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Record W1874682158 · doi:10.1186/1532-429x-15-s1-p295

Which MRI sequence provides the most accurate estimate of branch pulmonary artery size in children with single ventricle?

2013· article· en· W1874682158 on OpenAlexaff
Edythe Tham, Kimberley Myers, Chodchanok Vijarnsorn, David J. Patton, Michelle Noga

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2013
Typearticle
Languageen
FieldMedicine
TopicCongenital Heart Disease Studies
Canadian institutionsAlberta Children's HospitalStollery Children's Hospital
Fundersnot available
KeywordsMedicineAngiologyVentriclePulmonary arteryCardiologyInternal medicineSequence (biology)Radiology

Abstract

fetched live from OpenAlex

Accurate evaluation of branch pulmonary artery size in children with single ventricle is important for surgical planning and has prognostic implications after Fontan surgery. Various cardiac MRI sequences are employed to evaluate these sometimes hypoplastic pulmonary arteries, which increases imaging time in anesthetised children. The aim of this study was to evaluate which MRI sequence(s) correlate with angiography measurements of pulmonary artery size made at cardiac catheterization in children with single ventricle. Twenty children (age: 21±30 months, weight 10±7kg) with single ventricle who underwent cardiac catheterization with pulmonary angiography, and cardiac MRI (Siemens 1.5T) within 43±29 days were included at any surgical stage. Pulmonary arteries were measured within the hilum, proximal to the first branch in both MRI and catheterization angiography. We used 4 different MRI sequences to assess pulmonary artery size: 1) Axial black blood (HASTE or TSE), 2) Axial cine, 3) Phase contrast (PC) through plane flow, and 4) 3D contrast-enhanced MRA images. The maximum diameter was measured in mid-systole for cines. For MRA images, the long axis of each pulmonary artery was reconstructed using multiplanar reformatting (MPR) and diameters in 2 dimensions were measured (RPA: axial and coronal, LPA: axial and sagittal-oblique). Cross-sectional areas and diameters were measured from MRA and through plane flow images. Pearson's correlation and linear regression with 95% confidence intervals were used to compare MRI with the "gold" standard catheterization angiography measurements (p<0.05). For the RPA, all MRA measured dimensions correlated well with catheterization angiography (axial r=0.81, coronal r=0.89, cross-sectional area r=0.81, p<0.0001), with axial dark blood (r=0.65, p=0.02) and cine diameters (r=0.67, p=0.03) showing modest correlations. In contrast, LPA through plane PC area correlated best (r=0.73, p=0.02), with modest correlations for axial dark blood (r=0.54, p=0.04), MRA axial diameter (r=0.55, p=0.02), and MRA cross-sectional area (r=0.48, p=0.05). In children with single ventricle, MPR contrast enhanced MRA measurements showed the best correlate of RPA size compared to catheterization angiography. However, LPA cross-sectional area from PC flow measurements, and not MRA, were the best correlate of LPA measurements. Selection of the most appropriate sequence will provide a more accurate pre-operative evaluation of pulmonary artery size to aid the surgical strategy in this population. Knowledge of this will help tailor protocols to study pulmonary artery size in this population and imaging time may be shortened with this in mind.

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)0.007
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.231
Teacher spread0.221 · 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".

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Citations0
Published2013
Admission routes1
Has abstractyes

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