Evidence map›Paper›PMID 24480728›Full record

ArticleJournal of neurointerventional surgery2015

Quantitative analysis of high-resolution, contrast-enhanced, cone-beam CT for the detection of intracranial in-stent hyperplasia.

Thomas F Flood, Imramsjah M J van der Bom, Lara Strittmatter, Ajit S Puri, Gregory M Hendricks, Ajay K Wakhloo, Matthew J Gounis

Open access · hybridAbstract readCase Reports
In one paragraph

Article in Journal of neurointerventional surgery, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
2.7field-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

14 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Optimizing contrast-enhanced cone-beam CT protocol to facilitate simultaneous visualization of neurovascular pathologies and surrounding structures of interest.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2019
    Article
  11. Article
  12. Article
  13. Use of self-expanding stents for better intracranial flow diverter wall apposition.Interventional neuroradiology : journal of peritherapeutic neuroradiology, surgical procedures and related neurosciences · 2017
    Article
  14. 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

7 authors at 1 institution in 1 country.

Thomas F FloodDepartment of Radiology, New England Center for Stroke Research, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Imramsjah M J van der BomDepartment of Radiology, New England Center for Stroke Research, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Lara StrittmatterDepartment of Cell Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Ajit S PuriDepartment of Radiology, New England Center for Stroke Research, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Gregory M HendricksDepartment of Cell Biology, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Ajay K WakhlooDepartment of Radiology, New England Center for Stroke Research, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
Matthew J GounisDepartment of Radiology, New England Center for Stroke Research, University of Massachusetts Medical School, Worcester, Massachusetts, USA.
University of Massachusetts Chan Medical School · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIntracranial in-stent hyperplasia is a stroke-associated complication that requires routine surveillance.

objectiveTo compare the results of in vivo experiments to determine the accuracy and precision of in-stent hyperplasia measurements obtained with modified C-arm contrast-enhanced, cone-beam CT (CE-CBCT) imaging with those obtained by 'gold standard' histomorphometry. Additionally, to carry out clinical analyses comparing this CE-CBCT protocol with digital subtraction angiography (DSA).

methodsA non-binned CE-CBCT protocol (VasoCT) was used that acquires x-ray images with a small field-of-view and applies a full-scale reconstruction algorithm providing high-resolution three-dimensional (3D) imaging with 100 µm isotropic voxels. In an vivo porcine model, VasoCT cross-sectional area measurements were compared with gold standard vessel histology. VasoCT and DSA were used to calculate in-stent stenosis in 23 imaging studies.

resultsPorcine VasoCT cross-sectional stent, lumen, and in-stent hyperplasia areas strongly correlated with histological measurements (r(2)=0.97, 0.93, 0.90; slope=1.14, 1.07, and 0.76, respectively; p<0.0001). Clinical VasoCT percentage stenosis correlated well with DSA percentage stenosis (r(2)=0.84; slope=0.76), and the two techniques were free of consistent bias (Bland-Altman, bias=3.29%; 95% CI -14.75% to 21.33%). An illustrative clinical case demonstrated the advantages of VasoCT, including 3D capability and non-invasive IV contrast administration, for detection of in-stent hyperplasia.

conclusionsC-arm VasoCT is a high-resolution 3D capable imaging technique that has been validated in an animal model for measurement of in-stent tissue growth. Successful clinical implementation of the protocol was performed in a small case series.

Indexed as

AgedAnimalsCerebral InfarctionCone-Beam Computed TomographyHumansHyperplasiaRetrospective StudiesStentsSwineCTCT AngiographyInterventionStentTechnology

Identifiers

PMID24480728
PMCPMC4316917
OpenAlexW1967055446

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.