Emphysema Quantifications With CT Scan: Assessing the Effects of Acquisition Protocols and Imaging Parameters Using...

CT scan has notable potential to quantify the severity and progression of emphysema in patients. Such quantification should ideally reflect the true attributes and pathologic conditions of subjects, not scanner parameters. To achieve such an objective, the effects of the scanner conditions need to be understood so the influence can be mitigated.

How do CT scan imaging parameters affect the accuracy of emphysema-based quantifications and biomarkers?

Twenty anthropomorphic digital phantoms were developed with diverse anatomic attributes and emphysema abnormalities informed by a real COPD cohort. The phantoms were input to a validated CT scan simulator (DukeSim), modeling a commercial scanner (Siemens Flash). Virtual images were acquired under various clinical conditions of dose levels, tube current modulations (TCM), and reconstruction techniques and kernels. The images were analyzed to evaluate the effects of imaging parameters on the accuracy of density-based quantifications (percent of lung voxels with HU < -950 [LAA-950] and 15^th percentile of lung histogram HU [Perc15]) across varied subjects. Paired t tests were performed to explore statistical differences between any two imaging conditions.

The most accurate imaging condition corresponded to the highest acquired dose (100 mAs) and iterative reconstruction (SAFIRE) with the smooth kernel of I31, where the measurement errors (difference between measurement and ground truth) were 35 ± 3 Hounsfield Units (HU), -4% ± 5%, and 26 ± 10 HU (average ± SD), for the mean lung HU, LAA-950, and Perc15, respectively. Without TCM and at the I31 kernel, increase of dose (20 to 100 mAs) improved the lung mean absolute error (MAE) by 4.2 ± 2.3 HU (average ± SD). TCM did not contribute to a systematic improvement of lung MAE.

The results highlight that although CT scan quantification is possible, its reliability is impacted by the choice of imaging parameters. The developed virtual imaging trial platform in this study enables comprehensive evaluation of CT scan methods in reliable quantifications, an effort that cannot be readily made with patient images or simplistic physical phantoms.