Faculty Bibliography

RATIONALE AND OBJECTIVES/OBJECTIVE:To determine factors influencing low-field MRI lung opacity severity 6-24 months after acute Covid-19 pneumonia. MATERIALS AND METHODS/METHODS:104 post-acute Covid-19 patients with 167 MRI exams were included. 32 patients had more than one exam, and 63 exams were serial exams. Pulmonary findings were graded on a scale of 0-4 by quadrant, total score ranging from 0 (no opacity) to 16 (opacity > 75%), and score >8 considered moderate and >12 severe opacity. Kruskal-Wallis, Mann-Whitney, and Spearman rank correlation was used to assess the association of clinical and demographic factors with MR opacity severity at time intervals from acute infection. Random coefficients regression was used to assess whether opacity score changed over time. RESULTS:Severity of initial illness was associated with increased MR opacity score at timeframes up to 24 months (p < .05). Among the 167 exams, moderate to severe MR opacities (total opacity score >8) were identified in 33% of exams beyond 6 months: 37% at 6 - <12 months (n = 23/63); 31% at 12- < 18 months (n = 13/42); 25% at 18- < 24 months (n = 6/24); and 50% at > 24 months (n = 3/6). No significant change in total opacity score over time was identified by random coefficients regression. Among the 32 patients with serial exams, 11 demonstrated no change in opacity score from initial to final exam, 10 decrease in score (mean 2.3, stdev 1.25, range 1-4), and 11 increase in score (average 2.8, stdev 1.48, range 1-7). CONCLUSION/CONCLUSIONS:Initial Covid-19 disease severity was associated with increased MRI total opacity score at time intervals up to 24 months, and moderate to severe opacities were commonly identified by low-field MRI beyond 6 months from acute illness.

BACKGROUND:Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. PURPOSE/OBJECTIVE:To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. STUDY TYPE/METHODS:Prospective analysis of retrospectively acquired data. SUBJECTS/METHODS:A total of 37 postacute Covid-19 patients (25 male; median [interquartile range (IQR)] age: 58 [42-64] years; median [IQR] days from acute infection: 335 [186-449]). FIELD STRENGTH/SEQUENCE/UNASSIGNED:0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. ASSESSMENT/RESULTS:Patients were stratified into three groups based on presence of no (N = 11), 1 (N = 14), or ≥2 (N = 14) cardiopulmonary symptoms, assessed using a standardized symptom inventory within 1 month of MRI. An automated lung postprocessing workflow segmented each lung in each trueFISP image (temporal resolution 0.2 seconds) and respiratory curves were generated. Quantitative parameters were derived including tidal lung area, rates of inspiration and expiration, lung area coefficient of variability (CV), and respiratory incoherence (departure from sinusoidal pattern) were. Pulmonary function tests were recorded if within 1 month of MRI. Qualitative assessment of respiratory pattern and lung opacity was performed by three independent readers with 6, 9, and 23 years of experience. STATISTICAL TESTS/METHODS:Analysis of variance to assess differences in demographic, clinical, and quantitative MRI parameters among groups; univariable analysis and multinomial logistic regression modeling to determine features predictive of patient symptom status; Akaike information criterion to compare the quality of regression models; Cohen and Fleiss kappa (κ) to quantify inter-reader reliability. Two-sided 5% significance level was used. RESULTS:; CV: 0.072, 0.067, and 0.058). Respiratory incoherence was significantly higher in patients with two or more symptoms than in those with one or no symptoms (0.05 vs. 0.043 vs. 0.033). There were no significant differences in patient age (P = 0.19), sex (P = 0.88), lung opacity severity (P = 0.48), or pulmonary function tests (P = 0.35-0.97) among groups. Qualitative reader assessment did not distinguish between groups and showed slight inter-reader agreement (κ = 0.05-0.11). DATA CONCLUSION/CONCLUSIONS:Quantitative respiratory pattern measures derived from dynamic higher-temporal resolution MRI have potential to stratify patients by symptom burden in a postacute Covid-19 cohort. LEVEL OF EVIDENCE/METHODS:3 TECHNICAL EFFICACY: Stage 3.

PURPOSE/OBJECTIVE:To introduce an alternative idea for fat suppression that is suited both for low-field applications where conventional fat-suppression approaches become ineffective due to narrow spectral separation and for applications with strong B0 homogeneities. METHODS:Separation of fat and water is achieved by sweeping the frequency of RF saturation pulses during continuous radial acquisition and calculating frequency-resolved images using regularized iterative reconstruction. Voxel-wise signal-response curves are extracted that reflect tissue's response to RF saturation at different frequencies and allow the classification into fat or water. This information is then utilized to generate water-only composite images. The principle is demonstrated in free-breathing abdominal and neck examinations using stack-of-stars 3D balanced SSFP (bSSFP) and gradient-recalled echo (GRE) sequences at 0.55 and 3T. Moreover, a potential extension toward quantitative fat/water separation is described. RESULTS:Experiments with a proton density fat fraction (PDFF) phantom validated the reliability of fat/water separation using signal-response curves. As demonstrated for abdominal imaging at 0.55T, the approach resulted in more uniform fat suppression without loss of water signal and in improved CSF-to-fat signal ratio. Moreover, the approach provided consistent fat suppression in 3T neck exams where conventional spectrally-selective fat saturation failed due to strong local B0 inhomogeneities. The feasibility of simultaneous fat/water quantification has been demonstrated in a PDFF phantom. CONCLUSION/CONCLUSIONS:The proposed principle achieves reliable fat suppression in low-field applications and adapts to high-field applications with strong B0 inhomogeneity. Moreover, the principle potentially provides a basis for developing an alternative approach for PDFF quantification.

Creating a patient-centered experience is becoming increasingly important for radiology departments around the world. The goal of patient-centered radiology is to ensure that radiology services are sensitive to patients' needs and desires. This article provides a framework for addressing the patient's experience by dividing their imaging journey into three distinct time periods: pre-exam, day of exam, and post-exam. Each time period has aspects that can contribute to patient anxiety. Although there are components of the patient journey that are common in all regions of the world, there are also unique features that vary by location. This paper highlights innovative solutions from different parts of the world that have been introduced in each of these time periods to create a more patient-centered experience. CLINICAL RELEVANCE STATEMENT: Adopting innovative solutions that help patients understand their imaging journey and decrease their anxiety about undergoing an imaging examination are important steps in creating a patient centered imaging experience. KEY POINTS: • Patients often experience anxiety during their imaging journey and decreasing this anxiety is an important component of patient centered imaging. • The patient imaging journey can be divided into three distinct time periods: pre-exam, day of exam, and post-exam. • Although components of the imaging journey are common, there are local differences in different regions of the world that need to be considered when constructing a patient centered experience.

The fastMRI brain and knee dataset has enabled significant advances in exploring reconstruction methods for improving speed and image quality for Magnetic Resonance Imaging (MRI) via novel, clinically relevant reconstruction approaches. In this study, we describe the April 2023 expansion of the fastMRI dataset to include biparametric prostate MRI data acquired on a clinical population. The dataset consists of raw k-space and reconstructed images for T2-weighted and diffusion-weighted sequences along with slice-level labels that indicate the presence and grade of prostate cancer. As has been the case with fastMRI, increasing accessibility to raw prostate MRI data will further facilitate research in MR image reconstruction and evaluation with the larger goal of improving the utility of MRI for prostate cancer detection and evaluation. The dataset is available at https://fastmri.med.nyu.edu.

INTRODUCTION/BACKGROUND:Prostate cancer diffusion weighted imaging (DWI) MRI is typically performed at high-field strength (3.0 T) in order to overcome low signal-to-noise ratio (SNR). In this study, we demonstrate the feasibility of prostate DWI at low field enabled by random matrix theory (RMT)-based denoising, relying on the MP-PCA algorithm applied during image reconstruction from multiple coils. METHODS:Twenty-one volunteers and 2 prostate cancer patients were imaged with a 6-channel pelvic surface array coil and an 18-channel spine array on a prototype 0.55 T system created by ramping down a commercial magnetic resonance imaging system (1.5 T MAGNETOM Aera Siemens Healthcare) with 45 mT/m gradients and 200 T/m/s slew rate. Diffusion-weighted imagings were acquired with 4 non-collinear directions, for which b = 50 s/mm2 was used with 8 averages and b = 1000 s/mm2 with 40 averages; 2 extra b = 50 s/mm2 were used as part of the dynamic field correction. Standard and RMT-based reconstructions were applied on DWI over different ranges of averages. Accuracy/precision was evaluated using the apparent diffusion coefficient (ADC), and image quality was evaluated over 5 separate reconstructions by 3 radiologists with a 5-point Likert scale. For the 2 patients, we compare image quality and lesion visibility of the RMT reconstruction versus the standard one on 0.55 T and on clinical 3.0 T. RESULTS:The RMT-based reconstruction in this study reduces the noise floor by a factor of 5.8, thereby alleviating the bias on prostate ADC. Moreover, the precision of the ADC in prostate tissue after RMT increases over a range of 30%-130%, with the increase in both signal-to-noise ratio and precision being more prominent for a low number of averages. Raters found that the images were consistently of moderate to good overall quality (3-4 on the Likert scale). Moreover, they determined that b = 1000 s/mm2 images from a 1:55-minute scan with the RMT-based reconstruction were on par with the corresponding images from a 14:20-minute scan with standard reconstruction. Prostate cancer was visible on ADC and calculated b = 1500 images even with the abbreviated 1:55 scan reconstructed with RMT. CONCLUSIONS:Prostate imaging using DWI is feasible at low field and can be performed more rapidly with noninferior image quality compared with standard reconstruction.

Pancreatic cystic lesions are frequently identified on cross-sectional imaging. As many of these are presumed branch-duct intraductal papillary mucinous neoplasms, these lesions generate much anxiety for the patients and clinicians, often necessitating long-term follow-up imaging and even unnecessary surgical resections. However, the incidence of pancreatic cancer is overall low for patients with incidental pancreatic cystic lesions. Radiomics and deep learning are advanced tools of imaging analysis that have attracted much attention in addressing this unmet need, however, current publications on this topic show limited success and large-scale research is needed.

PURPOSE:Diffusion-weighted imaging (DWI) of the abdomen has increased dramatically for both research and clinical purposes. Motion and static field inhomogeneity related challenges limit image quality of abdominopelvic imaging with the most conventional echo-planar imaging (EPI) pulse sequence. While reversed phase encoded imaging is increasingly used to facilitate distortion correction, it typically assumes one motion independent magnetic field distribution. In this study, we describe a more generalized workflow for the case of kidney DWI in which the field inhomogeneity at multiple respiratory phases is mapped and used to correct all images in a multi-contrast DWI series. METHODS:In this HIPAA-compliant and IRB-approved prospective study, 8 volunteers (6 M, ages 28-51) had abdominal imaging performed in a 3 T MRI system (MAGNETOM Prisma; Siemens Healthcare, Erlangen, Germany) with ECG gating. Coronal oblique T2-weighted HASTE images were collected for anatomical reference. Sagittal phase-contrast (PC) MRI images through the left renal artery were collected to determine systolic and diastolic phases. Cardiac triggered oblique coronal DWI were collected at 10 b-values between 0 and 800 s/mm2 and 12 directions. DWI series were distortion corrected using field maps generated by forward and reversed phase encoded b = 0 images collected over the full respiratory cycle and matched by respiratory phase. Morphologic accuracy, intraseries spatial variability, and diffusion tensor imaging (DTI) metrics mean diffusivity (MD) and fractional anisotropy (FA) were compared for results generated with no distortion correction, correction with only one respiratory bin, and correction with multiple respiratory bins across the breathing cycle. RESULTS:Computed field maps showed significant variation in static field with kidney laterality, region, and respiratory phase. Distortion corrected images showed significantly better registration to morphologic images than uncorrected images; for the left kidney, the multiple bin correction outperformed one bin correction. Line profile analysis showed significantly reduced spatial variation with multiple bins than one bin correction. DTI metrics were mostly similar between correction methods, with some differences observed in MD between uncorrected and corrected datasets. CONCLUSIONS:Our results indicate improved morphology of kidney DWI and derived parametric maps as well as reduced variability over the full image series using the motion-resolved distortion correction. This work highlights some morphologic and quantitative metric improvements can be obtained for kidney DWI when distortion correction is performed in a respiratory-resolved manner.

PURPOSE/OBJECTIVE:-weighted radial stack-of-stars 3D gradient echo (GRE) sequence with comparable image quality to conventional MP-RAGE and to demonstrate how the radial acquisition scheme can be utilized for additional retrospective motion correction to improve robustness to head motion. METHODS:The proposed sequence, named MP-RAVE, has been derived from a previously described radial stack-of-stars 3D GRE sequence (RAVE) and includes a 180° inversion recovery pulse that is generated once for every stack of radial views. The sequence is combined with retrospective 3D motion correction to improve robustness. The effectiveness has been evaluated in phantoms and healthy volunteers and compared to conventional MP-RAGE acquisition. RESULTS:MP-RAGE and MP-RAVE anatomical images were rated "good" to "excellent" in overall image quality, with artifact level between "mild" and "no artifacts", and with no statistically significant difference between methods. During head motion, MP-RAVE showed higher inherent robustness with artifacts confined to local brain regions. In combination with motion correction, MP-RAVE provided noticeably improved image quality during different head motion and showed statistically significant improvement in image sharpness. CONCLUSION/CONCLUSIONS:MP-RAVE provides comparable image quality and contrast to conventional MP-RAGE with improved robustness to head motion. In combination with retrospective 3D motion correction, MP-RAVE can be a useful alternative to MP-RAGE, especially in non-cooperative or pediatric patients.