Evidence map›Paper›PMID 41749723›Full record

ArticleBioengineering (Basel, Switzerland)2026

Harmonic Ratio Analysis in Magnetic Particle Imaging Enables Differentiation of Malignant and Benign Human Breast Tissues: A Feasibility Study.

Hongyu Yang, Haoran Zhang, Yiyin Zhang, Yixiang Zhou, Xinmiao Qu, Xun Zhang, Ke Li, Hanfu Shi, Hui Lin, Shu Wang and 1 more

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 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
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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

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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

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5 · Who and what money

Authors and funding

11 authors.

Hongyu YangKey Laboratory of Big Data-Based Precision Medicine of Ministry of Industry and Information Technology, School of Engineering Medicine, Beihang University, Beijing 100191, China.ORCID 0009-0004-5220-0052
Haoran ZhangSchool of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China.
Yiyin ZhangBreast Center, Peking University People's Hospital, Peking University, Beijing 100044, China.
Yixiang ZhouKey Laboratory of Big Data-Based Precision Medicine of Ministry of Industry and Information Technology, School of Engineering Medicine, Beihang University, Beijing 100191, China.
Xinmiao QuKey Laboratory of Big Data-Based Precision Medicine of Ministry of Industry and Information Technology, School of Engineering Medicine, Beihang University, Beijing 100191, China.
Xun ZhangKey Laboratory of Big Data-Based Precision Medicine of Ministry of Industry and Information Technology, School of Engineering Medicine, Beihang University, Beijing 100191, China.
Ke LiBreast Center, Peking University People's Hospital, Peking University, Beijing 100044, China.
Hanfu ShiAcademy of Macroeconomic Research National Development and Reform Commission of People's Republic of China, Beijing 100038, China.
Hui LinDepartment of General Surgery, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310018, China.
Shu WangBreast Center, Peking University People's Hospital, Peking University, Beijing 100044, China.ORCID 0000-0002-8651-4795
Zeyu ZhangKey Laboratory of Big Data-Based Precision Medicine of Ministry of Industry and Information Technology, School of Engineering Medicine, Beihang University, Beijing 100191, China.

Funding

Beijing Natural Science Foundation 7244427Beijing Natural Science Foundation L241074National Key Research and Development Program of China 2024YFC3405700National Natural Science Foundation of China 62471019National Natural Science Foundation of China 92359301National Natural Science Foundation of China U23A20487Sichuan Clinical Research Center for Medical Imaging (Dazhou) YXYX2416
6 · The paper itself

Abstract

Accurate intraoperative differentiation between malignant and benign breast tissues, particularly the assessment of lymph node status and tumor margins, is critical for surgical decision-making and prognosis. Traditional histopathological methods, such as frozen section analysis, are time-consuming and labor-intensive. Magnetic Particle Imaging (MPI) is a novel, radiation-free modality that senses the microenvironmental properties of tissues through the dynamic response of magnetic tracers. In this study, we propose a diagnostic method utilizing the higher-order harmonic response of magnetic nanoparticles. Various ex vivo breast tissue samples were immersed in Synomag-50 nanoparticles. Using a custom-built MPI spectrometer (5 kHz excitation, 9 mT amplitude) operating in spectroscopic mode, we implemented a rapid acquisition protocol in which each sample was measured 10 times, with 0.1 s per cycle. We analyzed the magnetic response spectrum and calculated the ratio of the third to the fifth harmonic (H3/H5). Histological analysis confirmed the effective infiltration of MNPs into the interstitial spaces. The repeated measurement data demonstrated high stability. A distinct stepwise increase in harmonic ratios was observed from normal tissue to tumor-adjacent tissue and finally to malignant tumors. Specifically, malignant samples showed ratios that generally exceeded 2.2, whereas benign samples remained below 2.0. These preliminary findings suggest that the harmonic ratio could serve as a sensitive biomarker reflecting the microenvironmental constraints associated with malignancy. This study validates the feasibility of utilizing MPI signal harmonics as a quantitative metric with rapid signal acquisition capabilities for differentiating benign and malignant lymph nodes.

Indexed as

breast cancerharmonic ratiolymph nodesmagnetic nanoparticlesMagnetic Particle Imaging (MPI)tissue characterization

Identifiers

PMID41749723
PMCPMC12938619

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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.