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Record W2024447835 · doi:10.2214/ajr.13.11693

Diagnostic Performance of Quantitative Shear Wave Elastography in the Evaluation of Solid Breast Masses: Determination of the Most Discriminatory Parameter

2014· article· en· W2024447835 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAmerican Journal of Roentgenology · 2014
Typearticle
Languageen
FieldMedicine
TopicUltrasound Imaging and Elastography
Canadian institutionsSunnybrook HospitalUniversity Health Network
Fundersnot available
KeywordsMedicineElastographyShear (geology)RadiologyUltrasoundComposite material

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this article is to assess the diagnostic performance of quantitative shear wave elastography in the evaluation of solid breast masses and to determine the most discriminatory parameter. SUBJECTS AND METHODS: B-mode ultrasound and shear wave elastography were performed before core biopsy of 123 masses in 112 women. The diagnostic performance of ultrasound and quantitative shear wave elastography parameters (mean elasticity, maximum elasticity, and elasticity ratio) were compared. The added effect of shear wave elastography on the performance of ultrasound was determined. RESULTS: The mean elasticity, maximum elasticity, and elasticity ratio were 24.8 kPa, 30.3 kPa, and 1.90, respectively, for 79 benign masses and 130.7 kPa, 154.9 kPa, and 11.52, respectively, for 44 malignant masses (p < 0.001). The optimal cutoff value for each parameter was determined to be 42.5 kPa, 46.7 kPa, and 3.56, respectively. The AUC of each shear wave elastography parameter was higher than that of ultrasound (p < 0.001); the AUC value for the elasticity ratio (0.943) was the highest. By adding shear wave elastography parameters to the evaluation of BI-RADS category 4a masses, about 90% of masses could be downgraded to BI-RADS category 3. The numbers of downgraded masses were 40 of 44 (91%) for mean elasticity, 39 of 44 (89%) for maximum elasticity, and 42 of 44 (95%) for elasticity ratio. The numbers of correctly downgraded masses were 39 of 40 (98%) for mean elasticity, 38 of 39 (97%) for maximum elasticity, and 41 of 42 (98%) for elasticity ratio. There was improvement in the diagnostic performance of ultrasound of mass assessment with shear wave elastography parameters added to BI-RADS category 4a masses compared with ultrasound alone. Combined ultrasound and elasticity ratio had the highest improvement, from 35.44% to 87.34% for specificity, from 45.74% to 80.77% for positive predictive value, and from 57.72% to 90.24% for accuracy (p < 0.0001). The AUC of combined ultrasound and elasticity ratio (0.914) was the highest compared with the other combined parameters. CONCLUSION: There was a statistically significant difference in the values of the quantitative shear wave elastography parameters of benign and malignant solid breast masses. By adding shear wave elastography parameters to BI-RADS category 4a masses, we found that about 90% of them could be correctly downgraded to BI-RADS category 3, thereby avoiding biopsy. Elasticity ratio (cutoff, 3.56) appeared to be the most discriminatory parameter.

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.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.137
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.019
GPT teacher head0.297
Teacher spread0.277 · 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