ReviewRadiology. Imaging cancer2026
Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.
Review in Radiology. Imaging cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Small cell lung cancer (SCLC) is an aggressive pulmonary neuroendocrine carcinoma characterized by rapid progression and early metastasis. Despite recent therapeutic advances, including immune checkpoint inhibitors and emerging targeted agents, survival outcomes remain poor. Recent molecular insights have identified four transcription factor-driven subtypes-SCLC-A, SCLC-N, SCLC-P, and the inflamed subtype SCLC-I-providing a framework for precision and immunotherapy-based strategies. This review summarizes the evolving scope of imaging in SCLC and highlights emerging approaches that support personalized medicine. Conventional imaging with CT, MRI, and fluorine 18 fluorodeoxyglucose PET/CT remains essential for diagnosis, staging, and treatment response assessment. Semiquantitative, volume-based PET/CT metrics, such as metabolic tumor volume and total lesion glycolysis, correlate with tumor proliferation and provide stronger prognostic value than maximum standardized uptake value. Emerging imaging approaches, including radiomics, radiogenomics, and machine learning, may further enable noninvasive tumor characterization and outcome prediction. Recent advances in molecular imaging, including delta-like ligand 3- and somatostatin receptor-targeted immune-PET, represent key steps toward biomarker-guided and personalized therapy. Together, integration of structural, functional, and molecular imaging with biologic insights is expected to shape the next phase of precision oncology in this highly aggressive malignancy.
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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.