Evidence map›Paper›PMID 26450104›Full record

ArticleInternational journal of computer assisted radiology and surgery2016

Intra-operative assessment of fractured articular surfaces in cone beam CT image data.

Michael Brehler, Joseph Görres, Sven Y Vetter, Jochen Franke, Paul A Grützner, Hans-Peter Meinzer, Ivo Wolf

Abstract read
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In one paragraph

Article in International journal of computer assisted radiology and surgery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact, top 96% 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

2 citing papers in PubMed, 6 citations in OpenAlex.

  1. Intraoperative revision rates due to three-dimensional imaging in orthopedic trauma surgery: results of a case series of 4721 patients.European journal of trauma and emergency surgery : official publication of the European Trauma Society · 2023
    Article
  2. Semi-automatic micro-CT segmentation of the midfoot using calibrated thresholds.International journal of computer assisted radiology and surgery · 2021
    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 4 institutions in 1 country.

Michael BrehlerDivision of Medical and Biological Informatics (E130), German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany. m.brehler@dkfz-heidelberg.de.
Joseph GörresDivision of Medical and Biological Informatics (E130), German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
Sven Y VetterBG Trauma Center, Ludwig-Guttmann-Strae 13, 67071, Ludwigshafen, Germany.
Jochen FrankeBG Trauma Center, Ludwig-Guttmann-Strae 13, 67071, Ludwigshafen, Germany.
Paul A GrütznerBG Trauma Center, Ludwig-Guttmann-Strae 13, 67071, Ludwigshafen, Germany.
Hans-Peter MeinzerDivision of Medical and Biological Informatics (E130), German Cancer Research Center, Im Neuenheimer Feld 280, 69120, Heidelberg, Germany.
Ivo WolfMannheim University of Applied Sciences, Paul-Wittsack-Str. 10, 68163, Mannheim, Germany.
Klinikum Ludwigshafen · DEHeidelberg University · DEGerman Cancer Research Center · DEMannheim University of Applied Sciences · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe assessment of intra-operatively acquired volumetric data is a difficult and often time-consuming task, which demands a new set of skills from the surgeons. In the case of orthopedic surgeries such as the treatment of calcaneal fractures, the correctness of the reduction of the bone fragments can be verified with the help of C-arm CT volumetric images. For an accurate intra-operative assessment of the displaced fragments, an automatic segmentation of the articular surfaces and color-coded visualization was developed.

methodsOur automatic approach consists of three major steps: first, using adjusted standard planes intersecting the articular region, the joint space is localized with an intensity profile-based method. In a second step, the localized joint space is segmented on the Laplacian of Gaussian filtered volumetric image by a modified binary flood fill algorithm. Finally, a 3D surface model of the segmented joint space is analyzed and visualized with focus on critical displacements of the surface.

resultsA specifically designed human cadaver study consisting of ten lower legs of ten different donors was conducted to acquire 48 realistic C-arm CT images of misaligned bone fragments (steps of varying sizes) in the posterior talar articular surface of the calcaneus. The proposed algorithmic pipeline was verified by the acquired image data and showed very good results with no false positives and an overall correct displacement assessment of 93.8%.

conclusionsThe proposed algorithmic pipeline can be easily integrated into the clinical workflow and qualifies for intra-operative usage. It showed very good results on the reference data set of the cadaver study. With the help of such an assistance system, the time-consuming process of 2D view adjustment and visual assessment of the gray value images can be greatly simplified.

Indexed as

AlgorithmsCadaverCalcaneusCone-Beam Computed TomographyFractures, BoneHumansArticular surfaceC-arm CTDisplacement detectionIntra-operative assessmentLaplacian of GaussianSegmentation

Identifiers

PMID26450104
OpenAlexW1884071937

What OpenQuestion holds

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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.