What are the long-term lung problems after covid-19

How does COVID-19 affect the overall respiratory system: short and long term? 

COVID-19 can affect the respiratory system in a variety of ways and across a spectrum of levels of disease severity, depending on a person’s immune system, age and comorbidities. Symptoms can range from mild, such as cough, shortness of breath and fevers, to critical disease, including respiratory failure, shock and multi-organ system failure.

It is particularly important that patients who have underlying lung disease can certainly have worsening of those conditions with contraction or exposure to COVID-19. With this, COVID-19 can cause overall worsening of these conditions, such as asthma, chronic obstructive pulmonary disease (COPD), interstitial lung disease, etc.

For those people who are diagnosed with COVID-19 and then recover, what are the short-term effects of COVID-19 on the lungs?

According to the World Health Organization, recovery time appears to be around two weeks for mild infection and three to six weeks for severe disease. However, this is variable and depends on a patient’s pre-existing comorbidities in addition to illness severity.

Several surveys conducted in the U.S. and Italy are showing that only 39% of those who had been hospitalized reported a return to baseline health by 14-21 days after diagnosis.

Similarly, in a study of 143 patients hospitalized for COVID-19, only 13% were symptom-free after a mean of 60 days following disease onset.

The most common symptoms were dyspnea (43%), fatigue (53%), joint pain and chest pain.

However, there have been reports of persistent severe illness with weeks of fevers and pneumonia persisting in immunosuppressed patients.

With milder infection, patients can still have prolonged symptoms. A recent survey showed that only 65% reported a return to baseline health by 14-21 days after diagnosis. Those who did return to baseline health did so a median of seven days after the diagnosis. Symptoms that can persist include cough (43%), fatigue (35%) and rarely fevers and chills in those with prior mild infection.

What are the physiological changes in lung structure and function that causes serious complications? What causes these changes specifically?

A major issue with COVID-19 is with gas exchange in the alveolus. Usually, there is a very tight connection between the alveolar epithelium (type-1 cells) and the capillary. COVID-19 infects AT2 cells, kills them and floods the alveolus. In addition, there is evidence for microthrombosis, which may block the vascular side.

Clinically, this may appear as several conditions: severe bronchopneumonia, acute respiratory distress syndrome (ARDS) or sepsis.

Pneumonia is inflammation and fluid in the lungs, making it difficult to breathe. Patients can experience shortness of breath, fevers and cough, which can be productive. More severe inflammation can lead to ARDS, which can require significant treatment including the use of oxygen therapies, including mechanical ventilation or even extracorporeal membrane oxygenation (ECMO), which is a lung bypass machine that oxygenates the blood. If a patient develops this severe of a syndrome, this can lead to longer-lasting effects on the lungs, such as fibrosis (scarring of the lung).

Sepsis is a syndrome of abnormal inflammation that usually results from infection. It can lead to multiple organs not working in a coordinated fashion. This syndrome can require support for failing organs, and thereafter, have a lasting impact on their long-term functionality. 

See also the article by Cho and Villacreses et al in this issue.

Dr Elicker is a clinical professor in the Department of Radiology and Biomedical Imaging at the University of California, San Francisco (UCSF). He did a radiology residency at Yale and thoracic imaging fellowship at UCSF. His clinical and research interests are in the areas of diffuse lung disease and lung cancer.

The COVID-19 pandemic has been ongoing for 2 years. Over this period, Radiology and other peer-reviewed journals have distributed information regarding the nature of the pandemic with unprecedented speed. Based on the extensively documented clinical and imaging manifestations of acute COVID-19 infection, expert thoracic imagers have developed imaging categories that classify patterns according to the likelihood that they represent COVID-19 infection (1).

Acute COVID-19 has a somewhat unique appearance among viral infections on CT scans. It manifests as ground-glass opacity and/or consolidation, often with a strong peripheral distribution. Also, there are CT findings suggesting that organizing pneumonia (OP) is a common pattern of injury. OP is associated with a wide variety of different infections, although it appears particularly common with COVID-19 (2). However, the long-term pulmonary manifestations of COVID-19 pneumonia (part of so-called “long COVID”) remain lacking in the literature.

It is important to understand our current knowledge of viral infections and their typical manifestations within the lungs. The long-term sequelae of viral pneumonia, in general, vary depending upon two factors: (a) direct injury caused by the viral organisms and (b) the host’s immune reaction to those organisms. These result in a variety of different patterns of injury, each of which is associated with specific permanent long-term sequelae. The histologic manifestations of acute pulmonary viral infections can be divided broadly into two primary patterns: bronchiolitis and inflammation adjacent to airways, and diffuse alveolar damage (DAD). On images, bronchiolitis and airway inflammation manifest as bronchial wall thickening, centrilobular nodules, and tree-in-bud opacities, whereas DAD manifests as bilateral ground-glass opacity and/or consolidation.

The long-term effects of these two patterns are also characteristic. Inflammation within and around the airways may induce concentric fibrosis around the bronchioles, resulting in airway narrowing or obliteration. This is termed constrictive (or obliterative) bronchiolitis, the development of which may result in persistent dyspnea after resolution of the acute infection, with an associated obstructive defect on pulmonary function tests. Typical CT findings of constrictive bronchiolitis include mosaic attenuation and air trapping, sometimes associated with bronchiectasis. The long-term manifestations of DAD, on the other hand, are quite different. Histologically, fibrosis develops 1–2 weeks after the development of acute symptoms. On images, this is associated with the development of reticulation and traction bronchiectasis. Over time, usually months, the fibrosis may improve; however, residual fibrosis is common (3) and often located in the anterior subpleural lung, which may be associated with restrictive physiology on pulmonary function testing.

OP is particularly common with COVID-19 and its clinical and imaging features have been studied (4), mainly in the setting of cryptogenic (idiopathic) disease. OP is usually a highly steroid-responsive disease with opacities that quickly improve or resolve with treatment, although residual fibrosis may occur. This residual fibrosis often has a pattern that resembles nonspecific interstitial pneumonia with basilar predominant reticulation, traction bronchiectasis, and subpleural sparing (5). It is also important to note that OP and DAD may coexist, with overlapping imaging findings.

Understanding the different patterns of injury associated with viral infections and their long-term sequelae is important for putting the long-term effects of COVID-19 infection in context. Han et al (6) were among the first to describe the persistent CT findings of COVID-19 6 months after the onset of acute symptoms. In their study, more than one-third of patients showed evidence of fibrotic changes.

In this issue of Radiology, Cho and colleagues (7) address these long-term pulmonary manifestations in a prospective study of 100 participants with persistent (>30 days) pulmonary symptoms after an acute COVID-19 infection; 106 healthy controls were also evaluated. The particular emphasis of this investigation was on the presence of air trapping on expiratory CT scans. The severity of disease varied among the three study groups, which included participants who were ambulatory, participants who were hospitalized, and those who required admission to the intensive care unit (ICU). Cho et al discovered that air trapping was present in 58% of participants following COVID-19 infection, with its highest prevalence in the hospitalized group (73%). Using quantitative analysis, air trapping affected a mean of 25%–35% of the lungs in participants, depending on the clinical severity of disease, compared with 7% in the healthy controls (P < .001). The authors did not identify obstructive airways disease with spirometry in any of the groups. The lack of obstruction at spirometry in patients with air trapping is not surprising. In a cohort of soldiers deployed to Iraq and Afghanistan with biopsy-proven constrictive bronchiolitis (8), the majority did not have obstruction on pulmonary function tests. Restriction was present at spirometry in the participants with COVID-19 in the study by Cho et al, specifically in the hospitalized and ICU groups. Ground-glass opacity, traction bronchiectasis, and other signs of fibrosis were most frequent in those admitted to the ICU (94%, 69%, and 81%, respectively, compared with 36%, 8%, and 3% of the ambulatory group, respectively).

In summary, the study by Cho et al (7) demonstrates that air trapping on CT scans is common in individuals with persistent symptoms after COVID-19. When considering the long-term pulmonary effects of COVID-19 infection, this is an important finding and may correspond to the development of postviral constrictive bronchiolitis, an entity seen with other viral infections and particularly adenovirus infection. Interestingly, the CT findings of acute COVID-19 are not highly airway-centric. Centrilobular nodules and tree-in-bud opacities, reflecting airway-centric inflammation, are not typical findings of acute COVID-19 infection. Regardless, these results indicate a long-term impact on bronchiolar obstruction. In the study by Cho et al, the presence of ground-glass opacity and/or fibrosis on CT scans was most common in the participants admitted to the ICU and likely corresponds to post-OP and/or post-DAD fibrosis.

It is important to note that not all incidences of pulmonary fibrosis, including those of the airway and of the parenchyma, are permanent. Collagen may be absorbed for months after the acute insult; thus, it is not entirely clear whether the abnormalities seen in the study by Cho et al will be permanent. The median time from COVID-19 diagnosis to the clinic visit for persistent post–COVID-19 symptoms was only 75 days. However, eight of nine participants (of 100 total participants) who underwent imaging more than 200 days from the acute infection had persistent air trapping. Regardless of the imaging findings, the most important question is whether the airways obstruction and/or fibrosis cause clinical symptoms. The results reported by Cho et al suggest that airways obstruction and post-OP and/or post-DAD fibrosis contribute to persistent symptoms after COVID-19 infection, with the contribution of airways disease being greater in the ambulatory group and the contribution of OP and DAD being greater in those admitted to the ICU. Longer-term studies assessing clinical and imaging manifestations 1–2 years after the initial infection are needed to fully ascertain the permanent manifestations of post–COVID-19 fibrosis.

References

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MRI showed a regional decrease of lung perfusion after exposure to tobacco smoke and a local increase of lung perfusion after electronic nicotine delivery systems use.

• ■ In tobacco smokers, a regional decrease of lung perfusion at functional MRI was shown following a single smoking session compared with the baseline measurement.

• ■ In participants who used an electronic nicotine delivery system, a local increase of lung perfusion was shown after exposure.

• ■ In healthy control participants, the mean difference between both measurements for perfusion impairment was –0.1% (95% CI: 1.4, –1.7).

In recent years, electronic nicotine delivery systems (ENDS; also known as vaping) have been established as substitutes for traditional cigarettes and are promoted as facilitating smoking cessation by replacing tobacco smoking. Randomized control trials suggest that ENDS can effectively support smoking cessation (1,2). Contrary to nicotine replacement therapy, a higher proportion of smokers who successfully quit tobacco smoking and were supported by ENDS continue to use ENDS beyond the point of successful smoking cessation (2). Although the use of ENDS is increasing on a global scale, there are limited data regarding the short- and long-term effects of ENDS usage on the lung. In laboratory analyses, ENDS is associated with a safer risk profile than conventional cigarettes (3). However, vaping increases heart rate and blood pressure similarly to conventional tobacco smoking (4). Previous in-vitro studies showed that electronic cigarette, or e-cigarette, exposure induces inflammation and oxidative stress in pulmonary endothelium and stem cells (5,6). Different studies assessed ENDS short-term effects on lung function (7,8). Five minutes of use of ENDS reduces the fraction of exhaled nitric oxide, a volatile molecule indicating airway inflammation, and increased airway resistance (8). One study used MRI to show that inhaling nicotine-free e-cigarette aerosol transiently affected endothelial function in healthy nonsmokers (9).

Compared with lung function tests, noninvasive MRI techniques have shown a high sensitivity and reproducibility in detecting local lung perfusion and ventilation impairment, in addition to helping assess structural changes in the lung parenchyma (10,11). Several reports suggested that functional MRI of the lungs could be a sensitive marker of parenchymal alteration, depicting early changes in ventilation and perfusion not detectable with traditional lung function parameters (11,12). Functional MRI in the lungs could be a sensitive marker to help assess early changes in ventilation and perfusion that are not detectable with traditional lung functional assessment.

The aim of our study is to investigate the short-term responsiveness of ventilation and perfusion changes to vaping and tobacco smoking exposure by using nitrogen multiple-breath washout, spirometry, and functional MRI. We hypothesize that use of ENDS and tobacco smoking variably affect lung perfusion and ventilation in comparison to a healthy control group.

This pilot study is a prospective observational study performed at the Bern University Hospital conducted between November 2019 and September 2021 and represents a substudy of the ongoing Efficacy, Safety and Toxicology of Electronic Nicotine Delivery Systems (ESTxENDS), which is a randomized controlled trial (NCT03589989). In ESTxENDS, active adult smokers consuming at least five cigarettes per day who are willing to make a serious quit attempt are randomized into usual care (control group) or usual care with ENDS and e-liquids for 6 months. Participants in the ESTxENDS trial in Bern were scheduled for their 6-month follow-up visit with the following smoking and/or use of ENDS status: former smokers (recent quitters for a maximum of 6 months and no current use of ENDS), ENDS users, and tobacco smokers. A healthy control group of never-smokers was included in Basel to assess the reproducibility of the MRI measurements. This study was approved by the local ethics committees at Bern and Basel (2017–02332 and 2018–00079, respectively). Written informed consent from all participants was obtained prior to study inclusion. All measurements in each individual participant were performed on the same day (Fig 1).

Figure 1: Study flowchart. ENDS = electronic nicotine delivery system.

Baseline measurements (nitrogen multiple-breath washout, spirometry, carbon monoxide diffusion capacity) in tobacco smokers and ENDS users were acquired after 2 hours of substance abstinence; 2 hours was chosen because that is the approximate plasma half-life of nicotine (13,14). Following the baseline measurements, tobacco smokers and ENDS users were instructed to smoke and vape, respectively. Immediately thereafter, study participants performed the same lung function tests again (nitrogen multiple-breath washout, spirometry, carbon monoxide diffusion capacity) to capture short-term effects. Former smokers performed repeated baseline measurements without smoking exposure.

Following the lung function assessment (before and after tobacco smoke or ENDS exposure), participants had to adhere to another 2-hour abstinence interval (no smoking or use of ENDS). The first MRI examination was performed in tobacco smokers and ENDS users. After undergoing MRI, participants were instructed again to smoke or vape until a subjective state of satisfaction was achieved. Immediately following this second exposure to tobacco smoke or ENDS, a second MRI examination was performed. Former smokers and healthy volunteers were measured without previous exposure.

MRI examinations were performed with a 1.5-T whole-body MRI scanner (Magnetom Aera; Siemens Healthineers) by using a 12-channel thorax and a 24-channel spine receiver coil array. Functional imaging was performed by using the matrix pencil decomposition free-breathing MRI technique without contrast agent administration (15,16). The matrix pencil MRI relies on dynamic free-breathing ultrafast balanced steady-state free precession lung image acquisitions and provides regional ventilation and perfusion information from a single acquisition series (17). Main parameters of the ultrafast balanced steady-state free precession pulse sequence are given in Table 1. The segmented areas are processed voxelwise by using a matrix pencil decomposition method in combination with a linear least square analysis to generate fractional ventilation and perfusion maps. Fractional ventilation maps reflect changes of the lung parenchyma density during respiration, whereas the perfusion maps reflect the amplitude of signal modulation caused by the pulsatile blood flow. For each subject, the lungs were automatically segmented on the calculated fractional ventilation and perfusion maps by using an artificial neural network (18,19). MRI postprocessing was fully automatized and required no manual interaction. The robustness of the automatized segmentation versus manual segmentation was recently assessed (17). Detailed information about MRI data evaluation is described in Appendix E1 (online). Software and protocols were the same at both sites.

Voxel distributions of the segmented lung regions in fractional ventilation and perfusion maps were used to estimate threshold values indicating a functional impairment (20). Primary outcomes were percentage of the lung volume with impaired fractional ventilation (RFV) and measured impairment of lung perfusion (RQ). Morphologic scans were chosen on the basis of published standard MRI protocols for chest examinations (21). Structural changes in the lung parenchyma were assessed on the proton MRI images by two independent reviewers; discrepancies were resolved by consensus. Observers were blinded to the participants’ groups.

Nitrogen multiple-breath washout was performed with a commercially available device (Exhalyzer D; Eco Medics) according to consensus guidelines (22). The primary outcome was the lung clearance index (LCI). Spirometry (Jaeger MasterScreen; CareFusion) was conducted according to the official clinical practice guideline of the American Thoracic Society, the European Respiratory Society, the Japanese Respiratory Society, and the Latin American Thoracic Society (23). Primary outcomes were forced expiratory volume in 1 second (FEV1) and the FEV1-to–forced vital capacity (FVC) ratio. Diffusion capacity of the lungs for carbon monoxide was assessed as recommended (24–26).

Continuous variables were skewed and described by using nonparametric estimates. Differences between measurements were compared with paired Wilcoxon signed-rank test, and differences between groups were compared with unpaired Mann-Whitney test. Participants who used ENDS were stratified in groups of those who used nicotine-containing e-liquids and those who used nicotine-free e-liquids. Post hoc analysis was performed by comparing LCI before exposure (based on all nitrogen multiple-breath washout tests with the LCI from the first nitrogen multiple-breath washout test) and directly after exposure. Associations between functional indexes from MRI and lung function before and after exposure were examined graphically and were quantified by using the Spearman correlation coefficient. The agreement over two measurements was assessed by using intraclass correlation (ICC) coefficients and Bland Altman plot. ICC is defined as very good (ICC, >0.8), good (ICC, 0.6–0.8) and moderate (ICC, 0.4–0.6) (27). Upper limit of normal LCI was calculated with published data for healthy adults (ie, mean + 1.6 × SD) (28). P values less than .05 were considered to indicate statistical significance. Analyses were performed by using software (StataTM Stata Statistical Software, release 13, StataCorp; Matlab 2012b, MathWorks; and GraphPad Prism, GraphPad Software).

A total of 44 adult participants (28 men; mean age, 41 years ± 12 [SD]) were enrolled. Seven tobacco smokers consumed more than 10 cigarettes per day. Eight ENDS users vaped more than 50 puffs per day. Nine ENDS users were using the ENDS device provided to participants at the ESTxENDS trial and four participants (30.7%) were not vaping nicotine-containing e-liquids (Table E1 [online]). Characteristics of study participants are given in Table 2.

All 44 participants were able to perform functional MRI at both points. Functional lung MRI was performed for an average of 6.3 minutes (range, 5.3–9.8 minutes). All morphologic scans and functional measurements were of good diagnostic image quality. Morphologic imaging included an ultrashort echo time sequence without depiction of extensive parenchymal abnormalities (eg, lung fibrosis).

Exposure duration was set for the minimum time required to smoke at least one cigarette or use an ENDS product (ie, use of nicotine-containing e-liquids and nicotine-free e-liquids). On average, 1.6 cigarettes ± 1.2 were smoked for 6.8 minutes ± 3.6. In the ENDS users’ group, 19 ± 13 puffs were vaped for 4.9 minutes ± 1.1 (Table 2). Measurements were performed directly afterward. Common symptoms after exposure were dry mouth (n = 6; 24%) and cough (n = 5; 20%).

Local perfusion decreased in tobacco smokers after exposure (RQ, 8.6% [IQR, 7.2%–10.0%] to 9.1% [IQR, 7.8%–10.7%]; P = .03 compared with the baseline measurement) (Fig 2, Table 3). However, local perfusion increased in participants who used ENDS after exposure (RQ, 9.7% [IQR, 7.1%–10.9%] to 9.0% [IQR, 6.9%–10.0%]; P = .01) (Figs 3, 4). Subsequently, we stratified participants in the following groups: participants who used nicotine-containing e-liquids (n = 9; 69%) and participants who used nicotine-free e-liquids (n = 4; 31%). Local perfusion increased after exposure in participants who used ENDS with nicotine containing e-liquids (RQ, 9.7% [IQR, 8.4%–10.7%] to 8.0% [IQR, 7.3%–9.9%]; P = .01). No change in perfusion was detected in the group of participants who used nicotine-free e-liquids (8.3% [IQR, 5.2%–11.9%] to 7.8% [IQR, 5.2%–10.5%]; P = .5; Fig E1 [online]). RFV did not change in any group (Fig E2 [online]).

Figure 2: (A–C) Example of pulmonary perfusion images obtained by using noncontrast-enhanced matrix pencil MRI in three different tobacco smokers before exposure (pre-exposure) and after exposure (post-exposure). The images before and after exposure were acquired at corresponding coronal section locations. Arrows indicate lung regions with decreased regional perfusion after the exposure to nicotine. Red corresponds to high values of ventilation amplitude and perfusion amplitude, whereas blue corresponds to low values.

Figure 3: (A–C) Example of pulmonary perfusion images obtained by using noncontrast matrix pencil MRI in three electronic nicotine delivery system (ENDS) users before exposure (pre-exposure) and after exposure (post-exposure). The images before and after exposure were acquired at corresponding coronal section locations. The arrows indicate lung regions with increased regional perfusion after the exposure. Red corresponds to high values of ventilation amplitude and perfusion amplitude, whereas the blue color corresponds to low values.

Figure 4: Box and whisker plot of impairment of perfusion in all participants. Electronic nicotine delivery system (ENDS) users and tobacco smokers performed measurements before and after exposure. Former smokers and healthy control participants performed measurements at MRI without exposure. * = Significant P value.

The LCI was elevated in five of nine former smokers (56%), five of 13 ENDS users (38%), and six of 12 tobacco smokers (50%) before exposure (Table 4). Spirometry and diffusion capacity of the lungs for carbon monoxide indexes did not show any obstructive lung disease, abnormal dynamic volumes according to z-scores, or other impairment in tobacco smokers and ENDS users. No change in lung function compared with baseline was observed in the stratified participants who used nicotine-containing e-liquids and who used nicotine-free e-liquids (Table E2 [online]). After exposure, the mean of the LCI (on the basis of the sum of repeated nitrogen multiple-breath washout measurements) did not change for any group. However, the post hoc analysis showed that the initial first LCI measurement directly after exposure increased in tobacco smokers from 8.3 (IQR, 8.0–8.8) to 9.5 (IQR, 8.3–11.3) (P = .02) (Fig 5), indicating increased global ventilation inhomogeneity. In all groups, there were no systematic changes in spirometry and diffusion capacity of the lungs for carbon monoxide indexes between both measurements (Table 4).

Figure 5: Graph of short-term change of lung clearance index (LCI) before and after tobacco smoking. LCI was assessed at nitrogen multiple-breath washout to capture ventilation inhomogeneity and spirometry to assess airflow limitation. After exposure, the mean LCI did not change in participants after they smoked tobacco. However, the post hoc analysis showed that LCI from the first initial nitrogen multiple-breath washout measurement after exposure (P = .02) increased, indicating increased global ventilation inhomogeneit y. * = First initial nitrogen multiple-breath washout measurement after exposure. ** = Mean of all nitrogen multiple-breath washout measurements.

In tobacco smokers and ENDS users, the extent of RQ was between 5% and 13.0% before exposure and 5% and 15.0% after exposure, respectively. In tobacco smokers, we suggested a correlation between RQ and LCI after exposure (r = 0.65; P = .02) (Fig 6). The extent of impaired ventilation relative to lung volume (ie, RFV) in tobacco smokers and ENDS users ranged between 7% and 18% before exposure and 6% and 17% after exposure, respectively. RFV showed no correlation with LCI after exposure in in tobacco smokers and ENDS users (r = 0.35, P = .27; and r = 0.37, P = .21, respectively). We found no correlation between FEV1 or FEV1-to-FVC ratio and functional MRI indexes in any group.

Figure 6: Plot of correlation between lung clearance index (LCI) and perfusion impairment of the lung in percentage. LCI was assessed at nitrogen multiple-breath washout to capture ventilation inhomogeneity and spirometry to assess airflow limitation. Participants were tobacco smokers, and the correlation was determined after exposure. In tobacco smokers, we suggest a correlation between perfusion and LCI after exposure (r = 0.65; P = .02).

Agreement measured by ICC in former smokers ranged between very good and good for lung function and MRI indexes. The ICC for RFV between two measurements in the same individual was very good in former smokers (ICC, 0.9). The ICC for RQ was good in former smokers (ICC, 0.6). The ICC for LCI was very good in former smokers (ICC, 0.9). In healthy control participants, the ICC was very good for MRI indexes. The ICC for RFV and RQ between two measurements in the same participant was very good (ICC, 0.9). In healthy control participants, the mean difference between both measurements for perfusion impairment was –0.1% (95% CI: 1.4, –1.7). For ventilation impairment, the mean difference was –0.02% (95% CI: 1.9, –2.0) (Fig 7).

Figure 7: Bland-Altman plots for intertest agreement of two consecutive MRI measurements, the (A) perfusion impairment and (B) ventilation impairment, in healthy control participants (never-smokers; n = 10). Ninety-five percent limits of agreement are shown as dotted lines and mean differences are displayed as dashed lines.

We examined the intra-individual short-term responsiveness of lung perfusion and ventilation after the use of electronic nicotine delivery systems (ENDS) and tobacco smoking assessed by using a matrix pencil MRI technique and lung function tests. By using noncontrast-enhanced functional lung MRI, perfusion decreased in tobacco smokers after exposure (measured impairment of lung perfusion [RQ], 8.6% [IQR, 7.2%–10.0%] to 9.1% [IQR, 7.8%–10.7%]; P = .03) compared with the baseline measurement. However, perfusion increased after exposure in participants who used ENDS (RQ, 9.7% [IQR, 7.1%–10.9%] to 9.0% [IQR, 6.9%–10.0%]; P = .01). Among participants who used nicotine-free e-liquids, no systematic change in RQ was detected (RQ, 8.3% [IQR, 5.2%–11.9%] to 7.8% [IQR, 5.2%–10.5%]; P = .5). In healthy control participants, the intervisit reproducibility for measured impairment of fractional ventilation and RQ was very good, and the relatively small systematic changes detected in our study were considered reliable. Spirometry-derived forced expiratory volume in 1 second–to–forced vital capacity ratio z-scores did not systematically change after exposure and was normal at the baseline in tobacco smoker and ENDS users. However, lung clearance index from the nitrogen multiple-breath washout was elevated in five of nine former smokers (56%), five of 13 ENDS users (38%), and six of 12 tobacco smokers (50%) at baseline. This indicated increased ventilation inhomogeneity related to the small airways disease, potentially caused by smoking exposure.

After exposure, the mean LCI (based on the sum of repeated nitrogen multiple-breath washout measurements) did not change for any group. However, the post hoc analysis showed that the initial first LCI measurement directly after exposure increased (higher ventilation inhomogeneity) in tobacco smokers (LCI, 8.3 [IQR, 8.0–8.8] and 9.5 [IQR, 8.3–11.3], respectively; P = .02). Overall, the correlation between perfusion impairment and LCI in tobacco smoking suggested that tobacco smoking induces a short-term change in lung function. This finding was not confirmed by the RFV at MRI. This could be attributable to the MRI method itself, where the ventilation maps are an extrapolation from the changes of signal intensities from the perfusion maps.

Our results indicated opposite effects of tobacco smoke and ENDS aerosol on perfusion impairment assessed at functional MRI. We demonstrated a decrease of local perfusion after tobacco smoking. This agrees with previous studies, showing ventilation and perfusion mismatch in response to smoking one cigarette by measuring the blood flow in the pulmonary capillaries (29). In tobacco smoking products, nicotine is one major constituent that is a strong alkaloid (30). As a result, peripheral vasoconstriction, tachycardia, and elevated blood pressure may be observed after nicotine intake (31). Another study demonstrated acute vasoconstriction of the epicardial coronary arteries and reduced coronary flow reserve after smoking (32). However, we found an increase of local perfusion with functional MRI after exposure to ENDS products. We stratified a priori the participants into two groups: one who used nicotine-containing e-liquids and the other group who used e-liquids without nicotine. In participants who used nicotine-containing e-liquids, we observed an increase of local perfusion impairment in functional MRI. Flavorings can alter airway responsiveness in murine models (33). Sixty-nine percent of participants in our study had different flavors in their e-liquids. Whether short-term perfusion changes in the ENDS users in our study is caused by additives remains unexplored and requires further investigation. To our knowledge, long-term consequences of perfusion changes in healthy individuals are unknown and should be investigated.

With findings that were different than what we found in our data, Caporale et al (9) found a decrease in luminal flow-mediated dilation and reactive hyperemia peak velocity after vaping in the thigh arterial vasculature, which is a different perfusion territory that serves the skeletal muscle and has a high resistive index with biphasic flow at rest. Measurements were on the basis of the peripheral vascular reactivity (femoral artery). In our study, we used a dynamic free-breathing multisection ultrafast balanced steady-state free precession acquisition in the whole lung, providing regional fractional ventilation and perfusion maps. It remains unclear why different effects on the vessels were observed on pulmonary compared with peripheral vessels in the lungs. Similar to our study, a recent study found increased ventilation and perfusion mismatch in people who vape. Kizhakke et al (34) used oxygen-enhanced MRI and had results that were comparable to ours but in a study population of younger participants. Instead of the oxygen-enhanced MRI method, we used the matrix pencil MRI technique, which did not require any gas or contrast media application. Both techniques indicated that ENDS liquids and their constituents affect lung perfusion.

This is a small sample size, and these data need to be confirmed in a larger study. Our study design allowed for an observation period that was created to noninvasively standardize the study protocol while also allowing participants to enlist without concerns of nicotine deprivation. Considering the relatively short half-live of nicotine (approximately 2 hours), this approach guaranteed complete adherence to the protocol by all participants. A critical point is the overlap of the results in the intergroup comparison. However, our aim was to detect intraindividual changes of lung perfusion and ventilation, yielding significant results. In addition, differences in the outcome values could be influenced by a large number of variables (eg, age, sex, weight, degree of emphysema, and heart disease).

In conclusion, short-term perfusion changes after use of electronic nicotine delivery systems and tobacco smoke exposure can be sensitively detected by functional MRI. Perfusion impairment at MRI did correlate with ventilation inhomogeneity (lung clearance index) and was altered after tobacco smoking. Lung ventilation at MRI showed no changes after exposure to nicotine. These preliminary results suggest that MRI indexes may be considered as a noninvasive test to complement pulmonary function testing in this setting.

The authors thank all participants for their contribution to the study. The authors express their thankfulness especially to Verena Beutler-Minth; Jessica Kuhn; Jeannette Frey, MD; and Ian Leigh Alberts, MD; and to all the study nurses and medical-technical assistants from the radiology department for their participant care, support in measurements, and recruitment of the participants.

Author Contributions

Author contributions: Guarantors of integrity of entire study, S.N., L.E.; study concepts/study design or data acquisition or data analysis/interpretation, all authors; manuscript drafting or manuscript revision for important intellectual content, all authors; approval of final version of submitted manuscript, all authors; agrees to ensure any questions related to the work are appropriately resolved, all authors; literature research, S.N., O.P., F.S., M.I., A.C., L.E.; clinical studies, O.P., C.G., A.S., J.T.H., O.B., R.A., M.F.C., L.E.; experimental studies, O.P., M.I., A.C., O.B., L.E.; statistical analysis, S.N., G.B., I.K., O.P., F.S., A.C., L.E.; and manuscript editing, S.N., G.B., I.K., O.P., F.S., M.I., A.S., J.T.H., A.C., N.R., O.B., T.G., R.A., M.F.C., L.E.

* S.N. and G.B. contributed equally to this work.

** M.F.C. and L.E. are co-senior authors.

Study supported by the Clinical Trial Unit Research Grant and the Lung League Bern research grant; the Swiss National Science Foundation, via the “Investigator-initiated clinical trials—IICT (grant no. 33IC30_173552); and the Clinical Trial Unit Research Grant and the Lung League Bern research grant. R.A. supported by the Tobacco Prevention Fund (TPF 19.017477) and Swiss Cancer Research (grant no. KSF4744-02-2019)

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Published Online:Apr 5 2022https://doi.org/10.1148/radiol.220325

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