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LIGHT MICROSCOPY EVALUATION OF TENDINOSIS: THE BONAR SCORE REVISITED

2013· article· en· W2134082870 on OpenAlexaff
A. Fearon, Jane E. Dahlstrom, Jane Twin, Jill Cook, Alex Scott

Bibliographic record

VenueBritish Journal of Sports Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicTendon Structure and Treatment
Canadian institutionsUniversity of British Columbia Hospital
Fundersnot available
KeywordsVascularityTendinosisMedicineTendinopathyTendonGrading (engineering)PathologicalHypervascularityRadiologyPathologyBiology

Abstract

fetched live from OpenAlex

Introduction Grading the extent of degenerative change in tendon is an important aspect of tendinopathy research. The Bonar score1 has been widely used for this purpose since 2004. This method provides valuable guidelines for tendinosis assessment but is not without limitations, and many groups have made modifications to the original method.2 It is common for researchers to evaluate the area of highest morphological change, however the method of defining this area, and the implications of using different methods, have not been documented. In this study, we asked whether selecting the level of greatest morphological change using different aspects of the score (degree of collagen disruption, the level of cell morphological change, or the degree of vascularity) would lead to similar or different Bonar scores. Methods Human tendon from people undergoing gluteal tendon reconstruction or hip arthroplasty was assessed in each part of this study. Two researchers experienced in using the Bonar score systematically reviewed each domain of the Bonar score while viewing tendon sections. By consensus, the appropriate level of magnification used for each domain was determined. The need for polarisation was also reviewed. Additional clauses of pathological acellularity and avascularity were added to the third. Hyper and hypo cellularity were defined, and, modification of the vascularity and cellularity scores were confirmed. Two researchers, with a third to resolve disputes evaluated 32 sections of tendon. Each domain within the Bonar score was evaluated in each of the following areas: the area of worst collagen disruption; the area scoring the highest vascularity; and thirdly the area scoring the highest tenocyte morphology change. Results A total of 84 areas of tendon were evaluated. The total Bonar score was highest in the areas of most cellular morphological (CM) changes (mean, (SD) 14.4 (1.50)) then highest collagen disruption (CD: 13.0 (2.56)), and lowest for the area of vascularity (VS) (11.6 (1.68), (regression: CD vs TM p=0.008, CM vs VS p<0.001, CD vs VS p=0.013). Our review of this method found that collagen disruption should be assessed over the entire section using ×100 total magnification with polarisation. The field of view (FoV) with the highest level of disruption should be further evaluated to provide the section score. Conclusions and recommendations This paper provides clarification of, and recommendations on the use of the commonly used Bonar score. Cellularity is best assessed using one FoV×100. In human tissue, hypo-cellularity ≤20 nuclei per HPF, Hyper-cellularity ≥30 nuclei per HPF. Normal=20 to 30 nuclei per HPF. Cell morphology was best assessed at ×200 magnification, over four FoV. Vascularity should be assessed at ×400 magnification, up to 10 FoV, and Ground substance was best assessed at ×100. When evaluating a FoV, a 20% rule should be applied. That is, if 20% of the tissue can be scored at the highest level, this score is applied to the entire FoV. To provide accurate/reliable assessment, tendon sections should be viewed by a minimum, of two researchers, simultaneously, but independently with the final score decided either by consensus, or a third assessor. These results suggest that using the area of maximum tenocyte morphological changes provides a justifiable score that is representative of the worst degree of tendinosis in the specimen. We believe our modified Bonar score provides clearer definitions of each grade and also specifies the level of magnification for each domain, producing a more robust assessment tool. Further evaluation of the Bonar score's applicability to commonly used tendinopathy laboratory models should be carried out.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0070.003
Science and technology studies0.0010.003
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.294
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2013
Admission routes1
Has abstractyes

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