Evidence map›Paper›PMID 42831125›Full record

ArticlePhotoacoustics2026

Robot-assisted wide-amplitude oscillatory photoacoustic scanning for three-dimensional human peripheral vascular imaging: A preliminary feasibility study.

Yongjian Zhao, Li Shen, Hengrong Lan, Yanting Liang, Fei Gao, Nanguang Chen

Abstract read
In one paragraph

Article in Photoacoustics, 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

6 authors.

Yongjian ZhaoSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Li ShenSchool of Computer Science and Engineering, Southeast University, Nanjing, 211189, Jiangsu, China.
Hengrong LanSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Yanting LiangDepartment of Nephrology, Shenzhen Key Laboratory of Kidney Diseases, Shenzhen People's Hospital (The Second Clinical Medical College, Jinan University; The First Affiliated Hospital, Southern University of Science and Technology), Shenzhen, 518020, Guangdong, China.
Fei GaoSchool of Biomedical Engineering, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230026, Anhui, China.
Nanguang ChenDepartment of Biomedical Engineering, The Hong Kong Polytechnic University, Hung Hom, Kowloon, 999077, Hong Kong Special Administrative Region of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photoacoustic tomography (PAT) is a promising tool for non-invasive vascular imaging, yet conventional linear scanning suffers from "limited-view" artifacts and structural discontinuities due to restricted transducer acceptance angles. To overcome these physical bottlenecks, we propose a robot-assisted wide-amplitude oscillatory (WAO) scanning strategy. By integrating controlled lateral harmonic oscillations into axial linear trajectories via a 6-DoF robotic arm, this method achieves kinematic modulation to physically synthesize a dynamic aperture. This approach effectively captures high-frequency acoustic information typically lost in single-path scans, compensating for hardware-based detection limits. Numerical simulations and a preliminary

Indexed as

Robotic photoacoustic tomographyThree-dimensional imagingVascular imaging in humanWide-amplitude oscillatory scanning

Identifiers

PMID42831125
PMCPMC13634726

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.