Evidence map›Paper›PMID 41882234›Full record

ReviewNpj imaging2026

Advanced imaging techniques for tumor intraoperative navigation imaging.

Ke Li, Yiyin Zhang, Houpu Yang, Shu Wang

Abstract readReview
In one paragraph

Review in Npj imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

4 authors.

Ke Li *Department of Breast Center, Peking University People's Hospital, Peking University, Beijing, China.
Yiyin Zhang *Department of Breast Center, Peking University People's Hospital, Peking University, Beijing, China.
Houpu YangDepartment of Breast Center, Peking University People's Hospital, Peking University, Beijing, China.
Shu WangDepartment of Breast Center, Peking University People's Hospital, Peking University, Beijing, China. shuwang@pkuph.edu.cn.

Funding

National Key Research and Development Program of China 2024YFC3405300National Natural Science Foundation of China 82372629Natural Science Foundation of Beijing Municipality 7244427
6 · The paper itself

Abstract

Cancer remains a leading cause of mortality and morbidity, with surgical resection being a fundamental element of treatment. However, early detection and precise tumor resection are critical for improving survival and minimizing recurrence. Conventional imaging techniques face limitations in resolution, real-time feedback, and tissue differentiation, often leading to imprecise resection. Recent advancements in intraoperative imaging technologies have gradually addressed these challenges. Fluorescence imaging offers superior tissue penetration, enhanced signal-to-noise ratio, and resilience under a surgical environment, making it ideal for real-time tissue and lymph node detection. Targeted molecular probes and advanced fluorescence techniques further enhance tumor specificity. Modalities like photoacoustic and Raman spectroscopy provide complementary insights, while three-dimensional reconstruction and multimodal systems improve anatomical precision. Early clinical studies demonstrate these technologies' high sensitivity and clinical feasibility in tumor detection and margin assessment. Integrating artificial intelligence and personalized medicine into intraoperative imaging holds promise for further refining these techniques, leading to more tailored and effective interventions. This review provides an overview of the evolution and clinical practice of novel intraoperative imaging technologies, highlighting their superiority over traditional methods and outlining the future research directions in this rapidly advancing field.

Identifiers

PMID41882234
PMCPMC13018579

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.