A deep learning-based model to estimate pulmonary function from chest x-rays: multi-institutional model development and validation study in Japan

BACKGROUND

Chest x-ray is a basic, cost-effective, and widely available imaging method that is used for static assessments of organic diseases and anatomical abnormalities, but its ability to estimate dynamic measurements such as pulmonary function is unknown. We aimed to estimate two major pulmonary functions from chest x-rays.

METHODS

In this retrospective model development and validation study, we trained, validated, and externally tested a deep learning-based artificial intelligence (AI) model to estimate forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1) from chest x-rays. We included consecutively collected results of spirometry and any associated chest x-rays that had been obtained between July 1, 2003, and Dec 31, 2021, from five institutions in Japan (labelled institutions A-E). Eligible x-rays had been acquired within 14 days of spirometry and were labelled with the FVC and FEV1. X-rays from three institutions (A-C) were used for training, validation, and internal testing, with the testing dataset being independent of the training and validation datasets, and then x-rays from the two other institutions (D and E) were used for independent external testing. Performance for estimating FVC and FEV1 was evaluated by calculating the Pearson's correlation coefficient (r), intraclass correlation coefficient (ICC), mean square error (MSE), root mean square error (RMSE), and mean absolute error (MAE) compared with the results of spirometry.

FINDINGS

We included 141 734 x-ray and spirometry pairs from 81 902 patients from the five institutions. The training, validation, and internal test datasets included 134 307 x-rays from 75 768 patients (37 718 [50%] female, 38 050 [50%] male; mean age 56 years [SD 18]), and the external test datasets included 2137 x-rays from 1861 patients (742 [40%] female, 1119 [60%] male; mean age 65 years [SD 17]) from institution D and 5290 x-rays from 4273 patients (1972 [46%] female, 2301 [54%] male; mean age 63 years [SD 17]) from institution E. External testing for FVC yielded r values of 0·91 (99% CI 0·90-0·92) for institution D and 0·90 (0·89-0·91) for institution E, ICC of 0·91 (99% CI 0·90-0·92) and 0·89 (0·88-0·90), MSE of 0·17 L2 (99% CI 0·15-0·19) and 0·17 L2 (0·16-0·19), RMSE of 0·41 L (99% CI 0·39-0·43) and 0·41 L (0·39-0·43), and MAE of 0·31 L (99% CI 0·29-0·32) and 0·31 L (0·30-0·32). External testing for FEV1 yielded r values of 0·91 (99% CI 0·90-0·92) for institution D and 0·91 (0·90-0·91) for institution E, ICC of 0·90 (99% CI 0·89-0·91) and 0·90 (0·90-0·91), MSE of 0·13 L2 (99% CI 0·12-0·15) and 0·11 L2 (0·10-0·12), RMSE of 0·37 L (99% CI 0·35-0·38) and 0·33 L (0·32-0·35), and MAE of 0·28 L (99% CI 0·27-0·29) and 0·25 L (0·25-0·26).

INTERPRETATION

This deep learning model allowed estimation of FVC and FEV1 from chest x-rays, showing high agreement with spirometry. The model offers an alternative to spirometry for assessing pulmonary function, which is especially useful for patients who are unable to undergo spirometry, and might enhance the customisation of CT imaging protocols based on insights gained from chest x-rays, improving the diagnosis and management of lung diseases. Future studies should investigate the performance of this AI model in combination with clinical information to enable more appropriate and targeted use.

FUNDING

None.

Spirometry test values can be estimated from a single chest radiograph

Introduction

Physical measurements of expiratory flow volume and speed can be obtained using spirometry. These measurements have been used for the diagnosis and risk assessment of chronic obstructive pulmonary disease and play a crucial role in delivering early care. However, spirometry is not performed frequently in routine clinical practice, thereby hindering the early detection of pulmonary function impairment. Chest radiographs (CXRs), though acquired frequently, are not used to measure pulmonary functional information. This study aimed to evaluate whether spirometry parameters can be estimated accurately from single frontal CXR without image findings using deep learning.

Methods

Forced vital capacity (FVC), forced expiratory volume in 1 s (FEV1), and FEV1/FVC as spirometry measurements as well as the corresponding chest radiographs of 11,837 participants were used in this study. The data were randomly allocated to the training, validation, and evaluation datasets at an 8:1:1 ratio. A deep learning network was pretrained using ImageNet. The input and output information were CXRs and spirometry test values, respectively. The training and evaluation of the deep learning network were performed separately for each parameter. The mean absolute error rate (MAPE) and Pearson's correlation coefficient (r) were used as the evaluation indices.

Results

The MAPEs between the spirometry measurements and AI estimates for FVC, FEV1 and FEV1/FVC were 7.59% (r = 0.910), 9.06% (r = 0.879) and 5.21% (r = 0.522), respectively. A strong positive correlation was observed between the measured and predicted indices of FVC and FEV1. The average accuracy of >90% was obtained in each estimation of spirometry indices. Bland-Altman analysis revealed good agreement between the estimated and measured values for FVC and FEV1.

Discussion

Frontal CXRs contain information related to pulmonary function, and AI estimation performed using frontal CXRs without image findings could accurately estimate spirometry values. The network proposed for estimating pulmonary function in this study could serve as a recommendation for performing spirometry or as an alternative method, suggesting its utility.

CT evaluation of interstitial lung disease related to systemic sclerosis: visual versus automated assessment. A systematic review

AIM

To identify similarities and differences between visual (VA) and automated assessment (AA) of systemic sclerosis-related interstitial lung disease (SSc-ILD) at chest computed tomography (CT) in terms of clinical applicability.

MATERIALS AND METHODS

Medline, Embase, and Web of Science were searched to identify all studies investigating VA and AA for SSc-ILD assessment, from inception to 31 July 2022. Exclusion criteria were manuscripts not in English, absence of full-text, reviews, diseases other than ILD in SSc, CT not analysed with both VA and AA, VA and AA not adopted for the same purpose or not compared, overlap syndromes, SSc-ILD data not extractable, and studies with <10 patients.

RESULTS

Ten full-text studies (804 patients) were included. The most adopted VAs were the Warrick or Goh score (four studies each), while densitometry (eight studies) or lung texture analysis (LTA, two studies) were utilised as AAs. The main field of investigation was the correlation with baseline pulmonary function tests (PFT, six studies). Warrick VA showed lower correlations compared to densitometry, while Goh VA demonstrated more heterogeneous results. Compared to LTA, Goh VA obtained lower correlations with lung volumes but similar or stronger coefficients with alveolar diffusibility.

CONCLUSIONS

VA and AA may show heterogeneous results comparing their correlations with PFT, probably depending on the specific analysis adopted for each method. More data are needed on VA versus LTA. Comparisons between VA and AA regarding correlation with PFT follow-up and as prognostic elements, or for disease monitoring, are lacking. AAs in progressive fibrosis diagnosis remain to be tested.

Advanced and traditional chest MRI sequence for the clinical assessment of systemic sclerosis related interstitial lung disease, compared to CT: disease extent analysis and correlations with pulmonary function tests

BACKGROUND

MRI is a radiation-free emerging alternative to CT in systemic sclerosis related interstitial lung disease (SSc-ILD) assessment. We aimed to compare a T2 radial TSE and a PD UTE MRI sequence with CT in SSc-ILD extent evaluation and correlations with pulmonary function tests (PFT).

MATERIAL AND METHODS

29 SSc-ILD patients underwent CT, MRI and PFT. ILD extent was visually assessed. Lin's concordance correlation coefficients (CCC) and Kruskal Wallis test (p-value < 0.05) were computed for inter-method comparison. Patients were divided in limited and extended disease, defining extended ILD with two methods: (A) ILD>30% or 10%20% or 20% with FVC%<70%. MRI Sensitivity, Specificity, Positive Predictive Value (PPV), Negative Predictive Value (NPV) and Accuracy were assessed. Pearson correlation coefficients r (p-value<0.025) were computed between ILD extents and PFT (FVC% and DLCO%).

RESULTS

Median ILD extents were 11%, 11%, 10% on CT, radial TSE and UTE, respectively. CCC between CT and MRI was 0.95 for both sequences (Kruskal-Wallis p-value=0.64). Sensitivity, Specificity, PPV, NPV and Accuracy in identifying extended disease were: (A) 87.5 %, 100 %, 100 %, 95.5 and 96.6 % with radial TSE and 87.5 %, 95.2 %, 87.5 %, 95.2 and 93.1 % with UTE; (B) 86.7 %, 86.4 %, 66.7 %, 95.0 % and 86.2 % for both sequences. Pearson r of CT, radial TSE and UTE ILD extents with FVC were -0.66, -0.60 and -0.68 with FVC, -0.59, -0.56 and -0.57 with DLCO, respectively (p<0.002).

CONCLUSIONS

MRI sequences may have similar accuracy to CT to determine SSc-ILD extent and severity, with analogous correlations with PFT.

Common and Uncommon CT Findings in CVID-Related GL-ILD: Correlations with Clinical Parameters, Therapeutic Decisions and Potential Implications in the Differential Diagnosis

PURPOSE

To investigate computed tomography (CT) findings of Granulomatous Lymphocytic Interstitial Lung Disease (GL-ILD) in Common Variable Immunodeficiency (CVID), also in comparison with non-GL-ILD abnormalities, correlating GL-ILD features with functional/immunological parameters and looking for GL-ILD therapy predictive elements.

METHODS

CT features of 38 GL-ILD and 38 matched non-GL-ILD subjects were retrospectively described. Correlations of GL-ILD features with functional/immunological features were assessed. A logistic regression was performed to find a predictive model of GL-ILD therapeutic decisions.

RESULTS

Most common GL-ILD CT findings were bronchiectasis, non-perilymphatic nodules, consolidations, Ground Glass Opacities (GGO), bands and enlarged lymphnodes. GL-ILD was usually predominant in lower fields. Multiple small nodules (≤10 mm), consolidations, reticulations and fibrotic ILD are more indicative of GL-ILD. Bronchiectasis, GGO, Reticulations and fibrotic ILD correlated with decreased lung performance. Bronchiectasis, GGO and fibrotic ILD were associated with low IgA levels, whereas high CD4+ T cells percentage was related to GGO. Twenty out of 38 patients underwent GL-ILD therapy. A model combining Marginal Zone (MZ) B cells percentage, IgA levels, lower field consolidations and lymphnodes enlargement showed a good discriminatory capacity with regards to GL-ILD treatment.

CONCLUSIONS

GL-ILD is a lower field predominant disease, commonly characterized by bronchiectasis, non-perilymphatic small nodules, consolidations, GGO and bands. Multiple small nodules, consolidations, reticulations and fibrotic ILD may suggest the presence of GL-ILD in CVID. MZ B cells percentage, IgA levels at diagnosis, lower field consolidations and mediastinal lymphnodes enlargement may predict the need of a specific GL-ILD therapy.

Correlation of spirometry indices to chest radiology in the diagnosis of chronic airway disease among regional and rural Indigenous Australians

BACKGROUND

The majority of Indigenous Australians reside in non-urban locations, with reduced access to chest radiology such as computed tomography (CT). Spirometry and chest X-ray (CXR) may be used in the absence of CT; however, the correlation of spirometry indices to CT-defined chronic airway diseases (i.e. chronic obstructive pulmonary disease (COPD) and bronchiectasis) compared with CXR among Indigenous people is sparsely reported.

AIM

To evaluate spirometry indices against CXR and CT findings among adult Indigenous Australians.

METHODS

Indigenous patients who had undergone a spirometry test between 2012 and 2020 and had a CXR or chest CT scan assessed for the presence (+ )/absence (- ) of airway diseases were included in this study.

RESULTS

Of 643 patients (57% female, 31% remote/very remote), 364 (57%) had CT and CXR available. Patients who were 'CT- and CXR- ' for airway diseases (48%) recorded a mean FVC, FEV1 and FEV1 /FVC of 61%, 59% and 0.76 compared to 57%, 49% and 0.66 in the 'CT+ and CXR- ' group and 53%, 39% and 0.58 in the 'CT+ and CXR+ ' group. CXR showed sensitivity (44%) and specificity (88%), while spirometry showed 62% and 77% compared to CT. Spirometry demonstrated predominately restrictive impairment among 'CT- and CXR- ' and mixed/obstructive impairment among 'CT+ and CXR- ' and 'CT+ and CXR+ ' groups.

CONCLUSION

Indigenous Australians tend to demonstrate restrictive impairment in the absence of radiological evidence of airway disease. However, in the presence of airway disease, combinations of mixed and obstructive impairments were common. Obstructive impairment shows greater sensitivity for identifying COPD than that shown by CXR; however, CXR shows greater specificity. Hence, spirometry in conjunction with chest radiology should be utilised to aid in the assessment of airway diseases in this population.

Association between pulmonary ventilatory function and mild cognitive impairment: A population-based study in rural China

Background

Mild cognitive impairment (MCI), a reversible intermediate state, plays an important role in the development and prevention of dementia. The relationship between pulmonary function and MCI risk has not yet been well-elucidated.

Methods

We included 2,947 rural Chinese residents aged ≥35 years who were free from a history of stroke, dementia, or other brain diseases and measured pulmonary ventilatory function using calibrated spirometry according to the recommended method. MCI was assessed with the Montreal Cognitive Assessment-Basic for Chinese scale. Logistic regression models and restricted cubic splines with covariate adjustment were performed to explore the association between pulmonary function and MCI risk.

Results

The prevalence of MCI increased with decreasing pulmonary function, from the lowest quartile to the highest quartile of pulmonary function: 63.9, 50.5, 43.8, and 43.6%, respectively. After adjustment for confounding factors, participants in the first quartile had a significantly increased risk of MCI (ORs, 1.691, 95% CI, 1.267-2.258), with the highest quartile as the reference. In the subgroup analysis, a significant association of pulmonary function and MCI was found in females and those with low physical activity. Meanwhile, we observed an L-shaped relationship between pulmonary function and MCI (P _non-linear = 0.032).

Conclusions

Poor pulmonary function was associated with an increased risk of MCI among rural Chinese adults, and presented a non-linear relationship. These findings remind us of the need for early cognitive assessment in local populations with lower pulmonary function.

Röntgenbefunde bei diffusen parenchymatösen Lungenerkrankungen

Klinisches Problem

Empfehlungen für die Praxis

Assessment of Multi-Layer Perceptron Neural Network for Pulmonary Function Test’s Diagnosis Using ATS and ERS Respiratory Standard Parameters

The aim of the research work is to investigate the operability of the entire 23 pulmonary function parameters, which are stipulated by the American Thoracic Society (ATS) and the European Respiratory Society (ERS), to design a medical decision support system capable of classifying the pulmonary function tests into normal, obstructive, restrictive, or mixed cases. The 23 respiratory parameters specified by the ATS and the ERS guidelines, obtained from the Pulmonary Function Test (PFT) device, were employed as input features to a Multi-Layer Perceptron (MLP) neural network. Thirteen possible MLP Back Propagation (BP) algorithms were assessed. Three different categories of respiratory diseases were evaluated, namely obstructive, restrictive, and mixed conditions. The framework was applied on 201 PFT examinations: 103 normal and 98 abnormal cases. The PFT decision support system’s outcomes were compared with both the clinical truth (physician decision) and the PFT built-in diagnostic software. It yielded 92–99% and 87–92% accuracies on the training and the test sets, respectively. An 88–94% area under the receiver operating characteristic curve (ROC) was recorded on the test set. The system exceeded the performance of the PFT machine by 9%. All 23 ATS\ERS standard PFT parameters can be used as inputs to design a PFT decision support system, yielding a favorable performance compared with the literature and the PFT machine’s diagnosis program.

Atypical Causes of Dyspnea: A Review of Neuromuscular and Chest Wall Disorders that Compromise Ventilation

Dyspnea is a common presenting symptom among patients with cardiopulmonary diseases. However, several neuromuscular and chest wall conditions are often overlooked and under-recognized causes of dyspnea. These disorders frequently adversely affect the structure and function of the ventilatory pump (diaphragm, accessory muscles of ventilation) and can precipitate respiratory failure despite normal lung parenchyma. Weakened musculature impairs clearance of airway secretions leading to aspiration and pneumonia, further compromising respiratory function. Radiologists should be aware of the pathophysiology and imaging manifestations of these conditions and might suggest them to be causes of dyspnea which otherwise may not have been considered by referring clinicians.

Acute appendicitis following the COVID-19 vaccine

We report the case of a previously healthy 69-year-old female who developed appendicitis after receiving the third dose of the Pfizer-BioNTech Coronavirus Disease 2019 (COVID-19) vaccine; no other triggers were identified. We speculate that an association exists which may be mediated by colonic lymphoid hyperplasia, a condition that might be indicative of an enhanced immunological mucosal response to antigenic stimulation. As widespread vaccination coverage continues, it is crucial to monitor and accurately report the adverse reactions that may otherwise remain unidentified in vaccination trials. Therefore, we suggest that adults experiencing spontaneous, severe abdominal pain following COVID-19 vaccination may benefit from seeking emergent medical care. Likewise, providers should have a low threshold to consider and evaluate patients for appendicitis. If a true causal link is identified, the risk must also be deliberated in context with the millions of patients who have been safely vaccinated and the known morbidity and mortality from COVID-19 infection.

Pulmonary Barotrauma in a BUD/S Candidate Following Shallow Dives Using the MK 25 Rebreather

Pulmonary barotrauma of ascent is a well-recognized risk of compressed air diving in the civilian and military diving communities. Chest imaging is a beneficial adjunct to clinical evaluation in screening select individuals for fitness to dive, evaluating dive-related injuries, and safely returning individuals to diving duty. We present a case of a 26-year-old male U.S. Navy Ensign and Basic Underwater Demolition/SEAL (BUD/S) candidate who experienced pulmonary barotrauma following two shallow dives to a maximum depth of 18 feet of seawater using the MK-25 100% oxygen rebreather. A chest radiograph showed a left upper lobe peripheral wedge-shaped opacity abutting the pleural surface. A subsequent computerized tomography (CT) scan of the chest showed multifocal areas of peripheral pulmonary hemorrhage associated with small pneumatoceles. Two months after the diving injury, chest CT showed resolution of the pulmonary hemorrhage and pneumatoceles. Diving-related pulmonary barotrauma occurs most often secondary to breath-holding on ascent by inexperienced divers and is one of the most common diving injuries seen in BUD/S candidates. The risk of pulmonary barotrauma may be decreased through adequate training and thorough medical screening to include assessing for symptoms of infection before every dive. In cases of acute pulmonary barotrauma, chest radiographs may be used to screen for thoracic injury. Chest CT with inspiratory and expiratory sequences should be used to screen dive candidates on a case-by-case basis and to evaluate lung injury and predisposing pulmonary conditions following pulmonary barotrauma.

[Chest radiography findings in diffuse parenchymal lung diseases]

CLINICAL ISSUE

Diffuse parenchymal lung diseases include a heterogeneous group of diseases of the lung parenchyma, the alveolar spaces, the vessels and the airways, which can be triggered by various pathomechanisms, such as inflammation and fibrotic changes. Since the therapeutic approaches and prognoses differ significantly between the diseases, the correct diagnosis is of fundamental importance. In routine clinical practice, next to the patients' history, the clinical presentation, the laboratory findings and the bronchoscopy, imaging plays a central role in establishing a diagnosis.

PRACTICAL RECOMMENDATIONS

The diagnosis of diffuse parenchymal lung diseases is an enormous challenge for clinicians, radiologists as well as pathologists and should therefore preferably be carried out in a multidisciplinary setting. Since patients often present with unspecific, respiratory symptoms, chest radiographs are the first imaging method used. Many patterns of diffuse parenchymal lung diseases (e.g., ground-glass opacities and consolidations), their distribution (e.g., cranial-caudal) and the presence of additional findings (e.g., mediastinal lymphadenopathy) are often already detectable on chest X‑rays. However, the imaging reference standard and thus, an integral part of the assessment of diffuse parenchymal lung disease, is the chest HR-CT. In some cases, the pattern of the HR-CT is pathognomonic, in others it is unspecific for a disease, so that further diagnostic steps are necessary.

Instructional Training Compared with Self-Study for Pulmonary Function Test Interpretation

Background

Pulmonary diseases have considerable prognostic relevance for all-cause mortality. Most patients with lung diseases such as chronic obstructive pulmonary disease are treated by general practitioners. Understanding the clinical consequences such as pulmonary hyperinflation or reduced diffusion capacity is important for the management and prognosis of patients with chronic respiratory disorders. Therefore, the interpretation of pulmonary function testing (PFT) results needs to see more emphasis in the medical education curriculum.

Objective

To develop PFT training for final-year medical students and to compare the efficacy of instructional training to self-reliant textbook study.

Methods

A two-armed randomized control trial compares learning outcomes in PFT interpretation. A total of 25 final-year medical students were selected at random into the 1) instructional training group or 2) self-reliant textbook study group on PFT interpretation. The learning time for both groups was 2 hours. The duration of the written pre- and post-training examinations was 60 minutes each. Both exams had a knowledge section (30 questions, maximum 120 points) and a skills section (11 case studies, maximum 75 points).

Results

The instructional training group acquired significantly more knowledge and, in particular, higher skill levels when compared with the self-reliant reading group. In the reading group, knowledge scores increased from 48 to 60% (12%) and skills scores increased from 14 to 22% (8%), whereas in the instructional group, knowledge increased from 47 to 71% (24%) and skills from 18 to 58% (40%). A multivariate analysis (Pillai’s Trace: 0.633; P < 0.001) as well as follow-up univariate analyses reveal that these differences are statistically significant (knowledge: F = 8.811, df = 1, P = 0.007; skills F = 33.965, df = 1, P < 0.001). Interestingly, there was no significant group effect in the pure knowledge gain about respiratory disorders per se.

Conclusion

The self-reliant study group was less able to translate their newly acquired knowledge into interpretation of comprehensive PFT reports. A mandatory 2-hour instructional training greatly enhances the students’ knowledge and skills about PFT interpretation. Obligatory PFT instructional training should therefore be included in the students’ curriculum.

Pulmonary function testing for the primary care nurse practitioner

ABSTRACT

Knowledge of which pulmonary function tests are commonly performed in primary care and interpretation of their results is integral for the diagnosis, care, and management of those with pulmonary symptoms. This article provides an overview of the most common pulmonary function tests and interpretation of their results.

Imaging Dynamic Expiration: Feasibility of MRI Spirometry Using Hyperpolarized Xenon Gas

Purpose

To examine the feasibility of imaging-based spirometry using high-temporal-resolution projection MRI and hyperpolarized xenon 129 (¹²⁹Xe) gas.

Materials and Methods

In this prospective exploratory study, five healthy participants (age range, 25-45 years; three men) underwent an MRI spirometry technique using inhaled hyperpolarized ¹²⁹Xe and rapid two-dimensional projection MRI. Participants inhaled ¹²⁹Xe, then performed a forced expiratory maneuver while in an MR imager. Images of the lungs during expiration were captured in time intervals as short as 250 msec. Volume-corrected images of the lungs at expiration commencement (0 second), 1 second after expiration, and 6 seconds after expiration were extracted to generate forced expiratory volume in 1 second (FEV₁), forced vital capacity (FVC), and FEV₁/FVC ratio pulmonary maps. For comparison, participants performed conventional spirometry in the sitting position using room air, in the supine position using room air, and in the supine position using a room air and ¹²⁹Xe mixture. Paired t tests with Bonferroni corrections for multiple comparisons were used for statistical analyses.

Results

The mean MRI-derived FEV₁/FVC value was lower in comparison with conventional spirometry (0.52 ± 0.03 vs 0.70 ± 0.05, P < .01), which may reflect selective ¹²⁹Xe retention. A secondary finding of this study was that 1 L of inhaled ¹²⁹Xe negatively impacted pulmonary function as measured by conventional spirometry (in supine position), which reduced measured FEV₁ (2.70 ± 0.90 vs 3.04 ± 0.85, P < .01) and FEV₁/FVC (0.70 ± 0.05 vs 0.79 ± 0.04, P < .01).

Conclusion

A forced expiratory maneuver was successfully imaged with hyperpolarized ¹²⁹Xe and high-temporal-resolution MRI. Derivation of regional lung spirometric maps was feasible.Keywords: MR-Imaging, MR-Dynamic Contrast Enhanced, MR-Functional Imaging, Pulmonary, Thorax, Diaphragm, Lung, Pleura, Physics Supplemental material is available for this article. © RSNA, 2021.

Association of short-term fine particulate matter exposure with pulmonary function in populations at intermediate to high-risk of cardiovascular disease: A panel study in three Chinese cities

BACKGROUND

Decline in pulmonary function contributes to increasing cardiovascular disease (CVD) risk. Although adverse effects of short-term exposure to fine particulate matter (PM_2.5) on pulmonary function have been recognized in healthy people or patients with respiratory disease, these results were not well illustrated among people with elevated CVD risk.

MATERIALS AND METHODS

A panel study was conducted in three Chinese cities with three repeated visits among populations at intermediate to high-risk of CVD, defined as treated hypertension patients or those with blood pressure ≥ 130/80 mmHg, who met any of the three conditions including abdominal obesity, dyslipidemia, and diabetes mellitus. Individualized PM_2.5 exposure and pulmonary function were measured during each seasonal visit. Linear mixed-effect models were applied to analyze the associations of PM_2.5 concentrations with pulmonary function indicators, including forced expiratory volume in 1 s (FEV₁), FEV₁/forced vital capacity (FVC), maximal mid-expiratory flow (MMF), and peak expiratory flow (PEF).

RESULTS

Short-term PM_2.5 exposure was significantly associated with decreased pulmonary function and an increment of 10 μg/m³ in PM_2.5 concentrations during lag 12-24 hour was associated with declines of 41.7 ml/s (95% confidence interval [CI]: 7.7-75.7), 0.35% (95% CI: 0.01, 0.69), and 20.9 ml/s (95% CI: 0.5-41.3) for PEF, FEV₁/FVC, and MMF, respectively. Results from stratified and sensitivity analyses were generally similar with the overall findings, while the adverse effects of PM_2.5 on pulmonary functions were more pronounced in those who were physically inactive.

CONCLUSIONS

This study first identified short-term exposure to PM_2.5 was associated with impaired pulmonary function and physical activity might attenuate the adverse effects of PM_2.5 among populations at intermediate to high-risk of CVD. These findings provide new robust evidence on health effects of air pollution and call for effective prevention measures among people at CVD risk.

Diagnostic Classification of Interstitial Lung Disease in Clinical Practice

Interstitial lung diseases (ILDs) are challenging to diagnose, requiring integration of multiple complex features that are often difficult to interpret. This article reviews a pragmatic approach to ILD diagnosis and classification, focusing on diagnostic tools and strategies that are used to separate different subtypes and identify the most appropriate management. We discuss the evolution of ILD classification and the contemporary approach that integrates routinely used diagnostic tools in a multidisciplinary discussion. We highlight the increasing importance of taking a multipronged approach to ILD classification that reflects the recent emphasis on disease behavior while also considering etiopathogenesis and morphologic features.

Persistent Dyspnea in a 74-Year-Old Man With Normal Spirometry and Lung Volumes

CASE PRESENTATION

A 74-year-old man was referred to a pulmonologist for evaluation of a 1-year history of nonproductive cough and progressive exertional dyspnea. He was initially evaluated by his primary care physician, where he had spirometry that was negative for any obstructive or restrictive lung disease. An echocardiogram showed a normal left ventricular ejection fraction, with no wall motion abnormality or valvular heart disease. He had an outpatient chest radiograph performed (Fig 1), and he was subsequently treated empirically for a COPD exacerbation with 5 days of oral prednisone and azithromycin. He was eventually referred to a pulmonologist because of a lack of clinical improvement. On seeing his pulmonary physician, he described the same exertional dyspnea and a nonproductive cough. A review of systems was negative for fever, chills, wheezing, angina, arthralgia, myalgia, rash, or leg swelling. He denied any medical illness and was not taking any medications. He was currently retired and had worked as a cashier his entire adult life. He had no occupational exposure to asbestos, coal dust, beryllium, silica dust, or dust from hard metal objects, such as cobalt. However, he had smoked approximately 1 to 2 packs of cigarettes per day and had done so for the past 50 years. His vital signs were unremarkable, aside from an oxygen saturation of 94% on room air. His physical examination revealed bibasilar "velcro-like" inspiratory crackles on lung examination. There was no digital clubbing, nor was there peripheral edema in his lower extremities. He had no muscle tenderness and demonstrated normal muscle strength against resistance.

Prediction of Obstructive Lung Disease from Chest Radiographs via Deep Learning Trained on Pulmonary Function Data

Background

Chronic obstructive pulmonary disease (COPD), the third leading cause of death worldwide, is often underdiagnosed.

Purpose

To develop machine learning methods to predict COPD using chest radiographs and a convolutional neural network (CNN) trained with near-concurrent pulmonary function test (PFT) data. Comparison is made to natural language processing (NLP) of the associated radiologist text reports.

Materials and Methods

This IRB-approved single-institution retrospective study uses 6749 two-view chest radiograph exams (2012–2017, 4436 unique subjects, 54% female, 46% male), same-day associated radiologist text reports, and PFT exams acquired within 180 days. The Image Model (Resnet18 pre-trained with ImageNet CNN) is trained using frontal and lateral radiographs and PFTs with 10% of the subjects for validation and 19% for testing. The NLP Model is trained using radiologist text reports and PFTs. The primary metric of model comparison is the area under the receiver operating characteristic curve (AUC).

Results

The Image Model achieves an AUC of 0.814 for prediction of obstructive lung disease (FEV1/FVC <0.7) from chest radiographs and performs better than the NLP Model (AUC 0.704, p<0.001) from radiologist text reports where FEV1 = forced expiratory volume in 1 second and FVC = forced vital capacity. The Image Model performs better for prediction of severe or very severe COPD (FEV1 <0.5) with an AUC of 0.837 versus the NLP model AUC of 0.770 (p<0.001).

Conclusion

A CNN Image Model trained on physiologic lung function data (PFTs) can be applied to chest radiographs for quantitative prediction of obstructive lung disease with good accuracy.

Multi-scale models of lung fibrosis

The architectural complexity of the lung is crucial to its ability to function as an organ of gas exchange; the branching tree structure of the airways transforms the tracheal cross-section of only a few square centimeters to a blood-gas barrier with a surface area of tens of square meters and a thickness on the order of a micron or less. Connective tissue comprised largely of collagen and elastic fibers provides structural integrity for this intricate and delicate system. Homeostatic maintenance of this connective tissue, via a balance between catabolic and anabolic enzyme-driven processes, is crucial to life. Accordingly, when homeostasis is disrupted by the excessive production of connective tissue, lung function deteriorates rapidly with grave consequences leading to chronic lung conditions such as pulmonary fibrosis. Understanding how pulmonary fibrosis develops and alters the link between lung structure and function is crucial for diagnosis, prognosis, and therapy. Further information gained could help elaborate how the healing process breaks down leading to chronic disease. Our understanding of fibrotic disease is greatly aided by the intersection of wet lab studies and mathematical and computational modeling. In the present review we will discuss how multi-scale modeling has facilitated our understanding of pulmonary fibrotic disease as well as identified opportunities that remain open and have produced techniques that can be incorporated into this field by borrowing approaches from multi-scale models of fibrosis beyond the lung.

Quantitative CT analysis for bronchiolitis obliterans in perinatally HIV-infected adolescents-comparison with controls and lung function data

OBJECTIVE

To compare quantitative chest CT parameters in perinatally HIV-infected adolescents with and without bronchiolitis obliterans compared with HIV-uninfected controls and their association with lung function measurements.

MATERIALS AND METHODS

Seventy-eight (41 girls) HIV-infected adolescents with a mean age of 13.8 ± 1.65 years and abnormal pulmonary function tests in the prospective Cape Town Adolescent Antiretroviral Cohort underwent contrast-enhanced chest CT on inspiration and expiration. Sixteen age-, sex-, and height-matched non-infected controls were identified retrospectively. Fifty-one HIV-infected adolescents (28 girls) displayed mosaic attenuation on expiration suggesting bronchiolitis obliterans. Pulmonary function tests were collected. The following parameters were obtained: low- and high-attenuation areas, mean lung density, kurtosis, skewness, ventilation heterogeneity, lung mass, and volume.

RESULTS

HIV-infected adolescents showed a significantly higher mean lung density, ventilation heterogeneity, mass, and high- and low-attenuation areas compared with non-infected individuals. Kurtosis and skewness were significantly lower as well. HIV-infected adolescents with bronchiolitis obliterans had a significantly lower kurtosis and skewness compared with those without bronchiolitis obliterans. Lung mass and volume showed the strongest correlations with forced expiratory volume in 1 s (FEV₁), forced vital capacity (FVC), and alveolar volume. Low-attenuation areas below - 950 HU and ventilation heterogeneity showed the strongest correlation with FEV₁/FVC (range, - 0.51 to - 0.34) and forced expiratory flow between 25 and 75% of FVC (range, - 0.50 to - 0.35).

CONCLUSION

Quantitative chest CT on inspiration is a feasible technique to differentiate perinatally HIV-infected adolescents with and without bronchiolitis obliterans. Quantitative CT parameters correlate with spirometric measurements of small-airway disease.

KEY POINTS

• Perinatally HIV-infected adolescents showed a more heterogeneous attenuation of the lung parenchyma with a higher percentage of low- and high-attenuation areas compared with non-infected patients. • Kurtosis and skewness are able to differentiate between HIV-infected adolescents with and without bronchiolitis obliterans using an inspiratory chest CT. • Quantitative CT parameters of the chest correlate significantly with pulmonary function test. Low-attenuation areas and ventilation heterogeneity are particularly associated with spirometric parameters related to airway obstruction.

Association of rheumatoid arthritis-related autoantibodies with pulmonary function test abnormalities in a rheumatoid arthritis registry

INTRODUCTION

We investigated whether rheumatoid arthritis (RA)-related autoantibodies were associated with abnormalities on pulmonary function tests (PFTs).

METHODS

We studied RA serostatus and PFT abnormalities within a RA registry. RA serostatus was assessed by research assays for cyclic citrullinated peptide (CCP) and rheumatoid factor (RF). Outcomes were abnormalities on clinically indicated PFTs, including restriction, obstruction, and diffusion abnormality. Logistic regression was used to obtain ORs and 95% CIs for the PFT abnormalities by RA serologic phenotypes independent of lifestyle and RA characteristics.

RESULTS

Among 1272 analyzed subjects, mean age was 56.3 years (SD 14.1), 82.2% were female, and 69.5% were seropositive. There were 100 subjects with abnormal PFTs. Compared with seronegativity, seropositivity was associated with increased odds of any PFT abnormality (multivariable OR 2.29, 95% CI 1.30-4.03). When analyzing type of PFT abnormality, seropositivity was also associated with restriction, obstruction, and diffusion abnormalities; multivariable ORs were 2.48 (95% CI 1.26-4.87), 3.12 (95% CI 1.28-7.61), and 2.30 (95% CI 1.09-4.83), respectively. When analyzing by CCP and RF status, the associations were stronger for RF+ than for CCP+ (any PFT abnormality OR 1.99, 95% CI 1.21-3.27 for RF+ vs. RF-; OR 1.67, 95% CI 1.03-2.69 for CCP+ vs. CCP-) with a dose effect of higher RF titer increasing odds for each PFT abnormality (p for trend < 0.05).

CONCLUSIONS

Seropositive RA patients had two-fold increased risk for abnormalities on PFTs performed for clinical indications compared with seronegative RA. Patients with seropositive RA, particularly those with high-titer RF positivity, may be more likely to have obstructive and restrictive abnormalities, independent of smoking.Key points• Due to the known excess pulmonary morbidity/mortality in RA, we studied the relationship of rheumatoid arthritis (RA)-related autoantibodies with pulmonary function test (PFT) abnormalities using a large RA registry.• We evaluated whether presence and levels of cyclic citrullinated peptide (CCP) and rheumatoid factor (RF) were associated with restriction, obstruction, and diffusion abnormalities on PFTs among 1272 subjects with RA.• Seropositivity was associated with two-fold increased risk for any PFT abnormality, independent of confounders including smoking. Higher titers of RF conferred greatest risk for all PFT outcomes: obstruction, restriction, and diffusion abnormality.• These results provide evidence that patients with RA should be closely monitored for pulmonary involvement, particularly those with high-titer RF seropositivity.

Pulmonary quantitative CT imaging in focal and diffuse disease: current research and clinical applications

The frenetic development of imaging technology-both hardware and software-provides exceptional potential for investigation of the lung. In the last two decades, CT was exploited for detailed characterization of pulmonary structures and description of respiratory disease. The introduction of volumetric acquisition allowed increasingly sophisticated analysis of CT data by means of computerized algorithm, namely quantitative CT (QCT). Hundreds of thousands of CTs have been analysed for characterization of focal and diffuse disease of the lung. Several QCT metrics were developed and tested against clinical, functional and prognostic descriptors. Computer-aided detection of nodules, textural analysis of focal lesions, densitometric analysis and airway segmentation in obstructive pulmonary disease and textural analysis in interstitial lung disease are the major chapters of this discipline. The validation of QCT metrics for specific clinical and investigational needs prompted the translation of such metrics from research field to patient care. The present review summarizes the state of the art of QCT in both focal and diffuse lung disease, including a dedicated discussion about application of QCT metrics as parameters for clinical care and outcomes in clinical trials.