Evidence map›Paper›PMID 42790152›Full record

ArticleUltrasonics sonochemistry2026

Microbubble-assisted pLIFU enhances riboflavin delivery and corneal cross-linking in an in vivo rabbit keratoconus-like model.

Qiao Wang, Shifang Guo, Youjia Sun, Yaojie Wu, Ziyi Lin, Tongyu Wang, Xipeng Chen, Qiang Su, Yupin Zheng, Yue Wu and 2 more

Abstract read
In one paragraph

Article in Ultrasonics sonochemistry, 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

12 authors.

Qiao WangDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Shifang GuoDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Youjia SunDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Yaojie WuDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Ziyi LinDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Tongyu WangDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Xipeng ChenDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.
Qiang SuDepartment of Oncology, Beijing Friendship Hospital, Capital Medical University. Beijing, China.
Yupin ZhengDepartment of Ophthalmology, the Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China.
Yue WuDepartment of Cardiology, the First Affiliated Hospital, Xi'an Jiaotong University, Xi'an, China.
Diya WangDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China. Electronic address: wang.diya@xjtu.edu.cn.
Mingxi WanDepartment of Biomedical Engineering, Key Laboratory of Biomedical Information Engineering of the Ministry of Education, School of Life Science and Technology, Xi'an Jiaotong University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Epithelium-off corneal collagen cross-linking (CXL) slows keratoconus progression but disrupts the epithelial barrier, whereas epithelium-on CXL is constrained by limited stromal riboflavin loading and insufficient evidence that physical delivery enhancement improves CXL outcomes in vivo keratoconus-like ectasia. Here, we developed microbubble-assisted pulsed low-intensity focused ultrasound (pLIFU) to enhance riboflavin transport through cavitation and evaluated its therapeutic effect in a collagenase-induced rabbit keratoconus-like model. Passive cavitation detection and temperature monitoring identified a treatment condition of 1 Hz pulse repetition frequency, 20 % duty cycle, 1.43 MPa focal-zone peak negative pressure, and 200 μl SonoVue solution, with maximum temperature rise limited to 1.5 °C. Hydrophone measurements showed low posterior-segment acoustic action, with a retinal-position mechanical index of approximately 0.076. Confocal fluorescence imaging showed that pLIFU with microbubbles increased peak stromal riboflavin fluorescence by 9.27 ± 2.16-fold (p < 0.0001) and effective penetration depth by 4.09-fold (p < 0.001) relative to control. In vivo, pLIFU-microbubble-enhanced CXL produced greater corneal flattening and a larger shear-wave-speed response than the US group. One month after treatment, central corneal curvature decreased by 45.85 ± 6.32 % and shear-wave speed (c

Indexed as

CorneaDrug Delivery SystemsKeratoconusMicrobubblesRiboflavinUltrasonic WavesAnimalsCollagenCorneal Cross-LinkingDisease Models, AnimalRabbitsCollagenRiboflavinAcoustic cavitationCorneal collagen cross-linkingKeratoconusMicrobubble cavitationPulsed low-intensity focused ultrasoundRiboflavin delivery

Identifiers

PMID42790152
PMCPMC13635697

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Registered trials

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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.