MétaCan
Menu
Back to cohort
Record W1014610620 · doi:10.1186/1532-429x-17-s1-q7

Characterization of the ultra-short echo time magnetic resonance (UTE MR) collagen signal associated with myocardial fibrosis

2015· article· en· W1014610620 on OpenAlexafffund
Adrienne Grace Siu, Andrew Ramadeen, Xudong Hu, Lily Morikawa, Li Zhang, Justin Y. C. Lau, Garry Liu, Mihaela Pop, Kim A. Connelly, Paul Dorian, Graham A. Wright

Bibliographic record

VenueJournal of Cardiovascular Magnetic Resonance · 2015
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsToronto Centre for PhenogenomicsSt. Michael's HospitalUniversity of TorontoSunnybrook Health Science Centre
FundersCanadian Institutes of Health Research
KeywordsGadoliniumMyocardial fibrosisMagnetic resonance imagingMedicineFibrosisNuclear magnetic resonanceAngiologyPathologyRadiologyChemistryCardiology

Abstract

fetched live from OpenAlex

The homogeneous distribution of collagen in diffuse myocardial fibrosis renders the disease unsuitable for imaging using late gadolinium enhancement (LGE) [ 1 ]. More recently, the estimation of extracellular volume from T 1 maps involving gadolinium agents has shown promise; however, these methods are not specific to collagen and are governed by gadolinium kinetics [ 2 ]. The diagnosis of diffuse myocardial fibrosis would benefit from an imaging method that can directly detect collagen. Notably, ultra-short echo time magnetic resonance (UTE MR) is a technique that can be used to detect short T 2 * species, including collagen [ 3 ]. Our objective is to characterize the UTE signal of protons in the collagen molecule, including their T 2 * and chemical shift. Direct isolation of a collagen signal could aid in the diagnosis of myocardial fibrosis, especially for diffuse distributions, and the assessment of disease extent. Collagen solutions of concentrations ranging from 0 % m/v to 50 % m/v were prepared by dissolving hydrolyzed type I and III collagen powder in 0.125 mM MnCl 2 , where the signal decay of MnCl 2 mimicked that of cardiac muscle. Each solution was scanned using a 3D UTE pulse sequence at 7 T, acquiring TEs from 0.02 ms to 25 ms, at a resolution of 0.781 mm isotropic. Upon fitting with a model of bi-exponential T 2 * with oscillation, the UTE collagen signal fraction was determined and calibrated against the collagen concentration. The T 2 * and resonance frequency (arising from the chemical shift) of collagen were assessed in collagen solutions. Validation of the collagen signal properties was also performed in formalin-fixed canine heart tissue, imaged with TEs from 0.02 ms to 25 ms, at a resolution of 0.156 mm isotropic. For collagen concentrations of 10 % to 50 %, the mean collagen T 2 * was 0.75 ± 0.05 ms, and the mean collagen frequency was 1.061 ± 0.004 kHz. A linear relationship (slope = 0.40 ± 0.01, R = 0.99696) was determined between the UTE collagen signal fraction associated with these characteristics and the measured collagen concentration (Figure 1 ). Similarly in canine heart tissue, a signal with T 2 * of 1.1 ± 0.3 ms and resonance frequency of 1.11 ± 0.02 kHz upfield of water was determined, consistent with collagen (Figure 2 ). The UTE collagen signal fraction of 1.2 ± 0.2 % in tissue corresponded to a collagen concentration of 2.3 ± 0.9 %, which was within the uncertainty of the collagen area fraction determined from histology (4 ± 2 %). UTE results in collagen solutions. (a) Collagen solution calibration plot, demonstrating a linear relationship between the UTE collagen signal fraction and the collagen concentration. m = slope, b = y-intercept, R = correlation coefficient, s r = standard deviation about the regression. (b) T 2 * decay of the 50 % collagen solution, fitted using a bi-exponential T 2 * model with oscillation. T 2 * long denotes the long T 2 * of MnCl 2 (mimicking cardiac muscle). Although not all long TEs were fitted, the focus was in the characterization of the short TEs ≤ 2 ms, where the T 2 * model is accurate. Histology and UTE results in canine heart tissue. (a) Histological slice of heart tissue, stained with Picrosirius Red. The 781.2 μm x 781.2 μm region-of-interest (ROI) used for analysis is delineated. The collagen area fraction in the ROI was determined to be 4 ± 2 %, based on a pixel threshold algorithm. (b) Corresponding UTE MR image at TE = 0.02 ms, with the ROI delineated. (c) T 2 * decay within the ROI. T 2 * long denotes the long T 2 * of cardiac muscle. TEs ≤ 2 ms were finely sampled to determine the collagen T 2 * and resonance frequency, where the T 2 * model is accurate. Based on the calibration plot in Figure 1a , the collagen signal fraction of 1.2 ± 0.2 % was equivalent to a collagen concentration of 2.3 ± 0.9 %. Hence, there was agreement between the collagen area fraction determined from histology (4 ± 2 %) and the collagen concentration. The results suggest that collagen associated with myocardial fibrosis can be endogenously detected and quantified using UTE MRI. This signal is specific to protons in collagen, characterized by a T 2 * of ~ 0.8 ms and a resonance frequency of ~ 1.1 kHz upfield of water at 7 T. Such properties would be beneficial in the determination of collagen content due to disease.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
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 head0.012
GPT teacher head0.225
Teacher spread0.213 · 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

Citations1
Published2015
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Cardiovascular Magnetic ResonanceSame topicAdvanced MRI Techniques and ApplicationsFrench-language works237,207