Evidence map›Paper›PMID 31583552›Full record

ArticleAnnals of biomedical engineering2020

Quantifying Subresolution 3D Morphology of Bone with Clinical Computed Tomography.

S S Karhula, M A J Finnilä, S J O Rytky, D M Cooper, J Thevenot, M Valkealahti, K P H Pritzker, M Haapea, A Joukainen, P Lehenkari and 4 more

Abstract read
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In one paragraph

Article in Annals of biomedical engineering, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
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

9 citing papers in PubMed.

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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

14 authors.

S S KarhulaResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland. sakari.karhula@oulu.fi.
M A J FinniläResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
S J O RytkyResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
D M CooperDepartment of Anatomy Physiology and Pharmacology, University of Saskatchewan, Saskatoon, SK, Canada.
J ThevenotResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
M ValkealahtiDepartment of Surgery and Intensive Care, Oulu University Hospital, Oulu, Finland.
K P H PritzkerDepartment of Laboratory Medicine and Pathobiology, Surgery University of Toronto, Toronto, ON, Canada.
M HaapeaResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
A JoukainenDepartment of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland.
P LehenkariMedical Research Center, University of Oulu, Oulu, Finland.
H KrögerDepartment of Orthopaedics, Traumatology and Hand Surgery, Kuopio University Hospital, Kuopio, Finland.
R K KorhonenDepartment of Applied Physics, University of Eastern Finland, Kuopio, Finland.
H J NieminenResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.
S SaarakkalaResearch Unit of Medical Imaging, Physics and Technology, University of Oulu, POB 5000, 90014, Oulu, Finland.

Funding

Academy of Finland 268378Academy of Finland 303786FP7 Ideas: European Research Council 336267
6 · The paper itself

Abstract

The aim of this study was to quantify sub-resolution trabecular bone morphometrics, which are also related to osteoarthritis (OA), from clinical resolution cone beam computed tomography (CBCT). Samples (n = 53) were harvested from human tibiae (N = 4) and femora (N = 7). Grey-level co-occurrence matrix (GLCM) texture and histogram-based parameters were calculated from CBCT imaged trabecular bone data, and compared with the morphometric parameters quantified from micro-computed tomography. As a reference for OA severity, histological sections were subjected to OARSI histopathological grading. GLCM and histogram parameters were correlated to bone morphometrics and OARSI individually. Furthermore, a statistical model of combined GLCM/histogram parameters was generated to estimate the bone morphometrics. Several individual histogram and GLCM parameters had strong associations with various bone morphometrics (|r| > 0.7). The most prominent correlation was observed between the histogram mean and bone volume fraction (r = 0.907). The statistical model combining GLCM and histogram-parameters resulted in even better association with bone volume fraction determined from CBCT data (adjusted R

Indexed as

Bone DensityCone-Beam Computed TomographyX-Ray MicrotomographyCancellous BoneFemaleHumansMaleOsteoarthritisCone beam computed tomographyGrey-level co-occurrence matrixImagingMicro-computed tomographyOsteoarthritisTextural analysis

Identifiers

PMID31583552
PMCPMC6949315

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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.