Multimodality imaging of acute and chronic pulmonary thromboembolic disease.

Pulmonary embolism (PE) is a pathological entity characterised by venous thromboembolism in the pulmonary arteries. It is a common entity in daily clinical practice and is the third most common cause of cardiovascular death. Correct diagnostic work-up is pivotal to ensure timely institution of appropriate therapy. This requires recognition of the characteristic imaging findings and awareness of the role and peculiarities of the different imaging techniques involved in the diagnostic and therapeutic process. This review aims to showcase the most commonly encountered imaging findings associated with pulmonary thromboembolism for each imaging modality, outline their advantages and disadvantages, and define the specific role of these techniques in the clinical setting. The latest innovations concerning the diagnostic work-up of PE will be also briefly discussed, yielding a perspective on the future developments and challenges that the radiologist will have to face in the coming years.

ERS International Congress 2023: highlights from the Clinical Techniques, Imaging and Endoscopy Assembly.

The Clinical Techniques, Imaging and Endoscopy Assembly is involved in the diagnosis and treatment of several pulmonary diseases, as demonstrated at the 2023 European Respiratory Society (ERS) International Congress in Milan, Italy. From interventional pulmonology, the congress included several exciting results for the use of bronchoscopy in lung cancer, including augmented fluoroscopy, robotic-assisted bronchoscopy and cryobiopsies. In obstructive lung disease, the latest results on bronchoscopic treatment of emphysema with hyperinflation and chronic bronchitis were presented. Research on using cryobiopsies to diagnose interstitial lung disease was further explored, with the aims of elevating diagnostic yield and minimising risk. For imaging, the latest updates in using artificial intelligence to overcome the increased workload of radiologists were of great interest. Novel imaging in sarcoidosis explored the use of magnetic resonance imaging, photon-counting computed tomography and positron emission tomography/computed tomography in the diagnostic work-up. Lung cancer screening is still a hot topic and new results were presented regarding incorporation of biomarkers, identifying knowledge gaps and improving screening programmes. The use of ultrasound in respiratory medicine is an expanding field, which was demonstrated by the large variety in studies presented at the 2023 ERS Congress. Ultrasound of the diaphragm in patients with amyotrophic lateral sclerosis and myasthenia gravis was used to assess movements and predict respiratory fatigue. Furthermore, studies using ultrasound to diagnose or monitor pulmonary disease were presented. The congress also included studies regarding the training and assessment of competencies as an important part of implementing ultrasound in clinical practice.

Impact of ultra-high-resolution imaging of the lungs on perceived diagnostic image quality using photon-counting CT.

OBJECTIVES: To compare clinical image quality and perceived impact on diagnostic interpretation of chest CT findings between ultra-high-resolution photon-counting CT (UHR-PCCT) and conventional high-resolution energy-integrating-detector CT (HR-EIDCT) using visual grading analysis (VGA) scores. MATERIALS AND METHODS: Fifty patients who underwent a UHR-PCCT (matrix 512 × 512, 768 × 768, or 1024 × 1024; FOV average 275 × 376 mm, 120 × 0.2 mm; focal spot size 0.6 × 0.7 mm) between November 2021 and February 2022 and with a previous HR-EIDCT within the last 14 months were included. Four readers evaluated central and peripheral airways, lung vasculature, nodules, ground glass opacities, inter- and intralobular lines, emphysema, fissures, bullae/cysts, and air trapping on PCCT (0.4 mm) and conventional EIDCT (1 mm) via side-by-side reference scoring using a 5-point diagnostic quality score. The median VGA scores were compared and tested using one-sample Wilcoxon signed rank tests with hypothesized median values of 0 (same visibility) and 2 (better visibility on PCCT with impact on diagnostic interpretation) at a 2.5% significance level. RESULTS: Almost all lung structures had significantly better visibility on PCCT compared to EIDCT (p < 0.025; exception for ground glass nodules (N = 2/50 patients, p = 0.157)), with the highest scores seen for peripheral airways, micronodules, inter- and intralobular lines, and centrilobular emphysema (mean VGA > 1). Although better visibility, a perceived difference in diagnostic interpretation could not be demonstrated, since the median VGA was significantly different from 2. CONCLUSION: UHR-PCCT showed superior visibility compared to HR-EIDCT for central and peripheral airways, lung vasculature, fissures, ground glass opacities, macro- and micronodules, inter- and intralobular lines, paraseptal and centrilobular emphysema, bullae/cysts, and air trapping. CLINICAL RELEVANCE STATEMENT: UHR-PCCT has emerged as a promising technique for thoracic imaging, offering improved spatial resolution and lower radiation dose. Implementing PCCT into daily practice may allow better visibility of multiple lung structures and optimization of scan protocols for specific pathology. KEY POINTS: • The aim of this study was to verify if the higher spatial resolution of UHR-PCCT would improve the visibility and detection of certain lung structures and abnormalities. • UHR-PCCT was judged to have superior clinical image quality compared to conventional HR-EIDCT in the evaluation of the lungs. UHR-PCCT showed better visibility for almost all tested lung structures (except for ground glass nodules). • Despite superior image quality, the readers perceived no significant impact on the diagnostic interpretation of the studied lung structures and abnormalities.

Prognostic Value of Chest CT Findings at BOS Diagnosis in Lung Transplant Recipients.

BACKGROUND: Bronchiolitis obliterans syndrome (BOS) after lung transplantation is characterized by fibrotic small airway remodeling, recognizable on high-resolution computed tomography (HRCT). We studied the prognostic value of key HRCT features at BOS diagnosis after lung transplantation. METHODS: The presence and severity of bronchiectasis, mucous plugging, peribronchial thickening, parenchymal anomalies, and air trapping, summarized in a total severity score, were assessed using a simplified Brody II scoring system on HRCT at BOS diagnosis, in a cohort of 106 bilateral lung transplant recipients transplanted between January 2004 and January 2016. Obtained scores were subsequently evaluated regarding post-BOS graft survival, spirometric parameters, and preceding airway infections. RESULTS: A high total Brody II severity score at BOS diagnosis (P = 0.046) and high subscores for mucous plugging (P = 0.0018), peribronchial thickening (P = 0.0004), or parenchymal involvement (P = 0.0121) are related to worse graft survival. A high total Brody II score was associated with a shorter time to BOS onset (P = 0.0058), lower forced expiratory volume in 1 s (P = 0.0006) forced vital capacity (0.0418), more preceding airway infections (P = 0.004), specifically with Pseudomonas aeruginosa (P = 0.002), and increased airway inflammation (P = 0.032). CONCLUSIONS: HRCT findings at BOS diagnosis after lung transplantation provide additional information regarding its underlying pathophysiology and for future prognosis of graft survival.

ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer.

BACKGROUND: Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation. METHODS: A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council. RESULTS: Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements. CONCLUSIONS: This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible.

ERS/ESTS/ESTRO/ESR/ESTI/EFOMP statement on management of incidental findings from low dose CT screening for lung cancer.

BACKGROUND: Screening for lung cancer with low radiation dose computed tomography has a strong evidence base, is being introduced in several European countries and is recommended as a new targeted cancer screening programme. The imperative now is to ensure that implementation follows an evidence-based process that will ensure clinical and cost effectiveness. This European Respiratory Society (ERS) task force was formed to provide an expert consensus for the management of incidental findings which can be adapted and followed during implementation. METHODS: A multi-European society collaborative group was convened. 23 topics were identified, primarily from an ERS statement on lung cancer screening, and a systematic review of the literature was conducted according to ERS standards. Initial review of abstracts was completed and full text was provided to members of the group for each topic. Sections were edited and the final document approved by all members and the ERS Science Council. RESULTS: Nine topics considered most important and frequent were reviewed as standalone topics (interstitial lung abnormalities, emphysema, bronchiectasis, consolidation, coronary calcification, aortic valve disease, mediastinal mass, mediastinal lymph nodes and thyroid abnormalities). Other topics considered of lower importance or infrequent were grouped into generic categories, suitable for general statements. CONCLUSIONS: This European collaborative group has produced an incidental findings statement that can be followed during lung cancer screening. It will ensure that an evidence-based approach is used for reporting and managing incidental findings, which will mean that harms are minimised and any programme is as cost-effective as possible.

Single-cell transcriptomics identifies pathogenic T-helper 17.1 cells and pro-inflammatory monocytes in immune checkpoint inhibitor-related pneumonitis.

BACKGROUND: Immune checkpoint inhibitor (ICI)-related pneumonitis is the most frequent fatal immune-related adverse event associated with programmed cell death protein-1/programmed death ligand-1 blockade. The pathophysiology however remains largely unknown, owing to limited and contradictory findings in existing literature pointing at either T-helper 1 or T-helper 17-mediated autoimmunity. In this study, we aimed to gain novel insights into the mechanisms of ICI-related pneumonitis, thereby identifying potential therapeutic targets. METHODS: In this prospective observational study, single-cell RNA and T-cell receptor sequencing was performed on bronchoalveolar lavage fluid of 11 patients with ICI-related pneumonitis and 6 demographically-matched patients with cancer without ICI-related pneumonitis. Single-cell transcriptomic immunophenotyping and cell fate mapping coupled to T-cell receptor repertoire analyses were performed. RESULTS: We observed enrichment of both CD4+ and CD8+ T cells in ICI-pneumonitis bronchoalveolar lavage fluid. The CD4+ T-cell compartment showed an increase of pathogenic T-helper 17.1 cells, characterized by high co-expression of TBX21 (encoding T-bet) and RORC (ROR-γ), IFN-G (IFN-γ), IL-17A, CSF2 (GM-CSF), and cytotoxicity genes. Type 1 regulatory T cells and naïve-like CD4+ T cells were also enriched. Within the CD8+ T-cell compartment, mainly effector memory T cells were increased. Correspondingly, myeloid cells in ICI-pneumonitis bronchoalveolar lavage fluid were relatively depleted of anti-inflammatory resident alveolar macrophages while pro-inflammatory 'M1-like' monocytes (expressing TNF, IL-1B, IL-6, IL-23A, and GM-CSF receptor CSF2RA, CSF2RB) were enriched compared with control samples. Importantly, a feedforward loop, in which GM-CSF production by pathogenic T-helper 17.1 cells promotes tissue inflammation and IL-23 production by pro-inflammatory monocytes and vice versa, has been well characterized in multiple autoimmune disorders but has never been identified in ICI-related pneumonitis. CONCLUSIONS: Using single-cell transcriptomics, we identified accumulation of pathogenic T-helper 17.1 cells in ICI-pneumonitis bronchoalveolar lavage fluid-a phenotype explaining previous divergent findings on T-helper 1 versus T-helper 17 involvement in ICI-pneumonitis-,putatively engaging in detrimental crosstalk with pro-inflammatory 'M1-like' monocytes. This finding yields several novel potential therapeutic targets for the treatment of ICI-pneumonitis. Most notably repurposing anti-IL-23 merits further research as a potential efficacious and safe treatment for ICI-pneumonitis.

Lung Aeration in COVID-19 Pneumonia by Ultrasonography and Computed Tomography.

We conducted a prospective single-center observational study to determine lung ultrasound reliability in assessing global lung aeration in 38 hospitalized patients with non-critical COVID-19. On admission, fixed chest CT scans using visual (CTv) and software-based (CTs) analyses along with lung ultrasound imaging protocols and scoring systems were applied. The primary endpoint was the correlation between global chest CTs score and global lung ultrasound score. The secondary endpoint was the association between radiographic features and clinical disease classification or laboratory indices of inflammation. Bland−Altman analysis between chest CT scores obtained visually (CTv) or using software (CTs) indicated that only 1 of the 38 paired measures was outside the 95% limits of agreement (−4 to +4 score). Global lung ultrasound score was highly and positively correlated with global software-based CTs score (r = 0.74, CI = 0.55−0.86; p < 0.0001). Significantly higher median CTs score (p = 0.01) and lung ultrasound score (p = 0.02) were found in severe compared to moderate COVID-19. Furthermore, we identified significantly lower (p < 0.05) lung ultrasound and CTs scores in those patients with a more severe clinical condition manifested by SpO2 < 92% and C-reactive protein > 58 mg/L. We concluded that lung ultrasound is a reliable bedside clinical tool to assess global lung aeration in hospitalized non-critical care patients with COVID-19 pneumonia.

Value of [68Ga]Ga-somatostatin receptor PET/CT in the grading of pulmonary neuroendocrine (carcinoid) tumours and the detection of disseminated disease: single-centre pathology-based analysis and review of the literature.

BACKGROUND: Although most guidelines suggest performing a positron emission tomography/computed tomography (PET/CT) with somatostatin receptor (SSTR) ligands for staging of pulmonary carcinoid tumours (PC), only a limited number of studies have evaluated the role of this imaging tool in this specific patient population. The preoperative differentiation between typical carcinoid (TC) and atypical carcinoid (AC) and the extent of dissemination (N/M status) are crucial factors for treatment allocation and prognosis of these patients. Therefore, we performed a pathology-based retrospective analysis of the value of SSTR PET/CT in tumour grading and detection of nodal and metastatic involvement of PC and compared this with the previous literature and with [18F]FDG PET/CT in a subgroup of patients. METHODS: SSTR PET/CT scans performed between January 2007 and May 2020 in the context of PC were included. If available, [18F]FDG PET/CT images were also evaluated. The maximum standardized uptake (SUVmax) values of the primary tumour, of the pathologically examined hilar and mediastinal lymph node stations, as well as of the distant metastases, were recorded. Tumoural SUVmax values were related to the tumour type (TC versus AC) for both SSTR and [18F]FDG PET/CT in diagnosing and differentiating both tumour types. Nodal SUVmax values were compared to the pathological status (N+ versus N-) to evaluate the diagnostic accuracy of SSTR PET/CT in detecting lymph node involvement. Finally, a mixed model analysis of all pathologically proven distant metastatic lesions was performed. RESULTS: A total of 86 SSTR PET/CT scans performed in 86 patients with PC were retrospectively analysed. [18F]FDG PET/CT was available in 46 patients. Analysis of the SUVmax values in the primary tumour showed significantly higher SSTR uptake in TC compared with AC (median SUVmax 18.4 vs 3.8; p = 0.003) and significantly higher [18F]FDG uptake in AC compared to TC (median SUVmax 5.4 vs 3.5; p = 0.038). Receiver operating characteristic (ROC) curve analysis resulted in an area under the curve (AUC) of 0.78 for the detection of TC on SSTR PET/CT and of 0.73 for the detection of AC on [18F]FDG PET/CT. A total of 267 pathologically evaluated hilar and mediastinal lymph node stations were analysed. ROC analysis of paired SSTR/[18F]FDG SUVmax values for the detection of metastasis of TC in 83 lymph node stations revealed an AUC of 0.91 for SSTR PET/CT and of 0.74 for [18F]FDG PET/CT (difference 0.17; 95% confidence interval - 0.03 to 0.38; p = 0.10). In a sub-cohort of 10 patients with 12 distant lesions that were pathologically examined due to a suspicious aspect on SSTR PET/CT, a positive predictive value (PPV) of 100% was observed. CONCLUSION: Our findings confirm the higher SSTR ligand uptake in TC compared to AC and vice versa for [18F]FDG uptake. More importantly, we found a good diagnostic performance of SSTR PET/CT for the detection of hilar and mediastinal lymph node metastases of TC. Finally, a PPV of 100% for SSTR PET/CT was found in a small sub-cohort of patients with pathologically investigated distant metastatic lesions. Taken together, SSTR PET/CT has a very high diagnostic value in the TNM assessment of pulmonary carcinoids, particularly in TC, which underscores its position in European guidelines.

Prospective longitudinal evaluation of hospitalised COVID-19 survivors 3 and 12 months after discharge.

Background: Long-term outcome data of coronavirus disease 2019 (COVID-19) survivors are needed to understand their recovery trajectory and additional care needs. Methods: A prospective observational multicentre cohort study was carried out of adults hospitalised with COVID-19 from March through May 2020. Workup at 3 and 12 months following admission consisted of clinical review, pulmonary function testing, 6-min walk distance (6MWD), muscle strength, chest computed tomography (CT) and quality of life questionnaires. We evaluated factors correlating with recovery by linear mixed effects modelling. Results: Of 695 patients admitted, 299 and 226 returned at 3 and 12 months, respectively (median age 59 years, 69% male, 31% severe disease). About half and a third of the patients reported fatigue, dyspnoea and/or cognitive impairment at 3 and 12 months, respectively. Reduced 6MWD and quadriceps strength were present in 20% and 60% at 3 months versus 7% and 30% at 12 months. A high anxiety score and body mass index correlated with poor functional recovery. At 3 months, diffusing capacity for carbon monoxide (D LCO) and total lung capacity were below the lower limit of normal in 35% and 18%, decreasing to 21% and 16% at 12 months; predictors of poor D LCO recovery were female sex, pre-existing lung disease, smoking and disease severity. Chest CT improved over time; 10% presented non-progressive fibrotic changes at 1 year. Conclusion: Many COVID-19 survivors, especially those with severe disease, experienced limitations at 3 months. At 1 year, the majority showed improvement to almost complete recovery. To identify additional care or rehabilitation needs, we recommend a timely multidisciplinary follow-up visit following COVID-19 admission.

Detection of pulmonary nodules with scoutless fixed-dose ultra-low-dose CT: a prospective study.

OBJECTIVES: To determine the accuracy of scoutless, fixed-dose ultra-low-dose (ULD) CT compared to standard-dose (SD) CT for pulmonary nodule detection and semi-automated nodule measurement, across different patient sizes. METHODS: Sixty-three patients underwent ULD and SD CT. Two readers examined all studies visually and with computer-aided detection (CAD). Nodules detected on SD CT were included in the reference standard by consensus and stratified into 4 categories (nodule category, NODCAT) from the Dutch-Belgian Lung Cancer Screening trial (NELSON). Effects of NODCAT and patient size on nodule detection were determined. For each nodule, volume and diameter were compared between both scans. RESULTS: The reference standard comprised 173 nodules. For both readers, detection rates on ULD versus SD CT were not significantly different for NODCAT 3 and 4 nodules > 50 mm3 (reader 1: 93% versus 89% (p = 0.257); reader 2: 96% versus 98% (p = 0.317)). For NODCAT 1 and 2 nodules < 50 mm3, detection rates on ULD versus SD CT dropped significantly (reader 1: 66% versus 80% (p = 0.023); reader 2: 77% versus 87% (p = 0.039)). Body mass index and chest circumference did not influence nodule detectability (p = 0.229 and p = 0.362, respectively). Calculated volumes and diameters were smaller on ULD CT (p < 0.0001), without altering NODCAT (84% agreement). CONCLUSIONS: Scoutless ULD CT reliably detects solid lung nodules with a clinically relevant volume (> 50 mm3) in lung cancer screening, irrespective of patient size. Since detection rates were lower compared to SD CT for nodules < 50 mm3, its use for lung metastasis detection should be considered on a case-by-case basis. KEY POINTS: • Detection rates of pulmonary nodules > 50 mm3are not significantly different between scoutless ULD and SD CT (i.e. volumes clinically relevant in lung cancer screening based on the NELSON trial), but were different for the detection of nodules < 50 mm3(i.e. volumes still potentially relevant in lung metastasis screening). • Calculated nodule volumes were on average 0.03 mL or 9% smaller on ULD CT, which is below the 20-25% interscan variability previously reported with software-based volumetry. • Even though a scoutless, fixed-dose ULD CT protocol was used (CTDIvol0.15 mGy), pulmonary nodule detection was not influenced by patient size.

Radiological findings in low-dose CT for COVID-19 pneumonia in 182 patients: Correlation of signs and severity with patient outcome.

ABSTRACT: To characterize computed tomography (CT) findings of coronavirus disease 2019 (COVID-19) pneumonia and their value in outcome prediction.Chest CTs of 182 patients with a confirmed diagnosis of COVID-19 infection by real-time reverse transcription polymerase chain reaction were evaluated for the presence of CT-abnormalities and their frequency. Regarding the patient outcome each patient was categorized in 5 progressive stages and the duration of hospitalization was determined. Regression analysis was performed to find which CT findings are predictive for patient outcome and to assess prognostic factors for the hospitalization duration.Multivariate statistical analysis confirmed a higher age (OR = 1.023, P  =  .025), a higher total visual severity score (OR = 1.038, P  =  .002) and the presence of crazy paving (OR = 2.160, P  =  .034) as predictive parameters for patient outcome. A higher total visual severity score (+0.134 days; P  =  .012) and the presence of pleural effusion (+13.985 days, P  =  0.005) were predictive parameters for a longer hospitalization duration. Moreover, a higher sensitivity of chest CT (false negatives 10.4%; true positives 78.6%) in comparison to real-time reverse transcription polymerase chain reaction was obtained.An increasing percentage of lung opacity as well as the presence of crazy paving and a higher age are associated with a worse patient outcome. The presence of a higher total visual severity score and pleural effusion are significant predictors for a longer hospitalization duration. These results are underscoring the value of chest CT as a diagnostic and prognostic tool in the pandemic outbreak of COVID-19, to facilitate fast detection and to preserve the limited (intensive) care capacity only for the most vulnerable patients.

CT-Guided Transthoracic Biopsy of Lung Lesions Using a Non-Coaxial Biopsy Needle Technique: CT Characteristics Predictive for Diagnostic Accuracy and Pneumothorax.

OBJECTIVES: To analyze computed tomography (CT) characteristics predictive for diagnostic accuracy and pneumothorax in CT fluoroscopy-guided transthoracic biopsy (CTF-TTB) of lung lesions using non-coaxial biopsy needle technique. METHODS: Retrospectively 274 lung lesion biopsies with confirmed histology were included in our study. CTF-TTB was done using an 18-gauge non-coaxial cutting needle. Diagnostic accuracy rates were calculated per lesion size and CT and procedural characteristics were evaluated for their predictive value regarding diagnostic accuracy and development of pneumothorax (maximal nodule diameter, distance to pleura, location per lung segment, nodule composition, benign versus malignant histology, and number of specimens). RESULTS: Overall diagnostic accuracy of CTF-TTB was high (93%). Diagnostic accuracy for lesions ≤10 mm was 81%. Maximal nodule diameter was the only predictive CT characteristic for diagnostic success (p = 0.03). Pneumothorax occurred in 27%. Distance of lesion to pleura was the only risk factor for pneumothorax (p < 0.00001). Pneumothorax rates were significantly lower in subpleural lesions (14%) compared to those located 1-10 mm (47%), 10-20 mm (33%), and >20 mm from pleura (29%). CONCLUSIONS: High diagnostic accuracy rates were achieved with CTF-TTB using non-coaxial biopsy technique, even for lesions ≤10 mm. Pneumothorax rates were comparable with other studies. Lesion size was the only predictive CT characteristic for diagnostic accuracy. Distance to pleura was the only risk factor for pneumothorax.

Comparing Visual Scoring of Lung Injury with a Quantifying AI-Based Scoring in Patients with COVID-19.

OBJECTIVES: Fast diagnosis of Coronavirus Disease 2019 (COVID-19), and the detection of high-risk patients are crucial but challenging in the pandemic outbreak. The aim of this study was to evaluate if deep learning-based software correlates well with the generally accepted visual-based scoring for quantification of the lung injury to help radiologist in triage and monitoring of COVID-19 patients. MATERIALS AND METHODS: In this retrospective study, the lobar analysis of lung opacities (% opacities) by means of a prototype deep learning artificial intelligence (AI)-based software was compared to visual scoring. The visual scoring system used five categories (0: 0%, 1: 0-5%, 2: 5-25%, 3: 25-50%, 4: 50-75% and 5: >75% involvement). The total visual lung injury was obtained by the sum of the estimated grade of involvement of each lobe and divided by five. RESULTS: The dataset consisted of 182 consecutive confirmed COVID-19 positive patients with a median age of 65 ± 16 years, including 110 (60%) men and 72 (40%) women. There was a correlation coefficient of 0.89 (p < 0.001) between the visual and the AI-based estimates of the severity of lung injury. CONCLUSION: The study indicates a very good correlation between the visual scoring and AI-based estimates of lung injury in COVID-19.

Performance of Low-Dose Chest CT as a Triage Tool for Suspected COVID-19 Patients.

PURPOSE: To investigate the role of low-dose chest computed tomography (CT) imaging in the triage of patients suspected of coronavirus disease 2019 (COVID-19) in an emergency setting. MATERIALS AND METHODS: Data from 610 patients admitted to our emergency unit from March 20, 2020, until April 11, 2020, with suspicion of COVID-19 were collected. Diagnostic values of low-dose chest CT for COVID-19 were calculated using consecutive reverse-transcription polymerase chain reaction (RT-PCR) tests and bronchoalveolar lavage (BAL) as reference. Comparative analysis of the 199 COVID-19 positive versus 411 COVID-19 negative patients was done with identification of risk factors and predictors of worse outcome. RESULTS: Sensitivity and specificity of low-dose CT for the diagnosis of COVID-19 respectively ranged from 75% (150/199) to 88% (175/199) and 94% (386/411) to 99% (386/389), depending on the inclusion of inconclusive results. On multivariate analysis, a higher body mass index (BMI), fever, and dyspnea on admission were risk factors for COVID-19 (all p-values < 0.05). The mortality rate was 12.6% (25/199). Higher age and high levels of C-reactive protein (CRP) and D-dimers were predictors of worse outcome (all p-values < 0.05). CONCLUSION: Low-dose chest CT has a high specificity and a moderate to high sensitivity in symptomatic patients with suspicion of COVID-19 and could be used as an effective tool in setting of triage in high-prevalence areas.

Discriminating mild from critical COVID-19 by innate and adaptive immune single-cell profiling of bronchoalveolar lavages.

How the innate and adaptive host immune system miscommunicate to worsen COVID-19 immunopathology has not been fully elucidated. Here, we perform single-cell deep-immune profiling of bronchoalveolar lavage (BAL) samples from 5 patients with mild and 26 with critical COVID-19 in comparison to BALs from non-COVID-19 pneumonia and normal lung. We use pseudotime inference to build T-cell and monocyte-to-macrophage trajectories and model gene expression changes along them. In mild COVID-19, CD8+ resident-memory (TRM) and CD4+ T-helper-17 (TH17) cells undergo active (presumably antigen-driven) expansion towards the end of the trajectory, and are characterized by good effector functions, while in critical COVID-19 they remain more naïve. Vice versa, CD4+ T-cells with T-helper-1 characteristics (TH1-like) and CD8+ T-cells expressing exhaustion markers (TEX-like) are enriched halfway their trajectories in mild COVID-19, where they also exhibit good effector functions, while in critical COVID-19 they show evidence of inflammation-associated stress at the end of their trajectories. Monocyte-to-macrophage trajectories show that chronic hyperinflammatory monocytes are enriched in critical COVID-19, while alveolar macrophages, otherwise characterized by anti-inflammatory and antigen-presenting characteristics, are depleted. In critical COVID-19, monocytes contribute to an ATP-purinergic signaling-inflammasome footprint that could enable COVID-19 associated fibrosis and worsen disease-severity. Finally, viral RNA-tracking reveals infected lung epithelial cells, and a significant proportion of neutrophils and macrophages that are involved in viral clearance.

Methodology to create 3D models of COVID-19 pathologies for virtual clinical trials.

Purpose: We describe the creation of computational models of lung pathologies indicative of COVID-19 disease. The models are intended for use in virtual clinical trials (VCT) for task-specific optimization of chest x-ray (CXR) imaging. Approach: Images of COVID-19 patients confirmed by computed tomography were used to segment areas of increased attenuation in the lungs, all compatible with ground glass opacities and consolidations. Using a modeling methodology, the segmented pathologies were converted to polygonal meshes and adapted to fit the lungs of a previously developed polygonal mesh thorax phantom. The models were then voxelized with a resolution of 0.5 × 0.5 × 0.5 mm 3 and used as input in a simulation framework to generate radiographic images. Primary projections were generated via ray tracing while the Monte Carlo transport code was used for the scattered radiation. Realistic sharpness and noise characteristics were also simulated, followed by clinical image processing. Example images generated at 120 kVp were used for the validation of the models in a reader study. Additionally, images were uploaded to an Artificial Intelligence (AI) software for the detection of COVID-19. Results: Nine models of COVID-19 associated pathologies were created, covering a range of disease severity. The realism of the models was confirmed by experienced radiologists and by dedicated AI software. Conclusions: A methodology has been developed for the rapid generation of realistic 3D models of a large range of COVID-19 pathologies. The modeling framework can be used as the basis for VCTs for testing detection and triaging of COVID-19 suspected cases.

Assembly 14: clinical techniques, imaging and endoscopy.

Meet @EuroRespSoc Assembly 14: clinical techniques, imaging and endoscopy http://bit.ly/2oAf65R.

An unusual presentation of a more common disease entity.

Beware unusual presentations of more common disease entities, as in this interactive case report http://ow.ly/qj7f30eVFsp.