Evidence map›Paper›PMID 34324394›Full record

ArticleDento maxillo facial radiology2022

The challenge of applying digital image processing software on intraoral radiographs for osteoporosis risk assessment.

Joanna Gullberg, Ayman Al-Okshi, Dalia Homar Asan, Anita Zainea, Daniel Sundh, Mattias Lorentzon, Christina Lindh

Open access · bronzeAbstract read
In one paragraph

Article in Dento maxillo facial radiology, 2022. 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
0.7field-weighted citation impact, top 34% 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, 5 citations in OpenAlex.

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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

7 authors at 4 institutions in 3 countries.

Joanna GullbergFaculty of Odontology, Malmö University, Malmö, Sweden.ORCID 0000-0002-1895-3366
Ayman Al-OkshiDepartment of Oral Medicine and Radiology, Faculty of Dentistry, Sebha University, Sebha, Libya.
Dalia Homar AsanFaculty of Odontology, Malmö University, Malmö, Sweden.
Anita ZaineaFaculty of Odontology, Malmö University, Malmö, Sweden.
Daniel SundhSahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Mattias LorentzonSahlgrenska Osteoporosis Centre, Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, University of Gothenburg, Gothenburg, Sweden.
Christina LindhFaculty of Odontology, Malmö University, Malmö, Sweden.
Malmö University · SESahlgrenska University Hospital · SESebha University · LYUniversity of Gothenburg · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesThe purpose of this study was to evaluate rater agreement and the accuracy of a semi-automated software and its fully automated tool for osteoporosis risk assessment in intraoral radiographs.

methodsA total of 567 intraoral radiographs was selected retrospectively from women aged 75-80 years participating in a large population-based study (SUPERB) based in Gothenburg, Sweden. Five raters assessed participants' risk of osteoporosis in the intraoral radiographs using a semi-automated software. Assessments were repeated after 4 weeks on 121 radiographs (20%) randomly selected from the original 567. Radiographs were also assessed by the softwares' fully automated tool for analysis.

resultsOverall interrater agreement for the five raters was 0.37 (95% CI 0.32-0.41), and for the five raters with the fully automated tool included as 'sixth rater' the overall Kappa was 0.34 (0.30-0.38). Intrarater agreement varied from moderate to substantial according to the Landis and Koch interpretation scale. Diagnostic accuracy was calculated in relation to reference standard for osteoporosis diagnosis which is T-score values for spine, total hip and femoral neck and presented in form of sensitivities, specificities, predictive values, likelihood ratios and odds ratios. All raters' mean sensitivity, including the fully automated tool, was 40,4% (range 14,3%-57,6%). Corresponding values for specificity was 69,5% (range 59,7%-90,4%). The diagnostic odds ratios ranged between 1 and 2.7.

conclusionThe low diagnostic odds ratio and agreement between raters in osteoporosis risk assessment using the software for analysis of the trabecular pattern in intraoral radiographs shows that more work needs to be done to optimise the automation of trabecular pattern analysis in intraoral radiographs.

Indexed as

OsteoporosisAgedAged, 80 and overFemaleHumansImage Processing, Computer-AssistedReproducibility of ResultsRetrospective StudiesRisk AssessmentSoftwareComputer-Assisted Image AnalysisData AccuracyDental Digital RadiographyOsteoporosisRisk assessment

Identifiers

PMID34324394
PMCPMC8693323
OpenAlexW3185418398

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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.