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Record W4412616832 · doi:10.32768/abc.6520237689199

Image-Guided Pre-Operative Magnetic Seed Localization of Breast Lesions: Experience of a Northern Ontario Hospital with the Magnetic Occult Lesion Localization Instrument (MOLLI)

2025· article· en· W4412616832 on OpenAlexaffabout
Zacharie Gagné, Yasmine Sallam, Shaista Riaz, Amr ElNayal

Bibliographic record

VenueArchives of Breast Cancer · 2025
Typearticle
Languageen
FieldComputer Science
TopicAI in cancer detection
Canadian institutionsHealth Sciences NorthNOSM University
Fundersnot available
KeywordsOccultLesionMedicineRadiologyMagnetic resonance imagingPathology

Abstract

fetched live from OpenAlex

Background: Breast cancer remains one of the leading malignancies among Canadian women. Lumpectomies have been increasing in number over total mastectomies due to comparable survival and lower reoperation rates. While wire localization has been the traditional method for the localization of non-palpable breast lesions, it presents logistical and patient comfort challenges. Magnetic localization systems, such as the Magnetic Occult Lesion Localization Instrument (MOLLI), offer an alternative with potential advantages. Methods: A retrospective review was conducted, examining the outcomes of 145 patients who underwent MOLLI seed localization between December 2023 and October 2024. A total of 154 seeds were placed, with localization performed predominantly via sonographic guidance. The primary outcomes were placement success, retrieval rates, margin status of the surgical specimens, and the number of days between seed placement and surgical excision. Results: The mean patient age was 62 years. MOLLI seeds were successfully placed in 100% of cases, with 76% within or adjacent to the lesion. Of the excised lesions, 70.3% were malignant, with a positive margin rate of 17.3%, which was defined as invasive carcinoma or ductal carcinoma in situ (DCIS) being less than 2 mm from the margins. The MOLLI seeds were successfully retrieved in 100% of cases. Conclusion: The MOLLI localization system demonstrated high accuracy and retrieval success, offering a viable alternative to traditional wire localization. The findings suggest MOLLI and other magnetic localizers may improve lesion localization and excision while also improving patient comfort. As this was a retrospective single-center study, further large-scale trials are needed to confirm generalizability.

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.582
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.007
GPT teacher head0.240
Teacher spread0.233 · 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

Citations0
Published2025
Admission routes2
Has abstractyes

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