The CT's sample volume as an approximate, instrumental measure for density resolution in densitometry of the lung

Optimization of a secondary VOI protocol for lung imaging in a clinical CT scanner

We present a solution to meet an unmet clinical need of an in-situ "close look" at a pulmonary nodule or at the margins of a pulmonary cyst revealed by a primary (screening) chest CT while the patient is still in the scanner. We first evaluated options available on current whole-body CT scanners for high resolution screening scans, including ROI reconstruction of the primary scan data and HRCT, but found them to have insufficient SNR in lung tissue or discontinuous slice coverage. Within the capabilities of current clinical CT systems, we opted for the solution of a secondary, volume-of-interest (VOI) protocol where the radiation dose is focused into a short-beam axial scan at the z position of interest, combined with a small-FOV reconstruction at the xy position of interest. The objective of this work was to design a VOI protocol that is optimized for targeted lung imaging in a clinical whole-body CT system. Using a chest phantom containing a lung-mimicking foam insert with a simulated cyst, we identified the appropriate scan mode and optimized both the scan and recon parameters. The VOI protocol yielded 3.2 times the texture amplitude-to-noise ratio in the lung-mimicking foam when compared to the standard chest CT, and 8.4 times the texture difference between the lung mimicking and reference foams. It improved details of the wall of the simulated cyst and better resolution in a line-pair insert. The Effective Dose of the secondary VOI protocol was 42% on average and up to 100% in the worst-case scenario of VOI positioning relative to the standard chest CT. The optimized protocol will be used to obtain detailed CT textures of pulmonary lesions, which are biomarkers for the type and stage of lung diseases.

Reference standard and statistical model for intersite and temporal comparisons of CT attenuation in a multicenter quantitative lung study

PURPOSE

The purpose of this study was to detect and analyze anomalies between a large number of computed tomography (CT) scanners, tracked over time, utilized to collect human pulmonary CT data for a national multicenter study: chronic obstructive pulmonary disease genetic epidemiology study (COPDGene).

METHODS

A custom designed CT reference standard "Test Object" has been developed to evaluate the relevant differences in CT attenuation between CT scanners in COPDGene. The materials used in the Test Object to assess CT scanner accuracy and precision included lung equivalent foam (-856 HU), internal air (-1000 HU), water (0 HU), and acrylic (120 HU). Nineteen examples of the Test Object were manufactured. Initially, all Test Objects were scanned on the same CT scanner before the Test Objects were sent to the 20 specific sites and 42 individual CT scanners that were used in the study. The Test Objects were scanned over 17 months while the COPDGene study continued to recruit subjects. A mixed linear effect statistical analysis of the CT scans on the 19 Test Objects was performed. The statistical model reflected influence of reconstruction kernels, tube current, individual Test Objects, CT scanner models, and temporal consistency on CT attenuation.

RESULTS

Depending on the Test Object material, there were significant differences between reconstruction kernels, tube current, individual Test Objects, CT scanner models, and temporal consistency. The two Test Object materials of most interest were lung equivalent foam and internal air. With lung equivalent foam, there were significant (p < 0.05) differences between the Siemens B31 (-856.6, ±0.82; mean ± SE) and the GE Standard (-856.6 ± 0.83) reconstruction kernel relative to the Siemens B35 reference standard (-852.5 ± 1.4). Comparing lung equivalent foam attenuation there were also significant differences between CT scanner models (p < 0.01), tube current (p < 0.005), and in temporal consistency (p < 0.005) at individual sites. However, there were no significant effects measurable using different examples of the Test Objects at the various sites compared to the reference scans of the 19 Test Objects. For internal air, significant (p < 0.005) differences were found between all reconstruction kernels (Siemens B31, GE Standard, and Phillips B) compared to the reference standard. There were significant differences between CT models (p < 0.005), and tube current (p < 0.005). There were no significant effects measurable using different examples of the Test Objects at the various sites compared to the reference scans of the 19 Test Objects. Differences, across scanners, between external air and internal air measures in this simple (relative to the in vivo lung) test object varied by as much as 15 HU.

CONCLUSIONS

The authors conclude that the Test Object designed for this study was able to detect significant effects regarding individual CT scanners that altered the CT attenuation measurements relevant to the study that are used to determine lung density. Through an understanding of individual scanners, the Test Object analysis can be used to detect anomalies in an individual CT scanner and to statistically model out scanner differences and individual scanner changes over time in a large multicenter trial.

A low-cost density reference phantom for computed tomography

The authors characterized a commercially available foam composed of polyurethane and polyisocyanurate which is marketed for modeling parts in the aircraft, automotive, and related industries. The authors found that the foam may be suitable for use as a density reference standard in the range below -400 Hounsfield units. This range is coincident with the density of lung tissue. The foam may be helpful in making the diagnosis of lung disease more systematic.

On segmentation of lung parenchyma in quantitative computed tomography of the lung

Our purpose in this study was to investigate the influence of segmentation threshold and number of erosions on parameters used in quantitative computed tomography (CT) of the lung (erosions are shrink operations on the segmented area). Parameters assessed were mean lung density, area of the segmented lung, two percentiles, and the pixel index, which is the relative area of the histogram below -905 Hounsfield Units (HU). We analyzed images of ten emphysematous and ten nonemphysematous patients, that had been scanned at carina level in inspiration and expiration, using sections of 1, 2, 3, 5, and 10 mm in combination with a standard, a smooth, and an ultrasmooth reconstruction kernel. The lungs were segmented using pixel tracing at thresholds of -200, -400, and -600 HU with 0-4 erosions, followed by histogram analysis. The area of the segmented lungs decreased with 0.9%-3.2% per 100 HU decrease in threshold and with 2.2%-3.1% per erosion, dependent on patient group and respiratory status. Estimated mean lung density changed up to 30% by changing the threshold and the number of erosions. The pixel index and the 10th percentile depended only slightly on threshold and number of erosions, but the 90th percentile showed a strong dependence of up to 40%. It is concluded that the segmentation protocol can have a large impact on densitometric parameters and that standardization is mandatory for obtaining comparable results. Ideally a threshold equal to the average of the densities of lung and soft tissue should be used, but -400 HU will do in a limited but common density range (-910 to -790 HU). For densitometry two erosions are recommended, for volumetry zero erosions should be used.