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Record W2143283199 · doi:10.1109/iembs.2008.4649999

A new lateral guidance device for stereotactic breast biopsy using an add-on unit to an upright mammography system

2008· article· en· W2143283199 on OpenAlexaff
K. Ma, Aaron Fenster, Anat Kornecki, Y. Mundt, Jeff Bax

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicBreast Lesions and Carcinomas
Canadian institutionsSt. Joseph's HospitalRobarts Clinical Trials
Fundersnot available
KeywordsImaging phantomElevation angleComputer scienceBiomedical engineeringFlexibility (engineering)Computer hardwareMedicineRadiologyMathematics

Abstract

fetched live from OpenAlex

Stereotactic breast biopsy (SBB) is the gold standard for noninvasive breast cancer diagnosis. Current systems rely on one of two methods for needle insertion: a vertical-approach (from above the breast compression plate) or a lateral-approach (parallel to the compression plate). While the vertical-approach is more commonly used, it is not feasible in patients with thin breasts (less than 3 cm thickness after compression) or with superficial lesions. We present a novel design of lateral guidance device for SBB which addresses these limitations of the vertical-approach, and provides improvements over existing lateral guidance hardware. This device incorporates spherical linkages to allow two degrees of rotational freedom in the needle trajectory for increased targeting flexibility, as well as an adjustable rigid needle support to minimize needle deflection within the tissue. Needle placement error in SBB experiments is compared using both the new lateral guidance device and a commercial lateral guidance device in agar phantoms. The effect of elevation angle on needle placement accuracy using the new lateral guidance device is also assessed. Finally, a biopsy accuracy experiment is presented using a certified SBB phantom to compare the new design and the commercial lateral guidance device. In these experiments, SBB performed using the new lateral guidance device resulted in improved needle placement error and biopsy accuracy, while increasing targeting flexibility and maintaining procedural workflow.

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)0.000
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 score0.208
Threshold uncertainty score0.730

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.066
GPT teacher head0.305
Teacher spread0.239 · 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

Citations4
Published2008
Admission routes1
Has abstractyes

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