Evidence map›Paper›PMID 39768042›Full record

ArticleBioengineering (Basel, Switzerland)2024

Methods for Rapid Characterization of Tunable Microbubble Formulations.

Savannah L Harpster, Alexandra M Piñeiro, Joyce Y Wong

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2024. 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. Review
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.

Savannah L HarpsterDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.ORCID 0009-0009-3974-1774
Alexandra M PiñeiroDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.
Joyce Y WongDepartment of Biomedical Engineering, Boston University, Boston, MA 02215, USA.ORCID 0000-0002-3526-6381

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To optimize microbubble formulations for clinical applications, the size distribution, concentration, and acoustic intensity must be rapidly measurable to allow for the successful iteration of microbubble design. In this paper, a comprehensive method was developed to compare microbubble formulations with different lipid shell compositions using optical and acoustic methods of measurement to collect the size distribution, concentration, and mean scattering intensity. An open-source ImageJ macro code was modified for the selective counting and sizing of brightfield microbubble images. A high-throughput agarose phantom was designed to collect multiple scattering reflections of microbubble samples to estimate the echogenicity of each microbubble solution. The information contained in the size distribution and concentration, combined with the instantaneous scattering power, can identify modifications needed for prototyping specific microbubble formulations.

Indexed as

lipidsmedical imagingmicrobubblesparticle segmentationtissue-mimicking phantomultrasound

Identifiers

PMID39768042
PMCPMC11673760

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.