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

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

BACKGROUND

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.

RESEARCH QUESTION

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

STUDY DESIGN AND METHODS

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 15th percentile of lung histogram HU [Perc15]) across varied subjects. Paired t tests were performed to explore statistical differences between any two imaging conditions.

RESULTS

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.

INTERPRETATION

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.

Quantitative Imaging Metrics for the Assessment of Pulmonary Pathophysiology: An Official American Thoracic Society and Fleischner Society Joint Workshop Report

Multiple thoracic imaging modalities have been developed to link structure to function in the diagnosis and monitoring of lung disease. Volumetric computed tomography (CT) renders three-dimensional maps of lung structures and may be combined with positron emission tomography (PET) to obtain dynamic physiological data. Magnetic resonance imaging (MRI) using ultrashort-echo time (UTE) sequences has improved signal detection from lung parenchyma; contrast agents are used to deduce airway function, ventilation-perfusion-diffusion, and mechanics. Proton MRI can measure regional ventilation-perfusion ratio. Quantitative imaging (QI)-derived endpoints have been developed to identify structure-function phenotypes, including air-blood-tissue volume partition, bronchovascular remodeling, emphysema, fibrosis, and textural patterns indicating architectural alteration. Coregistered landmarks on paired images obtained at different lung volumes are used to infer airway caliber, air trapping, gas and blood transport, compliance, and deformation. This document summarizes fundamental "good practice" stereological principles in QI study design and analysis; evaluates technical capabilities and limitations of common imaging modalities; and assesses major QI endpoints regarding underlying assumptions and limitations, ability to detect and stratify heterogeneous, overlapping pathophysiology, and monitor disease progression and therapeutic response, correlated with and complementary to, functional indices. The goal is to promote unbiased quantification and interpretation of in vivo imaging data, compare metrics obtained using different QI modalities to ensure accurate and reproducible metric derivation, and avoid misrepresentation of inferred physiological processes. The role of imaging-based computational modeling in advancing these goals is emphasized. Fundamental principles outlined herein are critical for all forms of QI irrespective of acquisition modality or disease entity.

Task-based validation and application of a scanner-specific CT simulator using an anthropomorphic phantom

BACKGROUND

Quantitative analysis of computed tomography (CT) images traditionally utilizes real patient data that can pose challenges with replicability, efficiency, and radiation exposure. Instead, virtual imaging trials (VITs) can overcome these hurdles through computer simulations of models of patients and imaging systems. DukeSim is a scanner-specific CT imaging simulator that has previously been validated with simple cylindrical phantoms, but not with anthropomorphic conditions and clinically relevant measurements.

PURPOSE

To validate a scanner-specific CT simulator (DukeSim) for the assessment of lung imaging biomarkers under clinically relevant conditions across multiple scanners using an anthropomorphic chest phantom, and to demonstrate the utility of virtual trials by studying the effects or radiation dose and reconstruction kernels on the lung imaging quantifications.

METHODS

An anthropomorphic chest phantom with customized tube inserts was imaged with two commercial scanners (Siemens Force and Siemens Flash) at 28 dose and reconstruction conditions. A computational version of the chest phantom was used with a scanner-specific CT simulator (DukeSim) to simulate virtual images corresponding to the settings of the real acquisitions. Lung imaging biomarkers were computed from both real and simulated CT images and quantitatively compared across all imaging conditions. The VIT framework was further utilized to investigate the effects of radiation dose (20-300 mAs) and reconstruction settings (Qr32f, Qr40f, and Qr69f reconstruction kernels using ADMIRE strength 3) on the accuracy of lung imaging biomarkers, compared against the ground-truth values modeled in the computational chest phantom.

RESULTS

The simulated CT images matched closely the real images for both scanners and all imaging conditions qualitatively and quantitatively, with the average biomarker percent error of 3.51% (range 0.002%-18.91%). The VIT study showed that sharper reconstruction kernels had lower accuracy with errors in mean lung HU of 84-94 HU, lung volume of 797-3785 cm3 , and lung mass of -800 to 1751 g. Lower tube currents had the lower accuracy with errors in mean lung HU of 6-84 HU, lung volume of 66-3785 cm3 , and lung mass of 170-1751 g. Other imaging biomarkers were consistent under the studied reconstruction settings and tube currents.

CONCLUSION

We comprehensively evaluated the realism of DukeSim in an anthropomorphic setup across a diverse range of imaging conditions. This study paves the way toward utilizing VITs more reliably for conducting medical imaging experiments that are not practical using actual patient images.

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study

OBJECTIVE

Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reconstruction (DLR) method, as well as filtered back projection (FBP), hybrid-type iterative reconstruction (IR), and model-based IR methods, has been clinically used. The purpose of this study was to directly compare lung CT number and airway dimension evaluation capabilities of UHR-CT using different scan modes with those of MDCT with different reconstruction methods as investigated in a lung density and airway phantom design recommended by QIBA.

MATERIALS AND METHODS

Lung CT number, inner diameter (ID), inner area (IA), and wall thickness (WT) were measured, and mean differences between measured CT number, ID, IA, WT, and standard reference were compared by means of Tukey's HSD test between all UHR-CT data and MDCT reconstructed with FBP as 1.0-mm section thickness.

RESULTS

For each reconstruction method, mean differences in lung CT numbers and all airway parameters on 0.5-mm and 1-mm section thickness CTs obtained with SHR and HR modes showed significant differences with those obtained with the NR mode on UHR-CT and MDCT (p < 0.05). Moreover, the mean differences on all UHR-CTs obtained with SHR, HR, or NR modes were significantly different from those of 1.0-mm section thickness MDCTs reconstructed with FBP (p < 0.05).

CONCLUSION

Scan modes and reconstruction methods used for UHR-CT were found to significantly affect lung CT number and airway dimension evaluations as did reconstruction methods used for MDCT.

KEY POINTS

• Scan and reconstruction methods used for UHR-CT showed significantly higher CT numbers and smaller airway dimension evaluations as did those for MDCT in a QIBA phantom study (p < 0.05). • Mean differences in lung CT number for 0.25-mm, 0.5-mm, and 1.0-mm section thickness CT images obtained with SHR and HR modes were significantly larger than those for CT images at 1.0-mm section thickness obtained with MDCT and reconstructed with FBP (p < 0.05). • Mean differences in inner diameter (ID), inner area (IA), and wall thickness (WT) measured with SHR and HR modes on 0.5- and 1.0-mm section thickness CT images were significantly smaller than those obtained with NR mode on UHR-CT and MDCT (p < 0.05).

Influence of Radiation Dose and Reconstruction Kernel on Fat Fraction Analysis in Dual-energy CT: A Phantom Study

BACKGROUND/AIM

The quantitative evaluation of fat tissue, mainly for the determination of liver steatosis, is possible by using dual-energy computed tomography. Different photon energy acquisitions allow for estimation of attenuation coefficients. The effect of variation in radiation doses and reconstruction kernels on fat fraction estimation was investigated.

MATERIALS AND METHODS

A six-probe-phantom with fat concentrations of 0%, 20%, 40%, 60%, 80%, and 100% were scanned in Sn140/100 kV with radiation doses ranging between 20 and 200 mAs before and after calibration. Images were reconstructed using iterative kernels (I26,Q30,I70).

RESULTS

Fat fractions measured in dual-energy computed tomography (DECT) were consistent with the 20%-stepwise varying actual concentrations. Variation in radiation dose resulted in 3.1% variation of fat fraction. Softer reconstruction kernel (I26) underestimated the fat fraction (-9.1%), while quantitative (Q30) and sharper kernel (I70) overestimated fat fraction (10,8% and 13,1, respectively).

CONCLUSION

The fat fraction in DECT approaches the actual fat concentration when calibrated to the reconstruction kerneö. Variation of radiation dose caused an acceptable 3% variation.

A calibration CT mini-lung-phantom created by 3-D printing and subtractive manufacturing

We describe the creation and characterization of a calibration CT mini‐lung‐phantom incorporating simulated airways and ground‐glass densities. Ten duplicate mini‐lung‐phantoms with Three‐Dimensional (3‐D) printed tubes simulating airways and gradated density polyurethane foam blocks were designed and built. Dimensional accuracy and CT numbers were measured using micro‐CT and clinical CT scanners. Micro‐CT images of airway tubes demonstrated an average dimensional variation of 0.038 mm from nominal values. The five different densities of incorporated foam blocks, simulating ground‐glass, showed mean CT numbers (±standard deviation) of −897.0 ± 1.5, −844.1 ± 1.5, −774.1 ± 2.6, −695.3 ± 1.6, and −351.0 ± 3.7 HU, respectively. Three‐Dimensional printing and subtractive manufacturing enabled rapid, cost‐effective production of ground‐truth calibration mini‐lung‐phantoms with low inter‐sample variation that can be scanned simultaneously with the patient undergoing lung quantitative CT.

FOOTPRINTS study protocol: rationale and methodology of a 3-year longitudinal observational study to phenotype patients with COPD

INTRODUCTION

A better understanding is needed of the different phenotypes that exist for patients with chronic obstructive pulmonary disease (COPD), their relationship with the pathogenesis of COPD and how they may affect disease progression. Biomarkers, including those associated with emphysema, may assist in characterising patients and in predicting and monitoring the course of disease. The FOOTPRINTS study (study 352.2069) aims to identify biomarkers associated with emphysema, over a 3-year period.

METHODS AND ANALYSIS

The FOOTPRINTS study is a prospective, longitudinal, multinational (12 countries), multicentre (51 sites) biomarker study, which has enrolled a total of 463 ex-smokers, including subjects without airflow limitation (as defined by the 2015 Global Initiative for Chronic Obstructive Lung Disease (GOLD) strategy report), patients with COPD across the GOLD stages 1-3 and patients with COPD and alpha1-antitrypsin deficiency. The study has an observational period lasting 156 weeks that includes seven site visits and additional phone interviews. Biomarkers in blood and sputum, imaging data (CT and magnetic resonance), clinical parameters, medical events of special interest and safety are being assessed at regular visits. Disease progression based on biomarker values and COPD phenotypes are being assessed using multivariate statistical prediction models.

ETHICS AND DISSEMINATION

The study protocol was approved by the authorities and ethics committees/institutional review boards of the respective institutions where applicable, which included study sites in Belgium, Canada, Denmark, Finland, Germany, Japan, Korea, Poland, Spain, Sweden, UK and USA; written informed consent has been obtained from all study participants. Ethics committee approval was obtained for all participating sites prior to enrolment of the study participants. The study results will be reported in peer-reviewed publications.

TRIAL REGISTRATION NUMBER

NCT02719184.

Influence of acquisition settings and radiation exposure on CT lung densitometry-An anthropomorphic ex vivo phantom study

Objectives

To systematically evaluate the influence of acquisition settings in conjunction with raw-data based iterative image reconstruction (IR) on lung densitometry based on multi-row detector computed tomography (CT) in an anthropomorphic chest phantom.

Materials and methods

Ten porcine heart-lung explants were mounted in an ex vivo chest phantom shell, six with highly and four with low attenuating chest wall. CT (Somatom Definition Flash, Siemens Healthineers) was performed at 120kV_p and 80kV_p, each combined with current-time products of 120, 60, 30, and 12mAs, and was reconstructed with filtered back projection (FBP) and IR (Safire, Siemens Healthineers). Mean lung density (LD), air density (AD) and noise were measured by semi-automated region-of interest (ROI) analysis, with 120kV_p/120 mAs serving as the standard of reference.

Results

Using IR, noise in lung parenchyma was reduced by ~ 31% at high attenuating chest wall and by ~ 22% at low attenuating chest wall compared to FBP, respectively (p<0.05). IR induced changes in the order of ±1 HU to mean absolute LD and AD compared to corresponding FBP reconstructions which were statistically significant (p<0.05).

Conclusions

Densitometry is influenced by acquisition parameters and reconstruction algorithms to a degree that may be clinically negligible. However, in longitudinal studies and clinical research identical protocols and potentially other measures for calibration may be required.

SPIROMICS Protocol for Multicenter Quantitative Computed Tomography to Phenotype the Lungs

Multidetector row computed tomography (MDCT) is increasingly taking a central role in identifying subphenotypes within chronic obstructive pulmonary disease (COPD), asthma, and other lung-related disease populations, allowing for the quantification of the amount and distribution of altered parenchyma along with the characterization of airway and vascular anatomy. The embedding of quantitative CT (QCT) into a multicenter trial with a variety of scanner makes and models along with the variety of pressures within a clinical radiology setting has proven challenging, especially in the context of a longitudinal study. SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study), sponsored by the National Institutes of Health, has established a QCT lung assessment system (QCT-LAS), which includes scanner-specific imaging protocols for lung assessment at total lung capacity and residual volume. Also included are monthly scanning of a standardized test object and web-based tools for subject registration, protocol assignment, and data transmission coupled with automated image interrogation to assure protocol adherence. The SPIROMICS QCT-LAS has been adopted and contributed to by a growing number of other multicenter studies in which imaging is embedded. The key components of the SPIROMICS QCT-LAS along with evidence of implementation success are described herein. While imaging technologies continue to evolve, the required components of a QCT-LAS provide the framework for future studies, and the QCT results emanating from SPIROMICS and the growing number of other studies using the SPIROMICS QCT-LAS will provide a shared resource of image-derived pulmonary metrics.

Autocalibration method for non-stationary CT bias correction

Computed tomography (CT) is a widely used imaging modality for screening and diagnosis. However, the deleterious effects of radiation exposure inherent in CT imaging require the development of image reconstruction methods which can reduce exposure levels. The development of iterative reconstruction techniques is now enabling the acquisition of low-dose CT images whose quality is comparable to that of CT images acquired with much higher radiation dosages. However, the characterization and calibration of the CT signal due to changes in dosage and reconstruction approaches is crucial to provide clinically relevant data. Although CT scanners are calibrated as part of the imaging workflow, the calibration is limited to select global reference values and does not consider other inherent factors of the acquisition that depend on the subject scanned (e.g. photon starvation, partial volume effect, beam hardening) and result in a non-stationary noise response. In this work, we analyze the effect of reconstruction biases caused by non-stationary noise and propose an autocalibration methodology to compensate it. Our contributions are: 1) the derivation of a functional relationship between observed bias and non-stationary noise, 2) a robust and accurate method to estimate the local variance, 3) an autocalibration methodology that does not necessarily rely on a calibration phantom, attenuates the bias caused by noise and removes the systematic bias observed in devices from different vendors. The validation of the proposed methodology was performed with a physical phantom and clinical CT scans acquired with different configurations (kernels, doses, algorithms including iterative reconstruction). The results confirmed the suitability of the proposed methods for removing the intra-device and inter-device reconstruction biases.

Correcting Nonpathological Variation in Longitudinal Parametric Response Maps of CT Scans in COPD Subjects: SPIROMICS

Small airways disease (SAD) is one of the leading causes of airflow limitations in patients diagnosed with chronic obstructive pulmonary disease (COPD). Parametric response mapping (PRM) of computed tomography (CT) scans allows for the quantification of this previously invisible COPD component. Although PRM is being investigated as a diagnostic tool for COPD, variability in the longitudinal measurements of SAD by PRM has been reported. Here, we show a method for correcting longitudinal PRM data because of non-pathological variations in serial CT scans. In this study, serial whole-lung high-resolution CT scans over a 30-day interval were obtained from 90 subjects with and without COPD accrued as part of SPIROMICS. It was assumed in all subjects that the COPD did not progress between examinations. CT scans were acquired at inspiration and expiration, spatially aligned to a single geometric frame, and analyzed using PRM. By modeling variability in longitudinal CT scans, our method could identify, at the voxel-level, shifts in PRM classification over the 30-day interval. In the absence of any correction, PRM generated serial percent volumes of functional SAD with differences as high as 15%. Applying the correction strategy significantly mitigated this effect with differences ~1%. At the voxel-level, significant differences were found between baseline PRM classifications and the follow-up map computed with and without correction (P <. 01 over GOLD). This strategy of accounting for nonpathological sources of variability in longitudinal PRM may improve the quantification of COPD phenotypes transitioning with disease progression.

Use of MDCT to Assess the Results of Bronchial Thermoplasty

OBJECTIVE

The purpose of this study was to evaluate the use of MDCT to assess response to bronchial thermoplasty treatment for severe persistent asthma.

MATERIALS AND METHODS

MDCT data from 26 patients with severe persistent asthma who underwent imaging before and after bronchial thermoplasty were analyzed retrospectively. Changes in the following parameters were assessed: total lung volume, mean lung density, airway wall thickness, CT air trapping index (attenuation < -856 HU), and expiratory-inspiratory ratio of mean lung density (E/I index). Asthma Quality of Life Questionnaire score changes were also assessed.

RESULTS

Median total lung volumes before and after bronchial thermoplasty were 2668 mL (range, 2226-3096 mL) and 2399 mL (range, 1964-2802 mL; p = 0.08), respectively. Patients also showed a pattern of obstruction improvement in air trapping values (median before thermoplasty, 14.25%; median after thermoplasty, 3.65%; p < 0.001] and in mean lung density values ± SD (before thermoplasty, -702 ± 72 HU; after thermoplasty, -655 ± 66 HU; p < 0.01). Median airway wall thickness also decreased after bronchial thermoplasty (before thermoplasty, 1.5 mm; after thermoplasty, 1.1 mm; p < 0.05). There was a mean Asthma Quality of Life Questionnaire overall score change of 1.00 ± 1.35 (p < 0.001), indicating asthma clinical improvement.

CONCLUSION

Our study showed improvement in CT measurements after bronchial thermoplasty, along with Asthma Quality of Life Questionnaire score changes. Thus, MDCT could be useful for imaging evaluation of patients undergoing this treatment.

The effects of iterative reconstruction and kernel selection on quantitative computed tomography measures of lung density

PURPOSE

To determine the effects of iterative reconstruction (IR) and high-frequency kernels on quantitative computed tomography (qCT) density measures at reduced X-ray dose.

MATERIALS AND METHODS

The COPDGene 2 Phantom (CTP 698, The Phantom Laboratory, Salem, NY) with four embedded lung mimicking foam densities (12lb, 20lb, and 4lb), as well as water, air, and acrylic reference inserts, was imaged using a GE 64 slice CT750 HD scanner in helical mode with four current-time products ranging from 12 to 100 mAs. The raw acquired data were reconstructed using standard (STD - low frequency) and Bone (high frequency) kernels with filtered back projection (FBP), 100% ASiR, and Veo reconstruction algorithms. The reference density inserts were manually segmented using Slicer3D (www.slicer.org), and the mean, standard deviation, and histograms of the segmented regions were generated using Fiji (http://fiji.sc/Fiji) for each reconstruction. Measurements of threshold values placed on the cumulative frequency distribution of voxels determined by these measured histograms at 5%, PD5_phant , and 15%, PD15_phant , (analogous to the relative area below -950 HU (RA-950) and percent density 15 (PD15) in human lung emphysema quantification, respectively), were also performed.

RESULTS

The use of high-resolution kernels in conjunction with ASiR and Veo did not significantly affect the mean Hounsfield units (HU) of each of the density standards (< 4 HU deviation) and current-time products within the phantom when compared with the STD+FBP reconstruction conventionally used in clinical applications. A truncation of the scanner reported HU values at -1024 that shifts the mean toward more positive values was found to cause a systematic error in lower attenuating regions. Use of IR drove convergence toward the mean of measured histograms (~100-137% increase in the number measured voxels at the mean of the histogram), while the combination of Bone+ASiR preserved the standard deviation of HU values about the mean compared to STD+FBP, with the added effect of improved spatial resolution and accuracy in airway measures. PD5_phant and PD15_phant were most similar between the Bone+ASiR and STD+FBP in all regions except those affected by the -1024 truncation artifact.

CONCLUSIONS

Extension of the scanner reportable HU values below the present limit of -1024 will mitigate discrepancies found in qCT lung densitometry in low-density regions. The density histogram became more sharply peaked, and standard deviation was reduced for IR, directly effecting density thresholds, PD5_phant and PD15_phant, placed on the cumulative frequency distribution of each region in the phantom, which serve as analogs to RA-950 and PD15 typically used in lung density quantitation. The combination of high-frequency kernels (Bone) with ASiR mitigates this effect and preserves density measures derived from the image histogram. Moreover, previous studies have shown improved accuracy of qCT airway measures of wall thickness (WT) and wall area percentage (WA%) when using high-frequency kernels in combination with ASiR to better represent airway walls. The results therefore suggest an IR approach for accurate assessment of airway and parenchymal density measures in the lungs.

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.

A controlled statistical study to assess measurement variability as a function of test object position and configuration for automated surveillance in a multicenter longitudinal COPD study (SPIROMICS)

PURPOSE

A test object (phantom) is an important tool to evaluate comparability and stability of CT scanners used in multicenter and longitudinal studies. However, there are many sources of error that can interfere with the test object-derived quantitative measurements. Here the authors investigated three major possible sources of operator error in the use of a test object employed to assess pulmonary density-related as well as airway-related metrics.

METHODS

Two kinds of experiments were carried out to assess measurement variability caused by imperfect scanning status. The first one consisted of three experiments. A COPDGene test object was scanned using a dual source multidetector computed tomographic scanner (Siemens Somatom Flash) with the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) inspiration protocol (120 kV, 110 mAs, pitch = 1, slice thickness = 0.75 mm, slice spacing = 0.5 mm) to evaluate the effects of tilt angle, water bottle offset, and air bubble size. After analysis of these results, a guideline was reached in order to achieve more reliable results for this test object. Next the authors applied the above findings to 2272 test object scans collected over 4 years as part of the SPIROMICS study. The authors compared changes of the data consistency before and after excluding the scans that failed to pass the guideline.

RESULTS

This study established the following limits for the test object: tilt index ≤0.3, water bottle offset limits of [-6.6 mm, 7.4 mm], and no air bubble within the water bottle, where tilt index is a measure incorporating two tilt angles around x- and y-axis. With 95% confidence, the density measurement variation for all five interested materials in the test object (acrylic, water, lung, inside air, and outside air) resulting from all three error sources can be limited to ±0.9 HU (summed in quadrature), when all the requirements are satisfied. The authors applied these criteria to 2272 SPIROMICS scans and demonstrated a significant reduction in measurement variation associated with the test object.

CONCLUSIONS

Three operator errors were identified which significantly affected the usability of the acquired scan images of the test object used for monitoring scanner stability in a multicenter study. The authors' results demonstrated that at the time of test object scan receipt at a radiology core laboratory, quality control procedures should include an assessment of tilt index, water bottle offset, and air bubble size within the water bottle. Application of this methodology to 2272 SPIROMICS scans indicated that their findings were not limited to the scanner make and model used for the initial test but was generalizable to both Siemens and GE scanners which comprise the scanner types used within the SPIROMICS study.

Low-dose lung cancer screening with photon-counting CT: a feasibility study

To evaluate the feasibility of using a whole-body photon-counting detector (PCD) CT scanner for low-dose lung cancer screening compared to a conventional energy integrating detector (EID) system. Radiation dose-matched EID and PCD scans of the COPDGene 2 phantom were acquired at different radiation dose levels (CTDI_vol: 3.0, 1.5, and 0.75 mGy) and different tube voltages (120, 100, and 80 kVp). EID and PCD images were compared for quantitative Hounsfield unit (HU) accuracy, noise levels, and contrast-to-noise ratios (CNR) for detection of ground-glass nodules (GGN) and emphysema. The PCD HU accuracy was better than EID for water at all scan parameters. PCD HU stability for lung, GGN and emphysema regions were superior to EID and PCD attenuation values were more reproducible than EID for all scan parameters (all P  <  0.01), while HUs for lung, GGN and emphysema ROIs changed significantly for EID with decreasing dose (all P  <  0.001). PCD showed lower noise levels at the lowest dose setting at 120, 100 and 80 kVp (15.2  ±  0.3 HU versus 15.8  ±  0.2 HU, P  =  0.03; 16.1  ±  0.3 HU versus 18.0  ±  0.4 HU, P  =  0.003; and 16.1  ±  0.3 HU versus 17.9  ±  0.3 HU, P  =  0.001, respectively), resulting in superior CNR for evaluation of GGNs and emphysema at 100 and 80 kVp. PCD provided better HU stability for lung, ground-glass, and emphysema-equivalent foams at lower radiation dose settings with better reproducibility than EID. Additionally, PCD showed up to 10% less noise, and 11% higher CNR at 0.75 mGy for both 100 and 80 kVp. PCD technology may help reduce radiation exposure in lung cancer screening while maintaining diagnostic quality.

Parenchymal density changes in acute pulmonary embolism: Can quantitative CT be a diagnostic tool? A preliminary study

PURPOSE

Determine the ability of quantitative CT (QCT) in defining parenchymal density changes in acute pulmonary embolism (PE).

MATERIAL & METHODS

Mean lung density (MLD) and percentage distribution values (PDV) were calculated in 34 patients suspected of PE using software application based on computerized volumetric anatomical segmentation.

RESULTS

Total, left, and right MLD differed significantly between emboli positive(n=23) and negative(n=11) groups(p<0.006, p<0.009, p<0.014). PDVs differed between groups (p<0.05) except for LUZ and RLZ. When PE was present in lobe &/segment branches, PDVs were significantly lower except RUZ.

CONCLUSION

QCT is a promising application for defining parenchymal density changes in PE revealing potential functional impact of emboli. This preliminary study suggests QCT could provide added value to CTPA in peripheral PE.

Advances in Imaging and Automated Quantification of Pulmonary Diseases in Non-neoplastic Diseases

Histological examination has always been the gold standard for the detection and quantification of lung remodeling. However, this method has some limitations regarding the invasiveness of tissue acquisition. Quantitative imaging methods enable the acquisition of valuable information on lung structure and function without the removal of tissue from the body; thus, they are useful for disease identification and follow-up. This article reviews the various quantitative imaging modalities used currently for the non-invasive study of chronic obstructive pulmonary disease, asthma, and interstitial lung diseases. Some promising computer-aided diagnosis methods are also described.

Multicentre chest computed tomography standardisation in children and adolescents with cystic fibrosis: the way forward

Progressive cystic fibrosis (CF) lung disease is the main cause of mortality in CF patients. CF lung disease starts in early childhood. With current standards of care, respiratory function remains largely normal in children and more sensitive outcome measures are needed to monitor early CF lung disease. Chest CT is currently the most sensitive imaging modality to monitor pulmonary structural changes in children and adolescents with CF. To quantify structural lung disease reliably among multiple centres, standardisation of chest CT protocols is needed. SCIFI CF (Standardised Chest Imaging Framework for Interventions and Personalised Medicine in CF) was founded to characterise chest CT image quality and radiation doses among 16 participating European CF centres in 10 different countries. We aimed to optimise CT protocols in children and adolescents among several CF centres. A large variety was found in CT protocols, image quality and radiation dose usage among the centres. However, the performance of all CT scanners was found to be very similar, when taking spatial resolution and radiation dose into account. We conclude that multicentre standardisation of chest CT in children and adolescents with CF can be achieved for future clinical trials.

Pulmonary CT and MRI phenotypes that help explain chronic pulmonary obstruction disease pathophysiology and outcomes

Pulmonary x-ray computed tomographic (CT) and magnetic resonance imaging (MRI) research and development has been motivated, in part, by the quest to subphenotype common chronic lung diseases such as chronic obstructive pulmonary disease (COPD). For thoracic CT and MRI, the main COPD research tools, disease biomarkers are being validated that go beyond anatomy and structure to include pulmonary functional measurements such as regional ventilation, perfusion, and inflammation. In addition, there has also been a drive to improve spatial and contrast resolution while at the same time reducing or eliminating radiation exposure. Therefore, this review focuses on our evolving understanding of patient-relevant and clinically important COPD endpoints and how current and emerging MRI and CT tools and measurements may be exploited for their identification, quantification, and utilization. Since reviews of the imaging physics of pulmonary CT and MRI and reviews of other COPD imaging methods were previously published and well-summarized, we focus on the current clinical challenges in COPD and the potential of newly emerging MR and CT imaging measurements to address them. Here we summarize MRI and CT imaging methods and their clinical translation for generating reproducible and sensitive measurements of COPD related to pulmonary ventilation and perfusion as well as parenchyma morphology. The key clinical problems in COPD provide an important framework in which pulmonary imaging needs to rapidly move in order to address the staggering burden, costs, as well as the mortality and morbidity associated with COPD.

Lung density changes with growth and inflation

BACKGROUND

With body growth from childhood, the lungs can enlarge by either increasing the volume of air in the periphery (as would occur with inspiration) or by increasing the number of peripheral acinar units. In the former case, the lung tissue density would decrease with inflation, whereas in the latter case, the lung density would be relatively constant as the lung grows. To address this fundamental structural issue, we measured the CT scan density in human subjects of widely varying size at two different lung volumes.

METHODS

Five hundred one subjects were enrolled in the study. They underwent a chest CT scan at full inspiration and another scan at end expiration. Spirometry, body plethysmography, and diffusing capacity of the lung for carbon monoxide were also measured.

RESULTS

There was a strong correlation between the size of the lungs measured at full inspiration on CT scan and the mean lung density (r = -0.72, P = .001). People with larger lungs had significantly lower mean lung density. These density changes among different subjects overlapped the density changes within subjects at different lung volumes.

CONCLUSIONS

Lung structure in subjects with larger lungs is different from that in subjects with smaller lungs. Tissue volume does not increase in proportion to lung size, as would be required if larger lungs just had more alveoli. These observations suggest that the growth of the lung into adulthood is not accompanied by new alveoli, but rather by enlargement of existing structures. The presence of greater air spaces in larger lungs could impact the occurrence and pathogenesis of spontaneous pneumothorax or COPD.

Effect of Reducing Field of View on Multidetector Quantitative Computed Tomography Parameters of Airway Wall Thickness in Asthma

OBJECTIVE

We reduced the computed tomography (CT)-reconstructed field of view (FOV), increasing pixel density across airway structures and reducing partial volume effects, to determine whether this would improve accuracy of airway wall thickness quantification.

METHODS

We performed CT imaging on a lung phantom and 29 participants. Images were reconstructed at 30-, 15-, and 10-cm FOV using a medium-smooth kernel. Cross-sectional airway dimensions were compared at each FOV with repeated-measures analysis of variance.

RESULTS

Phantom measurements were more accurate when FOV decreased from 30 to 15 cm (P < 0.05). Decreasing FOV further to 10 cm did not significantly improve accuracy. Human airway measurements similarly decreased by decreasing FOV (P < 0.001). Percent changes in all measurements when reducing FOV from 30 to 15 cm were less than 3%.

CONCLUSIONS

Airway measurements at 30-cm FOV are near the limits of CT resolution using a medium-smooth kernel. Reducing reconstructed FOV would minimally increase sensitivity to detect differences in airway dimensions.

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.

Very low-dose (0.15 mGy) chest CT protocols using the COPDGene 2 test object and a third-generation dual-source CT scanner with corresponding third-generation iterative reconstruction software

OBJECTIVES

The purpose of this study was to evaluate the impact of ultralow radiation dose single-energy computed tomographic (CT) acquisitions with Sn prefiltration and third-generation iterative reconstruction on density-based quantitative measures of growing interest in phenotyping pulmonary disease.

MATERIALS AND METHODS

The effects of both decreasing dose and different body habitus on the accuracy of the mean CT attenuation measurements and the level of image noise (SD) were evaluated using the COPDGene 2 test object, containing 8 different materials of interest ranging from air to acrylic and including various density foams. A third-generation dual-source multidetector CT scanner (Siemens SOMATOM FORCE; Siemens Healthcare AG, Erlangen, Germany) running advanced modeled iterative reconstruction (ADMIRE) software (Siemens Healthcare AG) was used.We used normal and very large body habitus rings at dose levels varying from 1.5 to 0.15 mGy using a spectral-shaped (0.6-mm Sn) tube output of 100 kV(p). Three CT scans were obtained at each dose level using both rings. Regions of interest for each material in the test object scans were automatically extracted. The Hounsfield unit values of each material using weighted filtered back projection (WFBP) at 1.5 mGy was used as the reference value to evaluate shifts in CT attenuation at lower dose levels using either WFBP or ADMIRE. Statistical analysis included basic statistics, Welch t tests, multivariable covariant model using the F test to assess the significance of the explanatory (independent) variables on the response (dependent) variable, and CT mean attenuation, in the multivariable covariant model including reconstruction method.

RESULTS

Multivariable regression analysis of the mean CT attenuation values showed a significant difference with decreasing dose between ADMIRE and WFBP. The ADMIRE has reduced noise and more stable CT attenuation compared with WFBP. There was a strong effect on the mean CT attenuation values of the scanned materials for ring size (P < 0.0001) and dose level (P < 0.0001). The number of voxels in the region of interest for the particular material studied did not demonstrate a significant effect (P > 0.05). The SD was lower with ADMIRE compared with WFBP at all dose levels and ring sizes (P < 0.05).

CONCLUSIONS

The third-generation dual-source CT scanners using third-generation iterative reconstruction methods can acquire accurate quantitative CT images with acceptable image noise at very low-dose levels (0.15 mGy). This opens up new diagnostic and research opportunities in CT phenotyping of the lung for developing new treatments and increased understanding of pulmonary disease.

CT reconstruction techniques for improved accuracy of lung CT airway measurement

PURPOSE

To determine the impact of constrained reconstruction techniques on quantitative CT (qCT) of the lung parenchyma and airways for low x-ray radiation dose.

METHODS

Measurement of small airways with qCT remains a challenge, especially for low x-ray dose protocols. Images of the COPDGene quality assurance phantom (CTP698, The Phantom Laboratory, Salem, NY) were obtained using a GE discovery CT750 HD scanner for helical scans at x-ray radiation dose-equivalents ranging from 1 to 4.12 mSv (12-100 mA s current-time product). Other parameters were 40 mm collimation, 0.984 pitch, 0.5 s rotation, and 0.625 mm thickness. The phantom was sandwiched between 7.5 cm thick water attenuating phantoms for a total length of 20 cm to better simulate the scatter conditions of patient scans. Image data sets were reconstructed using STANDARD (STD), DETAIL, BONE, and EDGE algorithms for filtered back projection (FBP), 100% adaptive statistical iterative reconstruction (ASIR), and Veo reconstructions. Reduced (half) display field of view (DFOV) was used to increase sampling across airway phantom structures. Inner diameter (ID), wall area percent (WA%), and wall thickness (WT) measurements of eight airway mimicking tubes in the phantom, including a 2.5 mm ID (42.6 WA%, 0.4 mm WT), 3 mm ID (49.0 WA%, 0.6 mm WT), and 6 mm ID (49.0 WA%, 1.2 mm WT) were performed with Airway Inspector (Surgical Planning Laboratory, Brigham and Women's Hospital, Boston, MA) using the phase congruency edge detection method. The average of individual measures at five central slices of the phantom was taken to reduce measurement error.

RESULTS

WA% measures were greatly overestimated while IDs were underestimated for the smaller airways, especially for reconstructions at full DFOV (36 cm) using the STD kernel, due to poor sampling and spatial resolution (0.7 mm pixel size). Despite low radiation dose, the ID of the 6 mm ID airway was consistently measured accurately for all methods other than STD FBP. Veo reconstructions showed slight improvement over STD FBP reconstructions (4%-9% increase in accuracy). The most improved ID and WA% measures were for the smaller airways, especially for low dose scans reconstructed at half DFOV (18 cm) with the EDGE algorithm in combination with 100% ASIR to mitigate noise. Using the BONE + ASIR at half BONE technique, measures improved by a factor of 2 over STD FBP even at a quarter of the x-ray dose.

CONCLUSIONS

The flexibility of ASIR in combination with higher frequency algorithms, such as BONE, provided the greatest accuracy for conventional and low x-ray dose relative to FBP. Veo provided more modest improvement in qCT measures, likely due to its compatibility only with the smoother STD kernel.

Sinogram Affirmed Iterative Reconstruction (SAFIRE) versus weighted filtered back projection (WFBP) effects on quantitative measure in the COPDGene 2 test object

PURPOSE

Assessing pulmonary emphysema using Quantitative CT of the lung depends on accurate measures of CT density. Sinogram-Affirmed-Iterative-Reconstruction (SAFIRE) is a new approach for reconstructing CT data acquired at significantly lower doses. However, quantitative effects of this method remain unexplored. The authors investigated the effects on the median values of materials in the COPDGene2 test-object as a function of the reconstruction method [weighted filtered back projection (WFBP) versus SAFIRE], test-object size, dose, and material composition using a Siemens SOMATOM Definition FLASH CT scanner.

METHODS

The COPDGene2 test-object contains eight materials; acrylic, water, four foams (20 lb, 12 lb, lung-equivalent, and 4 lb emphysema-equivalent), internal and external-air. The test-object was scanned with three different outer ring sizes, simulating three different body habitus. There is an average size (36 cm) Ring A, large size (40 cm) Ring B, and small size Ring C (30 cm). The CT protocol used 120 kVp, 0.5 s rotation, 1.0 pitch, and a 0.6 slice collimation with progressively decreasing x-ray exposure values, 11.94-0.74 mGy. With a thorax length of 30 cm, the corresponding effective doses would be 5.01-0.31 mSv. The effects of using SAFIRE versus WFBP were assessed using a two tailed t-test for each ring size, material, and dose. Multivariable linear regression was used to evaluate the relative effects of ring size, material composition, dose, and reconstruction method on the measured median value in HU.

RESULTS

SAFIRE versus WFBP, at the largest ring size and two lowest doses there was a significant difference in median values of 4 lb-foam, p<0.01. Using the smallest ring size at the lowest dose level there was a significant difference in the median value of 4 lb-foam, but the effect size was small, 1 HU. There is a significant difference in median values of both internal and external air using both the small and medium size rings at the three lowest dose levels, p<0.05. There are significant differences noted at both high and low dose levels when using the large ring size in the median values of internal and external air when, p<0.05. These effects on 4 lb-foam, inside and outside air are shown to be in part due to truncation effects on the median value since the lowest HU value in the CT scale used is -1024 HU. Multivariable linear regression results demonstrated significant effects on the measured material median value and standard deviation due to ring size, material composition, dose level, and reconstruction method, p<0.05.

CONCLUSIONS

The authors have shown that there is no significant effect on the median values obtained when using WFBP versus SAFIRE in materials with CT density between 120 and -856 HU using three different test-object sizes and CT doses that vary from 11.94 to 0.74 mGy. The authors have demonstrated there are significant effects on median values obtained when using WFBP versus SAFIRE in materials with CT density values between -937 and -1000 HU depending on the ring size and dose used. As expected, there is considerable reduction in image noise (lower standard deviation) using SAFIRE versus WFBP with all ring sizes, doses, and materials in the COPDGene2 test-object.

CT-Definable Subtypes of Chronic Obstructive Pulmonary Disease: A Statement of the Fleischner Society

The purpose of this statement is to describe and define the phenotypic abnormalities that can be identified on visual and quantitative evaluation of computed tomographic (CT) images in subjects with chronic obstructive pulmonary disease (COPD), with the goal of contributing to a personalized approach to the treatment of patients with COPD. Quantitative CT is useful for identifying and sequentially evaluating the extent of emphysematous lung destruction, changes in airway walls, and expiratory air trapping. However, visual assessment of CT scans remains important to describe patterns of altered lung structure in COPD. The classification system proposed and illustrated in this article provides a structured approach to visual and quantitative assessment of COPD. Emphysema is classified as centrilobular (subclassified as trace, mild, moderate, confluent, and advanced destructive emphysema), panlobular, and paraseptal (subclassified as mild or substantial). Additional important visual features include airway wall thickening, inflammatory small airways disease, tracheal abnormalities, interstitial lung abnormalities, pulmonary arterial enlargement, and bronchiectasis.

Variation in the percent of emphysema-like lung in a healthy, nonsmoking multiethnic sample. The MESA lung study

RATIONALE

Computed tomography (CT)-based lung density is used to quantitate the percentage of emphysema-like lung (hereafter referred to as percent emphysema), but information on its distribution among healthy nonsmokers is limited.

OBJECTIVES

We evaluated percent emphysema and total lung volume on CT scans of healthy never-smokers in a multiethnic, population-based study.

METHODS

The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study investigators acquired full-lung CT scans of 3,137 participants (ages 54-93 yr) between 2010-12. The CT scans were taken at full inspiration following the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) protocol. "Healthy never-smokers" were defined as participants without a history of tobacco smoking or respiratory symptoms and disease. "Percent emphysema" was defined as the percentage of lung voxels below -950 Hounsfield units. "Total lung volume" was defined by the volume of lung voxels.

MEASUREMENTS AND MAIN RESULTS

Among 854 healthy never-smokers, the median percent emphysema visualized on full-lung scans was 1.1% (interquartile range, 0.5-2.5%). The percent emphysema values were 1.2 percentage points higher among men compared with women and 0.7, 1.2, and 1.2 percentage points lower among African Americans, Hispanics, and Asians compared with whites, respectively (P < 0.001). Percent emphysema was positively related to age and height and inversely related to body mass index. The findings were similar for total lung volume on CT scans and for percent emphysema defined at -910 Hounsfield units and measured on cardiac scans. Reference equations to account for these differences are presented for never, former and current smokers.

CONCLUSIONS

Similar to lung function, percent emphysema varies substantially by demographic factors and body size among healthy never-smokers. The presented reference equations will assist in defining abnormal values for percent emphysema and total lung volume on CT scans, although validation is pending.

Parametric response mapping monitors temporal changes on lung CT scans in the subpopulations and intermediate outcome measures in COPD Study (SPIROMICS)

RATIONALE AND OBJECTIVES

The longitudinal relationship between regional air trapping and emphysema remains unexplored. We have sought to demonstrate the utility of parametric response mapping (PRM), a computed tomography (CT)-based biomarker, for monitoring regional disease progression in chronic obstructive pulmonary disease (COPD) patients, linking expiratory- and inspiratory-based CT metrics over time.

MATERIALS AND METHODS

Inspiratory and expiratory lung CT scans were acquired from 89 COPD subjects with varying Global Initiative for Chronic Obstructive Lung Disease (GOLD) status at 30 days (n = 13) or 1 year (n = 76) from baseline as part of the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS) clinical trial. PRMs of CT data were used to quantify the relative volumes of normal parenchyma (PRM(Normal)), emphysema (PRM(Emph)), and functional small airways disease (PRM(fSAD)). PRM measurement variability was assessed using the 30-day interval data. Changes in PRM metrics over a 1-year period were correlated to pulmonary function (forced expiratory volume at 1 second [FEV1]). A theoretical model that simulates PRM changes from COPD was compared to experimental findings.

RESULTS

PRM metrics varied by ∼6.5% of total lung volume for PRM(Normal) and PRM(fSAD) and 1% for PRM(Emph) when testing 30-day repeatability. Over a 1-year interval, only PRM(Emph) in severe COPD subjects produced significant change (19%-21%). However, 11 of 76 subjects showed changes in PRM(fSAD) greater than variations observed from analysis of 30-day data. Mathematical model simulations agreed with experimental PRM results, suggesting fSAD is a transitional phase from normal parenchyma to emphysema.

CONCLUSIONS

PRM of lung CT scans in COPD patients provides an opportunity to more precisely characterize underlying disease phenotypes, with the potential to monitor disease status and therapy response.

Variation of densitometry on computed tomography in COPD--influence of different software tools

Objectives

Quantitative multidetector computed tomography (MDCT) as a potential biomarker is increasingly used for severity assessment of emphysema in chronic obstructive pulmonary disease (COPD). Aim of this study was to evaluate the user-independent measurement variability between five different fully-automatic densitometry software tools.

Material and Methods

MDCT and full-body plethysmography incl. forced expiratory volume in 1s and total lung capacity were available for 49 patients with advanced COPD (age = 64±9 years, forced expiratory volume in 1s = 31±6% predicted). Measurement variation regarding lung volume, emphysema volume, emphysema index, and mean lung density was evaluated for two scientific and three commercially available lung densitometry software tools designed to analyze MDCT from different scanner types.

Results

One scientific tool and one commercial tool failed to process most or all datasets, respectively, and were excluded. One scientific and another commercial tool analyzed 49, the remaining commercial tool 30 datasets. Lung volume, emphysema volume, emphysema index and mean lung density were significantly different amongst these three tools (p<0.001). Limits of agreement for lung volume were [−0.195, −0.052l], [−0.305, −0.131l], and [−0.123, −0.052l] with correlation coefficients of r = 1.00 each. Limits of agreement for emphysema index were [−6.2, 2.9%], [−27.0, 16.9%], and [−25.5, 18.8%], with r = 0.79 to 0.98. Correlation of lung volume with total lung capacity was good to excellent (r = 0.77 to 0.91, p<0.001), but segmented lung volume (6.7±1.3 – 6.8±1.3l) were significantly lower than total lung capacity (7.7±1.7l, p<0.001).

Conclusions

Technical incompatibilities hindered evaluation of two of five tools. The remaining three showed significant measurement variation for emphysema, hampering quantitative MDCT as a biomarker in COPD. Follow-up studies should currently use identical software, and standardization efforts should encompass software as well.

Improved CT-based estimate of pulmonary gas trapping accounting for scanner and lung-volume variations in a multicenter asthmatic study

Lung air trapping is estimated via quantitative computed tomography (CT) using density threshold-based measures on an expiration scan. However, the effects of scanner differences and imaging protocol adherence on quantitative assessment are known to be problematic. This study investigates the effects of protocol differences, such as using different CT scanners and breath-hold coaches in a multicenter asthmatic study, and proposes new methods that can adjust intersite and intersubject variations. CT images of 50 healthy subjects and 42 nonsevere and 52 severe asthmatics at total lung capacity (TLC) and functional residual capacity (FRC) were acquired using three different scanners and two different coaching methods at three institutions. A fraction threshold-based approach based on the corrected Hounsfield unit of air with tracheal density was applied to quantify air trapping at FRC. The new air-trapping method was enhanced by adding a lung-shaped metric at TLC and the lobar ratio of air-volume change between TLC and FRC. The fraction-based air-trapping method is able to collapse air-trapping data of respective populations into distinct regression lines. Relative to a constant value-based clustering scheme, the slope-based clustering scheme shows the improved performance and reduced misclassification rate of healthy subjects. Furthermore, both lung shape and air-volume change are found to be discriminant variables for differentiating among three populations of healthy subjects and nonsevere and severe asthmatics. In conjunction with the lung shape and air-volume change, the fraction-based measure of air trapping enables differentiation of severe asthmatics from nonsevere asthmatics and nonsevere asthmatics from healthy subjects, critical for the development and evaluation of new therapeutic interventions.

Effect of inspiration on airway dimensions measured in maximal inspiration CT images of subjects without airflow limitation

OBJECTIVES

To study the effect of inspiration on airway dimensions measured in voluntary inspiration breath-hold examinations.

METHODS

961 subjects with normal spirometry were selected from the Danish Lung Cancer Screening Trial. Subjects were examined annually for five years with low-dose CT. Automated software was utilized to segment lungs and airways, identify segmental bronchi, and match airway branches in all images of the same subject. Inspiration level was defined as segmented total lung volume (TLV) divided by predicted total lung capacity (pTLC). Mixed-effects models were used to predict relative change in lumen diameter (ALD) and wall thickness (AWT) in airways of generation 0 (trachea) to 7 and segmental bronchi (R1-R10 and L1-L10) from relative changes in inspiration level.

RESULTS

Relative changes in ALD were related to relative changes in TLV/pTLC, and this distensibility increased with generation (p < 0.001). Relative changes in AWT were inversely related to relative changes in TLV/pTLC in generation 3--7 (p < 0.001). Segmental bronchi were widely dispersed in terms of ALD (5.7 ± 0.7 mm), AWT (0.86 ± 0.07 mm), and distensibility (23.5 ± 7.7%).

CONCLUSIONS

Subjects who inspire more deeply prior to imaging have larger ALD and smaller AWT. This effect is more pronounced in higher-generation airways. Therefore, adjustment of inspiration level is necessary to accurately assess airway dimensions.

KEY POINTS

Airway lumen diameter increases and wall thickness decreases with inspiration. The effect of inspiration is greater in higher-generation (more peripheral) airways. Airways of generation 5 and beyond are as distensible as lung parenchyma. Airway dimensions measured from CT should be adjusted for inspiration level.

Sources of variation in quantitative computed tomography of the lung

The goal of quantitative analysis of computed tomography (CT) scans is to understand the anatomic structure that is responsible for the physiological function of the lung. The gold standard for structural analysis requires the examination of tissue, which is not practical in most studies. Quantitative CT allows valuable information on lung structure to be obtained without removal of tissue from the body, thereby aiding longitudinal studies on chronic lung diseases. This review briefly discusses CT analysis of the lung and some of the sources of variation that can cause differences in the CT metrics used for analysis of lung disease. Although there are many sources of variation, this review will show that, if the study is properly designed to take into account these variations and if the CT scanner is properly calibrated, valuable information can be obtained from CT scans that should allow us to study the pathogenesis of lung disease and the effect of treatment.

Relationships between airflow obstruction and quantitative CT measurements of emphysema, air trapping, and airways in subjects with and without chronic obstructive pulmonary disease

OBJECTIVE

This study evaluates the relationships between quantitative CT (QCT) and spirometric measurements of disease severity in cigarette smokers with and without chronic obstructive pulmonary disease (COPD).

MATERIALS AND METHODS

Inspiratory and expiratory CT scans of 4062 subjects in the Genetic Epidemiology of COPD (COPDGene) Study were evaluated. Measures examined included emphysema, defined as the percentage of low-attenuation areas≤-950 HU on inspiratory CT, which we refer to as "LAA-950I"; air trapping, defined as the percentage of low-attenuation areas≤-856 HU on expiratory CT, which we refer to as "LAA-856E"; and the inner diameter, inner and outer areas, wall area, airway wall thickness, and square root of the wall area of a hypothetical airway of 10-mm internal perimeter of segmental and subsegmental airways. Correlations were determined between spirometry and several QCT measures using statistics software (SAS, version 9.2).

RESULTS

QCT measurements of low-attenuation areas correlate strongly and significantly (p<0.0001) with spirometry. The correlation between LAA-856E and forced expiratory volume in 1 second (FEV1) and the ratio of FEV1 to forced vital capacity (FVC) (r=-0.77 and -0.84, respectively) is stronger than the correlation between LAA-950I and FEV1 and FEV1/FVC (r=-0.67 and r=-0.76). Inspiratory and expiratory volume changes decreased with increasing disease severity, as measured by the Global Initiative for Chronic Obstructive Pulmonary Disease (GOLD) staging system (p<0.0001). When airway variables were included with low-attenuation area measures in a multiple regression model, the model accounted for a statistically greater proportion of variation in FEV1 and FEV1/FVC (R2=0.72 and 0.77, respectively). Airway measurements alone are less correlated with spirometric measures of FEV1 (r=0.15 to -0.44) and FEV1/FVC (r=0.19 to -0.34).

CONCLUSION

QCT measurements are strongly associated with spirometric results showing impairment in smokers. LAA-856E strongly correlates with physiologic measurements of airway obstruction. Airway measurements can be used concurrently with QCT measures of low-attenuation areas to accurately predict lung function.

Registration-based lung mechanical analysis of chronic obstructive pulmonary disease (COPD) using a supervised machine learning framework

RATIONALE AND OBJECTIVES

This study evaluated the performance of computed tomography (CT)-derived biomechanical based features of lung function and the presence and severity of chronic obstructive pulmonary disease (COPD). It performed well when compared to CT-derived density and textural features of lung function and the presence and severity of COPD.

MATERIALS AND METHODS

A total of 162 subjects (Global Initiative for Chronic Obstructive Lung Disease [GOLD] stages 0-4 and nonsmokers) subjects with CT scan performed at total lung capacity or expiration to functional residual capacity were evaluated. CT-derived biomechanical, density, and textural feature sets were compared to forced expiratory volume in 1 second (FEV1)%, FEV1/forced vital capacity, and total St. George's respiratory questionnaire scores. The ability of these feature sets to assess the presence and severity of COPD was also evaluated. Optimal features are selected by linear forward feature selection and the classification is done using k nearest neighbor learning algorithm.

RESULTS

The proposed biomechanical features showed good correlations with the pulmonary function tests and health status metrics. In COPD versus non-COPD classification, biomechanical feature set achieved an area under the curve (AUC) of 0.85 performing well in comparison to density (AUC = 0.83) and texture (AUC = 0.89) feature sets. Classifying the subjects into the severity of GOLD stage using biomechanical features (AUC = 0.81) performed better than the density- and texture-based feature sets, AUC = 0.76 and 0.73, respectively. The biomechanical features performed better alone than in combination with the other two feature sets.

CONCLUSION

This study shows the effectiveness of CT-derived biomechanical measures in the assessment of airflow obstruction and quality of life in subjects with COPD. CT-derived biomechanical features performed well in assessing the presence and severity of COPD.