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Record W2512385345

Respiratory gating and phase-matched attenuation correction improves uniformity of regional myocardial blood flow estimates during hypercapnea-induced stress imaging with dynamic rubidium-82 PET

2016· article· en· W2512385345 on OpenAlexaff
Colin Jones, Chad Hunter, Terrence D. Ruddy, Ran Klein, Robert A. deKemp

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicMedical Imaging Techniques and Applications
Canadian institutionsOttawa Heart InstituteOttawa HospitalMontreal Heart InstituteUniversity of Ottawa
Fundersnot available
KeywordsExpirationBlood flowNuclear medicineCorrection for attenuationHypercapniaPerfusionMedicineBiomedical engineeringAnesthesiaRespiratory systemInternal medicinePositron emission tomography
DOInot available

Abstract

fetched live from OpenAlex

1960 Objectives The use of exogenous CO2 inhalation (hypercapnea) has been proposed as an alternative method to induce hyperemia for stress myocardial perfusion imaging (MPI). Breathing rate and tidal volume are increased dramatically in response to CO2, inducing a mismatch between PET and CT attenuation correction scans. Our objective is to determine the effect of respiratory gating and phase-matched attenuation correction on the uniformity of regional myocardial blood flow quantification during hypercapnia-induced stress imaging with dynamic rubidium-82 PET. Methods List-mode data from rest/ hypercapnea-stress scans in healthy normal subjects (N=7) were gated into four phases. Dynamic images from each phase, as well as the full ungated series, were reconstructed and analyzed for blood flow quantification using FlowQuant. Polar-map uniformity was measured as SD/mean of the 460 sectors, and differences between the four phases were evaluated using one-way ANOVA and post-hoc t-testing. Two-factor ANOVA was used to evaluate the regional variation in blood flow values using a 5-segment model. Results No significant differences in blood flow uniformity were found between respiratory phases at rest (p=0.75). For stress scans, significant differences in uniformity were found between the phases (p = 0.017). Post-hoc testing revealed no difference between the two inspiration phases, nor between the two expiration phases, but there were differences between the inspiration and expiration phases (46% vs 21%; p=0.002). Segmental ANOVA showed no effect due to inspiration vs expiration (p=0.49), but highly significant effects between segments (p Conclusions Respiratory gating and phase-matched attenuation correction decreases the variability of regional blood flow estimates, improving uniformity in healthy normals during hypercapnea -induced stress imaging with dynamic rubidium-82 PET.

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)0.001
metaresearch head score (Gemma)0.001
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0010.000

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 head0.015
GPT teacher head0.290
Teacher spread0.275 · 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".

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Citations0
Published2016
Admission routes1
Has abstractyes

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