CNNs trained with adult data are useful in pediatrics. A pneumonia classification example.

BACKGROUND AND OBJECTIVES: The scarcity of data for training deep learning models in pediatrics has prompted questions about the feasibility of employing CNNs trained with adult images for pediatric populations. In this work, a pneumonia classification CNN was used as an exploratory example to showcase the adaptability and efficacy of such models in pediatric healthcare settings despite the inherent data constraints. METHODS: To develop a curated training dataset with reduced biases, 46,947 chest X-ray images from various adult datasets were meticulously selected. Two preprocessing approaches were tried to assess the impact of thoracic segmentation on model attention outside the thoracic area. Evaluation of our approach was carried out on a dataset containing 5,856 chest X-rays of children from 1 to 5 years old. RESULTS: An analysis of attention maps indicated that networks trained with thorax segmentation placed less attention on regions outside the thorax, thus eliminating potential bias. The ensuing network exhibited impressive performance when evaluated on an adult dataset, achieving a pneumonia discrimination AUC of 0.95. When tested on a pediatric dataset, the pneumonia discrimination AUC reached 0.82. CONCLUSIONS: The results of this study show that adult-trained CNNs can be effectively applied to pediatric populations. This could potentially shift focus towards validating adult models over pediatric population instead of training new CNNs with limited pediatric data. To ensure the generalizability of deep learning models, it is important to implement techniques aimed at minimizing biases, such as image segmentation or low-quality image exclusion.

Preacinar Arterial Dilation Mediates Outcomes of Quantitative Interstitial Abnormalities in COPDGene.

RATIONALE: Quantitative interstitial abnormalities (QIA) are a computed tomography (CT) measure of early parenchymal lung disease associated with worse clinical outcomes including exercise capacity and symptoms. The presence of pulmonary vasculopathy in QIA and its role in the QIA-outcome relationship is unknown. OBJECTIVES: To quantify radiographic pulmonary vasculopathy in quantitative interstitial abnormalities (QIA) and determine if this vasculopathy mediates the QIA-outcome relationship. METHODS: Ever-smokers with QIA, outcome, and pulmonary vascular mediator data were identified from the COPDGene cohort. CT-based vascular mediators were: right ventricle-to-left ventricle ratio (RV/LV), pulmonary artery-to-aorta ratio (PA/Ao), and pre-acinar intraparenchymal arterial dilation (PA volume 5-20mm2 in cross-sectional area, normalized to total arterial volume). Outcomes were: six-minute walk distance (6MWD) and modified Medical Council Research Council (mMRC) Dyspnea score ≥2. Adjusted causal mediation analyses were used to determine if the pulmonary vasculature mediated the QIA effect on outcomes. Associations of pre-acinar arterial dilation with select plasma biomarkers of pulmonary vascular dysfunction were examined. MAIN RESULTS: Among 8,200 participants, QIA burden correlated positively with vascular damage measures including pre-acinar arterial dilation. Pre-acinar arterial dilation mediated 79.6% of the detrimental impact of QIA on 6MWD (56.2-100%, p<0.001). PA/Ao was a weak mediator and RV/LV was a suppressor. Similar results were observed in the QIA-mMRC relationship. Pre-acinar arterial dilation correlated with increased pulmonary vascular dysfunction biomarker levels including angiopoietin-2 and NT-proBNP. CONCLUSIONS: Parenchymal quantitative interstitial abnormalities (QIA) deleteriously impact outcomes primarily through pulmonary vasculopathy. Pre-acinar arterial dilation may be a novel marker of pulmonary vasculopathy in QIA.

COPD: pulmonary vascular volume associated with cardiac structure and function.

BACKGROUND: Early recognition of cardiac dysfunction in patients with chronic obstructive pulmonary disease (COPD) may prevent future cardiac impairment and improve prognosis. Quantitative assessment of subsegmental and segmental vessel volume by Computed Tomographic (CT) imaging can provide a surrogate of pulmonary vascular remodeling. We aimed to examine the relationship between lung segmental- and subsegmental vessel volume, and echocardiographic measures of cardiac structure and function in patients with COPD. METHODS: We studied 205 participants with COPD, included in a large cohort study of cardiovascular disease in COPD patients. Participants had an available CT scan and echocardiogram. Artificial intelligence (AI) algorithms calculated the subsegmental vessel fraction as the vascular volume in vessels below 10 mm2 in cross-sectional area, indexed to total intrapulmonary vessel volume. Linear regressions were conducted, and standardized ß-coefficients were calculated. Scatterplots were created to visualize the continuous correlations between the vessel fractions and echocardiographic parameters. RESULTS: We found that lower subsegmental vessel fraction and higher segmental vessel volume were correlated with higher left ventricular (LV) mass, LV diastolic dysfunction, and inferior vena cava (IVC) dilatation. Subsegmental vessel fraction was correlated with right ventricular (RV) remodeling, while segmental vessel fraction was correlated with higher pulmonary pressure. Measures of LV mass and right atrial pressure displayed the strongest correlations with pulmonary vasculature measures. CONCLUSION: Pulmonary vascular remodeling in patients with COPD, may negatively affect cardiac structure and function. AI-identified remodeling in pulmonary vasculature may provide a tool for early identification of COPD patients at higher risk for cardiac impairment.

Silent Airway Mucus Plugs in COPD and Clinical Implications.

BACKGROUND: Airway mucus plugs are frequently identified on CT scans of patients with COPD with a smoking history without mucus-related symptoms (ie, cough, phlegm [silent mucus plugs]). RESEARCH QUESTION: In patients with COPD, what are the risk and protective factors associated with silent airway mucus plugs? Are silent mucus plugs associated with functional, structural, and clinical measures of disease? STUDY DESIGN AND METHODS: We identified mucus plugs on chest CT scans of participants with COPD from the COPDGene study. The mucus plug score was defined as the number of pulmonary segments with mucus plugs, ranging from 0 to 18, and categorized into three groups (0, 1-2, and ≥ 3). We determined risk and protective factors for silent mucus plugs and the associations of silent mucus plugs with measures of disease severity using multivariable linear and logistic regression models. RESULTS: Of 4,363 participants with COPD, 1,739 had no cough or phlegm. Among the 1,739 participants, 627 (36%) had airway mucus plugs identified on CT scan. Risk factors of silent mucus plugs (compared with symptomatic mucus plugs) were older age (OR, 1.02), female sex (OR, 1.40), and Black race (OR, 1.93) (all P values < .01). Among those without cough or phlegm, silent mucus plugs (vs absence of mucus plugs) were associated with worse 6-min walk distance, worse resting arterial oxygen saturation, worse FEV1 % predicted, greater emphysema, thicker airway walls, and higher odds of severe exacerbation in the past year in adjusted models. INTERPRETATION: Mucus plugs are common in patients with COPD without mucus-related symptoms. Silent mucus plugs are associated with worse functional, structural, and clinical measures of disease. CT scan-identified mucus plugs can complement the evaluation of patients with COPD.

Suspected Bronchiectasis and Mortality in Adults With a History of Smoking Who Have Normal and Impaired Lung Function : A Cohort Study.

BACKGROUND: Bronchiectasis in adults with chronic obstructive pulmonary disease (COPD) is associated with greater mortality. However, whether suspected bronchiectasis-defined as incidental bronchiectasis on computed tomography (CT) images plus clinical manifestation-is associated with increased mortality in adults with a history of smoking with normal spirometry and preserved ratio impaired spirometry (PRISm) is unknown. OBJECTIVE: To determine the association between suspected bronchiectasis and mortality in adults with normal spirometry, PRISm, and obstructive spirometry. DESIGN: Prospective, observational cohort. SETTING: The COPDGene (Genetic Epidemiology of Chronic Obstructive Pulmonary Disease) study. PARTICIPANTS: 7662 non-Hispanic Black or White adults, aged 45 to 80 years, with 10 or more pack-years of smoking history. Participants who were former and current smokers were stratified into normal spirometry (n = 3277), PRISm (n = 986), and obstructive spirometry (n = 3399). MEASUREMENTS: Bronchiectasis identified by CT was ascertained using artificial intelligence-based measurements of an airway-to-artery ratio (AAR) greater than 1 (AAR >1), a measure of bronchial dilatation. The primary outcome of "suspected bronchiectasis" was defined as an AAR >1 of greater than 1% plus 2 of the following: cough, phlegm, dyspnea, and history of 2 or more exacerbations. RESULTS: Among the 7662 participants (mean age, 60 years; 52% women), 1352 (17.6%) had suspected bronchiectasis. During a median follow-up of 11 years, 2095 (27.3%) died. Ten-year mortality risk was higher in participants with suspected bronchiectasis, compared with those without suspected bronchiectasis (normal spirometry: difference in mortality probability [Pr], 0.15 [95% CI, 0.09 to 0.21]; PRISm: Pr, 0.07 [CI, -0.003 to 0.15]; obstructive spirometry: Pr, 0.06 [CI, 0.03 to 0.09]). When only CT was used to identify bronchiectasis, the differences were attenuated in the normal spirometry (Pr, 0.04 [CI, -0.001 to 0.08]). LIMITATIONS: Only 2 racial groups were studied. Only 1 measurement was used to define bronchiectasis on CT. Symptoms of suspected bronchiectasis were nonspecific. CONCLUSION: Suspected bronchiectasis was associated with a heightened risk for mortality in adults with normal and obstructive spirometry. PRIMARY FUNDING SOURCE: National Heart, Lung, and Blood Institute.

Association Between Pulmonary Vascular Volume and Cardiac Structure and Function in Patients With Atrial Fibrillation.

Pulmonary vascular abnormalities, quantified from computed tomography scans, have frequently been observed in patients with pulmonary diseases. However, little is known about pulmonary vascular changes in patients with cardiac disease. Thus, we aimed to examine the cardiopulmonary relation in patients with atrial fibrillation (AF) by comparing pulmonary vascular volume (PVV) to echocardiographic measures and AF severity. A total of 742 patients (median age 63 years, 70% men) who underwent ablation for AF were included. Preprocedural cardiac computed tomography was used to measure the total and small-vessel PVV, along with the pulmonary artery to aorta ratio and the degree of emphysema. The association between PVV and echocardiographic parameters was evaluated using a multivariable linear regression analysis. Lower total and small-vessel PVV were associated with more impaired measures of cardiac structure and function, including but not limited to left ventricular ejection fraction and peak atrial longitudinal strain. Patients with reduced total and small-vessel PVV had higher odds of having persistent AF than paroxysmal AF in the unadjusted logistic regression analyses. However, after clinical and echocardiographic adjustments, only reduced small-vessel PVV remained independently associated with persistent AF (odds ratio 1.90, 95% confidence interval 1.26 to 2.87, p = 0.002). In conclusion, pulmonary vascular remodeling is associated with persistent AF and with more impaired measures of cardiac structure and function, providing further insights into heart-lung interactions in this patient group.

CT imaging determinants of persistent hypoxemia in acute intermediate-risk pulmonary embolism.

The factors associated with persistent hypoxemia after pulmonary embolus (PE) are not well understood. Predicting the need for oxygen post discharge at the time of diagnosis using available CT imaging will enable better discharge planning. To examine the relationship between CT derived imaging markers (automated computation of arterial small vessel fraction, pulmonary artery diameter to aortic diameter ratio (PA:A), right to left ventricular diameter ratio (RV:LV) and new oxygen requirement at the time of discharge in patients diagnosed with acute intermediate-risk PE. CT measurements were obtained in a retrospective cohort of patients with acute-intermediate risk PE admitted to Brigham and Women's Hospital between 2009 and 2017. Twenty one patients without a history of lung disease requiring home oxygen and 682 patients without discharge oxygen requirements were identified. There was an increased median PA:A ratio (0.98 vs. 0.92, p = 0.02) and arterial small vessel fraction (0.32 vs. 0.39, p = 0.001) in the oxygen-requiring group], but no difference in the median RV:LV ratio (1.20 vs. 1.20, p = 0.74). Being in the upper quantile for the arterial small vessel fraction was associated with decreased odds of oxygen requirement (OR 0.30 [0.10-0.78], p = 0.02). Loss of arterial small vessel volume as measured by arterial small vessel fraction and an increase in the PA:A ratio at the time of diagnosis were associated with the presence of persistent hypoxemia on discharge in acute intermediate-risk PE.

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.

QUANTITATIVE BIOMARKERS REPRODUCIBILITY USING GENERATIVE ADVERSARIAL APPROACHES IN REDUCED TO CONVENTIONAL DOSE CT.

In recent years, several techniques for image-to-image translation by means of generative adversarial neural networks (GAN) have been proposed to learn mapping characteristics between a source and a target domain. In particular, in the medical imaging field conditional GAN frameworks with paired samples (cGAN) and unconditional cycle-consistent GANs with unpaired data (CycleGAN) have been demonstrated as a powerful scheme to model non-linear mappings that produce realistic target images from different modality sources. When proposing the usage and adaptation of these frameworks for medical image synthesis, quantitative and qualitative validation are usually performed by assessing the similarity between synthetic and target images in terms of metrics such as mean absolute error (MAE) or structural similarity (SSIM) index. However, an evaluation of clinically relevant markers showing that diagnostic information is not overlooked in the translation process is often missing. In this work, we aim at demonstrating the importance of validating medical image-to-image translation techniques by assessing their effect on the measurement of clinically relevant metrics and biomarkers. We implemented both a conditional and an unconditional approach to synthesize conventional dose chest CT scans from reduced dose CT and show that while both visually and in terms of traditional metrics the network appears to successfully minimize perceptual discrepancies, these methods are not reliable to systematically reproduce quantitative measurements of various chest biomarkers.

Pulmonary arterial pruning is associated with CT-derived bronchiectasis progression in smokers.

Loss of small pulmonary arteries measured as the ratio of blood vessel volume in arteries <5 mm2 in cross-section to total arterial blood vessel volume (BV5a/TBVa), with lower values indicating more pruning, was associated with 5-yr progressing CT-derived bronchiectasis in smokers (Odds Ratio (OR) [95% Confidence interval], 1.28 [1.07-1.53] per 5% lower BV5a/TBVa, P = 0.007). Corresponding results in smokers with COPD were: OR 1.45 [1.11-1.89] per 5% lower BV5a/TBVa, P = 0.007. The results support a vascular factor for structural progression of bronchiectasis.

Loss of Pulmonary Vascular Volume as a Predictor of Right Ventricular Dysfunction and Mortality in Acute Pulmonary Embolism.

BACKGROUND: In acute pulmonary embolism, chest computed tomography angiography derived metrics, such as the right ventricle (RV): left ventricle ratio are routinely used for risk stratification. Paucity of intraparenchymal blood vessels has previously been described, but their association with clinical biomarkers and outcomes has not been studied. We sought to determine if small vascular volumes measured on computed tomography scans were associated with an abnormal RV on echocardiography and mortality. We hypothesized that decreased small venous volume would be associated with greater RV dysfunction and increased mortality. METHODS: A retrospective cohort of patients with intermediate risk pulmonary embolism admitted to Brigham and Women's Hospital between 2009 and 2017 was assembled, and clinical and radiographic data were obtained. We performed 3-dimensional reconstructions of vasculature to assess intraparenchymal vascular volumes. Statistical analyses were performed using multivariable regression and cox proportional hazards models, adjusting for age, sex, lung volume, and small arterial volume. RESULTS: Seven hundred twenty-two subjects were identified of whom 573 had documented echocardiography. A 50% reduction in small venous volume was associated with an increased risk of RV dilation (relative risk: 1.38 [95% CI, 1.18-1.63], P<0.001), RV dysfunction (relative risk: 1.62 [95% CI, 1.36-1.95], P<0.001), and RV strain (relative risk: 1.67 [95% CI, 1.37-2.04], P<0.001); increased cardiac biomarkers, and higher 30-day and 90-day mortality (hazard ratio: 2.50 [95% CI, 1.33-4.67], P=0.004 and hazard ratio: 1.84 [95% CI, 1.11-3.04], P=0.019, respectively). CONCLUSIONS: Loss of small venous volume quantified from computed tomography angiography is associated with increased risk of abnormal RV on echocardiography, abnormal cardiac biomarkers, and higher risk of 30- and 90-day mortality. Small venous volume may be a useful marker for assessing disease severity in acute pulmonary embolism.

Quantification of Arterial and Venous Morphologic Markers in Pulmonary Arterial Hypertension Using CT Imaging.

BACKGROUND: Pulmonary hypertension is a heterogeneous disease, and a significant portion of patients at risk for it have CT imaging available. Advanced automated processing techniques could be leveraged for early detection, screening, and development of quantitative phenotypes. Pruning and vascular tortuosity have been previously described in pulmonary arterial hypertension (PAH), but the extent of these phenomena in arterial vs venous pulmonary vasculature and in exercise pulmonary hypertension (ePH) have not been described. RESEARCH QUESTION: What are the arterial and venous manifestations of pruning and vascular tortuosity using CT imaging in PAH, and do they also occur in ePH? STUDY DESIGN AND METHODS: A cohort of patients with PAH and ePH and control subjects with available CT angiograms were retrospectively identified to examine the differential arterial and venous presence of pruning and tortuosity in patients with precapillary pulmonary hypertension not confounded by lung or thromboembolic disease. The pulmonary vasculature was reconstructed, and an artificial intelligence method was used to separate arteries and veins and to compute arterial and venous vascular volumes and tortuosity. RESULTS: A total of 42 patients with PAH, 12 patients with ePH, and 37 control subjects were identified. There was relatively lower (median [interquartile range]) arterial small vessel volume in subjects with PAH (PAH 14.7 [11.7-16.5; P < .0001]) vs control subjects (16.9 [15.6-19.2]) and venous small vessel volume in subjects with PAH and ePH (PAH 8.0 [6.5-9.6; P < .0001]; ePH, 7.8 [7.5-11.4; P = .004]) vs control subjects (11.5 [10.6-12.2]). Higher large arterial volume, however, was only observed in the pulmonary arteries (PAH 17.1 [13.6-23.4; P < .0001] vs control subjects 11.4 [8.1-15.4]). Similarly, tortuosity was higher in the pulmonary arteries in the PAH group (PAH 3.5 [3.3-3.6; P = .0002] vs control 3.2 [3.2-3.3]). INTERPRETATION: Lower small distal pulmonary vascular volume, higher proximal arterial volume, and higher arterial tortuosity were observed in PAH. These can be quantified by using automated techniques from clinically acquired CT scans of patients with ePH and resting PAH.

Paired CT Measures of Emphysema and Small Airways Disease and Lung Function and Exercise Capacity in Smokers with Radiographic Bronchiectasis.

RATIONALE AND OBJECTIVES: Bronchiectasis (BE) is associated with chronic obstructive pulmonary disease (COPD), but emphysema and small airways disease, main pathologic features of COPD, have been sparsely studied in BE. We aimed to objectively assess those features in smokers with and without radiographic BE and examine its relationships to airflow obstruction and exercise capacity. MATERIAL AND METHODS: We measured emphysema and small airways disease on paired inspiratory-expiratory computed tomography (CT) scans with the parametric response map (PRMEMPH and PRMSAD) method in 1184 smokers with and without radiographic BE. PRMSAD and PRMEMPH are expressed as the percentage of lung area. Clinical, spirometry, and exercise capacity data were measured with standardized methods. The differences in PRMSAD and PRMEMPH between subjects with and without radiographic BE were assessed using multivariable linear regression analysis, and their associations with FEV1 and six-minute walk test (6MWT) were assessed with generalized linear models. RESULTS: Out of 1184 subjects, 383 (32%) had radiographic BE. PRMEMPH but not PRMSAD was higher in subjects with radiographic BE than those without radiographic BE in adjusted models. Subjects with radiographic BE and PRMEMPH (defined as ≥5% on paired CTs) had lower FEV1 (least square mean, 1479 mL vs. 2350 mL p < 0.0001) and 6MWT (372 m vs. 426 m p = 0.0007) than those with radiographic BE alone in adjusted models. CONCLUSION: Smokers with radiographic BE have an increased burden of emphysema on paired CTs, and those with radiographic BE and emphysema have lower airflow and exercise capacity.

Smaller Left Ventricle Size at Noncontrast CT Is Associated with Lower Mortality in COPDGene Participants.

Background Smokers with chronic obstructive pulmonary disease (COPD) have smaller left ventricles (LVs) due to reduced preload. Skeletal muscle wasting is also common in COPD, but less is known about its contribution to LV size. Purpose To explore the relationships between CT metrics of emphysema, venous vascular volume, and sarcopenia with the LV epicardial volume (LVEV) (myocardium and chamber) estimated from chest CT images in participants with COPD and then to determine the clinical relevance of the LVEV in multivariable models, including sex and anthropomorphic metrics. Materials and Methods The COPDGene study (ClinicalTrials.gov identifier: NCT00608764) is an ongoing prospective longitudinal observational investigation that began in 2006. LVEV, distal pulmonary venous blood volume for vessels smaller than 5 mm2 in cross section (BV5), CT emphysema, and pectoralis muscle area were retrospectively extracted from 3318 nongated, unenhanced COPDGene CT scans. Multivariable linear and Cox regression models were used to explore the association between emphysema, venous BV5, pectoralis muscle area, and LVEV as well as the association of LVEV with health status using the St George's Respiratory Questionnaire, 6-minute walk distance, and all-cause mortality. Results The median age of the cohort was 64 years (interquartile range, 57-70 years). Of the 2423 participants, 1806 were men and 617 were African American. The median LVEV between Global Initiative for Chronic Obstructive Lung Disease (GOLD) 1 and GOLD 4 COPD was reduced by 13.9% in women and 17.7% in men (P < .001 for both). In fully adjusted models, higher emphysema percentage (ß = -4.2; 95% confidence interval [CI]: -5.0, -3.4; P < .001), venous BV5 (ß = 7.0; 95% CI: 5.7, 8.2; P < .001), and pectoralis muscle area (ß = 2.7; 95% CI: 1.2, 4.1; P < .001) were independently associated with reduced LVEV. Reductions in LVEV were associated with improved health status (ß = 0.3; 95% CI: 0.1, 0.4) and 6-minute walk distance (ß = -12.2; 95% CI: -15.2, -9.3). These effects were greater in women than in men. The effect of reduced LVEV on mortality (hazard ratio: 1.07; 95% CI: 1.05, 1.09) did not vary by sex. Conclusion In women more than men with chronic obstructive pulmonary disease, a reduction in the estimated left ventricle epicardial volume correlated with a loss of pulmonary venous vasculature, greater pectoralis muscle sarcopenia, and lower all-cause mortality. © RSNA, 2020 Online supplemental material is available for this article.

Generative-based airway and vessel morphology quantification on chest CT images.

Accurately and precisely characterizing the morphology of small pulmonary structures from Computed Tomography (CT) images, such as airways and vessels, is becoming of great importance for diagnosis of pulmonary diseases. The smaller conducting airways are the major site of increased airflow resistance in chronic obstructive pulmonary disease (COPD), while accurately sizing vessels can help identify arterial and venous changes in lung regions that may determine future disorders. However, traditional methods are often limited due to image resolution and artifacts. We propose a Convolutional Neural Regressor (CNR) that provides cross-sectional measurement of airway lumen, airway wall thickness, and vessel radius. CNR is trained with data created by a generative model of synthetic structures which is used in combination with Simulated and Unsupervised Generative Adversarial Network (SimGAN) to create simulated and refined airways and vessels with known ground-truth. For validation, we first use synthetically generated airways and vessels produced by the proposed generative model to compute the relative error and directly evaluate the accuracy of CNR in comparison with traditional methods. Then, in-vivo validation is performed by analyzing the association between the percentage of the predicted forced expiratory volume in one second (FEV1%) and the value of the Pi10 parameter, two well-known measures of lung function and airway disease, for airways. For vessels, we assess the correlation between our estimate of the small-vessel blood volume and the lungs' diffusing capacity for carbon monoxide (DLCO). The results demonstrate that Convolutional Neural Networks (CNNs) provide a promising direction for accurately measuring vessels and airways on chest CT images with physiological correlates.

An open-source framework for pulmonary fissure completeness assessment.

We present an open-source framework for pulmonary fissure completeness assessment. Fissure incompleteness has been shown to associate with emphysema treatment outcomes, motivating the development of tools that facilitate completeness estimation. Generally, the task of fissure completeness assessment requires accurate detection of fissures and definition of the boundary surfaces separating the lung lobes. The framework we describe acknowledges a) the modular nature of fissure detection and lung lobe segmentation (lobe boundary detection), and b) that methods to address these challenges are varied and continually developing. It is designed to be readily deployable on existing lung lobe segmentation and fissure detection data sets. The framework consists of multiple components: a flexible quality control module that enables rapid assessment of lung lobe segmentations, an interactive lobe segmentation tool exposed through 3D Slicer for handling challenging cases, a flexible fissure representation using particles-based sampling that can handle fissure feature-strength or binary fissure detection images, and a module that performs fissure completeness estimation using voxel counting and a novel surface area estimation approach. We demonstrate the usage of the proposed framework by deploying on 100 cases exhibiting various levels of fissure completeness. We compare the two completeness level approaches and also compare to visual reads. The code is available to the community via github as part of the Chest Imaging Platform and a 3D Slicer extension module.