Evidence map›Paper›PMID 36348364›Full record

ArticleBMC musculoskeletal disorders2022

Registration based assessment of femoral torsion for rotational osteotomies based on the contralateral anatomy.

Armando Hoch, Julian Hasler, Pascal Schenk, Jakob Ackermann, Lars Ebert, Philipp Fürnstahl, Patrick Zingg, Lazaros Vlachopoulos

Open access · goldAbstract read
In one paragraph

Article in BMC musculoskeletal disorders, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 35% 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, 1 synthesis or guideline pooled it, 2 citations in OpenAlex.

  1. Pooled it
  2. 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

8 authors at 1 institution in 1 country.

Armando HochDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland. armando.hoch@balgrist.ch.
Julian HaslerDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Pascal SchenkDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Jakob AckermannDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Lars EbertZurich Institute of Forensic Medicine, University of Zurich, Zurich, Switzerland.
Philipp FürnstahlResearch in Orthopaedic Computer Science, Balgrist University Hospital, University of Zurich, Zurich, Switzerland.
Patrick ZinggDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
Lazaros VlachopoulosDepartment of Orthopaedics, Balgrist University Hospital, University of Zurich, Forchstrasse 340, 8008, Zurich, Switzerland.
University of Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundComputer-assisted techniques for surgical treatment of femoral deformities have become increasingly important. In state-of-the-art 3D deformity assessments, the contralateral side is used as template for correction as it commonly represents normal anatomy. Contributing to this, an iterative closest point (ICP) algorithm is used for registration. However, the anatomical sections of the femur with idiosyncratic features, which allow for a consistent deformity assessment with ICP algorithms being unknown. Furthermore, if there is a side-to-side difference, this is not considered in error quantification. The aim of this study was to analyze the influence and value of the different sections of the femur in 3D assessment of femoral deformities based on the contralateral anatomy. MATERIAL AND

methods3D triangular surface models were created from CT of 100 paired femurs (50 cadavers) without pathological anatomy. The femurs were divided into sections of eponymous anatomy of a predefined percentage of the whole femoral length. A surface registration algorithm was applied to superimpose the ipsilateral on the contralateral side. We evaluated 3D femoral contralateral registration (FCR) errors, defined as difference in 3D rotation of the respective femoral section before and after registration to the contralateral side. To compare this method, we quantified the landmark-based femoral torsion (LB FT). This was defined as the intra-individual difference in overall femoral torsion using with a landmark-based method.

resultsContralateral rotational deviation ranged from 0° to 9.3° of the assessed femoral sections, depending on the section. Among the sections, the FCR error using the proximal diaphyseal area for registration was larger than any other sectional error. A combination of the lesser trochanter and the proximal diaphyseal area showed the smallest error. The LB FT error was significantly larger than any sectional error (p < 0.001).

conclusionWe demonstrated that if the contralateral femur is used as reconstruction template, the built-in errors with the registration-based approach are smaller than the intraindividual difference of the femoral torsion between both sides. The errors are depending on the section and their idiosyncratic features used for registration. For rotational osteotomies a combination of the lesser trochanter and the proximal diaphyseal area sections seems to allow for a reconstruction with a minimal error.

Indexed as

Bone DiseasesTomography, X-Ray ComputedAlgorithmsCadaverFemurHumansOsteotomy3D imagingComputer assisted surgeryFemoral osteotomyFemoral torsion

Identifiers

PMID36348364
PMCPMC9641797
OpenAlexW4308595115

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.