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Record W2324346909 · doi:10.1177/016173460702900303

Investigation of Micro-Ultrasound for Microvessel Imaging in a Model of Chronic Total Occlusion

2007· article· en· W2324346909 on OpenAlexafffund
Amandeep S. Thind, General Leung, Nigel R. Munce, John Graham, Kevan Anderson, Alexander Dick, Bradley H. Strauss, Graham A. Wright, F. Stuart Foster

Bibliographic record

VenueUltrasonic Imaging · 2007
Typearticle
Languageen
FieldMedicine
TopicCoronary Interventions and Diagnostics
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
FundersNational Cancer InstituteCanadian Institutes of Health Research
KeywordsUltrasoundMicrovesselUltrasound imagingMedicineRadiologyOcclusionBiomedical engineeringCardiologyInternal medicineAngiogenesis

Abstract

fetched live from OpenAlex

The aim of the current study is to investigate the ability of micro-ultrasound (microUS) to identify microvasculature in CTOs in vivo. Results are compared with MRI studies. CTOs were developed in nine porcine superficial femoral arteries (SFA) by percutaneous insertion of a dissolvable polymer plug. This model is characterized by acute thrombosis that later organizes into a fibrotic CTO containing abundant microchannels. 3D microUS images with Power Doppler (PD) overlays from the arteries were acquired at two timepoints: one and eight weeks after placement ofthe polymerplug. Phase contrast MRI and contrast enhanced MRI was also performed. Imaging was performed transcutaneously. Microvessels were identified in vivo in six of eight CTOs using microUS, and in three of seven CTO vessels with MRI, compared with five of seven seen histologically. PW Doppler profiles showed pulsatile blood velocities of approximately 2 cm/s. Intraluminal microvessels within CTOs can be consistently identified by 3D microUS. This technique appears to be more sensitive than MRI. MicroUS may play a role in guiding CTO interventions.

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 score0.104
Threshold uncertainty score0.595

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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

Citations6
Published2007
Admission routes2
Has abstractyes

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