Low-dose computed tomography lung cancer screening: Clinical evidence and implementation research

Benefit of adjuvant chemotherapy for resected stage I lung cancer with spread through air spaces: a systematic review and meta-analysis

BACKGROUND

Spread through air spaces (STAS) has been proved to be an independent risk factor for poor prognosis in patients with stage I lung cancer. Evidence regarding the application of adjuvant chemotherapy (ACT) in STAS-positive patients with stage I lung cancer remains insufficient. This study aims to elucidate the significance and indication of ACT in patients with stage I lung cancer with STAS.

METHODS

Three major electronic databases were searched to identify relevant studies published up to June 26, 2024. Subsequently, the retrieved studies were screened according to predetermined inclusion and exclusion criteria. Hazard ratio (HR) and corresponding 95 % confidence interval (CI) were computed, and sensitivity analysis was performed to evaluate the sources of heterogeneity.

RESULTS

Five studies involving 2899 patients were included in the meta-analysis. ACT could effectively prolong disease-free survival (DFS; HR 0.69 [95 % CI 0.48-0.99]; P = 0.044) and overall survival (OS; HR 0.61 [95 % CI 0.47-0.79]; P < 0.001) in patients with stage I lung cancer with STAS. Even patients who have undergone lobectomy could benefit from ACT (DFS; HR 0.61 [95 % CI 0.45-0.82]; P = 0.001| OS; HR 0.60 [95 % CI 0.42-0.85]; P = 0.005). Moreover, ACT significantly extended DFS in STAS-positive stage IB cases (HR 0.55, 95 % CI 0.38-0.79; P = 0.001), rather than stage IA cases (HR 0.72, 95 %CI 0.42-1.25; P = 0.246).

CONCLUSION

ACT might be recommended to STAS-positive stage IB lung cancer patients, even if they have undergone radical lobectomy. Randomized controlled trials (RCTs), however, are required to confirm these findings.

O-GlcNAcylation of hexokinase 2 modulates mitochondrial dynamics and enhances the progression of lung cancer

Non-small cell lung cancer (NSCLC) stands as the prevailing manifestation of lung cancer, with current therapeutic modalities linked to a dismal prognosis, necessitating further advancements. Hexokinase 2 (HK2), a critical enzyme positioned on the mitochondrial membrane, exerts control over diverse biological pathways, thereby regulating cancer. Nevertheless, the precise role and mechanism of HK2 in NSCLC remain inadequately elucidated, warranting comprehensive investigation. HK2 expression in NSCLC tissues and cell lines was detected through immunohistochemistry and western blot analysis. Concurrently, shRNA assays were applied to scrutinize the impact of HK2 on cell proliferation, apoptosis, migration, and invasion processes in NSCLC cell lines, utilizing CCK8, flow cytometry, wound-healing assay, and transwell techniques. The involvement of HK2 in mitochondrial dynamics was probed through western blot analysis, mitochondrial membrane potential assay, and assessment of ROS generation. Next, the functional role of HK2 was assessed by examining its influence on xenograft tumor growth in nude mice in vivo. Further research has demonstrated that HK2 played a role in NSCLC through its O-GlcNAcylation process. The results of the study revealed that HK2 O-GlcNAcylation promoted the proliferation, migration, and invasive characteristics of NSCLC cells, while alleviating mitochondrial damage, whereas O-GlcNAcylation inactivation yielded the opposite effect. Furthermore, in vivo experiments in nude mice illustrated that HK2 O-GlcNAcylation could stimulate tumor growth in NSCLC. These results suggested that HK2 may impact mitochondrial dynamics in NSCLC through its O-GlcNAcylation, thereby contributing to the progression of NSCLC.

Quality of life outcomes after robotic-assisted and video-assisted thoracoscopic surgery for early-stage non-small cell lung cancer

Background

Limited research exists comparing the impacts of robotic-assisted thoracic surgery (RATS) and video-assisted thoracic surgery (VATS) on patients' physical and mental health-related quality of life (QoL).

Methods

A prospective cohort of stage IA non-small cell lung cancer (NSCLC) patients in the Initiative for Early Lung Cancer Research on Treatment from Mount Sinai Health System had QoL measured before surgery and at 2, 6, and 12 months post-treatment using the Medical Outcomes Study Short-Form 12 (SF-12), with Physical Component Summary (PCS) and Mental Component Summary (MCS); the Functional Assessment of Cancer Therapy-Lung Cancer Subscale (FACT-LCS); and Patient Health Questionnaire-4 (PHQ-4; for depression/anxiety). A locally weighted smoothing curve was fitted to identify the best interval knot for post-treatment QoL trends. A piecewise linear mixed-effects model was developed to estimate differences in baseline, 2-month, and 12-month QoL scores and rates of change, adjusting for age, sex, race, ethnicity, smoking status, pack-years, nodule size/consistency, comorbidities, and surgical extent.

Results

The study cohort comprised 698 patients, including 458 (65.6%) who underwent VATS and 240 (34.4%) who underwent RATS. The RATS group exhibited a more significant initial decline in physical health at 2 months post-surgery but showed significant recovery by 12 months, achieving similar or slightly higher physical scores compared to baseline. No significant differences in mental health scores over time were seen between the groups. Both groups displayed consistent anxiety and depression scores, with significant improvements in anxiety symptoms at the 2-month mark. The RATS group had fewer postoperative complications and conversion to open thoracotomy.

Conclusions

RATS and VATS offer similar long-term QoL outcomes for early-stage NSCLC patients, though RATS patients may experience a sharper initial decline in physical health.

Application of ATR-FTIR spectroscopy and multivariate statistical analysis in cancer diagnosis

Lung cancer is one of the most prevalent and lethal malignant tumors worldwide. Currently, clinical diagnosis primarily relies on chest X-ray examinations, histopathological analysis, and the detection of tumor markers in blood. However, each of these methods has inherent limitations. The current study aims to explore novel diagnostic approaches for lung cancer by employing attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy in conjunction with multiple machine learning models. Fourier transform infrared spectroscopy can detect subtle differences in the material structures that reflect the carcinogenic process between lung cancer tissues and normal tissues. By applying principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) to analyze infrared spectral data, these subtle differences can be amplified. The study revealed that the combination of spectral bands within the 3500-3000 cm-1 and 1600-1500 cm-1 ranges is particularly significant for differentiating between the two groups. Three classification models-Support Vector Machine (SVM), k-Nearest Neighbor (kNN), and Linear Discriminant Analysis (LDA)-were constructed for spectral analysis of various band combinations. The results indicated that in detecting lung cancer samples, the combination of the 3500-3000 cm-1 and 1600-1500 cm-1 bands offers significant advantages. The analysis of the receiver operating characteristic (ROC) curve demonstrated that the area under the curve (AUC) exceeded 0.95 for all models, with the LDA model achieving an accuracy rate of 99.4% in identifying lung cancer patients compared to healthy individuals. The findings suggest that the integration of ATR-FTIR spectroscopy with multiple machine learning models represents a promising auxiliary diagnostic method for clinical lung cancer diagnosis, enabling detection at the molecular level.

Integrating multimodal features to predict the malignancy of pulmonary ground-glass nodules: a multicenter prospective model development and validation study

Background

There is a clinical need for accurate noninvasive evaluation of the malignancy of pulmonary ground-glass nodules (GGNs) to reduce risks of overdiagnosis and overtreatment. This study aimed to develop and validate a clinic-biomarker-combined deep radiomic model for the prediction of GGN malignancy.

Materials and methods

This study recruited patients with GGNs from seven medical centers across five cities in China. The participants included in this study were divided into the training-validation and the test groups on the basis of the centers from which they were recruited. The malignancy of GGNs was determined based on pathological results. Clinical, radiological, and biomarker features with significant differences were used to establish predictive models. Six types of models based on different features were developed on the training-validation group: clinical-radiological (CR), biomarker-combined CR (B-CR), deep radiomic (DR), clinic-combined DR (C-DR), biomarker-combined DR (B-DR), and clinic-biomarker-combined DR (CB-DR) models. The models were then evaluated on the test group for discrimination, calibration, and clinical utility.

Results

A total of 501 participants with 571 GGNs were included in the study. Four hundred and seven participants with 454 GGNs were assigned to the training-validation group, whereas 94 participants with 117 GGNs were assigned to the test group. Significant differences were observed in sex, smoking history, triosephosphate isomerase-1 and microRNA-206 between patients with and without malignant GGNs. And size, location, and lobulation were significantly different between benign and malignant GGNs. Among all the models, the CB-DR model achieved the highest performance in classifying GGNs, with an AUC of 0.90 (95% CI: 0.81-0.97). At the optimal cutoff, the corresponding accuracy, sensitivity, and specificity were 0.89 (95% CI: 0.83-0.94), 0.90 (95% CI: 0.84-0.96), and 0.82 (95% CI: 0.62-1.00), respectively. Furthermore, malignancy evaluation based on the CB-DR model would have reduced overtreatment for 82.4% (14/17) of benign GGNs and enabled timely interventions for 90.0% (90/100) of malignant GGNs.

Conclusion

The CB-DR model developed in this study exhibited satisfactory performance in predicting the malignancy of GGNs and holds potential as a valuable tool for aiding clinical decision-making in GGN management.

Paradigm shift in early detection: Lung cancer screening to comprehensive CT screening

Large-scale lung cancer screening implementation combined with improvements in early detection techniques for three major tobacco-related diseases presents a rare opportunity to markedly improve population health outcomes for millions of people. Chest CT enables routine detection of early lung cancer as well as characterizing coronary calcium and detecting early emphysema in the course of lung cancer screening. Integrated preventive care centered on comprehensive chest CT screening has the potential to bring large benefits across co-morbid diseases with a common etiology. The current one-disease/ silo paradigm of medical practice is an obstacle to maximizing chest CT screening's benefits. The large potential for improved health outcomes across the world demands careful public health, quality assurance, and health policy considerations. A systematic analysis of imaging and health data from ongoing chest CT screening could accelerate this paradigm shift through sustained optimization of screening detection, quantitation and management for the three most lethal tobacco-related co-morbidities. To coordinate this effort to advance progress with implementing the full benefit of comprehensive chest CT screening, a new multi- disciplinary professional and advocacy consortium has been developed to foster collaboration to realize the future of multi-disease chest CT screening.

A Thorough Review of the Clinical Applications of Artificial Intelligence in Lung Cancer

According to data from the World Health Organization (WHO), lung cancer is becoming a global epidemic. It is particularly high in the list of the leading causes of death not only in developed countries, but also worldwide; furthermore, it holds the leading place in terms of cancer-related mortality. Nevertheless, many breakthroughs have been made the last two decades regarding its management, with one of the most prominent being the implementation of artificial intelligence (AI) in various aspects of disease management. We included 473 papers in this thorough review, most of which have been published during the last 5-10 years, in order to describe these breakthroughs. In screening programs, AI is capable of not only detecting suspicious lung nodules in different imaging modalities-such as chest X-rays, computed tomography (CT), and positron emission tomography (PET) scans-but also discriminating between benign and malignant nodules as well, with success rates comparable to or even better than those of experienced radiologists. Furthermore, AI seems to be able to recognize biomarkers that appear in patients who may develop lung cancer, even years before this event. Moreover, it can also assist pathologists and cytologists in recognizing the type of lung tumor, as well as specific histologic or genetic markers that play a key role in treating the disease. Finally, in the treatment field, AI can guide in the development of personalized options for lung cancer patients, possibly improving their prognosis.

Anti-FDX1 Autoantibody as a Potential Biomarker for Non-Small Cell Lung Cancer Detection

BACKGROUND

Autoantibodies can be readily identified prior to biopsy and may serve as valuable biomarkers for cancer detection. Ferredoxin 1 (FDX1) is a key regulator in the process of cuproptosis and affects the prognosis of lung cancer. In this study, we investigated whether the anti-FDX1 autoantibody could serve as a novel biomarker for the detection of non-small cell lung cancer (NSCLC).

METHODS

A total of 1,155 plasma samples were divided into the verification and validation groups. The expression levels of the anti-FDX1 autoantibody in 414 patients with NSCLC, 327 patients with benign pulmonary nodules (BPN), and 414 normal controls (NC) were detected using ELISA. Western blotting and immunofluorescence analyses were performed to confirm the ELISA results.

RESULTS

Plasma anti-FDX1 autoantibody levels were significantly higher in patients with NSCLC than in patients with BPN and NCs in the verification and validation groups. The ELISA results were confirmed by Western blotting and immunofluorescence. The anti-FDX1 autoantibody distinguished NSCLC from NC and BPN with an AUC (95% confidence interval) of 0.806 (0.772-0.839) and 0.627 (0.584-0.670), respectively.

CONCLUSIONS

Our study demonstrated the potential benefits of the anti-FDX1 autoantibody as a novel biomarker for NSCLC detection.

IMPACT

These findings suggested that the anti-FDX1 autoantibody may facilitate the detection of NSCLC.

Diagnosis of Lung Cancer Using Endobronchial Ultrasonography Image Based on Multi-Scale Image and Multi-Feature Fusion Framework

Lung cancer is the leading cause of cancer-related deaths globally and ranks among the most common cancer types. Given its low overall five-year survival rate, early diagnosis and timely treatment are essential to improving patient outcomes. In recent years, advances in computer technology have enabled artificial intelligence to make groundbreaking progress in imaging-based lung cancer diagnosis. The primary aim of this study is to develop a computer-aided diagnosis (CAD) system for lung cancer using endobronchial ultrasonography (EBUS) images and deep learning algorithms to facilitate early detection and improve patient survival rates. We propose M3-Net, which is a multi-branch framework that integrates multiple features through an attention-based mechanism, enhancing diagnostic performance by providing more comprehensive information for lung cancer assessment. The framework was validated on a dataset of 95 patient cases, including 13 benign and 82 malignant cases. The dataset comprises 1140 EBUS images, with 540 images used for training, and 300 images each for the validation and test sets. The evaluation yielded the following results: accuracy of 0.76, F1-score of 0.75, AUC of 0.83, PPV of 0.80, NPV of 0.75, sensitivity of 0.72, and specificity of 0.80. These findings indicate that the proposed attention-based multi-feature fusion framework holds significant potential in assisting with lung cancer diagnosis.

The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations

BACKGROUND

Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibility and cost-effectiveness analysis of a community-based program that used a mobile low-dose computed tomography (LDCT) scan unit and discuss the operational challenges faced during its implementation.

METHODS

This study was conducted in rural areas in Fujian Province, China from July 2022 to August 2022. Individuals aged 40 years and above who had not previously undergone LDCT and who were socioeconomically marginalized were included. Participants received a LDCT program from a multidisciplinary research team. Physicians analyzed the images with the assistance of artificial intelligence "InferRead CT Lung Research" and completed structured reports on their impressions. The primary evaluation indicators for mobile LDCT screening effectiveness were the lung cancer detection rate and diagnosis rate, while the main evaluation indicators for cost-effective analysis were the cost-effective ratio and early detection cost index.

RESULTS

A total of 10,159 individuals participated in this study. The detection rates of suspected lung cancer cases and confirmed cases were 1.06% (n = 108) and 0.7% (n = 71), respectively. The cost of lung cancer screening (LCS) was ¥1,203,504 (US$188,847.71), the average cost per screening was ¥118.47 (US$18.65), and the cost effective ratios for the detection of suspected lung cancer and confirmed lung cancer were ¥11,143.56 (US$1,753.29) and ¥16,950.76 (US$2,669.94), respectively. The early detection cost indices for suspected lung cancer were 0.09 and 0.13 for confirmed lung cancer, respectively.

CONCLUSION

This LDCT with artificial intelligence model for LCS holds economic promise for reducing health disparities in underserved areas and promote larger populations in similar low-income country.

Assessing lung cancer progression and survival with infrared spectroscopy of blood serum

BACKGROUND

Infrared molecular fingerprinting has been identified as a new minimally invasive technological tool for disease diagnosis. While the utility of cross-molecular infrared fingerprints of serum and plasma for in vitro cancer diagnostics has been recently demonstrated, their potential for stratifying and predicting the prognosis of lung cancer remained unexplored. This study investigates the capability of this approach to predict survival and stratify lung cancer patients.

METHODS

Molecular fingerprinting through vibrational spectroscopy is employed to probe lung cancer. Fourier-transform infrared (FTIR) spectroscopy is applied to blood sera from 160 therapy-naive lung cancer patients, who were followed for up to 4 years. Machine learning is then utilized to evaluate the prognostic utility of this new approach. Additionally, a case-control study involving 501 individuals is analyzed to investigate the relationship between FTIR spectra and disease progression.

RESULTS

Overall, we establish a strong correlation between the infrared fingerprints and disease progression, specifically in terms of tumor stage. Furthermore, we demonstrate that infrared fingerprinting provides insights into patient survival at performance levels comparable to those of tumor stage and relevant blood-based biomarkers.

CONCLUSIONS

Identifying the combined capacity of infrared fingerprinting to complement primary lung cancer diagnostics and to assist in the assessment of lung cancer survival represents the first proof-of-concept study underscoring the potential of this profiling platform. This may provide new avenues for the development of tailored, personalized treatment decision-making.

Minimally invasive biomarkers for triaging lung nodules-challenges and future perspectives

CT chest scans are commonly performed worldwide, either in routine clinical practice for a wide range of indications or as part of lung cancer screening programs. Many of these scans detect lung nodules, which are small, rounded opacities measuring 8-30 mm. While the concern about nodules is that they may represent early lung cancer, in screening programs, only 1% of such nodules turn out to be cancer. This leads to a series of complex decisions and, at times, unnecessary biopsies for nodules that are ultimately determined to be benign. Additionally, patients may be anxious about the status of detected lung nodules. The high rate of false positive lung nodule detections has driven advancements in biomarker-based research aimed at triaging lung nodules (benign versus malignant) to identify truly malignant nodules better. Biomarkers found in biofluids and breath hold promise owing to their minimally invasive sampling methods, ease of use, and cost-effectiveness. Although several biomarkers have demonstrated clinical utility, their sensitivity and specificity are still relatively low. Combining multiple biomarkers could enhance the characterisation of small pulmonary nodules by addressing the limitations of individual biomarkers. This approach may help reduce unnecessary invasive procedures and accelerate diagnosis in the future. This review offers a thorough overview of emerging minimally invasive biomarkers for triaging lung nodules, emphasising key challenges and proposing potential solutions for biomarker-based nodule differentiation. It focuses on diagnosis rather than screening, analysing research published primarily in the past five years with some exceptions. The incorporation of biomarkers into clinical practice will facilitate the early detection of malignant nodules, leading to timely interventions and improved outcomes. Further efforts are needed to increase the cost-effectiveness and practicality of many of these applications in clinical settings. However, the range of technologies is advancing rapidly, and they may soon be implemented in clinics in the near future.

Multi-center study on the application potential of Siaα-2,6Gal in early and differential diagnosis of lung cancer

OBJECTIVE

This study aimed to investigate the application potential of the abnormal glycan structure Siaα-2,6Gal in the early and differential diagnosis of lung cancer.

METHODS

Clinical data and serum samples from 730 patients and 120 healthy individuals participating in clinical trials on Siaα-2,6Gal were collected at three medical centers between January 2022 and June 2023. The levels of Siaα-2,6Gal, carcinoembryonic antigen (CEA), cytokeratin 19 fragment antigen (CYFRA21-1), squamous cell carcinoma antigen (SCC), neuron-specific enolase (NSE), and pro-gastrin-releasing peptide (ProGRP) in serum were measured. The application potentials of these markers in the early and differential diagnosis, classification, and staging of lung cancer were explored.

RESULTS

(1) Serum Siaα-2,6Gal levels in the lung cancer group were 2,606 (1,970-3,458) U/mL, significantly higher than those in the benign lung disease, miscellaneous malignant tumor, miscellaneous benign disease, and healthy individual groups at 1,359 (950-1,528), 1,252 (903-1,532), 1,196 (850-1,490), and 1,210 (1,100-1,287) U/mL (P < 0.0001). (2) Serum Siaα-2,6Gal levels in the early-stage lung cancer (stages 0-II) group were 2,576 (1,929-3,338) U/mL, significantly higher than those in the benign pulmonary nodule group at 1,419 (1,105-1,820) U/mL (P < 0.0001). (3) Receiver operating characteristic curves showed that Siaα-2,6Gal had a high diagnostic efficiency for lung cancer (area under the curve (AUC) = 0.9217), significantly superior to CEA, CYFRA21-1, SCC, NSE, and ProGRP (AUCs of 0.6618, 0.6605, 0.5783, 0.5985, and 0.6381).

CONCLUSION

Siaα-2,6Gal is a promising biomarker for lung cancer diagnosis and may offer superior differential diagnosis of early-stage lung cancer from benign pulmonary nodules compared to traditional tumor markers.

Co-occurrence of bronchiectasis, airway wall thickening, and emphysema in Chinese low-dose CT screening

OBJECTIVE

To assess the co-occurrence of incidental CT lung findings (emphysema, bronchiectasis, and airway wall thickening) as well as associated risk factors in low-dose CT (LDCT) lung cancer screening in a Chinese urban population.

METHODS

Data from 978 participants aged 40-74 years from the Chinese NELCIN-B3 urban population study who underwent LDCT screening were selected. CT scans were reviewed for incidental lung findings: emphysema, bronchiectasis and airway wall thickness. Emphysema was defined in three ways (≥ trace, ≥ mild, or ≥ moderate) depending on severity. Participants were described and stratified by presence or absence of incidental lung findings. Logistic regression analyses were performed to examine the relationship between participant characteristics and CT findings.

RESULTS

Mean age was 61.3 years ± 6.8 and 533 (54.6%) were female. 48% of participants had incidental lung findings: 19.9% had emphysema (≥ mild), 9.2% had bronchiectasis, and 35.7% had airway wall thickening. Among 978 participants, 2.1% showed all three findings. Multivariable analysis showed that higher age (OR: 1.06; 95% CI: 1.04-1.08; p < 0.001), male sex (OR: 1.68; 95% CI: 1.14-2.47; p = 0.008) smoking history (OR: 1.76; 95% CI: 1.02-3.03; p = 0.04 for former smokers; OR: 2.45; 95% CI: 1.59-3.78; p < 0.001 for current smokers), and the presence of respiratory symptoms (OR: 1.42; 95% CI: 1.01-2.00; p = 0.04) were associated with the risk of having at least one incidental lung findings. When different definitions of emphysema were used, the results remained consistent.

CONCLUSION

In a Chinese urban population undergoing LDCT lung cancer screening, 48% had at least one incidental CT lung finding, which was associated with higher age, male sex, questionnaire-based respiratory symptoms and smoking history.

KEY POINTS

Question Reporting of incidental lung findings that indicate lung disease risk lacks consensus in the cancer screening setting and needs evidence of co-occurrence in general populations. Findings Almost half of the 978 participants had at least one incidental lung CT finding; these were associated with older age, male sex, respiratory symptoms, and smoking history. Clinical relevance Incidental lung findings and related risk factors are often observed in low-dose CT lung cancer screening, and careful consideration of their relevance should be given to their inclusion in future screenings.

The Positioning Method of Pulmonary Nodules in Thoracoscopic Surgery Based on CT Simulation Positioning System for Radiotherapy

PURPOSE

The application of wedge resection in thoracoscopic surgery is becoming more and more widely prevalent. However, achieving precise intraoperative positioning of the pulmonary nodules still poses challenges. This study proposed a method for surface positioning using a computed tomography (CT) simulation positioning system in the radiation physics room.

METHODS

After screening patients, the level of nodules was located under the CT simulation positioning system, and the pleural projection point of the nodule and the closest surface puncture point from this point to the body surface were determined by the laser positioning system. During the operation, a needle was inserted at a predetermined angle at the puncture point, leaving a pinhole in the visceral pleura. Finally, the distance between the true pleural projection point of the nodule and the pinhole was measured on the specimen.

RESULTS

The success rate of our positioning method was 97.2%. The average distance between the puncture pinhole location and the actual pleural projection point of the nodule was 8.1 mm. No related complications occurred during the perioperative period.

CONCLUSION

The new method of preoperative surface positioning and intraoperative lung positioning through puncture has a high success rate, good positioning accuracy, and good safety, which is worthy of clinical application.

Burdens of Tracheal, Bronchus, and Lung Cancer From 1990 to 2021 in China Compared to the Global Projection of 2036: Findings From the 2021 Global Burden of Disease Study

BACKGROUND

Tracheal, bronchial, and lung cancers (TBL cancers) pose a significant global health challenge, with rising incidence and mortality rates, particularly in China. Studies from the Global Burden of Disease (GBD), 2021, can guide screening and prevention strategies for TBL cancer. This study aims to provide a comprehensive analysis of the burden of TBL cancers in China compared to global data.

METHODS

We conducted an analysis of incidence, prevalence, mortality, and disability-adjusted life years (DALYs) from 1990 to 2021. We also performed Joinpoint regression analysis and Bayesian age-period-cohort (BAPC) modeling to project future trends.

RESULTS

From 1990 to 2021, there was a substantial increase in TBL cancer indicators for all sexes in China, with the most significant rise observed in females. The female population showed alarming increases in age-standardized incidence rate (ASIR) and age-standardized prevalence rate (ASPR). While global efforts have managed to stabilize these rates, China's figures remain high, suggesting the impact of persistent risk factors such as smoking and air pollution, coupled with an aging population. Furthermore, we utilized the projection model in China to estimate that these indicators of TBL cancers in females will likely follow continuous and rapid upward trends, while the burden of TBL cancers among males is expected to have a steady trend.

CONCLUSION

Although global efforts have been effective in reducing the burden of TBL cancers over the past three decades, there still remains strong regional and gender heterogeneity. TBL cancers need more screening strategies and medical attention in China and in the female population.

Multisite DNA methylation alterations of peripheral blood mononuclear cells serve as novel biomarkers for the diagnosis of AIS/stage I lung adenocarcinoma: a multicenter cohort study

BACKGROUND

Early diagnosis remains an obstacle for improving the outcome of lung adenocarcinoma (LUAD). DNA methylation changes in peripheral blood mononuclear cells (PBMCs) could reflect an immune response to tumorigenesis, providing the theoretical basis for early cancer diagnosis based on immune cell profiling.

METHODS

This multi-center study evaluated the DNA methylation patterns based on PBMCs samples from 1115 individuals at nine medical centers. Genome-wide DNA methylation profiling of PBMCs in a discovery cohort (35 LUAD patients and 50 healthy controls) was performed using Illumina 850K microarray. Candidate differentially methylated CpG positions (DMPs) were selected and validated in a two-step DMPs screening cohort (65 LUAD patients and 80 healthy controls) by pyrosequencing and multiple target region methylation enrichment sequencing (MTRMES). Then, an early LUAD Diagnostic Panel (LDP score) based on multisite methylation-specific chip-based digital PCR was constructed in a training set and then confirmed in a validation set from the LDP score development cohort (389 AIS/stage I LUAD patients and 293 healthy controls). Besides, we included 157 other cancer patients, including 52 gastric cancer (GC) patients, 50 breast cancer (BC) patients, and 55 colorectal cancer (CRC) patients to assess the specificity of the LDP score. In addition, we also evaluated the early warning ability of LDP score for LUAD in a prospective cohort (46 people who were at high-risk of developing LC).

RESULTS

A total of 1415 LUAD-specific DMPs were identified. Then, six DMPs were selected for validation and three DMPs were finally verified. The LDP score was constructed by combining the three DMPs, age, and sex, and showed an AUC of 0.916, sensitivity of 88.17%, and specificity of 80.20% in a combined set, outperforming traditional methods, such as CEA and CT (detection rate: 87.79% vs. 4.69%; 87.79% vs. 35.21%). This diagnostic performance was confirmed in sub-types of LUAD with clinical challenges, such as 6-20 mm LUAD (AUC: 0.914, 95% CI: 0.889-0.934) and ground-glass nodules (AUC: 0.916, 95% CI: 0.889-0.938). Importantly, our LDP score had significant improvement in terms of selecting high-risk individuals who should receive low-dose computed tomography (87.80% vs. 9.28%). Remarkably, the LDP score could predict LUAD around 2 years before clinical diagnosis in our prospective cohort.

CONCLUSIONS

The novel developed LDP score represented a convenient and effective assay for the detection of AIS/stage I LUAD with high sensitivity and specificity, and had demonstrated unique advantages over traditional detection methods.

The effectiveness and safety of computed tomography-guided hook-wire localization for secondary video-assisted thoracoscopic surgery: a retrospective study

Background

Computed tomography (CT)-guided hook-wire localization is currently the most commonly used technique for preoperative localization of pulmonary nodules in clinical practice. With the increasing incidence of multiple primary lung cancers and the increasing occurrence of second primary lung cancers or local recurrences after lung cancer surgery, some patients need to undergo an ipsilateral or contralateral second pulmonary resection. In order to reduce the surgical difficulty of the second operation and accurately guide the surgical resection, preoperative localization of some nodules is necessary. This study retrospectively analyzed the CT-guided hook-wire localization information of patients undergoing a second ipsilateral or contralateral video-assisted thoracoscopic surgery (VATS), discussed the safety and effectiveness of hook-wire localization for ipsilateral and contralateral surgeries, and analyzed the risk factors for complications after localization.

Methods

This study retrospectively collected data from 113 patients with isolated solitary pulmonary nodules who underwent a second pulmonary resection and completed CT-guided hook-wire localization at The First Affiliated Hospital of Soochow University from January 2020 to June 2024. The patients were divided into contralateral surgery group and ipsilateral surgery group to compare clinical characteristics, localization time, incidence of complications, and other information between the two groups. Logistic regression analysis was used to identify the risk factors for complications associated with the localization methods in each group.

Results

Compared to the contralateral group, the ipsilateral group had a longer interval between the two surgeries, which was 28.0±9.3 months (P<0.001). The maximum diameter of nodules in the ipsilateral group was 10.8±1.7 mm, higher than that in the contralateral group (P<0.001). There were no statistical differences between the two groups in terms of localization time, number of CT scans, depth of the release position, and incidence of complications. In the contralateral group, 25 patients (30.5%) developed pneumothorax, while in the ipsilateral group, there were 2 cases (6.5%), showing a statistically significant difference (P=0.008). In the contralateral group, 3.7% patients developed hemopneumothorax, while the incidence in the ipsilateral group was as high as 16.1% (P=0.04). Localization time [odds ratio (OR) =1.306, P=0.006] and depth of the release position (OR =1.202, P<0.001) were independent risk factors for the overall occurrence of complications and pneumothorax, while thoracic adhesions (OR =4.115, P=0.03) was an independent risk factor for hemopneumothorax. History of localization (OR =0.109, P=0.02) was identified as a protective factor for pneumothorax.

Conclusions

CT-guided hook-wire localization can effectively complete the localization of isolated nodules on the ipsilateral or contralateral side in patients requiring a second pulmonary resection, with similar safety. In the future, it is more advisable to promote more precise and personalized localization methods for different patients in clinical practice.

Comparison of Lung-RADS Version 2022 and British Thoracic Society Guidelines in Classifying Solid Pulmonary Nodules Detected at Lung Cancer Screening CT

BACKGROUND AND OBJECTIVES

Lung cancer screening is critical for early detection and management, particularly through the use of computed tomography (CT). This study aims to compare the Lung Imaging Reporting and Data System (Lung-RADS) Version 2022 with the British Thoracic Society (BTS) guidelines in classifying solid pulmonary nodules detected at lung cancer screening CT examinations.

MATERIALS AND METHODS

This retrospective study included 224 patients who underwent lung cancer screening CT between 2016 and 2022 and had a reported solid pulmonary nodule. A fellowship-trained thoracic radiologist reviewed the CT images, characterizing nodules by size, location, margins, attenuation, calcification, growth at follow-up, and final pathologic diagnosis if malignant. The sensitivity and specificity of Lung-RADS Version 2022 in detecting malignant nodules were compared with those of the BTS guidelines using the McNemar test.

RESULTS

Of the 224 patients, 198 (88%) had nodules deemed benign, while 26 (12%) had malignant nodules. The Lung-RADS Version 2022 resulted in higher specificity than the BTS guidelines (85% vs. 65%, p < 0.001), without sacrificing sensitivity (92% for both). Nodules larger than 8 mm, spiculated margins, upper lobe location, and interval growth were associated with higher malignancy risk (p < 0.01).

CONCLUSIONS

Compared with the BTS guidelines, Lung-RADS Version 2022 reduces the number of false-positive screening CT examinations while maintaining high sensitivity for detecting malignant solid pulmonary nodules.

The Global, Regional, and National Burden of Tracheal, Bronchus, and Lung Cancer Caused by Smoking: An Analysis Based on the Global Burden of Disease Study 2021

Background: Smoking is the primary risk factor for tracheal, bronchus, and lung (TBL) cancer. Objective: This study aims to explore the epidemiological trends of smoking-attributable TBL cancer from 1990 to 2021. Methods: Mortality and disability-adjusted life-years (DALYs) data for smoking-related TBL cancer from 1990 to 2021 were sourced from the Global Burden of Disease Study (GBD) 2021. Estimated annual percentage changes (EAPCs) were calculated to evaluate trends in age-standardized mortality rates (ASMRs) and age-standardized DALY rates (ASDRs). Additionally, the relationship between disease burden, EAPCs, and the sociodemographic index (SDI) was assessed. Findings: Compared with 1990, both the mortality and DALYs due to smoking-related TBL cancer substantially increased by 2021. However, during this period, ASMR [EAPC: -0.97; 95% confidence interval (CI): -1.05 to -0.89] and ASDR (EAPC: -1.29; 95% CI: -1.37 to -1.22) demonstrated a downward trend. ASMR and ASDR in females were consistently lower than in males. In 2021, East Asia had the highest ASMR, while Central Europe recorded the highest ASDR, with Greenland exhibiting the highest ASMR and ASDR at the national level. Nationally, ASMR for smoking-related TBL cancer in 2021 showed a positive correlation with SDI, while the EAPC of both ASMR and ASDR from 1990 to 2021 displayed a negative correlation with SDI. Furthermore, in 2021, the greatest number of deaths from smoking-related TBL cancer occurred in individuals aged 70-74, while DALYs were highest in the 65-69 age group. Conclusions: The burden of smoking-related TBL cancer varies across age, sex, geography, and SDI regions. Tailored public health interventions aligned with these epidemiological characteristics are essential for alleviating the disease burden.

Emerging trends and hotspots in lung cancer-prediction models research

Objective

In recent years, lung cancer-prediction models have become popular. However, few bibliometric analyses have been performed in this field.

Methods

This study aimed to reveal the scientific output and trends in lung cancer-prediction models from a global perspective. In this study, publications were retrieved and extracted from the Web of Science Core Collection (WoSCC) database. CiteSpace 6.1.R3 and VOSviewer 1.6.18 were used to analyze hotspots and theme trends.

Results

A marked increase in the number of publications related to lung cancer-prediction models was observed. A total of 2711 institutions from in 64 countries/regions published 2139 documents in 566 academic journals. China and the United States were the leading country in the field of lung cancer-prediction models. The institutions represented by Fudan University had significant academic influence in the field. Analysis of keywords revealed that lncRNA, tumor microenvironment, immune, cancer statistics, The Cancer Genome Atlas, nomogram, and machine learning were the current focus of research in lung cancer-prediction models.

Conclusions

Over the last two decades, research on risk-prediction models for lung cancer has attracted increasing attention. Prognosis, machine learning, and multi-omics technologies are both current hotspots and future trends in this field. In the future, in-depth explorations using different omics should increase the sensitivity and accuracy of lung cancer-prediction models and reduce the global burden of lung cancer.

The Pivotal Role of Baseline LDCT for Lung Cancer Screening in the Era of Artificial Intelligence

In this narrative review, we address the ongoing challenges of lung cancer (LC) screening using chest low-dose computerized tomography (LDCT) and explore the contributions of artificial intelligence (AI), in overcoming them. We focus on evaluating the initial (baseline) LDCT examination, which provides a wealth of information relevant to the screening participant's health. This includes the detection of large-size prevalent LC and small-size malignant nodules that are typically diagnosed as LCs upon growth in subsequent annual LDCT scans. Additionally, the baseline LDCT examination provides valuable information about smoking-related comorbidities, including cardiovascular disease, chronic obstructive pulmonary disease, and interstitial lung disease (ILD), by identifying relevant markers. Notably, these comorbidities, despite the slow progression of their markers, collectively exceed LC as ultimate causes of death at follow-up in LC screening participants. Computer-assisted diagnosis tools currently improve the reproducibility of radiologic readings and reduce the false negative rate of LDCT. Deep learning (DL) tools that analyze the radiomic features of lung nodules are being developed to distinguish between benign and malignant nodules. Furthermore, AI tools can predict the risk of LC in the years following a baseline LDCT. AI tools that analyze baseline LDCT examinations can also compute the risk of cardiovascular disease or death, paving the way for personalized screening interventions. Additionally, DL tools are available for assessing osteoporosis and ILD, which helps refine the individual's current and future health profile. The primary obstacles to AI integration into the LDCT screening pathway are the generalizability of performance and the explainability.

The Potential Benefit of a Novel Urine Biosensor Platform for Lung Cancer Detection in the Decision-Making Process: From the Bench to the Bedside

Background: Lung cancer is the leading cause of cancer-related mortality worldwide. Lung cancer screening and early detection resulted in a decrease in cancer-specific mortality; however, it introduced additional dilemmas and adherence barriers for patients and providers. Methods: Innovations such as biomolecular diagnosis and biosensor-based technology improve the detection and stratification of high-risk patients and might assist in overcoming adherence barriers, hence providing new horizons for better selection of screened populations. Conclusions: In the present manuscript, we discuss some of the dilemmas clinicians are currently facing during the diagnosis and treatment processes. We further highlight the potential benefits of a novel biosensor platform for lung cancer detection during the decision making process surrounding lung cancer.

A predictive model of computed tomography and clinical features of EGFR gene mutation in lung adenocarcinoma

Purpose: This study aims to develop a predictive model for epidermal growth factor receptor (EGFR) mutations in lung adenocarcinoma by integrating computed tomography (CT) imaging features with clinical characteristics. Methods: A retrospective analysis was conducted using electronic medical records from 194 patients diagnosed with lung adenocarcinoma between January 2016 and December 2020, with approval from the institutional review board. Features were selected using LASSO regression, and predictive models were built using logistic regression, support vector machine, and random forest methods. Individual models were created for clinical features, CT imaging features, and a combined model to predict EGFR mutations. Results: The training set revealed that alcohol consumption, intrapulmonary metastasis, and pleural effusion were statistically significant in distinguishing between wild-type and mutation groups (p < 0.05). In the testing set, hilar and mediastinal lymphadenopathy showed statistical significance (p < 0.05). The combined model outperformed the individual clinical and CT imaging feature models. In the testing set, the logistic regression model achieved the highest AUC of 0.827, with sensitivity, specificity, and accuracy of 0.714, 0.712, and 0.712, respectively. Nomogram analysis identified lobulation as an important feature, with a predicted probability of up to 0.9. The decision curve analysis showed that the CT imaging feature model provided a higher net benefit compared to both the clinical feature model and the combined model. Conclusion: In summary, while the combined model outperformed the individual feature models in the testing set, the CT imaging feature model demonstrated the greatest clinical net benefit. Lobulation was identified as an important predictor of EGFR mutations in lung adenocarcinoma.

Safety and efficacy of percutaneous biopsy and microwave ablation in patients with pulmonary nodules on antithrombotic therapy: A study with rivaroxaban bridging

BACKGROUND

To evaluate the safety and efficacy of percutaneous biopsy and microwave ablation (B + MWA) in patients with pulmonary nodules (PNs) who are receiving antithrombotic therapy by rivaroxaban as bridging therapy.

METHODS

The study comprised 187 patients with PNs who underwent 187 B + MWA sessions from January 1, 2020, to December 31, 2021. The enrolled patients were divided into two groups: Group A, who received antithrombotic therapy five days before the procedure and received rivaroxaban as a bridging drug during hospitalization, and group B, who had no antithrombotic treatment. Information about the technical success rate, positive biopsy rate, complete ablative rate, and major complications were collected and analyzed.

RESULTS

Group A comprised 53 patients and group B comprised 134 patients. The technical success rate was 100% in both groups. The positive biopsy rates were 88.68% and 91.04%, respectively (p = 0.6211, X2 = 0.2443). In groups A and B, the complete ablative rates at 6, 12, and 24 months were 100.0% versus 99.25%, 96.23% versus 96.27%, and 88.68% versus 89.55%, respectively. There were no significant differences in bleeding and thrombotic complications between the two groups. No grade 5 complications occurred.

CONCLUSIONS

It is generally considered safe and effective that patients who are on antithrombotic therapy by rivaroxaban as bridging to undergo B + MWA for treating PNs.

Correlation of LOXL2 expression in non-small cell lung cancer with immunotherapy

Lung cancer is the most prevalent and lethal disease globally, with approximately 80% of cases being non-small cell lung cancer (NSCLC). NSCLC is primarily composed of lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Despite chemotherapy currently being the primary treatment for NSCLC, chemotherapy resistance remains a significant challenge for patients. Recent studies have proposed immunotherapy as a promising new avenue for treating NSCLC. The association between the lysyl oxidase-like 2 (LOXL2) gene and NSCLC was explored using multiple online tools and bioinformatics analysis software based on the available datasets from TCGA. The immune microenvironment of the tumor was explored by calculating ImmuneScore, StromalScore, and TumorPurity of LUAD and LUSC and analyzing the infiltration of 22 immune cells in lung cancer tissues. LOXL2-related loads were obtained from the Xena database for LUSC and LUAD patients, and relevant prognostic genes were identified by analyzing survival curves. Functional and pathway enrichment analyses of prognostic, predictive genes were performed using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The expression of LOXL2 in NSCLC was detected by RT-qPCR. LOXL2 may be involved in the progression of LUAD and LUSC and is closely related to the T-lymphocyte subpopulation, T-reg cells. SEMA7A and VEGFC are identified as the genes that interact with LOXL2 and could be used as prognostic signature genes in NSCLC patients. LOXL2 may become a prognostic marker and a new target for immunotherapy.

Comparative Study of Indocyanine Green Intravenous Injection and the Inflation-Deflation Method for Assessing Resection Margins in Segmentectomy for Lung Cancer: A Single-Center Retrospective Study

Background

The inflation-deflation (ID) method has long been the standard for intraoperative margin assessment in segmentectomy. However, with advancements in vision technology, the use of near-infrared mapping with indocyanine green (ICG) has become increasingly common. This study was conducted to compare the perioperative outcomes and resection margins achieved using these methods.

Methods

This retrospective study included patients who underwent direct segmentectomy for clinical stage I lung cancer between January 2018 and September 2022. We compared perioperative factors, including bronchial and parenchymal resection margins, according to the margin assessment method and the type of segmentectomy performed. Since the ICG approach was adopted in April 2021, we also examined a recent subgroup of patients treated from then onward.

Results

A total of 319 segmentectomies were performed. ID and ICG were utilized for 261 (81.8%) and 58 (18.2%) patients, respectively. Following April 2021, 61 patients (51.3%) were treated with ID, while 58 (48.7%) received ICG. We observed no significant difference in resection margins between ID and ICG for bronchial (2.7 cm vs. 2.3 cm, p=0.07) or parenchymal (2.5 cm vs. 2.3 cm, p=0.46) margins. Additionally, the length of hospitalization and the complication rate were comparable between groups. Analysis of the recent subgroup confirmed these findings, showing no significant differences in resection margins (bronchial: 2.6 cm vs. 2.3 cm, p=0.25; parenchymal: 2.4 cm vs. 2.3 cm, p=0.75), length of hospitalization, or complication rate.

Conclusion

The perioperative outcomes and resection margins achieved using ID and ICG were comparable, suggesting that both methods can safely guide segmentectomy procedures.

Gender-specific outcomes of low-dose computed tomography screening for lung cancer detection: A retrospective study in Chinese never-smoker population

OBJECTIVES

Low-dose computed tomography (LDCT) has emerged as a pivotal tool for detecting lung cancer among ever-smokers. This study aims to evaluate the gender-specific outcomes of LDCT screening within the Chinese never-smoking population.

METHODS

We conducted a single-center, retrospective cohort study, which analyzed LDCT screening outcomes for 42,018 asymptomatic participants. Specifically, we focused on assessing gender-specific differences in the prevalence of pulmonary nodules, and the incidence of lung cancer diagnosis among never-smokers.

RESULTS

Among the 42,018 eligible participants, 41.50% were females and 58.50% were males. Most participants were non-smokers (77.57%), with a significantly higher proportion of non-smokers among females than males (99.33% vs. 62.14%). Pulmonary nodules were identified in 2.66% of participants, with a higher prevalence in females (2.99%) than males (2.43%) (p < 0.001). Non-smoking females had a higher incidence of positive nodules than non-smoking males (2.98% vs. 2.38%, p < 0.001). Invasive biopsies were performed in 334 individuals with nodules, confirming lung cancer in 258 cases. The majority of these cancer cases were non-smokers (212), with non-smoking females showing a higher incidence (0.85%) compared to males (0.43%) (p < 0.001). There was no significant difference in the false-positive rates between non-smoking females (0.14%) and males (0.13%). Multivariate analysis showed that never-smoking women were more likely to undergo biopsies (OR 1.65, p = 0.0016) and had a higher, though not statistically significant, probability of lung cancer diagnosis (OR 1.84, p = 0.06).

CONCLUSION

This study elucidates sex-based differences within the Chinese population, revealing a higher prevalence of pulmonary nodules and lung cancers among non-smoking females. These findings offer valuable reference for both clinical practice and future research initiatives.

Global, regional, and national burden of tracheal, bronchus, and lung cancer and its risk factors from 1990 to 2021: findings from the global burden of disease study 2021

Background

Studies from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2021 can guide screening and prevention strategies for tracheal, bronchus, and lung (TBL) cancer. We aim to provide global, regional, and national estimates of the TBL cancer burden and its attributable risk from 1990 to 2021, including during the coronavirus disease 2019 (COVID-19) pandemic.

Methods

Incidence, age-standardised incidence rate (ASIR), deaths, age-standardised mortality rate (ASMR), disability-adjusted life years (DALYs), age-standardised rate of DALYs (ASDR), and the burden due to risk factors associated with TBL cancer were analysed from 1990 to 2021. Trends in ASIR, ASMR, and ASDR of TBL cancer during the COVID-19 pandemic (2019-2021) were also determined. All statistical analyses were performed using Join-point software (version 4.9.1.0).

Findings

Between 1990 and 2021, the global incidence, deaths, and DALYs of TBL cancer to varying degrees. However, the ASIR (Average Annual Percent Change [AAPC], -0.3 [-0.4 to -0.2]), ASMR (AAPC, -0.5 [-0.7 to -0.4]), and ASDR (AAPC, -0.9 [-1.0 to -0.7]) all showed a decreasing trend. However, the ASIR, ASMR, and ASDR of TBL cancer in males all showed a decreasing trend from 1990 to 2021. In contrast, the ASIR and ASMR of TBL cancer in females showed an increasing trend, while the ASDR showed a relatively stable trend. During the COVID-19 pandemic, the trends for ASIR, ASMR, and ASDR remained stable across both sexes combined, females, males, five socio-demographic index (SDI) quintiles, and the 21 GBD regions. In 2021, smoking was a major risk factor for TBL cancer DALYs, but the attributable ASDR for smoking decreased from 1990 to 2021 in both sexes combined, as well as individually for males and females. Conversely, the attributable ASDR for secondhand smoke, high fasting plasma glucose and occupational exposure factors increased primarily among females. Furthermore, the attributable ASDR for ambient particulate matter pollution, household air pollution from solid fuels, and low-fruit diets increased primarily in regions with lower SDI quintiles from 1990 to 2021.

Interpretation

The burden attributable to TBL cancer has increased in some populations from 1990 to 2021, highlighting the importance of implementing targeted measures to mitigate this trend. No significant change in the burden of TBL cancer was observed during the COVID-19 pandemic; however, post-COVID-19 rates still require further observation.

Funding

This study was supported by National Key Research and Development Program of China (2023YFC3503300, 2023YFC3503305), and High Level Chinese Medical Hospital Promotion Project (HLCMHPP2023085, HLCMHPP2023001, HLCMHPP2023097).

Cost-Effectiveness of Lung Cancer Screening with Low-Dose Computed Tomography: Comparing Hungarian Screening Protocols with the US NLST

We aimed to directly compare the cost-effectiveness of Hungarian (following the NELSON trial) and NLST screening protocols, two trials influencing lung-cancer-screening implementation internationally. A decision-analytic model analyzing the cost-effectiveness of Hungarian protocols was manipulated to reflect the protocols of the NLST, while maintaining features specific to the Hungarian healthcare setting. In the Hungarian protocol, there are three possible outcomes to the initial round of screening, positive, negative, and indeterminate, indicating an uncertain degree of suspicion for lung cancer. This protocol differs from the NLST, in which the only possible screening outcomes are positive or negative, with no indeterminate option. The NLST pathway for smokers aged 55-74 resulted in a EUR 43 increase in the total average lifetime costs compared to the Hungarian screening pathway and resulted in a lifetime gain of 0.006 QALYs. The incremental costs and QALYs yielded an ICER of 7875 EUR/QALY. Our results demonstrate that assigning any suspicious LDCT screen as a positive result (NLST protocol) rather than indeterminate (Hungarian protocol) can reduce patient uncertainty and yield a slight QALY gain that is worth the additional use of resources according to Hungary's willingness-to-pay threshold. A stratified analysis by age was also conducted, revealing decreasing cost-effectiveness when screening older cohorts. Our study provides insight into the cost-effectiveness, advantages, and disadvantages of various LDCT screening protocols for lung cancer and can assist other countries as they implement their screening programs.

Is There a Link between Chronic Obstructive Pulmonary Disease and Lung Adenocarcinoma? A Clinico-Pathological and Molecular Study

Chronic Obstructive Pulmonary Disease (COPD) and lung cancer are strictly related. To date, it is unknown if COPD-associated cancers are different from the tumors of non-COPD patients. The main goal of the study was to compare the morphological/molecular profiles of lung adenocarcinoma (LUAD) samples of COPD, non-COPD/smokers and non-COPD/non-smokers, and to investigate if a genetic instability also characterized non-pathological areas. This study included 110 patients undergoing surgery for a LUAD, divided into three groups: COPD/smoker LUAD (38), non-COPD/smoker LUAD (54) and non-COPD/non-smoker LUAD (18). The tissue samples were systemically evaluated by pathologists and analyzed using a 30-gene Next Generation Sequencing (NGS) panel. In a subset of patients, tissues taken far from the neoplasia were also included. The non-COPD/smoker LUAD were characterized by a higher proliferative index (p = 0.001), while the non-COPD/non-smoker LUAD showed higher percentages of lepidic pattern (p = 0.008), lower necrosis, higher fibrosis, and a significantly lower mutation rate in the KRAS and PIK3CA genes. Interestingly, the same gene mutations were found in pathological and normal areas exclusively in the COPD/smokers and non-COPD/smokers. COPD/smoker LUAD seem to be similar to non-COPD/smoker LUAD, particularly for the genetic background. A less aggressive cancer phenotype was confirmed in non-COPD/non-smokers. The genetic alterations detected in normal lungs from smokers with and without COPD reinforce the importance of screening to detect early neoplastic lesions.

Postoperative chronic operation-related symptoms after minimally invasive lung surgery: a prospective observational protocol

INTRODUCTION

Significant numbers of patients undergoing minimally invasive lung surgery develop chronic symptoms such as chronic pain and chronic cough after surgery, which may lead to a reduced quality of life (QoL). Despite this, there remains a dearth of high-quality prospective studies on this topic. Therefore, our study aims to systematically investigate the incidence and progression of long-term chronic symptoms following minimally invasive lung surgery, as well as changes in patient's psychological status and long-term QoL.

METHODS

This is a single-centre, observational, prospective study that included patients with stage I non-small cell lung cancer or benign lesions. Prior to surgery, patients' baseline levels of chronic pain, chronic cough and sleep will be documented. Anxiety, depression and QoL assessments will be conducted using the Hospital Anxiety and Depression Scale (HADS) and the European Organisation for Research and Treatment of Cancer (EORTC) 30-item QoL Questionnaire (QLQ-C30). Following surgery, pain and cough will be evaluated during the initial 3 days using the Numeric Pain Rating Scale and Visual Analogue Scale score, with assessments performed thrice daily. Additionally, sleep status will be recorded daily during this period. Subsequently, postoperative chronic symptoms and QoL will be assessed at weeks 1, 2, 4, 12, 26 and 52. Chronic cough will be evaluated using the Leicester Cough Questionnaire, chronic pain will be assessed via the Brief Pain Inventory and McGill Pain Questionnaire while the EORTC QLQ-C30 questionnaire and HADS will provide continuous monitoring of QoL, anxiety and depression statuses. Data will also include the timing of chronic symptom onset, predisposing factors, as well as aggravating and relieving factors.

ETHICS AND DISSEMINATION

Ethical approval was obtained from the Ethics Committees of Fujian Medical University Union Hospital. The findings will be disseminated in peer-reviewed publications.

TRIAL REGISTRATION NUMBER

NCT06016881.

Functional status in patients undergoing lung resection

Introduction

This prospective study aimed to evaluate the functional status and risk factors in patients undergoing lung resection.

Methods

Functional status defined by the parameters of spirometry (VC, FVC, FEV1, FEV1/FVC) and whole-body plethysmography (TLC) examination was assessed before lung resection, at hospital discharge, 3 weeks after surgery, and 3 months after surgery.

Results

The sample comprised 24 participants who were observed from 5/2021 to 10/2022. The functional status worsened significantly after the surgery, but the lung function values improved over time.

Conclusions

Lung functions dropped sharply after the surgery but improved over time.

Screening for lung cancer using thin-slice low-dose computed tomography in southwestern China: a population-based real-world study

OBJECTIVES

Lung cancer is one of the most common malignant tumors threatening human life and health. At present, low-dose computed tomography (LDCT) screening for the high-risk population to achieve early diagnosis and treatment of lung cancer has become the first choice recommended by many authoritative international medical organizations. To further optimize the lung cancer screening method, we conducted a real-world study of LDCT lung cancer screening in a large sample of a healthy physical examination population, comparing differences in lung nodules and lung cancer detection between thin and thick-slice LDCT scanning.

METHODS

A total of 29 296 subjects who underwent low-dose thick-slice CT scanning (5 mm thickness) from January 2015 to December 2015 and 28 058 subjects who underwent low-dose thin-slice CT scanning (1 mm thickness) from January 2018 to December 2018 in West China Hospital were included. The positive detection rate, detection rate of lung cancer, pathological stage of lung cancer, and mortality rate of lung cancer were analyzed and compared between the two groups.

RESULTS

The positive rate of LDCT screening in the thin-slice scanning group was significantly higher than that in the thick-slice scanning group (20.1% vs. 14.4%, p < 0.001). In addition, the lung cancer detection rate in the thin-slice LDCT screening positive group was significantly higher than that in the thick-slice scanning group (78.0% vs. 52.9%, p < 0.001).

CONCLUSIONS

The screening positive rate of low-dose thin-slice CT scanning is higher and more early-stage lung cancer (IA1 stage) can be detected in the screen-positive group.

Screening for liver fibrosis: lessons from colorectal and lung cancer screening

Many countries have incorporated population screening programmes for cancer, such as colorectal and lung cancer, into their health-care systems. Cirrhosis is more prevalent than colorectal cancer and has a comparable age-standardized mortality rate to lung cancer. Despite this fact, there are no screening programmes in place for early detection of liver fibrosis, the precursor of cirrhosis. In this Perspective, we use insights from colorectal and lung cancer screening to explore the benefits, challenges, implementation strategies and pathways for future liver fibrosis screening initiatives. Several non-invasive methods and referral pathways for early identification of liver fibrosis exist, but in addition to accurate detection, screening programmes must also be cost-effective and demonstrate benefit through a reduction in liver-related mortality. Randomized controlled trials are needed to confirm this. Future randomized screening trials should evaluate not only the screening tests, but also interventions used to halt disease progression in individuals identified through screening.

Exhaled VOC detection in lung cancer screening: a comprehensive meta-analysis

BACKGROUND

Lung cancer (LC), characterized by high incidence and mortality rates, presents a significant challenge in oncology. Despite advancements in treatments, early detection remains crucial for improving patient outcomes. The accuracy of screening for LC by detecting volatile organic compounds (VOCs) in exhaled breath remains to be determined.

METHODS

Our systematic review, following PRISMA guidelines and analyzing data from 25 studies up to October 1, 2023, evaluates the effectiveness of different techniques in detecting VOCs. We registered the review protocol with PROSPERO and performed a systematic search in PubMed, EMBASE and Web of Science. Reviewers screened the studies' titles/abstracts and full texts, and used QUADAS-2 tool for quality assessment. Then performed meta-analysis by adopting a bivariate model for sensitivity and specificity.

RESULTS

This study explores the potential of VOCs in exhaled breath as biomarkers for LC screening, offering a non-invasive alternative to traditional methods. In all studies, exhaled VOCs discriminated LC from controls. The meta-analysis indicates an integrated sensitivity and specificity of 85% and 86%, respectively, with an AUC of 0.93 for VOC detection. We also conducted a systematic analysis of the source of the substance with the highest frequency of occurrence in the tested compounds. Despite the promising results, variability in study quality and methodological challenges highlight the need for further research.

CONCLUSION

This review emphasizes the potential of VOC analysis as a cost-effective, non-invasive screening tool for early LC detection, which could significantly improve patient management and survival rates.

Nanomaterials promote the fast development of electrochemical MiRNA biosensors

Cancer has become the leading cause of death worldwide. In recent years, molecular diagnosis has demonstrated great potential in the prediction and diagnosis of cancer. MicroRNAs (miRNAs) are short oligonucleotides that regulate gene expression and cell function and are considered ideal biomarkers for cancer detection, diagnosis, and patient prognosis. Therefore, the specific and sensitive detection of ultra-low quantities of miRNA is of great significance. MiRNA biosensors based on electrochemical technology have advantages of high sensitivity, low cost and fast response. Nanomaterials show great potential in miRNA electrochemical detection and promote the rapid development of electrochemical miRNA biosensors. Some methods and signal amplification strategies for miRNA detection in recent years are reviewed herein, followed by a discussion of the latest progress in electrochemical miRNA detection based on different types of nanomaterial. Future perspectives and challenges are also proposed for further exploration of nanomaterials to bring breakthroughs in electrochemical miRNA detection.

Exploring shared decision-making needs in lung cancer screening among high-risk groups and health care providers in China: a qualitative study

BACKGROUND

The intricate balance between the advantages and risks of low-dose computed tomography (LDCT) impedes the utilization of lung cancer screening (LCS). Guiding shared decision-making (SDM) for well-informed choices regarding LCS is pivotal. There has been a notable increase in research related to SDM. However, these studies possess limitations. For example, they may ignore the identification of decision support and needs from the perspective of health care providers and high-risk groups. Additionally, these studies have not adequately addressed the complete SDM process, including pre-decisional needs, the decision-making process, and post-decision experiences. Furthermore, the East-West divide of SDM has been largely ignored. This study aimed to explore the decisional needs and support for shared decision-making for LCS among health care providers and high-risk groups in China.

METHODS

Informed by the Ottawa Decision-Support Framework, we conducted qualitative, face-to-face in-depth interviews to explore shared decision-making among 30 lung cancer high-risk individuals and 9 health care providers. Content analysis was used for data analysis.

RESULTS

We identified 4 decisional needs that impair shared decision-making: (1) LCS knowledge deficit; (2) inadequate supportive resources; (3) shared decision-making conceptual bias; and (4) delicate doctor-patient bonds. We identified 3 decision supports: (1) providing information throughout the LCS process; (2) providing shared decision-making decision coaching; and (3) providing decision tools.

CONCLUSIONS

This study offers valuable insights into the decisional needs and support required to undergo LCS among high-risk individuals and perspectives from health care providers. Future studies should aim to design interventions that enhance the quality of shared decision-making by offering LCS information, decision tools for LCS, and decision coaching for shared decision-making (e.g., through community nurses). Simultaneously, it is crucial to assess individuals' needs for effective deliberation to prevent conflicts and regrets after arriving at a decision.

[Results of Lung Cancer Screening with Low-dose Computed Tomography and Exploration of Risk Factors in Guangzhou]

BACKGROUND

Both of lung cancer incidence and mortality rank first among all cancers in China. Previous lung cancer screening trials were mostly selective screening for high-risk groups such as smokers. Non-smoking women accounted for a considerable proportion of lung cancer cases in Asia. This study aimed to evaluate the outcome of community-based mass screening in Guangzhou and identify the high-risk factors for lung cancer.

METHODS

Residents aged 40-74 years in Guangzhou were screened with low-dose computed tomography (LDCT) for lung cancer and the pulmonary nodules were classified and managed according to China National Lung Cancer Screening Guideline with Low-dose Computed Tomography (2018 version). The detection rate of positive nodules was calculated. Before the LDCT examination, residents were required to complete a "lung cancer risk factors questionnaire". The risk factors of the questionnaire were analyzed by least absolute shrinkage and selection operator (LASSO) penalized Logistic regression analysis.

RESULTS

A total of 6256 residents were included in this study. 1228 positive nodules (19.63%) and 117 lung cancers were confirmed, including 6 cases of Tis, 103 cases of stage I (accounting for 88.03% of lung cancer). The results of LASSO penalized Logistic regression analysis indicated that age ≥50 yr (OR=1.07, 95%CI: 1.06-1.07), history of cancer (OR=3.29, 95%CI: 3.22-3.37), textile industry (OR=1.10, 95%CI: 1.08-1.13), use coal for cooking in childhood (OR=1.14, 95%CI: 1.13-1.16) and food allergy (OR=1.10, 95%CI: 1.07-1.13) were risk factors of lung cancer for female in this district.

CONCLUSIONS

This study highlighted that numerous early stages of lung cancer cases were detected by LDCT, which could be applied to screening of lung cancer in women. Besides, age ≥50 yr, personal history of cancer, textile industry and use coal for cooking in childhood are risk factors for women in this district, which suggested that it's high time to raise the awareness of early lung cancer screening in this group.

Clinical application of computed tomographic volumetric imaging in postoperative lung function assessment in patients with lung cancer

BACKGROUND

To evaluate the effectiveness of the computed tomographic (CT) volumetric analysis in postoperative lung function assessment and the predicting value for postoperative complications in patients who had segmentectomy for lung cancer.

METHODS

CT scanning and pulmonary function examination were performed for 100 patients with lung cancer. CT volumetric analyses were performed by specific software, for the volume of the inspiratory phase (Vin), the mean inspiratory lung density (MLDin), the volume of expiratory phase (Vex), and the mean lung density at expiratory phase (MLDex). Pulmonary function examination results and CT volumetric analysis results were used to predict postoperative lung function. The concordance and correlations of these values were assessed by Bland-Altman analysis and Pearson correlation analysis, respectively. Multivariate binomial logistic regression analysis was executed to assess the associations of CT data with complication occurrence.

RESULTS

Correlations between CT scanning data and pulmonary function examination results were significant in both pre- and post-operation (0.8083 ≤ r ≤ 0.9390). Forced vital capacity (FVC), forced expiratory volume in the first second (FEV1), and the ratio of FVC and FEV1 estimated by CT volumetric analyses showed high concordance with those detected by pulmonary function examination. Preoperative (Vin-Vex) and (MLDex- MLDin) values were identified as predictors for post-surgery complications, with hazard ratios of 5.378 and 6.524, respectively.

CONCLUSIONS

CT volumetric imaging analysis has the potential to determine the pre- and post-operative lung function, as well as to predict post-surgery complication occurrence in lung cancer patients with pulmonary lobectomy.

Plasma Metabolite Profiling in the Search for Early-Stage Biomarkers for Lung Cancer: Some Important Breakthroughs

Lung cancer is the leading cause of cancer-related mortality worldwide. In order to improve its overall survival, early diagnosis is required. Since current screening methods still face some pitfalls, such as high false positive rates for low-dose computed tomography, researchers are still looking for early biomarkers to complement existing screening techniques in order to provide a safe, faster, and more accurate diagnosis. Biomarkers are biological molecules found in body fluids, such as plasma, that can be used to diagnose a condition or disease. Metabolomics has already been shown to be a powerful tool in the search for cancer biomarkers since cancer cells are characterized by impaired metabolism, resulting in an adapted plasma metabolite profile. The metabolite profile can be determined using nuclear magnetic resonance, or NMR. Although metabolomics and NMR metabolite profiling of blood plasma are still under investigation, there is already evidence for its potential for early-stage lung cancer diagnosis, therapy response, and follow-up monitoring. This review highlights some key breakthroughs in this research field, where the most significant biomarkers will be discussed in relation to their metabolic pathways and in light of the altered cancer metabolism.

Is low-dose computed tomography for lung cancer screening conveniently accessible in China? A spatial analysis based on cross-sectional survey

BACKGROUND

Regular Low-Dose Computed Tomography (LDCT) for lung cancer high-risk population has been proved to improve health outcomes and relieve disease burden efficiently for both individual and society. With geographical impedance becoming the major barrier preventing patients from getting timely healthcare service, this study incorporated health seeking behavior in estimating spatial accessibility of relative scarce LDCT resource in China, thus to provide real-world evidence for future government investment and policy making.

METHODS

Taking Sichuan Province in southwest China as the study area, a cross-sectional survey was first carried out to collect actual practice and preferences for seeking LDCT services. Using Computed Tomography (CT) registration data reported by owner institutions representing LDCT services capacity, and grided town-level high-risk population as demand, the Nearest Neighbor Method was then utilized to calculate spatial accessibility of LDCT services.

RESULTS

A total of 2,529 valid questionnaires were collected, with only 34.72% of the high-risk populations (746 individuals) followed the recommended annual screening. Participants preferred to travel to municipal-level and above institutions within 60 min for LDCT services. Currently, every thousand high-risk populations own 0.0845 CT scanners in Sichuan Province, with 96.95% able to access LDCT within 60 min and over half within 15 min. Urban areas generally showed better accessibility than rural areas, and the more developed eastern regions were better than the western regions with ethnic minority clusters.

CONCLUSIONS

Spatial access to LDCT services is generally convenient in Sichuan Province, but disparity exists between different regions and population groups. Improving LDCT capacity in county-level hospitals as well as promoting health education and policy guidance to the public can optimize efficiency of existing CT resources. Implementing mobile CT services and improving rural public transportation may alleviate emerging disparities in accessing early lung cancer detection.

A disulfidptosis-related lncRNA signature for predicting prognosis and evaluating the tumor immune microenvironment of lung adenocarcinoma

As a novel form of regulated cell death (RCD), disulfidptosis offering a significant opportunity in better understanding of tumor pathogenesis and therapeutic strategies. Long non-coding RNAs (lncRNAs) regulate the biology functions of tumor cells by engaging with a range of targets. However, the prognostic value of disulfidptosis-related lncRNAs (DRlncRNAs) in lung adenocarcinoma (LUAD) remains unclear. Therefore, our study aimed at establishing a prognostic model for LUAD patients based on DRlncRNAs. RNA-seq data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Subsequently, a prognostic model based on DRlncRNAs was constructed using LASSO and COX regression analysis. Patients were stratified into high- and low-risk groups based on their risk scores. Differences between the high-risk and low-risk groups were investigated in terms of overall survival (OS), functional enrichment, tumor immune microenvironment (TIME), somatic mutations, and drug sensitivity. Finally, the role of lncRNA GSEC in LUAD was validated through in vitro experiments. Using the prognostic model consists of 5 DRlncRNAs (AL365181.2, GSEC, AC093673.1, AC012615.1, AL606834.1), the low-risk group exhibited a markedly superior survival in comparison to the high-risk group. The significant differences were observed among patients from different risk groups in OS, immune cell infiltration, immune checkpoint expression, immunotherapy response, and mutation landscape. Experimental results from cellular studies demonstrate the knockdown of lncRNA GSEC leading to a significant reduction in the proliferation and migration abilities of LUAD cells. Our prognostic model, constructed using 5 DRlncRNAs, exhibited the capacity to independently predict the survival of LUAD patients, providing the potentially significant assistance in prognosis prediction, and treatment effects optimization. Moreover, our study established a foundation for further research on disulfidptosis in LUAD and proposed new perspectives for the treatment of LUAD.

Analysis of screening outcomes and factors influencing compliance among community-based lung cancer high-risk population in Nanchang, China, 2018-2020

Objective

To investigate the screening results and compliance of low-dose computed tomography (LDCT) screening among the high-risk lung cancer populations in Jiangxi Province from 2018 to 2020, and to explore the related influencing factors of compliance.

Methods

From November 2018 to October 2020, permanent residents in Nanchang City were selected and their demographic data and lung cancer risk factor data were collected to screen high-risk groups, and LDCT screening was performed on high-risk groups with diagnostic reports by 2 chief physicians. Descriptive analysis method was used to analyze the basic information of screening, screening results and screening compliance. χ2 and logistic regression test were used to conduct single and multi-factor analysis of screening compliance.

Results

A total of 26,588 people participated in this screening, of which 34.4% (n=9,139) were at high risk of lung cancer, 3,773 participants were completed LDCT screening, and the screening compliance rate was 41.3%. Screening results showed that 389 participants were positive for suspected pulmonary tumor or lung nodules, the screening positive rate of 10.3%. The logistic multivariable results of screening compliance showed that the compliance was better in males, those who quit smoking, those with chronic respiratory diseases and family history of cancer, and those who have primary education, those with a history of occupational harmful exposure had a poor compliance.

Conclusion

Compliance with lung cancer screening in Jiangxi Province, China still needs to be improved, and gender, education level, harmful occupational exposure, smoking, chronic respiratory diseases, and family history of tumors cancer play an important role on screening compliance.

Comparison of safety and anxiety/depression in computed tomography-guided hook-wire localization versus electromagnetic navigation bronchoscopy-guided localization: a retrospective cohort study

Background

The utilization of computed tomography (CT)-guided localization and electromagnetic navigation bronchoscopy (ENB)-guided localization has gained significant traction in the localization of pulmonary nodules before video-assisted thoracoscopic surgery (VATS). This study aimed to ascertain the precision and safety of the two groups in the preoperative resection of isolated nodules in small peripheral lungs. Furthermore, we examined the subsequent outcomes pertaining to the decline in lung function and alterations in anxiety and depression following resection utilizing both localization techniques.

Methods

A total of 177 patients with small-sized pulmonary nodules, scheduled to undergo video-assisted thoracoscopic limited resection, were enrolled in this study. The study involved the examination and comparison of pertinent findings obtained through the utilization of CT-guided hook-wire or ENB injection techniques.

Results

The nodules were localized by ENB in 57 patients and by CT guidance in 120 patients. There were no significant complications in ENB-guided localization group (0/57). CT-guided hook-wire localization group had more complications (61/120, P<0.001). There was no disparity observed in pulmonary function decline 3 months post-operation between the two cohorts. The analysis of postoperative Hospital Anxiety and Depression Scale (HADS) scores indicated that the CT-guided localization group exhibited higher anxiety and depression scores on the initial day and 2 weeks following surgery.

Conclusions

ENB-guided and CT-guided localization can effectively identify solitary pulmonary nodules. ENB-guided localization has fewer complications, lower incidence of adverse events, and less impact on postoperative anxiety or depression, suggesting that this is a promising, safe, and feasible method for localization of solitary pulmonary nodules.

Pneumothorax and pulmonary hemorrhage after C-arm cone-beam computed tomography-guided percutaneous transthoracic lung biopsy: incidence, clinical significance, and correlation

OBJECTIVE

This study aimed to assess the incidence and clinical significance of pneumothorax (PTX) and pulmonary hemorrhage (PH) after percutaneous transthoracic lung biopsy (PTLB) guided by C-arm cone-beam computed tomography (CBCT). Furthermore, this study aimed to examine the relationships between PTX and PH with demographics, clinical characteristics, imaging, and PTLB parameters.

METHODS

A retrospective analysis was conducted on 192 patients who underwent PTLB at our hospital between January 2019 and October 2022. Incidences of PTX and PH were recorded. PTX was considered clinically significant if treated with chest tube insertion (CTI), and PH if treated with bronchoscopes or endovascular treatments. The various factors on PTX and PH were analyzed using the Chi-squared test and Student t-test. Logistic regression analyses were then used to determine these factors on the correlation to develop PTX and PH.

RESULTS

PTX occurred in 67/192 cases (34.9%); CTI was required in 5/67 (7.5%). PH occurred in 63/192 cases (32.8%) and none of these cases required bronchoscopes or endovascular treatments. Lesion diameter (ORPTX = 0.822; ORPH = 0.785), presence of pulmonary emphysema (ORPH = 2.148), the number of samples (ORPH = 1.834), the use of gelfoam (ORPTX = 0.474; ORPH = 0.341) and ablation (ORPTX = 2.351; ORPH = 3.443) showed statistically significant correlation to PTX and PH.

CONCLUSIONS

CBCT-guided PTLB is a safe and effective method for performing lung biopsies. The use of gelfoam has been shown to reduce the occurrence of PTX and PH. However, caution should be exercised when combining radiofrequency ablation with PTLB, as it may increase the risk of PTX and PH.

Diagnostic value of artificial intelligence based on computed tomography (CT) density in benign and malignant pulmonary nodules: a retrospective investigation

OBJECTIVE

To evaluate the diagnostic value of artificial intelligence (AI) in the detection and management of benign and malignant pulmonary nodules (PNs) using computed tomography (CT) density.

METHODS

A retrospective analysis was conducted on the clinical data of 130 individuals diagnosed with PNs based on pathological confirmation. The utilization of AI and physicians has been employed in the diagnostic process of distinguishing benign and malignant PNs. The CT images depicting PNs were integrated into AI-based software. The gold standard for evaluating the accuracy of AI diagnosis software and physician interpretation was the pathological diagnosis.

RESULTS

Out of 226 PNs screened from 130 patients diagnosed by AI and physician reading based on CT, 147 were confirmed by pathology. AI had a sensitivity of 94.69% and radiologists had a sensitivity of 85.40% in identifying PNs. The chi-square analysis indicated that the screening capacity of AI was superior to that of physician reading, with statistical significance (p < 0.05). 195 of the 214 PNs suggested by AI were confirmed pathologically as malignant, and 19 were identified as benign; among the 29 PNs suggested by AI as low risk, 13 were confirmed pathologically as malignant, and 16 were identified as benign. From the physician reading, 193 PNs were identified as malignant, 183 were confirmed malignant by pathology, and 10 appeared benign. Physician reading also identified 30 low-risk PNs, 19 of which were pathologically malignant and 11 benign. The physician readings and AI had kappa values of 0.432 and 0.547, respectively. The physician reading and AI area under curves (AUCs) were 0.814 and 0.798, respectively. Both of the diagnostic techniques had worthy diagnostic value, as indicated by their AUCs of >0.7.

CONCLUSION

It is anticipated that the use of AI-based CT diagnosis in the detection of PNs would increase the precision in early detection of lung carcinoma, as well as yield more precise evidence for clinical management.

Multimodal Diagnostics of Changes in Rat Lungs after Vaping

(1) Background: The use of electronic cigarettes has become widespread in recent years. The use of e-cigarettes leads to milder pathological conditions compared to traditional cigarette smoking. Nevertheless, e-liquid vaping can cause morphological changes in lung tissue, which affects and impairs gas exchange. This work studied the changes in morphological and optical properties of lung tissue under the action of an e-liquid aerosol. To do this, we implemented the "passive smoking" model and created the specified concentration of aerosol of the glycerol/propylene glycol mixture in the chamber with the animal. (2) Methods: In ex vivo studies, the lungs of Wistar rats are placed in the e-liquid for 1 h. For in vivo studies, Wistar rats were exposed to the e-liquid vapor in an aerosol administration chamber. After that, lung tissue samples were examined ex vivo using optical coherence tomography (OCT) and spectrometry with an integrating sphere. Absorption and reduced scattering coefficients were estimated for the control and experimental groups. Histological sections were made according to the standard protocol, followed by hematoxylin and eosin staining. (3) Results: Exposure to e-liquid in ex vivo and aerosol in in vivo studies was found to result in the optical clearing of lung tissue. Histological examination of the lung samples showed areas of emphysematous expansion of the alveoli, thickening of the alveolar septa, and the phenomenon of plasma permeation, which is less pronounced in in vivo studies than for the exposure of e-liquid ex vivo. E-liquid aerosol application allows for an increased resolution and improved imaging of lung tissues using OCT. Spectral studies showed significant differences between the control group and the ex vivo group in the spectral range of water absorption. It can be associated with dehydration of lung tissue owing to the hyperosmotic properties of glycerol and propylene glycol, which are the main components of e-liquids. (4) Conclusions: A decrease in the volume of air in lung tissue and higher packing of its structure under e-liquid vaping causes a better contrast of OCT images compared to intact lung tissue.

China lung cancer screening (CLUS) version 2.0 with new techniques implemented: Artificial intelligence, circulating molecular biomarkers and autofluorescence bronchoscopy

OBJECTIVE

The present study, CLUS version 2.0, was conducted to evaluate the performance of new techniques in improving the implementation of lung cancer screening and to validate the efficacy of LDCT in reducing lung cancer-specific mortality in a high-risk Chinese population.

METHODS

From July 2018 to February 2019, high-risk participants from six screening centers in Shanghai were enrolled in our study. Artificial intelligence, circulating molecular biomarkers and autofluorescencebronchoscopy were applied during screening.

RESULTS

A total of 5087 eligible high-risk participants were enrolled in the study; 4490 individuals were invited, and 4395 participants (97.9%) finally underwent LDCT detection. Positive screening results were observed in 857 (19.5%) participants. Solid nodules represented 53.6% of all positive results, while multiple nodules were the most common location type (26.8%). Up to December 2020, 77 participants received lung resection or biopsy, including 70 lung cancers, 2 mediastinal tumors, 1 tracheobronchial tumor, 1 malignant pleural mesothelioma and 3 benign nodules. Lung cancer patients accounted for 1.6% of all the screened participants, and 91.4% were in the early stage (stage 0-1).

CONCLUSIONS

LDCT screening can detect a high proportion of early-stage lung cancer patients in a Chinese high-risk population. The utilization of new techniques would be conducive to improving the implementation of LDCT screening.