Ultra-low-dose CT combined with noise reduction techniques for quantification of emphysema in COPD patients: An intra-individual comparison study with standard-dose CT

Abstract Purpose Phantom studies in CT emphysema quantification show that iterative reconstruction and deep learning-based noise reduction (DLNR) allow lower radiation dose. We compared on ultra-low-dose (ULDCT) with without reduction, to standard-dose (SDCT) chronic obstructive pulmonary disease (COPD). Method Forty-nine COPD patients underwent ULDCT (third generation dual-source CT; 70ref-mAs, Sn-filter 100kVp; median CTDIvol 0.38 mGy) SDCT (64-multidetector 40mAs, 120kVp; 3.04 mGy). Scans were reconstructed filtered backprojection (FBP) soft kernel. For ULDCT, we also applied advanced modelled (ADMIRE), levels 1/3/5, DLNR, 1/3/5/9. Emphysema was quantified as Low Attenuation Value percentage (LAV%, ≤-950HU). measures reference standard. Results the dose 84 % than for SDCT. Median extent of 18.6 ULD-FBP 15.4 (inter-quartile range: 11.8–28.4 9.2 %–28.7 %, p = 0.002). Compared SDCT, range limits agreement measure variability 14.4 ULD-FBP, 11.0–13.1 ULD-ADMIRE 10.1–13.9 ULD-DLNR levels. Optimal settings ADMIRE 3 DLNR 3, reducing by 24 27 at slight underestimation (−1.5 −2.9 respectively). Conclusions Ultra-low-dose allows %. State-of-the-art methods resulted Noise (especially 3) reduced up FBP.