CT-guided transthoracic core-needle biopsy (CT-TTNB) is a minimally invasive procedure that plays a crucial role in diagnosing pulmonary nodules. With high diagnostic yield and low complication rates, CT-TTNB is favored over traditional surgical biopsies, providing accuracy in detecting both malignant and benign conditions. This literature review aims to present a comprehensive overview of CT-TTNB, focusing on its indications, procedural techniques, diagnostic yield, and safety considerations. Studies published between 2013 and 2024 were systematically reviewed from PubMed, Web of Science, Scopus, and Cochrane Library using the SANRA methodology. The results highlight that CT-TTNB has a diagnostic yield of 85–95% and sensitivity rates for detecting malignancies between 92 and 97%. Several factors, including nodule size, lesion depth, needle passes, and imaging techniques, influence diagnostic success. Complications such as pneumothorax and pulmonary hemorrhage were noted, with incidence rates varying from 12 to 45% for pneumothorax and 4 to 27% for hemorrhage. Preventative strategies and management algorithms are essential for minimizing and addressing these risks. In conclusion, CT-TTNB remains a reliable and effective method for diagnosing pulmonary nodules, particularly in peripheral lung lesions. Advancements such as PET/CT fusion imaging, AI-assisted biopsy planning, and robotic systems further enhance precision and safety. This review emphasizes the importance of careful patient selection and procedural planning to maximize outcomes while minimizing risks, ensuring that CT-TTNB continues to be an indispensable tool in pulmonary diagnostics.

This review addresses the ongoing challenges in asthma management, particularly focusing on patient adherence to inhaler therapy. Asthma, a chronic condition characterized by variable respiratory symptoms and airflow obstruction, can lead to significant morbidity and mortality if not properly managed. Despite advances in inhaler technology and therapeutic options, non-adherence remains a significant barrier to optimal asthma control. This review explores both intentional and unintentional non-adherence, influenced by factors such as age, socioeconomic status, and the complexity of inhaler devices. The Global Initiative for Asthma (GINA) provides guidelines aimed at improving adherence through targeted interventions, and this review examines their application. Common inhaler technique errors, including incorrect inhalation speed, not exhaling before inhaling, and failure to hold breath post-inhalation, are identified as major contributors to inadequate asthma control. Furthermore, the review explores the emerging role of electronic monitoring devices (EMDs), such as CapMedic and DigiHaler, which offer real-time feedback to enhance inhaler technique and adherence. The role of biomarkers in assessing adherence and the potential of personalized treatment strategies, including biologic therapies, are also discussed. Overall, addressing adherence requires a comprehensive approach that integrates patient education, tailored interventions, and technological innovations to achieve better clinical outcomes in asthma management.

Background/Objectives: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Immune checkpoint inhibitors (ICIs) have transformed treatment paradigms, but assessing response remains challenging due to atypical patterns such as pseudoprogression, hyperprogression and dissociated response. Conventional evaluation criteria, such as RECIST 1.1, may not fully capture these patterns, leading to potential misclassification and premature therapy discontinuation. This review explores the role of 18F-FDG PET/CT in assessing immunotherapy response and highlights novel imaging criteria to enhance clinical decision-making. Methods: A systematic literature review was conducted across PubMed, Web of Science, Scopus, and Cochrane Library, selecting relevant studies published between 2013 and 2024. The review focuses on the strengths and limitations of PET-based imaging in monitoring NSCLC immunotherapy outcomes. Specific attention was given to evolving evaluation frameworks, including iRECIST, PERCIST, imPERCIST, and iPERCIST, as well as metabolic biomarkers such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG). Results: Compared with anatomical-based assessment, metabolic imaging using 18F-FDG PET/CT may offer deeper insights into tumor behavior during immunotherapy. PET-derived parameters seem to improve the detection of immune-related response patterns, providing a more refined approach to differentiate true progression from pseudoprogression. Emerging evidence indicates that metabolic biomarkers such as metabolic tumor volume (MTV) and total lesion glycolysis (TLG) could serve as useful predictors of therapeutic efficacy and support treatment adaptation. Nevertheless, current findings are mainly based on small, heterogeneous, and predominantly retrospective studies, with variable PET timing and threshold definitions that limit the generalizability of these results. Conclusions: 18F-FDG PET/CT represents a promising complementary tool for assessing immunotherapy response in NSCLC. Its integration with advanced imaging criteria and metabolic tumor biomarkers may enhance response evaluation and assist clinical decision-making. Nonetheless, the current evidence remains preliminary, and further standardization and large prospective validation studies are required before its routine implementation in clinical practice.

Background/Objective: Asthma-related quality of life is related to multiple clinical, physiological, and behavioral factors. Nonetheless, the domain-specific associations of asthma control, inhaler adherence, lung function, and demographic characteristics remain poorly understood. This study aimed to examine the adjusted associations of asthma control, inhaler adherence, lung function, and age with individual domains of asthma-related quality of life. Methods: This cross-sectional observational study included 92 adults with asthma who demonstrated correct inhaler technique and adequate knowledge of their prescribed inhaler regimen. Asthma control was measured using the Asthma Control Test (ACT), inhaler adherence using the Test of Adherence to Inhalers (TAI), and quality of life using the Asthma Quality of Life Questionnaire (AQLQ). Pulmonary function was determined through spirometry. Spearman correlation analyses were initially conducted to identify associations between variables. Subsequently, separate multivariable linear regression models were created for each AQLQ domain, including ACT score, TAI score, age, and FEV₁ % predicted as predictors. Results: A total of 92 adult patients with asthma were studied. Asthma control was significantly positively correlated with all AQLQ domains (all p < 0.001). In multivariable analyses, ACT had the largest absolute standardized coefficient within each of the four domain-specific models (standardized β range: 0.339–0.791). After adjustment, age was associated with the activity limitation and symptom domains, whereas FEV₁ % predicted was associated only with the environmental stimuli domain. Inhaler adherence showed an inverse association with emotional functioning in the fully adjusted model (B = −0.094, 95% CI −0.158–−0.031; p = 0.0038). However, this association was absent in the bivariate analysis and in a sensitivity model excluding ACT (B = −0.015, 95% CI −0.067–0.037; p = 0.562), suggesting a possible suppression effect. Conclusions: ACT showed the largest standardized association within each domain-specific model, although the magnitude of its associations with the symptom and activity-limitation domains may partly reflect conceptual overlap between the instruments. The inverse TAI–emotional-functioning coefficient was model-dependent, did not meet the conservative multiplicity benchmark, and should be considered exploratory and hypothesis-generating. Additionally, lung function and age showed domain-specific associations, highlighting the need for a comprehensive, multidimensional approach in asthma management.