Quantitative Characterization of Respiratory Patterns on Dynamic Higher Temporal Resolution MRI to Stratify Postacute Covid-19 Patients by Cardiopulmonary Symptom Burden.

BACKGROUND: Postacute Covid-19 patients commonly present with respiratory symptoms; however, a noninvasive imaging method for quantitative characterization of respiratory patterns is lacking. PURPOSE: To evaluate if quantitative characterization of respiratory pattern on free-breathing higher temporal resolution MRI stratifies patients by cardiopulmonary symptom burden. STUDY TYPE: Prospective analysis of retrospectively acquired data. SUBJECTS: 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: 0.55 T/two-dimensional coronal true fast imaging with steady-state free precession (trueFISP) at higher temporal resolution. ASSESSMENT: 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: 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: Tidal area and lung area CV were significantly higher in patients with two or more symptoms than in those with one or no symptoms (area: 15.4 cm2 vs. 12.9 cm2 vs. 12.8 cm2 ; 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: 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: 3 TECHNICAL EFFICACY: Stage 3.

Prevalence of Adenopathy at Chest Computed Tomography After Vaccination for Severe Acute Respiratory Syndrome Coronavirus 2.

OBJECTIVE: This study aimed to determine the prevalence of axillary and subpectoral (SP) lymph nodes after ipsilateral COVID-19 vaccine administration on chest computed tomography (CT). METHODS: Subjects with chest CTs between 2 and 25 days after a first or second vaccine dose, December 15, 2020, to February 12, 2021, were included. Orthogonal measures of the largest axillary and SP nodes were recorded by 2 readers blinded to vaccine administration and clinical details. A mean nodal diameter discrepancy of ≥6 mm between contralateral stations was considered positive for asymmetry. Correlation with the side of vaccination, using a Spearman rank correlation, was performed on the full cohort and after excluding patients with diseases associated with adenopathy. RESULTS: Of the 138 subjects (81 women, 57 men; mean [SD] age, 74.4 ± 11.7 years), 48 (35%) had asymmetrically enlarged axillary and/or SP lymph nodes, 42 (30%) had ipsilateral, and 6 (4%) had contralateral to vaccination ( P = 0.003). Exclusion of 29 subjects with conditions associated with adenopathy showed almost identical correlation, with asymmetric nodes in 32 of 109 (29%) ipsilateral and in 5 of 109 (5%) contralateral to vaccination ( P = 0.002). CONCLUSIONS: Axillary and/or SP lymph nodes ipsilateral to vaccine administration represents a clinical conundrum. Asymmetric nodes were detected at CT in 30% of subjects overall and 29% of subjects without conditions associated with adenopathy, approximately double the prevalence rate reported to the Centers for Disease Control and Prevention by vaccine manufacturers. When interpreting examinations correlation with vaccine administration timing and site is important for pragmatic management.

Deep Learning Denoising of Low-Dose Computed Tomography Chest Images: A Quantitative and Qualitative Image Analysis.

PURPOSE: To assess deep learning denoised (DLD) computed tomography (CT) chest images at various low doses by both quantitative and qualitative perceptual image analysis. METHODS: Simulated noise was inserted into sinogram data from 32 chest CTs acquired at 100 mAs, generating anatomically registered images at 40, 20, 10, and 5 mAs. A DLD model was developed, with 23 scans selected for training, 5 for validation, and 4 for test.Quantitative analysis of perceptual image quality was assessed with Structural SIMilarity Index (SSIM) and Fréchet Inception Distance (FID). Four thoracic radiologists graded overall diagnostic image quality, image artifact, visibility of small structures, and lesion conspicuity. Noise-simulated and denoised image series were evaluated in comparison with one another, and in comparison with standard 100 mAs acquisition at the 4 mAs levels. Statistical tests were conducted at the 2-sided 5% significance level, with multiple comparison correction. RESULTS: At the same mAs levels, SSIM and FID between noise-simulated and reconstructed DLD images indicated that images were closer to a perfect match with increasing mAs (closer to 1 for SSIM, and 0 for FID).In comparing noise-simulated and DLD images to standard-dose 100-mAs images, DLD improved SSIM and FID. Deep learning denoising improved SSIM of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in SSIM from 0.91 to 0.94, 0.87 to 0.93, 0.67 to 0.87, and 0.54 to 0.84, respectively. Deep learning denoising improved FID of 40-, 20-, 10-, and 5-mAs simulations in comparison with standard-dose 100-mAs images, with change in FID from 20 to 13, 46 to 21, 104 to 41, and 148 to 69, respectively.Qualitative image analysis showed no significant difference in lesion conspicuity between DLD images at any mAs in comparison with 100-mAs images. Deep learning denoising images at 10 and 5 mAs were rated lower for overall diagnostic image quality ( P < 0.001), and at 5 mAs lower for overall image artifact and visibility of small structures ( P = 0.002), in comparison with 100 mAs. CONCLUSIONS: Deep learning denoising resulted in quantitative improvements in image quality. Qualitative assessment demonstrated DLD images at or less than 10 mAs to be rated inferior to standard-dose images.

Percutaneous Dilational Tracheostomy for Coronavirus Disease 2019 Patients Requiring Mechanical Ventilation.

OBJECTIVES: To assess the impact of percutaneous dilational tracheostomy in coronavirus disease 2019 patients requiring mechanical ventilation and the risk for healthcare providers. DESIGN: Prospective cohort study; patients were enrolled between March 11, and April 29, 2020. The date of final follow-up was July 30, 2020. We used a propensity score matching approach to compare outcomes. Study outcomes were formulated before data collection and analysis. SETTING: Critical care units at two large metropolitan hospitals in New York City. PATIENTS: Five-hundred forty-one patients with confirmed severe coronavirus disease 2019 respiratory failure requiring mechanical ventilation. INTERVENTIONS: Bedside percutaneous dilational tracheostomy with modified visualization and ventilation. MEASUREMENTS AND MAIN RESULTS: Required time for discontinuation off mechanical ventilation, total length of hospitalization, and overall patient survival. Of the 541 patients, 394 patients were eligible for a tracheostomy. One-hundred sixteen were early percutaneous dilational tracheostomies with median time of 9 days after initiation of mechanical ventilation (interquartile range, 7-12 d), whereas 89 were late percutaneous dilational tracheostomies with a median time of 19 days after initiation of mechanical ventilation (interquartile range, 16-24 d). Compared with patients with no tracheostomy, patients with an early percutaneous dilational tracheostomy had a higher probability of discontinuation from mechanical ventilation (absolute difference, 30%; p < 0.001; hazard ratio for successful discontinuation, 2.8; 95% CI, 1.34-5.84; p = 0.006) and a lower mortality (absolute difference, 34%, p < 0.001; hazard ratio for death, 0.11; 95% CI, 0.06-0.22; p < 0.001). Compared with patients with late percutaneous dilational tracheostomy, patients with early percutaneous dilational tracheostomy had higher discontinuation rates from mechanical ventilation (absolute difference 7%; p < 0.35; hazard ratio for successful discontinuation, 1.53; 95% CI, 1.01-2.3; p = 0.04) and had a shorter median duration of mechanical ventilation in survivors (absolute difference, -15 d; p < 0.001). None of the healthcare providers who performed all the percutaneous dilational tracheostomies procedures had clinical symptoms or any positive laboratory test for severe acute respiratory syndrome coronavirus 2 infection. CONCLUSIONS: In coronavirus disease 2019 patients on mechanical ventilation, an early modified percutaneous dilational tracheostomy was safe for patients and healthcare providers and associated with improved clinical outcomes.

Imaging Course of Lung Transplantation: From Patient Selection to Postoperative Complications.

Lung transplant is increasingly performed for the treatment of end-stage lung disease. As the number of lung transplants and transplant centers continues to rise, radiologists will more frequently participate in the care of patients undergoing lung transplant, both before and after transplant. Potential donors and recipients undergo chest radiography and CT as part of their pretransplant assessment to evaluate for contraindications to transplant and to aid in surgical planning. After transplant, recipients undergo imaging during the postoperative hospitalization and also in the long-term outpatient setting. Radiologists encounter a wide variety of conditions leading to end-stage lung disease and a myriad of posttransplant complications, some of which are unique to lung transplantation. Familiarity with these pathologic conditions, including their imaging findings and their temporal relationship to the transplant, is crucial to accurate radiologic interpretation. Knowledge of the surgical techniques and expected postoperative appearance prevents confusing normal posttransplant imaging findings with complications. A basic understanding of the indications, contraindications, and surgical considerations of lung transplant aids in imaging interpretation and protocoling and also facilitates communication between radiologists and transplant physicians. Despite medical and surgical advances over the past several decades, lung transplant recipients currently have an average posttransplant life expectancy of only 6.7 years. As members of the transplant team, radiologists can help maximize patient survival and hopefully increase posttransplant life expectancy and quality of life in the coming decades. ©RSNA, 2021 An invited commentary by Bierhals is available online. Online supplemental material is available for this article.

Nuclear quantum effects in thermal conductivity from centroid molecular dynamics.

We show that the centroid molecular dynamics (CMD) method provides a realistic way to calculate the thermal diffusivity a = λ/ρcV of a quantum mechanical liquid such as para-hydrogen. Once a has been calculated, the thermal conductivity can be obtained from λ = ρcVa, where ρ is the density of the liquid and cV is the constant-volume heat capacity. The use of this formula requires an accurate quantum mechanical heat capacity cV, which can be obtained from a path integral molecular dynamics simulation. The thermal diffusivity can be calculated either from the decay of the equilibrium density fluctuations in the liquid or by using the Green-Kubo relation to calculate the CMD approximation to λ and then dividing this by the corresponding approximation to ρcV. We show that both approaches give the same results for liquid para-hydrogen and that these results are in good agreement with the experimental measurements of the thermal conductivity over a wide temperature range. In particular, they correctly predict a decrease in the thermal conductivity at low temperatures-an effect that stems from the decrease in the quantum mechanical heat capacity and has eluded previous para-hydrogen simulations. We also show that the method gives equally good agreement with the experimental measurements for the thermal conductivity of normal liquid helium.

Percutaneous Transthoracic Lung Biopsy: Optimizing Yield and Mitigating Risk.

ABSTRACT: Percutaneous computed tomography-guided transthoracic lung biopsy is an effective and minimally invasive procedure to achieve tissue diagnosis. Radiologists are key in appropriate referral for further workup, with percutaneous computed tomography-guided transthoracic lung biopsy performed by both thoracic and general interventionalists. Percutaneous computed tomography-guided transthoracic lung biopsy is increasingly performed for both diagnostic and research purposes, including molecular analysis. Multiple patient, lesion, and technique-related variables influence diagnostic accuracy and complication rates. A comprehensive understanding of these factors aids in procedure planning and may serve to maximize diagnostic yield while minimizing complications, even in the most challenging scenarios.

Increased Incidence of Barotrauma in Patients with COVID-19 on Invasive Mechanical Ventilation.

Background A high number of patients with coronavirus disease 2019 (COVID-19) pneumonia who had barotrauma related to invasive mechanical ventilation at the authors' institution were observed. Purpose To determine if the rate of barotrauma in patients with COVID-19 infection was greater than in other patients requiring invasive mechanical ventilation at the authors' institution. Materials and Methods In this retrospective study, clinical and imaging data of patients seen between March 1, 2020, and April 6, 2020, who tested positive for COVID-19 and experienced barotrauma associated with invasive mechanical ventilation, were compared with patients without COVID-19 infection during the same period. Historical comparison was made to barotrauma rates of patients with acute respiratory distress syndrome from February 1, 2016, to February 1, 2020, at the authors' institution. Comparison of patient groups was performed using categoric or continuous statistical testing as appropriate, with multivariable regression analysis. Patient survival was assessed using Kaplan-Meier curves analysis. Results A total of 601 patients with COVID-19 infection underwent invasive mechanical ventilation (mean age, 63 years ± 15 [standard deviation]; 71% men). Of the total, there were 89 (15%) patients with one or more barotrauma events for a total of 145 barotrauma events (24% overall events) (95% confidence interval [CI]: 21%, 28%). During the same period, 196 patients without COVID-19 infection (mean age, 64 years ± 19; 52% men) with invasive mechanical ventilation had one barotrauma event (0.5%; 95% CI: 0%, 3%; P < .001 vs the group with COVID-19 infection). Of 285 patients with acute respiratory distress syndrome on invasive mechanical ventilation during the previous 4 years (mean age, 68 years ± 17; 60% men), 28 patients (10%) had 31 barotrauma events, with an overall barotrauma rate of 11% (95% CI: 8%, 15%; P < .001 vs the group with COVID-19 infection). Barotrauma is an independent risk factor for death in COVID-19 (odds ratio = 2.2; P = .03) and is associated with a longer hospital stay (odds ratio = 0.92; P < .001). Conclusion Patients with coronavirus disease 2019 (COVID-19) infection and invasive mechanical ventilation had a higher rate of barotrauma than patients with acute respiratory distress syndrome and patients without COVID-19 infection. © RSNA, 2020 Online supplemental material is available for this article.

SARS-CoV-2 From the Trenches: A Perspective From New York City.

OBJECTIVE. The response to coronavirus disease (COVID-19) is evolving in New York City. We would like to share our experiences, thoughts, and perspectives on coping with the pandemic. CONCLUSION. This article presents experiences that are meant to help foster discussion as the wave of COVID-19 continues. Thoughtful leadership and careful continuous communication will help us minimize anxiety and frustration during this difficult time.

Low left ventricular outflow tract velocity time integral is associated with poor outcomes in acute pulmonary embolism.

The left ventricular outflow tract (LVOT) velocity time integral (VTI) is an easily measured echocardiographic stroke volume index analog. Low values predict adverse outcomes in left ventricular failure. We postulate the left ventricular VTI may be a signal of right ventricular dysfunction in acute pulmonary embolism, and therefore a predictor of poor outcomes. We retrospectively reviewed echocardiograms on all Pulmonary Embolism Response Team activations at our institution at the time of pulmonary embolism diagnosis. Low LVOT VTI was defined as ⩽ 15 cm. We examined two composite outcomes: (1) in-hospital death or cardiac arrest; and (2) shock or need for primary reperfusion therapies. Sixty-one of 188 patients (32%) had a LVOT VTI of ⩽ 15 cm. Low VTI was associated with in-hospital death or cardiac arrest (odds ratio (OR) 6, 95% CI 2, 17.9; p = 0.0014) and shock or need for reperfusion (OR 23.3, 95% CI 6.6, 82.1; p < 0.0001). In a multivariable model, LVOT VTI ⩽ 15 remained significant for death or cardiac arrest (OR 3.48, 95% CI 1.02, 11.9; p = 0.047) and for shock or need for reperfusion (OR 8.12, 95% CI 1.62, 40.66; p = 0.011). Among intermediate-high-risk patients, low VTI was the only variable associated with the composite outcome of death, cardiac arrest, shock, or need for reperfusion (OR 14, 95% CI 1.7, 118.4; p = 0.015). LVOT VTI is associated with adverse short-term outcomes in acute pulmonary embolism. The VTI may help risk stratify patients with intermediate-high-risk pulmonary embolism.

Simultaneous Evaluation of Lung Anatomy and Ventilation Using 4D Respiratory-Motion-Resolved Ultrashort Echo Time Sparse MRI.

BACKGROUND: Computed tomography (CT) and spirometry are the current standard methods for assessing lung anatomy and pulmonary ventilation, respectively. However, CT provides limited ventilation information and spirometry only provides global measures of lung ventilation. Thus, a method that can enable simultaneous examination of lung anatomy and ventilation is of clinical interest. PURPOSE: To develop and test a 4D respiratory-resolved sparse lung MRI (XD-UTE: eXtra-Dimensional Ultrashort TE imaging) approach for simultaneous evaluation of lung anatomy and pulmonary ventilation. STUDY TYPE: Prospective. POPULATION: In all, 23 subjects (11 volunteers and 12 patients, mean age = 63.6 ± 8.4). FIELD STRENGTH/SEQUENCE: 3T MR; a prototype 3D golden-angle radial UTE sequence, a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence. ASSESSMENT: All subjects were scanned using the 3D golden-angle radial UTE sequence during normal breathing. Ten subjects underwent an additional scan during alternating normal and deep breathing. Respiratory-motion-resolved sparse reconstruction was performed for all the acquired data to generate dynamic normal-breathing or deep-breathing image series. For comparison, BH-VIBE was performed in 12 subjects. Lung images were visually scored by three experienced chest radiologists and were analyzed by two observers who segmented the left and right lung to derive ventilation parameters in comparison with spirometry. STATISTICAL TESTS: Nonparametric paired two-tailed Wilcoxon signed-rank test; intraclass correlation coefficient, Pearson correlation coefficient. RESULTS: XD-UTE achieved significantly improved image quality compared both with Cartesian BH-VIBE and radial reconstruction without motion compensation (P < 0.05). The global ventilation parameters (a sum of the left and right lung measures) were in good correlation with spirometry in the same subjects (correlation coefficient = 0.724). There were excellent correlations between the results obtained by two observers (intraclass correlation coefficient ranged from 0.8855-0.9995). DATA CONCLUSION: Simultaneous evaluation of lung anatomy and ventilation using XD-UTE is demonstrated, which have shown good potential for improved diagnosis and management of patients with heterogeneous lung diseases. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2019;49:411-422.

Informatics Solutions for Driving an Effective and Efficient Radiology Practice.

Radiologists are facing increasing workplace pressures that can lead to decreased job satisfaction and burnout. The increasing complexity and volumes of cases and increasing numbers of noninterpretive tasks, compounded by decreasing reimbursements and visibility in this digital age, have created a critical need to develop innovations that optimize workflow, increase radiologist engagement, and enhance patient care. During their workday, radiologists often must navigate through multiple software programs, including picture archiving and communication systems, electronic health records, and dictation software. Furthermore, additional noninterpretive duties can interrupt image review. Fragmented data and frequent task switching can create frustration and potentially affect patient care. Despite the current successful technological advancements across industries, radiology software systems often remain nonintegrated and not leveraged to their full potential. Each step of the imaging process can be enhanced with use of information technology (IT). Successful implementation of IT innovations requires a collaborative team of radiologists, IT professionals, and software programmers to develop customized solutions. This article includes a discussion of how IT tools are used to improve many steps of the imaging process, including examination protocoling, image interpretation, reporting, communication, and radiologist feedback. ©RSNA, 2018.

Differentiation of intrathoracic lymph node histopathology by volumetric dual energy CT radiomic analysis.

PURPOSE: To determine the performance of volumetric dual energy low kV and iodine radiomic features for the differentiation of intrathoracic lymph node histopathology, and influence of contrast protocol. MATERIALS AND METHODS: Intrathoracic lymph nodes with histopathologic correlation (neoplastic, granulomatous sarcoid, benign) within 90 days of DECT chest imaging were volumetrically segmented. 1691 volumetric radiomic features were extracted from iodine maps and low-kV images, totaling 3382 features. Univariate analysis was performed using 2-sample t-test and filtered for false discoveries. Multivariable analysis was used to compute AUCs for lymph node classification tasks. RESULTS: 129 lymph nodes from 72 individuals (mean age 61 ± 15 years) were included, 52 neoplastic, 51 benign, and 26 granulomatous-sarcoid. Among all contrast enhanced DECT protocol exams (routine, PE and CTA), univariable analysis demonstrated no significant differences in iodine and low kV features between neoplastic and non-neoplastic lymph nodes; in the subset of neoplastic versus benign lymph nodes with routine DECT protocol, 199 features differed (p = .01- < 0.05). Multivariable analysis using both iodine and low kV features yielded AUCs >0.8 for differentiating neoplastic from non-neoplastic lymph nodes (AUC 0.86), including subsets of neoplastic from granulomatous (AUC 0.86) and neoplastic from benign (AUC 0.9) lymph nodes, among all contrast protocols. CONCLUSIONS: Volumetric DECT radiomic features demonstrate strong collective performance in differentiation of neoplastic from non-neoplastic intrathoracic lymph nodes, and are influenced by contrast protocol.

Chest Intensive Care Unit Imaging: Pearls and Pitfalls.

Imaging plays a major role in the care of the intensive care unit (ICU) patients. An understanding of the monitoring devices is essential for the interpretation of imaging studies. An awareness of their expected locations aids in identifying complications in a timely manner. This review describes the imaging of ICU monitoring and support catheters, tubes, and pulmonary and cardiac devices, some more commonly encountered and others that have been introduced into clinical patient care more recently. Special focus will be placed on chest radiography and potential pitfalls encountered.

Radiation Therapy for Lung Cancer: Imaging Appearances and Pitfalls.

Radiation therapy is part of a multimodality treatment approach to lung cancer. The radiologist must be aware of both the expected and the unexpected imaging findings of the post-radiation therapy patient, including the time course for development of post- radiation therapy pneumonitis and fibrosis. In this review, a brief discussion of radiation therapy techniques and indications is presented, followed by an image-heavy differential diagnostic approach. The review focuses on computed tomography imaging examples to help distinguish normal postradiation pneumonitis and fibrosis from alternative complications, such as infection, local recurrence, or radiation-induced malignancy.

Diseases Involving the Lung Peribronchovascular Region: A CT Imaging Pathologic Classification.

TOPIC IMPORTANCE: Chest CT imaging holds a major role in the diagnosis of lung diseases, many of which affect the peribronchovascular region. Identification and categorization of peribronchovascular abnormalities on CT imaging can assist in formulating a differential diagnosis and directing further diagnostic evaluation. REVIEW FINDINGS: The peribronchovascular region of the lung encompasses the pulmonary arteries, airways, and lung interstitium. Understanding disease processes associated with structures of the peribronchovascular region and their appearances on CT imaging aids in prompt diagnosis. This article reviews current knowledge in anatomic and pathologic features of the lung interstitium composed of intercommunicating prelymphatic spaces, lymphatics, collagen bundles, lymph nodes, and bronchial arteries; diffuse lung diseases that present in a peribronchovascular distribution; and an approach to classifying diseases according to patterns of imaging presentations. Lung peribronchovascular diseases can appear on CT imaging as diffuse thickening, fibrosis, masses or masslike consolidation, ground-glass or air space consolidation, and cysts, acknowledging that some diseases may have multiple presentations. SUMMARY: A category approach to peribronchovascular diseases on CT imaging can be integrated with clinical features as part of a multidisciplinary approach for disease diagnosis.

Low-field MRI lung opacity severity associated with decreased DLCO in post-acute Covid-19 patients.

OBJECTIVES: To evaluate the clinical significance of low-field MRI lung opacity severity. METHODS: Retrospective cross-sectional analysis of post-acute Covid-19 patients imaged with low-field MRI from 9/2020 through 9/2022, and within 1 month of pulmonary function tests (PFTs), 6-min walk test (6mWT), and symptom inventory (SI), and/or within 3 months of St. George Respiratory Questionnaire (SGRQ) was performed. Univariate and correlative analyses were performed with Wilcoxon, Chi-square, and Spearman tests. The association between disease and demographic factors and MR opacity severity, PFTs, 6mWT, SI, and SGRQ, and association between MR opacity severity with functional and patient-reported outcomes (PROs), was evaluated with mixed model analysis of variance, covariance and generalized estimating equations. Two-sided 5 % significance level was used, with Bonferroni multiple comparison correction. RESULTS: 81 MRI exams in 62 post-acute Covid-19 patients (median age 57, IQR 41-64; 25 women) were included. Exams were a median of 8 months from initial illness. Univariate analysis showed lung opacity severity was associated with decreased %DLCO (ρ = -0.55, P = .0125), and lung opacity severity quartile was associated with decreased %DLCO, predicted TLC, FVC, and increased FEV1/FVC. Multivariable analysis adjusting for sex, initial disease severity, and interval from Covid-19 diagnosis showed MR lung opacity severity was associated with decreased %DLCO (P < .001). Lung opacity severity was not associated with PROs. CONCLUSION: Low-field MRI lung opacity severity correlated with decreased %DLCO in post-acute Covid-19 patients, but was not associated with PROs.

ACR Appropriateness Criteria® Tracheobronchial Disease.

A variety of thoracic imaging modalities and techniques have been used to evaluate diseases of the trachea and central bronchi. This document evaluates evidence for the use of thoracic imaging in the evaluation of tracheobronchial disease, including clinically suspected tracheal or bronchial stenosis, tracheomalacia or bronchomalacia, and bronchiectasis. Appropriateness guidelines for initial imaging evaluation of tracheobronchial disease and for pretreatment planning or posttreatment evaluation are included. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision process support the systematic analysis of the medical literature from peer reviewed journals. Established methodology principles such as Grading of Recommendations Assessment, Development, and Evaluation or GRADE are adapted to evaluate the evidence. The RAND/UCLA Appropriateness Method User Manual provides the methodology to determine the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where peer reviewed literature is lacking or equivocal, experts may be the primary evidentiary source available to formulate a recommendation.