AI-Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High-Contrast HER2-Positive Tumor Imaging.

Jiaying Zheng, Yi Zhu, Xinrui Li, Sunxian Dai, Xiangyuan Ma, Hongwei Lu, Zhongling Wang, Benqing Zhou

Abstract read

In one paragraph

Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 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.

Jiaying Zheng *Department of Biomedical Engineering, College of Engineering, Shantou University, Shantou, People's Republic of China.

Yi Zhu *Department of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.

Xinrui LiDepartment of Biomedical Engineering, College of Engineering, Shantou University, Shantou, People's Republic of China.

Sunxian DaiDepartment of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.

Xiangyuan MaDepartment of Biomedical Engineering, College of Engineering, Shantou University, Shantou, People's Republic of China.ORCID https://orcid.org/0000-0002-8107-6861

Hongwei LuDepartment of Biomedical Engineering, College of Engineering, Shantou University, Shantou, People's Republic of China.

Zhongling WangDepartment of Radiology, Shanghai General Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, People's Republic of China.ORCID https://orcid.org/0000-0002-5477-1287

Benqing ZhouDepartment of Biomedical Engineering, College of Engineering, Shantou University, Shantou, People's Republic of China.ORCID https://orcid.org/0000-0002-9202-3730

Funding

Guangdong Province Natural Science Foundation 2024A1515012067Guangdong Province Natural Science Foundation 2025A1515012213Li Ka Shing Foundation STU-GTIIT Joint-research Grant 2025LKSFG08National Natural Science Foundation of China 32301160National Natural Science Foundation of China 82272057National Natural Science Foundation of China 82372057

6 · The paper itself

Abstract

Breast cancer continues to be a leading cause of cancer-related mortality in women globally, where precise diagnosis and clear tumor demarcation are critical for effective treatment. Herein, we developed a strategic platform that combines a novel ultrasensitive magnetic resonance (MR) contrast agent with deep learning to significantly enhance the tumor-to-normal ratio (TNR). We designed ultrasmall iron oxide nanoparticles (USIO NPs) conjugated with trastuzumab (Tmab) for targeted MR imaging of HER2-positive breast cancer. The USIO@Tmab nanoprobe demonstrated excellent HER2 specificity and pH-responsive activation. The relaxivity of the nanoprobe shifted from a low T

Indexed as

3D nnU‐Netdeep learningHER2‐positive tumor imagingmagnetic resonance imagingultrasmall iron oxide nanoparticles

Identifiers

PMID42636021

DOI10.1002/advs.77355

PMCPMC13502355

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.