Evidence map›Paper›PMID 40944838›Full record

ReviewJournal of ultrasound2025

Biomechanical assessment of Hoffa fat pad characteristics with ultrasound: a narrative review focusing on diagnostic imaging and image-guided interventions.

Ni Qin, Bolong Zhang, Xiaoying Zhang, Li Tian

Abstract readReview
In one paragraph

Review in Journal of ultrasound, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Ni QinHenan University of Chinese Medicine, Zhengzhou, China.
Bolong ZhangHenan University of Chinese Medicine, Zhengzhou, China.
Xiaoying ZhangDepartment of Ultrasound, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China.
Li TianDepartment of Ultrasound, The Third Affiliated Hospital of Henan University of Chinese Medicine, Zhengzhou, China. 16696086465@163.com.ORCID http://orcid.org/0009-0006-1759-0299

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The infrapatellar fat pad (IFP), a key intra-articular knee structure, plays a crucial role in biomechanical cushioning and metabolic regulation, with fibrosis and inflammation contributing to osteoarthritis-related pain and dysfunction. This review outlines the anatomy and clinical value of IFP ultrasonography in static and dynamic assessment, as well as guided interventions. Shear wave elastography (SWE), Doppler imaging, and dynamic ultrasound effectively quantify tissue stiffness, vascular signals, and flexion-extension morphology. Due to the limited penetration capability of ultrasound imaging, it is difficult to directly observe IPF through the patella. However, its real-time capability and sensitivity effectively complement the detailed anatomical information provided by MRI, making it an important supplementary method for MRI-based IPF detection. This integrated approach creates a robust diagnostic pathway, from initial assessment and precise treatment guidance to long-term monitoring. Advances in ultrasound-guided precision medicine, protocol standardization, and the integration of Artificial Intelligence (AI) with multimodal imaging hold significant promise for improving the management of IFP pathologies.

Indexed as

Adipose TissueKnee JointUltrasonography, InterventionalBiomechanical PhenomenaElasticity Imaging TechniquesHumansUltrasonographyInfrapatellar fat padKnee osteoarthritisMultimodal imagingPrecision medicineUltrasound technology

Identifiers

PMID40944838
PMCPMC12675896

What Socratic 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 Socratic graph.