Dataset Information

Congenital lung abnormality quantification by computed tomography: The CLAQ method.

ABSTRACT: INTRODUCTION:To date, no consensus has been reached on the optimal management of congenital lung abnormalities, and factors predicting postnatal outcome have not been identified. We developed an objective quantitative computed tomography (CT) scoring method, and assessed its value for clinical decision-making. METHODS:Volumetric CT-scans of all patients born with a congenital lung abnormality between January 1999 and 2018 were assessed. Lung disease was quantified using the newly-developed congenital lung abnormality quantification (CLAQ) scoring method. In 20 equidistant axial slices, cells of a square grid were scored according to the abnormality within. The scored CT parameters were used to predict development of symptoms, and SD scores for spirometry and exercise tolerance (Bruce treadmill test) at 8 years of age. RESULTS:CT-scans of 124 patients with a median age of 5 months were scored. Clinical diagnoses included congenital pulmonary airway malformation (49%), bronchopulmonary sequestration (27%), congenital lobar overinflation (22%), and bronchogenic cyst (1%). Forty-four patients (35%) developed symptoms requiring surgery of whom 28 (22%) patients became symptomatic before a CT-scan was scheduled. Lesional hyperdensity was found as an important predictor of symptom development and decreased exercise tolerance. Using receiver operating characteristic analysis, an optimal cut-off value for developing symptoms was found at 18% total disease. CONCLUSION:CT-quantification of congenital lung abnormalities using the CLAQ method is an objective and reproducible system to describe congenital lung abnormalities on chest CT. The risk for developing symptoms may increase when more than a single lung lobe is affected.

SUBMITTER: Hermelijn SM

PROVIDER: S-EPMC7590128 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Congenital lung abnormality quantification by computed tomography: The CLAQ method.

Hermelijn Sergei M SM Dragt Olivier V OV Bosch Jochem J JJ Hijkoop Annelieke A Riera Luis L Ciet Pierluigi P Wijnen René M H RMH Schnater Johannes Marco JM Tiddens Harm A W M HAWM

Pediatric pulmonology 20200826 11

<h4>Introduction</h4>To date, no consensus has been reached on the optimal management of congenital lung abnormalities, and factors predicting postnatal outcome have not been identified. We developed an objective quantitative computed tomography (CT) scoring method, and assessed its value for clinical decision-making.<h4>Methods</h4>Volumetric CT-scans of all patients born with a congenital lung abnormality between January 1999 and 2018 were assessed. Lung disease was quantified using the newly- ...[more]

PMID: 32808750

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Project description:BackgroundIn vivo high-resolution micro-computed tomography allows for longitudinal image-based measurements in animal models of lung disease. The combination of repetitive high resolution imaging with fully automated quantitative image analysis in mouse models of lung fibrosis lung benefits preclinical research. This study aimed to develop and validate such an automated micro-computed tomography analysis algorithm for quantification of aerated lung volume in mice; an indicator of pulmonary fibrosis and emphysema severity.MethodologyMice received an intratracheal instillation of bleomycin (n = 8), elastase (0.25 U elastase n = 9, 0.5 U elastase n = 8) or saline control (n = 6 for fibrosis, n = 5 for emphysema). A subset of mice was scanned without intervention, to evaluate potential radiation-induced toxicity (n = 4). Some bleomycin-instilled mice were treated with imatinib for proof of concept (n = 8). Mice were scanned weekly, until four weeks after induction, when they underwent pulmonary function testing, lung histology and collagen quantification. Aerated lung volumes were calculated with our automated algorithm.Principal findingsOur automated image-based aerated lung volume quantification method is reproducible with low intra-subject variability. Bleomycin-treated mice had significantly lower scan-derived aerated lung volumes, compared to controls. Aerated lung volume correlated with the histopathological fibrosis score and total lung collagen content. Inversely, a dose-dependent increase in lung volume was observed in elastase-treated mice. Serial scanning of individual mice is feasible and visualized dynamic disease progression. No radiation-induced toxicity was observed. Three-dimensional images provided critical topographical information.ConclusionsWe report on a high resolution in vivo micro-computed tomography image analysis algorithm that runs fully automated and allows quantification of aerated lung volume in mice. This method is reproducible with low inherent measurement variability. We show that it is a reliable quantitative tool to investigate experimental lung fibrosis and emphysema in mice. Its non-invasive nature has the unique benefit to allow dynamic 4D evaluation of disease processes and therapeutic interventions.

Project description:Background: Interstitial lung disease (ILD) is a common complication in patients with systemic sclerosis (SSc), and its diagnosis contributes to early treatment decisions. Purposes: To quantify ILD associated with SSc (SSc-ILD) from chest CT images using an automatic quantification method based on the computation of the weight of interstitial lung opacities. Methods: Ninety-four patients with SSc underwent CT, forced vital capacity (FVC), and carbon monoxide diffusion capacity (DLCO) tests. Seventy-three healthy individuals without radiological evidence of lung disease served as controls. After lung and airway segmentation, the ratio between the weight of interstitial opacities [densities between -500 and +50 Hounsfield units (HU)] and the total lung weight (densities between -1,000 and +50 HU) was used as an ILD indicator (ILD[%] = 100 × [LW(-500 to +50HU)/LW(-1, 000 to +50HU)]). The cutoff of normality between controls and SSc was determined with a receiver operator characteristic curve. The severity of pulmonary involvement in SSc patients was also assessed by calculating Z scores of ILD relative to the average interstitial opacities in controls. Accordingly, SSc-ILD was classified as SSc Limited-ILD (Z score < 3) and SSc Extensive-ILD (Z score ≥ 3 or FVC < 70%). Results: Seventy-eight (83%) SSc patients were classified as presenting SSc-ILD (optimal ILD threshold of 23.4%, 0.83 sensitivity, 0.92 specificity, and 0.94 area under the receiver operator characteristic curve, 95% CI from 0.89 to 0.96, 0.93 positive predictive value, and 0.81 negative predictive value, p < 0.001) and exhibited radiological attenuations compatible with interstitial pneumonia dispersed in the lung parenchyma. Thirty-six (38%) patients were classified as SSc Extensive-ILD (ILD threshold ≥ 29.6% equivalent to a Z score ≥ 3) and 42 (45%) as SSc Limited-ILD. Eighteen (50%) patients with SSc Extensive-ILD presented FVC < 70%, being only five patients classified exclusively based on FVC. SSc Extensive-ILD also presented lower DLCO (57.9 ± 17.9% vs. 73.7 ± 19.8%; p < 0.001) and total lung volume (2,916 ± 674 vs. 4,286 ± 1,136, p < 0.001) compared with SSc Limited-ILD. Conclusion: The proposed method seems to provide an alternative to identify and quantify the extension of ILD in patients with SSc, mitigating the subjectivity of semiquantitative analyzes based on visual scores.

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Project description:BackgroundObjective assessment of metal artifact strength and the effectiveness of metal artifact reduction algorithms in computed tomography requires a quantitative metric. Metrics described in the literature are typically employed to compare the artifact strength in images reconstructed from the same raw data, but their robustness against varying scan conditions and repeated scans over time as it occurs in periodic quality assurance has not been investigated.PurposeA new robust metric for quantifying metal artifacts in computed-tomography images is proposed and compared to other commonly used metrics.MethodsThe proposed artifact metric is based on the location parameter of the Gumbel distribution, described previously in the literature, but normalized to the location parameter in a background region-of-interest to obtain a noise-independent artifact metric. The metric was compared to three other quantitative metal artifact metrics (artifact-index, contrast-to-noise ratio, Gumbel-evaluation method) by evaluating metals artifacts in phantom scans and in clinical images. Robustness of the artifact metrics was evaluated using repeated scans with varying noise and against small variations in the selected regions-of-interest.ResultsThe proposed artifact metric was independent of the underlying image noise and could be reproduced more consistently under slight changes of the region-of-interest within the artifact than the other investigated methods. The coefficient-of-variation was 5.7% on average with varying regions-of-interest in phantom scans and 2.5% in patient scans compared to 9.2% in phantoms scans and 9.9% in patient scans for the next-best performing noise-independent metric. Setup reproducibility was better than 5% and was comparable to the other metrics. The new metric correlated linearly with the artifact strength. The contrast-to-noise ratio, although often used in artifact quantification, was found to be an inadequate metric due to its lack of robustness against minute changes in the position, size, and pixel values of the region-of-interest chosen for calculating the metric and because it showed no correlation with the artifact strength.ConclusionsA new metal artifact metric has been proposed that is robust under changing scan conditions and less sensitive to user-dependent choices of the region-of-interest than other metrics. The new metric is straightforward to calculate and simple to implement in software commonly used for evaluation of medical imaging systems.

Dataset Information

Congenital lung abnormality quantification by computed tomography: The CLAQ method.

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Congenital lung abnormality quantification by computed tomography: The CLAQ method.

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