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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.

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.

Background The value of MRI in pediatric congenital heart disease (CHD) is well recognized; however, the requirement for expert oversight impedes its widespread use. Four-dimensional (4D) multiphase steady-state imaging with contrast enhancement (MUSIC) is a cardiovascular MRI technique that uses ferumoxytol and captures all anatomic features dynamically. Purpose To evaluate multicenter feasibility of 4D MUSIC MRI in pediatric CHD. Materials and Methods In this prospective study, participants with CHD underwent 4D MUSIC MRI at 3.0 T or 1.5 T between 2014 and 2020. From a pool of 460 total studies, an equal number of MRI studies from three sites (n = 60) was chosen for detailed analysis. With use of a five-point scale, the feasibility of 4D MUSIC was scored on the basis of artifacts, image quality, and diagnostic confidence for intracardiac and vascular connections (n = 780). Respiratory motion suppression was assessed by using the signal intensity profile. Bias between 4D MUSIC and two-dimensional (2D) cine imaging was evaluated by using Bland-Altman analysis; 4D MUSIC examination duration was compared with that of the local standard for CHD. Results A total of 206 participants with CHD underwent MRI at 3.0 T, and 254 participants underwent MRI at 1.5 T. Of the 60 MRI examinations chosen for analysis (20 per site; median participant age, 14.4 months [interquartile range, 2.3-49 months]; 33 female participants), 56 (93%) had good or excellent image quality scores across a spectrum of disease complexity (mean score ± standard deviation: 4.3 ± 0.6 for site 1, 4.9 ± 0.3 for site 2, and 4.6 ± 0.7 for site 3; P < .001). Artifact scores were inversely related to image quality (r = -0.88, P < .001) and respiratory motion suppression (P < .001, r = -0.45). Diagnostic confidence was high or definite in 730 of 780 (94%) intracardiac and vascular connections. The correlation between 4D MUSIC and 2D cine ventricular volumes and ejection fraction was high (range of r = 0.72-0.85; P < .001 for all). Compared with local standard MRI, 4D MUSIC reduced the image acquisition time (44 minutes ± 20 vs 12 minutes ± 3, respectively; P < .001). Conclusion Four-dimensional multiphase steady-state imaging with contrast enhancement MRI in pediatric congenital heart disease was feasible in a multicenter setting, shortened the examination time, and simplified the acquisition protocol, independently of disease complexity. Clinical trial registration no. NCT02752191 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Roest and Lamb in this issue.

Tracheobronchial masses encompass a broad spectrum of entities, ranging from benign and malignant neoplasms to infectious and inflammatory processes. This article reviews the cross-sectional findings of tracheal tumors and tumor-like entities, correlates imaging findings with histologic pathology, and discusses pearls and pitfalls in accurately diagnosing and classifying tracheal tumors and mimics.

Background: Balanced steady‐state free precession (bSSFP) imaging is commonly used in cardiac cine MRI but prone to image artifacts. Ferumoxytol‐enhanced (FE) gradient echo (GRE) has been proposed as an alternative. Utilizing the abundance of bSSFP images to develop a computationally efficient network that is applicable to FE GRE cine would benefit future network development. Purpose: To develop a variable‐splitting spatiotemporal network (VSNet) for image reconstruction, trained on bSSFP cine images and applicable to FE GRE cine images. Study Type: Retrospective and prospective. Subjects: 41 patients (26 female, 53 ± 19 y/o) for network training, 31 patients (19 female, 49 ± 17 y/o) and 5 healthy subjects (5 female, 30 ± 7 y/o) for testing. Field Strength/Sequence: 1.5T and 3T, bSSFP and GRE. Assessment: VSNet was compared to VSNet with total variation loss, compressed sensing and low rank methods for 14× accelerated data. The GRAPPA×2/×3 images served as the reference. Peak signal‐to‐noise‐ratio (PSNR), structural similarity index (SSIM), left ventricular (LV) and right ventricular (RV) end‐diastolic volume (EDV), end‐systolic volume (ESV), and ejection fraction (EF) were measured. Qualitative image ranking and scoring were independently performed by three readers. Latent scores were calculated based on scores of each method relative to the reference. Statistics: Linear mixed‐effects regression, Tukey method, Fleiss' Kappa, Bland–Altman analysis, and Bayesian categorical cumulative probit model. A P‐value <0.05 was considered statistically significant. Results: VSNet achieved significantly higher PSNR (32.7 ± 0.2), SSIM (0.880 ± 0.004), rank (2.14 ± 0.06), and latent scores (−1.72 ± 0.22) compared to other methods (rank >2.90, latent score < −2.63). Fleiss' Kappa was 0.52 for scoring and 0.61 for ranking. VSNet showed no significantly different LV and RV ESV (P = 0.938) and EF (P = 0.143) measurements, but statistically significant different (2.62 mL) EDV measurements compared to the reference. Conclusion: VSNet produced the highest image quality and the most accurate functional measurements for FE GRE cine images among the tested 14× accelerated reconstruction methods. Level of Evidence: 3 Technical Efficacy: Stage 1 [ABSTRACT FROM AUTHOR]

Purpose: To automate the segmentation of the peripheral arteries and veins in the lower extremities based on ferumoxytol‐enhanced MR angiography (FE‐MRA). Methods: Our automated pipeline has 2 sequential stages. In the first stage, we used a 3D U‐Net with local attention gates, which was trained based on a combination of the Focal Tversky loss with region mutual loss under a deep supervision mechanism to segment the vasculature from the high‐resolution FE‐MRA datasets. In the second stage, we used time‐resolved images to separate the arteries from the veins. Because the ultimate segmentation quality of the arteries and veins relies on the performance of the first stage, we thoroughly evaluated the different aspects of the segmentation network and compared its performance in blood vessel segmentation with currently accepted state‐of‐the‐art networks, including Volumetric‐Net, DeepVesselNet‐FCN, and Uception. Results: We achieved a competitive F1 = 0.8087 and recall = 0.8410 for blood vessel segmentation compared with F1 = (0.7604, 0.7573, 0.7651) and recall = (0.7791, 0.7570, 0.7774) obtained with Volumetric‐Net, DeepVesselNet‐FCN, and Uception. For the artery and vein separation stage, we achieved F1 = (0.8274/0.7863) in the calf region, which is the most challenging region in peripheral arteries and veins segmentation. Conclusion: Our pipeline is capable of fully automatic vessel segmentation based on FE‐MRA without need for human interaction in <4 min. This method improves upon manual segmentation by radiologists, which routinely takes several hours. [ABSTRACT FROM AUTHOR]