Evidence map›Paper›PMID 26910759›Full record

ArticlePloS one2016

In Vivo Quantitative Microcomputed Tomographic Analysis of Vasculature and Organs in a Normal and Diseased Mouse Model.

Nanditha Mohan Das, Sarah Hatsell, Kalyan Nannuru, Lily Huang, Xialing Wen, Lili Wang, Li-Hsien Wang, Vincent Idone, Jeffrey A Meganck, Andrew Murphy and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
2.8field-weighted citation impact, top 11% 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

16 citing papers in PubMed, 29 citations in OpenAlex.

  1. Review
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  4. Contrast-enhanced photon-counting micro-CT of tumor xenograft models.bioRxiv : the preprint server for biology · 2024
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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

12 authors at 2 institutions in 1 country.

Nanditha Mohan DasDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Sarah HatsellDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Kalyan NannuruDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Lily HuangDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Xialing WenDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Lili WangDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Li-Hsien WangDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Vincent IdoneDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Jeffrey A MeganckResearch and Development, PerkinElmer, Hopkinton, Massachusetts, United States of America.
Andrew MurphyDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Aris EconomidesDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
LiQin XieDepartment of Skeletal Diseases - Therapeutic Focus Areas, Regeneron Pharmaceuticals Inc., Tarrytown, New York, United States of America.
Regeneron (United States) · USPerkinElmer (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Non-bone in vivo micro-CT imaging has many potential applications for preclinical evaluation. Specifically, the in vivo quantification of changes in the vascular network and organ morphology in small animals, associated with the emergence and progression of diseases like bone fracture, inflammation and cancer, would be critical to the development and evaluation of new therapies for the same. However, there are few published papers describing the in vivo vascular imaging in small animals, due to technical challenges, such as low image quality and low vessel contrast in surrounding tissues. These studies have primarily focused on lung, cardiovascular and brain imaging. In vivo vascular imaging of mouse hind limbs has not been reported. We have developed an in vivo CT imaging technique to visualize and quantify vasculature and organ structure in disease models, with the goal of improved quality images. With 1-2 minutes scanning by a high speed in vivo micro-CT scanner (Quantum CT), and injection of a highly efficient contrast agent (Exitron nano 12000), vasculature and organ structure were semi-automatically segmented and quantified via image analysis software (Analyze). Vessels of the head and hind limbs, and organs like the heart, liver, kidneys and spleen were visualized and segmented from density maps. In a mouse model of bone metastasis, neoangiogenesis was observed, and associated changes to vessel morphology were computed, along with associated enlargement of the spleen. The in vivo CT image quality, voxel size down to 20 μm, is sufficient to visualize and quantify mouse vascular morphology. With this technique, in vivo vascular monitoring becomes feasible for the preclinical evaluation of small animal disease models.

Indexed as

Neoplasms, ExperimentalAngiographyAnimalsContrast MediaMiceNeovascularization, PathologicOrgan SpecificityX-Ray MicrotomographyContrast Media

Identifiers

PMID26910759
PMCPMC4765930
OpenAlexW2279530658

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.