Modeling Realistic Geometries in Human Intrathoracic Airways

Geometrical models of the airways offer a comprehensive perspective on the complex interplay between lung structure and function. Originating from mathematical frameworks, these models have evolved to include detailed lung imagery, a crucial enhancement that aids in the early detection of morphological changes in the airways, which are often the first indicators of diseases. The accurate representation of airway geometry is crucial in research areas such as biomechanical modeling, acoustics, and particle deposition prediction. This review chronicles the evolution of these models, from their inception in the 1960s based on ideal mathematical constructs, to the introduction of advanced imaging techniques like computerized tomography (CT) and, to a lesser degree, magnetic resonance imaging (MRI). The advent of these techniques, coupled with the surge in data processing capabilities, has revolutionized the anatomical modeling of the bronchial tree. The limitations and challenges in both mathematical and image-based modeling are discussed, along with their applications. The foundation of image-based modeling is discussed, and recent segmentation strategies from CT and MRI scans and their clinical implications are also examined. By providing a chronological review of these models, this work offers insights into the evolution and potential future of airway geometry modeling, setting the stage for advancements in diagnosing and treating lung diseases. This review offers a novel perspective by highlighting how advancements in imaging techniques and data processing capabilities have significantly enhanced the accuracy and applicability of airway geometry models in both clinical and research settings. These advancements provide unique opportunities for developing patient-specific models.

Machine learning-enhanced HRCT analysis for diagnosis and severity assessment in pediatric asthma

OBJECTIVES

Chest high-resolution computed tomography (HRCT) is conditionally recommended to rule out conditions that mimic or coexist with severe asthma in children. However, it may provide valuable insights into identifying structural airway changes in pediatric patients. This study aims to develop a machine learning-based chest HRCT image analysis model to aid pediatric pulmonologists in identifying features of severe asthma.

METHODS

This retrospective case-control study compared children with severe asthma (as defined by ERS/ATS guidelines) to age- and sex-matched controls without asthma, using chest HRCT scans for detailed imaging analysis. Statistical analysis included classification trees, random forests, and conventional ROC analysis to identify the most significant imaging features that mark severe asthma from controls.

RESULTS

Chest HRCT scans differentiated children with severe asthma from controls. Compared to controls (n = 21, mean age 11.4 years), children with severe asthma (n = 20, mean age 10.4 years) showed significantly greater bronchial thickening (BT) scores (p < 0.001), airway wall thickness percentage (AWT%, p < 0.001), bronchiectasis grading (BG) and bronchiectasis severity (BS) scores (p = 0.016), mucus plugging, and centrilobular emphysema (p = 0.009). Using AWT% as the predictor in conventional ROC analysis, an AWT% ≥ 38.6 emerged as the optimal classifier for discriminating severe asthmatics from controls, with 95% sensitivity, specificity, and overall accuracy.

CONCLUSION

Our study demonstrates the potential of machine learning-based analysis of chest HRCT scans to accurately identify features associated with severe asthma in children, enhancing diagnostic evaluation and contributing to the development of more targeted treatment approaches.

Paediatric Thoracic Imaging in Cystic Fibrosis in the Era of Cystic Fibrosis Transmembrane Conductance Regulator Modulation

Cystic fibrosis (CF) is one of the most common progressive life-shortening genetic conditions worldwide. Ground-breaking translational research has generated therapies that target the primary cystic fibrosis transmembrane conductance regulator (CFTR) defect, known as CFTR modulators. A crucial aspect of paediatric CF disease is the development and progression of irreversible respiratory disease in the absence of clinical symptoms. Accurate thoracic diagnostics have an important role to play in this regard. Chest radiographs are non-specific and insensitive in the context of subtle changes in early CF disease, with computed tomography (CT) providing increased sensitivity. Recent advancements in imaging hardware and software have allowed thoracic CTs to be acquired in paediatric patients at radiation doses approaching that of a chest radiograph. CFTR modulators slow the progression of CF, reduce the frequency of exacerbations and extend life expectancy. In conjunction with advances in CT imaging techniques, low-dose thorax CT will establish a central position in the routine care of children with CF. International guidelines regarding the choice of modality and timing of thoracic imaging in children with CF are lagging behind these rapid technological advances. The continued progress of personalised medicine in the form of CFTR modulators will promote the emergence of personalised radiological diagnostics.

Children with severe asthma have substantial structural airway changes on computed tomography

Background

In adults with severe asthma (SA) bronchial wall thickening, bronchiectasis and low attenuation regions (LAR) have been described on chest computed tomography (CT) scans. The extent to which these structural abnormalities are present in children with SA is largely unknown. Our aim was to study the presence and extent of airway abnormalities on chest CT of children with SA.

Methods

161 inspiratory and expiratory CT scans, either spirometer-controlled or technician-controlled, obtained in 131 children with SA (mean±SD age 11.0±3.8 years) were collected retrospectively. Inspiratory scans were analysed manually using a semi-quantitative score and automatically using LungQ (v2.1.0.1; Thirona B.V., Nijmegen, the Netherlands). LungQ segments the bronchial tree, identifies the generation for each bronchus-artery (BA) pair and measures the following BA dimensions: outer bronchial wall diameter (Bout), adjacent artery diameter (A) and bronchial wall thickness (Bwt). Bronchiectasis was defined as Bout/A ≥1.1, bronchial wall thickening as Bwt/A ≥0.14. LAR, reflecting small airways disease (SAD), was measured automatically on inspiratory and expiratory scans and manually on expiratory scans. Functional SAD was defined as FEF25-75 and/or FEF75 z-scores <-1.645. Results are shown as median and interquartile range.

Results

Bronchiectasis was present on 95.8% and bronchial wall thickening on all CTs using the automated method. Bronchiectasis was present on 28% and bronchial wall thickening on 88.8% of the CTs using the manual semi-quantitative analysis. The percentage of BA pairs defined as bronchiectasis was 24.62% (12.7-39.3%) and bronchial wall thickening was 41.7% (24.0-79.8%) per CT using the automated method. LAR was observed on all CTs using the automatic analysis and on 82.9% using the manual semi-quantitative analysis. Patients with LAR or functional SAD had more thickened bronchi than patients without.

Conclusion

Despite a large discrepancy between the automated and the manual semi-quantitative analysis, bronchiectasis and bronchial wall thickening are present on most CT scans of children with SA. SAD is related to bronchial wall thickening.

An Automated Broncho-Arterial (BA) Pair Segmentation Process and Assessment of BA Ratios in Children with Bronchiectasis Using Lung HRCT Scans: A Pilot Study

Bronchiectasis in children can progress to a severe lung condition if not diagnosed and treated early. The radiological diagnostic criteria for the diagnosis of bronchiectasis is an increased broncho-arterial (BA) ratio. From high-resolution computed tomography (HRCT) scans, the BA pairs must be detected first to derive the BA ratio. This study aims to identify potential BA pairs from HRCT scans of children undertaken to evaluate suppurative lung disease through an automated approach. After segmenting the lung regions, the HRCT scans are cleaned using a histogram analysis-based approach followed by a potential arteries identification process comprising four conditions based on imaging features. Potential arteries and their connected components are extracted, and potential bronchi are identified. Finally, the coordinates of potential arteries and potential bronchi are matched as the last step of BA pairs extraction. A total of 8-50 BA pairs are detected for each patient. Additionally, the area and several diameters of the bronchi and arteries are measured, and BA ratios based on these are calculated. Through this approach, the BA pairs of a CT scan datasets are detected and utilizing a deep learning model, a high classification test accuracy of 98.53% is achieved, validating the robustness of the proposed BA detection approach. The results show that visible BA pairs can be identified and segmented automatically, and the BA ratio calculated may help diagnose bronchiectasis with less effort and time.

Artificial Intelligence-based CT Assessment of Bronchiectasis: The COPDGene Study

Background CT is the standard method used to assess bronchiectasis. A higher airway-to-artery diameter ratio (AAR) is typically used to identify enlarged bronchi and bronchiectasis; however, current imaging methods are limited in assessing the extent of this metric in CT scans. Purpose To determine the extent of AARs using an artificial intelligence-based chest CT and assess the association of AARs with exacerbations over time. Materials and Methods In a secondary analysis of ever-smokers from the prospective, observational, multicenter COPDGene study, AARs were quantified using an artificial intelligence tool. The percentage of airways with AAR greater than 1 (a measure of airway dilatation) in each participant on chest CT scans was determined. Pulmonary exacerbations were prospectively determined through biannual follow-up (from July 2009 to September 2021). Multivariable zero-inflated regression models were used to assess the association between the percentage of airways with AAR greater than 1 and the total number of pulmonary exacerbations over follow-up. Covariates included demographics, lung function, and conventional CT parameters. Results Among 4192 participants (median age, 59 years; IQR, 52-67 years; 1878 men [45%]), 1834 had chronic obstructive pulmonary disease (COPD). During a 10-year follow-up and in adjusted models, the percentage of airways with AARs greater than 1 (quartile 4 vs 1) was associated with a higher total number of exacerbations (risk ratio [RR], 1.08; 95% CI: 1.02, 1.15; P = .01). In participants meeting clinical and imaging criteria of bronchiectasis (ie, clinical manifestations with ≥3% of AARs >1) versus those who did not, the RR was 1.37 (95% CI: 1.31, 1.43; P < .001). Among participants with COPD, the corresponding RRs were 1.10 (95% CI: 1.02, 1.18; P = .02) and 1.32 (95% CI: 1.26, 1.39; P < .001), respectively. Conclusion In ever-smokers with chronic obstructive pulmonary disease, artificial intelligence-based CT measures of bronchiectasis were associated with more exacerbations over time. Clinical trial registration no. NCT00608764 © RSNA, 2022 Supplemental material is available for this article. See also the editorial by Schiebler and Seo in this issue.

The effect of CFTR modulators on structural lung disease in cystic fibrosis

Background: Newly developed quantitative chest computed tomography (CT) outcomes designed specifically to assess structural abnormalities related to cystic fibrosis (CF) lung disease are now available. CFTR modulators potentially can reduce some structural lung abnormalities. We aimed to investigate the effect of CFTR modulators on structural lung disease progression using different quantitative CT analysis methods specific for people with CF (PwCF). Methods: PwCF with a gating mutation (Ivacaftor) or two Phe508del alleles (lumacaftor-ivacaftor) provided clinical data and underwent chest CT scans. Chest CTs were performed before and after initiation of CFTR modulator treatment. Structural lung abnormalities on CT were assessed using the Perth Rotterdam Annotated Grid Morphometric Analysis for CF (PRAGMA-CF), airway-artery dimensions (AA), and CF-CT methods. Lung disease progression (0-3 years) in exposed and matched unexposed subjects was compared using analysis of covariance. To investigate the effect of treatment in early lung disease, subgroup analyses were performed on data of children and adolescents aged <18 years. Results: We included 16 modulator exposed PwCF and 25 unexposed PwCF. Median (range) age at the baseline visit was 12.55 (4.25-36.49) years and 8.34 (3.47-38.29) years, respectively. The change in PRAGMA-CF %Airway disease (-2.88 (-4.46, -1.30), p = 0.001) and %Bronchiectasis extent (-2.07 (-3.13, -1.02), p < 0.001) improved in exposed PwCF compared to unexposed. Subgroup analysis of paediatric data showed that only PRAGMA-CF %Bronchiectasis (-0.88 (-1.70, -0.07), p = 0.035) improved in exposed PwCF compared to unexposed. Conclusion: In this preliminary real-life retrospective study CFTR modulators improve several quantitative CT outcomes. A follow-up study with a large cohort and standardization of CT scanning is needed to confirm our findings.

Morphological features of bronchiectasis in patients with non-tuberculous mycobacteriosis and interstitial pneumonia

Objective

To compare the morphological features of bronchiectasis between patients with different underlying diseases, we performed quantitative analysis of high-resolution computed tomography (HRCT) images of 14 patients with non-tuberculous mycobacteriosis (NTM) and 13 with idiopathic pulmonary fibrosis (IPF). A 3D image of the bronchial structure was made from HRCT data. Bronchiectasis was defined as abnormal dilatation of the bronchi with the diameter greater than that of the accompanying pulmonary artery. We measured the inner and outer diameters, wall area as %total airway cross sectional area (WA%), and wall thickness to airway diameter ratio (T/D) of the 4-8th generations of bronchi.

Results

In patients with IPF, the inner and outer diameters linearly decreased toward the distal bronchi. In contrast, the inner and outer diameters of NTM fluctuated. The coefficient of variation of the outer diameters of the 6-7th generations of bronchi was larger in the NTM patients than in those with IPF, whereas no significant difference was observed in the coefficient of variation of the inner diameters between the groups. In IPF patients, WA% and T/D varied between the generation of bronchi, but the coefficient of variation of WA% and T/D was relatively small in those with NTM.

State-of-the-art review of lung imaging in cystic fibrosis with recommendations for pulmonologists and radiologists from the "iMAging managEment of cySTic fibROsis" (MAESTRO) consortium

OBJECTIVE

Imaging represents an important noninvasive means to assess cystic fibrosis (CF) lung disease, which remains the main cause of morbidity and mortality in CF patients. While the development of new imaging techniques has revolutionised clinical practice, advances have posed diagnostic and monitoring challenges. The authors aim to summarise these challenges and make evidence-based recommendations regarding imaging assessment for both clinicians and radiologists.

STUDY DESIGN

A committee of 21 experts in CF from the 10 largest specialist centres in Italy was convened, including a radiologist and a pulmonologist from each centre, with the overall aim of developing clear and actionable recommendations for lung imaging in CF. An a priori threshold of at least 80% of the votes was required for acceptance of each statement of recommendation.

RESULTS

After a systematic review of the relevant literature, the committee convened to evaluate 167 articles. Following five RAND conferences, consensus statements were developed by an executive subcommittee. The entire consensus committee voted and approved 28 main statements.

CONCLUSIONS

There is a need for international guidelines regarding the appropriate timing and selection of imaging modality for patients with CF lung disease; timing and selection depends upon the clinical scenario, the patient's age, lung function and type of treatment. Despite its ubiquity, the use of the chest radiograph remains controversial. Both computed tomography and magnetic resonance imaging should be routinely used to monitor CF lung disease. Future studies should focus on imaging protocol harmonisation both for computed tomography and for magnetic resonance imaging. The introduction of artificial intelligence imaging analysis may further revolutionise clinical practice by providing fast and reliable quantitative outcomes to assess disease status. To date, there is no evidence supporting the use of lung ultrasound to monitor CF lung disease.

Detection and Classification of Bronchiectasis Through Convolutional Neural Networks

PURPOSE

Bronchiectasis is a chronic disease characterized by an irreversible dilatation of bronchi leading to chronic infection, airway inflammation, and progressive lung damage. Three specific patterns of bronchiectasis are distinguished in clinical practice: cylindrical, varicose, and cystic. The predominance and the extension of the type of bronchiectasis provide important clinical information. However, characterization is often challenging and is subject to high interobserver variability. The aim of this study is to provide an automatic tool for the detection and classification of bronchiectasis through convolutional neural networks.

MATERIALS AND METHODS

Two distinct approaches were adopted: (i) direct network performing a multilabel classification of 32×32 regions of interest (ROIs) into 4 classes: healthy, cylindrical, cystic, and varicose and (ii) a 2-network serial approach, where the first network performed a binary classification between normal tissue and bronchiectasis and the second one classified the ROIs containing abnormal bronchi into one of the 3 bronchiectasis typologies. Performances of the networks were compared with other architectures presented in the literature.

RESULTS

Computed tomography from healthy individuals (n=9, age=47±6, FEV1%pred=109±17, FVC%pred=116±17) and bronchiectasis patients (n=21, age=59±15, FEV1%pred=74±25, FVC%pred=91±22) were collected. A total of 19,059 manually selected ROIs were used for training and testing. The serial approach provided the best results with an accuracy and F1 score average of 0.84, respectively. Slightly lower performances were observed for the direct network (accuracy=0.81 and F1 score average=0.82). On the test set, cylindrical bronchiectasis was the subtype classified with highest accuracy, while most of the misclassifications were related to the varicose pattern, mainly to the cylindrical class.

CONCLUSION

The developed networks accurately detect and classify bronchiectasis disease, allowing to collect quantitative information regarding the radiologic severity and the topographical distribution of bronchiectasis subtype.

The effect of maintenance azithromycin on radiological features in patients with bronchiectasis - Analysis from the BAT randomized controlled trial

RATIONALE

Bronchiectasis (abnormal dilatation of bronchi) is usually diagnosed by high resolution computed tomography (HRCT) and radiological severity has been found to correspond with clinical outcome. A beneficial effect of macrolides maintenance treatment in frequent exacerbating bronchiectasis patients has been established in randomized trials. This study was undertaken to prospectively evaluate the effect of long-term azithromycin (AZM) on radiological features in patients with bronchiectasis.

METHODS

The BAT randomized controlled trial (2008-2010) investigated the effect of 1 year of AZM (250 mg OD) in bronchiectasis with frequent exacerbations. Chest (HR)CT-scans at baseline and after one year of study treatment were obtained and scored by two radiologists according to the Brody - and the Bhalla scoring system.

RESULTS

77 (93%) patients conducted the BAT trial were evaluated in this post-hoc analysis. A significant improvement of the radiological features based on the Brody score was found after one year of AZM therapy as compared to placebo (p = 0.024), with a not significant improvement of the Bhalla score (p=0.071). Especially the consolidation (Bhalla) and parenchymal changes (Brody) sub scores significantly improved (both p=0.030), and even a radiological deterioration was seen on the Brody bronchiectasis sub score for the placebo treated patients (mean 14.5 (11.7) vs.15.7 (11.9)).

CONCLUSIONS

The beneficial effect of long-term AZM treatment on radiological features was demonstrated in this randomized controlled trial. (HR)CT's can be used as an objective measure of treatment response in bronchiectasis.

CLINICAL TRIAL REGISTRATION NUMBER

NCT00415350.

Automatic airway segmentation from computed tomography using robust and efficient 3-D convolutional neural networks

This paper presents a fully automatic and end-to-end optimised airway segmentation method for thoracic computed tomography, based on the U-Net architecture. We use a simple and low-memory 3D U-Net as backbone, which allows the method to process large 3D image patches, often comprising full lungs, in a single pass through the network. This makes the method simple, robust and efficient. We validated the proposed method on three datasets with very different characteristics and various airway abnormalities: (1) a dataset of pediatric patients including subjects with cystic fibrosis, (2) a subset of the Danish Lung Cancer Screening Trial, including subjects with chronic obstructive pulmonary disease, and (3) the EXACT'09 public dataset. We compared our method with other state-of-the-art airway segmentation methods, including relevant learning-based methods in the literature evaluated on the EXACT'09 data. We show that our method can extract highly complete airway trees with few false positive errors, on scans from both healthy and diseased subjects, and also that the method generalizes well across different datasets. On the EXACT'09 test set, our method achieved the second highest sensitivity score among all methods that reported good specificity.

Imaging in non-cystic fibrosis bronchiectasis and current limitations

Non-cystic fibrosis bronchiectasis represents a heterogenous spectrum of disorders characterised by an abnormal and permanent dilatation of the bronchial tree associated with respiratory symptoms. To date, diagnosis relies on computed tomography (CT) evidence of dilated airways. Nevertheless, definite radiological criteria and standardised CT protocols are still to be defined. Although largely used, current radiological scoring systems have shown substantial drawbacks, mostly failing to correlate morphological abnormalities with clinical and prognostic data. In limited cases, bronchiectasis morphology and distribution, along with associated CT features, enable radiologists to confidently suggest an underlying cause. Quantitative imaging analyses have shown a potential to overcome the limitations of the current radiological criteria, but their application is still limited to a research setting.

In the present review, we discuss the role of imaging and its current limitations in non-cystic fibrosis bronchiectasis. The potential of automatic quantitative approaches and artificial intelligence in such a context will be also mentioned.

Crowdsourcing airway annotations in chest computed tomography images

Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotated scans for good performance. We investigate whether crowdsourcing can be used to gather airway annotations. We generate image slices at known locations of airways in 24 subjects and request the crowd workers to outline the airway lumen and airway wall. After combining multiple crowd workers, we compare the measurements to those made by the experts in the original scans. Similar to our preliminary study, a large portion of the annotations were excluded, possibly due to workers misunderstanding the instructions. After excluding such annotations, moderate to strong correlations with the expert can be observed, although these correlations are slightly lower than inter-expert correlations. Furthermore, the results across subjects in this study are quite variable. Although the crowd has potential in annotating airways, further development is needed for it to be robust enough for gathering annotations in practice. For reproducibility, data and code are available online: http://github.com/adriapr/crowdairway.git.

A multimodal approach to detect and monitor early lung disease in cystic fibrosis

Introduction: In the early stages, lung involvement in cystic fibrosis (CF) can be silent, with disease progression occurring in the absence of clinical symptoms. Irreversible airway damage is present in the early stages of disease; however, reliable biomarkers of early damage due to inflammation and infection that are universally applicable in day-to-day patient management have yet to be identified.Areas covered: At present, the main methods of detecting and monitoring early lung disease in CF are the lung clearance index (LCI), computed tomography (CT), and magnetic resonance imaging (MRI). LCI can be used to detect patients who may require more intense monitoring, identify exacerbations, and monitor responses to new interventions. High-resolution CT detects structural alterations in the lungs of CF patients with the best resolution of current imaging techniques. MRI is a radiation-free imaging alternative that provides both morphological and functional information. The role of MRI for short-term follow-up and pulmonary exacerbations is currently being investigated.Expert opinion: The roles of LCI and MRI are expected to expand considerably over the next few years. Meanwhile, closer collaboration between pulmonology and radiology specialties is an important goal toward improving care and optimizing outcomes in young patients with CF.

Chest computed tomography outcomes in a randomized clinical trial in cystic fibrosis: Lessons learned from the first ataluren phase 3 study

A phase 3 randomized double blind controlled, trial in 238 people with cystic fibrosis (CF) and at least one nonsense mutation (nmCF) investigated the effect of ataluren on FEV1. The study was of 48 weeks duration and failed to meet its primary endpoint. Unexpectedly, while FEV1 declined, chest computed tomography (CT) scores using the Brody-II score as secondary outcome measures did not show progression in the placebo group. Based on this observation it was concluded that the role of CT scans in CF randomized clinical trials was limited. However, more sensitive scoring systems were developed over the last decade warranting a reanalysis of this unique dataset. The aim of our study was to reanalyse all chest CT scans, obtained in the ataluren phase 3 study, using 2 independent scoring systems to characterize structural lung disease in this cohort and to compare progression of structural lung disease over the 48 weeks between treatment arms. 391 study CT scans from 210 patients were reanalysed in random order by 2 independent observers using the CF-CT and Perth-Rotterdam Annotated Grid Morphometric Analysis for CF (PRAGMA-CF) scoring systems. CF-CT and PRAGMA-CF subscores were expressed as %maximal score and %total lung volume, respectively. PRAGMA-CF subscores %Disease (p = 0.008) and %Mucus Plugging (p = 0.029) progressed over 48 weeks. CF-CT subscores did not show progression. There was no difference in progression of structural lung disease between treatment arm and placebo independent of tobramycin use. PRAGMA-CF Chest CT scores can be used as an outcome measure to study the effect of potential disease modifying drugs in CF on lung structure.

Current state of the art MRI for the longitudinal assessment of cystic fibrosis

Pulmonary MRI can now provide high-resolution images that are sensitive to early disease and specific to inflammation in cystic fibrosis (CF) lung disease. With specificity and function limited via computed tomography (CT), there are significant advantages to MRI. Many of the modern MRI techniques can be performed throughout life, and can be employed to understand changes over time, in addition to quantification of treatment response. Proton density and T1 /T2 contrast images can be obtained within a single breath-hold, providing depiction of structural abnormalities and active inflammation. Modern radial and/or spiral ultrashort echo-time (UTE) techniques rival CT in resolution for depiction and quantification of structure, for both airway and parenchymal abnormalities. Contrast perfusion MRI techniques are now utilized routinely to visualize changes in pulmonary and bronchial circulation that routinely occur in CF lung disease, and noncontrast techniques are moving closer to clinical translation. Functional information can be obtained from noncontrast proton images alone, using techniques such as Fourier decomposition. Hyperpolarized-gas MRI, increasingly using 129 Xe, is now becoming more widespread and has been demonstrated to have high sensitivity to early airway obstruction in CF via ventilation MRI. The sensitivity of 129 Xe MRI promises future use in personalized medicine, management of early CF lung disease, and in future clinical trials. By combining structural and functional techniques, with or without hyperpolarized gases, regional structure-function relationships can be obtained, giving insight into the pathophysiology of disease and improved clinical management. This article reviews the modern MRI techniques that can routinely be employed for CF lung disease in nearly any large medical center. Level of Evidence: 4 Technical Efficacy Stage: 5 J. Magn. Reson. Imaging 2019.

Congenital lung abnormality quantification by computed tomography: The CLAQ method

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.

Airway-artery quantitative assessment on chest computed tomography in paediatric primary ciliary dyskinesia

Chest computed tomography (CT) is the gold standard for detecting structural abnormalities in patients with primary ciliary dyskinesia (PCD) such as bronchiectasis, bronchial wall thickening and mucus plugging. There are no studies on quantitative assessment of airway and artery abnormalities in children with PCD. The objectives of the present study were to quantify airway and artery dimensions on chest CT in a cohort of children with PCD and compare these with control children to analyse the influence of covariates on airway and artery dimensions.

Chest CTs of 13 children with PCD (14 CT scans) and 12 control children were collected retrospectively. The bronchial tree was segmented semi-automatically and reconstructed in a three-dimensional view. All visible airway–artery (AA) pairs were measured perpendicular to the airway centre line, annotating per branch inner and outer airway and adjacent artery diameter and computing inner airway diameter/artery ratio (AinA ratio), outer airway diameter/artery ratio (AoutA ratio), wall thickness (WT), WT/outer airway diameter ratio (Awt ratio) and WT/artery ratio.

In the children with PCD (38.5% male, mean age 13.5 years, range 9.8–15.3) 1526 AA pairs were measured versus 1516 in controls (58.3% male, mean age 13.5 years, range 8–14.8). AinA ratio and AoutA ratio were significantly higher in children with PCD than in control children (both p<0.001). Awt ratio was significantly higher in control children than in children with PCD (p<0.001).

Our study showed that in children with PCD airways are more dilated than in controls and do not show airway wall thickening.

Chest CT is the gold standard for detecting structural abnormalities in patients with PCD, and this study is the first on quantitative assessment of airway and artery abnormalities in children with PCDhttps://bit.ly/2XZYWjU

The radiological diagnosis of bronchiectasis: what's in a name?

Diagnosis of bronchiectasis is usually made using chest computed tomography (CT) scan, the current gold standard method. A bronchiectatic airway can show abnormal widening and thickening of its airway wall. In addition, it can show an irregular wall and lack of tapering, and/or can be visible in the periphery of the lung. Its diagnosis is still largely expert based. More recently, it has become clear that airway dimensions on CT and therefore the diagnosis of bronchiectasis are highly dependent on lung volume. Hence, control of lung volume is required during CT acquisition to standardise the evaluation of airways. Automated image analysis systems are in development for the objective analysis of airway dimensions and for the diagnosis of bronchiectasis. To use these systems, clear and objective definitions for the diagnosis of bronchiectasis are needed. Furthermore, the use of these systems requires standardisation of CT protocols and of lung volume during chest CT acquisition. In addition, sex- and age-specific reference values are needed for image analysis outcome parameters. This review focusses on today's issues relating to the radiological diagnosis of bronchiectasis using state-of-the-art CT imaging techniques.

Bronchiectasis diagnosis is expert based. Clear definitions, standardisation of lung volume and CT protocols, and reference values are needed to allow automated image analysis for its diagnosis and to be used for clinical management and clinical studies.http://bit.ly/35vASqz

Diagnosis and quantification of bronchiectasis using computed tomography or magnetic resonance imaging: A systematic review

BACKGROUND

Bronchiectasis is an irreversible dilatation of the airways caused by inflammation and infection. To diagnose bronchiectasis in clinical care and to use bronchiectasis as outcome parameter in clinical trials, a radiological definition with exact cut-off values along with image analysis methods to assess its severity are needed. The aim of this study was to review diagnostic criteria and quantification methods for bronchiectasis.

METHODS

A systematic literature search was performed using Embase, Medline Ovid, Web of Science, Cochrane and Google Scholar. English written, clinical studies that included bronchiectasis as outcome measure and used image quantification methods were selected. Criteria for bronchiectasis, quantification methods, patient demographics, and data on image acquisition were extracted.

RESULTS

We screened 4182 abstracts, selected 972 full texts, and included 122 studies. The most often used criterion for bronchiectasis was an inner airway-artery ratio ≥1.0 (42%), however no validation studies for this cut-off value were found. Importantly, studies showed that airway-artery ratios are influenced by age. To quantify bronchiectasis, 42 different scoring methods were described.

CONCLUSION

Different diagnostic criteria for bronchiectasis are being used, but no validation studies were found to support these criteria. To use bronchiectasis as outcome in future studies, validated and age-specific cut-off values are needed.

Airway tapering: an objective image biomarker for bronchiectasis

Purpose

To estimate airway tapering in control subjects and to assess the usability of tapering as a bronchiectasis biomarker in paediatric populations.

Methods

Airway tapering values were semi-automatically quantified in 156 children with control CTs collected in the Normal Chest CT Study Group. Airway tapering as a biomarker for bronchiectasis was assessed on spirometer-guided inspiratory CTs from 12 patients with bronchiectasis and 12 age- and sex-matched controls. Semi-automatic image analysis software was used to quantify intra-branch tapering (reduction in airway diameter along the branch), inter-branch tapering (reduction in airway diameter before and after bifurcation) and airway-artery ratios on chest CTs. Biomarkers were further stratified in small, medium and large airways based on three equal groups of the accompanying vessel size.

Results

Control subjects showed intra-branch tapering of 1% and inter-branch tapering of 24–39%. Subjects with bronchiectasis showed significantly reduced intra-branch of 0.8% and inter-branch tapering of 19–32% and increased airway–artery ratios compared with controls (p < 0.01). Tapering measurements were significantly different between diseased and controls across all airway sizes. Difference in airway–artery ratio was only significant in small airways.

Conclusion

Paediatric normal values for airway tapering were established in control subjects. Tapering showed to be a promising biomarker for bronchiectasis as subjects with bronchiectasis show significantly less airway tapering across all airway sizes compared with controls. Detecting less tapering in larger airways could potentially lead to earlier diagnosis of bronchiectasis. Additionally, compared with the conventional airway–artery ratio, this novel biomarker has the advantage that it does not require pairing with pulmonary arteries.

Key Points

• Tapering is a promising objective image biomarker for bronchiectasis that can be extracted semi-automatically and has good correlation with validated visual scoring methods.

• Less airway tapering was observed in patients with bronchiectasis and can be observed sensitively throughout the bronchial tree, even in the more central airways.

• Tapering values seemed to be less influenced by variety in scanning protocols and lung volume making it a more robust biomarker for bronchiectasis detection.

Electronic supplementary material

The online version of this article (10.1007/s00330-019-06606-w) contains supplementary material, which is available to authorized users.

Early markers of cystic fibrosis structural lung disease: follow-up of the ACFBAL cohort

Little is known about early predictors of later cystic fibrosis (CF) structural lung disease. This study examined early predictors of progressive structural lung abnormalities in children who completed the Australasian CF Bronchoalveolar Lavage (ACFBAL) clinical trial at age 5-years and participated in an observational follow-up study (CF-FAB).

Eight Australian and New Zealand CF centres participated in CF-FAB and provided follow-up chest computed-tomography (CT) scans for children who had completed the ACFBAL study with baseline scans at age 5-years. CT scans were annotated using PRAGMA-CF scoring. Ordinal regression analysis and linear regression were used to investigate associations between PRAGMA-CF (Perth–Rotterdam Annotated Grid Morphometric Analysis for CF) outcomes at follow-up and variables measured during the ACFBAL study.

99 out of 157 ACFBAL children (mean±sd age 13±1.5 years) participated in the CF-FAB study. The probability of bronchiectasis at follow-up increased with airway disease severity on the baseline CT scan. In multiple regression (retaining factors at p<0.05) the extent of bronchiectasis at follow-up was associated with baseline atelectasis (OR 7.2, 95% CI 2.4–22; p≤ 0.001), bronchoalveolar lavage (BAL) log2 interleukin (IL)-8 (OR 1.2, 95% CI 1.05–1.5; p=0.010) and body mass index z-score (OR 0.49, 95% CI 0.24–1.00; p=0.05) at age 5 years. Percentage trapped air at follow-up was associated with BAL log2 IL-8 (coefficient 1.3, 95% CI 0.57–2.1; p<0.001) at age 5 years.

The extent of airway disease, atelectasis, airway inflammation and poor nutritional status in early childhood are risk factors for progressive structural lung disease in adolescence.

An unsupervised semi-automated pulmonary nodule segmentation method based on enhanced region growing

Background

Nowadays, computer technology is getting popular for clinical aided diagnosis, especially in the direction of medical images. It makes physician diagnosis of lung nodules more efficient by providing them with reliable and accurate segmentation.

Methods

A region growing based semi-automated pulmonary nodule segmentation algorithm (ReGANS) was developed with three improvements: an automatic threshold calculation method, a lesion area pre-projection method, and an optimized region growing method. The algorithm can quickly and accurately segment a whole lung nodule in a set of computed tomography (CT) images based on an initial manual point.

Results

The average time taken for ReGANS to segment 1 pulmonary nodule was 0.83s, and the probability rand index (PRI), global consistency error (GCE), and variation of information (VoI) from a comparison between the algorithm and the radiologist's 2 manual results were 0.93, 0.06, and 0.3 for the boundary range (BR), and 0.86, 0.06, 0.3 for the precise range (PR). The number of images covered by one pulmonary nodule in a CT image set was also evaluated to compare the segmentation algorithm with the radiologist's results, with an error rate of 15%. At the same time, the results were verified in multiple data sets to validate the robustness.

Conclusions

Compared with other algorithms, ReGANS can segment the lung nodule image region more quickly and more precisely. The experimental results show that ReGANS can assist medical imaging diagnosis and has good clinical application value. It also provides a faster and more convenient method for pre-data preparation of intelligent algorithms.

Hepatopulmonary syndrome has low prevalence of pulmonary vascular abnormalities on chest computed tomography

Purpose

Hepatopulmonary syndrome (HPS) is defined as an arterial oxygenation defect induced by intrapulmonary vascular dilatations associated with hepatic disease. This study aimed to assess the prevalence of type 1 and 2 pulmonary vascular abnormalities on chest computed tomography (CT) in patients with cirrhosis and HPS and to characterize intra- and interobserver reliability.

Materials and methods

Two thoracic radiologists retrospectively evaluated chest CT scans from 38 cirrhosis patients with HPS. They classified the pulmonary vascular abnormalities as type 1 (multiple dilated distal pulmonary arteries), type 2(nodular dilatation or individual pulmonary arterial malformation), or absence of abnormality. Furthermore, they measured the diameters of the central pulmonary arteries and subsegmental pulmonary arteries and bronchi. We analyzed the prevalence, intraobserver reliability, and interobserver reliability of abnormal CT findings related to HPS, and the correlation of these findings with partial arterial oxygen pressure (PaO₂).

Results

The overall prevalence of pulmonary vascular abnormalities was 28.9% (95% confidence intervals: 15.4%, 45.9%). Moreover, 26.3% of patients had type 1 abnormality (13.4%, 43.1%) and 2.6% of patients had type 2 abnormality (0.0%, 13.8%). The intraobserver reliability kappa value was 0.666 (0.40, 0.91) and the interobserver kappa value was 0.443 (0.12, 0.77). There was no correlation between pulmonary vascular abnormalities on CT and PaO₂ values.

Conclusions

The prevalence of pulmonary vascular abnormalities on chest CT of patients with cirrhosis and HPS is low and not correlated with PaO₂. These findings question the usefulness of chest CT for the evaluation of patients with cirrhosis and HPS.

Reproducibility of an airway tapering measurement in computed tomography with application to bronchiectasis

We propose a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on computed tomography (CT). We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure. We generate a spline from the centerline of an airway to measure the area and arclength at contiguous intervals. The tapering measurement is the gradient of the linear regression between area in log space and arclength. The reproducibility of the measure was assessed by analyzing different radiation doses, voxel sizes, and reconstruction kernel on single timepoint and longitudinal CT scans and by evaluating the effect of airway bifurcations. Using 74 airways from 10 CT scans, we show a statistical difference, p = 3.4 × 10 - 4 , in tapering between healthy airways ( n = 35 ) and those affected by bronchiectasis ( n = 39 ). The difference between the mean of the two populations is 0.011    mm - 1 , and the difference between the medians of the two populations was 0.006    mm - 1 . The tapering measurement retained a 95% confidence interval of ± 0.005    mm - 1 in a simulated 25 mAs scan and retained a 95% confidence of ± 0.005    mm - 1 on simulated CTs up to 1.5 times the original voxel size. We have established an estimate of the precision of the tapering measurement and estimated the effect on precision of the simulated voxel size and CT scan dose. We recommend that the scanner calibration be undertaken with the phantoms as described, on the specific CT scanner, radiation dose, and reconstruction algorithm that are to be used in any quantitative studies.

Semi-automatic Methods for Airway and Adjacent Vessel Measurement in Bronchiectasis Patterns in Lung HRCT Images of Cystic Fibrosis Patients

Airway and vessel characterization of bronchiectasis patterns in lung high-resolution computed tomography (HRCT) images of cystic fibrosis (CF) patients is very important to compute the score of disease severity. We propose a hybrid and evolutionary optimized threshold and model-based method for characterization of airway and vessel in lung HRCT images of CF patients. First, the initial model of airway and vessel is obtained using the enhanced threshold-based method. Then, the model is fitted to the actual image by optimizing its parameters using particle swarm optimization (PSO) evolutionary algorithm. The experimental results demonstrated the outperformance of the proposed method over its counterpart in R-squared, mean and variance of error, and run time. Moreover, the proposed method outperformed its counterpart for airway inner diameter/vessel diameter (AID/VD) and airway wall thickness/vessel diameter (AWT/VD) biomarkers in R-squared and slope of regression analysis.

Paediatric lung imaging: the times they are a-changin'

Until recently, functional tests were the most important tools for the diagnosis and monitoring of lung diseases in the paediatric population. Chest imaging has gained considerable importance for paediatric pulmonology as a diagnostic and monitoring tool to evaluate lung structure over the past decade. Since January 2016, a large number of papers have been published on innovations in chest computed tomography (CT) and/or magnetic resonance imaging (MRI) technology, acquisition techniques, image analysis strategies and their application in different disease areas. Together, these papers underline the importance and potential of chest imaging and image analysis for today's paediatric pulmonology practice. The focus of this review is chest CT and MRI, as these are, and will be, the modalities that will be increasingly used by most practices. Special attention is given to standardisation of image acquisition, image analysis and novel applications in chest MRI. The publications discussed underline the need for the paediatric pulmonology community to implement and integrate state-of-the-art imaging and image analysis modalities into their structure-function laboratory for the benefit of their patients.

Quantitative assessment of airway dimensions in young children with cystic fibrosis lung disease using chest computed tomography

OBJECTIVE

To evaluate lung disease progression using airway and artery (AA) dimensions on chest CT over 2-year interval in young CF patients longitudinally and compare to disease controls cross-sectionally.

METHODS

Retrospective analysis of pressure controlled end-inspiratory CTs, 12 routine baseline (CT₁ ) and follow up (CT₂ ) from AREST CF cohort; 12 disease controls with normal CT. All visible AA-pairs were measured perpendicular to the airway axis. Inner and outer airway diameters and wall (outer-inner radius) thickness were divided by adjacent arteries to compute A_in A-, A_out A-, and A_WT A-ratios, respectively. Differences between CF and control data were assessed using mixed effects models predicting AA-ratios per segmental generation (SG). Power calculations were performed with 80% power and ɑ = 0.05.

RESULTS

CF, median age CT₁ 2 years; CT₂ 3.9 years, 5 males. Controls, median age 2.9 years, 10 males. Total of 4798 AA-pairs measured. Cross-sectionally: A_in A-ratio showed no difference between controls and CF CT₁ or CT₂ . A_out A-ratio was significantly higher in CF CT₁ (SG 2-4) and CT₂ (SG 2-5) compared to controls. A_WT A-ratio was increased for CF CT₁ (SG 1-5) and CT₂ (SG 2-6) compared to controls. CF longitudinally: A_in A-ratio was significantly higher at CT₂ compared to CT₁ . Increase in A_out A-ratio at CT₂ compared to CT₁ was visible in SG ≥4. Sample sizes of 21 and 58 would be necessary for 50% and 30% A_out A-ratio reductions, respectively, between CF CT₂ and controls.

CONCLUSION

AA-ratio differences were present in young CF patients relative to disease controls. A_out A-ratio as an objective parameter for bronchiectasis could reduce sample sizes for clinical trials.

Diagnosis of bronchiectasis and airway wall thickening in children with cystic fibrosis: Objective airway-artery quantification

OBJECTIVES

To quantify airway and artery (AA)-dimensions in cystic fibrosis (CF) and control patients for objective CT diagnosis of bronchiectasis and airway wall thickness (AWT).

METHODS

Spirometer-guided inspiratory and expiratory CTs of 11 CF and 12 control patients were collected retrospectively. Airway pathways were annotated semi-automatically to reconstruct three-dimensional bronchial trees. All visible AA-pairs were measured perpendicular to the airway axis. Inner, outer and AWT (outer-inner) diameter were divided by the adjacent artery diameter to compute A_inA-, A_outA- and A_WTA-ratios. AA-ratios were predicted using mixed-effects models including disease status, lung volume, gender, height and age as covariates.

RESULTS

Demographics did not differ significantly between cohorts. Mean AA-pairs CF: 299 inspiratory; 82 expiratory.

CONTROLS

131 inspiratory; 58 expiratory. All ratios were significantly larger in inspiratory compared to expiratory CTs for both groups (p<0.001). A_outA- and A_WTA-ratios were larger in CF than in controls, independent of lung volume (p<0.01). Difference of A_outA- and A_WTA-ratios between patients with CF and controls increased significantly for every following airway generation (p<0.001).

CONCLUSION

Diagnosis of bronchiectasis is highly dependent on lung volume and more reliably diagnosed using outer airway diameter. Difference in bronchiectasis and AWT severity between the two cohorts increased with each airway generation.

KEY POINTS

• More peripheral airways are visible in CF patients compared to controls. • Structural lung changes in CF patients are greater with each airway generation. • Number of airways visualized on CT could quantify CF lung disease. • For objective airway disease quantification on CT, lung volume standardization is required.

Chest imaging in cystic fibrosis studies: What counts, and can be counted?

BACKGROUND

The dawn of precision medicine and CFTR modulators require more detailed assessment of lung structure in cystic fibrosis (CF) clinical studies. Various imaging markers have emerged and are measurable, but clarity is needed to identify what markers should count for clinical studies. High-resolution chest computed tomography (CT) scoring has yielded sensitive markers for the study of CF disease progression. Once completed, CT scores from ongoing randomized controlled trials can be used to examine relationships between imaging endpoints and therapeutic effectiveness. Similarly, Magnetic Resonance Imaging (MRI) is in development to generate structural as well as functional markers.

RESULTS

The aim of this review is to characterize the role of currently available CT and MRI markers in clinical studies, and to discuss study design, data processing and statistical challenges unique to these endpoints in CF studies. Suggestions to overcome these challenges in CF studies are included.

CONCLUSIONS

To maximize the potential of CT and MRI markers in clinical studies and advance treatment of CF disease progression, efforts should be made to conduct longitudinal randomized controlled trials including these modalities, develop data repositories, promote standardization and conduct reproducible research.