Association of Ground Glass Opacities with Systemic Inflammation and Progression of Emphysema.

RATIONAL: Ground glass opacities (GGO) in the absence of interstitial lung disease are understudied. OBJECTIVE: To assess the association of GGO with white blood cells (WBCs) and progression of quantified chest CT emphysema. METHODS: We analyzed data of participants in the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS). Chest radiologists and pulmonologists labeled regions of the lung as GGO and adaptive multiple feature method (AMFM) trained the computer to assign those labels to image voxels and quantify the volume of the lung with GGO (%GGOAMFM). We used multivariable linear regression, zero-inflated negative binomial, and proportional hazards regression models to assess the association of %GGOAMFM with WBC, changes in %emphysema, and clinical outcomes. MEASUREMENTS AND MAIN RESULTS: Among 2,714 participants, 1,680 had COPD and 1,034 had normal spirometry. Among COPD participants, based on the multivariable analysis, current smoking and chronic productive cough was associated with higher %GGOAMFM. Higher %GGOAMFM was cross-sectionally associated with higher WBCs and neutrophils levels. Higher %GGOAMFM per interquartile range at visit 1 (baseline) was associated with an increase in emphysema at one-year follow visit by 11.7% (Relative increase; 95%CI 7.5-16.1%;P<0.001). We found no association between %GGOAMFM and one-year FEV1 decline but %GGOAMFM was associated with exacerbations and all-cause mortality during a median follow-up time of 1,544 days (Interquartile Interval=1,118-2,059). Among normal spirometry participants, we found similar results except that %GGOAMFM was associated with progression to COPD at one-year follow-up. CONCLUSIONS: Our findings suggest that GGOAMFM is associated with increased systemic inflammation and emphysema progression.

Vessel and Airway Characteristics in One-Year Computed Tomography-defined Rapid Emphysema Progression: SPIROMICS.

Rationale: Rates of emphysema progression vary in chronic obstructive pulmonary disease (COPD), and the relationships with vascular and airway pathophysiology remain unclear. Objectives: We sought to determine if indices of peripheral (segmental and beyond) pulmonary arterial dilation measured on computed tomography (CT) are associated with a 1-year index of emphysema (EI; percentage of voxels <-950 Hounsfield units) progression. Methods: Five hundred ninety-nine former and never-smokers (Global Initiative for Chronic Obstructive Lung Disease stages 0-3) were evaluated from the SPIROMICS (Subpopulations and Intermediate Outcome Measures in COPD Study) cohort: rapid emphysema progressors (RPs; n = 188, 1-year ΔEI > 1%), nonprogressors (n = 301, 1-year ΔEI ± 0.5%), and never-smokers (n = 110). Segmental pulmonary arterial cross-sectional areas were standardized to associated airway luminal areas (segmental pulmonary artery-to-airway ratio [PAARseg]). Full-inspiratory CT scan-derived total (arteries and veins) pulmonary vascular volume (TPVV) was compared with small vessel volume (radius smaller than 0.75 mm). Ratios of airway to lung volume (an index of dysanapsis and COPD risk) were compared with ratios of TPVV to lung volume. Results: Compared with nonprogressors, RPs exhibited significantly larger PAARseg (0.73 ± 0.29 vs. 0.67 ± 0.23; P = 0.001), lower ratios of TPVV to lung volume (3.21 ± 0.42% vs. 3.48 ± 0.38%; P = 5.0 × 10-12), lower ratios of airway to lung volume (0.031 ± 0.003 vs. 0.034 ± 0.004; P = 6.1 × 10-13), and larger ratios of small vessel volume to TPVV (37.91 ± 4.26% vs. 35.53 ± 4.89%; P = 1.9 × 10-7). In adjusted analyses, an increment of 1 standard deviation in PAARseg was associated with a 98.4% higher rate of severe exacerbations (95% confidence interval, 29-206%; P = 0.002) and 79.3% higher odds of being in the RP group (95% confidence interval, 24-157%; P = 0.001). At 2-year follow-up, the CT-defined RP group demonstrated a significant decline in postbronchodilator percentage predicted forced expiratory volume in 1 second. Conclusions: Rapid one-year progression of emphysema was associated with indices indicative of higher peripheral pulmonary vascular resistance and a possible role played by pulmonary vascular-airway dysanapsis.

LungViT: Ensembling Cascade of Texture Sensitive Hierarchical Vision Transformers for Cross-Volume Chest CT Image-to-Image Translation.

Chest computed tomography (CT) at inspiration is often complemented by an expiratory CT to identify peripheral airways disease. Additionally, co-registered inspiratory-expiratory volumes can be used to derive various markers of lung function. Expiratory CT scans, however, may not be acquired due to dose or scan time considerations or may be inadequate due to motion or insufficient exhale; leading to a missed opportunity to evaluate underlying small airways disease. Here, we propose LungViT- a generative adversarial learning approach using hierarchical vision transformers for translating inspiratory CT intensities to corresponding expiratory CT intensities. LungViT addresses several limitations of the traditional generative models including slicewise discontinuities, limited size of generated volumes, and their inability to model texture transfer at volumetric level. We propose a shifted-window hierarchical vision transformer architecture with squeeze-and-excitation decoder blocks for modeling dependencies between features. We also propose a multiview texture similarity distance metric for texture and style transfer in 3D. To incorporate global information into the training process and refine the output of our model, we use ensemble cascading. LungViT is able to generate large 3D volumes of size 320×320×320 . We train and validate our model using a diverse cohort of 1500 subjects with varying disease severity. To assess model generalizability beyond the development set biases, we evaluate our model on an out-of-distribution external validation set of 200 subjects. Clinical validation on internal and external testing sets shows that synthetic volumes could be reliably adopted for deriving clinical endpoints of chronic obstructive pulmonary disease.

Nuclear epidermal growth factor receptor as a therapeutic target.

Epidermal growth factor receptor (EGFR) is one of the most well-studied oncogenes with roles in proliferation, growth, metastasis, and therapeutic resistance. This intense study has led to the development of a range of targeted therapeutics including small-molecule tyrosine kinase inhibitors (TKIs), monoclonal antibodies, and nanobodies. These drugs are excellent at blocking the activation and kinase function of wild-type EGFR (wtEGFR) and several common EGFR mutants. These drugs have significantly improved outcomes for patients with cancers including head and neck, glioblastoma, colorectal, and non-small cell lung cancer (NSCLC). However, therapeutic resistance is often seen, resulting from acquired mutations or activation of compensatory signaling pathways. Additionally, these therapies are ineffective in tumors where EGFR is found predominantly in the nucleus, as can be found in triple negative breast cancer (TNBC). In TNBC, EGFR is subjected to alternative trafficking which drives the nuclear localization of the receptor. In the nucleus, EGFR interacts with several proteins to activate transcription, DNA repair, migration, and chemoresistance. Nuclear EGFR (nEGFR) correlates with metastatic disease and worse patient prognosis yet targeting its nuclear localization has proved difficult. This review provides an overview of current EGFR-targeted therapies and novel peptide-based therapies that block nEGFR, as well as their clinical applications and potential for use in oncology.

Response to high dose ipilimumab plus temozolomide after progression on standard or low dose ipilimumab in advanced melanoma: a retrospective analysis.

Background: Despite advancements in checkpoint inhibitor-based immunotherapy, patients with advanced melanoma who have progressed on standard dose ipilimumab (Ipi) + nivolumab continue to have poor prognosis. Several studies support a dose-response activity of Ipi, and one promising combination is Ipi 10mg/kg (Ipi10) + temozolomide (TMZ). Methods: We performed a retrospective cohort analysis of patients with advanced melanoma treated with Ipi10+TMZ in the immunotherapy refractory/resistant setting (n = 6), using similar patients treated with Ipi3+TMZ (n = 6) as comparison. Molecular profiling by whole exome sequencing (WES) and RNA-seq of tumors harvested through one responder's treatment was performed. Results: With a median follow up of 119 days, patients treated with Ipi10+TMZ had statistically significant longer median progression free survival of 144.5 days (range 27-219) vs 44 (26-75) in Ipi3+TMZ, p=0.04, and a trend for longer median overall survival of 154.5 days (27-537) vs 89.5 (26-548). All patients in the Ipi10 cohort had progressed on prior Ipi+Nivo. WES revealed only 12 shared somatic mutations including BRAF V600E. RNA-seq showed enrichment of inflammatory signatures, including interferon responses in metastatic lesions after standard dose Ipi + nivo and Ipi10 + TMZ compared to the primary tumor, and downregulated negative immune regulators including Wnt and TGFb signaling. Conclusion: Ipi10+TMZ demonstrated efficacy including dramatic responses in patients with advanced melanoma refractory to prior Ipi + anti-PD1, even with CNS metastases. Molecular data suggest a potential threshold of Ipi dose for activation of sufficient anti-tumor immune response, and higher dose Ipi is required for some patients.

Localization supervision of chest x-ray classifiers using label-specific eye-tracking annotation.

Convolutional neural networks (CNNs) have been successfully applied to chest x-ray (CXR) images. Moreover, annotated bounding boxes have been shown to improve the interpretability of a CNN in terms of localizing abnormalities. However, only a few relatively small CXR datasets containing bounding boxes are available, and collecting them is very costly. Opportunely, eye-tracking (ET) data can be collected during the clinical workflow of a radiologist. We use ET data recorded from radiologists while dictating CXR reports to train CNNs. We extract snippets from the ET data by associating them with the dictation of keywords and use them to supervise the localization of specific abnormalities. We show that this method can improve a model's interpretability without impacting its image-level classification.

Quantifying the Preferential Direction of the Model Gradient in Adversarial Training With Projected Gradient Descent.

Adversarial training, especially projected gradient descent (PGD), has proven to be a successful approach for improving robustness against adversarial attacks. After adversarial training, gradients of models with respect to their inputs have a preferential direction. However, the direction of alignment is not mathematically well established, making it difficult to evaluate quantitatively. We propose a novel definition of this direction as the direction of the vector pointing toward the closest point of the support of the closest inaccurate class in decision space. To evaluate the alignment with this direction after adversarial training, we apply a metric that uses generative adversarial networks to produce the smallest residual needed to change the class present in the image. We show that PGD-trained models have a higher alignment than the baseline according to our definition, that our metric presents higher alignment values than a competing metric formulation, and that enforcing this alignment increases the robustness of models.

Predicting severe chronic obstructive pulmonary disease exacerbations using quantitative CT: a retrospective model development and external validation study.

BACKGROUND: Quantitative CT is becoming increasingly common for the characterisation of lung disease; however, its added potential as a clinical tool for predicting severe exacerbations remains understudied. We aimed to develop and validate quantitative CT-based models for predicting severe chronic obstructive pulmonary disease (COPD) exacerbations. METHODS: We analysed the Subpopulations and Intermediate Outcome Measures In COPD Study (SPIROMICS) cohort, a multicentre study done at 12 clinical sites across the USA, of individuals aged 40-80 years from four strata: individuals who never smoked, individuals who smoked but had normal spirometry, individuals who smoked and had mild to moderate COPD, and individuals who smoked and had severe COPD. We used 3-year follow-up data to develop logistic regression classifiers for predicting severe exacerbations. Predictors included age, sex, race, BMI, pulmonary function, exacerbation history, smoking status, respiratory quality of life, and CT-based measures of density gradient texture and airway structure. We externally validated our models in a subset from the Genetic Epidemiology of COPD (COPDGene) cohort. Discriminative model performance was assessed using the area under the receiver operating characteristic curve (AUC), which was also compared with other predictors, including exacerbation history and the BMI, airflow obstruction, dyspnoea, and exercise capacity (BODE) index. We evaluated model calibration using calibration plots and Brier scores. FINDINGS: Participants in SPIROMICS were enrolled between Nov 12, 2010, and July 31, 2015. Participants in COPDGene were enrolled between Jan 10, 2008, and April 15, 2011. We included 1956 participants from the SPIROMICS cohort who had complete 3-year follow-up data: the mean age of the cohort was 63·1 years (SD 9·2) and 1017 (52%) were men and 939 (48%) were women. Among the 1956 participants, 434 (22%) had a history of at least one severe exacerbation. For the CT-based models, the AUC was 0·854 (95% CI 0·852-0·855) for at least one severe exacerbation within 3 years and 0·931 (0·930-0·933) for consistent exacerbations (defined as ≥1 acute episode in each of the 3 years). Models were well calibrated with low Brier scores (0·121 for at least one severe exacerbation; 0·039 for consistent exacerbations). For the prediction of at least one severe event during 3-year follow-up, AUCs were significantly higher with CT biomarkers (0·854 [0·852-0·855]) than exacerbation history (0·823 [0·822-0·825]) and BODE index 0·812 [0·811-0·814]). 6965 participants were included in the external validation cohort, with a mean age of 60·5 years (SD 8·9). In this cohort, AUC for at least one severe exacerbation was 0·768 (0·767-0·769; Brier score 0·088). INTERPRETATION: CT-based prediction models can be used for identification of patients with COPD who are at high risk of severe exacerbations. The newly identified CT biomarkers could potentially enable investigation into underlying disease mechanisms responsible for exacerbations. FUNDING: National Institutes of Health and the National Heart, Lung, and Blood Institute.

Sorting nexin-dependent therapeutic targeting of oncogenic epidermal growth factor receptor.

Overexpression and/or overactivation of the Epidermal Growth Factor Receptor (EGFR) is oncogenic in several tumor types yet targeting the kinase domain of wildtype EGFR has had limited success. EGFR has numerous kinase-independent roles, one of which is accomplished through the Sorting Nexin-dependent retrotranslocation of EGFR to the nucleus, which is observed in some metastatic cancers and therapeutically resistant disease. Here, we have utilized the BAR domain of Sorting Nexin 1 to create a peptide-based therapeutic (cSNX1.3) that promotes cell death in EGFR-expressing cancer. We evaluated the efficacy of cSNX1.3 in tumor-bearing WAP-TGFα transgenic mice (an EGFR-dependent model of breast cancer), where cSNX1.3 treatment resulted in significant tumor regression without observable toxicity. Evaluation of remaining tumor tissues found evidence of increased PARP cleavage, suggesting apoptotic tumor cell death. To evaluate the mechanism of action for cSNX1.3, we found that cSNX1.3 binds the C-terminus of the EGFR kinase domain at an interface site opposite the ATP binding domain with a Kd of ~4.0 µM. In vitro analysis found that cSNX1.3 inhibits the nuclear localization of EGFR. To determine specificity, we evaluated cancer cell lines expressing wildtype EGFR (MDA-MB-468, BT20 and A549), mutant EGFR (H1975) and non-transformed lines (CHO and MCF10A). Only transformed lines expressing wildtype EGFR responded to cSNX1.3, while mutant EGFR and normal cells responded better to an EGFR kinase inhibitor. Phenotypically, cSNX1.3 inhibits EGF-, NRG-, and HGF-dependent migration, but not HA-dependent migration. Together, these data indicate that targeting retrotranslocation of EGFR may be a potent therapeutic for RTK-active cancer.

REFLACX, a dataset of reports and eye-tracking data for localization of abnormalities in chest x-rays.

Deep learning has shown recent success in classifying anomalies in chest x-rays, but datasets are still small compared to natural image datasets. Supervision of abnormality localization has been shown to improve trained models, partially compensating for dataset sizes. However, explicitly labeling these anomalies requires an expert and is very time-consuming. We propose a potentially scalable method for collecting implicit localization data using an eye tracker to capture gaze locations and a microphone to capture a dictation of a report, imitating the setup of a reading room. The resulting REFLACX (Reports and Eye-Tracking Data for Localization of Abnormalities in Chest X-rays) dataset was labeled across five radiologists and contains 3,032 synchronized sets of eye-tracking data and timestamped report transcriptions for 2,616 chest x-rays from the MIMIC-CXR dataset. We also provide auxiliary annotations, including bounding boxes around lungs and heart and validation labels consisting of ellipses localizing abnormalities and image-level labels. Furthermore, a small subset of the data contains readings from all radiologists, allowing for the calculation of inter-rater scores.

Feasibility and Clinical Utility of a Workflow Interfacing Radiation Oncology Lung Stereotactic Body Radiation Therapy Treatment Planning and Diagnostic Radiology.

Stereotactic body radiation therapy (SBRT) is commonly used to treat early-stage non-small cell lung cancer. Beam arrangements for SBRT include multiple entry and exit pathways resulting in irregular low-dose distributions within normal lung parenchyma. An improved understanding of posttreatment radiographic changes may improve the ability to predict clinical complications including radiation pneumonitis as well as assist in early detection of local failures. Radiation treatment planning is conducted using software systems separate from diagnostic radiology, often not accessible to the diagnostic radiologist. We developed a workflow for interfacing radiation dose information from lung SBRT treatments with a diagnostic radiology picture archiving and communication system (PACS). In an anonymized PACS study folder, SBRT dose maps depicting high-dose, low-dose, and nonirradiated lung volumes were viewable side by side with pretreatment and follow-up diagnostic computed tomography scans. Clinical utility was evaluated by 2 thoracic diagnostic radiologists reviewing posttreatment diagnostic follow-up scans in the PACS both with and without radiation dose maps available. The addition of the biologically effective dose map did not significantly change identification rates of radiation induced lung injury) (92% vs 95%; P = .32) but did significantly decrease radiologic suspicion for local recurrence (22% vs 8%; P = .003). The addition of biologically effective dose maps significantly increased confidence in identifying radiation induced lung injury (7.75 vs 8.82; P = .004) and local recurrence (5.5 vs 6.6; P = .005). The recommendation for additional workup was not significantly different (10% vs 7%; P = .41). We demonstrated the feasibility and clinical utility of a workflow generating simplified radiation dose maps that are viewable within a PACS for diagnostic radiology review.

PLOSL: Population learning followed by one shot learning pulmonary image registration using tissue volume preserving and vesselness constraints.

This paper presents the Population Learning followed by One Shot Learning (PLOSL) pulmonary image registration method. PLOSL is a fast unsupervised learning-based framework for 3D-CT pulmonary image registration algorithm based on combining population learning (PL) and one-shot learning (OSL). The PLOSL image registration has the advantages of the PL and OSL approaches while reducing their respective drawbacks. The advantages of PLOSL include improved performance over PL, substantially reducing OSL training time and reducing the likelihood of OSL getting stuck in local minima. PLOSL pulmonary image registration uses tissue volume preserving and vesselness constraints for registration of inspiration-to-expiration and expiration-to-inspiration pulmonary CT images. A coarse-to-fine convolution encoder-decoder CNN architecture is used to register large and small shape features. During training, the sum of squared tissue volume difference (SSTVD) compensates for intensity differences between inspiration and expiration computed tomography (CT) images and the sum of squared vesselness measure difference (SSVMD) helps match the lung vessel tree. Results show that the PLOSL (SSTVD+SSVMD) algorithm achieved subvoxel landmark error while preserving pulmonary topology on the SPIROMICS data set, the public DIR-LAB COPDGene and 4DCT data sets.

Application of Microfluidic Systems for Breast Cancer Research.

Cancer is a disease in which cells in the body grow out of control; breast cancer is the most common cancer in women in the United States. Due to early screening and advancements in therapeutic interventions, deaths from breast cancer have declined over time, although breast cancer remains the second leading cause of cancer death among women. Most deaths are due to metastasis, as cancer cells from the primary tumor in the breast form secondary tumors in remote sites in distant organs. Over many years, the basic biological mechanisms of breast cancer initiation and progression, as well as the subsequent metastatic cascade, have been studied using cell cultures and animal models. These models, although extremely useful for delineating cellular mechanisms, are poor predictors of physiological responses, primarily due to lack of proper microenvironments. In the last decade, microfluidics has emerged as a technology that could lead to a paradigm shift in breast cancer research. With the introduction of the organ-on-a-chip concept, microfluidic-based systems have been developed to reconstitute the dominant functions of several organs. These systems enable the construction of 3D cellular co-cultures mimicking in vivo tissue-level microenvironments, including that of breast cancer. Several reviews have been presented focusing on breast cancer formation, growth and metastasis, including invasion, intravasation, and extravasation. In this review, realizing that breast cancer can recur decades following post-treatment disease-free survival, we expand the discussion to account for microfluidic applications in the important areas of breast cancer detection, dormancy, and therapeutic development. It appears that, in the future, the role of microfluidics will only increase in the effort to eradicate breast cancer.

Forced Expiratory Flow at 25%-75% Links COPD Physiology to Emphysema and Disease Severity in the SPIROMICS Cohort.

BACKGROUND: Forced expiratory volume in 1 second (FEV1) is central to the diagnosis of chronic obstructive pulmonary disease (COPD) but is imprecise in classifying disease burden. We examined the potential of the maximal mid-expiratory flow rate (forced expiratory flow rate between 25% and 75% [FEF25%-75%]) as an additional tool for characterizing pathophysiology in COPD. OBJECTIVE: To determine whether FEF25%-75% helps predict clinical and radiographic abnormalities in COPD. STUDY DESIGN AND METHODS: The SubPopulations and InteRediate Outcome Measures In COPD Study (SPIROMICS) enrolled a prospective cohort of 2978 nonsmokers and ever-smokers, with and without COPD, to identify phenotypes and intermediate markers of disease progression. We used baseline data from 2771 ever-smokers from the SPIROMICS cohort to identify associations between percent predicted FEF25%-75% (%predFEF25%-75%) and both clinical markers and computed tomography (CT) findings of smoking-related lung disease. RESULTS: Lower %predFEF25-75% was associated with more severe disease, manifested radiographically by increased functional small airways disease, emphysema (most notably with homogeneous distribution), CT-measured residual volume, total lung capacity (TLC), and airway wall thickness, and clinically by increased symptoms, decreased 6-minute walk distance, and increased bronchodilator responsiveness (BDR). A lower %predFEF25-75% remained significantly associated with increased emphysema, functional small airways disease, TLC, and BDR after adjustment for FEV1 or forced vital capacity (FVC). INTERPRETATION: The %predFEF25-75% provides additional information about disease manifestation beyond FEV1. These associations may reflect loss of elastic recoil and air trapping from emphysema and intrinsic small airways disease. Thus, %predFEF25-75% helps link the anatomic pathology and deranged physiology of COPD.

Cxcl10 Chemokine Induces Migration of ING4-Deficient Breast Cancer Cells via a Novel Cross Talk Mechanism between the Cxcr3 and Egfr Receptors.

The chemokine Cxcl10 has been associated with poor prognosis in breast cancer, but the mechanism is not well understood. Our previous study has shown that CXCL10 was repressed by the ING4 tumor suppressor, suggesting a potential inverse functional relationship. We thus investigated a role for Cxcl10 in the context of ING4 deficiencies in breast cancer. We first analyzed public gene expression data sets and found that patients with CXCL10-high/ING4-low expressing tumors had significantly reduced disease-free survival in breast cancer. In vitro, Cxcl10 induced migration of ING4-deleted breast cancer cells but not of ING4-intact cells. Using inhibitors, we found that Cxcl10-induced migration of ING4-deleted cells required Cxcr3, Egfr, and the Gßγ subunits downstream of Cxcr3 but not Gαi. Immunofluorescent imaging showed that Cxcl10 induced early transient colocalization between Cxcr3 and Egfr in both ING4-intact and ING4-deleted cells, which recurred only in ING4-deleted cells. A peptide agent that binds to the internal juxtamembrane domain of Egfr inhibited Cxcr3/Egfr colocalization and cell migration. Taken together, these results presented a novel mechanism of Cxcl10 that elicits migration of ING4-deleted cells, in part by inducing a physical or proximal association between Cxcr3 and Egfr and signaling downstream via Gßγ. These results further indicated that ING4 plays a critical role in the regulation of Cxcl10 signaling that enables breast cancer progression.

Saturation recovery-prepared magnetic resonance angiography for assessment of left atrial and esophageal anatomy.

OBJECTIVES: Magnetic resonance angiography (MRA) has been established as an important imaging method in cardiac ablation procedures. In pulmonary vein (PV) isolation procedures, MRA has the potential to minimize the risk of severe complications, such as atrio-esophageal fistula, by providing detailed information on esophageal position relatively to cardiac structures. However, traditional non-gated, first-pass (FP) MRA approaches have several limitations, such as long breath-holds, non-uniform signal intensity throughout the left atrium (LA), and poor esophageal visualization. The aim of this observational study was to validate a respiratory-navigated, ECG-gated (EC), saturation recovery-prepared MRA technique for simultaneous imaging of LA, LA appendage, PVs, esophagus, and adjacent anatomical structures. METHODS: Before PVI, 106 consecutive patients with a history of AF underwent either conventional FP-MRA (n = 53 patients) or our new EC-MRA (n = 53 patients). Five quality scores (QS) of LA and esophagus visibility were assessed by two experienced readers. The non-parametric Mann-Whitney U-test was used to compare QS between FP-MRA and EC-MRA groups, and linear regression was applied to assess clinical contributors to image quality. RESULTS: EC-MRA demonstrated significantly better image quality than FP-MRA in every quality category. Esophageal visibility using the new MRA technique was markedly better than with the conventional FP-MRA technique (median 3.5 [IQR 1] vs median 1.0, p < 0.001). In contrast to FP-MRA, overall image quality of EC-MRA was not influenced by heart rate. CONCLUSION: Our ECG-gated, respiratory-navigated, saturation recovery-prepared MRA technique provides significantly better image quality and esophageal visibility than the established non-gated, breath-holding FP-MRA. Image quality of EC-MRA technique has the additional advantage of being unaffected by heart rate. ADVANCES IN KNOWLEDGE: Detailed information of cardiac anatomy has the potential to minimize the risk of severe complications and improve success rates in invasive electrophysiological studies. Our novel ECG-gated, respiratory-navigated, saturation recovery-prepared MRA technique provides significantly better image quality of LA and esophageal structures than the traditional first-pass algorithm. This new MRA technique is robust to arrhythmia (tachycardic, irregular heart rates) frequently observed in AF patients.

Mucus Plugs and Emphysema in the Pathophysiology of Airflow Obstruction and Hypoxemia in Smokers.

Rationale: The relative roles of mucus plugs and emphysema in mechanisms of airflow limitation and hypoxemia in smokers with chronic obstructive pulmonary disease (COPD) are uncertain.Objectives: To relate image-based measures of mucus plugs and emphysema to measures of airflow obstruction and oxygenation in patients with COPD.Methods: We analyzed computed tomographic (CT) lung images and lung function in participants in the Subpopulations and Intermediate Outcome Measures in COPD Study. Radiologists scored mucus plugs on CT lung images, and imaging software automatically quantified emphysema percentage. Unadjusted and adjusted relationships between mucus plug score, emphysema percentage, and lung function were determined using regression.Measurements and Main Results: Among 400 smokers, 229 (57%) had mucus plugs and 207 (52%) had emphysema, and subgroups could be identified with mucus-dominant and emphysema-dominant disease. Only 33% of smokers with high mucus plug scores had mucus symptoms. Mucus plug score and emphysema percentage were independently associated with lower values for FEV1 and peripheral oxygen saturation (P < 0.001). The relationships between mucus plug score and lung function outcomes were strongest in smokers with limited emphysema (P < 0.001). Compared with smokers with low mucus plug scores, those with high scores had worse COPD Assessment Test scores (17.4 ± 7.7 vs. 14.4 ± 13.3), more frequent annual exacerbations (0.75 ± 1.1 vs. 0.43 ± 0.85), and shorter 6-minute-walk distance (329 ± 115 vs. 392 ± 117 m) (P < 0.001).Conclusions: Symptomatically silent mucus plugs are highly prevalent in smokers and independently associate with lung function outcomes. These data provide rationale for targeting patients with mucus-high/emphysema-low COPD in clinical trials of mucoactive treatments.Clinical trial registered with www.clinicaltrials.gov (NCT01969344).

Clinical, Bronchoscopic, and Imaging Findings of e-Cigarette, or Vaping, Product Use-Associated Lung Injury Among Patients Treated at an Academic Medical Center.

Importance: e-Cigarette, or vaping, product use-associated lung injury (EVALI) has caused more than 2800 illnesses and 68 deaths in the United States. Better characterization of this novel illness is needed to inform diagnosis and management. Objective: To describe the clinical features, bronchoscopic findings, imaging patterns, and outcomes of EVALI. Design, Setting, and Participants: This case series of 31 adult patients diagnosed with EVALI between June 24 and December 10, 2019, took place at an academic medical center in Salt Lake City, Utah. Exposures: e-Cigarette use, also known as vaping. Main Outcomes and Measures: Symptoms, laboratory findings, bronchoscopic results, imaging patterns, and clinical outcomes. Results: Data from 31 patients (median [interquartile range] age, 24 [21-31] years) were included in the study. Patients were primarily men (24 [77%]) and White individuals (27 [87%]) who used e-cigarette products containing tetrahydrocannabinol (THC) (29 [94%]). Patients presented with respiratory (30 [97%]), constitutional (28 [90%]), and gastrointestinal (28 [90%]) symptoms. Serum inflammatory markers were elevated in all patients. Bronchoscopy was performed in 23 of 28 inpatients (82%) and bronchoalveolar lavage (BAL) revealed the presence of lipid-laden macrophages (LLMs) in 22 of 24 cases (91%). BAL samples tested positive for Pneumocystis jirovecii (3 patients [13%]), rhinovirus (2 patients [8%]), human metapneumovirus and Aspergillus (1 patient each [4%]); all except human metapneumovirus were determined to be false-positives or clinically inconsequential. The exclusive or dominant computed tomography (CT) pattern was organizing pneumonia in 23 of 26 cases (89%). Patients received antibiotics (26 [84%]) and corticosteroids (24 [77%]), and all survived; 20 patients (65%) seen in follow-up showed marked improvement, but residual symptoms (13 [65%]), radiographic opacities (8 [40%]), and abnormal pulmonary function tests (8 of 18 [44%]) were common. Conclusions and Relevance: In this case series, patients with EVALI characteristically presented with a flu-like illness with elevated inflammatory markers, LLMs on BAL samples, and an organizing pneumonia pattern on CT imaging. Bronchoscopic testing for infection had a high incidence of false-positive results. Patients had substantial residual abnormal results at early follow-up. These data suggest a limited role for bronchoscopy in typical presentations of EVALI without risk factors for alternative diagnoses and the need for careful longitudinal follow-up.

Reproducibility of clinical late gadolinium enhancement magnetic resonance imaging in detecting left atrial scar after atrial fibrillation ablation.

INTRODUCTION: Late gadolinium enhancement (LGE) cardiac magnetic resonance imaging (MRI) can be used to detect postablation atrial scar (PAAS) but its reproducibility and reliability in clinical scans across different magnetic flux densities and scar detection methods are unknown. METHODS: Patients (n = 45) having undergone two consecutive MRIs (3 months apart) on 3T and 1.5T scanners were studied. We compared PAAS detection reproducibility using four methods of thresholding: simple thresholding, Otsu thresholding, 3.3 standard deviations (SD) above blood pool (BP) mean intensity, and image intensity ratio (IIR). We performed a texture study by dividing the left atrial wall intensity histogram into deciles and evaluated the correlation of the same decile of the two scans as well as to a randomized distribution of intensities, quantified using Dice Similarity Coefficient (DSC). RESULTS: The choice of scanner did not significantly affect the reproducibility. The scar detection performed by Otsu thresholding (DSC of 71.26 ± 8.34) resulted in a better correlation of the two scans compared with the methods of 3.3 SD above BP mean intensity (DSC of 57.78 ± 21.2, p < .001) and IIR above 1.61 (DSC of 45.76 ± 29.55, p <.001). Texture analysis showed that correlation only for voxels with intensities in deciles above the 70th percentile of wall intensity histogram was better than random distribution (p < .001). CONCLUSIONS: Our results demonstrate that clinical LGE-MRI can be reliably used for visualizing PAAS across different magnetic flux densities if the threshold is greater than 70th percentile of the wall intensity distribution. Also, atrial wall-based thresholding is better than BP-based thresholding for reproducible PAAS detection.