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Record W2034415322 · doi:10.1118/1.2829871

A needle guidance system for biopsy and therapy using two-dimensional ultrasound

2008· article· en· W2034415322 on OpenAlexaff
Nathan Bluvol, Anat Kornecki, David C. Del Rey Fernández, Dónal B. Downey, Aaron Fenster

Bibliographic record

VenueMedical Physics · 2008
Typearticle
Languageen
FieldComputer Science
TopicAI in cancer detection
Canadian institutionsLondon Health Sciences CentreRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsImaging phantomBiopsyUltrasoundBreast biopsyNeedle biopsyMammographyComputer scienceRadiologyMedicineBreast cancerBiomedical engineeringMedical physicsCancer

Abstract

fetched live from OpenAlex

Image-guided needle biopsies are currently used to provide a definitive diagnosis of breast cancer; however, difficulties in tumor targeting exist as the ultrasound (US) scan plane and biopsy needle must remain coplanar throughout the procedure to display the actual needle tip position. The additional time associated with aligning and maintaining this coplanar relationship results in increased patient discomfort. Biopsy procedural efficiency is further hindered since needle pathway interpretation is often difficult, especially for needle insertions at large depths that usually require multiple reinsertions. The authors developed a system that would increase the speed and accuracy of current breast biopsy procedures using readily available two-dimensional (2D) US technology. This system is composed of a passive articulated mechanical arm that attaches to a 2D US transducer. The arm is connected to a computer through custom electronics and software, which were developed as an interface for tracking the positioning of the mechanical components in real time. The arm couples to the biopsy needle and provides visual guidance for the physician performing the procedure in the form of a real-time projected needle pathway overlay on an US image of the breast. An agar test phantom, with stainless steel targets interspersed randomly throughout, was used to validate needle trajectory positioning accuracy. The biopsy needle was guided by both the software and hardware components to the targets. The phantom, with the needle inserted and device decoupled, was placed in an x-ray stereotactic mammography (SM) machine. The needle trajectory and bead target locations were determined in three dimensions from the SM images. Results indicated a mean needle trajectory accuracy error of 0.75 +/- 0.42 mm. This is adequate to sample lesions that are < 2 mm in diameter. Chicken tissue test phantoms were used to compare core needle biopsy procedure times between experienced radiologists and inexperienced resident radiologists using free-hand US and the needle guidance system. Cylindrical polyvinyl alcohol cryogel lesions, colored blue, were embedded in chicken tissue. Radiologists identified the lesions, visible as hypoechoic masses in the US images, and performed biopsy using a 14-gauge needle. Procedure times were compared based on experience and the technique performed. Using a pair-wise t test, lower biopsy procedure times were observed when using the guidance system versus the free-hand technique (t = 12.59, p < 0.001). The authors believe that with this improved biopsy guidance they will be able to reduce the "false negative" rate of biopsies, especially in the hands of less experienced physicians.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.863
Threshold uncertainty score0.354

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 head0.037
GPT teacher head0.281
Teacher spread0.244 · 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 designSimulation or modeling
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

Citations27
Published2008
Admission routes1
Has abstractyes

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