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Tobacco smoking is the leading cause of preventable deaths in the United States. Beyond the risks of cardiovascular disease and several cancers, smoking contributes to lung inflammation, lung destruction, and smoking-related interstitial lung diseases (SRILD). SRILD describes a broad range of conditions that includes respiratory bronchiolitis, respiratory bronchiolitis-associated interstitial lung disease, desquamative interstitial pneumonia, pulmonary Langerhans cell histiocytosis, acute eosinophilic pneumonia, idiopathic pulmonary fibrosis, combined pulmonary fibrosis and emphysema, interstitial lung abnormality, and smoking-related interstitial fibrosis.Computed tomography (CT) is central to the diagnosis and understanding of clinicopathologic manifestations of smoking-related lung injury. Common features of SRILD on CT include low-attenuation areas, ground-glass opacities, fibrosis, and lung nodules. Although the various SRILDs are often described as distinct entities, they may manifest with nonspecific features or exhibit mixed patterns and may more accurately be described as a continuum of pathology. Understanding the broad range of radiologic features and recognizing the potential coexistence and overlap of disease processes is essential to maintaining an appropriate differential diagnosis. In this article, we review the radiologic findings associated with SRILDs with a focus on diagnostic considerations and challenges when interpreting CT images.

CT is crucial for diagnosing chest diseases, with image quality affected by spatial resolution. Thick-slice CT remains prevalent in practice due to cost considerations, yet its coarse spatial resolution may hinder accurate diagnoses. Our multicenter study develops a deep learning synthetic model with Convolutional-Transformer hybrid encoder-decoder architecture for generating thin-slice CT from thick-slice CT on a single center (1576 participants) and access the synthetic CT on three cross-regional centers (1228 participants). The qualitative image quality of synthetic and real thin-slice CT is comparable (p = 0.16). Four radiologists accuracy in diagnosing community-acquired pneumonia using synthetic thin-slice CT surpasses thick-slice CT (p  0.99). For lung nodule detection, sensitivity with thin-slice CT outperforms thick-slice CT (p  0.05). These findings indicate the potential of our model to generate high-quality synthetic thin-slice CT as a practical alternative when real thin-slice CT is preferred but unavailable.

Standard of care echocardiography can have limited diagnostic accuracy in certain cases of fetal congenital heart disease. Prenatal cardiovascular magnetic resonance (CMR) imaging has potential to provide additional anatomic imaging information, including excellent soft tissue images in multiple planes, improving prenatal diagnostics and in utero hemodynamic assessment. We conducted a literature review of fetal CMR, including its development and implementation into clinical practice, and compiled and analyzed the results. Our findings included the fact that technological and innovative approaches are required to overcome some of the challenges in fetal CMR, in part due to the dynamic nature of the fetal heart. A number of reconstruction algorithms and cardiac gating strategies have been developed over time to improve fetal CMR image quality, allowing unique investigations into fetal hemodynamics, oxygenation, and growth. Studies demonstrate that incorporating CMR in the prenatal arena influences postnatal clinical management. With further refinement and experience, fetal CMR in congenital heart disease continues to evolve and demonstrate ongoing potential as a complementary imaging modality to fetal echocardiography in the care of these patients.

A greater understanding of molecular, cellular, and immunological changes during the early stages of lung adenocarcinoma development could improve diagnostic and therapeutic approaches in patients with pulmonary nodules at risk for lung cancer. To elucidate the immunopathogenesis of early lung tumorigenesis, we evaluated surgically resected pulmonary nodules representing the spectrum of early lung adenocarcinoma as well as associated normal lung tissues using single-cell RNA sequencing and validated the results by flow cytometry and multiplex immunofluorescence (MIF). Single-cell transcriptomics revealed a significant decrease in gene expression associated with cytolytic activities of tumor-infiltrating natural killer and natural killer T cells. This was accompanied by a reduction in effector T cells and an increase of CD4+ regulatory T cells (Treg) in subsolid nodules. An independent set of resected pulmonary nodules consisting of both adenocarcinomas and associated premalignant lesions corroborated the early increment of Tregs in premalignant lesions compared with the associated normal lung tissues by MIF. Gene expression analysis indicated that cancer-associated alveolar type 2 cells and fibroblasts may contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid nodules through ligand-receptor interactions. These findings suggest that there is a suppression of immune surveillance across the spectrum of early-stage lung adenocarcinoma.SignificanceAnalysis of a spectrum of subsolid pulmonary nodules by single-cell RNA sequencing provides insights into the immune regulation and cell-cell interactions in the tumor microenvironment during early lung tumor development.

The implementation of low-dose chest CT for lung screening presents a crucial opportunity to advance lung cancer care through early detection and interception. In addition, millions of pulmonary nodules are incidentally detected annually in the United States, increasing the opportunity for early lung cancer diagnosis. Yet, realization of the full potential of these opportunities is dependent on the ability to accurately analyze image data for purposes of nodule classification and early lung cancer characterization. This review presents an overview of traditional image analysis approaches in chest CT using semantic characterization as well as more recent advances in the technology and application of machine learning models using CT-derived radiomic features and deep learning architectures to characterize lung nodules and early cancers. Methodological challenges currently faced in translating these decision aids to clinical practice, as well as the technical obstacles of heterogeneous imaging parameters, optimal feature selection, choice of model, and the need for well-annotated image data sets for the purposes of training and validation, will be reviewed, with a view toward the ultimate incorporation of these potentially powerful decision aids into routine clinical practice.

Vascular imaging can be challenging because of the wide variability of contrast dynamics in different vascular territories and potential safety concerns in patients with renal insufficiency or allergies. Off-label diagnostic use of ferumoxytol, a superparamagnetic iron nanoparticle approved for therapy, is a promising alternative to gadolinium-based contrast agents for MR angiography (MRA). Ferumoxytol has exhibited a reassuring safety profile when used within the dose range recommended for diagnostic imaging. Because of its prolonged and stable intravascular residence, ferumoxytol can be used in its steady-state distribution for a wide variety of imaging indications, including some where conventional MRA is unreliable. In this article, authors discuss some of the major vascular applications of ferumoxytol and highlight how it may be used to provide highly diagnostic images and improve the quality, workflow, and reliability of vascular imaging. Keywords: MR Angiography, MRI Contrast Agent, Cardiac, Vascular © RSNA, 2022.

Cardiac magnetic resonance imaging and angiography have a crucial role in the diagnostic evaluation and follow up of pediatric and adult patients with congenital heart disease. Although much of the information required of advanced imaging studies can be provided by standard gadolinium-enhanced magnetic resonance imaging, the limitations of precise bolus timing, long scan duration, complex imaging protocols, and the need to image small structures limit more widespread use of this modality. Recent experience with off-label diagnostic use of ferumoxytol has helped to mitigate some of these barriers. Approved by the U.S. FDA for intravenous treatment of anemia, ferumoxytol is an ultrasmall superparamagnetic iron oxide nanoparticle that has a long blood pool residence time and high relaxivity. Once metabolized by macrophages, the iron core is incorporated into the reticuloendothelial system. In this work, we aim to summarize the evolution of ferumoxytol-enhanced cardiovascular magnetic resonance imaging and angiography and highlight its many applications for congenital heart disease.

Lung cancer screening (LCS) is effective in reducing mortality, particularly when patients adhere to follow-up recommendations standardized by the Lung CT Screening Reporting & Data System (Lung-RADS). Nevertheless, patient adherence to recommended intervals varies, potentially diminishing benefit from screening. We conducted a systematic review and meta-analysis of patient adherence to Lung-RADS-recommended screening intervals. We systematically searched MEDLINE, EMBASE, Web of Science, the Cochrane Central Register of Controlled Trials, and major radiology and oncology conference archives between April 28, 2014, and December 17, 2020. Eligible studies mentioned patient adherence to the recommendations of Lung-RADS. The review protocol was registered with PROSPERO (CRD42020189326). We identified 24 eligible studies for qualitative summary, of which 21 were suitable for meta-analysis. The pooled adherence rate was 57% (95% confidence interval: 46%-69%) for defined adherence (e.g., an annual incidence screen was performed within 15 mo) among 6689 patients and 65% (95% confidence interval: 55%-75%) for anytime adherence among 5085 patients. Large heterogeneity in adherence rates between studies was observed (I2 = 99% for defined adherence, I2 = 98% for anytime adherence). Heterogeneous adherence rates were associated with Lung-RADS scores, with significantly higher adherence rates among Lung-RADS 3 to 4 than Lung-RADS 1 to 2 (p < 0.05). Patient adherence to Lung-RADS-recommended screening intervals is suboptimal across clinical LCS programs in the United States, especially among patients with results of Lung-RADS categories 1 to 2. To improve adherence rates, future research may focus on implementing tailored interventions after identifying barriers to LCS. We also propose a minimum standardized set of data elements for future pooled analyses of LCS adherence on the basis of our findings.

BackgroundRandomized controlled trials (RCT) play a central role in evidence-based healthcare. However, the clinical and policy implications of implementing RCTs in clinical practice are difficult to predict as the studied population is often different from the target population where results are being applied. This study illustrates the concepts of generalizability and transportability, demonstrating their utility in interpreting results from the National Lung Screening Trial (NLST).MethodsUsing inverse-odds weighting, we demonstrate how generalizability and transportability techniques can be used to extrapolate treatment effect from (i) a subset of NLST to the entire NLST population and from (ii) the entire NLST to different target populations.ResultsOur generalizability analysis revealed that lung cancer mortality reduction by LDCT screening across the entire NLST [16% (95% confidence interval [CI]: 4-24)] could have been estimated using a smaller subset of NLST participants. Using transportability analysis, we showed that populations with a higher prevalence of females and current smokers had a greater reduction in lung cancer mortality with LDCT screening [e.g., 27% (95% CI, 11-37) for the population with 80% females and 80% current smokers] than those with lower prevalence of females and current smokers.ConclusionsThis article illustrates how generalizability and transportability methods extend estimation of RCTs' utility beyond trial participants, to external populations of interest, including those that more closely mirror real-world populations.ImpactGeneralizability and transportability approaches can be used to quantify treatment effects for populations of interest, which may be used to design future trials or adjust lung cancer screening eligibility criteria.

BackgroundClinical management of boys with Duchenne muscular dystrophy (DMD) relies on in-depth understanding of cardiac involvement, but right ventricular (RV) structural and functional remodeling remains understudied.PurposeTo evaluate several analysis methods and identify the most reliable one to measure RV pre- and postcontrast T1 (RV-T1) and to characterize myocardial remodeling in the RV of boys with DMD.Study typeProspective.PopulationBoys with DMD (N = 27) and age-/sex-matched healthy controls (N = 17) from two sites.Field strength/sequence3.0 T using balanced steady state free precession, motion-corrected phase sensitive inversion recovery and modified Look-Locker inversion recovery sequences.AssessmentBiventricular mass (Mi), end-diastolic volume (EDVi) and ejection fraction (EF) assessment, tricuspid annular excursion (TAE), late gadolinium enhancement (LGE), pre- and postcontrast myocardial T1 maps. The RV-T1 reliability was assessed by three observers in four different RV regions of interest (ROI) using intraclass correlation (ICC).Statistical testsThe Wilcoxon rank sum test was used to compare RV-T1 differences between DMD boys with negative LGE(-) or positive LGE(+) and healthy controls. Additionally, correlation of precontrast RV-T1 with functional measures was performed. A P-value  0.91) for assessing RV-T1. Precontrast RV-T1 was significantly higher in boys with DMD compared to controls. Both LGE(-) and LGE(+) boys had significantly elevated precontrast RV-T1 compared to controls (1543 [1489-1597] msec and 1550 [1402-1699] msec vs. 1436 [1399-1473] msec, respectively). Compared to healthy controls, boys with DMD had preserved RVEF (51.8 [9.9]% vs. 54.2 [7.2]%, P = 0.31) and significantly reduced RVMi (29.8 [9.7] g vs. 48.0 [15.7] g), RVEDVi (69.8 [29.7] mL/m2 vs. 89.1 [21.9] mL/m2 ), and TAE (22.0 [3.2] cm vs. 26.0 [4.7] cm). Significant correlations were found between precontrast RV-T1 and RVEF (β = -0.48%/msec) and between LV-T1 and LVEF (β = -0.51%/msec).Data conclusionPrecontrast RV-T1 is elevated in boys with DMD compared to healthy controls and is negatively correlated with RVEF.Level of evidence1 TECHNICAL EFFICACY: Stage 2.

PurposeDevelop a novel three-dimensional (3D) generative adversarial network (GAN)-based technique for simultaneous image reconstruction and respiratory motion compensation of 4D MRI. Our goal was to enable high-acceleration factors 10.7X-15.8X, while maintaining robust and diagnostic image quality superior to state-of-the-art self-gating (SG) compressed sensing wavelet (CS-WV) reconstruction at lower acceleration factors 3.5X-7.9X.MethodsOur GAN was trained based on pixel-wise content loss functions, adversarial loss function, and a novel data-driven temporal aware loss function to maintain anatomical accuracy and temporal coherence. Besides image reconstruction, our network also performs respiratory motion compensation for free-breathing scans. A novel progressive growing-based strategy was adapted to make the training process possible for the proposed GAN-based structure. The proposed method was developed and thoroughly evaluated qualitatively and quantitatively based on 3D cardiac cine data from 42 patients.ResultsOur proposed method achieved significantly better scores in general image quality and image artifacts at 10.7X-15.8X acceleration than the SG CS-WV approach at 3.5X-7.9X acceleration (4.53 ± 0.540 vs. 3.13 ± 0.681 for general image quality, 4.12 ± 0.429 vs. 2.97 ± 0.434 for image artifacts, P < .05 for both). No spurious anatomical structures were observed in our images. The proposed method enabled similar cardiac-function quantification as conventional SG CS-WV. The proposed method achieved faster central processing unit-based image reconstruction (6 s/cardiac phase) than the SG CS-WV (312 s/cardiac phase).ConclusionThe proposed method showed promising potential for high-resolution (1 mm3 ) free-breathing 4D MR data acquisition with simultaneous respiratory motion compensation and fast reconstruction time.

PurposeStandard balanced SSFP (bSSFP) cine MRI often suffers from blood outflow artifacts. We propose a method that spatially encodes these outflowing spins to reduce their effects in the intended slice.MethodsBloch simulations were performed to characterize through-plane flow and to investigate how the use of phase encoding along the slice select's direction ("slice encoding") could alleviate its issues. Phantom scans and in vivo cines were acquired on a 3T system, comparing the standard 2D acquisition to the proposed slice-encoding method. Nineteen healthy volunteers were recruited for short-axis and horizontal long-axis oriented scans. An expert radiologist evaluated each slice-encoded/standard cine pairs in a rank comparison test and graded their quality on a 1-5 scale. The grades were used for a nonparametric paired evaluation for independent samples with a null hypothesis that there was no statistical difference between the two quality-grade distributions for α = 0.05 significance.ResultsBloch simulation results demonstrated this technique's feasibility, showing a fully resolved slice profile given a sufficient number of slice encodes. These results were confirmed with the phantom experiments. Each in vivo slice-encoded cine had a higher quality than its corresponding standard acquisition. The nonparametric paired evaluation came to 0.01 significance, encouraging us to reject the null hypothesis and conclude that slice-encoding effectively works in reducing outflow effects.ConclusionThe slice-encoding balanced SSFP technique is helpful in mitigating outflow effects and is achievable within a single breath hold, being a useful alternative for cases in which the flow artifacts are significant.

Cardiac aspergillomas are rare and associated with high mortality. We present a case of right ventricular cardiac aspergilloma in an asymptomatic renal transplant recipient. Intracavitary aspergilloma is an important consideration in evaluation of an intracardiac mass in an immunocompromised patient. (Level of Difficulty: Advanced.).

The aim of this study was to develop a deep neural network for respiratory motion compensation in free-breathing cine MRI and evaluate its performance. An adversarial autoencoder network was trained using unpaired training data from healthy volunteers and patients who underwent clinically indicated cardiac MRI examinations. A U-net structure was used for the encoder and decoder parts of the network and the code space was regularized by an adversarial objective. The autoencoder learns the identity map for the free-breathing motion-corrupted images and preserves the structural content of the images, while the discriminator, which interacts with the output of the encoder, forces the encoder to remove motion artifacts. The network was first evaluated based on data that were artificially corrupted with simulated rigid motion with regard to motion-correction accuracy and the presence of any artificially created structures. Subsequently, to demonstrate the feasibility of the proposed approach in vivo, our network was trained on respiratory motion-corrupted images in an unpaired manner and was tested on volunteer and patient data. In the simulation study, mean structural similarity index scores for the synthesized motion-corrupted images and motion-corrected images were 0.76 and 0.93 (out of 1), respectively. The proposed method increased the Tenengrad focus measure of the motion-corrupted images by 12% in the simulation study and by 7% in the in vivo study. The average overall subjective image quality scores for the motion-corrupted images, motion-corrected images and breath-held images were 2.5, 3.5 and 4.1 (out of 5.0), respectively. Nonparametric-paired comparisons showed that there was significant difference between the image quality scores of the motion-corrupted and breath-held images (P < .05); however, after correction there was no significant difference between the image quality scores of the motion-corrected and breath-held images. This feasibility study demonstrates the potential of an adversarial autoencoder network for correcting respiratory motion-related image artifacts without requiring paired data.

BackgroundCardiovascular disease is the leading cause of death in patients with Duchenne muscular dystrophy (DMD)-a fatal X-linked genetic disorder. Late gadolinium enhancement (LGE) imaging is the current gold standard for detecting myocardial tissue remodeling, but it is often a late finding. Current research aims to investigate cardiovascular magnetic resonance (CMR) biomarkers, including native (pre-contrast) T1 and extracellular volume (ECV) to evaluate the early on-set of microstructural remodeling and to grade disease severity. To date, native T1 measurements in DMD have been reported predominantly at 1.5T. This study uses 3T CMR: (1) to characterize global and regional myocardial pre-contrast T1 differences between healthy controls and LGE + and LGE- boys with DMD; and (2) to report global and regional myocardial post-contrast T1 values and myocardial ECV estimates in boys with DMD, and (3) to identify left ventricular (LV) T1-mapping biomarkers capable of distinguishing between healthy controls and boys with DMD and detecting LGE status in DMD.MethodsBoys with DMD (N = 28, 13.2 ± 3.1 years) and healthy age-matched boys (N = 20, 13.4 ± 3.1 years) were prospectively enrolled and underwent a 3T CMR exam including standard functional imaging and T1 mapping using a modified Look-Locker inversion recovery (MOLLI) sequence. Pre-contrast T1 mapping was performed on all boys, but contrast was administered only to boys with DMD for post-contrast T1 and ECV mapping. Global and segmental myocardial regions of interest were contoured on mid LV T1 and ECV maps. ROI measurements were compared for pre-contrast myocardial T1 between boys with DMD and healthy controls, and for post-contrast myocardial T1 and ECV between LGE + and LGE- boys with DMD using a Wilcoxon rank-sum test. Results are reported as median and interquartile range (IQR). p-Values

Hereditary hemorrhagic telangiectasia (HHT) is an autosomal dominant disorder characterized by the development of arteriovenous malformations. The arteriovenous shunts may result in high output heart failure, which predisposes to atrial dilatation and atrial fibrillation. Due to recurrent bleeding from epistaxis or the gastrointestinal tract, patients with HHT and atrial fibrillation are at high risk of bleeding if anticoagulated for stroke prevention. In this report, we present a case of a 74-year-old woman with a history of HHT and atrial fibrillation who developed a large left atrial thrombus that initially was thought to represent an atrial myxoma. The diagnosis was confirmed with cardiac magnetic resonance imaging, and the patient underwent surgical resection of the thrombus. This case demonstrates the role of different imaging modalities in the assessment of left atrial masses and presents an opportunity to review the data on safety of anticoagulation in patients with HHT.