Academic Radiology, Journal Year: 2024, Volume and Issue: 31(11), P. 4661 - 4675
Published: May 12, 2024
Language: Английский
Seminars in Nuclear Medicine, Journal Year: 2025, Volume and Issue: unknown
Published: March 1, 2025
Lung cancer remains one of the most prevalent cancers globally and leading cause cancer-related deaths, accounting for nearly one-fifth all fatalities. Fluoro-2-deoxy-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) plays a vital role in assessing lung managing disease progression. While traditional PET/CT imaging relies on qualitative analysis basic quantitative parameters, radiomics offers more advanced approach to analyzing tumor phenotypes. Recently, has gained attention its potential enhance prognostic diagnostic capabilities [18F]FDG various cancers. This review explores expanding PET/CT-based radiomics, particularly when integrated with artificial intelligence (AI), cancer, especially non-small cell (NSCLC). We how AI improve diagnostics, staging, subtype identification, molecular marker detection, which influence treatment decisions. Additionally, we address challenges clinical integration, such as protocol standardization, feature reproducibility, need extensive prospective studies. Ultimately, hold great promise enabling personalized effective treatments, potentially transforming management.
Language: Английский
Citations
5
PLoS ONE, Journal Year: 2025, Volume and Issue: 20(1), P. e0317276 - e0317276
Published: Jan. 14, 2025
Background Artificial intelligence broadly refers to computer systems that simulate intelligent behaviour with minimal human intervention. Emphasizing patient-centered care, research has explored patients’ perspectives on artificial in medical indicating general acceptance of the technology but also concerns about supervision. However, these views have not been systematically examined from perspective patients cancer, whose opinions may differ given distinct psychosocial toll disease. Objectives This protocol describes a scoping review aimed at summarizing existing literature attitudes cancer toward use their care. The primary goal is identify knowledge gaps and highlight opportunities for future research. Methods will adhere Preferred Reporting Items Systematic Reviews Meta-Analyses guidelines (PRISMA-ScR). electronic databases MEDLINE (OVID), EMBASE, PsycINFO, CINAHL be searched peer-reviewed articles published academic journals. We two independent reviewers screen retrieved search select relevant studies based our inclusion criteria, third reviewer resolving any disagreements. then compile data included into narrative summary discuss implications clinical practice Discussion To knowledge, this first map regarding
Language: Английский
Citations
1
Clinica Chimica Acta, Journal Year: 2025, Volume and Issue: unknown, P. 120191 - 120191
Published: Feb. 1, 2025
Language: Английский
Citations
1
Biomedicines, Journal Year: 2024, Volume and Issue: 12(3), P. 472 - 472
Published: Feb. 20, 2024
The aim of our study was to predict the occurrence distant metastases in non-small-cell lung cancer (NSCLC) patients using machine learning methods and texture analysis 18F-labeled 2-deoxy-d-glucose Positron Emission Tomography/Computed Tomography {[18F]FDG PET/CT} images. In this retrospective single-center study, we evaluated 79 with advanced NSCLC who had undergone [18F]FDG PET/CT scan at diagnosis before any therapy. Patients were divided into two independent training (n = 44) final testing 35) cohorts. Texture features primary tumors lymph node extracted from images LIFEx program. Six applied dataset entire panel features. Dedicated selection used generate different combinations five performance selected determined accuracy, confusion matrix, receiver operating characteristic (ROC) curves, area under curve (AUC). A total 104 78 lesions analyzed cohorts, respectively. support vector (SVM) decision tree showed highest accuracy cohort. Seven obtained introduced models subsequently cohorts SVM tree. AUC method higher than those best combination included shape sphericity, gray level run length matrix_run non-uniformity (GLRLM_RLNU), Total Lesion Glycolysis (TLG), Metabolic Tumor Volume (MTV), compacity. these could an 74.4% 0.63 patients.
Language: Английский
Citations
7
Colloids and Surfaces B Biointerfaces, Journal Year: 2024, Volume and Issue: 236, P. 113824 - 113824
Published: Feb. 24, 2024
Language: Английский
Citations
6
Breathe, Journal Year: 2024, Volume and Issue: 20(2), P. 230192 - 230192
Published: June 1, 2024
The progress in lung cancer treatment is closely interlinked with the diagnostic methods. There are four steps before commencing treatment: estimation of patient's performance status, assessment disease stage (tumour, node, metastasis), recognition histological subtype, and detection biomarkers. resection rate <30% >70% patients need systemic therapy, which individually adjusted. Accurate diagnosis very important it basis further molecular diagnosis. In many cases only small biopsy samples available rules for their defined this review. use immunochemistry at least thyroid transcription factor 1 (TTF1) p40 decisive distinction between adenocarcinoma squamous cell carcinoma. Molecular known driver mutations necessary introducing targeted therapy multiplex gene panel assays using next-generation sequencing recommended. Immunotherapy checkpoint inhibitors second promising method best results tumours high programmed death-ligand (PD-L1) expression on cells. Finally, determination a full tumour pattern will be possible artificial intelligence near future.
Language: Английский
Citations
4
Journal of drug targeting, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 85
Published: Jan. 2, 2025
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis intricate biological data and extraction substantial associations from datasets for a variety biomedical uses. AI has attracted interest in research due its features: (i) better patient care through early diagnosis detection; (ii) enhanced workflow; (iii) lowering medical errors; (v) costs; (vi) reducing morbidity mortality; (vii) enhancing performance; (viii) precision; (ix) time efficiency. Quantitative metrics are crucial evaluating implementations, providing insights, enabling informed decisions, measuring impact AI-driven initiatives, thereby transparency, accountability, overall impact. The implementation fields faces challenges such as ethical privacy concerns, lack awareness, technology unreliability, professional liability. brief discussion given techniques, which include Virtual screening (VS), DL, ML, Hidden Markov models (HMMs), Neural networks (NNs), Generative (GMs), Molecular dynamics (MD), Structure-activity relationship (SAR) models. study explores application fields, highlighting predictive accuracy, treatment efficacy, diagnostic efficiency, faster decision-making, personalized strategies, precise interventions.
Language: Английский
Citations
0
Meta-Radiology, Journal Year: 2025, Volume and Issue: unknown, P. 100124 - 100124
Published: Jan. 1, 2025
Language: Английский
Citations
0
Biomedicines, Journal Year: 2025, Volume and Issue: 13(1), P. 130 - 130
Published: Jan. 8, 2025
Background and Objectives: The current study aimed to compare the effectiveness of Lung Imaging Reporting Data System (Lung-RADS) Version 2022 British Thoracic Society (BTS) guidelines in differentiating lung metastases from de novo primary cancer on CT scans patients without prior diagnosis. Materials Methods: This retrospective included 196 who underwent chest between 2015 a known history but with detected pulmonary nodules. images characterized nodules based size, number, location, margins, attenuation, growth patterns. Nodules were classified according Lung-RADS BTS guidelines. Statistical analyses compared sensitivity specificity distinguishing cancer. Subgroup conducted nodule characteristics. Results: Of patients, 148 (75.5%) had cancer, 48 (24.5%) occult tumors. demonstrated higher than (87.2% vs. 72.3%, p < 0.001) while maintaining similar (91.7% 93.8%, = 0.68) more likely present multiple (81.3% 18.2%, 0.001), lower lobe distribution (58.3% 28.4%, smooth margins (70.8% 20.3%, whereas cancers associated solitary nodules, upper spiculated margins. Conclusions: provides Recognizing characteristic imaging features can improve diagnostic accuracy guide appropriate management.
Language: Английский
Citations
0
The Indian Journal of Medical Research, Journal Year: 2025, Volume and Issue: 160, P. 561 - 569
Published: Jan. 15, 2025
There is a growing burden of lung cancer cases in India, incidence projected to increase from 63,708 (2015) 81,219 (2025). The increasing numbers are attributed smoking (India currently has nearly 100 million adult smokers) and environmental pollution. Most patients present with advanced disease (80-85% incurable), causing 60,000 annual deaths cancer. Early detection through screening (LCS) can result curative therapies for earlier stages improved survival. Annual low-dose computerized tomography (LDCT) the standard method LCS. Usually, high-risk populations (age>50 yr >20 pack-years smoking) considered LCS, but even such focused may be challenging resource-limited countries like India. However, developing smart LCS programme high yield possible by leveraging demographic genomic data, use tools, judicious blood-based biomarkers. Developing this model over next several years will facilitate structured at highest risk In paper, we discuss demographics India its relation patterns. Further, elaborate on potential applications challenges bringing approach
Language: Английский
Citations
0