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Record W4413450137 · doi:10.1016/j.soi.2025.100184

A single arm, prospective, open label, multicenter study assessing the safety and effectiveness of SPY AGENT GREEN and SPY fluorescence imaging systems in the visualization of lymphatic vessels and lymph nodes during lymphatic mapping and sentinel lymph node biopsy in subjects with breast cancer

2025· article· en· W4413450137 on OpenAlexafffund
David C. Weintritt, Beth‐Ann Lesnikoski, Michelle E. Goecke, Christine Desbiens, Allison A. DiPasquale, Sommer R. Gunia

Bibliographic record

VenueSurgical Oncology Insight · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBreast Cancer Treatment Studies
Canadian institutionsHôpital du Saint-SacrementFraser Health
FundersHealth CanadaStryker
KeywordsLymphVisualizationMedicineLymphatic systemRadiologyPathologyComputer scienceData mining

Abstract

fetched live from OpenAlex

Background Sentinel Lymph Node Biopsy (SLNB) using technetium-99m (Tc-99m) is standard for axillary staging in early-stage breast cancer. Indocyanine green (ICG) is an alternative method with meta-analyses reporting clinical effectiveness of ICG comparable or superior to Tc-99m. Methods This prospective study evaluated the safety and effectiveness of SPY Portable Handheld Imaging System (SPY-PHI)/SPY AGENT GREEN (SAG) in the identification of histology confirmed lymph nodes (LN). Patients were administered Tc-99m per institutional protocol and SAG intradermally in the peri-areolar area. LNs were subsequently identified/excised under intraoperative fluorescence, then assessed for radioactivity using a gamma probe. Effectiveness of nodal detection was determined by comparing the proportion of LNs identified by SAG to the proportion identified by Tc-99m. Effectiveness of per subject LN identification, intraoperative fluorescence visualization of lymphatic vessels, and safety of intradermal injection of SAG were also evaluated. Results One hundred fifty-one subjects completed the study and follow-up. Lymphatic mapping/SLNB were unsuccessful with either technique in 3 subjects, resulting in 148 evaluable subjects. SPY-PHI/SAG identified 89% (360/406) of LNs while Tc-99m identified 66% (266/406). For both methods the per patient identification rate was 98% (145/148). These results demonstrate SPY-PHI/SAG was non-inferior to Tc-99m (p-value <0.0001). SPY-PHI/SAG provided visualization of lymphatic flow confirming mapping and aiding in identification of 99% (357/360) of SPY-PHI/SAG identified LNs. Forty metastatic LNs were confirmed in 29 subjects. At least one metastatic LN was detected in 93% of these subjects using SPY-PHI/SAG versus 83% using Tc-99m. There were no adverse events related to SPY-PHI/SAG. Conclusions SPY-PHI/SAG are an effective modality for visualizing and identifying lymphatic nodes and vessels in early-stage breast cancer.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.014
GPT teacher head0.312
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNon-randomized trial
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 abstractno

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