ReviewBreathe (Sheffield, England)2024
New developments in the imaging of lung cancer.
Review in Breathe (Sheffield, England), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pretreatment CT Texture Analysis for Predicting Survival Outcomes in Advanced Nonsmall Cell Lung Cancer Patients Receiving Immunotherapy: A Systematic Review and Meta-Analysis.Thoracic cancer · 2025Pooled it
- Radiographic tumor regression as a predictor for pathologic response after neoadjuvant therapy for non-small cell lung cancer.JTCVS open · 2026Article
- Intraoperative localization of pulmonary nodules using indocyanine green-lipiodol marking: a single-center case series.General thoracic and cardiovascular surgery · 2026Article
- Radiomics in Lung Cancer Imaging: A Narrative Review of Current Evidence.Journal of imaging · 2026Review
- Clinical Effectiveness of miR-760 to Distinguish Benign and Malignant Pulmonary Nodules on the Basis of Low-Dose Spiral CT Imaging.Molecular imaging and biology · 2026Article
- Attention-Enhanced Hybrid Bidirectional LSTM and Temporal Convolutional Network for Early Detection of Lung Cancer in Low-Dose CT Scans.Biomedical engineering and computational biology · 2026Article
- FAD-YOLO: a lightweight feature-refined and task-aligned framework for AIS-MIA discrimination on pulmonary CT.Frontiers in medicine · 2026Article
- Absent preoperative non-small cell lung cancer confirmation and relevant stage migration in the era before neoadjuvant chemoimmunotherapy: implications for treatment decisions in resectable non-small cell lung cancer.Translational lung cancer research · 2025Article
- Clinical TNM Lung Cancer Staging: A Diagnostic Algorithm with a Pictorial Review.Diagnostics (Basel, Switzerland) · 2025Review
- Recent advancements in lung cancer research: a narrative review.Translational lung cancer research · 2025Review
- Lung Cancer-Epidemiology, Pathogenesis, Treatment and Molecular Aspect (Review of Literature).International journal of molecular sciences · 2025Review
- A Holistic Approach to Implementing Artificial Intelligence in Lung Cancer.Indian journal of surgical oncology · 2025Review
- Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC.Cancer management and research · 2025Review
- From images to clinical insights: an educational review on radiomics in lung diseases.Breathe (Sheffield, England) · 2025Review
- Optimal Pathways to Lung Cancer Screening in Primary Care Settings: A Scoping Review.Current oncology (Toronto, Ont.) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Radiological and nuclear medicine methods play a fundamental role in the diagnosis and staging of patients with lung cancer. Imaging is essential in the detection, characterisation, staging and follow-up of lung cancer. Due to the increasing evidence, low-dose chest computed tomography (CT) screening for the early detection of lung cancer is being introduced to the clinical routine in several countries. Radiomics and radiogenomics are emerging fields reliant on artificial intelligence to improve diagnosis and personalised risk stratification. Ultrasound- and CT-guided interventions are minimally invasive methods for the diagnosis and treatment of pulmonary malignancies. In this review, we put more emphasis on the new developments in the imaging of lung cancer.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.