Inter-scan repeatability of CT-based lung densitometry in the surveillance of emphysema in a lung cancer screening setting

Lung densitometry: why, how and when

Lung densitometry assesses with computed tomography (CT) the X-ray attenuation of the pulmonary tissue which reflects both the degree of inflation and the structural lung abnormalities implying decreased attenuation, as in emphysema and cystic diseases, or increased attenuation, as in fibrosis. Five reasons justify replacement with lung densitometry of semi-quantitative visual scales used to measure extent and severity of diffuse lung diseases: (I) improved reproducibility; (II) complete vs. discrete assessment of the lung tissue; (III) shorter computation times; (IV) better correlation with pathology quantification of pulmonary emphysema; (V) better or equal correlation with pulmonary function tests (PFT). Commercially and open platform software are available for lung densitometry. It requires attention to technical and methodological issues including CT scanner calibration, radiation dose, and selection of thickness and filter to be applied to sections reconstructed from whole-lung CT acquisition. Critical is also the lung volume reached by the subject at scanning that can be measured in post-processing and represent valuable information per se. The measurements of lung density include mean and standard deviation, relative area (RA) at -970, -960 or -950 Hounsfield units (HU) and 1st and 15th percentile for emphysema in inspiratory scans, and RA at -856 HU for air trapping in expiratory scans. Kurtosis and skewness are used for evaluating pulmonary fibrosis in inspiratory scans. The main indication for lung densitometry is assessment of emphysema component in the single patient with chronic obstructive pulmonary diseases (COPD). Additional emerging applications include the evaluation of air trapping in COPD patients and in subjects at risk of emphysema and the staging in patients with lymphangioleiomyomatosis (LAM) and with pulmonary fibrosis. It has also been applied to assess prevalence of smoking-related emphysema and to monitor progression of smoking-related emphysema, alpha1 antitrypsin deficiency emphysema, and pulmonary fibrosis. Finally, it is recommended as end-point in pharmacological trials of emphysema and lung fibrosis.

Reproducibility of airway luminal size in asthma measured by HRCT

Brown RH, Henderson RJ, Sugar EA, Holbrook JT, Wise RA, on behalf of the American Lung Association Airways Clinical Research Centers. Reproducibility of airway luminal size in asthma measured by HRCT. J Appl Physiol 123: 876-883, 2017. First published July 13, 2017; doi:10.1152/japplphysiol.00307.2017.-High-resolution CT (HRCT) is a well-established imaging technology used to measure lung and airway morphology in vivo. However, there is a surprising lack of studies examining HRCT reproducibility. The CPAP Trial was a multicenter, randomized, three-parallel-arm, sham-controlled 12-wk clinical trial to assess the use of a nocturnal continuous positive airway pressure (CPAP) device on airway reactivity to methacholine. The lack of a treatment effect of CPAP on clinical or HRCT measures provided an opportunity for the current analysis. We assessed the reproducibility of HRCT imaging over 12 wk. Intraclass correlation coefficients (ICCs) were calculated for individual airway segments, individual lung lobes, both lungs, and air trapping. The ICC [95% confidence interval (CI)] for airway luminal size at total lung capacity ranged from 0.95 (0.91, 0.97) to 0.47 (0.27, 0.69). The ICC (95% CI) for airway luminal size at functional residual capacity ranged from 0.91 (0.85, 0.95) to 0.32 (0.11, 0.65). The ICC measurements for airway distensibility index and wall thickness were lower, ranging from poor (0.08) to moderate (0.63) agreement. The ICC for air trapping at functional residual capacity was 0.89 (0.81, 0.94) and varied only modestly by lobe from 0.76 (0.61, 0.87) to 0.95 (0.92, 0.97). In stable well-controlled asthmatic subjects, it is possible to reproducibly image unstimulated airway luminal areas over time, by region, and by size at total lung capacity throughout the lungs. Therefore, any changes in luminal size on repeat CT imaging are more likely due to changes in disease state and less likely due to normal variability.NEW & NOTEWORTHY There is a surprising lack of studies examining the reproducibility of high-resolution CT in asthma. The current study examined reproducibility of airway measurements. In stable well-controlled asthmatic subjects, it is possible to reproducibly image airway luminal areas over time, by region, and by size at total lung capacity throughout the lungs. Therefore, any changes in luminal size on repeat CT imaging are more likely due to changes in disease state and less likely due to normal variability.

Standardizing CT lung density measure across scanner manufacturers

PURPOSE

Computed Tomography (CT) imaging of the lung, reported in Hounsfield Units (HU), can be parameterized as a quantitative image biomarker for the diagnosis and monitoring of lung density changes due to emphysema, a type of chronic obstructive pulmonary disease (COPD). CT lung density metrics are global measurements based on lung CT number histograms, and are typically a quantity specifying either the percentage of voxels with CT numbers below a threshold, or a single CT number below which a fixed relative lung volume, nth percentile, falls. To reduce variability in the density metrics specified by CT attenuation, the Quantitative Imaging Biomarkers Alliance (QIBA) Lung Density Committee has organized efforts to conduct phantom studies in a variety of scanner models to establish a baseline for assessing the variations in patient studies that can be attributed to scanner calibration and measurement uncertainty.

METHODS

Data were obtained from a phantom study on CT scanners from four manufacturers with several protocols at various tube potential voltage (kVp) and exposure settings. Free from biological variation, these phantom studies provide an assessment of the accuracy and precision of the density metrics across platforms solely due to machine calibration and uncertainty of the reference materials. The phantom used in this study has three foam density references in the lung density region, which, after calibration against a suite of Standard Reference Materials (SRM) foams with certified physical density, establishes a HU-electron density relationship for each machine-protocol. We devised a 5-step calibration procedure combined with a simplified physical model that enabled the standardization of the CT numbers reported across a total of 22 scanner-protocol settings to a single energy (chosen at 80 keV). A standard deviation was calculated for overall CT numbers for each density, as well as by scanner and other variables, as a measure of the variability, before and after the standardization. In addition, a linear mixed-effects model was used to assess the heterogeneity across scanners, and the 95% confidence interval of the mean CT number was evaluated before and after the standardization.

RESULTS

We show that after applying the standardization procedures to the phantom data, the instrumental reproducibility of the CT density measurement of the reference foams improved by more than 65%, as measured by the standard deviation of the overall mean CT number. Using the lung foam that did not participate in the calibration as a test case, a mixed effects model analysis shows that the 95% confidence intervals are [-862.0 HU, -851.3 HU] before standardization, and [-859.0 HU, -853.7 HU] after standardization to 80 keV. This is in general agreement with the expected CT number value at 80 keV of -855.9 HU with 95% CI of [-857.4 HU, -854.5 HU] based on the calibration and the uncertainty in the SRM certified density.

CONCLUSIONS

This study provides a quantitative assessment of the variations expected in CT lung density measures attributed to non-biological sources such as scanner calibration and scanner x-ray spectrum and filtration. By removing scanner-protocol dependence from the measured CT numbers, higher accuracy and reproducibility of quantitative CT measures were attainable. The standardization procedures developed in study may be explored for possible application in CT lung density clinical data.

The Impact of Sources of Variability on Parametric Response Mapping of Lung CT Scans

Parametric response mapping (PRM) of inspiration and expiration computed tomography (CT) images improves the radiological phenotyping of chronic obstructive pulmonary disease (COPD). PRM classifies individual voxels of lung parenchyma as normal, emphysematous, or nonemphysematous air trapping. In this study, bias and noise characteristics of the PRM methodology to CT and clinical procedures were evaluated to determine best practices for this quantitative technique. Twenty patients of varying COPD status with paired volumetric inspiration and expiration CT scans of the lungs were identified from the baseline COPDGene cohort. The impact of CT scanner manufacturer and reconstruction kernels were evaluated as potential sources of variability in PRM measurements along with simulations to quantify the impact of inspiration/expiration lung volume levels, misregistration, and image spacing on PRM measurements. Negligible variation in PRM metrics was observed when CT scanner type and reconstruction were consistent and inspiration/expiration lung volume levels were near target volumes. CT scanner Hounsfield unit drift occurred but remained difficult to ameliorate. Increasing levels of image misregistration and CT slice spacing were found to have a minor effect on PRM measurements. PRM-derived values were found to be most sensitive to lung volume levels and mismatched reconstruction kernels. As with other quantitative imaging techniques, reliable PRM measurements are attainable when consistent clinical and CT protocols are implemented.

Airflow limitation in chronic obstructive pulmonary disease: ratio and difference of percentage of low-attenuation lung regions in paired inspiratory/expiratory computed tomography

RATIONALE AND OBJECTIVES

The purpose of this study was to analyze the relationship between airflow limitation and two types of computed tomography (CT) measurements: expiratory/inspiratory (E/I) ratio and E/I difference of percentage of low-attenuation lung regions (LAA%).

MATERIALS AND METHODS

Thirty patients who underwent inspiratory and expiratory CT scans were included in this study. The CT data were used to calculate the LAA% E/I ratio and E/I difference. Other types of CT measurements were also obtained, including the E/I ratio and E/I difference of lung volume, mean lung density, standard deviation, skewness, and kurtosis. LAA% was calculated at 20 thresholds (-990 to -800 HU). Pearson's correlation between the measurements and forced expiratory flow in 1 second was used to determine the efficacy of LAA% E/I ratio and E/I difference. P values of <5.88 × 10⁻⁵ were considered statistically significant with Bonferroni correction.

RESULTS

The LAA% E/I ratio and E/I difference significantly correlated with forced expiratory flow in 1 second. The best correlation coefficient for the LAA% E/I ratio was -0.699 (P = 1.75 × 10⁻⁵) and for the LAA% E/I difference was -0.723 (P = 6.53 × 10⁻⁶). The best correlation coefficient for the LAA% E/I difference was stronger than that for the other types of CT measurements.

CONCLUSIONS

The LAA% E/I ratio and E/I difference significantly correlated with airflow limitation in chronic obstructive pulmonary disease.

Repeatability and Sample Size Assessment Associated with Computed Tomography-Based Lung Density Metrics

RATIONALE AND OBJECTIVES

Density-based metrics assess severity of lung disease but vary with lung inflation and method of scanning. The aim of this study was to evaluate the repeatability of single center, CT-based density metrics of the lung in a normal population and assess study sample sizes needed to detect meaningful changes in lung density metrics when scan parameters and volumes are tightly controlled.

MATERIALS AND METHODS

Thirty-seven subjects (normal smokers and non-smokers) gave consent to have randomly assigned repeated, breath-held scans at either inspiration (90% vital capacity: TLC) or expiration (20% vital capacity: FRC). Repeated scans were analyzed for: mean lung density (MLD), 15th percentile point of the density histogram (P15), low attenuation areas (LAA) and alpha (fractal measure of hole size distribution). Using inter-subject differences and previously reported bias, sample size was estimated from month or yearly change in density metrics obtained from published literature (i.e. meaningful change).

RESULTS

Inter-scan difference measurements were small for density metrics (ICC > 0.80) and average ICCs for whole lung alpha-910 and alpha-950 were 0.57 and 0.64, respectively. Power analyses demonstrated that, under the control conditions with minimal extrinsic variation, population sizes needed to detect meaningful changes in density measures for TLC or FRC repeated scans ranged from a few (20-40) to a few hundred subjects, respectively.

CONCLUSION

A meaningful sample size was predicted from this study using volume-controlled normal subjects in a controlled imaging environment. Under proper breath-hold conditions, high repeatability was obtained in cohorts of normal smokers and non-smokers.

Quantitative analysis of emphysema and airway measurements according to iterative reconstruction algorithms: comparison of filtered back projection, adaptive statistical iterative reconstruction and model-based iterative reconstruction

OBJECTIVES

To evaluate filtered back projection (FBP) and two iterative reconstruction (IR) algorithms and their effects on the quantitative analysis of lung parenchyma and airway measurements on computed tomography (CT) images.

METHODS

Low-dose chest CT obtained in 281 adult patients were reconstructed using three algorithms: FBP, adaptive statistical IR (ASIR) and model-based IR (MBIR). Measurements of each dataset were compared: total lung volume, emphysema index (EI), airway measurements of the lumen and wall area as well as average wall thickness. Accuracy of airway measurements of each algorithm was also evaluated using an airway phantom.

RESULTS

EI using a threshold of -950 HU was significantly different among the three algorithms in decreasing order of FBP (2.30 %), ASIR (1.49 %) and MBIR (1.20 %) (P < 0.01). Wall thickness was also significantly different among the three algorithms with FBP (2.09 mm) demonstrating thicker walls than ASIR (2.00 mm) and MBIR (1.88 mm) (P < 0.01). Airway phantom analysis revealed that MBIR showed the most accurate value for airway measurements.

CONCLUSION

The three algorithms presented different EIs and wall thicknesses, decreasing in the order of FBP, ASIR and MBIR. Thus, care should be taken in selecting the appropriate IR algorithm on quantitative analysis of the lung.

KEY POINTS

• Computed tomography is increasingly used to provide objective measurements of intra-thoracic structures. • Iterative reconstruction algorithms can affect quantitative measurements of lung and airways. • Care should be taken in selecting reconstruction algorithms in longitudinal analysis. • Model-based iterative reconstruction seems to provide the most accurate airway measurements.