Quantitative CT Evaluation of Small Pulmonary Vessels Has Functional and Prognostic Value in Pulmonary Hypertension.

Background The in vivo relationship between peel pulmonary vessels, small pulmonary vessels, and pulmonary hypertension (PH) is not fully understood. Purpose To quantitatively assess peel pulmonary vessel volumes (PPVVs) and small pulmonary vessel volumes (SPVVs) as estimated from CT pulmonary angiography (CTPA) in different subtypes of PH compared with controls, their relationship to pulmonary function and right heart catheter metrics, and their prognostic value. Materials and Methods In this retrospective single-center study performed from January 2008 to February 2018, quantitative CTPA analysis of total SPVV (TSPVV) (0.4- to 2-mm vessel diameter) and PPVV (within 15, 30, and 45 mm from the lung surface) was performed. Results A total of 1823 patients (mean age, 69 years ± 13 [SD]; 1192 women [65%]) were retrospectively analyzed; 1593 patients with PH (mean pulmonary arterial pressure [mPAP], 43 mmHg ± 13 [SD]) were compared with 230 patient controls (mPAP, 19 mm Hg ± 3). The mean vessel volumes in pulmonary peels at 15-, 30-, and 45-mm depths were higher in pulmonary arterial hypertension (PAH) and PH secondary to lung disease compared with chronic thromboembolic PH (45-mm peel, mean difference: 6.4 mL [95% CI: 1, 11] [P < .001] vs 6.8 mL [95% CI: 1, 12] [P = .01]). Mean small vessel volumes at a diameter of less than 2 mm were lower in PAH and PH associated with left heart disease compared with controls (1.6-mm vessels, mean difference: -4.3 mL [95% CI: -8, -0.1] [P = .03] vs -6.8 mL [95% CI: -11, -2] [P < .001]). In patients with PH, the most significant positive correlation was noted with forced vital capacity percentage predicted (r = 0.30-0.40 [all P < .001] for TSPVVs and r = 0.21-0.25 [all P < .001] for PPVVs). Conclusion The volume of pulmonary small vessels is reduced in pulmonary arterial hypertension and pulmonary hypertension (PH) associated with left heart disease, with similar volume of peel vessels compared with controls. For chronic thromboembolic PH, the volume of peel vessels is reduced. In PH, small pulmonary vessel volume is associated with pulmonary function tests. Clinical trial registration no. NCT02565030 Published under a CC BY 4.0 license Online supplemental material is available for this article.

Severe pulmonary hypertension associated with lung disease is characterised by a loss of small pulmonary vessels on quantitative computed tomography.

Background: Pulmonary hypertension (PH) in patients with chronic lung disease (CLD) predicts reduced functional status, clinical worsening and increased mortality, with patients with severe PH-CLD (≥35 mmHg) having a significantly worse prognosis than mild to moderate PH-CLD (21-34 mmHg). The aim of this cross-sectional study was to assess the association between computed tomography (CT)-derived quantitative pulmonary vessel volume, PH severity and disease aetiology in CLD. Methods: Treatment-naïve patients with CLD who underwent CT pulmonary angiography, lung function testing and right heart catheterisation were identified from the ASPIRE registry between October 2012 and July 2018. Quantitative assessments of total pulmonary vessel and small pulmonary vessel volume were performed. Results: 90 patients had PH-CLD including 44 associated with COPD/emphysema and 46 with interstitial lung disease (ILD). Patients with severe PH-CLD (n=40) had lower small pulmonary vessel volume compared to patients with mild to moderate PH-CLD (n=50). Patients with PH-ILD had significantly reduced small pulmonary blood vessel volume, compared to PH-COPD/emphysema. Higher mortality was identified in patients with lower small pulmonary vessel volume. Conclusion: Patients with severe PH-CLD, regardless of aetiology, have lower small pulmonary vessel volume compared to patients with mild-moderate PH-CLD, and this is associated with a higher mortality. Whether pulmonary vessel changes quantified by CT are a marker of remodelling of the distal pulmonary vasculature requires further study.

Subclinical Pulmonary Congestion and Abnormal Hemodynamics in Heart Failure With Preserved Ejection Fraction.

OBJECTIVES: The authors hypothesized that quantitative computed tomography (QCT) imaging would reveal subclinical increases in lung congestion in patients with heart failure and preserved ejection fraction (HFpEF) and that this would be related to pulmonary vascular hemodynamic abnormalities. BACKGROUND: Gross evidence of lung congestion on physical examination, laboratory tests, and radiography is typically absent among compensated ambulatory patients with HFpEF. However, pulmonary gas transfer abnormalities are commonly observed and associated with poor outcomes. METHODS: Patients referred for invasive hemodynamic exercise testing who had undergone chest computed tomography imaging within 1 month were identified (N = 137). A novel artificial intelligence QCT algorithm was used to measure pulmonary fluid content. RESULTS: Compared with control subjects with noncardiac dyspnea, patients with HFpEF displayed increased mean lung density (-758 HU [-793, -709 HU] vs -787 HU [-828, -747 HU]; P = 0.002) and a higher ratio of extravascular lung water to total lung volume (EVLWV/TLV) (1.25 [0.80, 1.76] vs 0.66 [0.01, 1.03]; P < 0.0001) by QCT imaging, indicating greater lung congestion. EVLWV/TLV was directly correlated with pulmonary vascular pressures at rest, with stronger correlations observed during exercise. Patients with increasing tertiles of EVLWV/TLV demonstrated higher mean pulmonary artery pressures at rest (34 ± 11 mm Hg vs 39 ± 14 mm Hg vs 45 ± 17 mm Hg; P = 0.0003) and during exercise (55 ± 17 mm Hg vs 59 ± 17 mm Hg vs 69 ± 22 mm Hg; P = 0.0003). CONCLUSIONS: QCT imaging identifies subclinical lung congestion in HFpEF that is not clinically apparent but is related to abnormalities in pulmonary vascular hemodynamics. These data provide new insight into the long-term effects of altered hemodynamics on pulmonary structure and function in HFpEF.

Association of Computed Tomography Densitometry with Disease Severity, Functional Decline, and Survival in Systemic Sclerosis-associated Interstitial Lung Disease.

Rationale: Measuring disease extent and progression of systemic sclerosis-associated interstitial lung disease (SSc-ILD) is challenging, with recent studies suggesting potential utility of quantitative measurements from computed tomography (CT) scans.Objectives: To determine the associations of quantitative computed tomography (qCT) density-based measures with physiological parameters, visual CT scores, and survival in patients with SSc-ILD.Methods: Patients with SSc-ILD and volumetric high-resolution CT images with ≤1.25-mm slice thickness were retrospectively identified. Cardiothoracic radiologists produced visual CT scores of ground glass, reticulation, and honeycombing, with visual fibrosis score equaling the sum of reticulation and honeycombing. qCT measurements included high-attenuation areas (HAA), skewness, kurtosis, and mean lung attenuation (MLA). Associations of qCT measures with pulmonary physiology, visual CT scores, and mortality were analyzed using Spearman's rank correlation and Cox regression.Results: A total of 503 CT scans from 170 patients with SSc-ILD were included. qCT HAA, skewness, kurtosis, and MLA were associated with lung function and visual fibrosis scores, independent of age, sex, and pack-years, using both baseline and change data. Baseline and changes in qCT measures (except ∆skewness) were associated with mortality on unadjusted analysis. Changes in all qCT variables remained associated with survival after adjustment for baseline age, sex, pack-years, and lung function, but not when adjusting for changes in lung function. ∆HAA and ∆MLA were associated with survival after adjustment for age, sex, pack-years, and change in visual CT scores.Conclusions: CT density measurements correlate with physiologic impairment and visual CT scores in patients with SSc-ILD; however, they were not associated with survival independent of changes in pulmonary physiology. The clinical utility of more sophisticated qCT measures should be explored.

Centrally located lung cancer and risk of occult nodal disease: an objective evaluation of multiple definitions of tumour centrality with dedicated imaging software.

INTRODUCTION: Current guidelines recommend invasive mediastinal staging in patients with centrally located radiographic stage T1N0M0 nonsmall cell lung cancer (NSCLC). The lack of a specific definition of a central tumour has resulted in discrepancies among guidelines and heterogeneity in practice patterns. METHODS: Our objective was to study specific definitions of tumour centrality and their association with occult nodal disease. Pre-operative chest computed tomography scans from patients with clinical (c) T1N0M0 NSCLC were processed with a dedicated software system that divides the lungs in thirds following vertical and concentric lines. This software accurately assigns tumours to a specific third based both on the location of the centre of the tumour and its most medial aspect, creating eight possible definitions of central tumours. RESULTS: 607 patients were included in our study. Surgery was performed for 596 tumours (98%). The overall pathological (p) N disease was: 504 (83%) N0, 56 (9%) N1, 47 (8%) N2 and no N3. The prevalence of N2 disease remained relatively low regardless of tumour location. Central tumours were associated with upstaging from cN0 to any N (pN1/pN2). Two definitions were associated with upstaging to any N: concentric lines, inner one-third, centre of the tumour (OR 3.91, 95% CI 1.85-8.26; p<0.001) and concentric lines, inner two-thirds, most medial aspect of the tumour (OR 1.91, 95% CI 1.23-2.97; p=0.004). CONCLUSIONS: We objectively identified two specific definitions of central tumours. While the rate of occult mediastinal disease was relatively low regardless of tumour location, central tumours were associated with upstaging from cN0 to any N.

A Novel Method of Estimating Small Airway Disease Using Inspiratory-to-Expiratory Computed Tomography.

BACKGROUND: Disease accumulates in the small airways without being detected by conventional measurements. OBJECTIVES: To quantify small airway disease using a novel computed tomography (CT) inspiratory-to-expiratory approach called the disease probability measure (DPM) and to investigate the association with pulmonary function measurements. METHODS: Participants from the population-based CanCOLD study were evaluated using full-inspiration/full-expiration CT and pulmonary function measurements. Full-inspiration and full-expiration CT images were registered, and each voxel was classified as emphysema, gas trapping (GasTrap) related to functional small airway disease, or normal using two classification approaches: parametric response map (PRM) and DPM (VIDA Diagnostics, Inc., Coralville, IA, USA). RESULTS: The participants included never-smokers (n = 135), at risk (n = 97), Global Initiative for Chronic Obstructive Lung Disease I (GOLD I) (n = 140), and GOLD II chronic obstructive pulmonary disease (n = 96). PRMGasTrap and DPMGasTrap measurements were significantly elevated in GOLD II compared to never-smokers (p < 0.01) and at risk (p < 0.01), and for GOLD I compared to at risk (p < 0.05). Gas trapping measurements were significantly elevated in GOLD II compared to GOLD I (p < 0.0001) using the DPM classification only. Overall, DPM classified significantly more voxels as gas trapping than PRM (p < 0.0001); a spatial comparison revealed that the expiratory CT Hounsfield units (HU) for voxels classified as DPMGasTrap but PRMNormal (PRMNormal- DPMGasTrap = -785 ± 72 HU) were significantly reduced compared to voxels classified normal by both approaches (PRMNormal-DPMNormal = -722 ± 89 HU; p < 0.0001). DPM and PRMGasTrap measurements showed similar, significantly associations with forced expiratory volume in 1 s (FEV1) (p < 0.01), FEV1/forced vital capacity (p < 0.0001), residual volume/total lung capacity (p < 0.0001), bronchodilator response (p < 0.0001), and dyspnea (p < 0.05). CONCLUSION: CT inspiratory-to-expiratory gas trapping measurements are significantly associated with pulmonary function and symptoms. There are quantitative and spatial differences between PRM and DPM classification that need pathological investigation.

Association Between Expiratory Central Airway Collapse and Respiratory Outcomes Among Smokers.

IMPORTANCE: Central airway collapse greater than 50% of luminal area during exhalation (expiratory central airway collapse [ECAC]) is associated with cigarette smoking and chronic obstructive pulmonary disease (COPD). However, its prevalence and clinical significance are unknown. OBJECTIVE: To determine whether ECAC is associated with respiratory morbidity in smokers independent of underlying lung disease. DESIGN, SETTING, AND PARTICIPANTS: Analysis of paired inspiratory-expiratory computed tomography images from a large multicenter study (COPDGene) of current and former smokers from 21 clinical centers across the United States. Participants were enrolled from January 2008 to June 2011 and followed up longitudinally until October 2014. Images were initially screened using a quantitative method to detect at least a 30% reduction in minor axis tracheal diameter from inspiration to end-expiration. From this sample of screen-positive scans, cross-sectional area of the trachea was measured manually at 3 predetermined levels (aortic arch, carina, and bronchus intermedius) to confirm ECAC (>50% reduction in cross-sectional area). EXPOSURES: Expiratory central airway collapse. MAIN OUTCOMES AND MEASURES: The primary outcome was baseline respiratory quality of life (St George's Respiratory Questionnaire [SGRQ] scale 0 to 100; 100 represents worst health status; minimum clinically important difference [MCID], 4 units). Secondary outcomes were baseline measures of dyspnea (modified Medical Research Council [mMRC] scale 0 to 4; 4 represents worse dyspnea; MCID, 0.7 units), baseline 6-minute walk distance (MCID, 30 m), and exacerbation frequency (events per 100 person-years) on longitudinal follow-up. RESULTS: The study included 8820 participants with and without COPD (mean age, 59.7 [SD, 6.9] years; 4667 [56.7%] men; 4559 [51.7%] active smokers). The prevalence of ECAC was 5% (443 cases). Patients with ECAC compared with those without ECAC had worse SGRQ scores (30.9 vs 26.5 units; P < .001; absolute difference, 4.4 [95% CI, 2.2-6.6]) and mMRC scale scores (median, 2 [interquartile range [IQR], 0-3]) vs 1 [IQR, 0-3]; P < .001]), but no significant difference in 6-minute walk distance (399 vs 417 m; absolute difference, 18 m [95% CI, 6-30]; P = .30), after adjustment for age, sex, race, body mass index, forced expiratory volume in the first second, pack-years of smoking, and emphysema. On follow-up (median, 4.3 [IQR, 3.2-4.9] years), participants with ECAC had increased frequency of total exacerbations (58 vs 35 events per 100 person-years; incidence rate ratio [IRR], 1.49 [95% CI, 1.29-1.72]; P < .001) and severe exacerbations requiring hospitalization (17 vs 10 events per 100 person-years; IRR, 1.83 [95% CI, 1.51-2.21]; P < .001). CONCLUSIONS AND RELEVANCE: In a cross-sectional analysis of current and former smokers, the presence of ECAC was associated with worse respiratory quality of life. Further studies are needed to assess long-term associations with clinical outcomes.

Patterns of Emphysema Heterogeneity.

BACKGROUND: Although lobar patterns of emphysema heterogeneity are indicative of optimal target sites for lung volume reduction (LVR) strategies, the presence of segmental, or sublobar, heterogeneity is often underappreciated. OBJECTIVE: The aim of this study was to understand lobar and segmental patterns of emphysema heterogeneity, which may more precisely indicate optimal target sites for LVR procedures. METHODS: Patterns of emphysema heterogeneity were evaluated in a representative cohort of 150 severe (GOLD stage III/IV) chronic obstructive pulmonary disease (COPD) patients from the COPDGene study. High-resolution computerized tomography analysis software was used to measure tissue destruction throughout the lungs to compute heterogeneity (≥15% difference in tissue destruction) between (inter-) and within (intra-) lobes for each patient. Emphysema tissue destruction was characterized segmentally to define patterns of heterogeneity. RESULTS: Segmental tissue destruction revealed interlobar heterogeneity in the left lung (57%) and right lung (52%). Intralobar heterogeneity was observed in at least one lobe of all patients. No patient presented true homogeneity at a segmental level. There was true homogeneity across both lungs in 3% of the cohort when defining heterogeneity as ≥30% difference in tissue destruction. CONCLUSION: Many LVR technologies for treatment of emphysema have focused on interlobar heterogeneity and target an entire lobe per procedure. Our observations suggest that a high proportion of patients with emphysema are affected by interlobar as well as intralobar heterogeneity. These findings prompt the need for a segmental approach to LVR in the majority of patients to treat only the most diseased segments and preserve healthier ones.

Understanding the contribution of native tracheobronchial structure to lung function: CT assessment of airway morphology in never smokers.

BACKGROUND: Computed tomographic (CT) airway lumen narrowing is associated with lower lung function. Although volumetric CT measures of airways (wall volume [WV] and lumen volume [LV]) compared to cross sectional measures can more accurately reflect bronchial morphology, data of their use in never smokers is scarce. We hypothesize that native tracheobronchial tree morphology as assessed by volumetric CT metrics play a significant role in determining lung function in normal subjects. We aimed to assess the relationships between airway size, the projected branching generation number (BGN) to reach airways of <2mm lumen diameter -the site for airflow obstruction in smokers- and measures of lung function including forced expiratory volume in 1 second (FEV1) and forced expiratory flow between 25% and 75% of vital capacity (FEF 25-75). METHODS: We assessed WV and LV of segmental and subsegmental airways from six bronchial paths as well as lung volume on CT scans from 106 never smokers. We calculated the lumen area ratio of the subsegmental to segmental airways and estimated the projected BGN to reach a <2mm-lumen-diameter airway assuming a dichotomized tracheobronchial tree model. Regression analysis was used to assess the relationships between airway size, BGN, FEF 25-75, and FEV1. RESULTS: We found that in models adjusted for demographics, LV and WV of segmental and subsegmental airways were directly related to FEV1 (P <0.05 for all the models). In adjusted models for age, sex, race, LV and lung volume or height, the projected BGN was directly associated with FEF 25-75 and FEV1 (P = 0.001) where subjects with lower FEV1 had fewer calculated branch generations between the subsegmental bronchus and small airways. There was no association between airway lumen area ratio and lung volume. CONCLUSION: We conclude that in never smokers, those with smaller central airways had lower airflow and those with lower airflow had less parallel airway pathways independent of lung size. These findings suggest that variability in the structure of the tracheobronchial tree may influence the risk of developing clinically relevant smoking related airway obstruction.

Effect of emphysema on CT scan measures of airway dimensions in smokers.

BACKGROUND: In CT scans of smokers with COPD, the subsegmental airway wall area percent (WA%) is greater and more strongly correlated with FEV1 % predicted than WA% obtained in the segmental airways. Because emphysema is linked to loss of airway tethering and may limit airway expansion, increases in WA% may be related to emphysema and not solely to remodeling. We aimed to first determine whether the stronger association of subsegmental vs segmental WA% with FEV1 % predicted is mitigated by emphysema and, second, to assess the relationships among emphysema, WA%, and total bronchial area (TBA). METHODS: We analyzed CT scan segmental and subsegmental WA% (WA% = 100 × wall area/TBA) of six bronchial paths and corresponding lobar emphysema, lung function, and clinical data in 983 smokers with COPD. RESULTS: Compared with segmental WA%, the subsegmental WA% had a greater effect on FEV1% predicted (-0.8% to -1.7% vs -1.9% to -2.6% per 1-unit increase in WA%, respectively; P < .05 for most bronchial paths). After adjusting for emphysema, the association between subsegmental WA% and FEV1 % predicted was weakened in two bronchial paths. Increases in WA% between bronchial segments correlated directly with emphysema in all bronchial paths (P < .05). In multivariate regression models, emphysema was directly related to subsegmental WA% in most bronchial paths and inversely related to subsegmental TBA in all bronchial paths. CONCLUSION: The greater effect of subsegmental WA% on airflow obstruction is mitigated by emphysema. Part of the emphysema effect might be due to loss of airway tethering, leading to a reduction in TBA and an increase in WA%.

Extraction of airways from CT (EXACT'09).

This paper describes a framework for establishing a reference airway tree segmentation, which was used to quantitatively evaluate fifteen different airway tree extraction algorithms in a standardized manner. Because of the sheer difficulty involved in manually constructing a complete reference standard from scratch, we propose to construct the reference using results from all algorithms that are to be evaluated. We start by subdividing each segmented airway tree into its individual branch segments. Each branch segment is then visually scored by trained observers to determine whether or not it is a correctly segmented part of the airway tree. Finally, the reference airway trees are constructed by taking the union of all correctly extracted branch segments. Fifteen airway tree extraction algorithms from different research groups are evaluated on a diverse set of twenty chest computed tomography (CT) scans of subjects ranging from healthy volunteers to patients with severe pathologies, scanned at different sites, with different CT scanner brands, models, and scanning protocols. Three performance measures covering different aspects of segmentation quality were computed for all participating algorithms. Results from the evaluation showed that no single algorithm could extract more than an average of 74% of the total length of all branches in the reference standard, indicating substantial differences between the algorithms. A fusion scheme that obtained superior results is presented, demonstrating that there is complementary information provided by the different algorithms and there is still room for further improvements in airway segmentation algorithms.

Influence of rapid fluid loading on airway structure and function in healthy humans.

BACKGROUND: The present study examined the influence of rapid intravenous fluid loading (RFL) on airway structure and pulmonary vascular volumes using computed tomography imaging and the subsequent impact on pulmonary function in healthy adults (n = 16). METHODS AND RESULTS: Total lung capacity (DeltaTLC = -6%), forced vital capacity (DeltaFVC = -14%), and peak expiratory flow (DeltaPEF = -19%) decreased, and residual volume (DeltaRV = +38%) increased post-RFL (P < .05). Airway luminal cross-sectional area (CSA) decreased at the trachea, and at airway generation 3 (P < .05), wall thickness changed minimally with a tendency for increasing in generation five (P = .13). Baseline pulmonary function was positively associated with airway luminal CSA; however, this relationship deteriorated after RFL. Lung tissue volume and pulmonary vascular volumes increased 28% (P < .001) post-RFL, but did not fully account for the decline in TLC. CONCLUSIONS: These data suggest that RFL results in obstructive/restrictive PF changes that are most likely related to structural changes in smaller airways or changes in extrapulmonary vascular beds.

Comparison of airway diameter measurements from an anthropomorphic airway tree phantom using hyperpolarized 3He MRI and high-resolution computed tomography.

An anthropomorphic airway tree phantom was imaged with both hyperpolarized (HP) 3He MRI using a dynamic projection scan and computed tomography (CT). Airway diameter measurements from the HP 3He MR images obtained using a newly developed model-based algorithm were compared against their corresponding CT values quantified with a well-established method. Of the 45 airway segments that could be evaluated with CT, only 14 airway segments (31%) could be evaluated using HP 3He MRI. No airway segments smaller than approximately 4 mm in diameter and distal to the fourth generation were adequate for analysis in MRI. For the 14 airway segments measured, only two airway segments yielded a non-equivalent comparison between the two imaging modalities, while eight more had inconclusive comparison results, leaving only four airway segments (29%) that satisfied the designed equivalence criteria. Some of the potential problems in airway diameter quantification described in the formulation of the model-based algorithm were observed in this study. These results suggest that dynamic projection HP 3He MRI may have limited utility for measuring airway segment diameters, particularly those of the central airways.

Quantitative analysis of pulmonary airway tree structures.

A method for computationally efficient skeletonization of three-dimensional tubular structures is reported. The method is specifically targeting skeletonization of vascular and airway tree structures in medical images but it is general and applicable to many other skeletonization tasks. The developed approach builds on the following novel concepts and properties: fast curve-thinning algorithm to increase computational speed, endpoint re-checking to avoid generation of spurious side branches, depth-and-length sensitive pruning, and exact tree-branch partitioning allowing branch volume and surface measurements. The method was validated in computer and physical phantoms and in vivo CT scans of human lungs. The validation studies demonstrated sub-voxel accuracy of branch point positioning, insensitivity to changes of object orientation, and high reproducibility of derived quantitative indices of the tubular structures offering a significant improvement over previously reported methods (p<<0.001).

Segmentation and quantitative analysis of intrathoracic airway trees from computed tomography images.

The segmentation of the human airway tree from volumetric multidetector-row computed tomography images is an important prerequisite for many clinical applications and physiologic studies. We present a new airway segmentation method based on fuzzy connectivity. Small adaptive regions of interest are used that follow the airway branches as they are segmented. This method works on various types of scans (low dose and regular dose, normal subjects and diseased subjects) without the need for the user to manually adjust any parameters. Comparison with a commonly used region-growing segmentation algorithm shows that this method retrieves a significantly higher count of airway branches. In an additional processing step, this method provides accurate cross-sectional airway measurements that are conducted in the original gray-level volume. Validation on a phantom shows that subvoxel accuracy is achieved for all airway sizes and airway orientations. The utility of the reported method is demonstrated in a comparative analysis of normal and cystic fibrosis airway trees.

Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans.

The segmentation of the human airway tree from volumetric computed tomography (CT) images builds an important step for many clinical applications and for physiological studies. Previously proposed algorithms suffer from one or several problems: leaking into the surrounding lung parenchyma, the need for the user to manually adjust parameters, excessive runtime. Low-dose CT scans are increasingly utilized in lung screening studies, but segmenting them with traditional airway segmentation algorithms often yields less than satisfying results. In this paper, a new airway segmentation method based on fuzzy connectivity is presented. Small adaptive regions of interest are used that follow the airway branches as they are segmented. This has several advantages. It makes it possible to detect leaks early and avoid them, the segmentation algorithm can automatically adapt to changing image parameters, and the computing time is kept within moderate values. The new method is robust in the sense that it works on various types of scans (low-dose and regular dose, normal subjects and diseased subjects) without the need for the user to manually adjust any parameters. Comparison with a commonly used region-grow segmentation algorithm shows that the newly proposed method retrieves a significantly higher count of airway branches. A method that conducts accurate cross-sectional airway measurements on airways is presented as an additional processing step. Measurements are conducted in the original gray-level volume. Validation on a phantom shows that subvoxel accuracy is achieved for all airway sizes and airway orientations.

Matching and anatomical labeling of human airway tree.

Matching of corresponding branchpoints between two human airway trees, as well as assigning anatomical names to the segments and branchpoints of the human airway tree, are of significant interest for clinical applications and physiological studies. In the past, these tasks were often performed manually due to the lack of automated algorithms that can tolerate false branches and anatomical variability typical for in vivo trees. In this paper, we present algorithms that perform both matching of branchpoints and anatomical labeling of in vivo trees without any human intervention and within a short computing time. No hand-pruning of false branches is required. The results from the automated methods show a high degree of accuracy when validated against reference data provided by human experts. 92.9% of the verifiable branchpoint matches found by the computer agree with experts' results. For anatomical labeling, 97.1% of the automatically assigned segment labels were found to be correct.

Evaluation of the human airway with multi-detector x-ray-computed tomography and optical imaging.

Defining the healthy human airway is important in enhancing our understanding of pulmonary disease states such as inflammation and cancer. The structure of the human airway, both static and dynamic, can be assessed using multi-detector CT (MDCT) scanning. This modality also allows for the evaluation of structures outside of the airway. The airway wall can be directly visualized using CCD chip high-resolution color optical imaging through endoscopy allowing bronchial wall evaluation by traditional biopsy methods, as well as by newer optically based strategies. We suggest that these two imaging modalities, MDCT and optical imaging, provide complementary information about the normal airway, and the airway in various diseases. Methods for evaluating the human airway using MDCT images are presented facilitating automatic airway segmentation, branchpoint finding and airway dimension analysis. The airway wall color is objectively evaluated as an important surrogate for airway wall inflammation and cancer formation, and the integration of the color endoscopic information into the MDCT scan data set is currently ongoing. The amalgamation of these two digital imaging modalities appears increasingly useful for enabling biopsy techniques, and for relating structure and function of the airway. In addition, these developments may be progressively more useful in understanding the normal airway structure and function, for defining airway diseases patterns and for guiding biopsy and therapeutic procedures.

CT-based geometry analysis and finite element models of the human and ovine bronchial tree.

The interpretation of experimental results from functional medical imaging is complicated by intersubject and interspecies differences in airway geometry. The application of computational models in understanding the significance of these differences requires methods for generation of subject-specific geometric models of the bronchial airway tree. In the current study, curvilinear airway centerline and diameter models have been fitted to human and ovine bronchial trees using detailed data segmented from multidetector row X-ray-computed tomography scans. The trees have been extended to model the entire conducting airway system by using a volume-filling algorithm to generate airway centerline locations within detailed volume descriptions of the lungs or lobes. Analysis of the geometry of the scan-based and model-based airways has verified their consistency with measures from previous anatomic studies and has provided new anatomic data for the ovine bronchial tree. With the use of an identical parameter set, the volume-filling algorithm has produced airway trees with branching asymmetry appropriate for the human and ovine lung, demonstrating the dependence of the method on the shape of the lung or lobe volume. The modeling approach that has been developed can be applied to any level of detail of the airway tree and into any volume shape for the lung; hence it can be used directly for different individuals or animals and for any number of scan-based airways. The resulting models are subject-specific computational meshes with anatomically consistent geometry, suitable for application in simulation studies.