Evidence map›Paper›PMID 40503548›Full record

ReviewCancer management and research2025

Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC.

Jingyi Liu, Mei Xie, Jing Shen, Jie Yao, Xuwen Lin, Xinyu Bao, Xin Zhang, Yiran Liang, Yun Yang, Gege Jiang and 5 more

Abstract readReview
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Improved early response assessment of chemoimmunotherapy efficacy byEuropean journal of nuclear medicine and molecular imaging · 2026
    Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. [Immunotherapy advances · 2025
    Article
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

15 authors.

Jingyi LiuDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.ORCID 0009-0009-0018-5803
Mei XieDepartment of Respiratory and Critical Care, Emergency and Critical Care Medical Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Jing ShenDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.
Jie YaoDepartment of Respiratory and Critical Care, Emergency and Critical Care Medical Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Xuwen LinDepartment of Respiratory and Critical Care, Emergency and Critical Care Medical Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Xinyu BaoDepartment of Respiratory and Critical Care, Affiliated Hospital of Shandong Second Medical University, Weifang, People's Republic of China.
Xin ZhangDepartment of Respiratory and Critical Care, Affiliated Hospital of Shandong Second Medical University, Weifang, People's Republic of China.
Yiran LiangDepartment of Respiratory and Critical Care, Emergency and Critical Care Medical Center, Beijing Shijitan Hospital, Capital Medical University, Beijing, 100038, People's Republic of China.
Yun YangDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.
Gege JiangDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.
Ximeng DiaoDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.
Wenya HanDepartment of Respiratory and Critical Care Medicine, Taihe Hospital, Hubei University of Medicine, Shiyan, 442000, People's Republic of China.
Hai DuOrdos Central Hospital, Ordos City, 017000, People's Republic of China.
Xinying XueDepartment of Respiratory and Critical Care, Affiliated Hospital of Shandong Second Medical University, Weifang, People's Republic of China.
Jianlin WuDepartment of Radiology, Affiliated Zhongshan Hospital of Dalian University, Dalian, 116001, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

CTefficacy predictionimmunotherapyMRInon-small cell lung cancerPET

Identifiers

PMID40503548
PMCPMC12154533

What OpenQuestion holds

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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.