Evidence map›Paper›PMID 22771882›Full record

ArticleRadiology2012

Mapping microvasculature with acoustic angiography yields quantifiable differences between healthy and tumor-bearing tissue volumes in a rodent model.

Ryan C Gessner, Stephen R Aylward, Paul A Dayton

Abstract read
In one paragraph

Article in Radiology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
5.6field-weighted citation impact, top 4% of its field
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

67 citing papers in PubMed, 111 citations in OpenAlex.

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  7. Current trends in the characterization and monitoring of vascular response to cancer therapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024
    Review
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  9. Superharmonic and Microultrasound Imaging With Plane Wave Beamforming Techniques.IEEE transactions on ultrasonics, ferroelectrics, and frequency control · 2023
    Article
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  20. Acoustic Molecular Imaging Beyond the Diffraction Limit In Vivo.IEEE open journal of ultrasonics, ferroelectrics, and frequency control · 2022
    Article

7 more citing papers are in PubMed but not listed here.

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 at 3 institutions in 1 country.

Ryan C GessnerJoint Department of Biomedical Engineering, University of North Carolina, Chapel Hill and North Carolina State University, 304 Taylor Hall, 109 Mason Farm Rd, Chapel Hill, NC 27599-6136, USA.
Stephen R Aylward
Paul A Dayton
Kitware (United States) · USNorth Carolina State University · USUniversity of North Carolina at Chapel Hill · US

Funding

Tissue Procurement & PathologyP50CA058223 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI KATHERINE A. HOADLEY · 1992 to 2026
$59.3M
Image Registration for Ultrasound-Based Neurosurgical NavigationR01CA138419 · NCI · BRIGHAM AND WOMEN'S HOSPITAL · PI AYLWARD, STEPHEN R, WELLS, WILLIAM M. · 2009 to 2013
$1.8M
Immune-Shielded, Ultrasound-Stimulated Contrast Agents for Molecular ImagingR01EB009066 · NIBIB · UNIVERSITY OF COLORADO · PI BORDEN, MARK ANDREW, DAYTON, PAUL A · 2008 to 2011
$1.2M
NCI NIH HHS P50 CA058223NCI NIH HHS R01 CA138419NIBIB NIH HHS R01 EB009066
6 · The paper itself

Abstract

purposeTo determine if the morphologies of microvessels could be extracted from contrast material-enhanced acoustic angiographic ultrasonographic (US) images and used as a quantitative basis for distinguishing healthy from diseased tissue. MATERIALS AND

methodsAll studies were institutional animal care and use committee approved. Three-dimensional contrast-enhanced acoustic angiographic images were acquired in both healthy (n = 7) and tumor-bearing (n = 10) rats. High-spatial-resolution and high signal-to-noise acquisition was enabled by using a prototype dual-frequency US transducer (transmit at 4 MHz, receive at 30 MHz). A segmentation algorithm was utilized to extract microvessel structure from image data, and the distance metric (DM) and the sum of angles metric (SOAM), designed to distinguish different types of tortuosity, were applied to image data. The vessel populations extracted from tumor-bearing tissue volumes were compared against vessels extracted from tissue volumes in the same anatomic location within healthy control animals by using the two-sided Student t test.

resultsMetrics of microvascular tortuosity were significantly higher in the tumor population. The average DM of the tumor population (1.34 ± 0.40 [standard deviation]) was 23.76% higher than that of the control population (1.08 ± 0.08) (P < .0001), while the average SOAM (22.53 ± 7.82) was 50.73% higher than that of the control population (14.95 ± 4.83) (P < .0001). The DM and SOAM metrics for the control and tumor populations were significantly different when all vessels were pooled between the two animal populations. In addition, each animal in the tumor population had significantly different DM and SOAM metrics relative to the control population (P < .05 for all; P value ranges for DM, 3.89 × 10(-)(7) to 5.63 × 10(-)(3); and those for SOAM, 2.42 × 10(-)(12) to 1.57 × 10(-)(3)).

conclusionVascular network quantification by using high-spatial-resolution acoustic angiographic images is feasible. Data suggest that the angiogenic processes associated with tumor development in the models studied result in higher instances of vessel tortuosity near the tumor site.

Indexed as

MicrocirculationAnimalsContrast MediaDisease Models, AnimalFemaleFibrosarcomaImage Processing, Computer-AssistedImaging, Three-DimensionalMicrobubblesNeovascularization, PathologicProspective StudiesRatsRats, Inbred F344TransducersUltrasonographyContrast Media

Identifiers

PMID22771882
PMCPMC3426858
OpenAlexW2106142717

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.