Accuracy of emphysema quantification performed with reduced numbers of CT sections

Quantitative Computed Tomography Classification of Lung Nodules: Initial Comparison of 2- and 3-Dimensional Analysis

OBJECTIVE

The aim of this study was to compare the performance of 2- (2D) and 3-dimensional (3D) quantitative computed tomography (CT) methods for classifying lung nodules as lung cancer, metastases, or benign.

METHODS

Using semiautomated software and computerized analysis, we analyzed more than 50 quantitative CT features of 96 solid nodules in 94 patients, in 2D from a single slice and in 3D from the entire nodule volume. Multivariable logistic regression was used to classify nodule types. Model performance was assessed by the area under the receiver operating characteristic curve (AUC) using leave-one-out cross-validation.

RESULTS

The AUC for distinguishing 53 primary lung cancers from 18 benign nodules and 25 metastases ranged from 0.79 to 0.83 and was not significantly different for 2D and 3D analyses (P = 0.29-0.78). Models distinguishing metastases from benign nodules were statistically significant only by 3D analysis (AUC = 0.84).

CONCLUSIONS

Three-dimensional CT methods did not improve discrimination of lung cancer, but may help distinguish benign nodules from metastases.

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.

Multivariate compensation of quantitative pulmonary emphysema metric variation from low-dose, whole-lung CT scans

OBJECTIVE

Emphysema is a disease of the lung characterized by the destruction of the alveolar sac walls. Several quantitative densitometric measures of emphysema from wholelung CT have been proposed for evaluating disease severity and progression. However, a concern with these quantitative measures has been the large interscan variability observed during longitudinal studies of emphysema. To account for and reduce inherent measure variability, this work implements and evaluates the use of a multivariate random-effects model for correcting longitudinal variation in densitometric scores of emphysema due to inspiration.

MATERIALS AND METHODS

The method of multivariate compensation was validated on three of the most commonly reported densitometric measures of emphysema: the emphysema index, histogram percentile, and fractal dimension. Two short-interval, zero-change datasets, one for model development (n = 105) and one for validation (n = 106), were retrospectively identified and used to ensure that all variation was caused by inherent measure variability.

RESULTS

A statistically significant (F test, p < 0.001) reduction of 42.40% in measurement limits of agreement could be obtained after model application, with compensated emphysema metric differences showing 31-33% of the variance compared with uncompensated metric variance.

CONCLUSION

Compensation was still effective when the trained model was applied to the second validation dataset. Multivariate compensation was found to be useful in reducing interscan measurement variability and should be applied to future longitudinal studies of emphysema.

Equating quantitative emphysema measurements on different CT image reconstructions

PURPOSE

To mathematically model the relationship between CT measurements of emphysema obtained from images reconstructed using different section thicknesses and kernels and to evaluate the accuracy of the models for converting measurements to those of a reference reconstruction.

METHODS

CT raw data from the lung cancer screening examinations of 138 heavy smokers were reconstructed at 15 different combinations of section thickness and kernel. An emphysema index was quantified as the percentage of the lung with attenuation below -950 HU (EI950). Linear, quadratic, and power functions were used to model the relationship between EI950 values obtained with a reference 1 mm, medium smooth kernel reconstruction and values from each of the other 14 reconstructions. Preferred models were selected using the corrected Akaike information criterion (AICc), coefficients of determination (R2), and residuals (conversion errors), and cross-validated by a jackknife approach using the leave-one-out method.

RESULTS

The preferred models were power functions, with model R2 values ranging from 0.949 to 0.998. The errors in converting EI950 measurements from other reconstructions to the 1 mm, medium smooth kernel reconstruction in leave-one-out testing were less than 3.0 index percentage points for all reconstructions, and less than 1.0 index percentage point for five reconstructions. Conversion errors were related in part to image noise, emphysema distribution, and attenuation histogram parameters. Conversion inaccuracy related to increased kernel sharpness tended to be reduced by increased section thickness.

CONCLUSIONS

Image reconstruction-related differences in quantitative emphysema measurements were successfully modeled using power functions.