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Record W2906061451 · doi:10.1109/jtehm.2018.2889496

Pre-Clinical Translation of Second Harmonic Microscopy of Meniscal and Articular Cartilage Using a Prototype Nonlinear Microendoscope

2018· article· en· W2906061451 on OpenAlexafffund
Stephen J. Baskey, Marco Andreana, Eric Lanteigne, Andrew Ridsdale, Albert Stolow, Mark E. Schweitzer

Bibliographic record

VenueIEEE Journal of Translational Engineering in Health and Medicine · 2018
Typearticle
Languageen
FieldMedicine
TopicOsteoarthritis Treatment and Mechanisms
Canadian institutionsNational Research Council CanadaUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Air ForceGeneral Electric
KeywordsFibrocartilageBiomedical engineeringOsteoarthritisCartilageMaterials scienceMeniscusMicroscopyHyaline cartilageLaserType II collagenComputer scienceAnatomyOpticsArticular cartilagePathologyMedicinePhysics

Abstract

fetched live from OpenAlex

Previous studies using nonlinear microscopy have demonstrated that osteoarthritis (OA) is characterized by the gradual replacement of Type II collagen with Type I collagen. The objective of this study was to develop a prototype nonlinear laser scanning microendoscope capable of resolving the structural differences of collagen in various orthopaedically relevant cartilaginous surfaces. The current prototype developed a miniaturized femtosecond laser scanning instrument, mounted on an articulated positioning system, capable of both conventional arthroscopy and second-harmonic laser-scanning microscopy. Its optical system includes a multi-resolution optical system using a gradient index objective lens and a customized multi-purpose fiber optic sheath to maximize the collection of backscattered photons or provide joint capsule illumination. The stability and suitability of the prototype arthroscope to approach and image cartilage were evaluated through preliminary testing on fresh, minimally processed, and partially intact porcine knee joints. Image quality was sufficient to distinguish between hyaline cartilage and fibrocartilage through unique Type I and Type II collagen-specific characteristics. Imaging the meniscus revealed that the system was able to visualize differences in the collagen arrangement between the superficial and lamellar layers. Such detailed <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in vivo</i> imaging of the cartilage surfaces could obviate the need to perform biopsies for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ex vivo</i> histological analysis in the future, and provide an alternative to conventional external imaging to characterize and diagnose progressive and degenerative cartilage diseases such as OA. Moreover, this system is readily customizable and may provide a suitable and modular platform for developing additional tools utilizing femtosecond lasers for tissue cutting within the familiar confines of two or three portal arthroscopy techniques.

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)0.001
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 score0.251
Threshold uncertainty score0.376

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.037
GPT teacher head0.352
Teacher spread0.315 · 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

Citations16
Published2018
Admission routes2
Has abstractyes

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