background Iterative reconstruction (IR) has increasingly replaced traditional reconstruction methods in computed tomography (CT). The next paradigm shift in image reconstruction is likely to come from artificial intelligence, with deep learning reconstruction (DLR) solutions already entering the clinic. An enduring disadvantage to IR has been a change in noise texture, which can affect diagnostic confidence. DLR has demonstrated the potential to overcome this issue and has recently become available for dual‐energy CT. Purpose To evaluate the spatial resolution, noise properties, and detectability index of a commercially available DLR algorithm for dual‐energy CT of the abdomen and compare it to single‐energy (SE) CT. Methods An oval 25 cm x 35 cm custom‐made phantom was scanned on a GE Revolution CT scanner (GE Healthcare, Waukesha, WI) at two dose levels (13 and 5 mGy) and two iodine concentrations (8 and 2 mg/mL), using three typical abdominal scan protocols: dual‐energy (DE), SE 80 kV (SE‐80 kV) and SE 120 kV (SE‐120 kV). Reconstructions were performed with three strengths of IR (ASiR‐V: AR0%, AR50%, AR100%) and three strengths of DLR (TrueFidelity: low, medium, high). The DE acquisitions were reconstructed as mono‐energetic images between 40 and 80 keV. The noise power spectrum (NPS), task transfer function (TTF), and detectability index (d’) were determined for the reconstructions following the recommendations of AAPM Task Group 233. Results Noise magnitude reductions (relative to AR0%) for the SE protocols were on average (−29%, −21%) for (AR50%, TF‐M), while for DE‐70 keV were (−28%, −43%). There was less reduction in mean frequency (f av ) for DLR than for IR, with similar results for SE and DE imaging. There was, however, a substantial change in the NPS shape when using DE with DLR, quantifiable by a marked reduction in the peak frequency (f peak ) that was absent in SE mode. All protocols and reconstructions (including AR0%) exhibited slight to moderate shifts towards lower spatial frequencies at the lower dose (<12% in f av ). Spatial resolution was consistently superior for DLR compared to IR for SE but not for DE. All protocols and reconstructions (including AR0%) showed decreased resolution with reduced dose and iodine concentration, with less decrease for DLR compared to IR. DLR displayed a higher d’ than IR. The effect of energy was large: d’ increased with lower keV, and SE‐80 kV had higher d’ than SE‐120 kV. Using DE with DLR could provide higher d’ than SE‐80 kV at the higher dose but not at lower dose. Conclusions DE imaging with DLR maintained spatial resolution and reduced noise magnitude while displaying less change in noise texture than IR. The d’ was also higher with DLR than IR, suggesting superiority in detectability of iodinated contrast. Despite these trends being consistent with those previously established for SE imaging, there were some noteworthy differences. For DE imaging there was no improvement in resolution compared to IR and a change in noise texture. DE imaging with low keV and DLR had superior detectability to SE DLR at the high dose but was not better than SE‐80 kV at low dose.