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

BACKGROUND: 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%, 2 = >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 <0.05 was considered as significant. RESULTS: Defects extent on both V and Q maps showed a significant reduction after ABPA treatment (4.25 vs. 1.92 for V-defect-score and 5 vs. 2.75 for Q-defect-score). VSI_mean was significantly increased after treatment (280 vs. 167). Qualitative analyses reproducibility showed an ICC > 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: 4 TECHNICAL EFFICACY: Stage 3.

Simulation-based inference for non-parametric statistical comparison of biomolecule dynamics.

Numerous models have been developed to account for the complex properties of the random walks of biomolecules. However, when analysing experimental data, conditions are rarely met to ensure model identification. The dynamics may simultaneously be influenced by spatial and temporal heterogeneities of the environment, out-of-equilibrium fluxes and conformal changes of the tracked molecules. Recorded trajectories are often too short to reliably discern such multi-scale dynamics, which precludes unambiguous assessment of the type of random walk and its parameters. Furthermore, the motion of biomolecules may not be well described by a single, canonical random walk model. Here, we develop a two-step statistical testing scheme for comparing biomolecule dynamics observed in different experimental conditions without having to identify or make strong prior assumptions about the model generating the recorded random walks. We first train a graph neural network to perform simulation-based inference and thus learn a rich summary statistics vector describing individual trajectories. We then compare trajectories obtained in different biological conditions using a non-parametric maximum mean discrepancy (MMD) statistical test on their so-obtained summary statistics. This procedure allows us to characterise sets of random walks regardless of their generating models, without resorting to model-specific physical quantities or estimators. We first validate the relevance of our approach on numerically simulated trajectories. This demonstrates both the statistical power of the MMD test and the descriptive power of the learnt summary statistics compared to estimates of physical quantities. We then illustrate the ability of our framework to detect changes in α-synuclein dynamics at synapses in cultured cortical neurons, in response to membrane depolarisation, and show that detected differences are largely driven by increased protein mobility in the depolarised state, in agreement with previous findings. The method provides a means of interpreting the differences it detects in terms of single trajectory characteristics. Finally, we emphasise the interest of performing various comparisons to probe the heterogeneity of experimentally acquired datasets at different levels of granularity (e.g., biological replicates, fields of view, and organelles).

Radiological Diagnosis of Pulmonary Aspergillosis.

Imaging plays an important role in the various forms of Aspergillus-related pulmonary disease. Depending on the immune status of the patient, three forms are described with distinct imaging characteristics: invasive aspergillosis affecting severely immunocompromised patients, chronic pulmonary aspergillosis affecting less severely immunocompromised patients but suffering from a pre-existing structural lung disease, and allergic bronchopulmonary aspergillosis related to respiratory exposure to Aspergillus species in patients with asthma and cystic fibrosis. Computed tomography (CT) has been demonstrated more sensitive and specific than chest radiographs and its use has largely contributed to the diagnosis, follow-up, and evaluation of treatment in each condition. In the last few decades, CT has also been described in the specific context of cystic fibrosis. In this particular clinical setting, magnetic resonance imaging and the recent developments in artificial intelligence have shown promising results.

Generating High-Resolution Synthetic CT from Lung MRI with Ultrashort Echo Times: Initial Evaluation in Cystic Fibrosis.

Background Lung MRI with ultrashort echo times (UTEs) enables high-resolution and radiation-free morphologic imaging; however, its image quality is still lower than that of CT. Purpose To assess the image quality and clinical applicability of synthetic CT images generated from UTE MRI by a generative adversarial network (GAN). Materials and Methods This retrospective study included patients with cystic fibrosis (CF) who underwent both UTE MRI and CT on the same day at one of six institutions between January 2018 and December 2022. The two-dimensional GAN algorithm was trained using paired MRI and CT sections and tested, along with an external data set. Image quality was assessed quantitatively by measuring apparent contrast-to-noise ratio, apparent signal-to-noise ratio, and overall noise and qualitatively by using visual scores for features including artifacts. Two readers evaluated CF-related structural abnormalities and used them to determine clinical Bhalla scores. Results The training, test, and external data sets comprised 82 patients with CF (mean age, 21 years ± 11 [SD]; 42 male), 28 patients (mean age, 18 years ± 11; 16 male), and 46 patients (mean age, 20 years ± 11; 24 male), respectively. In the test data set, the contrast-to-noise ratio of synthetic CT images (median, 303 [IQR, 221-382]) was higher than that of UTE MRI scans (median, 9.3 [IQR, 6.6-35]; P < .001). The median signal-to-noise ratio was similar between synthetic and real CT (88 [IQR, 84-92] vs 88 [IQR, 86-91]; P = .96). Synthetic CT had a lower noise level than real CT (median score, 26 [IQR, 22-30] vs 42 [IQR, 32-50]; P < .001) and the lowest level of artifacts (median score, 0 [IQR, 0-0]; P < .001). The concordance between Bhalla scores for synthetic and real CT images was almost perfect (intraclass correlation coefficient, ≥0.92). Conclusion Synthetic CT images showed almost perfect concordance with real CT images for the depiction of CF-related pulmonary alterations and had better image quality than UTE MRI. Clinical trial registration no. NCT03357562 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Schiebler and Glide-Hurst in this issue.

TRamWAy: mapping physical properties of individual biomolecule random motion in large-scale single-particle tracking experiments.

MOTIVATION: Single-molecule localization microscopy allows studying the dynamics of biomolecules in cells and resolving the biophysical properties of the molecules and their environment underlying cellular function. With the continuously growing amount of data produced by individual experiments, the computational cost of quantifying these properties is increasingly becoming the bottleneck of single-molecule analysis. Mining these data requires an integrated and efficient analysis toolbox. RESULTS: We introduce TRamWAy, a modular Python library that features: (i) a conservative tracking procedure for localization data, (ii) a range of sampling techniques for meshing the spatio-temporal support of the data, (iii) computationally efficient solvers for inverse models, with the option of plugging in user-defined functions and (iv) a collection of analysis tools and a simple web-based interface. AVAILABILITY AND IMPLEMENTATION: TRamWAy is a Python library and can be installed with pip and conda. The source code is available at https://github.com/DecBayComp/TRamWAy.

Longitudinal Evaluation of Bronchial Changes in Cystic Fibrosis Patients Undergoing Elexacaftor/Tezacaftor/Ivacaftor Therapy Using Lung MRI With Ultrashort Echo-Times.

BACKGROUND: Lung magnetic resonance imaging (MRI) with ultrashort echo-times (UTE-MRI) allows high-resolution and radiation-free imaging of the lung structure in cystic fibrosis (CF). In addition, the combination of elexacaftor/tezacaftor/ivacaftor (ETI) has improved CF clinical outcomes such as need for hospitalization. However, the effect on structural disease still needs longitudinal evaluation at high resolution. PURPOSE: To analyze the effects of ETI on lung structural alterations using UTE-MRI, with a focus on bronchiectasis reversibility. STUDY TYPE: Retrospective. POPULATION: Fifty CF patients (mean age 24.3 ± 9.2; 23 males). FIELD STRENGTH/SEQUENCE: 1.5 T, UTE-MRI. ASSESSMENT: All subjects completed both UTE-MRI and pulmonary function tests (PFTs) during two annual visits (M0 and M12), and 30 of them completed a CT scan. They initiated ETI treatment after M0 within a maximum of 3 months from the annual examinations. Three observers scored a clinical MRI Bhalla score on UTE-MRI. Bronchiectasis reversibility was defined as a reduction in both outer and inner bronchial dimensions. Correlations were searched between the Bhalla score and PFT such as the forced expiratory volume in 1 second percentage predicted (FEV1%p). STATISTICAL TESTS: Comparison was assessed using the paired t-test, correlation using the Spearman correlation test with a significance level of 0.05. Concordance and reproducibility were assessed using intraclass correlation coefficient (ICC). RESULTS: There was a significant improvement in MRI Bhalla score after ETI treatment. UTE-MRI demonstrated bronchiectasis reversibility in a subgroup of 18 out of 50 CF patients (36%). These patients with bronchiectasis reversibility were significantly younger, with lower severity of wall thickening but no difference in mucus plugging extent (P = 0.39) was found. The reproducibility of UTE-MRI evaluations was excellent (ICC ≥ 0.95), was concordant with CT scan (N = 30; ICC ≥ 0.90) and significantly correlated to FEV1% at PFT at M0 (N = 50; r = 0.71) and M12 (N = 50; r = 0.72). DATA CONCLUSION: UTE-MRI is a reproducible tool for the longitudinal follow-up of CF patients, allowing to quantify the response to ETI and demonstrating the reversibility of some structural alterations such as bronchiectasis in a substantial fraction of this study population. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 2.

Development and external validation of a prediction model for the transition from mild to moderate or severe form of COVID-19.

OBJECTIVES: COVID-19 pandemic seems to be under control. However, despite the vaccines, 5 to 10% of the patients with mild disease develop moderate to critical forms with potential lethal evolution. In addition to assess lung infection spread, chest CT helps to detect complications. Developing a prediction model to identify at-risk patients of worsening from mild COVID-19 combining simple clinical and biological parameters with qualitative or quantitative data using CT would be relevant to organizing optimal patient management. METHODS: Four French hospitals were used for model training and internal validation. External validation was conducted in two independent hospitals. We used easy-to-obtain clinical (age, gender, smoking, symptoms' onset, cardiovascular comorbidities, diabetes, chronic respiratory diseases, immunosuppression) and biological parameters (lymphocytes, CRP) with qualitative or quantitative data (including radiomics) from the initial CT in mild COVID-19 patients. RESULTS: Qualitative CT scan with clinical and biological parameters can predict which patients with an initial mild presentation would develop a moderate to critical form of COVID-19, with a c-index of 0.70 (95% CI 0.63; 0.77). CT scan quantification improved the performance of the prediction up to 0.73 (95% CI 0.67; 0.79) and radiomics up to 0.77 (95% CI 0.71; 0.83). Results were similar in both validation cohorts, considering CT scans with or without injection. CONCLUSION: Adding CT scan quantification or radiomics to simple clinical and biological parameters can better predict which patients with an initial mild COVID-19 would worsen than qualitative analyses alone. This tool could help to the fair use of healthcare resources and to screen patients for potential new drugs to prevent a pejorative evolution of COVID-19. CLINICAL TRIAL REGISTRATION: NCT04481620. CLINICAL RELEVANCE STATEMENT: CT scan quantification or radiomics analysis is superior to qualitative analysis, when used with simple clinical and biological parameters, to determine which patients with an initial mild presentation of COVID-19 would worsen to a moderate to critical form. KEY POINTS: • Qualitative CT scan analyses with simple clinical and biological parameters can predict which patients with an initial mild COVID-19 and respiratory symptoms would worsen with a c-index of 0.70. • Adding CT scan quantification improves the performance of the clinical prediction model to an AUC of 0.73. • Radiomics analyses slightly improve the performance of the model to a c-index of 0.77.

Identifying neural substrates of competitive interactions and sequence transitions during mechanosensory responses in Drosophila.

Nervous systems have the ability to select appropriate actions and action sequences in response to sensory cues. The circuit mechanisms by which nervous systems achieve choice, stability and transitions between behaviors are still incompletely understood. To identify neurons and brain areas involved in controlling these processes, we combined a large-scale neuronal inactivation screen with automated action detection in response to a mechanosensory cue in Drosophila larva. We analyzed behaviors from 2.9x105 larvae and identified 66 candidate lines for mechanosensory responses out of which 25 for competitive interactions between actions. We further characterize in detail the neurons in these lines and analyzed their connectivity using electron microscopy. We found the neurons in the mechanosensory network are located in different regions of the nervous system consistent with a distributed model of sensorimotor decision-making. These findings provide the basis for understanding how selection and transition between behaviors are controlled by the nervous system.

Artificial intelligence in computed tomography for quantifying lung changes in the era of CFTR modulators.

BACKGROUND: 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 (p<0.001) and fair to good correlations to forced expiratory volume in 1 s % predicted at pulmonary function tests (p<0.001). Significant decreases in peribronchial thickening (p=0.005), bronchial mucus (p=0.005) and bronchiolar mucus (p=0.007) volumes were measured in patients with lumacaftor/ivacaftor. Conversely, bronchiectasis (p=0.002) and peribronchial thickening (p=0.008) volumes increased in patients without lumacaftor/ivacaftor. The reproducibility was almost perfect (Dice >0.99). 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.

Nebulised liposomal amphotericin-B as maintenance therapy in allergic bronchopulmonary aspergillosis: a randomised, multicentre trial.

BACKGROUND: In allergic bronchopulmonary aspergillosis (ABPA), prolonged nebulised antifungal treatment may be a strategy for maintaining remission. METHODS: We performed a randomised, single-blind, clinical trial in 30 centres. Patients with controlled ABPA after 4-month attack treatment (corticosteroids and itraconazole) were randomly assigned to nebulised liposomal amphotericin-B or placebo for 6 months. The primary outcome was occurrence of a first severe clinical exacerbation within 24 months following randomisation. Secondary outcomes included the median time to first severe clinical exacerbation, number of severe clinical exacerbations per patient, ABPA-related biological parameters. RESULTS: Among 174 enrolled patients with ABPA from March 2015 through July 2017, 139 were controlled after 4-month attack treatment and were randomised. The primary outcome occurred in 33 (50.8%) out of 65 patients in the nebulised liposomal amphotericin-B group and 38 (51.3%) out of 74 in the placebo group (absolute difference -0.6%, 95% CI -16.8- +15.6%; OR 0.98, 95% CI 0.50-1.90; p=0.95). The median (interquartile range) time to first severe clinical exacerbation was longer in the liposomal amphotericin-B group: 337 days (168-476 days) versus 177 days (64-288 days). At the end of maintenance therapy, total immunoglobulin-E and Aspergillus precipitins were significantly decreased in the nebulised liposomal amphotericin-B group. CONCLUSIONS: In ABPA, maintenance therapy using nebulised liposomal amphotericin-B did not reduce the risk of severe clinical exacerbation. The presence of some positive secondary outcomes creates clinical equipoise for further research.

Head and neck cancer and asbestos exposure.

OBJECTIVES: The aim of this study was to analyse, within a French cohort of workers previously occupationally exposed to asbestos, incidence and mortality from various sites of head and neck cancers (larynx excluded) and to examine the potential link of these cancers with pleural plaques. METHODS: A 10-year follow-up study was conducted in the 13 481 male subjects included in the cohort between October 2003 and December 2005. Asbestos exposure was assessed by industrial hygienist analysis of a standardised questionnaire. The final cumulative exposure index (CEI; in equivalent fibres.years/mL) for each subject was calculated as the sum of each employment period's four-level CEI. The number of head and neck cancers recorded by the National Health Insurance fund was collected in order to conduct an incidence study. Complementary analysis was restricted to men who had performed at least one chest CT scan (N=4804). A mortality study was also conducted. We used a Cox model with age as the time axis variable adjusted for smoking, time since first exposure, CEI of exposure to asbestos and pleural plaques on CT scans. RESULTS: We reported a significant dose-response relationship between CEI of exposure to asbestos and head and neck cancers after exclusion of laryngeal cancers, in the mortality study (HR 1.03, 95% CI (1.01 to 1.06) for an increase of 10 f.years/mL) and a close to significant dose-response relationship in the incidence study (HR 1.02, 95% CI (1.00 to 1.04) for an increase of 10 f.years/mL). No statistically significant association between pleural plaques and head and neck cancer incidence was observed. CONCLUSIONS: This large-scale study suggests a relationship between asbestos exposure and head and neck cancers, after exclusion of laryngeal cancers, regardless of whether associated pleural plaques were present.

Pleural plaques and risk of lung cancer in workers formerly occupationally exposed to asbestos: extension of follow-up.

BACKGROUND: Occupational asbestos exposure is associated with pleural plaques (PP), a benign disease often seen as a marker of past exposure to asbestos and lung cancer. The association between these two diseases has not been formally proved, the aim of this study was to evaluate this association in the asbestos-related disease cohort (ARDCO) cohort. METHODS: ARDCO is a French multicentric cohort including workers formerly occupationally exposed to asbestos from 2003 to 2005. CT scan was performed to diagnose PP with double reading and lung cancer (incidence and mortality) was followed through health insurance data and death certificates. Cox models were used to estimate the association between PP and lung cancer adjusting for occupational asbestos exposure (represented by cumulative exposure index, time since first exposure and time since last exposure) and smoking status. RESULTS: A total of 176 cases (of 5050 subjects) and 88 deaths (of 4938 subjects) of lung cancer were recorded. Smoking status was identified as an effect modifier. Lung cancer incidence and mortality were significantly associated with PP only in non-smokers, respectively, HR=3.13 (95% CI 1.04 to 9.35) and HR=16.83 (95% CI 1.87 to 151.24) after adjustment for age, occupational asbestos exposure and smoking status. CONCLUSIONS: ARDCO study was the first to study this association considering equal asbestos exposure, and more specifically, our study is the first to test smoking as an effect modifier, so comparison with scientific literature is difficult. Our results seem to consolidate the hypothesis that PP may be an independent risk factor for lung cancer but they must be interpreted with caution.

Quantification of MRI T2 Interstitial Lung Disease Signal-Intensity Volume in Idiopathic Pulmonary Fibrosis: A Pilot Study.

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.

Pulsed field ablation selectively spares the oesophagus during pulmonary vein isolation for atrial fibrillation.

AIMS: Extra-atrial injury can cause complications after catheter ablation for atrial fibrillation (AF). Pulsed field ablation (PFA) has generated preclinical data suggesting that it selectively targets the myocardium. We sought to characterize extra-atrial injuries after pulmonary vein isolation (PVI) between PFA and thermal ablation methods. METHODS AND RESULTS: Cardiac magnetic resonance (CMR) imaging was performed before, acutely (<3 h) and 3 months post-ablation in 41 paroxysmal AF patients undergoing PVI with PFA (N = 18, Farapulse) or thermal methods (N = 23, 16 radiofrequency, 7 cryoballoon). Oesophageal and aortic injuries were assessed by using late gadolinium-enhanced (LGE) imaging. Phrenic nerve injuries were assessed from diaphragmatic motion on intra-procedural fluoroscopy. Baseline CMR showed no abnormality on the oesophagus or aorta. During ablation procedures, no patient showed phrenic palsy. Acutely, thermal methods induced high rates of oesophageal lesions (43%), all observed in patients showing direct contact between the oesophagus and the ablation sites. In contrast, oesophageal lesions were observed in no patient ablated with PFA (0%, P < 0.001 vs. thermal methods), despite similar rates of direct contact between the oesophagus and the ablation sites (P = 0.41). Acute lesions were detected on CMR on the descending aorta in 10/23 (43%) after thermal ablation, and in 6/18 (33%) after PFA (P = 0.52). CMR at 3 months showed a complete resolution of oesophageal and aortic LGE in all patients. No patient showed clinical complications. CONCLUSION: PFA does not induce any signs of oesophageal injury on CMR after PVI. Due to its tissue selectivity, PFA may improve safety for catheter ablation of AF.

Pulsed field ablation prevents chronic atrial fibrotic changes and restrictive mechanics after catheter ablation for atrial fibrillation.

AIMS: Pulsed field ablation (PFA), a non-thermal ablative modality, may show different effects on the myocardial tissue compared to thermal ablation. Thus, this study aimed to compare the left atrial (LA) structural and mechanical characteristics after PFA vs. thermal ablation. METHODS AND RESULTS: Cardiac magnetic resonance was performed pre-ablation, acutely (<3 h), and 3 months post-ablation in 41 patients with paroxysmal atrial fibrillation (AF) undergoing pulmonary vein (PV) isolation with PFA (n = 18) or thermal ablation (n = 23, 16 radiofrequency ablations, 7 cryoablations). Late gadolinium enhancement (LGE), T2-weighted, and cine images were analysed. In the acute stage, LGE volume was 60% larger after PFA vs. thermal ablation (P < 0.001), and oedema on T2 imaging was 20% smaller (P = 0.002). Tissue changes were more homogeneous after PFA than after thermal ablation, with no sign of microvascular damage or intramural haemorrhage. In the chronic stage, the majority of acute LGE had disappeared after PFA, whereas most LGE persisted after thermal ablation. The maximum strain on PV antra, the LA expansion index, and LA active emptying fraction declined acutely after both PFA and thermal ablation but recovered at the chronic stage only with PFA. CONCLUSION: Pulsed field ablation induces large acute LGE without microvascular damage or intramural haemorrhage. Most LGE lesions disappear in the chronic stage, suggesting a specific reparative process involving less chronic fibrosis. This process may contribute to a preserved tissue compliance and LA reservoir and booster pump functions.

Structural and functional changes in COPD: What we have learned from imaging.

Chronic obstructive pulmonary disease (COPD) is the third leading cause of mortality worldwide. It is a heterogeneous disease involving different components of the lung to varying extents. Developments in medical imaging and image analysis techniques provide new insights in the assessment of the structural and functional changes of the disease. This article reviews the leading imaging techniques: CT and MRI of the lung in research settings and clinical routine. Both visual and quantitative methods are reviewed, emphasizing their relevance to patient phenotyping and outcome prediction.

Quantification of MRI T2-weighted High Signal Volume in Cystic Fibrosis: A Pilot Study.

Background In patients with cystic fibrosis (CF), pulmonary structures with high MRI T2 signal intensity relate to inflammatory changes in the lung and bronchi. These areas of pathologic abnormalities can serve as imaging biomarkers. The feasibility of automated quantification is unknown. Purpose To quantify the MRI T2 high-signal-intensity lung volume and T2-weighted volume-intensity product (VIP) by using a black-blood T2-weighted radial fast spin-echo sequence in participants with CF. Materials and Methods Healthy individuals and study participants with CF were prospectively enrolled between January 2017 and November 2017. All participants underwent a lung MRI protocol including T2-weighted radial fast spin-echo sequence. Participants with CF also underwent pulmonary function tests the same day. Participants with CF exacerbation underwent repeat MRI after their treatment with antibiotics. Two observers supervised automated quantification of T2-weighted high-signal-intensity volume (HSV) and T2-weighted VIP independently, and the average score was chosen as consensus. Statistical analysis used the Mann-Whitney test for comparison of medians, correlations used the Spearman test, comparison of paired medians used the Wilcoxon signed rank test, and reproducibility was evaluated by using intraclass correlation coefficient. Results In 10 healthy study participants (median age, 21 years [age range, 18-27 years]; six men) and 12 participants with CF (median age, 18 years [age range, 9-40 years]; eight men), T2-weighted HSV was equal to 0% and 4.1% (range, 0.1%-17%), respectively, and T2-weighted VIP was equal to 0 msec and 303 msec (range, 39-1012 msec), respectively (P < .001). In participants with CF, T2-weighted HSV or T2-weighted VIP were associated with forced expiratory volume in 1 second percentage predicted (ρ = -0.88 and ρ = -0.94, respectively; P < .001). In six participants with CF exacerbation and follow-up after treatment, a decrease in both T2-weighted HSV and T2-weighted VIP was observed (P = .03). The intra- and interobserver reproducibility of MRI were good (intraclass correlation coefficients, >0.99 and >0.99, respectively). Conclusion In patients with cystic fibrosis (CF), automated quantification of lung MRI high-signal-intensity volume was reproducible and correlated with pulmonary function testing severity, and it improved after treatment for CF exacerbation. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Revel and Chassagnon in this issue.

Interface processes between protected and unprotected areas: A global review and ways forward.

Land-use changes and the expansion of protected areas (PAs) have amplified the interaction between protected and unprotected areas worldwide. In this context, 'interface processes' (human-nature and cross-boundary interactions inside and around PAs) have become central to issues around the conservation of biodiversity and ecosystem services. This scientific literature review aimed to explore current knowledge and research gaps on interface processes regarding terrestrial PAs. At first, 3,515 references related to the topic were extracted through a standardized search on the Web of Science and analyzed with scientometric techniques. Next, a full-text analysis was conducted on a sample of 240 research papers. A keyword analysis revealed a wide diversity of research topics, from 'pure' ecology to sociopolitical research. We found a bias in the geographical distribution of research, with half the papers focusing on eight countries. Additionally, we found that the spatial extent of cross-boundary interactions was rarely assessed, preventing any clear delimitation of PA interactive zones. In the 240 research papers we scanned, we identified 403 processes that were studied. The ecological effects of PAs were well documented and appeared to be positive overall. In contrast, the effects of PAs on local communities were understudied and, according to the literature focusing on these, were very variable according to local contexts. Our findings highlight key research advances on interface processes, especially regarding the ecological outcomes of PAs, the influence of human activities on biodiversity, and PA governance issues. In contrast, main knowledge gaps concern the spatial extent of interactive zones, as well as the interactions between local people and conservation actions and how to promote synergies between them. While the review was limited to terrestrial PAs, its findings allow us to propose research priorities for tackling environmental and socioeconomic challenges in the face of a rapidly changing world.

Volumetric quantification of lung MR signal intensities using ultrashort TE as an automated score in cystic fibrosis.

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 < 0.001) and %MR-LSV and %CT-LAV (ρ = 0.60; p < 0.001). Automated MR metrics correlated to PFTs and Bhalla score (p < 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 > 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.

Towards fully automated third molar development staging in panoramic radiographs.

Staging third molar development is commonly used for age assessment in sub-adults. Current staging techniques are, at most, semi-automated and rely on manual interactions prone to operator variability. The aim of this study was to fully automate the staging process by employing the full potential of deep learning, using convolutional neural networks (CNNs) in every step of the procedure. The dataset used to train the CNNs consisted of 400 panoramic radiographs (OPGs), with 20 OPGs per developmental stage per sex, staged in consensus between three observers. The concepts of transfer learning, using pre-trained CNNs, and data augmentation were used to mitigate the issues when dealing with a limited dataset. In this work, a three-step procedure was proposed and the results were validated using fivefold cross-validation. First, a CNN localized the geometrical center of the lower left third molar, around which a square region of interest (ROI) was extracted. Second, another CNN segmented the third molar within the ROI. Third, a final CNN used both the ROI and the segmentation to classify the third molar into its developmental stage. The geometrical center of the third molar was found with an average Euclidean distance of 63 pixels. Third molars were segmented with an average Dice score of 93%. Finally, the developmental stages were classified with an accuracy of 54%, a mean absolute error of 0.69 stages, and a linear weighted Cohen's kappa coefficient of 0.79. The entire automated workflow on average took 2.72 s to compute, which is substantially faster than manual staging starting from the OPG. Taking into account the limited dataset size, this pilot study shows that the proposed fully automated approach shows promising results compared with manual staging.