Lung Cancer Screening with Low-Dose CT in Smokers: A Systematic Review and Meta-Analysis

Advancing lung cancer diagnosis: Combining 3D auto-encoders and attention mechanisms for CT scan analysis

ObjectiveThe goal of this study is to assess the effectiveness of a hybrid deep learning model that combines 3D Auto-encoders with attention mechanisms to detect lung cancer early from CT scan images. The study aims to improve diagnostic accuracy, sensitivity, and specificity by focusing on key features in the scans.Materials and methodsA hybrid model was developed that combines feature extraction using 3D Auto-encoder networks with attention mechanisms. First, the 3D Auto-encoder model was tested without attention, using feature selection techniques such as RFE, LASSO, and ANOVA. This was followed by evaluation using several classifiers: SVM, RF, GBM, MLP, LightGBM, XGBoost, Stacking, and Voting. The model's performance was evaluated based on accuracy, sensitivity, F1-Score, and AUC-ROC. After that, attention mechanisms were added to help the model focus on important areas in the CT scans, and the performance was re-assessed.ResultsThe 3D Auto-encoder model without attention achieved an accuracy of 93% and sensitivity of 89%. When attention mechanisms were added, the performance improved across all metrics. For example, the accuracy of SVM increased to 94%, sensitivity to 91%, and AUC-ROC to 0.96. Random Forest (RF) also showed improvements, with accuracy rising to 94% and AUC-ROC to 0.93. The final model with attention improved the overall accuracy to 93.4%, sensitivity to 90.2%, and AUC-ROC to 94.1%. These results highlight the important role of attention in identifying the most relevant features for accurate classification.ConclusionsThe proposed hybrid deep learning model, especially with the addition of attention mechanisms, significantly improves the early detection of lung cancer. By focusing on key features in the CT scans, the attention mechanism helps reduce false negatives and boosts overall diagnostic accuracy. This approach has great potential for use in clinical applications, particularly in the early-stage detection of lung cancer.

Development and assessment of a mortality risk prediction nomogram model for pneumocystis disease in ICU within 28 days

To develop and assess a nomogram predictive model for evaluating the 28-day mortality risk in patients diagnosed with Pneumocystis who have been admitted to the intensive care unit (ICU). From 2008 to 2022, clinical data on patients with Pneumocystis were collected using the American Critical Care Medical Information Database IV (MIMIC-IV). Initially, 63 significant predictive indicators were included, with ICU admission as the time node and all-cause mortality within 28 days as the outcome. Using complete data modeling, the variable selection approach combines two methods: Lasso regression (glmnet package) and collinearity screening (car package). Use the bootstrap method 1000 times for internal validation. Calculate the AUC, mean sensitivity, and specificity of 1000 resamplings, as well as the 95% confidence interval, and then plot the ROC, calibration, and DCA curves. The patients were split into two groups based on their 28-day survival status: 83 cases (67.48%) in the survival group and 40 instances (32.52%) in the death group. Five variables-the history of malignant tumors, Lods scores, Oasis scores, and complications of shock and severe renal injury-were eventually included in the entire sample after screening. According to Receiver Operating Characteristic (ROC) analysis, the model's sensitivity was 0.600 (95% CI 0.448-0.752), specificity was 0.904 (95% CI 0.840-0.967), and AUC was 0.814 (95% CI 0.732-0.897). The DCA curve indicates that the model application has high accuracy, which leads to a net benefit for population prediction, and the model calibration curve demonstrates good calibration accuracy. The bootstrap model's 1000 internal validation results demonstrate that the model's calibration performance is good and that its accuracy is highest when the probability of patient outcome events falls between 35 and 60%, which yields the highest net benefit for population prediction. This study developed a nomogram utilizing MIMIC-IV clinical big data to predict the 28-day mortality risk in patients with Pneumocystis disease. Incorporating five critical factors, the nomogram offers a user-friendly, visual method for calculating personalized risk scores based on patient-specific information, including medical history, laboratory results, and clinical scores. Demonstrating robust discrimination and calibration, this tool provides clinicians with a valuable resource for assessing prognosis and making evidence-based treatment decisions.

Strength in Numbers: Identifying a Significant Association between High Serum Ferritin Levels and Newly Diagnosed Malignancy in a Large Health Organization Cohort

BACKGROUND

Ferritin, an iron storage protein and acute phase reactant, has been implicated in various aspects of human health and disease, including cancer. Previous studies have identified elevated serum ferritin (SF) levels in several cancer types, but a comprehensive examination across different malignancies remains lacking. This study aims to fill this gap by utilizing anonymized data from Maccabi Health Services (MHS), one of Israel's largest health organizations, to explore the association between elevated SF levels and the diagnosis of different malignancies.

METHODS

An extensive dataset from MHS, comprising 2.7 million members, including 1.3 million individuals who underwent SF level testing, was analyzed. ORs and 95% confidence intervals were calculated to assess the association between high SF levels and cancer diagnosis. Subgroup analysis was conducted to investigate variations across different malignancies.

RESULTS

The analysis revealed a significant association between elevated SF levels and cancer diagnosis among MHS members, with an OR of 1.9 (95% confidence interval, 1.71-2.15). Subgroup analysis unveiled differences in the association across malignancy types, with hematologic, hepatobiliary, and respiratory malignancies more strongly associated with high SF levels.

CONCLUSIONS

This study provides further support for the link between elevated SF levels and malignancy, leveraging a vast dataset from MHS, underscoring potential utilities of elevated SF levels as a potential indicator for cancer with a variable role among different malignancy types.

IMPACT

The identification of elevated SF levels as a potential indicator for underlying malignancy for seemingly healthy individuals.

Lung Cancer Screening With Low-Dose CT: A Systematic Review

Lung cancer is highly prevalent worldwide and is the leading cause of cancer-related death in Portugal. There is increasing evidence that low-dose computed tomography (LDCT) screening reduces mortality; however, few countries have implemented screening strategies. This review aims to gather the best evidence to assess the relevance of implementing lung cancer screening. A search was conducted for clinical practice guidelines (CPGs), systematic reviews (SRs), and meta-analyses (MAs) published between January 1, 2010, and January 31, 2024, as well as randomized controlled trials (RCTs) published between January 1, 2019, and January 31, 2024, indexed in databases such as the National Guideline Clearinghouse, Cochrane Library, Guideline Finder, Canadian Medical Association, Evidence-Based Medicine Online, Database of Abstracts of Reviews of Effectiveness (DARE), and PubMed. The MeSH terms used were "lung cancer" and "screening". To evaluate the level of evidence (LE) and strength of recommendation (SR) in the included MAs, the Strength of Recommendation Taxonomy (SORT) from the American Academy of Family Physicians was applied. A total of 460 articles were found, with two CPGs, six MAs, two SRs, and one RCT being selected. The CPGs recommend screening with LDCT for smokers with a smoking history of more than 20 pack-years, aged between 50 and 80 years. All MAs show statistically significant evidence of reduced mortality in screened patients, although without a reduction in all-cause mortality. However, there was some heterogeneity regarding the age of the target population and the screening follow-up period. Overdiagnosis rates varied between MAs. The SRs and RCT also demonstrated a reduction in lung cancer mortality, but not in all-cause mortality. LDCT lung cancer screening shows a reduction in disease-related mortality, suggesting that the implementation of organized screening for at-risk populations could have a significant positive impact. Some uncertainties remain regarding the best strategy for implementing organized screening programs.

The Evidence Effect: How Fact Boxes Shift Perceptions of Lung Cancer Screening in Austrian Medical Practice

BACKGROUND

Recent results from the Dutch NELSON study have rekindled debates about the benefit-to-harm ratio of lung cancer screening and the comprehension of this by physicians.

METHODS

This research surveyed the perception and understanding of 136 Austrian physicians regarding the advantages and risks of lung cancer screening, examining the impact of educational data visualization tools, including fact box and icon array. Physicians participated in an online survey about their understanding before and after exposure to either a fact box alone or combined with an icon array.

RESULTS

The findings indicated that the fact box significantly enhanced physicians' grasp of the screening's benefits and harms, making them up to 13 times more likely to adjust their estimates within a predefined range. Notably, the intervention was more effective among physicians who initially did not recommend CT screening. However, the addition of the icon array did not offer significant improvement. Postintervention, physicians showcased better comprehension and an improved ability to offer patient-centered advice, which may bolster adherence to lung cancer screening protocols.

OUTLOOK

Despite its insights, the study's cross-sectional nature and the unique cultural context underline the need for more research. Further exploration should focus on different settings and assess the real-world implications on clinical practice and patient outcomes.

[Cancer prevention recommendations: Update 2024]

Cancer is one of the main causes of morbidity and mortality. Environmental factors along with lifestyle: tobacco and alcohol consumption, unhealthy diet and sedentary lifestyle and lack of physical activity, are some of the risk factors that have caused an increase in cancer. This article updates the evidence and recommendations for cancer prevention strategies through screening in asymptomatic patients, as well as early detection of signs and symptoms in medium-risk and high-risk populations.

Protein Biomarkers in Lung Cancer Screening: Technical Considerations and Feasibility Assessment

Lung cancer remains the leading cause of cancer-related deaths worldwide, mainly due to late diagnosis and the presence of metastases. Several countries around the world have adopted nation-wide LDCT-based lung cancer screening that will benefit patients, shifting the stage at diagnosis to earlier stages with more therapeutic options. Biomarkers can help to optimize the screening process, as well as refine the TNM stratification of lung cancer patients, providing information regarding prognostics and recommending management strategies. Moreover, novel adjuvant strategies will clearly benefit from previous knowledge of the potential aggressiveness and biological traits of a given early-stage surgically resected tumor. This review focuses on proteins as promising biomarkers in the context of lung cancer screening. Despite great efforts, there are still no successful examples of biomarkers in lung cancer that have reached the clinics to be used in early detection and early management. Thus, the field of biomarkers in early lung cancer remains an evident unmet need. A more specific objective of this review is to present an up-to-date technical assessment of the potential use of protein biomarkers in early lung cancer detection and management. We provide an overview regarding the benefits, challenges, pitfalls and constraints in the development process of protein-based biomarkers. Additionally, we examine how a number of emerging protein analytical technologies may contribute to the optimization of novel robust biomarkers for screening and effective management of lung cancer.

Effects of low dose computed tomography (LDCT) on lung cancer screening on incidence and mortality in regions with high tuberculosis prevalence: A systematic review

BACKGROUND

Lung cancer screening (LCS) using low-dose computed tomography (LDCT) is a strategy for early-stage diagnosis. The implementation of LDCT screening in countries with a high prevalence/incidence of tuberculosis (TB) is controversial. This systematic review and meta-analysis aim to identify whether LCS using LDCT increases early-stage diagnosis and decreases mortality, as well as the false-positive rate, in regions with a high prevalence of TB.

METHODS/DESIGN

Studies were identified by searching BVS, PUBMED, EMBASE, and SCOPUS. RCT and cohort studies (CS) that show the effects of LDCT in LC screening on mortality and secondary outcomes were eligible. Two independent reviewers evaluated eligibility and a third judged disagreements. We used the Systematic Review Data Repository (SRDR+) to extract the metadata and record decisions. The analyses were stratified by study design and incidence of TB. We used the Cochrane "Risk of bias" assessment tool.

RESULTS

The Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) were used. Thirty-seven papers were included, referring to 22 studies (10 RCTs and 12 cohorts). Few studies were from regions with a high incidence of TB (One RCT and four cohorts). Nonetheless, the evidence is compatible with European and USA studies. RCTs and CS also had consistent results. There is an increase in early-stage (I-II) diagnoses and reduced LC mortality in the LCDT arm compared to the control. Although false-positive rates varied, they stayed within the 20 to 30% range.

DISCUSSION

This is the first meta-analysis of LDCT for LCS focused on its benefits in regions with an increased incidence/prevalence of TB. Although the specificity of Lung-RADS was higher in participants without TB sequelae than in those with TB sequelae, our findings point out that the difference does not invalidate implementing LDCT LCS in these regions.

TRIAL REGISTRATION

Systematic review registration Systematic review registration PROSPERO CRD42022309581.

Which is a real valuable screening tool for lung cancer and measure thoracic diseases, chest radiography or low-dose computed tomography?: A review on the current status of Japan and other countries

Chest radiography (CR) has been used as a screening tool for lung cancer and the use of low-dose computed tomography (LDCT) is not recommended in Japan. We need to reconsider whether CR really contributes to the early detection of lung cancer. In addition, we have not well discussed about other major thoracic disease detection by CR and LDCT compared with lung cancer despite of its high frequency. We review the usefulness of CR and LDCT as veridical screening tools for lung cancer and other thoracic diseases. In the case of lung cancer, many studies showed that LDCT has capability of early detection and improving outcomes compared with CR. Recent large randomized trial also supports former results. In the case of chronic obstructive pulmonary disease (COPD), LDCT contributes to early detection and leads to the implementation of smoking cessation treatments. In the case of pulmonary infections, LDCT can reveal tiny inflammatory changes that are not observed on CR, though many of these cases improve spontaneously. Therefore, LDCT screening for pulmonary infections may be less useful. CR screening is more suitable for the detection of pulmonary infections. In the case of cardiovascular disease (CVD), CR may be a better screening tool for detecting cardiomegaly, whereas LDCT may be a more useful tool for detecting vascular changes. Therefore, the current status of thoracic disease screening is that LDCT may be a better screening tool for detecting lung cancer, COPD, and vascular changes. CR may be a suitable screening tool for pulmonary infections and cardiomegaly.

Applicability of selected reaction monitoring for precise screening tests

INTRODUCTION

The proactive identification of diseases through screening tests has long been endorsed as a means to preempt symptomatic onset. However, such screening endeavors are fraught with complications, such as diagnostic inaccuracies, procedural risks, and patient unease during examinations. These challenges are amplified when screenings for multiple diseases are administered concurrently. Selected Reaction Monitoring (SRM) offers a unique advantage, allowing for the high-throughput quantification of hundreds of analytes with minimal interferences.

AREAS COVERED

Our research posits that SRM-based assays, traditionally tailored for single-disease biomarker profiling, can be repurposed for multi-disease screening. This innovative approach has the potential to substantially alleviate time, labor, and cost demands on healthcare systems and patients alike. Nonetheless, there are formidable methodological hurdles to overcome. These include difficulties in detecting low-abundance proteins and the risk of model overfitting due to the multiple functionalities of single proteins across different disease spectrums - issues especially pertinent in blood-based assays where detection sensitivity is constrained. As we move forward, technological strides in sample preparation, online extraction, throughput, and automation are expected to ameliorate these limitations.

EXPERT OPINION

The maturation of mass spectrometry's integration into clinical laboratories appears imminent, positioning it as an invaluable asset for delivering highly sensitive, reproducible, and precise diagnostic results.

Effectiveness of a single low-dose computed tomography screening for lung cancer: A population-based perspective cohort study in China

The purpose of this perspective cohort study was to evaluate the effectiveness of low-dose computed tomography (LDCT) screening for lung cancer in China. This study was conducted under the China Urban Cancer Screening Program (CanSPUC). The analysis was based on participants aged 40 to 74 years from 2012 to 2019. A total of 255 569 eligible participants were recruited in the study. Among the 58 136 participants at high risk of lung cancer, 20 346 (35.00%) had a single LDCT scan (defined as the screened group) and 37 790 (65.00%) not (defined as the non-screened group). Overall, 1162 participants were diagnosed with lung cancer at median follow-up time of 5.25 years. The screened group had the highest cumulative incidence of lung cancer and the non-screened group had the highest cumulative lung cancer mortality and all-cause cumulative mortality. We performed inverse probability weighting (IPW) to account for potential imbalances, and Cox proportional hazards model to estimate the weighted association between mortality and LDCT scans. After IPW adjusted with baseline characteristics, the lung cancer incidence density was significantly increased (37.0% increase) (HR1.37 [95%CI 1.12-1.69]), lung cancer mortality was decreased (31.0% decrease) (HR0.69 [95%CI 0.49-0.97]), and the all-cause mortality was significantly decreased (23.0% lower) (HR0.77 [95% CI 0.68-0.87]) in the screened group. In summary, a single LDCT for lung cancer screening will reduce the mortality of lung cancer and all-cause mortality in China.

[Statement Paper on the Implementation of a National Organized Program in Germany for the Early Detection of Lung Cancer in Risk Populations Using Low-dose CT Screening Including Management of Screening Findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present concrete cornerstones for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process.

[Statement paper on the implementation of a national organized program in Germany for the early detection of lung cancer in risk populations using low-dose CT screening including management of screening findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on the early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present key points for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process. CITATION FORMAT: · Vogel-Claussen J, Blum TG, Andreas S et al. Position paper on the implementation of a nationally organized program in Germany for the early detection of lung cancer in high-risk populations using low-dose CT screening including the management of screening findings requiring further workup. Fortschr Röntgenstr 2024; 196: DOI 10.1055/a-2178-2846.

[Statement paper on the implementation of a national organized program in Germany for the early detection of lung cancer in risk populations using low-dose CT screening including management of screening findings]

The process of implementing early detection of lung cancer with low-dose CT (LDCT) in Germany has gained significant momentum in recent years. It is expected that the ordinance of the Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) on early detection of lung cancer, which has been commented on by the professional societies, will come into effect by the end of 2023. Based on this regulation, the Federal Joint Committee (G-BA) will set up a program for early lung cancer detection with LDCT in the near future. In this position paper, the specialist societies involved in lung cancer screening present concrete cornerstones for a uniform, structured and quality-assured early detection program for lung cancer in Germany to make a constructive contribution to this process.

Serum-based biomarkers associated with lung cancer risk and cause-specific mortality in the German randomized Lung Cancer Screening Intervention (LUSI) trial

Background

Lung cancer (LC) screening can be optimized using individuals' estimated risks of having a detectable lung tumor, as well as of mortality risk by competing causes, to guide decisions on screening eligibility, ideal screening intervals and stopping ages. Besides age, sex and smoking history, blood-based biomarkers may be used to improve the assessment of LC risk and risk of mortality by competing causes.

Methods

In the German randomized Lung Screening Intervention Trial (LUSI), we measured growth/differentiation factor-15 (GDF-15), interleukin-6 (IL-6), C-reactive protein (CRP) and N-terminal pro-brain natriuretic protein (NT-proBNP), in blood serum samples collected at start of the trial. Participants in the computed tomography (CT)-screening arm also had a pulmonary function test. Regression models were used to examine these markers as predictors for impaired lung function, LC risk and mortality due to LC or other causes, independently of age, sex and smoking history.

Results

Our models showed increases in LC risk among participants with elevated serum levels of GDF-15 [odds ratio (OR)Q4-Q1 =2.47, 95% confidence interval (CI): 1.49-4.26], IL-6 [ORQ4-Q1 =2.36 (1.43-4.00)] and CRP [ORQ4-Q1 =1.81 (1.08-2.75)]. Likewise, proportional hazards models showed increased risks for LC-related mortality, hazard ratio (HR)Q4-Q1 of 4.63 (95% CI: 2.13-10.07) for GDF-15, 3.56 (1.72-7.37) for IL-6 and 2.34 (1.24-4.39) for CRP. All four markers were associated with increased risk of mortality by causes other than LC, with strongest associations for GDF-15 [HRQ4-Q1 =3.04 (2.09-4.43)] and IL-6 [HRQ4-Q1 =2.98 (2.08-4.28)]. Significant associations were also observed between IL-6, CRP, GDF-15 and impaired pulmonary function [chronic obstructive pulmonary disease (COPD), preserved ratio impaired spirometry (PRISm)]. Multi-marker models identified GDF-15 and IL-6 as joint risk predictors for risk of LC diagnosis, without further discrimination by CRP or NT-proBNP. A model based on age, sex, smoking-related variables, GFD-15 and IL-6 provided moderately strong discrimination for prediction of LC diagnoses within 9 years after blood sampling [area under the curve (AUC) =74.3% (57.3-90.2%)], compared to 67.0% (49.3-84.8%) for a model without biomarkers. For mortality by competing causes, a model including biomarkers resulted in an AUC of 76.2% (66.6-85.3%)], compared to 70.0% (60.9-77.9%) a model including age, sex and smoking variables.

Conclusions

Serum GDF-15 and IL-6 may be useful indicators for estimating risks for LC and competing mortality among long-term smokers participating in LC screening, to optimize LC screening strategies.

How Artificial Intelligence Is Shaping Medical Imaging Technology: A Survey of Innovations and Applications

The integration of artificial intelligence (AI) into medical imaging has guided in an era of transformation in healthcare. This literature review explores the latest innovations and applications of AI in the field, highlighting its profound impact on medical diagnosis and patient care. The innovation segment explores cutting-edge developments in AI, such as deep learning algorithms, convolutional neural networks, and generative adversarial networks, which have significantly improved the accuracy and efficiency of medical image analysis. These innovations have enabled rapid and accurate detection of abnormalities, from identifying tumors during radiological examinations to detecting early signs of eye disease in retinal images. The article also highlights various applications of AI in medical imaging, including radiology, pathology, cardiology, and more. AI-based diagnostic tools not only speed up the interpretation of complex images but also improve early detection of disease, ultimately delivering better outcomes for patients. Additionally, AI-based image processing facilitates personalized treatment plans, thereby optimizing healthcare delivery. This literature review highlights the paradigm shift that AI has brought to medical imaging, highlighting its role in revolutionizing diagnosis and patient care. By combining cutting-edge AI techniques and their practical applications, it is clear that AI will continue shaping the future of healthcare in profound and positive ways.

Coronary Artery Calcium Identified on Non-Gated Chest CT Scans: A Wasted Opportunity for Preventive Cardiological Care

BACKGROUND

Coronary artery calcium (CAC) evaluated on dedicated cardiac computed tomography (CT) is an independent predictor of cardiovascular events. This study aimed to evaluate the correlation between CAC detected on non-gated standard chest CT and coronary lesions on coronary angiography (CAG) and determine its impact on prognosis.

METHODS

Consecutive patients who underwent CAG due to acute coronary syndrome and had prior non-contrasted non-gated chest CT were included and retrospectively evaluated. Coronary artery calcium was evaluated by quantitative (Agatston score) and qualitative (visual assessment) assessment.

RESULTS

A total of 114 patients were included in this study. The mean time difference between chest CT and CAG was 23 months. Coronary artery calcium was visually classified as mild, moderate, and severe in 31%, 33%, and 16% of patients, respectively. Moderate or severe CAC was an independent predictor of significant lesions on CAG (OR 22; 95% CI 8-61; p<0.001) and all-cause mortality (OR 4; 95% CI 2-9; p=0.001). Quantitative CAC evaluation accurately predicted significant lesions on CAG (AUC 0.81; p<0.001). While significant CAC was identified in 80% of chest CTs, formal reporting was 25%.

CONCLUSION

Coronary artery calcium evaluation with chest CT was feasible and strongly associated with severity of coronary disease on CAG and mortality. Although the identification of CAC on chest CT represents a unique opportunity for cardiovascular risk stratification for preventive care, CAC underreporting is frequent.

Common and Uncommon CT Findings in CVID-Related GL-ILD: Correlations with Clinical Parameters, Therapeutic Decisions and Potential Implications in the Differential Diagnosis

PURPOSE

To investigate computed tomography (CT) findings of Granulomatous Lymphocytic Interstitial Lung Disease (GL-ILD) in Common Variable Immunodeficiency (CVID), also in comparison with non-GL-ILD abnormalities, correlating GL-ILD features with functional/immunological parameters and looking for GL-ILD therapy predictive elements.

METHODS

CT features of 38 GL-ILD and 38 matched non-GL-ILD subjects were retrospectively described. Correlations of GL-ILD features with functional/immunological features were assessed. A logistic regression was performed to find a predictive model of GL-ILD therapeutic decisions.

RESULTS

Most common GL-ILD CT findings were bronchiectasis, non-perilymphatic nodules, consolidations, Ground Glass Opacities (GGO), bands and enlarged lymphnodes. GL-ILD was usually predominant in lower fields. Multiple small nodules (≤10 mm), consolidations, reticulations and fibrotic ILD are more indicative of GL-ILD. Bronchiectasis, GGO, Reticulations and fibrotic ILD correlated with decreased lung performance. Bronchiectasis, GGO and fibrotic ILD were associated with low IgA levels, whereas high CD4+ T cells percentage was related to GGO. Twenty out of 38 patients underwent GL-ILD therapy. A model combining Marginal Zone (MZ) B cells percentage, IgA levels, lower field consolidations and lymphnodes enlargement showed a good discriminatory capacity with regards to GL-ILD treatment.

CONCLUSIONS

GL-ILD is a lower field predominant disease, commonly characterized by bronchiectasis, non-perilymphatic small nodules, consolidations, GGO and bands. Multiple small nodules, consolidations, reticulations and fibrotic ILD may suggest the presence of GL-ILD in CVID. MZ B cells percentage, IgA levels at diagnosis, lower field consolidations and mediastinal lymphnodes enlargement may predict the need of a specific GL-ILD therapy.

[Prevention, Diagnosis, Therapy, and Follow-up of Lung Cancer - Interdisciplinary Guideline of the German Respiratory Society and the German Cancer Society - Abridged Version]

The current S3 Lung Cancer Guidelines are edited with fundamental changes to the previous edition based on the dynamic influx of information to this field:The recommendations include de novo a mandatory case presentation for all patients with lung cancer in a multidisciplinary tumor board before initiation of treatment, furthermore CT-Screening for asymptomatic patients at risk (after federal approval), recommendations for incidental lung nodule management , molecular testing of all NSCLC independent of subtypes, EGFR-mutations in resectable early stage lung cancer in relapsed or recurrent disease, adjuvant TKI-therapy in the presence of common EGFR-mutations, adjuvant consolidation treatment with checkpoint inhibitors in resected lung cancer with PD-L1 ≥ 50%, obligatory evaluation of PD-L1-status, consolidation treatment with checkpoint inhibition after radiochemotherapy in patients with PD-L1-pos. tumor, adjuvant consolidation treatment with checkpoint inhibition in patients withPD-L1 ≥ 50% stage IIIA and treatment options in PD-L1 ≥ 50% tumors independent of PD-L1status and targeted therapy and treatment option immune chemotherapy in first line SCLC patients.Based on the current dynamic status of information in this field and the turnaround time required to implement new options, a transformation to a "living guideline" was proposed.

Walk-through flat panel total-body PET: a patient-centered design for high throughput imaging at lower cost using DOI-capable high-resolution monolithic detectors

PURPOSE

Long axial field-of-view (LAFOV) systems have a much higher sensitivity than standard axial field-of-view (SAFOV) PET systems for imaging the torso or full body, which allows faster and/or lower dose imaging. Despite its very high sensitivity, current total-body PET (TB-PET) throughput is limited by patient handling (positioning on the bed) and often a shortage of available personnel. This factor, combined with high system costs, makes it hard to justify the implementation of these systems for many academic and nearly all routine nuclear medicine departments. We, therefore, propose a novel, cost-effective, dual flat panel TB-PET system for patients in upright standing positions to avoid the time-consuming positioning on a PET-CT table; the walk-through (WT) TB-PET. We describe a patient-centered, flat panel PET design that offers very efficient patient throughput and uses monolithic detectors (with BGO or LYSO) with depth-of-interaction (DOI) capabilities and high intrinsic spatial resolution. We compare system sensitivity, component costs, and patient throughput of the proposed WT-TB-PET to a SAFOV (= 26 cm) and a LAFOV (= 106 cm) LSO PET systems.

METHODS

Patient width, height (= top head to start of thighs) and depth (= distance from the bed to front of patient) were derived from 40 randomly selected PET-CT scans to define the design dimensions of the WT-TB-PET. We compare this new PET system to the commercially available Siemens Biograph Vision 600 (SAFOV) and Siemens Quadra (LAFOV) PET-CT in terms of component costs, system sensitivity, and patient throughput. System cost comparison was based on estimating the cost of the two main components in the PET system (Silicon Photomultipliers (SiPMs) and scintillators). Sensitivity values were determined using Gate Monte Carlo simulations. Patient throughput times (including CT and scout scan, patient positioning on bed and transfer) were recorded for 1 day on a Siemens Vision 600 PET. These timing values were then used to estimate the expected patient throughput (assuming an equal patient radiotracer injected activity to patients and considering differences in system sensitivity and time-of-flight information) for WT-TB-PET, SAFOV and LAFOV PET.

RESULTS

The WT-TB-PET is composed of two flat panels; each is 70 cm wide and 106 cm high, with a 50-cm gap between both panels. These design dimensions were justified by the patient sizes measured from the 40 random PET-CT scans. Each panel consists of 14 × 20 monolithic BGO detector blocks that are 50 × 50 × 16 mm in size and are coupled to a readout with 6 × 6 mm SiPMs arrays. For the WT-TB-PET, the detector surface is reduced by a factor of 1.9 and the scintillator volume by a factor of 2.2 compared to LAFOV PET systems, while demonstrating comparable sensitivity and much better uniform spatial resolution (< 2 mm in all directions over the FOV). The estimated component cost for the WT-TB-PET is 3.3 × lower than that of a 106 cm LAFOV system and only 20% higher than the PET component costs of a SAFOV. The estimated maximum number of patients scanned on a standard 8-h working day increases from 28 (for SAFOV) to 53-60 (for LAFOV in limited/full acceptance) to 87 (for the WT-TB-PET). By scanning faster (more patients), the amount of ordered activity per patient can be reduced drastically: the WT-TB-PET requires 66% less ordered activity per patient than a SAFOV.

CONCLUSIONS

We propose a monolithic BGO or LYSO-based WT-TB-PET system with DOI measurements that departs from the classical patient positioning on a table and allows patients to stand upright between two flat panels. The WT-TB-PET system provides a solution to achieve a much lower cost TB-PET approaching the cost of a SAFOV system. High patient throughput is increased by fast patient positioning between two vertical flat panel detectors of high sensitivity. High spatial resolution (< 2 mm) uniform over the FOV is obtained by using DOI-capable monolithic scintillators.

Determination of the Level of Cardiovascular Risk in 172,282 Spanish Working Women

Introduction, objectives: Although cardiovascular events have been traditionally associated mainly with men, some data reflect an increase in women, which may even exceed their male counterparts, constituting the leading cause of death in working women in Spain. The objective of this present study was to analyze the level of cardiovascular risk in Spanish working women by assessing the influence of age, type of work, and tobacco consumption.

MATERIAL, METHODS

A descriptive cross-sectional study was carried out in 172,282 working women from different Spanish geographical areas and from different companies between January 2018 and June 2020. A range of variables and risk factors were assessed and various cardiovascular risk scales were used to analyze the data.

RESULTS

An increase in cardiovascular risk was observed in the least qualified work groups, mainly corresponding to blue-collar workers, when using the SCORE or REGICOR risk equation. The prevalence of altered values for all the parameters analyzed (overweight and obesity, hypertension, dyslipidemia, diabetes, fatty liver, hepatic fibrosis, atherogenic indexes, and cardiovascular risk scales) was higher among blue-collar women. Age was the only factor that influenced all the cardiovascular risk scales studied, increasing risk when comparing the group of women aged 50 years and older with the others.

CONCLUSIONS

Aging and belonging to the blue-collar job category meant worse results in the cardiovascular risk scales and in all the parameters analyzed. This is in line with numerous studies that argue that age and zip code are more influential than genetic code.

Laterocervical lymph node metastases from suspected thyroidal primary site that turned out to be metastases of lung cancer: A case report

Incidental sonographic discovery of thyroid nodules is an increasingly common event in clinical practice. Less frequently, patients with cytological benign thyroid nodules have suspicious cervical lymph nodes detected by ultrasound examination or by cytological exam. Here, we discuss an intriguing case of cervical lymph node metastasis with a probable thyroid origin in a 65-year-old asymptomatic male smoker. He underwent thyroidectomy and unilateral cervical lymphadenectomy. Despite a negative chest X-ray, the postoperative histological examination revealed that the lymph node metastasis was actually from a lung carcinoma. Metastatic lesions in cervical lymph nodes from non-thyroidal origins must be excluded when evaluating lesions in the region, especially when thyroid nodules subjected to fine needle aspiration biopsy yield negative results, or lymph node cytological evaluations are inconsistent with thyroid cytological findings and sonographic features. Thyroid and lung adenocarcinomas share some epithelial and mesenchymal markers. Thyroglobulin helps differentiate primary thyroid tumors from lung ones, but in cases of poor differentiation, distinguishing metastatic lesions in the thyroid gland can be challenging. Lung cancer (LC) is the leading cause of cancer mortality worldwide, and survival rates have only marginally improved over the last several decades. The ongoing clinical challenge is detecting LC at earlier stages of the disease.

Lung Cancer Screening With Low-Dose Computed Tomography

BACKGROUND

Approximately 21 900 women and 35 300 men developed lung cancer in Germany in 2018, and 16 514 women and 28 365 men died of it. The outcome mainly depends on the tumor stage. In early stages (stage I or II), treatment can be curative; unfortunately, because early-stage lung cancers are generally asymptomatic, 74% of women and 77% of men already have advanced-stage disease (stage III or IV) at the time of diagnosis. Screening with low-dose computed tomography is an option enabling early diagnosis and curative treatment.

METHODS

This review is based on pertinent articles retrieved by a selective search of the literature on screening for lung cancer.

RESULTS

In the studies of lung cancer screening that have been published to date, sensitivity ranged from 68.5% to 93.8%, and specificity from 73.4% to 99.2%. A meta-analysis by the German Federal Office for Radiation Protection revealed a 15% reduction in lung cancer mortality when low-dose computed tomography was used in persons who were judged to be at high risk for lung cancer (risk ratio [RR] 0.85, 95% confidence interval [0.77; 0.95]). 1.9% of subjects died in the screening arm of the metaanalysis, and 2.2% in the control group. The observation periods ranged from 6.6 to 10 years; false-positive rates ranged from 84.9% to 96.4%. Malignant findings were confirmed in 45% to 70% of the biopsies or resective procedures that were performed.

CONCLUSION

Systematic lung cancer screening with low-dose CT lowers mortality from lung cancer in (current or former) heavy smokers. This benefit must be weighed against the high rate of false-positive findings and overdiagnoses.

Developing a pan-European technical standard for a comprehensive high-quality lung cancer computed tomography screening programme: an ERS technical standard

BACKGROUND

Screening for lung cancer with low radiation dose computed tomography (LDCT) has a strong evidence base. The European Council adopted a recommendation in November 2022 that lung cancer screening (LCS) be implemented using a stepwise approach. The imperative now is to ensure that implementation follows an evidence-based process that delivers clinical and cost-effectiveness. This European Respiratory Society (ERS) Task Force was formed to provide a technical standard for a high-quality LCS programme.

METHOD

A collaborative group was convened to include members of multiple European societies. Topics were identified during a scoping review and a systematic review of the literature was conducted. Full text was provided to members of the group for each topic. The final document was approved by all members and the ERS Scientific Advisory Committee.

RESULTS

Topics were identified representing key components of a screening programme. The actions on findings from the LDCT were not included as they are addressed by separate international guidelines (nodule management and clinical management of lung cancer) and by a linked ERS Task Force (incidental findings). Other than smoking cessation, other interventions that are not part of the core screening process were not included (e.g. pulmonary function measurement). 56 statements were produced and areas for further research identified.

CONCLUSIONS

This European collaborative group has produced a technical standard that is a timely contribution to implementation of LCS. It will serve as a standard that can be used, as recommended by the European Council, to ensure a high-quality and effective programme.

Evidence-based health policy in Germany: lack of communication and coordination between academia and health authorities?

Health-care decision making should consider the best available evidence, often in the form of systematic reviews (SRs). The number of existing SRs and their overlap make their identification and use difficult. Decision makers often rely on de novo SRs instead of using existing SRs. We describe two cases of duplicate reviews (minimum volume threshold of total knee arthroplasties and lung cancer screening) and one case of duplicate primary data analysis (transcatheter aortic valve implantation). All cases have in common that unintended duplication of research occurred between health authorities and academia, demonstrating a lack of communication and coordination between them.It is important to note that academia and health authorities have different incentives. Academics are often measured by the number of peer-reviewed publications and grants awarded. In contrast, health authorities must comply with laws and are commissioned to deliver a specific report within a defined period of time. Most replication is currently unintended. A solution may be the collaboration of stakeholders commonly referred to as integrated knowledge translation (IKT). The IKT approach means that research is conducted in collaboration with the end users of the research. It requires active collaborations between researchers and decision-makers or knowledge users (clinicians, managers, policy makers) throughout the research process. Wherever cooperation is possible in spite of requirements for independence or confidentiality, legal regulations should facilitate and support collaborative approaches between academia and health authorities.

[PAPPS Expert Groups. Cancer prevention recommendations: Update 2022]

Cancer is a major cause of morbidity and mortality. Tobacco use, unhealthy diet, and physical inactivity are some of the lifestyle risk factors that have led to an increase in cancer. This article updates the evidence and includes recommendations for prevention strategies for each of the cancers with the highest incidence. These are based on the reduction of risk factors (primary prevention) and early diagnosis of cancer through screening and early detection of signs and symptoms, in medium-risk and high-risk populations. This update of the 2022 PAPPS has taken into account the vision of the National Health System Cancer Strategy, an update approved by the Interterritorial Council of the National Health System on January 2021 and the European Strategy (Europe's Beating Cancer Plan) presented on 4 February 2021.

Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography

BACKGROUND

 Despite the high prevalence and mortality of lung cancer and proven effectiveness of low-dose computed tomography (LDCT) to reduce mortality, Germany still lacks a national screening program. The German Institute for Quality and Efficiency in Health Care (IQWiG) and the Federal Office for Radiation Protection (BfS) both published positive scientific evaluations recommending a quality-controlled national screening program. IQWiG underlined the importance of a clear risk definition, integrated smoking cessation programs, and quality assurance, highlighting the necessity of procedural optimization.

METHODS AND OBJECTIVES

 In the HANSE study, former and current smokers aged 55-79 years are assessed for their lung cancer risk by the NELSON and PLCO_M2012 risk scores. 5000 high-risk participants, defined as PLCO_M2012 6-year risk ≥ 1.58 % or fulfilling NELSON risk inclusion criteria, will be screened by LDCT at baseline and after 12 months. Lung nodules are analyzed by a modified Lung-RADS 1.1 score of the HANSE study, and values of emphysema and coronary calcium are determined and randomly reported to the participants. 7100 low-risk participants serve as a control. All patients are followed-up for up to 10 years. The sensitivity and specificity of the two risk assessments and LDCT screening, effects of the randomized LDCT reporting, efficiency of lung nodule management, and several other factors are assessed to analyze the success and quality of the holistic screening program.

CONCLUSION

 The HANSE study is designed as a holistic lung cancer screening study in northern Germany to answer pressing questions for a successful implementation of an effective German lung cancer screening program.

KEY POINTS

  · HANSE is designed to address pressing questions for the implementation of lung cancer screening in Germany.. · HANSE compares NELSON and PLCOM2012 risk assessments for optimal definition of the high-risk group. . · HANSE integrates cardiac calcium and pulmonary emphysema scoring in a holistic screening approach..

CITATION FORMAT

· Vogel-Claussen J, Lasch F, Bollmann B et al. Design and Rationale of the HANSE Study: A Holistic German Lung Cancer Screening Trial Using Low-Dose Computed Tomography. Fortschr Röntgenstr 2022; DOI: 10.1055/a-1853-8291.

[Translated article] Lung Cancer Screening: Survival in an Extensive Early Detection Program in Spain (I-ELCAP)

INTRODUCTION

Lung cancer (LC) is usually diagnosed at advanced stages with only a 12% 5-year survival. Trials as NLST and NELSON show a mortality decrease, which justifies implementation of lung cancer screening in risk population. Our objective was to show survival results of the largest LC screening program in Spain with low dosage computed tomography (LDCT).

METHODS

Clinical records from International Early Lung Cancer Detection Program (IELCAP) at Valencia, Spain were analyzed. This program recruited volunteers, ever-smokers aged 40-80 years, since 2008. Results are compared to those from other similar sizeable programs.

RESULTS

A total of 8278 participants were screened with at least two-rounds until November 2020. A mean of 6 annual screening rounds were performed. We detected 239 tumors along 12-year follow-up. Adenocarcinoma was the most common histology, being 61.3% at stage I. The lung cancer prevalence and incidence proportion was 1.5% and 1.4%, respectively with an annual detection rate of 0.17. One-year survival and 10-year survival were 90% and 80.1%, respectively. Adherence was 96.84%.

CONCLUSION

Largest lung cancer screening in Spain shows that survival is improved when is performed in multidisciplinary team experienced in management of LC, and is comparable to similar screening programs.

Earlier diagnosis of lung cancer

The purpose of this article is to review options for more rapid diagnosis of lung cancer at an earlier stage, thereby improving survival. These options include screening, allowing general practitioners to refer patients directly to low-dose computed tomography scan instead of a chest X-ray and the abolition of the "visitation filter", i.e. hospital doctors' ability to reject referrals from general practitioners without prior discussion with the referring doctor.

Lung Cancer Screening with Low-Dose CT: Radiation Risk and Benefit-Risk Assessment for Different Screening Scenarios

Lung cancer is a severe disease that affects predominantly smokers and represents a leading cause of cancer death in Europe. Recent meta-analyses of randomized controlled trials (RCTs) have yielded that low-dose computed tomography (LDCT) screening can significantly reduce lung cancer mortality in heavy smokers or ex-smokers by about 20% compared to a control group of persons who did not receive LDCT. This benefit must be weighed against adverse health effects associated with LDCT lung screening, in particular radiation risks. For this purpose, representative organ doses were determined for a volume CT dose index of 1 mGy that can be achieved on modern devices. Using these values, radiation risks were estimated for different screening scenarios by means of sex-, organ-, and age-dependent radio-epidemiologic models. In particular, the approach was adjusted to a Western European population. For an annual LDCT screening of (ex-)smokers aged between 50 and 75 years, the estimated radiation-related lifetime attributable risk to develop cancer is below 0.25% for women and about 0.1% for men. Assuming a mortality reduction of about 20% and taking only radiation risks into account, this screening scenario results in a benefit–risk ratio of about 10 for women and about 25 for men. These benefit–risk ratio estimates are based on the results of RCTs of the highest evidence level. To ensure that the benefit outweighs the radiation risk even in standard healthcare, strict conditions and requirements must be established for the entire screening process to achieve a quality level at least as high as that of the considered RCTs.

Preliminary study of 3 T-MRI native T1-mapping radiomics in differential diagnosis of non-calcified solid pulmonary nodules/masses

Background

Cumulative CT radiation damage was positively correlated with increased tumor risks. Although it has recently been known that non-radiation MRI is alternative for pulmonary imaging. There is little known about the value of MRI T1-mapping in the diagnosis of pulmonary nodules. This article aimed to investigate the value of native T1-mapping-based radiomics features in differential diagnosis of pulmonary lesions.

Methods

73 patients underwent 3 T-MRI examination in this prospective study. The 99 pulmonary lesions on native T1-mapping images were segmented twice by one radiologist at indicated time points utilizing the in-house semi-automated software, followed by extraction of radiomics features. The inter-class correlation coefficient (ICC) was used for analyzing intra-observer’s agreement. Dimensionality reduction and feature selection were performed via univariate analysis, and least absolute shrinkage and selection operator (LASSO) analysis. Then, the binary logical regression (LR), support vector machine (SVM) and decision tree classifiers with the input of optimal features were selected for differentiating malignant from benign lesions. The receiver operative characteristics (ROC) curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated. Z-test was used to compare differences among AUCs.

Results

107 features were obtained, of them, 19.5% (n = 21) had relatively good reliability (ICC ≥ 0.6). The remained 5 features (3 GLCM, 1 GLSZM and 1 shape features) by dimensionality reduction were useful. The AUC of LR was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70%, 85% and 80%. The AUC of SVM was 0.82(95%CI: 0.67–0.98), with sensitivity, specificity and accuracy of 70, 85 and 80%. The AUC of decision tree was 0.69(95%CI: 0.49–0.87), with sensitivity, specificity and accuracy of 50, 85 and 73.3%.

Conclusions

The LR and SVM models using native T1-mapping-based radiomics features can differentiate pulmonary malignant from benign lesions, especially for uncertain nodules requiring long-term follow-ups.

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.