MR Volumetry of Lung Nodules: A Pilot Study

Introduction: Computed tomography (CT) is currently the reference modality for the detection and follow-up of pulmonary nodules. While 2D measurements are commonly used in clinical practice to assess growth, increasingly 3D volume measurements are being recommended. The goal of this pilot study was to evaluate preliminarily the capabilities of 3D MRI using ultra-short echo time for lung nodule volumetry, as it would provide a radiation-free modality for this task.Material and Methods: Artificial nodules were manufactured out of Agar and measured using an ultra-short echo time MRI sequence. CT data were also acquired as a reference. Image segmentation was carried out using an algorithm based on signal intensity thresholding (SIT). For comparison purposes, we also performed manual slice by slice segmentation. Volumes obtained with MRI and CT were compared. Finally, the volumetry of a lung nodule was evaluated in one human subject in comparison with CT.Results: Using the SIT technique, minimal bias was observed between CT and MRI across the entire range of volumes (2%) with limits of agreement below 14%. Comparison of manually segmented MRI and CT resulted in a larger bias (8%) and wider limits of agreement (−23% to 40%). In vivo, nodule volume differed of <16% between modalities with the SIT technique.Conclusion: This pilot study showed very good concordance between CT and UTE-MRI to quantify lung nodule volumes, in both a phantom and human setting. Our results enhance the potential of MRI to quantify pulmonary nodule volume with similar performance to CT

Interstitial Lung Abnormalities Detected by CT in Asbestos-Exposed Subjects Are More Likely Associated to Age

OBJECTIVE: the aim of this study was to evaluate the association between interstitial lung abnormalities, asbestos exposure and age in a population of retired workers previously occupationally exposed to asbestos. METHODS: previously occupationally exposed former workers to asbestos eligible for a survey conducted between 2003 and 2005 in four regions of France, underwent chest CT examinations and pulmonary function testing. Industrial hygienists evaluated asbestos exposure and calculated for each subject a cumulative exposure index (CEI) to asbestos. Smoking status information was also collected in this second round of screening. Expert radiologists performed blinded independent double reading of chest CT-scans and classified interstitial lung abnormalities into: no abnormality, minor interstitial findings, interstitial findings inconsistent with UIP, possible or definite UIP. In addition, emphysema was assessed visually (none, minor: emphysema 50% of the lung). Logistic regression models adjusted for age and smoking were used to assess the relationship between interstitial lung abnormalities and occupational asbestos exposure. RESULTS: the study population consisted of 2157 male subjects. Interstitial lung abnormalities were present in 365 (16.7%) and emphysema in 444 (20.4%). Significant positive association was found between definite or possible UIP pattern and age (OR adjusted =1.08 (95% CI: 1.02-1.13)). No association was found between interstitial abnormalities and CEI or the level of asbestos exposure. CONCLUSION: presence of interstitial abnormalities at HRCT was associated to aging but not to cumulative exposure index in this cohort of former workers previously occupationally exposed to asbestos

Deep Learning for the Automatic Quantification of Pleural Plaques in Asbestos-Exposed Subjects

OBJECTIVE: This study aimed to develop and validate an automated artificial intelligence (AI)-driven quantification of pleural plaques in a population of retired workers previously occupationally exposed to asbestos. METHODS: CT scans of former workers previously occupationally exposed to asbestos who participated in the multicenter APEXS (Asbestos PostExposure Survey) study were collected retrospectively between 2010 and 2017 during the second and the third rounds of the survey. A hundred and forty-one participants with pleural plaques identified by expert radiologists at the 2nd and the 3rd CT screenings were included. Maximum Intensity Projection (MIP) with 5 mm thickness was used to reduce the number of CT slices for manual delineation. A Deep Learning AI algorithm using 2D-convolutional neural networks was trained with 8280 images from 138 CT scans of 69 participants for the semantic labeling of Pleural Plaques (PP). In all, 2160 CT images from 36 CT scans of 18 participants were used for AI testing versus ground-truth labels (GT). The clinical validity of the method was evaluated longitudinally in 54 participants with pleural plaques. RESULTS: The concordance correlation coefficient (CCC) between AI-driven and GT was almost perfect (>0.98) for the volume extent of both PP and calcified PP. The 2D pixel similarity overlap of AI versus GT was good (DICE = 0.63) for PP, whether they were calcified or not, and very good (DICE = 0.82) for calcified PP. A longitudinal comparison of the volumetric extent of PP showed a significant increase in PP volumes (p < 0.001) between the 2nd and the 3rd CT screenings with an average delay of 5 years. CONCLUSIONS: AI allows a fully automated volumetric quantification of pleural plaques showing volumetric progression of PP over a five-year period. The reproducible PP volume evaluation may enable further investigations for the comprehension of the unclear relationships between pleural plaques and both respiratory function and occurrence of thoracic malignancy

Eur Radiol

OBJECTIVES: The study aimed to validate automated quantification of high and low signal intensity volumes using ultrashort echo-time MRI, with CT and pulmonary function test (PFT) as references, to assess the severity of structural alterations in cystic fibrosis (CF). METHODS: This prospective study was performed in a single center between May 2015 and September 2017. Participants with CF completed clinical examination, CT, MRI, and PFT the same day during routine clinical follow-up (M0), and then 1 year after (M12) except for CT. Using MRI, percentage high (%MR-HSV), low (%MR-LSV), and total abnormal (%MR-TSV) signal intensity volumes were recorded, as well as their corresponding attenuation values using CT (%CT-HAV, %CT-LAV, %CT-TAV, respectively). Automated quantifications and visual Bhalla score were evaluated independently by two observers. Correlations were assessed using the Spearman test, comparisons using the Mann-Whitney test, and reproducibility using the intraclass correlation coefficient (ICC). RESULTS: A total of 30 participants were enrolled (median age 27 years, 18 men). At M0, there was a good correlation between %MR-HSV and %CT-HAV (ρ = 0.70; p \textbackslashtextless 0.001) and %MR-LSV and %CT-LAV (ρ = 0.60; p \textbackslashtextless 0.001). Automated MR metrics correlated to PFTs and Bhalla score (p \textbackslashtextless 0.05) while %MR-TSV was significantly different between CF with and without respiratory exacerbation (p = 0.01) at both M0 and M12. The variation of %MR-HSV correlated to the variation of FEV1% at PFT (ρ = - 0.49; p = 0.008). Reproducibility was almost perfect (ICCs \textbackslashtextgreater 0.95). CONCLUSIONS: Automated quantification of abnormal signal intensity volumes relates to CF severity and allows reproducible cross-sectional and longitudinal assessment. TRIAL REGISTRATION: Clinical trial identifier: NCT02449785 KEY POINTS: • Cross-sectionally, the automated quantifications of high and low signal intensity volumes at UTE correlated to the quantification of high and low attenuation using CT as reference. • Longitudinally, the variation of high signal intensity volume at UTE correlated to the variation of pulmonary function test and was significantly reduced in CF with an improvement in exacerbation status. • Automated quantification of abnormal signal intensity volumes are objective and reproducible tools to assess structural alterations in CF and follow-up longitudinally, for both research and clinical purposes

The clinical use of lung MRI in cystic fibrosis: what, now, how?

International audienceTo assess airway and lung parenchymal damage noninvasively in cystic fibrosis (CF), chest MRI has been historically out of the scope of routine clinical imaging because of technical difficulties such as low proton density and respiratory and cardiac motion. However, technological breakthroughs have emerged that dramatically improve lung MRI quality (including signal-to-noise ratio, resolution, speed, and contrast). At the same time, novel treatments have changed the landscape of CF clinical care. In this contemporary context, there is now consensus that lung MRI can be used clinically to assess CF in a radiation-free manner and to enable quantification of lung disease severity. MRI can now achieve three-dimensional, high-resolution morphologic imaging, and beyond this morphologic information, MRI may offer the ability to sensitively differentiate active inflammation vs scarring tissue. MRI could also characterize various forms of inflammation for early guidance of treatment. Moreover, functional information from MRI can be used to assess regional, small-airway disease with sensitivity to detect small changes even in patients with mild CF. Finally, automated quantification methods have emerged to support conventional visual analyses for more objective and reproducible assessment of disease severity. This article aims to review the most recent developments of lung MRI, with a focus on practical application and clinical value in CF, and the perspectives on how these modern techniques may converge and impact patient care soon

J Magn Reson Imaging

BACKGROUND: Imaging has played a pivotal role in the diagnosis of idiopathic pulmonary fibrosis (IPF). Recent reports suggest that T2 -weighted MRI could be sensitive to monitor signal-intensity modifications of the lung parenchyma, which may relate to the disease activity in IPF. However, there is a lack of automated tools to reproducibly quantify the extent of the disease, especially using MRI. PURPOSE: To assess the feasibility of T2 interstitial lung disease signal-intensity volume quantification using a semiautomated method in IPF. STUDY TYPE: Single center, retrospective. POPULATION: A total of 21 adult IPF patients and four control subjects without lung interstitial abnormalities. FIELD STRENGTH/SEQUENCE: Both free-breathing ultrashort echo time (TE) lung MRI using the spiral volume interpolated breath hold examination (VIBE) sequence (3D-UTE) and T2 -BLADE at 1.5T. ASSESSMENT: Semiautomated segmentation of the lung volume was done using 3D-UTE and registered to the T2 -BLADE images. The interstitial lung disease signal-intensity volume (ISIV) was quantified using a Gaussian mixture model clustering and then normalized to the lung volume to calculate T2 -ISIV. The composite physiological index (CPI) and forced vital capacity (FVC) were measured as known biomarkers of IPF severity. Measurements were performed independently by three readers and averaged. The reproducibility between measurements was also assessed. STATISTICAL TESTS: Reproducibility was assessed using the intraclass correlation coefficient (ICC) and Bland-Altman analysis. Correlations were assessed using Spearman test. Comparison of median was assessed using the Mann-Whitney test. RESULTS: The reproducibility of T2 -ISIV was high, with ICCs = 0.99. Using Bland-Altman analysis, the mean differences were found between -0.8 to 0.1. T2 -ISIV significantly correlated with CPI and FVC (rho = 0.48 and 0.50, respectively; P < 0.05). T2 -ISIV was significantly higher in IPF than in controls (P < 0.05). DATA CONCLUSION: T2 -ISIV appears to be able to reproducibly assess the volumetric extent of abnormal interstitial lung signal-intensity modifications in patients with IPF, and correlate with disease severity. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY STAGE: 1

Non-Contrast-Enhanced Functional Lung MRI to Evaluate Treatment Response of Allergic Bronchopulmonary Aspergillosis in Patients With Cystic Fibrosis: A Pilot Study

International audienceBackground: Allergic bronchopulmonary aspergillosis (ABPA) in cystic fibrosis (CF) patients is associated with severe lung damage and requires specific therapeutic management. Repeated imaging is recommended to both diagnose and follow-up response to treatment of ABPA in CF. However, high risk of cumulative radiation exposure requires evaluation of free-radiation techniques in the follow-up of CF patients with ABPA.Purpose: To evaluate whether Fourier decomposition (FD) functional lung MRI can detect response to treatment of ABPA in CF patients.Study Type: Retrospective longitudinal.Population: Twelve patients (7M, median-age:14 years) with CF and ABPA with pre- and post-treatment MRI.Field Strength/Sequence: 2D-balanced-steady-state free-precession (bSSFP) sequence with FD at 1.5T.Assessment: Ventilation-weighted (V) and perfusion-weighted (Q) maps were obtained after FD processing of 2D-coronal bSSFP time-resolved images acquired before and 3–9 months after treatment. Defects extent was assessed on the functional maps using a qualitative semi-quantitative score (0 = absence/negligible, 1 = 50%). Mean and coefficient of variation (CV) of the ventilation signal-intensity (VSI) and the perfusion signal-intensity (QSI) were calculated. Measurements were performed independently by three readers and averaged. Inter-reader reproducibility of the measurements was assessed. Pulmonary function tests (PFTs) were performed within 1 week of both MRI studies as markers of the airflow-limitation severity.Statistical Tests: Comparisons of medians were performed using the paired Wilcoxon-test. Reproducibility was assessed using intraclass correlation coefficient (ICC). Correlations between MRI and PFT parameters were assessed using the Spearman-test (rho correlation-coefficient). A P-value  0.90, while the ICCs of the quantitative measurements was almost perfect (>0.99). Changes in VSI_cv and QSI_cv before and after treatment correlated inversely with changes of FEV1%p (rho = −0.68 for both).Data Conclusion: Non-contrast-enhanced FD lung MRI has potential to reproducibly assess response to treatment of ABPA in CF patients and correlates with PFT obstructive parameters.Evidence Level: 4Technical Efficacy: Stage

Artificial intelligence in CT for quantifying lung changes in the era of CFTR modulators

International audienceBackground: Chest computed tomography (CT) remains the imaging standard for demonstrating cystic fibrosis (CF) airway structural disease in vivo. However, visual scoring systems as an outcome measure are time consuming, require training and lack high reproducibility. Our objective was to validate a fully automated artificial intelligence (AI)-driven scoring system of CF lung disease severity.Methods: Data were retrospectively collected in three CF reference centres, between 2008 and 2020, in 184 patients aged 4-54 years. An algorithm using three 2D convolutional neural networks was trained with 78 patients' CT scans (23 530 CT slices) for the semantic labelling of bronchiectasis, peribronchial thickening, bronchial mucus, bronchiolar mucus and collapse/consolidation. 36 patients' CT scans (11 435 CT slices) were used for testing versus ground-truth labels. The method's clinical validity was assessed in an independent group of 70 patients with or without lumacaftor/ivacaftor treatment (n=10 and n=60, respectively) with repeat examinations. Similarity and reproducibility were assessed using the Dice coefficient, correlations using the Spearman test, and paired comparisons using the Wilcoxon rank test.Results: The overall pixelwise similarity of AI-driven versus ground-truth labels was good (Dice 0.71). All AI-driven volumetric quantifications had moderate to very good correlations to a visual imaging scoring (p0.99).Conclusion: AI allows fully automated volumetric quantification of CF-related modifications over an entire lung. The novel scoring system could provide a robust disease outcome in the era of effective CF transmembrane conductance regulator modulator therapy.Trial registration: ClinicalTrials.gov NCT04760548

High-Resolution Late Gadolinium Enhancement Magnetic Resonance for the Diagnosis of Myocardial Infarction With Nonobstructed Coronary Arteries

International audienceObjectives: The aim of this study was to assess the diagnostic yield of cardiac magnetic resonance (CMR) including high-resolution (HR) late gadolinium enhancement (LGE) imaging using a 3-dimensional respiratory-navigated method in patients with myocardial infarction with nonobstructed coronary arteries (MINOCA).Background: CMR plays a pivotal role for the diagnosis of patients with MINOCA. However, the diagnosis remains inconclusive in a significant number of patients, the results of CMR being either negative or uncertain (i.e., compatible with multiple diagnoses).Methods: Consecutive patients categorized as having MINOCA after blood testing, electrocardiography, coronary angiography, and echocardiography underwent conventional CMR, including cine, T2-weighted, first-pass perfusion, and conventional breath-held LGE imaging. HR LGE imaging using a free-breathing method allowing improved spatial resolution (voxel size 1.25 × 1.25 × 2.5 mm) was added to the protocol when the results of conventional CMR were inconclusive and was optional otherwise. Diagnoses retained after reviewing conventional CMR were compared with those retained after the addition of HR LGE imaging.Results: From 2013 to 2016, 229 patients were included (mean age 56 ± 17 years, 45% women). HR LGE imaging was performed in 172 patients (75%). In this subpopulation, definite diagnoses were retained after conventional CMR in 86 patients (50%): infarction in 39 (23%), myocarditis in 32 (19%), takotsubo cardiomyopathy in 13 (8%), and other diagnoses in 2 (1%). In the remaining 86 patients (50%), results of CMR were inconclusive: negative in 54 (31%) and consistent with multiple diagnoses in 32 (19%). HR LGE imaging led to changes in final diagnosis in 45 patients (26%) and to a lower rate of inconclusive final diagnosis (29%) (p < 0.001). In particular, HR LGE imaging could reveal or ascertain the diagnosis of infarction in 14% and rule out the diagnosis of infarction in 12%. HR LGE imaging was particularly useful when the results of transthoracic echocardiography, ventriculography, and conventional CMR were negative, with a 48% rate of modified diagnosis in this subpopulation.Conclusions: HR LGE imaging has high diagnostic value in patients with MINOCA and inconclusive findings on conventional CMR. This has major diagnostic, prognostic, and therapeutic implications