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Lung cancer is the leading cause of cancer death worldwide. The absence of symptoms in early-stage (I/II) disease, when curative treatment is possible, results in >70% of cases being diagnosed at late stage (III/IV), when treatment is rarely curative. This contributes greatly to the poor prognosis of lung cancer, which sees only 16.2% of individuals diagnosed with the disease alive at 5 years. Early detection is key to improving lung cancer survival outcomes. As a result, there has been longstanding interest in finding a reliable screening test. After little success with chest radiography and sputum cytology, in 2011 the United States National Lung Screening Trial demonstrated that annual low-dose computed tomography (LDCT) screening reduced lung cancer-specific mortality by 20%, when compared with annual chest radiography. In 2020, the NELSON study demonstrated an even greater reduction in lung cancer-specific mortality for LDCT screening at 0, 1, 3 and 5.5 years of 24% in men, when compared to no screening. Despite these impressive results, a call to arms in the 2017 European position statement on lung cancer screening (LCS) and the widespread introduction across the United States, there was, until recently, no population-based European national screening programme in place. We address the potential barriers and outstanding concerns including common screening foes, such as false-positive tests, overdiagnosis and the negative psychological impact of screening, as well as others more unique to LDCT LCS, including appropriate risk stratification of potential participants, radiation exposure and incidental findings. In doing this, we conclude that whilst the evidence generated from ongoing work can be used to refine the screening process, for those risks which remain, appropriate and acceptable mitigations are available, and none should serve as barriers to the implementation of national unified LCS programmes across Europe and beyond.

To further define the epilepsy phenotype in a cohort of children with 15q13.3 microdeletion syndrome.We retrospectively reviewed the phenotypic spectrum of all children aged18 years with epilepsy and 15q13.3 microdeletion syndrome.Thirteen children were included, 69% were female. The median age of children in the cohort was 12 years (age range: 3 years-15 years). Median age at seizure onset was 4 years. Eleven children (85%) had intellectual disability. Nine of 13 children (69%) had a history of typical absence seizures with median age of onset at 5 years (2 had absence status epilepticus). Thirty-one percent (4/13) had focal with impaired awareness non-motor onset seizures. ILAE recognized absence epilepsy syndromes were diagnosed in 6/13 (46%). The remainder were classified as having genetic generalized epilepsies with overlap clinical features, combined or focal epilepsies. Electroencephalogram in the cohort showed generalized (85%) and focal epileptiform discharges (62%) and posterior dominant rhythm slowing (33%). One child had electrical status epilepticus of sleep. Neuroimaging was performed in 5 children (38%) and revealed abnormal findings in 3. Seizures were drug resistant in a third of the cohort. Valproate resulted in seizure freedom in 5 (42%). Oxcarbazepine caused clinical worsening in one child with combined seizure types. Two children tried cannabidiol and one tried the ketogenic diet; neither was effective.The epilepsy phenotype in children with 15q13.3 microdeletion syndrome is defined by childhood onset absence seizures, and may have atypical features such as, early onset absences, persistence into adolescence, status epilepticus, intellectual disability and treatment resistance. Focal seizures and focal EEG findings may be observed and should be treated cautiously, given the possibility of combined seizure types. Valproate appeared effective, although other treatments must be explored further.

In patients with IPF, this study aimed (i) to examine the relationship between serial change in CT parameters of lung volume and lung function, (ii) to identify the prognostic value of serial change in CT parameters of lung volume, and (iii) to define a threshold for serial change in CT markers of lung volume that optimally captures disease progression. Serial CTs were analysed for progressive volume loss or fibrosis progression in 81 IPF patients (66 males, median age = 67 years) with concurrent forced vital capacity (FVC) (median follow-up 12 months, range 6–23 months). Serial CT measurements of volume loss comprised oblique fissure posterior retraction distance (OFPRD), aortosternal distance (ASD), lung height corrected for body habitus (LH), and automated CT-derived total lung volumes (ALV) (measured using commercially available software). Fibrosis progression was scored visually. Serial changes in CT markers and FVC were compared using regression analysis, and evaluated against mortality using Cox proportional hazards. There were 58 deaths (72%, median survival = 17 months). Annual % change in ALV was most significantly related to annual % change in FVC (R2 = 0.26, p

Delivering lung cancer care during the COVID-19 pandemic has posed significant and ongoing challenges. There is a lack of published COVID-19 and lung cancer evidence-based reviews, including for the whole patient pathway. We searched for COVID-19 and lung cancer publications and brought together a multidisciplinary group of stakeholders to review and comment on the evidence and challenges. A rapid review of the literature was undertaken up to 28 October 2020, producing 144 papers, with 113 full texts screened. We focused on new primary data collection (qualitative or quantitative evidence) and excluded case reports, editorials and commentaries. Following exclusions, 15 published papers were included in the review and are summarised. They included one qualitative paper and 14 quantitative studies (surveys or cohort studies), with a total of 2295 lung cancer patients data included (mean study size 153 patients; range 7–803). Review of current evidence and commentary included awareness and help-seeking; lung cancer screening; primary care assessment and referral; diagnosis and treatment in secondary care, including oncology and surgery; patient experience and palliative care. Cross-cutting themes and challenges were identified using qualitative methods for patients, healthcare professionals and service delivery, with a clear need for continued studies to guide evidence-based decision-making.

Early detection and diagnosis of coronary artery disease could reduce the risk of developing a heart attack. The coronary arteries are optimally visualised using computed tomography coronary angiography (CTCA) imaging. These images are reviewed by specialist radiologists who evaluate the coronary arteries for potential narrowing. A lack of radiologists in the UK is a constraint to timely diagnosis of coronary artery disease, particularly in the acute accident and emergency department setting. The development of automated methods by which coronary artery narrowing can be identified rapidly and accurately are therefore timely. Such complex computer based tools also need to be sufficiently computationally efficient that they can run on servers typically found in hospital settings, where graphical processing units for example are unavailable. We propose a fully automatic two-dimensional Unet model to segment the aorta and coronary arteries on CTCA images. Two models are trained to segment two regions of interest, (1) the aorta and the coronary arteries or (2) the coronary arteries alone. Our method achieves 91.20% and 88.80% dice similarity coefficient accuracy on regions of interest 1 and 2 respectively. Compared with a semi-automatic segmentation method, our model performs better when segmenting the coronary arteries alone. The performance of the proposed method is comparable to existing published two-dimensional or three-dimensional deep learning models. Importantly, the algorithmic and graphical processing unit memory efficiencies are maintained such that the model can be deployed without requiring graphical processing units, and therefore can be used in a hospital setting.

Objective: There are limited data on tumour growth or pathologic upstaging in patients with early-stage lung cancer awaiting lung resection. We aimed to evaluate whether waiting times on the current lung cancer treatment pathway were associated with significant tumour growth or pathologic upstaging. Methods: This is a retrospective observational study of a consecutive series of patients with early-stage, non-small cell lung cancer who underwent resection for lung cancer. The difference between tumour size at diagnostic and preoperative computed tomography (CT) scans was calculated. Significant tumour growth was defined as a diameter increase of ⩾5 mm or ⩾20%. The time intervals between baseline and repeat CT (CT-int) and between baseline CT and date of surgery (Surg-int), as well as other potential clinical and pathologic prognostic factors, were compared between upstaged and nonupstaged patients. Results: There were 121 patients identified. Fifty-four patients (44.6%) had tumour growth ⩾5 mm and 27 patients (22%) had tumour growth ⩾20%. Median CT-int and Surg-int were 2.4 and 2.6 months, respectively. Forty-four patients (36%) were upstaged at surgery due to new lymph node involvement (n = 19), pleural invasion (n = 12), satellite nodules (n = 4), or increase in tumour diameter (n = 9). There was a marginal, but statistically insignificant, difference in median CT intervals in patients who had tumour growth Conclusion: Current cancer pathway waiting times are not associated with significant tumour growth or pathologic upstaging in this cohort.

The Lung Screen Uptake Trial tested a novel invitation strategy to improve uptake and reduce socioeconomic and smoking-related inequalities in lung cancer screening (LCS) participation. It provides one of the first UK-based ‘real-world’ LCS cohorts. Of 2012 invited, 1058 (52.6%) attended a ‘lung health check’. 768/996 (77.1%) in the present analysis underwent a low-dose CT scan. 92 (11.9%) and 33 (4.3%) participants had indeterminate pulmonary nodules requiring 3-month and 12-month surveillance, respectively; 36 lung cancers (4.7%) were diagnosed (median follow-up: 1044 days). 72.2% of lung cancers were stage I/II and 79.4% of non-small cell lung cancer had curative-intent treatment.

Rationale: Individuals eligible for lung cancer screening (LCS) by low-dose computed tomography (LDCT) are also at risk of chronic obstructive pulmonary disease (COPD) due to age and smoking exposure. Whether the LCS episode is useful for early detection of COPD is not well established. Objectives: To explore associations between symptoms, comorbidities, spirometry, and emphysema in participants enrolled in the Lung Screen Uptake Trial. Methods: This cross-sectional study was a prespecified analysis nested within Lung Screen Uptake Trial, which was a randomized study testing the impact of differing invitation materials on attendance of 60- to 75-year-old smokers and ex-smokers to a “lung health check” between November 2015 and July 2017. Participants with a smoking history ≥30 pack-years and who quit ≤15 years ago, or meeting a lung cancer risk of ≥1.51% via the Prostate Lung Colorectal Ovarian model or ≥2.5% via the Liverpool Lung Project model, were offered LDCT. COPD was defined and classified according to the GOLD (Global Initiative for Obstructive Lung Disease) criteria using prebronchodilator spirometry. Analyses included the use of descriptive statistics, chi-square tests to examine group differences, and univariable and multivariable logistic regression to explore associations between symptom prevalence, airflow limitation, and visually graded emphysema. Results: A total of 560 of 986 individuals included in the analysis (57%) had prebronchodilator spirometry consistent with COPD; 67% did not have a prior history of COPD and were termed “undiagnosed.” Emphysema prevalence in those with known and “undiagnosed” COPD was 73% and 68%, respectively. A total of 32% of those with “undiagnosed COPD” had no emphysema on LDCT. Inhaler use and symptoms were more common in the “known” than the “undiagnosed” COPD group (63% vs. 33% with persistent cough [P

Introduction Longitudinal data on management and progression of type 2 diabetes mellitus (T2DM) in India are scarce. LANDMARC (CTRI/2017/05/008452), first‐of‐its‐kind, pan‐India, prospective, observational study aimed to evaluate real‐world patterns and management of T2DM over 3 years. Methods Adults (≥25 to ≤60 years old at T2DM diagnosis; diabetes duration ≥2 years at enrolment; controlled/uncontrolled on ≥2 anti‐diabetic agents) were enrolled. The first‐year trends for glycaemic control, therapy and diabetic complications, including those from metropolitan and non‐metropolitan cities are reported here. Results Of 6236 enrolled participants, 5654 completed 1 year in the study. Although the overall mean glycated haemoglobin (HbA1c) improved by 0.5% (baseline: 8.1%) at 1 year, only 20% of the participants achieved HbA1c 3 vs. ≤3 OADs. Conclusions First‐year trends of the LANDMARC study offer insights into real‐world disease progression, suggesting the need for controlling risk factors and timely treatment intensification in people with T2DM., The literature describing the burden of T2DM in India are sparse. The present study reports 1‐year trend from LANDMARC study, a nationwide, prospective, longitudinal study planned for 3 years. This study highlights some important observations in terms of diabetes complications, treatment patterns and glycaemic control in T2DM patients from India and also emphasizes the disease burden in metropolitan and non‐metropolitan cities. This study revealed that the burden of uncontrolled T2DM is high in India with only 20% of participants achieving glycaemic control in 1 year (HbA1c

As the digital information technology domain is growing unprecedently, the process of making the devices mimic human like actions has gained an increased research attention. One of the main features of human like system is the human emotion or sentiment detection. Online shopping has made it easy for everyone in the world to buy different varieties of products from a single place. It also gives the opportunity for them to try new products. While trying to buy new products, people check for the reviews and ratings of those products given by the other customers. Those reviews and ratings can be used to determine the sentimentality of users, who have bought those products by using text mining techniques and classify them either as positive or negative reviews. To analyze these data, the proposed research work has used both Naive Bayes and linear regression algorithms. In our analysis, the accuracy rate of both algorithms is checked.

Background: CHEST guidelines on lung cancer screening during the COVID-19 pandemic1 support delaying interval scans for 3-6 months. There is a concern that progression during this time could result in a higher stage at diagnosis. To determine the safety of this approach, we investigated whether time to interval scan was associated with disease stage at diagnosis. Method: The SUMMIT Study aims to assess the implementation of low-dose CT for lung cancer screening in a high-risk population and to validate a multi-cancer early detection blood test. Indeterminate nodules are followed up at 3 months. Participants with interval scans delayed to ≥4 months due to the pandemic and a comparison pre-pandemic group with scans performed at the target timeframe of 3-4 months were identified. Outcomes from cases referred for definitive assessment following interval scan were analysed. Results: Conclusion: Preliminary data does not suggest a shift to higher stage at diagnosis from delayed interval scans performed at 4-6 months. Whilst this must be validated with additional cases, if confirmed this evidence supports the safety of the CHEST guidelines for lung cancer screening during the COVID pandemic. 1. Management of Lung Nodules and Lung Cancer Screening During the COVID-19 Pandemic CHEST 2020

Previously, naltrindole (NTI; selective delta opioid receptor antagonist) was shown to improve post-reperfused cardiac function and reduced infarct size when given prior to ischemia (I)/ reperfusion (R) in ex-vivo rat hearts. Conversely, naloxone (NX, broad-spectrum opioid antagonist) and nor-binaltrophine (BNI, selective kappa receptor antagonist) were similar to control hearts. In this study, the effects of NTI derivatives naltriben (NTB, delta receptor antagonist) and guanidonaltrindole (GNTI, kappa receptor antagonist) were compared to NTI, BNI, and NX. Isolated hearts from male SD rats (300g) were subjected to global I(30min)/R(45min). Treatments were given 5 min before I (preconditioning) and during the first 5 min of R. Left ventricular (LV) cardiac function was measured using a pressure transducer. At the end of reperfusion, infarcted heart tissue was compared to total tissue weight. Data were evaluated using ANOVA. As shown in Table 1, NTI, NTB, and GNTI significantly improved post-reperfused cardiac function and reduced infarct size compared to control hearts. NTI and NTB elicited direct effects on cardiac function when given during preconditioning in contrast to all other study groups and were the most robust at reducing infarct size and restoring post reperfusion cardiac function. The negative inotropic effects of NTI and NTB were correlated with a decrease in the rise of ischemic pressure. GNTI also elicited significant improvement in post-reperfused cardiac function and reduction of infarct size compared to BNI which suggests a separate cardioprotective mechanism that this NTI derivative may exert in contrast to kappa opioid receptor inhibition. Results suggest that NTI and derivatives, GNTI and NTB, are cardioprotective against I/R injury resulting in reduced ischemic peak pressure (NTI/NTB) and infarct size. In future studies, we will examine the mechanism of the protective effects of NTI and derivatives in hearts subjected to I/R injury.

Using publicly available data to determine the performance of methodological contributions is important as it facilitates reproducibility and allows scrutiny of the published results. In lung nodule classification, for example, many works report results on the publicly available LIDC dataset. In theory, this should allow a direct comparison of the performance of proposed methods and assess the impact of individual contributions. When analyzing seven recent works, however, we find that each employs a different data selection process, leading to largely varying total number of samples and ratios between benign and malignant cases. As each subset will have different characteristics with varying difficulty for classification, a direct comparison between the proposed methods is thus not always possible, nor fair. We study the particular effect of truthing when aggregating labels from multiple experts. We show that specific choices can have severe impact on the data distribution where it may be possible to achieve superior performance on one sample distribution but not on another. While we show that we can further improve on the state-of-the-art on one sample selection, we also find that on a more challenging sample selection, on the same database, the more advanced models underperform with respect to very simple baseline methods, highlighting that the selected data distribution may play an even more important role than the model architecture. This raises concerns about the validity of claimed methodological contributions. We believe the community should be aware of these pitfalls and make recommendations on how these can be avoided in future work., Accepted at PRIME, MICCAI 2021

Introduction Longitudinal data on progression, complications, and management of type 2 diabetes mellitus (T2DM) across India are scarce. LANDMARC (CTRI/2017/05/008452), the first pan‐India, longitudinal, prospective, observational study, aims to understand the management and real‐world outcomes of T2DM over 3 years. Methods Adults (≥25 to ≤60 years old at T2DM diagnosis; diabetes duration ≥2 years at enrollment; controlled/uncontrolled on ≥2 anti‐diabetic agents) were enrolled. Baseline characteristics were analyzed using descriptive statistics. Results Of the 6279 recruited participants, 6236 were eligible for baseline assessment (56.6% [n/N = 3528/6236] men; mean ± SD age: 52.1 ± 9.2 years, diabetes duration: 8.6 ± 5.6 years). mean ± SD HbA1c, fasting plasma glucose, and postprandial glucose values were 64 ± 17 mmol/mol (8.1 ± 1.6%), 142.8 ± 50.4 mg/dl, and 205.7 ± 72.3 mg/dl, respectively. Only 25.1% (n/N = 1122/6236) participants had controlled glycemia (HbA1c

[No Abstract Available], Wellcome Trust [209553/Z/17/Z]; UCLH Biomedical Research Centre, This study was supported by Wellcome Trust grant 209553/Z/17/Z and the UCLH Biomedical Research Centre. Funding information for this article has been deposited with the Crossref Funder Registry.

Therapy patterns were examined across various subgroups during the first year of LANDMARC, a 3-year prospective observational study (CTRI/2017/05/008452) that included patients with T2D on ≥2 antihyperglycemic medications. Of 6236 patients (mean baseline values - age: 52.1 years, T2D duration: 8.6 years and A1C: 8.05%) enrolled, 5654 completed 1-year follow-up visit. Therapeutic management was at the discretion of the treating physician. At the end of the first year, the proportion of patients taking insulin + OAD increased (baseline: 24%; 1-year: 30.7%); while, those taking only OADs decreased (baseline: 74.4%; 1-year: 67.3%). Biguanides and sulfonylureas were the most commonly used OAD classes, the highest increase in use was seen for DPP4 inhibitors (baseline: 48.9%; 1-year: 58.7%). Overall, at 1-year, glycemic parameters improved significantly (p≤0.001); HbA1c improved more in the insulin versus insulin naive subgroup (p 3 versus ≤3 OADs. All glycemic parameters improved in those receiving basal or premix insulins. Overall, 1-year data indicate that timely initiation of insulin may play an important role in improving glycemic parameters. Disclosure H. Thacker: None. R. Ghosh: Employee; Self; Sanofi. S. Krishnan: Employee; Self; Sanofi. A. Nair: Employee; Self; Sanofi. S. Mohanasundaram: Employee; Self; Sanofi. S. K. Menon: Employee; Self; Sanofi. V. Salvi: Employee; Self; Sanofi. D. Chodankar: Employee; Self; Sanofi. C. Trivedi: None. S. Wangnoo: None. A. H. Zargar: None. A. K. Das: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk, Roche Pharma, Sanofi. N. Rais: None. S. Joshi: Advisory Panel; Self; Abbott, AstraZeneca, Biocon, Franco Indian, Glenmark, Lupin, Marico, Roche, Twinhealth, Zydus, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis Pharmaceuticals Corporation, Novo Nordisk, Sanofi, Serdia Pharmaceuticals (India) Pvt. Ltd. A. Mithal: Advisory Panel; Self; Eris Lifesciences Limited, Consultant; Self; Glenmark Pharmaceuticals Limited, Lupin Pharmaceuticals, Inc., USV Private Limited, Speaker’s Bureau; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Intas Pharmaceuticals Ltd., Novo Nordisk, Sanofi. S. Kalra: Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk, Sanofi. A. Unnikrishnan: Advisory Panel; Self; Sanofi-Aventis, Other Relationship; Self; Novo Nordisk A/S, Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes. K. Kumar: Advisory Panel; Self; Sanofi-Aventis. B. Sethi: None. S. Chowdhury: None. Funding Sanofi

Real-world data on the effectiveness and safety of Gla-100 is limited in Indian people with T2DM. In a post-hoc analysis the effectiveness and hypoglycemia risk was studied in Indian T2DM participants (N=955) who started Gla-100 under daily routine practice and were followed-up for 6 months in the observational FINE-ASIA (overall N=2679) and GOAL (overall N=2704) registries. Mean age and duration of diabetes were 54.7±9.8 years and 9.8±6.3 years, respectively. HbA1c, FPG, body weight, dose, and incidence of hypoglycemia outcomes are summarized in Table. Mean HbA1c and FPG were significantly reduced after 6 months of Gla-100 treatment (-2.07±1.42%; -94.4±65.2 mg/dL). HbA1c targets of Disclosure V. C. Deshmukh: None. S. Mohanasundaram: Employee; Self; Sanofi. C. Trivedi: None. V. Salvi: Employee; Self; Sanofi. P. R. Narvekar: None. S. Kale: None. S. Ramakrishnan: None. G. Goyal: Advisory Panel; Self; Sanofi. T. Chaudhury: None. M. Chadha: Advisory Panel; Self; Sanofi, Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Pharma Ltd. M. S. Chawla: Speaker’s Bureau; Self; Abbott Diabetes, Boehringer Ingelheim Pharmaceuticals, Inc., Colgate-Palmolive, Eli Lilly and Company, Glenmark Pharmaceuticals Limited, Novo Nordisk. S. Mukherjee: None. S. U. Pitale: Speaker’s Bureau; Self; Sanofi. D. Basu: None. R. Ghosh: Employee; Self; Sanofi. A. Nair: Employee; Self; Sanofi. Funding Sanofi India

Data on glycemic status in patients with diabetes from metropolitan and non-metropolitan cities of India are unavailable. Hence, glycemic trend was evaluated among patients from metropolitan versus non-metropolitan cities during the first year of LANDMARC trial (a 3-year nationwide prospective observational study; CTRI/2017/05/008452). A total of 6236 patients with type 2 diabetes (T2D) taking ≥2 antihyperglycemic medications (with/without glycemic control) were enrolled, of which 5654 completed 1-year follow-up visit. The age, T2D duration, baseline A1C were comparable across patients from metropolitan and non-metropolitan cities (Table). At 1-year, a decrease in all glycemic parameters was noted. However, the difference in fall in A1C from baseline between patients from metropolitan and non-metropolitan cities was not significant (mean [95% CI]: -0.5% [-0.5, -0.4] vs. -0.5% [-0.5, -0.4]; p=0.86). For FPG and PPG, the difference in change from baseline between the two groups was also not significant (p>0.05) (Table). In the first-year, patients from both metropolitan and non-metropolitan cities showed marked improvement in glycemic status with similar trends for change in glycemic parameters. These results help compare the longitudinal glycemic patterns among patients with T2D in metropolitan and non-metropolitan cities across India. Disclosure A. Unnikrishnan: Advisory Panel; Self; Sanofi-Aventis, Other Relationship; Self; Novo Nordisk A/S, Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes. R. Ghosh: Employee; Self; Sanofi. S. Krishnan: Employee; Self; Sanofi. A. Nair: Employee; Self; Sanofi. S. Mohanasundaram: Employee; Self; Sanofi. S. K. Menon: Employee; Self; Sanofi. V. Salvi: Employee; Self; Sanofi. D. Chodankar: Employee; Self; Sanofi. C. Trivedi: None. S. Wangnoo: None. A. H. Zargar: None. A. K. Das: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Novo Nordisk, Roche Pharma, Sanofi. N. Rais: None. S. Joshi: Advisory Panel; Self; Abbott, AstraZeneca, Biocon, Franco Indian, Glenmark, Lupin, Marico, Roche, Twinhealth, Zydus, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Merck Sharp & Dohme Corp., Novartis Pharmaceuticals Corporation, Novo Nordisk, Sanofi, Serdia Pharmaceuticals (India) Pvt. Ltd. A. Mithal: Advisory Panel; Self; Eris Lifesciences Limited, Consultant; Self; Glenmark Pharmaceuticals Limited, Lupin Pharmaceuticals, Inc., USV Private Limited, Speaker’s Bureau; Self; Abbott, AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Intas Pharmaceuticals Ltd., Novo Nordisk, Sanofi. S. Kalra: Speaker’s Bureau; Self; Eli Lilly and Company, Novo Nordisk, Sanofi. K. Kumar: Advisory Panel; Self; Sanofi-Aventis. H. Thacker: None. B. Sethi: None. S. Chowdhury: None. Funding Sanofi

Purpose British Thoracic Society (BTS) guidelines advocate using FDG PET-CT with the Herder model to estimate malignancy risk in solitary pulmonary nodules (SPNs). Qualitative and semi-quantitative assessment of SPN uptake is based upon analysis of Ordered Subset Expected Maximisation (OSEM) PET images. Our aim was to assess the effect of a Bayesian Penalised Likelihood (BPL) PET reconstruction on the assessment of SPN FDG uptake and estimation of malignancy risk (Herder score). Methods Subjects with SPNs who underwent FDG PET-CT between 2014–2017, with histological confirmation of malignancy or histological/imaging follow-up confirmation of benignity were included. Two blinded readers independently classified SPN uptake on both OSEM and BPL (BTS score; 1 = none; 2 = ≤ mediastinal blood pool (MBP); 3 = >MBP but ≤ 2x liver; 4 = >2x liver), with resultant calculation of the Herder score (%) for both reconstructions. Results 97 subjects with 75 (77%) malignant SPNs were included. BPL increased the BTS score in 25 (26%) SPNs; 9 SPNs (7 malignant) increased from BTS score 2 to 3, 16 (13 malignant) from BTS score 3 to 4, with a mean Herder score increase of 18 ± 22%. The mean Herder score for all SPNs with BPL was higher than OSEM (73 ± 29 vs 68 ± 32%, p = 0.001). There was no difference in Herder model diagnostic performance between BPL and OSEM, with similar areas under the curve (0.84 vs 0.83, p = 0.39). Conclusion BPL increases the Herder score in 26% of SPNs compared to OSEM but does not alter the diagnostic performance of the Herder model.

We propose a novel patient-specific generative approach to simulate the emergence and growth of lung nodules using 3D cellular automata (CA) in computer tomography (CT). Our proposed method can be applied to individual images thus eliminating the need of external images that can contaminate and influence the generative process, a valuable characteristic in the medical domain. Firstly, we employ inpainting to generate pseudo-healthy representations of lung CT scans prior the visible appearance of each lung nodule. Then, for each nodule, we train a 3D CA to simulate nodule growth and progression using the image of that same nodule as a target. After each CA is trained, we generate early versions of each nodule from a single voxel until the growing nodule closely matches the appearance of the original nodule. These synthesized nodules are inserted where the original nodule was located in the pseudo-healthy inpainted versions of the CTs, which provide realistic context to the generated nodule. We utilize the simulated images for data augmentation yielding false positive reduction in a nodule detector. We found statistically significant improvements $(p \lt 0.001)$ in the detection of lung nodules.

Introduction The SUMMIT Study aims to assess the implementation of Low-Dose Computed Tomography (LDCT) for lung cancer screening in a high-risk population and to validate a multi-cancer early detection blood test. LDCT results are communicated to participants and their GPs by standardised letter. We aim to evaluate the turnaround time from the scan report to the subsequent management and communication of results via letter. Methods Results are automatically sent to participants and GPs according to pre-defined management plans based on findings collected via proformatised radiology report. Possible outcomes from these reports are: urgent referrals for suspicious findings, nodule surveillance LDCT at 3 months, 12 month surveillance LDCT, or suitable for randomisation at Year 1 to annual or biennial LDCT (see figure 1). Participants with suspicious findings are reviewed by the study clinicians. Where appropriate an urgent referral to the participant’s local hospital is completed manually after discussion with the participant; the automated letters in these cases are delayed until contact is made with the participant and a clinical plan confirmed. Results We report outcomes from the first 11,551 SUMMIT Study participants with completed baseline LDCT reports. We aim to action results within 5 days: 11,319 (98.0%) of all results letters were mailed to participants and 11,423 (98.9%) to their GPs within 5 days. 645 (5.6%) participants required further review and consideration of an urgent referral. For these, 84.6% of results letters were mailed within 5 days, and 95.5% within 12 days. As expected, increased mailing times were observed in cases that were more complex, requiring liaison with an external clinical team or review of imaging at our internal weekly radiology meeting. Discussion Timely reporting of results is crucial in establishing wider roll-out of lung cancer screening in the UK. The vast majority of results are automated and are reliably sent as programmed. A minority require further clinical input and image review, prior to completion of an onwards referral. We demonstrate a scalable and feasible approach to feeding back results following LDCT.

Convolutional Neural Networks (CNNs) are widely used for image classification in a variety of fields, including medical imaging. While most studies deploy cross-entropy as the loss function in such tasks, a growing number of approaches have turned to a family of contrastive learning-based losses. Even though performance metrics such as accuracy, sensitivity and specificity are regularly used for the evaluation of CNN classifiers, the features that these classifiers actually learn are rarely identified and their effect on the classification performance on out-of-distribution test samples is insufficiently explored. In this paper, motivated by the real-world task of lung nodule classification, we investigate the features that a CNN learns when trained and tested on different distributions of a synthetic dataset with controlled modes of variation. We show that different loss functions lead to different features being learned and consequently affect the generalization ability of the classifier on unseen data. This study provides some important insights into the design of deep learning solutions for medical imaging tasks., Accepted at iMIMIC, MICCAI 2021

Background: Idiopathic pulmonary fibrosis (IPF) and pleuroparenchymal fibroelastosis (PPFE) are known to have poor outcomes but detailed examinations of prognostic significance of an association between these morphologic processes are lacking. Methods: Retrospective observational study of independent derivation and validation cohorts of IPF populations. Upper-lobe PPFE extent was scored visually (vPPFE) as categories of absent, moderate, marked. Computerised upper-zone PPFE extent (cPPFE) was examined continuously and using a threshold of 2.5% pleural surface area. vPPFE and cPPFE were evaluated against 1-year FVC decline (estimated using mixed-effects models) and mortality. Multivariable models were adjusted for age, gender, smoking history, antifibrotic treatment and diffusion capacity for carbon monoxide. Findings: PPFE prevalence was 49% (derivation cohort, n = 142) and 72% (validation cohort, n = 145). vPPFE marginally contributed 3-14% to variance in interstitial lung disease (ILD) severity across both cohorts. In multivariable models, marked vPPFE was independently associated with 1-year FVC decline (derivation: regression coefficient 18.3, 95 CI 8.47-28.2%; validation: 7.51, 1.85-13.2%) and mortality (derivation: hazard ratio [HR] 7.70, 95% CI 3.50-16.9; validation: HR 3.01, 1.33-6.81). Similarly, continuous and dichotomised cPPFE were associated with 1-year FVC decline and mortality (cPPFE > 2.5% derivation: HR 5.26, 3.00-9.22; validation: HR 2.06, 1.28-3.31). Individuals with cPPFE > 2.5% or marked vPPFE had the lowest median survival, the cPPFE threshold demonstrated greater discrimination of poor outcomes at two and three years than marked vPPFE. Interpretation: PPFE quantification supports distinction of IPF patients with a worse outcome independent of established ILD severity measures. This has the potential to improve prognostic management and elucidate separate pathways of disease progression. Funding: This research was funded in whole or in part by the Wellcome Trust [209,553/Z/17/Z] and the NIHR UCLH Biomedical Research Centre, UK. (c) 2021 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/), Wellcome Trust [209553/Z/17/Z]; NIHR UCLH Biomedical Research Centre, UK; NIHR South-ampton Biomedical Research Centre; EPSRC [EP/M020533/1], This research was funded in whole or in part by the Wellcome Trust [209553/Z/17/Z]. For the purpose of open access, the author has applied a CC-BY public copyright licence to any author accepted manuscript version arising from this submission. This project, JJ, EG and SMJ were also supported by the NIHR UCLH Biomedical Research Centre, UK. MGJ and CB acknowledge the support of the NIHR South-ampton Biomedical Research Centre. EPSRC grant EP/M020533/1 helped support this work.

As the coronavirus pandemic evolves, the focus of radiology departments has begun to change. The acute phase of imaging a new disease entity whilst rationalising radiology services in the face of lockdown has passed. Radiologists are now becoming familiar with the complications of COVID-19, particularly the lung parenchymal and pulmonary vascular sequelae and are considering the impact follow-up imaging may have on departments already struggling with a backlog of suspended imaging in the face of reduced capacity. This review from the British Society of Thoracic Imaging explores both the thoracic and extra-thoracic complications of COVID-19, recognising the importance of a holistic approach to patient follow-up. The British Thoracic Society guidelines for respiratory follow-up of COVID-19 will be discussed, together with newly developed reporting templates, which aim to provide consistency for clinicians as well as an opportunity for longer-term data collection.

Lung cancer kills an estimated 35 000 people in the UK every year. Despite the improvements in treating late-stage disease, lung cancer outcomes have changed little in the last 40 years. Low-dose CT (LDCT) screening for lung cancer reduces lung cancer mortality by 20%–24% and all-cause mortality by 7%.1 2 Lung cancer screening (LCS) however remains contentious, particularly how to implement it in an efficient and efficacious way. This contention extends to the potential costs of screening—financial to the National Health Service (NHS), and physical and psychological harms to patients. These concerns are particularly relevant to how we manage both the findings we aim to detect through screening (pulmonary nodules) and those we pick up inadvertently (incidental findings). The SUMMIT Study is the largest CT screening study in Europe and a key endpoint is detailing the feasibility of delivering CT screening across a complete population within the NHS. We present here SUMMIT’s approach to nodule and incidental findings management, a pragmatic model that is neither overly burdensome nor unsafe and provides a practical solution to some of the challenges of LDCT LCS. The SUMMIT study (ClinicalTrials.gov NCT03934866) is an LCS study recruiting individuals 55–77 years old at high risk of lung and other smoking-related cancers to LDCT screening. Its twin aims are to examine the performance of delivering an LDCT screening service for lung cancer to a high-risk population and to validate a cell-free nucleic acid blood test for detection of multiple cancers. The study began enrolment in April 2019 after the development of protocols for the management of pulmonary nodules and incidental findings that enabled a consistent approach to management across the entirety of the study (target recruitment of 25 000). The study aims to deliver a programme of LCS that is pragmatic, evidence-based, and practically deliverable by …

The case series provides radiographers with essential information to preliminarily evaluate chest imaging and prompt the rapid diagnosis of COVID-19. Image 1

Since the emergence of the novel coronavirus SARS-CoV-2 in Wuhan, China in 2019 [1], the resulting COVID-19 disease has rapidly transitioned into a global pandemic with over 31 000 deaths and 215 000 infections in the UK as of 10th May 2020 [2]. Confirmation of SARS-CoV-2 infection requires reverse-transcriptase polymerase chain reaction (RT-PCR) testing [3]. Chest radiographic and/or computed tomography imaging is also central to diagnosis and management [4]., The National COVID-19 Chest Imaging Database (NCCID) is a repository of chest X-Ray, CT and MRI images and clinical data from COVID-19 patients across the UK, to support research and development of AI technology that may proffer insights into the disease.

Background The number of proposed prognostic models for COVID-19 is growing rapidly, but it is unknown whether any are suitable for widespread clinical implementation. Methods We independently externally validated the performance candidate prognostic models, identified through a living systematic review, among consecutive adults admitted to hospital with a final diagnosis of COVID-19. We reconstructed candidate models as per original descriptions and evaluated performance for their original intended outcomes using predictors measured at admission. We assessed discrimination, calibration and net benefit, compared to the default strategies of treating all and no patients, and against the most discriminating predictor in univariable analyses. Results We tested 22 candidate prognostic models among 411 participants with COVID-19, of whom 180 (43.8%) and 115 (28.0%) met the endpoints of clinical deterioration and mortality, respectively. Highest areas under receiver operating characteristic (AUROC) curves were achieved by the NEWS2 score for prediction of deterioration over 24 h (0.78; 95% CI 0.73–0.83), and a novel model for prediction of deterioration, Oxygen saturation on room air and patient age are strong predictors of deterioration and mortality among hospitalised adults with COVID-19, respectively. None of the 22 prognostic models evaluated in this study add incremental value to these univariable predictors.

Large numbers of people are being discharged from hospital following COVID-19 without assessment of recovery. In 384 patients (mean age 59.9 years; 62% male) followed a median 54 days post discharge, 53% reported persistent breathlessness, 34% cough and 69% fatigue. 14.6% had depression. In those discharged with elevated biomarkers, 30.1% and 9.5% had persistently elevated d-dimer and C reactive protein, respectively. 38% of chest radiographs remained abnormal with 9% deteriorating. Systematic follow-up after hospitalisation with COVID-19 identifies the trajectory of physical and psychological symptom burden, recovery of blood biomarkers and imaging which could be used to inform the need for rehabilitation and/or further investigation.

Glycemic change from baseline to 6-months was examined across various subgroups during first 6-months observational period in this 3 year prospective study (LANDMARC; CTRI/2017/05/008452). Descriptive statistics was used to assess glycemic trends in adults with T2D controlled/uncontrolled on ≥2 antihyperglycemic medications. Of 6236 enrolled participants, 5703 completed 6-month follow-up (visit 2 [V2]). A significant (p Disclosure R. Ghosh: Employee; Self; Sanofi. A.K. Das: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. A. Mithal: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Johnson & Johnson, Lilly Diabetes, Novo Nordisk A/S. S. Joshi: Advisory Panel; Self; Novo Nordisk A/S, Roche Pharma, Sanofi. K. Kumar: None. S. Kalra: Advisory Panel; Self; Eli Lilly and Company. Speaker’s Bureau; Self; Novo Nordisk A/S, Sanofi-Aventis. A. Unnikrishnan: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Eli Lilly and Company, Ipca Laboratories, Merck Sharp & Dohme Corp., Novartis AG. H. Thacker: None. B. Sethi: None. S. Mohanasundaram: Employee; Self; Sanofi. S.K. Menon: None. A. Nair: Employee; Self; Sanofi. N. Rais: None. S. Wangnoo: None. S. Chowdhury: Advisory Panel; Self; Novo Nordisk A/S. A.H. Zargar: None. Funding Sanofi India Limited

LANDMARC (CTRI/2017/05/008452) aims to evaluate the development and progression of diabetes complications over 3 years in Indian participants with T2D. Rate of diabetes complications was compared from baseline to 6 months (visit 2 [V2]) using McNemar’s test and Chi square test (when complications were stratified in subgroups). There was an increase in the rate of microvascular complications by V2 (Table). Microvascular complications were reported more commonly in participants with A1C≥7% than A1C Disclosure R. Ghosh: Employee; Self; Sanofi. A.K. Das: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. S. Joshi: Advisory Panel; Self; Novo Nordisk A/S, Roche Pharma, Sanofi. A. Mithal: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Johnson & Johnson, Lilly Diabetes, Novo Nordisk A/S. K. Kumar: None. S. Kalra: Advisory Panel; Self; Eli Lilly and Company. Speaker’s Bureau; Self; Novo Nordisk A/S, Sanofi-Aventis. A. Unnikrishnan: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Eli Lilly and Company, Ipca Laboratories, Merck Sharp & Dohme Corp., Novartis AG. H. Thacker: None. B. Sethi: None. S. Mohanasundaram: Employee; Self; Sanofi. S.K. Menon: None. A. Nair: Employee; Self; Sanofi. N. Rais: None. S. Wangnoo: None. S. Chowdhury: Advisory Panel; Self; Novo Nordisk A/S. A.H. Zargar: None. Funding Sanofi India Limited

Impact of cardiovascular (CV) risk factors in participants with T2D during the first 6-months of observational period were examined in this 3 year prospective study (LANDMARC; CTRI/2017/05/008452). CV risk factors (rate of hypertension, dyslipidemia, albuminuria, and family history of premature coronary disease) at baseline (V1) and 6 months (Visit 2 [V2]) were assessed and compared between subgroups. Overall, >50% of the participants who had A1C data available, had CV risks at both V1 (2385/4479; 53.2%) and V2 (2422/4479; 54.1%). More than half of the participants with obesity (BMI ≥25 kg/m2) had CV risks at V1 (2305/4150; 55.5%) and V2 (2340/4150; 56.4%). On comparing the insulin (N=1548) vs. insulin naïve (N=4688) subgroups, a higher proportion of participants on insulin had CV risks than those who were insulin naïve (V1: 60.1% vs. 50.1%; V2: 60.8% vs. 50.9%). At V2, hypertension and dyslipidemia were more predominant in those with BMI ≥23 kg/m2 than Disclosure R. Ghosh: Employee; Self; Sanofi. A.K. Das: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. S. Joshi: Advisory Panel; Self; Novo Nordisk A/S, Roche Pharma, Sanofi. A. Mithal: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Johnson & Johnson, Lilly Diabetes, Novo Nordisk A/S. K. Kumar: None. S. Kalra: Advisory Panel; Self; Eli Lilly and Company. Speaker’s Bureau; Self; Novo Nordisk A/S, Sanofi-Aventis. A. Unnikrishnan: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Eli Lilly and Company, Ipca Laboratories, Merck Sharp & Dohme Corp., Novartis AG. H. Thacker: None. B. Sethi: None. S. Mohanasundaram: Employee; Self; Sanofi. S.K. Menon: None. A. Nair: Employee; Self; Sanofi. N. Rais: None. S. Wangnoo: None. S. Chowdhury: Advisory Panel; Self; Novo Nordisk A/S. A.H. Zargar: None. Funding Sanofi India Limited

Therapy patterns were examined across various subgroups during the first 6-months of this 3 year prospective longitudinal study (LANDMARC; CTRI/2017/05/008452). During the observational period investigators were free to modify treatment in adults with T2D controlled/uncontrolled on ≥2 antihyperglycemic medications. Treatment patterns were analyzed using descriptive statistics and paired t-test. From baseline to 6-months (visit 2 [V2]), glycemic parameters analyzed for 5703 subjects improved significantly (p3 OADs vs. ≤3 OADs was noted in insulin naïve subgroup. Notably, in participants receiving insulin along with OADs, PPG improved more in basal vs. premix regimen (p=0.0024). Overall, insulin regimen was more effective than OADs. Intensification of treatment with >3 OADs may not be effective in improving glycemic parameters. In real-world setting, adding basal insulin may be more effective than premix. Disclosure R. Ghosh: Employee; Self; Sanofi. A.K. Das: Advisory Panel; Self; Novo Nordisk A/S, Sanofi. A. Mithal: Speaker’s Bureau; Self; AstraZeneca, Boehringer Ingelheim International GmbH, Johnson & Johnson, Lilly Diabetes, Novo Nordisk A/S. S. Joshi: Advisory Panel; Self; Novo Nordisk A/S, Roche Pharma, Sanofi. K. Kumar: None. S. Kalra: Advisory Panel; Self; Eli Lilly and Company. Speaker’s Bureau; Self; Novo Nordisk A/S, Sanofi-Aventis. A. Unnikrishnan: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Novo Nordisk Inc., Sanofi. Speaker’s Bureau; Self; Eli Lilly and Company, Ipca Laboratories, Merck Sharp & Dohme Corp., Novartis AG. H. Thacker: None. B. Sethi: None. S. Mohanasundaram: Employee; Self; Sanofi. S.K. Menon: None. A. Nair: Employee; Self; Sanofi. N. Rais: None. S. Wangnoo: None. S. Chowdhury: Advisory Panel; Self; Novo Nordisk A/S. A.H. Zargar: None. Funding Sanofi India Limited

In accordance with guidance from the Chief Medical Officer's office and the Royal College of Radiologists, the British Society of Thoracic Imaging (BSTI) recognises that based on the available evidence computed tomography (CT) currently has no upfront role in the diagnostic work-up of 2019 novel coronavirus (COVID-19) infection (https://www.rcr.ac.uk/college/coronavirus-covid-19-what-rcr-doing/rcr-position-role-ct-patients-suspected-covid-19). Nevertheless, a number of reports have been published highlighting CT appearances in COVID-19, raising the possibility of a role for CT in patient management.1, 2, 3, 4, 5 In response to these reports, the BSTI published a preliminary consensus statement on 6 March 2020.6 We discuss below what role, if any, CT would play in the detection and management of COVID-19 infection in the UK, and the logistics of imaging delivery. This role is heavily predicated on the clinical context as well as the timing of its intended use within the diagnostic pathway, especially relative to the current reference standard diagnostic test, real-time reverse transcriptase polymerase chain reaction (RT-PCR) of a pharyngeal swab,7 and other clinical and laboratory investigations. Although it may not be feasible or desirable for isolation purposes to perform a chest radiograph (CXR), we should acknowledge that pragmatically patients with a respiratory complaint are likely to present via any number of routes (primary care, emergency departments [EDs] or outpatient clinics) having already had a CXR, other than to isolation pods outside a hospital, and work-up of a respiratory complaint would usually include a CXR in such settings. Cognizant of this fact, in the following discussion we have considered how a CXR would also fit into diagnostic algorithms, and in particular, how the use of CT would alter management in settings where a CXR was or was not available. As such, we deliberate the following questions: (1) would a CT thorax contribute to management of symptomatic cases after a rapidly available RT-PCR result? (2) Would a CT thorax contribute to symptomatic cases if an RT-PCR test was not available or had to be rationed, and (a) a chest radiograph had been performed and was abnormal? (b) A chest radiograph had been performed and was normal, or was not/could not be performed? (3) Would a CT thorax contribute to the detection and management of COVID-19 in asymptomatic high-risk cases? (4) How should imaging (CT thorax or CXR) be provided? (5) What would a COVID-19 diagnostic algorithm look like? In the following discussion, a high pre-test probability is assumed for symptomatic cases, based on one or more of: clinical presentation (Pyrexia of 37.8); acute onset persistent cough, hoarseness, nasal discharge or congestion, shortness of breath, sore throat, wheezing, sneezing; and compatible laboratory abnormalities (relative lymphopenia, elevated C-reactive protein [CRP]).8

Increasing bacterial burden in the lower airways of patients with idiopathic pulmonary fibrosis confers an increased risk of disease progression and mortality. However, it remains unclear whether this increased bacterial burden directly influences progression of fibrosis or simply reflects the magnitude of the underlying disease extent or severity. We prospectively recruited 193 patients who underwent bronchoscopy and received a multidisciplinary diagnosis of idiopathic pulmonary fibrosis. Quantification of the total bacterial burden in bronchoalveolar lavage fluid was performed by 16S rRNA gene qPCR. Imaging was independently evaluated by two readers assigning quantitative scores for extent, severity and topography of radiographic changes and relationship of these features with bacterial burden was assessed. Increased bacterial burden significantly associated with disease progression (HR 2.1; 95% CI 1.287–3.474; p=0.0028). Multivariate stepwise regression demonstrated no relationship between bacterial burden and radiological features or extent of disease. When specifically considering patients with definite or probable usual interstitial pneumonia there was no difference in bacterial burden between these two groups. Despite a postulated association between pleuroparenchymal fibroelastosis and clinical infection, there was no relationship between either the presence or extent of pleuroparenchymal fibroelastosis and bacterial burden. We demonstrate that bacterial burden in the lower airways is not simply secondary to the extent of the underlying architectural destruction of the lung parenchyma seen in idiopathic pulmonary fibrosis. The independent nature of this association supports a relationship with the underlying pathogenic mechanisms and highlights the urgent need for functional studies., Elevated bacterial burden predicts mortality in IPF and is independent of both radiological features and extent of disease http://bit.ly/2RaDbdv

Key messages #### What is the key question? #### What is the bottom line? #### Why read on? Pulmonary nodules are common, with a prevalence of 14%–36%,1–5 usually less in case series of nodules that are incidentally detected on thoracic CT scans performed for a variety of clinical indications. Clinical management of CT-detected pulmonary nodules was based initially on a statement made by the Fleischner Society in 2005.6 Three further guidelines and one statement have been published since 2013 incorporating emerging evidence. The Fleischner Society provided specific recommendations for subsolid nodule management in 2013.7 In the same year, the American College of Chest Physicians (ACCP) issued nodule guidance as part of its recommendations for the diagnosis and management of lung cancer.8 In 2015, the British Thoracic Society (BTS) published guidelines for nodule management, accompanied by a comprehensive evidence review.9 Most recently, the Fleischner Society updated their guidance for management and measurement of nodules, replacing both their 2005 and 2013 guidance.10 11 Clinician awareness of, and adherence to, such guidance has historically been poor, and remains so.12–16 Guidelines that differ in their recommendations are a potential source of confusion and thus risk increasing variation in clinical practice rather than achieving one of …

The results of the Dutch-Belgian low-dose CT (LDCT) screening trial (NELSON) have been eagerly awaited since the US National Lung Screening Trial (NLST), published in 2011, demonstrated annual LDCT screening of the chest led to a 20% decrease in lung cancer mortality compared with chest X-ray screening.1 While the US Preventative Service Task Force approved lung cancer screening in 2014,2 Europe and the rest of the globe have been paralysed by fear of implementation costs and the feasibility of introducing national LDCT screening programmes. The consensus from healthcare payers outside of the USA has been that we should wait for the results of the NELSON trial which, while smaller in size, would give us the confidence of a second randomised controlled trial and proof of effect in a population outside of the US healthcare system. Indeed, a recent Health Technology Assessment of LDCT screening in the UK specifically named the NELSON trial as an important source of future information and explicitly stated the results were required in order to make a decision about its efficacy and cost-effectiveness.3 It was on this background of hope and perhaps, dare we say it, healthcare payer fear that the NELSON trial preliminary results were released at the World Conference on Lung Cancer in Toronto in October. Despite NELSON being smaller in size than NLST and having a preponderance of male participants, the results were clear: LDCT screening compared with no screening leads to a statistically significant lung cancer mortality reduction of 26% for men and numbers hint that the benefit could be even greater in women (between 40% and 60%). With this new data the UK, and indeed the world outside of the USA, now needs to cast aside concerns over efficacy, as well as procrastination over implementation, and concentrate more …

Background and objective This study evaluated whether patients with combined pulmonary fibrosis and emphysema (CPFE) have an increased likelihood of pulmonary hypertension (PHT) when compared with idiopathic pulmonary fibrosis (IPF) patients without emphysema. Methods Two consecutive IPF populations having undergone transthoracic echocardiography were examined (n = 223 and n = 162). Emphysema and interstitial lung disease (ILD) extent were quantified visually; ILD extent was also quantified by a software tool, CALIPER. Echocardiographic criteria categorized PHT risk. Results The prevalence of an increased PHT likelihood was 29% and 31% in each CPFE cohort. Survival at 12 months was 60% across both CPFE cohorts with no significantly worsened outcome identified when compared with IPF patients without emphysema. Using logistic regression models in both cohorts, total computed tomography (CT) disease extent (ILD and emphysema) predicted the likelihood of PHT. After adjustment for total disease extent, CPFE had no stronger association with PHT likelihood than IPF patients without emphysema. Conclusion Our findings indicate that the reported association between CPFE and PHT is explained by the summed baseline CT extents of ILD and emphysema. Once baseline severity is taken into account, CPFE is not selectively associated with a malignant microvascular phenotype, when compared with IPF patients without emphysema.

BackgroundThe NLST reported a significant 20% reduction in lung cancer mortality with three annual low-dose CT (LDCT) screens and the Dutch-Belgian NELSON trial indicates a similar reduction. We present the results of the UKLS trial.MethodsFrom October 2011 to February 2013, we randomly allocated 4 055 participants to either a single invitation to screening with LDCT or to no screening (usual care). Eligible participants (aged 50-75) had a risk score (LLPv2) ≥ 4.5% of developing lung cancer over five years. Data were collected on lung cancer cases to 31 December 2019 and deaths to 29 February 2020 through linkage to national registries. The primary outcome was mortality due to lung cancer. We included our results in a random-effects meta-analysis to provide a synthesis of the latest randomised trial evidence.Findings1 987 participants in the intervention and 1 981 in the usual care arms were followed for a median of 7.3 years (IQR 7.1-7.6), 86 cancers were diagnosed in the LDCT arm and 75 in the control arm. 30 lung cancer deaths were reported in the screening arm, 46 in the control arm, (relative rate 0.65 [95% CI 0.41-1.02]; p=0.062). The meta-analysis indicated a significant reduction in lung cancer mortality with a pooled overall relative rate of 0.84 (95% CI 0.76-0.92) from nine eligible trials.InterpretationThe UKLS trial of single LDCT indicates a reduction of lung cancer death of similar magnitude to the NELSON and NLST trials and was included in a meta-analysis of nine randomised trials which provides unequivocal support for lung cancer screening in identified risk groups.FundingNIHR Health Technology Assessment programme; NIHR Policy Research programme; Roy Castle Lung Cancer Foundation.

Aim: The treatment of patients with recurrent or progressive thymic epithelial tumors remains uncertain due to limited data in this rare disease. Materials & methods: A retrospective 10-year monoinstitutional analysis was conducted on 25 patients with first recurrence or disease progression following primary treatment. Results: Twenty patients had thymoma, five thymic carcinomas. Ten patients (40%) received surgery, four (40%) following chemotherapy; 17 (68%) had chemotherapy, with a combination regimen in 16 of them (94%). Surgery had a significant effect both on overall survival and progression-free survival-2 by univariate analysis (p = 0.04), combination chemotherapy only on progression-free survival-2 (p = 0.03). Conclusion: Combination chemotherapy and surgery at first recurrence/progression of thymic epithelial tumors were associated with improved survival. Discussion: Although several limitations may have affected this retrospective study on a relatively small number of patients with this rare entity of recurrent thymic malignancies, we suggest the use of combination chemotherapy and surgery at their first recurrence may have contributed to the high overall and progression-free survival observed with adequate follow-up and deserve further investigations in broader retrospective and comparative studies.

Background Unclassifiable-interstitial lung disease (uILD) represents a heterogeneous collection of pathologies encompassing those fibrosing lung diseases which do not fulfill current diagnostic criteria. We evaluated baseline and longitudinal functional and CT (visual and quantitative computer [CALIPER] analysis) variables to identify outcome predictors in uILD. Methods Consecutive patients with uILD on multidisciplinary review (n = 95) had baseline functional (FVC, DLco, CPI [composite physiologic index]) and CT features (visual evaluation: CT pattern, fibrosis extent, honeycombing presence, traction bronchiectasis severity, pulmonary artery (PA) diameter; CALIPER evaluation: fibrosis extent, pulmonary vessel volume (PVV)) examined in univariate and multivariate Cox regression models. Change in functional and CT variables were examined in a patient subset (n = 37), to identify indicators of outcome. Results On univariate analysis, CPI was the most powerful functional predictor of mortality (p < 0.0001). Visual traction bronchiectasis (p < 0.0001), PA diameter (p < 0.0001) and honeycombing presence (p = 0.0001) and CALIPER PVV (p = 0.0003) were the strongest CT outcome predictors. On multivariate analysis of baseline indices, traction bronchiectasis (p = 0.003), PA diameter (p = 0.003) and CPI (p = 0.0001) independently predicted mortality. Colinearity with functional indices precluded the evaluation of CALIPER PVV in multivariate models. On evaluation of longitudinal variables, increasing CALIPER fibrosis extent was the strongest outcome predictor, and remained so following adjustment for baseline disease severity, and when FVC declines were marginal. Conclusions In uILD patients, CPI, traction bronchiectasis severity and PA diameter independently predicted outcome at baseline. Increasing fibrosis extent measured by CALIPER was the most powerful index of outcome regardless of baseline disease severity and strongly predicted outcome in patients with marginal FVC declines.