ReviewCancer management and research2025
Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC.
Review in Cancer management and research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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
6 citing papers in PubMed.
- Improved early response assessment of chemoimmunotherapy efficacy byEuropean journal of nuclear medicine and molecular imaging · 2026Article
- Evolving non-invasive biomarkers in NSCLC immunotherapy: integrating liquid biopsy and multi-omics profiling for precision oncology.Frontiers in immunology · 2026Review
- Unlocking drug development: the distinctive roles of PET and SPECT imaging from molecular kinetics to therapeutic response.Archives of pharmacal research · 2026Review
- Advancements in intratumoral therapies for liver tumors.Frontiers in oncology · 2026Review
- Cancer neuroscience: illuminating the neural dimension of tumor biology.Scientific reports · 2025Article
- [Immunotherapy advances · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Immunotherapy has emerged as a transformative treatment for non-small cell lung cancer (NSCLC), yet its clinical benefits remain variable among patients. Early and accurate evaluation of treatment response is critical to guide therapeutic adjustments and improve outcomes. This review synthesizes recent advancements in multimodal imaging techniques-computed tomography (CT), positron emission tomography (PET)/CT, magnetic resonance imaging (MRI), and radiomics-for evaluating and predicting immunotherapy efficacy in NSCLC. We analyze the strengths and limitations of conventional morphological criteria (eg, RECIST, iRECIST) and highlight emerging quantitative biomarkers, including CT texture analysis, metabolic parameters (MTV, TLG), and diffusion-weighted MRI metrics. Notably, radiomics demonstrates promise in decoding tumor heterogeneity, PD-L1 expression, and immune microenvironment features, while immuno-PET probes targeting immune checkpoints offer novel insights into immune activity in vivo. Challenges such as pseudo-progression, nodal immune flare, and discrepancies between imaging responses and pathological responses are critically discussed. By integrating morphological, metabolic, and microenvironmental data, multimodal imaging enhances precision in patient stratification and therapeutic monitoring. Future research should prioritize multicenter, AI-driven radiomics validation and targeted tracer development to optimize NSCLC immunotherapy management. This review provides clinicians and researchers with new directions for utilizing multimodal imaging techniques in developing personalized treatment strategies.
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Identifiers
What Socratic 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 Socratic graph.