Evidence map›Paper›PMID 25426388›Full record

ArticlePlastic and reconstructive surgery. Global open2014

Topological Analysis for Arteriovenous Malformations via Computed Tomography Angiography: Part 1: Mathematical Concepts.

Yuki Hata, Keigo Osuga, Tateki Kubo, Ken Matsuda, Koichi Tomita, Mamoru Kikuchi, Takashi Fujiwara, Kenji Yano, Ko Hosokawa

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2014. 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
0.3field-weighted citation impact, top 40% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

9 authors at 1 institution in 1 country.

Yuki HataDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Keigo OsugaDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Tateki KuboDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Ken MatsudaDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Koichi TomitaDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Mamoru KikuchiDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Takashi FujiwaraDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Kenji YanoDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Ko HosokawaDepartment of Plastic Surgery, Osaka University Graduate School of Medicine, Osaka, Japan; and Department of Diagnostic and Interventional Radiology, Osaka University Graduate School of Medicine, Osaka, Japan.
Osaka University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundEvaluating the progression of soft-tissue arteriovenous malformation (AVMs) is still problematic. To establish a quantitative method, we took a morphological approach.

methodsNormal blood vessels in early-phase 3D-computed tomography angiography images are theoretically expected to be tree-like structures without loops, whereas AVM blood vessels are expected to be mesh-like structures with loops. Simplified to the utmost limit, these vascular structures can be symbolized with wire-frame models composed of nodes and connecting edges, in which making an extra loop always needs one more of edges than of nodes.

resultsTOTAL AMOUNT OF ABNORMAL VASCULAR STRUCTURES IS ESTIMATED FROM A SIMPLE EQUATION: Number of vascular loops = 1 - ([Number of nodes] - [Number of edges]).

conclusionAbnormalities of AVM vascular structures can be mathematically quantified using computed tomography angiography images.

Identifiers

PMID25426388
PMCPMC4236366
OpenAlexW1897923412

What OpenQuestion holds

Textmetadata
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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.