MétaCan
Menu
Back to cohort
Record W1994643849 · doi:10.1088/0031-9155/58/15/5009

Quantification of fibrosis in infarcted swine hearts by<i>ex vivo</i>late gadolinium-enhancement and diffusion-weighted MRI methods

2013· article· en· W1994643849 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePhysics in Medicine and Biology · 2013
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of OttawaToronto Centre for PhenogenomicsSunnybrook Health Science CentreUniversity of Toronto
FundersCanadian Institutes of Health Research
KeywordsFibrosisHistologyEx vivoMagnetic resonance imagingGadoliniumMedicineIn vivoEffective diffusion coefficientDiffusion MRIPathologyHigh resolutionInfarctionNuclear medicineChemistryMyocardial infarctionRadiologyBiologyCardiology

Abstract

fetched live from OpenAlex

Many have speculated that MRI signal characteristics can be used to identify regions of heterogeneous infarct associated with an arrhythmogenic substrate; however, direct evidence of this relationship is limited. The aim of this study was to demonstrate the remodelling characteristics of fibrosis by means of histology and high-resolution MR imaging. For this purpose, we performed whole-mount histology in heart samples (n = 9) collected from five swine at six weeks post-infarction and compared the extent of fibrosis in the infarcted areas delineated in these histological images with that obtained ex vivo by MRI using late gadolinium-enhancement (LGE) and diffusion-weighted imaging (DWI) methods. All MR images were obtained at a submillimetre resolution (i.e., voxel size of 0.6×0.6×1.2 mm(3)). Specifically, in the histology images, we differentiated moderate fibrosis (consisting of a mixture of viable and non-viable myocytes, known as border zone, BZ) from severe fibrosis (i.e., the dense scar). Correspondingly, tissue heterogeneities in the MR images were categorized by a Gaussian mixture model into healthy, BZ and scar. Our results showed that (a) both MRI methods were capable of qualitatively distinguishing sharp edges between dense scar and healthy tissue from regions of heterogeneous BZ; (b) the BZ and dense scar areas had intermediate-to-high increased values of signal intensity in the LGE images and of apparent diffusion coefficient in the DWI, respectively. In addition, as demonstrated by the Picrosirius Red and immunohistochemistry stains, the viable bundles in the BZ were clearly separated by thin collagen strands and had reduced expression of Cx43, whereas the core scar was composed of dense fibrosis. A quantitative analysis demonstrated that the comparison between BZ/scar extent in LGE and DWI to the corresponding areas identified in histology yielded very good correlations (i.e., for the scar identified by LGE, R(2) was 0.96 compared to R(2) = 0.93 for the scar identified in ADC maps, whereas the BZ had R(2) = 0.95 for the correlation between LGE and histology compared to R(2) = 0.91 obtained for ADC). This novel study represents an intermediate step in translating such research to the in vivo stages, as well as in establishing the best and most accurate MR method to help identify arrhythmia substrate in patients with structural heart 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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.246
Threshold uncertainty score0.354

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.127
GPT teacher head0.448
Teacher spread0.321 · 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