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Record W2010265989 · doi:10.1097/rli.0b013e31823fd42b

Accuracy of Dynamic Computed Tomography Adenosine Stress Myocardial Perfusion Imaging in Estimating Myocardial Blood Flow at Various Degrees of Coronary Artery Stenosis Using a Porcine Animal Model

2011· article· en· W2010265989 on OpenAlex
Fabian Bamberg, Rabea Hinkel, Florian Schwarz, T. Sandner, Elisabeth Baloch, Roy Marcus, Alexander Becker, Christian Kupatt, Bernd J. Wintersperger, Thorsten R. C. Johnson, Daniel Theisen, Ernst Klotz, Maximilian F. Reiser, Konstantin Nikolaou

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInvestigative Radiology · 2011
Typearticle
Languageen
FieldMedicine
TopicCardiac Imaging and Diagnostics
Canadian institutionsUniversity of Toronto
FundersSanofi
KeywordsMedicineBlood flowCardiologyPerfusionInternal medicineMyocardial perfusion imagingStenosisPerfusion scanningCoronary circulationArteryComputed tomographyRadiology

Abstract

fetched live from OpenAlex

OBJECTIVE: To determine the accuracy of computed tomography (CT) dynamic stress myocardial perfusion imaging to estimate myocardial blood flow (MBF) in a porcine animal model with variable degrees of induced coronary artery stenosis in comparison with microsphere-derived MBF. METHODS AND MATERIALS: Seven domestic pigs (36 ± 4 kg) received stents (confirmed 3.0 mm diameter) in the left anterior descending coronary artery distal to first diagonal branch. A balloon catheter was placed within the stent and inflated to various degrees to obtain a defined luminal narrowing (50% and 75% diameter stenosis) as confirmed by intra-arterial flow wire measurement. All models underwent adenosine-mediated (140 μg/kg/min) dynamic stress and rest myocardial perfusion CT imaging using a dual-source CT scanner (shuttle-mode with 100 kV/300 mAs, 20 mL iopromide) with prospective acquisitions every second heartbeat for 30 seconds. CT-estimated MBF (MBFCT) was calculated using a model-based parametric deconvolution method and correlated to that of fluorescent microspheres (MBFmic) injected at each perfusion state. RESULTS: All study procedures were performed without complications, and all animals completed the study protocol. Among 448 myocardial segments, 31 (7%) were considered nonevaluable because of motion artifacts. With stress, MBFCT increased significantly (1.10 ± 0.25 vs. 0.80 ± 0.28 mL/g/min, P < 0.001; at stress and rest, respectively) in all myocardial segments and correlated with MBFmic (r = 0.67, P < 0.001). MBFCT overestimated MBFmic, independently of adenosine-stress and degree of coronary stenosis (β = 2.3, 95% confidence interval: 1.81-2.79 mL/g/min, P < 0.001). Although there were no differences in MBFCT between 50% and 75% coronary stenosis at rest (0.01 ± 0.08 mL/g/min, P = 0.86), MBFCT was significantly lower at 75% than at 50% under stress conditions (0.53 ± 0.19 vs. 0.71 ± 0.24 mL/g/min, P = 0.002). CONCLUSIONS: CT-derived MBF measurements at rest and stress with varying degrees of coronary stenosis show a valid difference but an underestimated correlation with microsphere-derived MBF in a porcine animal model.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.456
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
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 head0.030
GPT teacher head0.265
Teacher spread0.235 · 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