Evidence map›Paper›PMID 42434845›Full record

ReviewAdvanced healthcare materials2026

Nanoplatforms for Sentinel and Tumor-Draining Lymph Node Mapping: From Visualization to Pathway-Informed Staging.

Xu Chen, Nina Li, Meiyan Zou, Zihao Zhou, Rongwei Xu, Weiyao Feng, Xinyuan Zhao, Li Cui

Abstract readReview
In one paragraph

Review in Advanced healthcare materials, 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

8 authors.

Xu ChenStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Nina LiStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Meiyan ZouStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Zihao ZhouStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Rongwei XuStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Weiyao FengStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.
Xinyuan ZhaoStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.ORCID https://orcid.org/0000-0003-4770-8877
Li CuiStomatological Hospital, School of Stomatology, Southern Medical University, Guangzhou, Guangdong, China.

Funding

Guangdong Provincial Science and Technology Project Foundation 2022A0505050038National Natural Science Foundation of China 82372905National Natural Science Foundation of China 82573074Science and Technology Program of Guangzhou 2025A04J3464Young Top-notch Talent of Pearl River Talent Plan 0920220228
6 · The paper itself

Abstract

Accurate identification of sentinel lymph nodes (SLNs) and tumor-draining lymph nodes (TDLNs) is central to oncologic staging, treatment stratification, and surgical decision-making. However, conventional radiotracer- and dye-based approaches remain limited by suboptimal signal specificity, inflexible workflows, and reduced reliability in anatomically complex or therapy-altered lymphatic networks. Nanoparticle-based lymphatic tracers address these limitations by enabling controllable lymphatic transport, stable intranodal retention, and multimodal signal generation, thereby expanding the precision and applicability of SLN/TDLN detection. This review analyzes recent advances in carbon-based, magnetic, metal/metal-oxide, polymeric/organic, and bio-derived or biomimetic nanoparticles for lymph node mapping, with emphasis on how material composition, surface engineering, and physical contrast mechanisms translate into clinically actionable imaging performance. Shared design principles underlying three key objectives are further synthesized: sensitive detection of early and occult nodes, reliable discrimination of metastatic involvement with improved staging accuracy, and robustness across delayed surgery, neoadjuvant therapy, and multi-step clinical workflows. Collectively, these advances position lymphotropic nanoparticles as a mechanistically grounded and clinically promising platform for extending both the accuracy and operational boundaries of SLN/TDLN assessment.

Indexed as

Lymph NodesNanoparticlesNeoplasmsSentinel Lymph NodeAnimalsHumansLymphatic MetastasisNeoplasm StagingSentinel Lymph Node Biopsylymphatic mappingmultimodal imagingnanoparticle tracerssentinel lymph nodestumor‐draining lymph nodes

Identifiers

PMID42434845
PMCPMC13474130

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.