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Record W3164886436

Respiratory motion correction reduces differences between immediate and delayed SPECT myocardial perfusion images

2021· article· en· W3164886436 on OpenAlexaff
Mahdi Zeghal, Juliana Brenande de Oliveira Brito, Clare Carey, Katie Dubie, Lewis Han, Farhan Mahmood, Gary R. Small, Terrence D. Ruddy, R. Glenn Wells

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMyocardial perfusion imagingMedicinePerfusionNuclear medicineVentricleBasal (medicine)Perfusion scanningCardiac PETRadiologyCardiologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

1659 Background: Current ASNC guidelines for SPECT myocardial perfusion imaging (MPI) recommend a 30-45 minute delay between radiotracer injection and image acquisition to reduce the impact of extra-cardiac interference. During acquisition, respiratory motion contributes significantly to motion-blurring of images and can increase extra-cardiac interference. This study assessed the extent by which differences between images acquired starting 5 minutes after injection (immediate) and at ~30-45 minutes post-injection (delayed) could be reduced by data-driven respiratory motion correction (RMC). Methods: SPECT MPI studies were retrospectively evaluated and processed using data-driven RMC software for a sample of 56 patients acquired using a pinhole cardiac camera. Immediate and delayed images without (NoMC) and with RMC were assessed using standard clinical software and the presence of extracardiac uptake was noted. Normalized myocardial perfusion value differences between delayed and immediate time-points were computed for each myocardial segment, based on a 17-segment left ventricle (LV) model. Using a Wilcoxon signed-rank test, perfusion value differences for NoMC data were evaluated in both stress and rest scans, as well as differences between immediate and delayed values derived from NoMC and RMC data. Results: Extracardiac activity was observed in g 70% of SPECT MPI studies, more than 60% of which had visually apparent differences between immediate and delayed images. With NoMC, differences between immediate and delayed images were significant in five basal segments (P l 0.001) and the five apical segments (P l 0.0001). RMC significantly reduced the difference between immediate and delayed images in some of the segments. For stress scans, significant decreases were noted in the mid anteroseptal (P l 0.001), apical lateral (P l 0.0001), and apex segments (P l 0.0001). For rest, there were significant decreases in the apical lateral (P =0.0004) and apical septal segments (P = 0.0001). Conclusions: A substantial number of SPECT MPI studies present with extracardiac activity which is often markedly reduced in delayed images compared to immediate images. In NoMC SPECT imaging, discrepancies between immediate and delayed image data are most significant in basal and apical segments. Current results demonstrate that RMC can reduce the change in measured myocardial uptake between immediate and delayed imaging in most apical segments.

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)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
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 head0.026
GPT teacher head0.309
Teacher spread0.283 · 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 designObservational
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
Published2021
Admission routes1
Has abstractyes

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