MétaCan
Menu
Back to cohort
Record W3083561833 · doi:10.1158/1538-7445.am2020-1644

Abstract 1644: Detection and quantification of lymphedema using optical coherence tomography lymphangiography

2020· article· en· W3083561833 on OpenAlexaff
Jennifer Kwan, Valentin Demidov, Blake C. Jones, Wei Shi, Justin Williams, Costel Flueraru, Kenneth W. Yip, Fei‐Fei Liu, I. Alex Vitkin

Bibliographic record

VenueCancer Research · 2020
Typearticle
Languageen
FieldEngineering
TopicOptical Coherence Tomography Applications
Canadian institutionsNational Research Council CanadaPrincess Margaret Cancer CentreUniversity of Toronto
Fundersnot available
KeywordsLymphatic systemLymphedemaMedicineOptical coherence tomographyLymphatic vesselPathologyLymphangiogenesisRadiologyCancerMetastasis

Abstract

fetched live from OpenAlex

Abstract Purpose: Imaging of the lymphatic system is important for monitoring and quantification of the vasculature of tumours and in lymphatic disorders (e.g. lymphedema, an obstruction of the lymphatic system that occurs as a side-effect of cancer treatments such as radiation and/or surgery). Traditional methods of lymphangiography require injection of a contrast agent to visualize the lymphatic system, which may be suboptimal when there is lymphatic obstruction. Thus, there is a need to develop intrinsic-contrast, high-resolution volumetric (3D) non-invasive quantitative in vivo imaging systems for both pre-clinical and potentially clinical use. Methods: An emerging non-invasive 3D imaging technology called optical coherence tomography (OCT) lymphangiography was optimized to visualize lymphatic vasculature and edema within tissues of C57BL/6 mice under normal and surgically-induced lymphedematous conditions. A murine tail lymphedema model was created by micro-surgical obstruction of the superficial and deep lymphatic networks under a dissecting microscope. OCT imaging was validated against fluorescent microscopy, an established but contrast-agent-dependent lymphangiography technique, as well as histology. Fluorescent microscopy was performed with intradermal injection of FITC-dextran followed by imaging with the AxioZoom.V16 Stereo Zoom Microscope. Immunofluorescence staining was performed with an anti-LYVE1 (Lymphatic Vessel Endothelial Receptor 1) antibody. Results: Comparing 3D OCT images and their 2D projections under normal and lymphedematous conditions showed significantly different networks. Quantification analysis revealed increased lymphatic vasculature dilation (~4X in vessel diameters, p<0.01) and increased fluid accumulation (~3X in edematous regions, p<0.05) under lymphedema conditions. Lymphatic vascular dilation and edema were confirmed by fluorescent microscopy and histology. Conclusions: OCT is an emerging non-invasive volumetric imaging modality that can be adapted to visualize lymphatic vasculature within normal and lymphedematous tissues without the use of vascular contrast agents. Furthermore, OCT has the ability to quantify the degree of vessel dilation and edema accumulation. Citation Format: Jennifer Y. Kwan, Valentin Demidov, Blake Jones, Wei Shi, Justin Williams, Costel Flueraru, Kenneth W. Yip, Fei-Fei Liu, Alex Vitkin. Detection and quantification of lymphedema using optical coherence tomography lymphangiography [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1644.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.141
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
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 head0.102
GPT teacher head0.359
Teacher spread0.257 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCancer ResearchSame topicOptical Coherence Tomography ApplicationsFrench-language works237,207