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Record W27758986

The Use of Dynamic Optical Imaging in Breast Cancer Detection

2010· article· en· W27758986 on OpenAlexfundno aff
Kyle Wilson

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicOptical Imaging and Spectroscopy Techniques
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBreast cancerMedicineCancerComputer scienceComputer visionRadiologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Breast cancer has affected many women around the world throughout history. In order to recognize and treat the early signs of breast cancer, obtaining high quality images is crucial. A variety of imaging modalities are available for use in breast imaging, including conventional mammography and newer optical imaging techniques. One such optical imaging system is the ComfortScan™, which uses red light to image the breast and was the focus of this study. The objectives include investigating whether performing a large scale clinical trial with the ComfortScan TM would be warranted to further patient care and diagnostics for breast imaging, and determining whether the ComfortScan ™ would achieve better correlation to biopsy than mammography alone. An additional goal was to investigate whether the ComfortScan TM system would be beneficial as a mainstream method for a radiologist to diagnose breast cancer risk. The preliminary study with 19 patients demonstrated that there was no difference in diagnostic information between the near-infrared (NIR) image and mammography (p>O.OS). Anecdotal evidence suggests cases where mammography disagreed with biopsy, whereas ComfortScan TM agreed, though these were not statistically significant. Based on these encouraging results, a large scale clinical trial was launched to investigate the potential of widespread use of the ComfortScan ™. The large scale trial included 126 NIR images and found difference in diagnostic information between NIR and mammography (p The potential of using polyvinyl alcohol cryogel (PVA-C) as a breast tissue mimic was investigated and PV A -C was then used to validate the mode of action of the ComfortScan TM system. Two experimental methods reported the absorption coefficients and reduced scattering coefficients of PV A-C. Using a double integrating sphere, the values were J.la = 0.012 ± 0.002 mm-1 and J.ls' = 1.5 ± 0.2 mm-1 and using steady-state spatially resolved diffuse reflectance, the values were J.la = 0.017 ± 0.005 mm-1 and J.ls' = 1.3 ± 0.2 mm-1 at 640 nm. These values are comparable to typical absorption coefficients for tissue reported by others. The mode of action suggested by DOBI (Dynamic Optical Breast Imaging) Medical for the ComfortScan ™ system is that under compression a malignant tumour will highly attenuate light, due to a partial collapse in the tumourous vasculature, resulting in an increased deoxygenation of blood over time. Using a PV A-C breast mimicking phantom, it was shown that by deoxygenating horse blood in a cavity, there was an increase in the attenuation of 640 nm light as compared with the surrounding phantom material; which suggests that the colour representative of malignancies on the ComfortScan ™ is caused by deoxygenating blood. Further evidence suggests that the ComfortS can TM system is not recognizing a total collapse of the vasculature and subsequent void of blood from the tumour as the trigger for malignant detection. The mode of action suggested by DOBI Medical is supported by our findings.

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)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation 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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.316
Teacher spread0.307 · 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 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

Citations0
Published2010
Admission routes1
Has abstractyes

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