Search Results (1,539)

Lung diseases are among the leading global causes of morbidity and mortality, and existing reviews on deep learning (DL) for pulmonary diagnosis rarely integrate imaging, acoustic, and electronic health record (EHR) modalities within a single framework. We aimed to synthesize the state of the art (2019–2024) in multimodal DL for lung disease detection and classification, identifying dominant architectures, performance benchmarks, and translational barriers across chest X-rays, CT scans, respiratory sounds, and EHRs. A structured narrative review was conducted using PubMed, Scopus, IEEE Xplore, and Web of Science, applying explicit inclusion criteria for peer-reviewed studies; performance metrics, dataset characteristics, and reported limitations were extracted. Research involving convolutional neural networks (CNNs) and more recent models such as Transformers have reported high performance in chest X-ray classification, whereas acoustic approaches based on spectrograms and self-supervised representations (e.g., Wav2Vec 2.0) show promising but dataset-dependent results. Full article

The early and accurate detection of lung cancer (LC) is one of the primary challenges in the clinical diagnostics process, which plays a vital role in the treatment of the disease. Although various deep learning (DL) techniques have been presented, the existing DL methods are mainly focused on single-modal images, either computed tomography (CT) or histopathological images, which are associated with poor generalization, diversity, and applicability. To mitigate the existing issues, the present work aims to develop a modality-independent ensemble DL framework that is independently evaluated on CT and histopathological image datasets for LC classification. In this work, the proposed framework was developed using the Beta Normalization Aggregation (BNA) technique, where the performance of three state-of-the-art pre-trained convolutional neural network (CNN) architectures was compared on two distinct imaging modalities images. Based on the comparative analysis of the performance metrics, Xception, DenseNet121, and MobileNetV2, are chosen to develop the Ensemble model. Predictions generated by the selected CNN models are aggregated using the proposed BNA strategy to improve classification robustness, which improves the confidence of the prediction results and discriminative capabilities. The experiments using public data sets have confirmed the excellent performance of the model. On the CT dataset, the proposed BNA Ensemble achieved a testing accuracy of 97.45%, with a precision of 97.88%, recall of 97.45%, F1-score of 97.45%, and an AUC of 0.9986. On the histopathological dataset, the framework achieved an accuracy of 99.80%, with precision, recall, and F1-score all reaching 99.80%, and an AUC of 1.0000. These results demonstrate the effectiveness, robustness, and generalizability of the proposed BNA framework. The analysis of the results using t-SNE plots, confusion matrices, ROC curves, and confidence distributions provided additional insights into feature separability, classification performance, and prediction confidence of the proposed framework. Full article

Background/Objectives: Merkel cell carcinoma (MCC) is a rare but aggressive skin cancer with a 40% recurrence rate. However, reliable biomarkers for early recurrence detection or treatment guidance are lacking, especially for virus-negative tumors. Circulating tumor DNA (ctDNA), a fragment of tumor-derived cell-free DNA in blood, has emerged across multiple cancers as a minimally invasive precision biomarker to detect minimal residual disease (MRD); predict recurrence; and monitor treatment response. This review’s objective was to summarize recent advances in ctDNA as a tool for therapeutic decision-making in MCC, contextualized by findings in other malignancies. Methods: A comprehensive literature review was performed, focusing on studies published between 2016 and 2026 that evaluate ctDNA in MCC and other cancers. Key prospective trials, observational studies, and case reports were identified through PubMed and relevant conference proceedings. Data on ctDNA assay methods (tumor-informed vs. tumor-agnostic), clinical sensitivity, lead time for recurrence detection, and predictive value for therapy response were extracted and synthesized. Results: Across cancers such as colorectal, lung, and melanoma, ctDNA positivity after curative treatment predicts relapse months in advance of imaging and can guide adjuvant therapy decisions. In MCC, recent studies demonstrate that ctDNA levels correlate with MCC tumor burden and exhibit high sensitivity and specificity for clinically evident disease. Stage I-III MCC patients who were ctDNA-positive within four months of treatment had a 7.4-fold higher recurrence risk within the subsequent 12–18 months of follow-up. Serial ctDNA monitoring may enable earlier intervention in otherwise asymptomatic ctDNA-positive MCC cases, helping distinguish responders from non-responders. Conclusions: ctDNA is an emerging precision biomarker that offers significant prognostic and surveillance utility in MCC. It enables earlier detection of recurrence, potentially allowing treatment to begin before clinical disease manifests. It also helps stratify patients by risk and treatment response, informing personalized surveillance intensity and therapeutic choices. Integrating ctDNA monitoring into MCC management could improve outcomes by guiding timely interventions, although prospective trials are needed to confirm that ctDNA-guided decisions translate to improved patient survival. Formal cost-effectiveness analyses have not yet been conducted and represent an important area for future investigation. Full article

Cigarette smoke is a major inducer of oxidative stress, promoting reactive oxygen species (ROS) accumulation and contributing to the pathogenesis of chronic obstructive pulmonary disease (COPD) and lung cancer. Heated tobacco products (HTP) and e-cigarettes are promoted as reduced-risk alternatives; however, their impact on cellular redox regulation remains unclear. Here, we investigated the effects of conventional cigarette smoke extract (CSE), HTP, and e-cigarette extracts on hydrogen peroxide (H₂O₂) permeability mediated by aquaporins (peroxiporins) and on the activity of key antioxidant enzymes (catalase, superoxide dismutase, and glutathione peroxidase) in ATII-like cells. Eight aquaporins were detected at the mRNA level, and seven were confirmed at the protein level. CSE markedly inhibited H₂O₂ permeability across plasma, mitochondrial, and nuclear membranes. HTP extract impaired H₂O₂ transport across the plasma membrane and nuclear envelope, while mitochondrial permeability was preserved. Both CSE and HTP extract reduced superoxide dismutase and glutathione peroxidase activities. In contrast, e-cigarette extract exerted minimal effects on membrane H₂O₂ permeability and selectively decreased superoxide dismutase activity. Overall, our findings identify a graded pattern of oxidative toxicity (CSE > HTP > e-cigarette) and highlight peroxiporins as critical regulators of intracellular redox homeostasis. Although less harmful than cigarettes, alternative nicotine delivery systems are not biologically inert. Full article

Background: Systemic sclerosis (SSc)-associated interstitial lung disease (SSc-ILD) is the leading cause of morbidity and mortality in patients with SSc, with an unmet need for validated, minimally invasive biomarkers for early detection. Extracellular vesicles (EVs) present underexplored pathogenic players and potential biomarker sources in SSc-ILD. We performed a proteomic shotgun study aiming to identify disease-specific protein signatures and potential biomarker candidates. Methods: The study included 30 SSc patients divided into SSc-ILD and SSc w/o ILD groups and 20 matched controls. Plasma-derived EV-enriched fractions were analysed using liquid chromatography–mass spectrometry. Bioinformatic analysis, including differentially expressed proteins (DEPs), functional enrichment, protein–protein interaction network and Markov Cluster (MCL) analysis was performed. Results: Analysis of DEPs showed 14 significantly upregulated and 1 downregulated protein when comparing the SSc-ILD to the SSc w/o ILD group, 222 upregulated and 257 downregulated proteins between the SSc-ILD and control group, as well as 362 upregulated and 492 downregulated proteins between the SSc w/o ILD and control group. Functional enrichment analysis and MCL analysis pointed to disease-specific processes of extracellular matrix (ECM) and immune dysregulation, which largely overlapped between SSc-ILD and SSc w/o ILD groups. Among identified DEPs, SP-B, Cav-1 and Siglec-5 emerged as potential candidate biomarkers for SSc-ILD. Conclusions: Proteomic analysis of plasma-derived EV-enriched fractions shows potential EV involvement in pathogenic SSc processes, mainly related to ECM and immune dysregulation, as well as potential candidate biomarkers for SSc-ILD. Further studies are required to validate these results and assess biomarker potential and translational applicability of identified proteins. Full article

Background: Spread through air spaces (STAS) is a recognized histologic pattern of invasion associated with poor prognosis in non-small-cell lung cancer (NSCLC), particularly adenocarcinoma. However, its presence in pulmonary squamous cell carcinoma (SCC), whether primary or metastatic, remains largely unexplored. Given the limited available evidence, this study was designed as an exploratory analysis to evaluate the prevalence and potential prognostic significance of STAS in pulmonary SCC. Material and Methods: In this exploratory retrospective study, we analyzed 57 patients who underwent surgical resection for pulmonary squamous cell carcinoma (P-SCC) at the Department of Thoracic Surgery at the University Hospital Erlangen between 2008 and 2020. The cohort included both primary lung SCC and metastatic SCC to the lung from extrapulmonary sites, primarily from ear, nose, and throat (ENT) tumors. Histological slides were reviewed to assess the presence of STAS, as defined by established morphological criteria. The Chi-square test was used to investigate the presence of STAS. Disease-free survival (DFS) and overall survival (OS) was evaluated using Kaplan–Meier analysis, and the prognostic impact of STAS along other variables were assessed using Cox proportional hazards regression. Results: A total of 57 patients with squamous cell carcinoma (SCC), 22 (39%) had primary lung SCC and 35 (61%) had metastatic SCC from head and neck tumours (ENT). Spread through air spaces (STAS) was detected in 20 patients (35%). Disease-free survival (DFS) differed according to primary tumour location (p-value of 0.009), with higher 1-, 3-, and 5-year DFS in patients with primary lung SCC (86.4%, 77.3%, 63.3%) than in those with head and neck SCC (54.3%, 31.4%, 22.2%). DFS was also significantly higher in patients undergoing solitary resections compared with multiple resections (78.6%, 64.3%, 49.5% vs. 33.3%, 6.7%, not estimable; p-value < 0.001). DFS was slightly longer in STAS-negative patients compared with STAS-positive patients (1-, 3-, 5-year DFS: 64.9%, 51.4%, 40.5% vs. 70%, 45%, not estimable), (median DFS 36 vs. 25 months; p-value of 0.776). Overall survival (OS) was significantly longer in patients with primary lung SCC (median OS 125 months) than in those with head and neck SCC (27 months; p-value of 0.039). STAS-negative patients had also a longer OS than STAS-positive patients (median OS 46 vs. 38 months; HR = 1.11, 95% CI 0.56–2.20; p-value of 0.771). Conclusions: STAS was identified in metastatic pulmonary SCC lesions as well as in primary lung SCC, occurring in approximately one-third of cases. However, due to the limited cohort size and the exploratory univariate design of the study, the prognostic significance of STAS could not be definitively established and requires further investigation in larger, adequately powered studies. Full article

Background: Lung cancer is a highly heterogeneous disease in which molecular characterization has become essential for guiding personalized therapies. The implementation of next-generation sequencing (NGS) allows for the simultaneous detection of multiple genomic alterations, improving tumor profiling and therapeutic decision-making. This study aimed to characterize the molecular landscape of lung cancer using NGS and to evaluate its association with histological subtypes and programmed death-ligand 1 (PD-L1) expression. Methods: A retrospective observational study was conducted on 96 patients diagnosed with lung cancer between 2023 and 2025. Molecular profiling was performed using the Action OncoKitDx panel. Associations between genetic alterations, histological subtypes, and PD-L1 expression were analyzed using Fisher’s exact test, with p < 0.05 considered statistically significant. Results: Adenocarcinoma was the most common histological subtype (67.7%), followed by squamous cell carcinoma (26%). The most common mutations were KRAS (34.4%), TP53 (29.2%), and EGFR (11.5%). KRAS mutations were significantly associated with adenocarcinoma (p = 0.001), while squamous cell carcinoma showed a higher frequency of cases without molecular alterations detected by the NGS panel (p = 0.002). Co-mutations were identified in 22.9% of cases, with KRAS–TP53 being the most common combination. Tumors harboring EGFR mutations showed a significantly lower frequency of co-mutations (p = 0.012). No significant associations were found between PD-L1 expression and either histological subtypes or the analyzed genetic alterations. Conclusions: Lung cancer exhibits marked molecular heterogeneity, with a predominance of KRAS mutations in adenocarcinoma. The low frequency of co-mutations in EGFR-mutated tumors supports their role as dominant driver alterations. The lack of association between PD-L1 expression and genomic alterations highlights the complexity of its regulation and suggests the involvement of multiple biological factors. These findings reinforce the clinical value of NGS in comprehensive tumor profiling and in the development of precision medicine strategies. Full article

The primary route of SARS-CoV-2 entry is via respiratory epithelium. However, many COVID-19 patients developed dermatological lesions, and SARS-CoV-2 RNA has been detected in the patients’ skin. Inflammatory skin diseases, psoriasis and atopic dermatitis (AD), significantly increased the risk of COVID-19. To evaluate the potential role of skin in SARS-CoV-2 host interactions, we utilized 3D human skin organoids (HSO) generated from human epidermal keratinocytes, as well as neonatal skin explants. HSO were treated with cytokines involved in acute and chronic skin inflammation and cytokine storm in severe COVID-19 disease: TNF-α, IL-6, IL-1β, and IFN-γ, individually and in combination. HSO were also treated with Th1 (TNF-α + IL-17) and Th2 (IL-4 + IL-13) cocktails inducing pro-psoriasis and pro-AD HSO changes, respectively. All individual cytokines, and especially their combinations, elevated the expression of ACE2 and TMPRSS2 at mRNA/protein levels. The Th2 cocktail induced only TMPRSS2, the Th1 cocktail predominantly induced ACE2. Topically applied Spike-pseudotyped lentiviral Tomato reporter, which binds ACE2 similarly to SARS-CoV-2, successfully transduced control and cytokine-treated HSO as well as neonatal skin explants. Cytokine treatment, especially TNF-α + IL-6 + IL-1β + IFN-γ and the Th1 cocktail, significantly increased viral entry. Transcriptomic analysis further revealed partial overlap between gene expression signatures induced by Spike-mediated entry in inflamed HSO and those observed in lung tissue from COVID-19 patients, supporting the biological relevance of skin models. Together, these findings demonstrate that inflammation may transiently alter the permissiveness of human skin to SARS-CoV-2 entry, suggesting that the skin may represent a previously underappreciated, although likely limited, interface in viral- host interactions. Full article

Background: Treatment monitoring in pulmonary tuberculosis increasingly requires assessment of residual inflammatory burden and structural lung damage beyond microbiologic response alone. High-resolution computed tomography (HRCT) can provide this information, but interpretation of serial examinations is time-consuming and partly subjective. This study did not aim to evaluate AI for the diagnosis of pulmonary tuberculosis. Instead, it explored whether artificial intelligence (AI)-assisted quantitative HRCT analysis could support longitudinal assessment of treatment-related imaging changes in patients with microbiologically confirmed pulmonary tuberculosis. Methods: We conducted a retrospective, single-center, exploratory longitudinal study of patients receiving treatment for pulmonary tuberculosis. HRCT examinations acquired at diagnosis and during follow-up were anonymized, reviewed by an expert thoracic radiologist, and processed using AVIEW Lung Texture (Coreline Soft v2.0). The software quantified total lung volume and six predefined parenchymal categories: normal lung, ground-glass opacity, consolidation, reticulation, honeycombing, and emphysema. Results: Ninety-six patients contributed 256 HRCT examinations. The most frequent software-detected abnormalities were ground-glass opacity, consolidation, and emphysema-labeled low-attenuation areas. Ground-glass opacity and consolidation showed the clearest decline across serial examinations, consistent with regression of active inflammatory disease during treatment. Reticulation showed a heterogeneous course, likely reflecting both inflammatory resolution and residual structural remodeling. Honeycombing was infrequent and quantitatively limited. Lung volume changed variably and did not consistently parallel visual improvement. A key methodological limitation was the absence of a dedicated cavity class. As a result, emphysema-labeled low-attenuation areas should not be interpreted as conventional emphysema alone, because tuberculous cavities and post-destructive abnormalities were frequently included in this category. Conclusions: AI-assisted HRCT quantification may support longitudinal assessment of pulmonary tuberculosis by providing structured and reproducible measures of interval change. However, tuberculosis-specific interpretation remains dependent on expert radiologic oversight, particularly in cavitary disease. Full article

Introduction: Lung cancer, the leading cause of cancer-related mortality worldwide, is a heterogeneous malignancy comprising distinct histological and molecular subtypes, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of cases and adenocarcinoma (ADC) representing the most prevalent histotype. An emerging pathological feature of NSCLC, spread through air spaces (STAS)—defined as the extension of tumor cells into the lung parenchyma beyond the main tumor margin—has been associated with worse disease-free and overall survival and has been proposed as a possible predictor of recurrence to guide surgical extent. Concurrently, recent comprehensive genomic profiling of early-stage NSCLC has highlighted the need to interpret multi-omics data and their relationship with pathological variables, including IASLC histological subtypes, to better personalize treatment strategies. In this context, we investigated the overall distribution of STAS and its association with tumor mutational profiles and IASLC histological subtypes in a large real-world cohort of lung adenocarcinoma patients from the LANTERN project. Materials and Methods: In a prospective, multicenter observational study (March 2023–December 2024), 271 NSCLC patients were enrolled, and clinicopathological, immunohistochemical, and genomic data were collected; comprehensive genomic profiling was performed using the TruSight Oncology 500 assay to analyze 523 cancer-related genes, tumor mutational burden (TMB), and microsatellite instability; and STAS was assessed according to IASLC criteria. Adenocarcinoma accounted for roughly 90% of the cases, with a median age of 69 years and a predominance of stage IV disease (49.5%). STAS was evaluable in 162 cases and was detected in 17.9% of tumors. Results: STAS-positive tumors showed a higher trend towards locally advanced and advanced disease; no differences were observed in sex, age, smoking status, tumor mutational burden, or PD-L1 expression. Additionally, STAS-positive tumors showed a higher association with micropapillary, mucinous, and papillary patterns, whereas the acinar pattern was more frequent in STAS-negative tumors. The most frequently mutated genes were TP53, KRAS, EGFR, and STK11, with no significant differences between groups; ROS1 alterations were absent in STAS-negative tumors but detected more frequently in STAS-positive cases. Conclusions: Overall, these findings indicate that STAS positivity is associated with high-risk histological subtypes and advanced disease, suggesting its importance as a marker of tumor aggressiveness and emphasizing the need for its systematic evaluation in lung adenocarcinoma to better guide surgical planning and patient risk assessment. Full article

Olfactory (or odorant) receptors (ORs) were initially characterized in 1991 by Drs. Richard Axel and Linda Buck, and subsequent additional efforts have contributed to our understanding of their canonical function in odorant identification in the nasal cavity, including ligands for many of the ORs and the signaling pathways involved. More recently, OR transcripts and proteins have been identified in cells and organs outside of the nasal cavity, ranging from skin to sperm to tumors, suggesting that they have biological roles in ectopic locations other than their canonical function of odorant molecule detection in the nose. This mini narrative review discusses ectopic human ORs and their potential ligand-activated functions in the skin, lung, and sperm, as well as in diseases such as nonalcoholic steatohepatitis (NASH), melanoma and prostate cancer. Full article

Background/Objectives: Rabbit farming in Romania is increasingly important for providing high-quality meat, yet productivity is frequently threatened by enteric diseases, particularly in young animals. Among bacterial etiologies, Clostridioides difficile (C. difficile) has emerged as a significant gastrointestinal pathogen, with findings suggestive of systemic dissemination and public health implications. This study aimed to investigate a fatal case of C. difficile infection in a farmed rabbit and to characterize the pathogen’s microbiological, toxigenic, and antimicrobial profile. Methods: An 11-month-old male German Giant Spotted rabbit presenting acute diarrhea, anorexia, and rapid deterioration after unsupervised administration of enrofloxacin and sulfaquinoxaline was submitted postmortem. Necropsy was performed, and samples from cecum, colon, liver, spleen, mesenteric lymph nodes, lungs, and femoral bone marrow were collected. Microbiological analysis included selective culture on CCFA medium, ELISA for toxin A and B detection, MALDI-TOF MS identification, PCR confirmation, and antimicrobial susceptibility testing with the VITEK 2 system. Histopathological examination was conducted on intestinal and parenchymal tissues. Results: Necropsy revealed severe congestion and necrosis of the cecal and colonic mucosa, hepatomegaly, splenic congestion, and petechial hemorrhages. C. difficile was isolated from intestinal sites, confirmed as toxigenic by ELISA and PCR. Histopathology showed necrotizing colitis with epithelial desquamation, fibrin deposition, and heterophilic infiltration. The strain exhibited resistance to clindamycin, ampicillin, and tetracycline, with susceptibility to vancomycin, linezolid, and tigecycline. Conclusions: This case demonstrates that C. difficile can cause severe disease in rabbits, particularly following antimicrobial-induced dysbiosis. The findings underscore the importance of prudent antibiotic use, monitoring of toxigenic strains in rabbit populations, and implementation of preventive strategies to mitigate health risks in both animals and potentially humans. Full article

Background/Objectives: Cystic fibrosis is a chronic multisystem disease in which pulmonary involvement is the main determinant of morbidity and mortality. Chest computed tomography is the reference standard for assessing structural lung damage, but its repeated use is limited by cumulative radiation exposure. Lung ultrasound has emerged as a radiation-free alternative; however, its role in adult patients remains incompletely defined. This study aimed to evaluate the correlation between CT-derived structural lung damage and ultrasound findings, and to assess the complementary role of these imaging modalities. Methods: A prospective cohort study was conducted including adult patients with cystic fibrosis who underwent both chest computed tomography and lung ultrasound during the same clinical episode. Structural lung involvement was assessed using the Bhalla score, while lung aeration was evaluated using the Lung Ultrasound Score. Correlation analyses, severity stratification, regression modeling, and longitudinal comparisons were performed. Results: Thirteen patients contributed 24 imaging evaluations. A strong positive correlation between Bhalla score and ultrasound findings was observed in the cross-sectional analysis and remained consistent when all examinations were included. Ultrasound scores increased significantly across CT-defined severity groups, and regression analysis confirmed a significant association between the two methods. Exploratory analysis showed stronger associations for peripheral and aeration-related abnormalities, while weaker associations were observed for deeper airway changes. No significant correlation was identified in longitudinal analysis. Conclusions: Lung ultrasound correlates well with CT-derived structural lung damage and may serve as a complementary, radiation-free tool for disease assessment in adult cystic fibrosis. However, its limited sensitivity in detecting temporal changes highlights the continued importance of CT in selected clinical scenarios. Full article

Background: The clinical burden of pulmonary diseases associated with the genus Aspergillus is increasing, although diagnostic focus remains largely on A. fumigatus. This study evaluated the diagnostic value of testing for A. flavus and A. niger-specific IgG in patients with chronic respiratory conditions. Methods: A retrospective study was conducted on 274 subjects (156 with chronic respiratory diseases, Bronchiectasis, Hypersensitivity Pneumonitis [HP], and Interstitial Lung Disease [ILD] non-HP, and 67 healthy controls). Cut-off values were established at the 97.5th percentile of the control group: 30 mg/L for A. fumigatus, 13 mg/L for A. flavus, and 8 mg/L for A. niger. Results: Among 109 patients who tested negative for A. fumigatus, 49.5% showed positivity to at least one other species, preventing a significant diagnostic gap in exposure detection. Notably, 40.4% of these patients exhibited simultaneous positivity for both A. flavus and A. niger. In the HP subgroup, 100% of patients who were A. fumigatus-positive also showed concurrent positivity to the two other species. Furthermore, the Bronchiectasis group showed the highest rate of isolated A. flavus at 11.8%. Conclusions: Testing solely for A. fumigatus IgG leads to substantial underestimation of Aspergillus exposure. Integrating A. flavus and A. niger into diagnostic panels is essential for a comprehensive immunological assessment of fungal interaction, particularly in HP and ILD, where identifying specific antigenic exposure is crucial for managing chronic inflammation and preventing disease progression. Full article

Accurate regional lymph node staging is essential for guiding treatment and predicting outcomes in non-small cell lung cancer. While the 9th edition of the TNM classification introduced prognostic subdivisions for N2 disease, the N1 category remains a single, unified descriptor. However, N1 disease is highly heterogeneous. Evidence shows significant survival differences between single-station (N1a) and multi-station (N1b) involvement, as well as between peripheral (N1p) and hilar (N1h) metastases. Standard medical imaging evaluation and conventional bronchoscopy often fail to detect “occult N1 disease,” leading to postoperative stage migration and suboptimal treatment sequencing. This diagnostic gap affects critical clinical decisions, including the selection of patients for sublobar resection, the administration of neoadjuvant chemoimmunotherapy, and the precision of radiation target volumes. The main obstacle to refining N1 staging has been the limited ability of existing clinical staging modalities to access and accurately assess N1p nodes. However, recent technological advances, particularly in thin convex probe endobronchial ultrasound examination, have renewed interest in bronchoscopic evaluation of N1p and in improving preoperative clinical N1 staging. The purpose of this review is to summarize the biological and immunological basis for N1 subclassification and evaluate how emerging technologies can bridge the gap between clinical and pathological staging. Refining the N1 compartment is vital for a personalized staging system that reflects the true biological spectrum of lung cancer. Full article