Follow-up of CT-derived airway wall thickness: Correcting for changes in inspiration level improves reliability

Pompe, Esther; Rikxoort, Eva M. van; Mets, Onno M.; Charbonnier, Jean-Paul; Kuhnigk, Jan-Martin; Koning, Harry J. de; Oudkerk, Matthijs; Vliegenthart, Rozemarijn; Zanen, Pieter; Lammers, Jan‐Willem J.; Ginneken, Bram van; Jong, Pim A. de; Hoesein, Firdaus A. A. Mohamed

doi:10.1016/j.ejrad.2016.09.009

Cited by 8 publications

(6 citation statements)

References 26 publications

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“…The least number of segmented airways was observed in the control protocol variability set; however, this set showed the smallest lung volume at approximately 200 mL less than the remaining scans. It is well known that lung volume has an effect on quantitative density measures with normalizations developed to compensate for differences in volume across breath holds . Therefore, we compared results taken from volumes within the same breath hold; however, variability was still observed within the control variability set despite mechanical enforcement.…”

Section: Discussionmentioning

confidence: 99%

“…It is well known that lung volume has an effect on quantitative density measures with normalizations developed to compensate for differences in volume across breath holds. 43 Therefore, we compared results taken from volumes within the same breath hold; however, variability was still observed within the control variability set despite mechanical enforcement. To minimize this limitation, we used the control and first target volume to acquire difference measures for comparison.…”

Section: Discussionmentioning

confidence: 99%

“…Extrapolation of our results to comparisons across subjects and time points may be minimal, although our findings in this biological model support those of similar studies performed using test objects. 23,39 As a baseline measure of variability, we compared measurements across breath holds; however, no corrections were made to compensate for inspiratory volume differences, 43 which ranged from 1.7 to 2.1 L despite mechanically enforced breath holds. This reflects a significant challenge of consistent inspiratory lung volume for repeated measures, also encountered in clinical studies incorporating quantitative CT measures for lung assessment.…”

Section: Discussionmentioning

confidence: 99%

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Comparison of low‐ and ultralow‐dose computed tomography protocols for quantitative lung and airway assessment

et al. 2017

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Purpose Quantitative computed tomography (CT) measures are increasingly being developed and used to characterize lung disease. With recent advances in CT technologies, we sought to evaluate the quantitative accuracy of lung imaging at low and ultra-low radiation doses with the use of iterative reconstruction (IR), tube current modulation (TCM), and spectral shaping. Methods We investigated the effect of five independent CT protocols reconstructed with IR on quantitative airway measures and global lung measures using an in-vivo large animal model as a human subject surrogate. A control protocol was chosen (NIH-SPIROMICS + TCM) and five independent protocols investigating TCM, low and ultra-low radiation dose, and spectral shaping. For all scans quantitative global parenchymal measurements (mean, median and standard deviation of the parenchymal HU, along with measures of emphysema) and global airway measurements (number of segmented airways and pi10) were generated. In addition, selected individual airway measurements (minor and major inner diameter, wall thickness, inner and outer area, inner and outer perimeter, wall area fraction, and inner equivalent circle diameter) were evaluated. Comparisons were made between control and target protocols using difference and repeatability measures. Results Estimated CT volume dose index (CTDIvol) across all protocols ranged from 7.32 mGy to 0.32 mGy. Low and ultra-low dose protocols required more manual editing and resolved fewer airway branches; yet, comparable pi10 whole lung measures were observed across all protocols. Similar trends in acquired parenchymal and airway measurements were observed across all protocols, with increased measurement differences using the ultra-low dose protocols. However, for small airways (1.9 ± 0.2mm) and medium airways (5.7 ± 0.4mm) the measurement differences across all protocols were comparable to the control protocol repeatability across breath-holds. Diameters, wall thickness, wall area fraction, and equivalent diameter had smaller measurement differences, than area and perimeter measurements. Conclusions In conclusion, the use of IR with low and ultra-low dose CT protocols with CT volume dose indices down to 0.32 mGy maintains selected quantitative parenchymal and airway measurements relevant to pulmonary disease characterization.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Comparison of low‐ and ultralow‐dose computed tomography protocols for quantitative lung and airway assessment

et al. 2017

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“…Several airway abnormalities on chest CT scans correlate with dyspnea, quality of life and functional capacity, and predict lung function decline (Supplemental Table 1) (57,107). Pi10, a measure of the thickness of medium size airways, relates to incident COPD over 3-5 years (108,109) and is sensitive to change over time (110), even over short follow-up periods (111).…”

Section: Lung Imagingmentioning

confidence: 99%

Treatment Trials in Young Patients with Chronic Obstructive Pulmonary Disease and Pre–Chronic Obstructive Pulmonary Disease Patients: Time to Move Forward

Martínez

Agustí

Celli

et al. 2022

Am J Respir Crit Care Med

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Chronic Obstructive Pulmonary Disease is the end-result of a series of dynamic and cumulative gene-environment interactions over a lifetime. The evolving understanding of COPD biology provides novel opportunities for prevention, early diagnosis, and intervention. To advance these concepts we propose therapeutic trials in two major groups of subjects: those "young" individuals with COPD and those with pre-COPD. Given that lungs grow to about 20 years of age and begin to age at approximately 50 years, we consider "young" COPD those patients in the age range of 20-50 years. Pre-COPD relates to individuals of any age who have respiratory symptoms with or without structural and/or functional abnormalities, in the absence of airflow limitation, and who may develop persistent airflow limitation over time. We exclude from the current discussion infants and adolescents because of their unique physiological context and COPD in older adults given their representation in prior randomized clinical trials (RCTs). We highlight the need of RCTs focused on young COPD or Pre-COPD patients to reduce disease progression, providing innovative approaches to identifying and engaging potential study subjects. We detail approaches to RCTs design including potential outcomes such as lung function, patient reported outcomes, exacerbations, lung imaging, mortality, and composite endpoints. We critically review study design components such as statistical powering and analysis, duration of study treatment, and formats to trial structure including platform, basket, and umbrella trials. We provide a call to action for treatment RCTs in (1) young adults with COPD and (2) those with pre-COPD at any age.

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“…Then, a Euclidean distance transform is applied for generating the distance map. The thickness of airway walls is approximately 2 mm, thus, the response range of the DTA term was set to [0, 3] mm. For determining the response to airway walls, a Gaussian function is adopted as the kernel that centers on μ and scales with σ , as follows:

D_{p}^{normalDTA} false(d_{p} false| L_{p} = l false) = \{\begin{matrix} {(- 1)}^{l} \cdot e^{- \frac{{false(d_{p} - μ false)}^{2}}{2 σ^{2}}}, & if 0 < d_{p} < 3 mm \\ 0, & otherwise . \end{matrix}

The neighbor term

V_{p, q} false(L_{p}, L_{q} false)

from Eq.…”

Section: Methodsmentioning

confidence: 99%

Automatic quantitative analysis of pulmonary vascular morphology in CT images

et al. 2019

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PurposeVascular remodeling is a significant pathological feature of various pulmonary diseases, which may be assessed by quantitative computed tomography (CT) imaging. The purpose of this study was therefore to develop and validate an automatic method for quantifying pulmonary vascular morphology in CT images.MethodsThe proposed method consists of pulmonary vessel extraction and quantification. For extracting pulmonary vessels, a graph‐cuts‐based method is proposed which considers appearance (CT intensity) and shape (vesselness from a Hessian‐based filter) features, and incorporates distance to the airways into the cost function to prevent false detection of airway walls. For quantifying the extracted pulmonary vessels, a radius histogram is generated by counting the occurrence of vessel radii, calculated from a distance transform‐based method. Subsequently, two biomarkers, slope α and intercept β, are calculated by linear regression on the radius histogram. A public data set from the VESSEL12 challenge was used to independently evaluate the vessel extraction. The quantitative analysis method was validated using images of a three‐dimensional (3D) printed vessel phantom, scanned by a clinical CT scanner and a micro‐CT scanner (to obtain a gold standard). To confirm the association between imaging biomarkers and pulmonary function, 77 scleroderma patients were investigated with the proposed method.ResultsIn the independent evaluation with the public data set, our vessel segmentation method obtained an area under the receiver operating characteristic (ROC) curve of 0.976. The median radius difference between clinical and micro‐CT scans of a 3D printed vessel phantom was 0.062 ± 0.020 mm, with interquartile range of 0.199 ± 0.050 mm. In the studied patient group, a significant correlation between diffusion capacity for carbon monoxide and the biomarkers, α (R = −0.27, P = 0.018) and β (R = 0.321, P = 0.004), was obtained.ConclusionIn conclusion, the proposed method was validated independently using a public data set resulting in an area under the ROC curve of 0.976 and using a 3D printed vessel phantom data set, showing a vessel sizing error of 0.062 mm (0.16 in‐plane pixel units). The correlation between imaging biomarkers and diffusion capacity in a clinical data set confirmed an association between lung structure and function. This quantification of pulmonary vascular morphology may be helpful in understanding the pathophysiology of pulmonary vascular diseases.

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Follow-up of CT-derived airway wall thickness: Correcting for changes in inspiration level improves reliability

Cited by 8 publications

References 26 publications

Comparison of low‐ and ultralow‐dose computed tomography protocols for quantitative lung and airway assessment

Comparison of low‐ and ultralow‐dose computed tomography protocols for quantitative lung and airway assessment

Treatment Trials in Young Patients with Chronic Obstructive Pulmonary Disease and Pre–Chronic Obstructive Pulmonary Disease Patients: Time to Move Forward

Automatic quantitative analysis of pulmonary vascular morphology in CT images

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