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Record W4399268305 · doi:10.1186/s42490-024-00079-9

A handheld device for intra-cavity and ex vivo fluorescence imaging of breast conserving surgery margins with 5-aminolevulinic acid

2024· article· en· W4399268305 on OpenAlexafffund
Christopher Gibson, Shirley C. Wang, Arcturus Phoon, Nayana Thalanki Anantha, Kathryn Ottolino‐Perry, Stephen Petropoulos, Vasanth Subramanian, Anam Shahid, Cristiana O’Brien, Steven Carcone, Suzanne Chung, Teresa Tsui, Viktor Son, Mayleen Sukhram, Fannong Meng, Susan J. Done, Alexandra Easson, Tulin Cil, Michael Reedijk, Wey L. Leong, Ralph S. DaCosta

Bibliographic record

VenueBMC Biomedical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoCanada Research ChairsUniversity Health Network
FundersCanadian Institutes of Health Research
KeywordsEx vivoMedicineMobile deviceBiomedical engineeringBreast-conserving surgeryFluorescenceIn vivoSurgeryMaterials scienceOpticsMastectomyBreast cancerInternal medicineComputer scienceBiologyWorld Wide WebPhysicsCancer

Abstract

fetched live from OpenAlex

Abstract Background Visualization of cancer during breast conserving surgery (BCS) remains challenging; the BCS reoperation rate is reported to be 20-70% of patients. An urgent clinical need exists for real-time intraoperative visualization of breast carcinomas during BCS. We previously demonstrated the ability of a prototype imaging device to identify breast carcinoma in excised surgical specimens following 5-aminolevulinic acid (5-ALA) administration. However, this prototype device was not designed to image the surgical cavity for remaining carcinoma after the excised lumpectomy specimen is removed. A new handheld fluorescence (FL) imaging prototype device, designed to image both excised specimens and within the surgical cavity, was assessed in a clinical trial to evaluate its clinical utility for first-in-human, real-time intraoperative imaging during index BCS. Results The imaging device combines consumer-grade imaging sensory technology with miniature light-emitting diodes (LEDs) and multiband optical filtering to capture high-resolution white light (WL) and FL digital images and videos. The technology allows for visualization of protoporphyrin IX (PpIX), which fluoresces red when excited by violet-blue light. To date, $$n = 17$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>n</mml:mi> <mml:mo>=</mml:mo> <mml:mn>17</mml:mn> </mml:mrow> </mml:math> patients have received $$20\frac{\text {mg}}{\textrm{kg}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mn>20</mml:mn> <mml:mfrac> <mml:mtext>mg</mml:mtext> <mml:mtext>kg</mml:mtext> </mml:mfrac> </mml:mrow> </mml:math> bodyweight (BW) 5-ALA orally 2-4 h before imaging to facilitate the accumulation of PpIX within tumour cells. Tissue types were identified based on their colour appearance. Breast tumours in sectioned lumpectomies appeared red, which contrasted against the green connective tissues and orange-brown adipose tissues. In addition, ductal carcinoma in situ (DCIS) that was missed during intraoperative standard of care was identified at the surgical margin at &lt;1 mm depth. In addition, artifacts due to the surgical drape, illumination, and blood within the surgical cavity were discovered. Conclusions This study has demonstrated the detection of a grossly occult positive margin intraoperatively. Artifacts from imaging within the surgical cavity have been identified, and potential mitigations have been proposed. Trial Registration Identifier: (Trial start date is September 2010. It was registered to ClinicalTrials.gov retrospectively on April 23, 2013, then later updated on April 9, 2020, to reflect the introduction of the new imaging device.)

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.991

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 head0.010
GPT teacher head0.209
Teacher spread0.198 · 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 designBench or experimental
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

Citations3
Published2024
Admission routes2
Has abstractyes

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