Low-Dose CT lung cancer screening:clinical evidence and implementation research

Lung cancer causes more deaths than breast, cervical, and colorectal cancer combined. Nevertheless, population-based lung cancer screening is still not considered standard practice in most countries worldwide. Early lung cancer detection leads to better survival outcomes: patients diagnosed with stage 1A lung cancer have a >75% 5-year survival rate, compared to < 5% at stage 4. LDCT thorax imaging for the secondary prevention of lung cancer has been studied at length, and has been shown to significantly reduce lung cancer mortality in high-risk populations. The US national lung screening trial reported 20% overall reduction in lung cancer mortality when comparing LDCT to chest x-ray, and the NELSON trial more recently reported 24% reduction when comparing LDCT to no screening. Hence, the focus has now shifted to implementation research. Consequently, the 4-IN-THE-LUNG-RUN consortium, based in 5 European countries, has set up a large-scale multi-center implementation trial. Successful implementation and accessibility of low-dose CT lung cancer screening are dependent on many factors, not limited to; population selection, recruitment strategy, CT-screening frequency, lung nodule management, participant compliance and cost-effectiveness. This review provides an overview of current evidence for LDCT lung cancer screening, and draws attention to major factors which need to be addressed to successfully implement standardized, effective, and accessible screening throughout Europe. Evidence shows that through the appropriate use of risk-prediction models and a more personalized approach to screening, efficacy could be improved. Further, extending the screening interval for low-risk individuals to reduce costs and associated harms is a possibility, and through the use of volumetric based measurement and follow-up, false positive results can be greatly reduced. Finally, smoking cessation programs could be a valuable addition to screening programs and artificial intelligence could offer the solution to the added workload pressures Radiologists are facing

Seasonal prevalence and characteristics of low-dose CT detected lung nodules in a general Dutch population

We investigated whether presence and characteristics of lung nodules in the general population using low-dose computed tomography (LDCT) varied by season. Imaging in Lifelines (ImaLife) study participants who underwent chest LDCT-scanning between October 2018 and October 2019 were included in this sub-study. Hay fever season (summer) was defined as 1st April to 30th September and Influenza season (winter) as 1st October to 31st March. All lung nodules with volume of ≥ 30 mm3 (approximately 3 mm in diameter) were registered. In total, 2496 lung nodules were found in 1312 (38%) of the 3456 included participants (nodules per participant ranging from 1 to 21, median 1). In summer, 711 (54%) participants had 1 or more lung nodule(s) compared to 601 (46%) participants in winter (p = 0.002). Of the spherical, perifissural and left-upper-lobe nodules, relatively more were detected in winter, whereas of the polygonal-, irregular-shaped and centrally-calcified nodules, relatively more were detected in summer. Various seasonal diseases with inflammation as underlying pathophysiology may influence presence and characteristics of lung nodules. Further investigation into underlying pathophysiology using short-term LDCT follow-up could help optimize the management strategy for CT-detected lung nodules in clinical practice

Machine-perfused donor kidneys as a source of human renal endothelial cells

Renal endothelial cells (ECs) play crucial roles in vasorelaxation, ultrafiltration, and selective transport of electrolytes and water, but also in leakage of the glomerular filtration barrier and inflammatory processes like complement activation and leukocyte recruitment. In addition, they are target cells for both cellular and antibody-mediated rejection in the transplanted kidney. To study the molecular and cellular processes underlying EC behavior in renal disease, well-characterized primary renal ECs are indispensible. In this report, we describe a straightforward procedure to isolate ECs from the perfusion fluid of human donor kidneys by a combination of negative selection of monocytes/macrophages, positive selection by CD31 Dynabeads, and propagation in endothelium-specific culture medium. Thus, we isolated and propagated renal ECs from 102 donor kidneys, representative of all blood groups and major human leukocyte antigen (HLA) class I and II antigens. The obtained ECs were positive for CD31 and von Willebrand factor, expressed other endothelial markers such as CD34, VEGF receptor-2, TIE2, and plasmalemmal vesicle associated protein-1 to a variable extent, and were negative for the monocyte marker CD14 and lymphatic endothelial marker podoplanin. HLA class II was either constitutively expressed or could be induced by interferon-y. Furthermore, as a proof of principle, we showed the diagnostic value of this renal endothelial biobank in renal endothelium-specific cross-matching tests for HLA antibodies. NEW & NOTEWORTHY We describe a new and widely accessible approach to obtain human primary renal endothelial cells in a \standardized fashion, by isolating from the perfusate of machine-perfused donor kidneys. Characterization of the cells showed a mixed population originating from different compartments of the kidney. As a proof of principle, we demonstrated a possible diagnostic application in an endothelium-specific cross-match. Next to transplantation, we foresee further applications in the field renal endothelial research

Garotas de loja, história social e teoria social [Shop Girls, Social History and Social Theory]

Shop workers, most of them women, have made up a significant proportion of Britain’s labour force since the 1850s but we still know relatively little about their history. This article argues that there has been a systematic neglect of one of the largest sectors of female employment by historians and investigates why this might be. It suggests that this neglect is connected to framings of work that have overlooked the service sector as a whole as well as to a continuing unease with the consumer society’s transformation of social life. One element of that transformation was the rise of new forms of aesthetic, emotional and sexualised labour. Certain kinds of ‘shop girls’ embodied these in spectacular fashion. As a result, they became enduring icons of mass consumption, simultaneously dismissed as passive cultural dupes or punished as powerful agents of cultural destruction. This article interweaves the social history of everyday shop workers with shifting representations of the ‘shop girl’, from Victorian music hall parodies, through modernist social theory, to the bizarre bombing of the Biba boutique in London by the Angry Brigade on May Day 1971. It concludes that progressive historians have much to gain by reclaiming these workers and the service economy that they helped create

Outstanding negative prediction performance of solid pulmonary nodule volume AI for ultra-LDCT baseline lung cancer screening risk stratification

OBJECTIVE: To evaluate performance of AI as a standalone reader in ultra-low-dose CT lung cancer baseline screening, and compare it to that of experienced radiologists. METHODS: 283 participants who underwent a baseline ultra-LDCT scan in Moscow Lung Cancer Screening, between February 2017-2018, and had at least one solid lung nodule, were included. Volumetric nodule measurements were performed by five experienced blinded radiologists, and independently assessed using an AI lung cancer screening prototype (AVIEW LCS, v1.0.34, Coreline Soft, Co. ltd, Seoul, Korea) to automatically detect, measure, and classify solid nodules. Discrepancies were stratified into two groups: positive-misclassification (PM); nodule classified by the reader as a NELSON-plus /EUPS-indeterminate/positive nodule, which at the reference consensus read was < 100 mm3, and negative-misclassification (NM); nodule classified as a NELSON-plus /EUPS-negative nodule, which at consensus read was ≥ 100 mm3. RESULTS: 1149 nodules with a solid-component were detected, of which 878 were classified as solid nodules. For the largest solid nodule per participant (n = 283); 61 [21.6 %; 53 PM, 8 NM] discrepancies were reported for AI as a standalone reader, compared to 43 [15.1 %; 22 PM, 21 NM], 36 [12.7 %; 25 PM, 11 NM], 29 [10.2 %; 25 PM, 4 NM], 28 [9.9 %; 6 PM, 22 NM], and 50 [17.7 %; 15 PM, 35 NM] discrepancies for readers 1, 2, 3, 4, and 5 respectively. CONCLUSION: Our results suggest that through the use of AI as an impartial reader in baseline lung cancer screening, negative-misclassification results could exceed that of four out of five experienced radiologists, and radiologists' workload could be drastically diminished by up to 86.7%

Current and Future Perspectives on CT Screening for Lung Cancer: A Road Map for 2023-2027 from the IASLC.

Low-dose computed tomography (LDCT) screening for lung cancer significantly reduces mortality from lung cancer, as demonstrated in randomized controlled trials and meta-analyses. This review is based on the ninth CT screening symposium of the International Association for the Study of Lung Cancer (IASLC) which focuses on the major themes pertinent to the successful global implementation of LDCT screening and developed a strategy to further the implementation of lung cancer screening globally. These recommendations provide a 5-year road map to advance the implementation of LDCT screening globally including: (i) establishing universal screening program quality indicators; (ii) establishing evidence-based criteria to identify individuals who have never smoked but are at high risk of developing lung cancer; (iii) develop recommendations for incidentally detected lung nodule tracking and management protocols to complement programmatic lung cancer screening; (iv) Integrate artificial intelligence (AI) and biomarkers to increase the prediction of malignancy in suspicious CT screen-detected lesions; and (v) standardize high-quality performance AI protocols that lead to substantial reductions in costs, resource utilization and radiologist reporting time; (vi) personalize CT screening intervals based on an individual's lung cancer risk; (vii) develop evidence to support clinical management and cost-effectiveness of other identified abnormalities on a lung cancer screening CT; (viii) develop publicly accessible, easy-to-use, geospatial tools to plan and monitor equitable access to screening services; and (ix) establish a global shared education resource for lung cancer screening CT to ensure high quality reading and reporting