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Record W6902392117 · doi:10.6084/m9.figshare.c.5699759

Revisiting left atrial volumetry by magnetic resonance imaging: the role of atrial shape and 3D angle between left ventricular and left atrial axis

2021· other· en· W6902392117 on OpenAlexaboutno aff

Bibliographic record

VenueFigshare · 2021
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBiplaneSphericityShort axisMagnetic resonance imagingLong axisStroke volumeOrientation (vector space)Ventricular volumeIntraclass correlation

Abstract

fetched live from OpenAlex

Abstract Background Accurate measurement of left atrial (LA) volumes is needed in cardiac diagnostics and the follow up of heart and valvular diseases. Geometrical assumptions with 2D methods for LA volume estimation contribute to volume misestimation. In this study, we test agreement of 3D and 2D methods of LA volume detection and explore contribution of 3D LA axis orientation and LA shape in introducing error in 2D methods by cardiovascular magnetic resonance imaging. Methods 30 patients with prior first-ever ischemic stroke and no known heart disease, and 30 healthy controls were enrolled (age 18–49) in a substudy of a prospective case–control study. All study subjects underwent cardiac magnetic resonance imaging and were pooled for this methodological study. LA volumes were calculated by biplane area-length method from both conventional long axis (LAVAL-LV) and LA long axis-oriented images (LAVAL-LA) and were compared to 3D segmented LA volume (LAVSAX) to assess accuracy of volume detection. 3D orientation of LA long axis to left ventricular (LV) long axis and to four-chamber plane were determined, and LA 3D sphericity indices were calculated to assess sources of error in LA volume calculation. Shapiro–Wilk test, Bland–Altman analysis, intraclass and Pearson correlation, and Spearman’s rho were used for statistical analysis. Results Biases were − 9.9 mL (− 12.5 to − 7.2) for LAVAL-LV and 13.4 (10.0–16.9) for LAVAL-LA [mean difference to LAVSAX (95% confidence interval)]. End-diastolic LA long axis 3D deviation angle to LV long axis was 28.3 ± 6.2° [mean ± SD] and LA long axis 3D rotation angle to four-chamber plane 20.5 ± 18.0°. 3D orientation of LA axis or 3D sphericity were not correlated to error in LA volume calculation. Conclusions Calculated LA volume accuracy did not improve by using LA long axis-oriented images for volume calculation in comparison to conventional method. We present novel data on LA axis orientation and a novel metric of LA sphericity and conclude that these measures cannot be utilized to assess error in LA volume calculation. Trial registration Main study Searching for Explanations for Cryptogenic Stroke in the Young: Revealing the Etiology, Triggers, and Outcome (SECRETO; NCT01934725) has been registered previously.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.808
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
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.4000.000

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 head0.010
GPT teacher head0.208
Teacher spread0.198 · 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.

Study designNot applicable
Domainnot available
GenreReview

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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