Evidence map›Paper›PMID 42065647›Full record

ReviewRadiology. Imaging cancer2026

Imaging of Small Cell Lung Cancer: An Updated Overview of Current and Emerging Applications.

Min Jae Cha, Hyewon Choi, Boda Nam, Chung Ryul Oh, Se-Hoon Lee, Joon Young Choi, Semin Chong, Joungho Han, Kyung Soo Lee

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Min Jae ChaDepartment of Radiology, University of Washington, UW Medical Center-Montlake, Seattle, Wash.ORCID 0000-0001-6358-8081
Hyewon ChoiDepartment of Radiology, Chung-Ang University Hospital, Seoul, Korea.ORCID 0000-0003-3735-6791
Boda NamDepartment of Radiology, Chung-Ang University Hospital, Seoul, Korea.ORCID 0000-0001-7822-6104
Chung Ryul OhDivision of Hematology and Oncology, Department of Medicine, Chung-Ang University Hospital, Chung-Ang University School of Medicine, Seoul, Korea.ORCID 0000-0003-1788-4538
Se-Hoon LeeDivision of Hematology and Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID 0000-0002-9219-3350
Joon Young ChoiDepartment of Nuclear Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Korea.ORCID 0000-0003-1060-0096
Semin ChongDepartment of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Kangnam-Ku, Seoul 135-710, Korea.
Joungho HanDepartment of Pathology, Samsung Medical Center, Sunkyunkwan University School of Medicine, Seoul, Korea.
Kyung Soo LeeDepartment of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, 50 Ilwon-Dong, Kangnam-Ku, Seoul 135-710, Korea.ORCID 0000-0002-3660-5728

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Precision MedicineSmall Cell Lung CarcinomaLung NeoplasmsMagnetic Resonance ImagingPositron Emission Tomography Computed TomographyCTDiagnosisImaging ModalityLungMachine LearningMolecular ImagingMRIMR ImagingNeoplasms-PrimaryOncologyPersonalized MedicinePETPET/CTRadiogenomicsRadiolabeled TracerSmall Cell Lung Cancer

Identifiers

PMID42065647
PMCPMC13231205

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.