TH‐CD‐207B‐11: Multi‐Vendor Phantom Study of CT Lung Density Metrics: Is a Reproducibility of Less Than 1 HU Achievable?

Purpose: To standardize the calibration procedures of CT lung density measurements using low‐density reference foams in a phantom, and to demonstrate a reproducibility of less than 1 HU for lung equivalent foam densities measured across CT vendor platforms and protocols. Methods: A phantom study was conducted on CT scanner models from 4 vendors at 100, 120, and 135/140 kVp and 1.5, 3, and 6 mGy dose settings, using a lung density phantom containing air, water, and 3 reference foams (indirectly calibrated) with discrete densities simulating a 5‐cm slice of the human chest. Customized segmentation software was used to analyze the images and generate a mean HU and variance for each of the density for the 22 vendor/protocols. A 3‐step calibration process was devised to remove a scanner‐dependent parameter using linear regression of the HU value vs the relative electron density. The results were mapped to a single energy (80 keV) for final comparison. Results: The heterogeneity across vendor platforms for each density assessed by a random effects model was reduced by 50% after re‐calibration, while the standard deviation of the mean HU values also improved by about the same amount. The 95% CI of the final HU value was within +/−1 HU for all 3 reference foam densities. For the backing lung foam in the phantom (served as an “unknown”), this CI is +/− 1.6 HU. The kVp and dose settings did not appear to have significant contributions to the variability. Conclusion: With the proposed calibration procedures, the inter‐scanner reproducibility of better than 1 HU is demonstrated in the current phantom study for the reference foam densities, but not yet achieved for a test density. The sources of error are being investigated in the next round of scanning with a certified Standard Reference Material for direct calibration. Fain: research funding from GE Healthcare to develop pulmonary MRI techniques. Hoppel: employee of Toshiba Medical Research Institute USA/financial interest with GE Healthcare. M. Fuld: employee of Siemens Healthcare for medical device equipment and software. This project is supported partially by RSNA QIBA Concept Award (Fain), NIH/NIBIB, HHSN268201300071C (Y).