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Record W3165299490 · doi:10.9778/cmajo.20200211

Evaluation of the quality of mammographic breast positioning: a quality improvement study

2021· article· en· W3165299490 on OpenAlexafffundvenueabout
Julie Rouette, Noémie Elfassy, Nathaniel Bouganim, Hui Yin, Nathaniel Lasry, Laurent Azoulay

Bibliographic record

VenueCMAJ Open · 2021
Typearticle
Languageen
FieldMedicine
TopicDigital Radiography and Breast Imaging
Canadian institutionsMcGill UniversityInternational Medias Data Services (Canada)Jewish General HospitalUniversity of Toronto
FundersCanadian Institutes of Health ResearchBiogenPfizerAmgen
KeywordsMammographyMedicineMedical physicsCertificationContext (archaeology)Confidence intervalBreast imagingQuality assurancePopulationBreast cancerEnvironmental healthExternal quality assessmentInternal medicinePathology

Abstract

fetched live from OpenAlex

BACKGROUND: Although there are concerns that inadequate breast positioning in mammographic examinations may lead to cancers being missed, few studies have examined the quality of breast positioning, especially in the Canadian context. Our objective was to assess the quality of breast positioning in mammographic examinations in a Quebec-wide representative sample of technologists. METHODS: This quality improvement study was part of a professional inspection launched by the Ordre des technologues en imagerie médicale, en radio-oncologie et en électrophysiologie médicale du Québec among its members. The inspection was conducted between May and July 2017 on a proportionate stratified random sample of all active technologists certified in mammography in Quebec. Each technologist provided images from 15 consecutive mammographic examinations they performed in the previous 6 months. The quality of positioning was then evaluated by senior technologists using a quality assessment tool specifically developed for this inspection. A technologist was deemed to have failed the professional inspection when at least 7 of the 15 mammographic examinations were scored as critical failures. Proportions were calculated accounting for sampling weights and correction for finite population. RESULTS: Among the 520 technologists certified in mammography in Quebec, 76 technologists (14.6%) were randomly selected for the professional inspection and contributed images from 1127 mammographic examinations. Thirty-eight technologists (weighted percentage 50.3%, 95% confidence interval [CI] 37.6% to 63.0%) failed the professional inspection. Overall, 492 mammographic examinations (43.7%, 95% CI 38.6% to 48.8%) had at least 1 image scored as a critical failure. INTERPRETATION: Half of the technologists performing mammographic examinations in Quebec who participated in this study failed the inspection, and a substantial proportion of their mammographic examinations demonstrated critical failures in breast positioning. Overall, our findings are concordant with those of previous studies and highlight the need for additional investigations assessing the quality of breast positioning in mammographic examinations in other jurisdictions.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.145
Threshold uncertainty score0.272

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.082
GPT teacher head0.405
Teacher spread0.323 · 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 teacher head, 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".

Quick stats

Citations13
Published2021
Admission routes4
Has abstractyes

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