Evidence map›Paper›PMID 36964560›Full record

ArticleBiomedical engineering online2023

3D shape reconstruction of the femur from planar X-ray images using statistical shape and appearance models.

Daniel Nolte, Shuqiao Xie, Anthony M J Bull

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Article in Biomedical engineering online, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

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0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Daniel NolteDepartment of Bioengineering, Imperial College London, London, SW7 2AZ, UK.
Shuqiao XieDepartment of Bioengineering, Imperial College London, London, SW7 2AZ, UK. s.xie19@imperial.ac.uk.
Anthony M J BullDepartment of Bioengineering, Imperial College London, London, SW7 2AZ, UK.

Funding

EPSRC Global Challenges Research Fund EP/P510798/1NIHR Global Health Research Grant GHR Project:16/137/45
6 · The paper itself

Abstract

Major trauma is a condition that can result in severe bone damage. Customised orthopaedic reconstruction allows for limb salvage surgery and helps to restore joint alignment. For the best possible outcome three dimensional (3D) medical imaging is necessary, but its availability and access, especially in developing countries, can be challenging. In this study, 3D bone shapes of the femur reconstructed from planar radiographs representing bone defects were evaluated for use in orthopaedic surgery. Statistical shape and appearance models generated from 40 cadaveric X-ray computed tomography (CT) images were used to reconstruct 3D bone shapes. The reconstruction simulated bone defects of between 0% and 50% of the whole bone, and the prediction accuracy using anterior-posterior (AP) and anterior-posterior/medial-lateral (AP/ML) X-rays were compared. As error metrics for the comparison, measures evaluating the distance between contour lines of the projections as well as a measure comparing similarities in image intensities were used. The results were evaluated using the root-mean-square distance for surface error as well as differences in commonly used anatomical measures, including bow, femoral neck, diaphyseal-condylar and version angles between reconstructed surfaces from the shape model and the intact shape reconstructed from the CT image. The reconstructions had average surface errors between 1.59 and 3.59 mm with reconstructions using the contour error metric from the AP/ML directions being the most accurate. Predictions of bow and femoral neck angles were well below the clinical threshold accuracy of 3°, diaphyseal-condylar angles were around the threshold of 3° and only version angle predictions of between 5.3° and 9.3° were above the clinical threshold, but below the range reported in clinical practice using computer navigation (i.e., 17° internal to 15° external rotation). This study shows that the reconstructions from partly available planar images using statistical shape and appearance models had an accuracy which would support their potential use in orthopaedic reconstruction.

Indexed as

FemurImaging, Three-DimensionalHumansLower ExtremityModels, StatisticalRadiographyX-Rays2D–3D reconstructionAnatomical measuresBone lossDigitally reconstructed radiographsOrthopaedic reconstruction

Identifiers

PMID36964560
PMCPMC10039582

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