Dataset Information

Impact of the Choice of Native T₁ in Pixelwise Myocardial Blood Flow Quantification.

ABSTRACT:

Background

Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T₁ values of blood and myocardium.

Purpose

To assess the impact of T₁ values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T₁ values.

Study type

Prospective.

Subjects

Fifteen patients with chronic coronary heart disease.

Field strength/sequence

3T; modified Look-Locker inversion recovery for T₁ mapping and saturation recovery gradient echo for DCE imaging, both acquired in a mid-ventricular short-axis slice in systole and diastole.

Assessment

MBF was estimated using Fermi modeling and signal intensity nonlinearity correction with different T₁ values: study population-averaged blood and myocardial, subject-specific systolic and diastolic, and segmental T₁ values. Myocardial segments with perfusion deficits were identified visually from DCE series.

Statistical tests

The relationships between MBF parameters derived by different methods were analyzed by Bland-Altman analysis; corresponding mean values were compared by t-test.

Results

Using subject-specific diastolic T₁ values, global diastolic MBF was 0.61?±?0.13?mL/(min·g). It did not differ from global MBF derived from the study population-averaged T₁ (P = 0.88), but the standard deviation of differences was large (0.07?mL/(min·g), 11% of mean MBF). Global diastolic and systolic MBF did not differ (P = 0.12), whereas global diastolic MBF using systolic (0.62?±?0.13?mL/(min·g)) and diastolic T₁ values differed (P?1 values were used, segmental MBF was lower in segments with perfusion deficits (bias = -0.03?mL/(min·g), -7% of mean MBF, P?Data conclusionWhereas cardiac phase-specific T₁ values have a minor impact on MBF estimates, subject-specific and myocardial segment-specific T₁ values substantially affect MBF quantification.

Level of evidence

3 TECHNICAL EFFICACY STAGE: 3.

SUBMITTER: Krauter C

PROVIDER: S-EPMC7891429 | biostudies-literature | 2021 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Impact of the Choice of Native T<sub>1</sub> in Pixelwise Myocardial Blood Flow Quantification.

Kräuter Corina C Reiter Ursula U Reiter Clemens C Nizhnikava Volha V Schmidt Albrecht A Stollberger Rudolf R Fuchsjäger Michael M Reiter Gert G

Journal of magnetic resonance imaging : JMRI 20201008 3

<h4>Background</h4>Quantification of myocardial blood flow (MBF) from dynamic contrast-enhanced (DCE) MRI can be performed using a signal intensity model that incorporates T<sub>1</sub> values of blood and myocardium.<h4>Purpose</h4>To assess the impact of T<sub>1</sub> values on pixelwise MBF quantification, specifically to evaluate the influence of 1) study population-averaged vs. subject-specific, 2) diastolic vs. systolic, and 3) regional vs. global myocardial T<sub>1</sub> values.<h4>Study ...[more]

PMID: 33034120

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Project description:BackgroundTissue characterisation with cardiovascular magnetic resonance (CMR) parametric mapping has the potential to detect and quantify both focal and diffuse alterations in myocardial structure not assessable by late gadolinium enhancement. Native T1 mapping in particular has shown promise as a useful biomarker to support diagnostic, therapeutic and prognostic decision-making in ischaemic and non-ischaemic cardiomyopathies.MethodsConvolutional neural networks (CNNs) with Bayesian inference are a category of artificial neural networks which model the uncertainty of the network output. This study presents an automated framework for tissue characterisation from native shortened modified Look-Locker inversion recovery ShMOLLI T1 mapping at 1.5 T using a Probabilistic Hierarchical Segmentation (PHiSeg) network (PHCUMIS 119-127, 2019). In addition, we use the uncertainty information provided by the PHiSeg network in a novel automated quality control (QC) step to identify uncertain T1 values. The PHiSeg network and QC were validated against manual analysis on a cohort of the UK Biobank containing healthy subjects and chronic cardiomyopathy patients (N=100 for the PHiSeg network and N=700 for the QC). We used the proposed method to obtain reference T1 ranges for the left ventricular (LV) myocardium in healthy subjects as well as common clinical cardiac conditions.ResultsT1 values computed from automatic and manual segmentations were highly correlated (r=0.97). Bland-Altman analysis showed good agreement between the automated and manual measurements. The average Dice metric was 0.84 for the LV myocardium. The sensitivity of detection of erroneous outputs was 91%. Finally, T1 values were automatically derived from 11,882 CMR exams from the UK Biobank. For the healthy cohort, the mean (SD) corrected T1 values were 926.61 (45.26), 934.39 (43.25) and 927.56 (50.36) for global, interventricular septum and free-wall respectively.ConclusionsThe proposed pipeline allows for automatic analysis of myocardial native T1 mapping and includes a QC process to detect potentially erroneous results. T1 reference values were presented for healthy subjects and common clinical cardiac conditions from the largest cohort to date using T1-mapping images.

Dataset Information

Impact of the Choice of Native T₁ in Pixelwise Myocardial Blood Flow Quantification.

Background

Purpose

Study type

Subjects

Field strength/sequence

Assessment

Statistical tests

Results

Level of evidence

Publications

Impact of the Choice of Native T<sub>1</sub> in Pixelwise Myocardial Blood Flow Quantification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Dataset Information

Impact of the Choice of Native T1 in Pixelwise Myocardial Blood Flow Quantification.

Background

Purpose

Study type

Subjects

Field strength/sequence

Assessment

Statistical tests

Results

Level of evidence

Publications

Impact of the Choice of Native T<sub>1</sub> in Pixelwise Myocardial Blood Flow Quantification.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

Impact of the Choice of Native T₁ in Pixelwise Myocardial Blood Flow Quantification.