CT Imaging Assessment of Response to Treatment in Allergic Bronchopulmonary Aspergillosis in Adults With Bronchial Asthma.

BACKGROUND: One of the major challenges in managing allergic bronchopulmonary aspergillosis remains consistent and reproducible assessment of response to treatment. RESEARCH QUESTION: What are the most relevant changes in CT scan parameters over time for assessing response to treatment? STUDY DESIGN AND METHODS: In this ancillary study of a randomized clinical trial (NEBULAMB), patients with asthma with available CT scan and without exacerbation during a 4-month allergic bronchopulmonary aspergillosis exacerbation treatment period (corticosteroids and itraconazole) were included. Changed CT scan parameters were assessed by systematic analyses of CT scan findings at initiation and end of treatment. CT scans were assessed by two radiologists blinded to the clinical data. Radiologic parameters were determined by selecting those showing significant changes over time. Improvement of at least one, without worsening of the others, defined the radiologic response. Agreement between radiologic changes and clinical and immunologic responses was likewise investigated. RESULTS: Among the 139 originally randomized patients, 132 were included. We identified five CT scan parameters showing significant changes at end of treatment: mucoid impaction extent, mucoid impaction density, centrilobular micronodules, consolidation/ground-glass opacities, and bronchial wall thickening (P < .05). These changes were only weakly associated with one another, except for mucoid impaction extent and density. No agreement was observed between clinical, immunologic, and radiologic responses, assessed as an overall response, or considering each of the parameters (Cohen κ, -0.01 to 0.24). INTERPRETATION: Changes in extent and density of mucoid impaction, centrilobular micronodules, consolidation/ground-glass opacities, and thickening of the bronchial walls were found to be the most relevant CT scan parameters to assess radiologic response to treatment. A clinical, immunologic, and radiologic multidimensional approach should be adopted to assess outcomes, probably with a composite definition of response to treatment. TRIAL REGISTRATION: ClinicalTrials.gov; No.: NCT02273661; URL: www. CLINICALTRIALS: gov).

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.

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.

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.

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.

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.

Allergic bronchopulmonary aspergillosis: A multidisciplinary review.

Allergic bronchopulmonary aspergillosis (ABPA) is a rare disease characterized by a complex allergic inflammatory reaction of airways against Aspergillus affecting patients with chronic respiratory diseases (asthma, cystic fibrosis). Exacerbation is often the way to diagnose ABPA and marks its evolution by its recurrent character leading to cortico-requirement or long-term antifungal treatment. Early diagnosis allows treatment of ABPA at an initial stage, preventing recurrence of exacerbations and long-term complications, mainly represented by bronchiectasis. This review of the literature aims to present the current state of the art in terms of diagnosis and treatment of ABPA from a multidisciplinary perspective. As there is no clinical, biological nor radiological specific sign, diagnostic criteria are regularly revised. They are mainly based on the elevation of total and specific IgE against Aspergillus fumigatus and the presence of suggestive CT abnormalities such as mucoid impaction and consolidations. ABPA management includes eviction of mold and pharmacological therapy. Exacerbations are treated in first line with a moderate dose of oral corticosteroids. Azole antifungal agents represent an alternative for the treatment of exacerbations and are the preferential strategy to reduce the future risk of exacerbations and for corticosteroids sparing. Asthma biologics may be of interest; however, their place remains to be determined. Avoiding complications of ABPA while limiting the side effects of systemic drugs remains a major challenge of ABPA management. Several drugs, including new antifungals and asthma biologics, are currently being tested and may be useful in the future.

Pleural Plaques and the Role of Exposure to Mineral Particles in the Asbestos Post-exposure Survey.

BACKGROUND: Previous studies have inconsistently reported associations between refractory ceramic fibers (RCFs) or mineral wool fibers (MWFs) and the presence of pleural plaques. All these studies were based on chest radiographs, known to be associated with a poor sensitivity for the diagnosis of pleural plaques. RESEARCH QUESTION: Does the risk of pleural plaques increase with cumulative exposure to RCFs, MWFs, and silica? If the risk does increase, do these dose-response relationships depend on the co-exposure to asbestos or, conversely, are the dose-response relationships for asbestos modified by co-exposure to RCFs, MWFs, and silica? STUDY DESIGN AND METHODS: Volunteer workers were invited to participate in a CT scan screening program for asbestos-related diseases in France. Asbestos exposure was assessed by industrial hygienists, and exposure to RCFs, MWFs, and silica was determined by using job-exposure matrices. A cumulative exposure index (CEI) was then calculated for each subject and separately for each of the four mineral particle exposures. All available CT scans were submitted to randomized double reading by a panel of radiologists. RESULTS: In this cohort of 5,457 subjects, significant dose-response relationships were determined after adjustment for asbestos exposure between CEI to RCF or MWF and the risk of PPs (ORs of 1.29 [95% CI, 1.00-1.67] and 1.84 [95% CI, 1.49-2.27] for the highest CEI quartile, respectively). Significant interactions were found between asbestos on one hand and MWF or RCF on the other. INTERPRETATION: This study suggests the existence of a significant association between exposure to RCFs and MWFs and the presence of pleural plaques in a large population previously exposed to asbestos and screened by using CT scans.

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).

Variational inference of fractional Brownian motion with linear computational complexity.

We introduce a simulation-based, amortized Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method. In the first step a graph neural network is trained on simulated data to learn optimized low-dimensional summary statistics of the random walk. In the second step an invertible neural network generates the posterior distribution of the parameters from the learned summary statistics using variational inference. We apply our method to infer the parameters of the fractional Brownian motion model from single trajectories. The computational complexity of the amortized inference procedure scales linearly with trajectory length, and its precision scales similarly to the Cramér-Rao bound over a wide range of lengths. The approach is robust to positional noise, and generalizes to trajectories longer than those seen during training. Finally, we adapt this scheme to show that a finite decorrelation time in the environment can furthermore be inferred from individual trajectories.

Cost-Effectiveness of an Organized Lung Cancer Screening Program for Asbestos-Exposed Subjects.

Background: The National Lung Screening Trial (NLST) and NELSON study opened the debate on the relevance of lung cancer (LC) screening in subjects exposed to occupational respiratory carcinogens. This analysis reported the incremental cost-effectiveness ratios (ICER) of an organized LC screening program for an asbestos-exposed population. Methods: Using Markov modelization, individuals with asbestos exposure were either monitored without intervention or annual low-dose thoracic computed-tomography (LDTCT) scan LC screening. LC incidence came from a prospective observational cohort of subjects with occupational asbestos exposure. The intervention parameters were those of the NLST study. Utilities and LC-management costs came from published reports. A sensitivity analysis evaluated different screening strategies. Results: The respective quality-adjusted life year (QALY) gain, supplementary costs and ICER [95% confidence interval] were: 0.040 [0.010-0.065] QALY, 6900 [3700-11,800] € and 170,000 [75,000-645,000] €/QALY for all asbestos-exposed subjects; and 0.144 [0.071-0.216] QALY, 13,000 [5700-26,800] € and 90,000 [35,000-276,000] €/QALY for smokers with high exposure. When screening was based on biennial LDTCT scans, the ICER was 45,000 [95% CI: 15,000-116,000] €/QALY. Conclusions: Compared to the usual ICER thresholds, biennial LDTCT scan LC screening for smokers with high occupational exposure to asbestos is acceptable and preferable to annual scans.

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.

Improved myocardial scar visualization with fast free-breathing motion-compensated black-blood T1-rho-prepared late gadolinium enhancement MRI.

PURPOSE: Clinical guidelines recommend the use of bright-blood late gadolinium enhancement (BR-LGE) for the detection and quantification of regional myocardial fibrosis and scar. This technique, however, may suffer from poor contrast at the blood-scar interface, particularly in patients with subendocardial myocardial infarction. The purpose of this study was to assess the clinical performance of a two-dimensional black-blood LGE (BL-LGE) sequence, which combines free-breathing T1-rho-prepared single-shot acquisitions with an advanced non-rigid motion-compensated patch-based reconstruction. MATERIALS AND METHODS: Extended phase graph simulations and phantom experiments were performed to investigate the performance of the motion-correction algorithm and to assess the black-blood properties of the proposed sequence. Fifty-one patients (37 men, 14 women; mean age, 55 ± 15 [SD] years; age range: 19-81 years) with known or suspected cardiac disease prospectively underwent free-breathing T1-rho-prepared BL-LGE imaging with inline non-rigid motion-compensated patch-based reconstruction at 1.5T. Conventional breath-held BR-LGE images were acquired for comparison purposes. Acquisition times were recorded. Two readers graded the image quality and relative contrasts were calculated. Presence, location, and extent of LGE were evaluated. RESULTS: BL-LGE images were acquired with full ventricular coverage in 115 ± 25 (SD) sec (range: 64-160 sec). Image quality was significantly higher on free-breathing BL-LGE imaging than on its breath-held BR-LGE counterpart (3.6 ± 0.7 [SD] [range: 2-4] vs. 3.9 ± 0.2 [SD] [range: 3-4]) (P <0.01) and was graded as diagnostic for 44/51 (86%) patients. The mean scar-to-myocardium and scar-to-blood relative contrasts were significantly higher on BL-LGE images (P < 0.01 for both). The extent of LGE was larger on BL-LGE (median, 5 segments [IQR: 2, 7 segments] vs. median, 4 segments [IQR: 1, 6 segments]) (P < 0.01), the method being particularly sensitive in segments with LGE involving the subendocardium or papillary muscles. In eight patients (16%), BL-LGE could ascertain or rule out a diagnosis otherwise inconclusive on BR-LGE. CONCLUSION: Free-breathing T1-rho-prepared BL-LGE imaging with inline motion compensated reconstruction offers a promising diagnostic technology for the non-invasive assessment of myocardial injuries.

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.

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.

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.

Evaluation of the VISAGE basic tool for appearance and ancestry inference using ForenSeq® chemistry on the MiSeq FGx® system.

The possibility of providing investigative leads when conventional DNA identification methods fail to solve a case can be of extreme relevance to law enforcement. Therefore, the forensic genetics community has focused research towards the broadened use of DNA, particularly for prediction of appearance traits, bio-geographical ancestry and age. The VISible Attributes through GEnomics (VISAGE) Consortium expanded the use of DNA phenotyping by developing new molecular and statistical tools for appearance, age and ancestry prediction. The VISAGE basic tool for appearance (EVC) and ancestry (BGA) prediction was initially developed using Ampliseq chemistry, but here is being evaluated using ForenSeq chemistry. The VISAGE basic tool offers a total of 41 EVC and 115 BGA SNPs and thus provides more predictions, i.e., skin color, than achieved with the ForenSeq DNA Signature Prep kit that is based on 24 EVC and 56 BGA SNPs. Five VISAGE laboratories participated in collaborative experiments to provide foreground for developmental validation of the assay. Assessment of assay performance and quality metrics, reproducibility, sensitivity, inhibitor tolerance and species specificity are described. Furthermore, the assay was tested using challenging samples such as mock casework samples and artificially degraded DNA. Two different analysis strategies were applied for this study and output on genotype calls and read depth was compared. Overall, inter-laboratory, inter-method and concordance with publicly available data were analysed and compared. Finally, the results showed a reliable and robust tool, which can be easily applied for laboratories already using a MiSeq FGx with ForenSeq reagents.