Evidence map›Paper›PMID 40136814›Full record

ArticleBiomimetics (Basel, Switzerland)2025

Optimization of High-Frequency Ultrasound Imaging to Detect Incremental Changes in Mineral Content at the Cartilage-Bone Interface Ex Vivo.

Akshay Charan, Parag V Chitnis, Caroline D Hoemann

Abstract read
In one paragraph

Article in Biomimetics (Basel, Switzerland), 2025. 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

3 authors.

Akshay CharanDepartment of Bioengineering, George Mason University, Manassas, VA 20110, USA.
Parag V ChitnisDepartment of Bioengineering, George Mason University, Manassas, VA 20110, USA.
Caroline D HoemannDepartment of Bioengineering, George Mason University, Manassas, VA 20110, USA.ORCID 0000-0003-3750-7879

Funding

George Mason University 162921
6 · The paper itself

Abstract

(1) Background: Osteoarthritis is a degenerative disease of the whole joint marked by cartilage-bone interface (CBI) remodeling, but methods to monitor subtle changes in mineralization are lacking. We optimized a non-destructive ultrasound imaging method to monitor incremental shifts in mineralization, using brief decalcification as a mimetic of CBI remodeling. (2) Methods: We used a 35-MHz transducer to scan 3 mm diameter bovine osteochondral explants wrapped with parafilm to produce surface-directed decalcification and dedicated 3D-printed holders to maintain sample orientation. Customized MATLAB codes and a matched pair design were used for quantitative hypothesis testing. (3) Results: Optimal scan precision was obtained when the High-Frequency Ultrasound (HFUS) focal distance was trained at the CBI. HFUS cartilage thickness increased by 53 ± 21 µm or 97 ± 28 µm after three or seven hours of ethylene diamine tetra-acetic acid (EDTA) (but not PBS), respectively, and was highly correlated with histological cartilage thickness (R = 0.98). The en face CBI backscatter pattern was irregular and shifted after the EDTA-displacement of the mineral front. Collective data suggested that the -10 dB echogenic CBI signal originated from the mineral front and varied topographically with undulating mineral thickness. (4) Conclusions: This imaging approach could be used to monitor tidemark remodeling in live explant cultures, toward identifying new treatments that inhibit tidemark advancement and slow osteoarthritis progression.

Indexed as

cartilage–bone interfacedecalcificationhard/soft interface remodelinghigh frequency ultrasoundnon-decalcified histologytidemarkvon Kossa stain

Identifiers

PMID40136814
PMCPMC11940126

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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.