Dataset Information

Quantitative Perfusion Analysis of First-Pass Contrast Enhancement Kinetics: Application to MRI of Myocardial Perfusion in Coronary Artery Disease.

ABSTRACT:

Purpose

Perfusion analysis from first-pass contrast enhancement kinetics requires modeling tissue contrast exchange. This study presents a new approach for numerical implementation of the tissue homogeneity model, incorporating flexible distance steps along the capillary (NTHf).

Methods

The proposed NTHf model considers contrast exchange in fluid packets flowing along the capillary, incorporating flexible distance steps, thus allowing more efficient and stable calculations of the transit of tracer through the tissue. We prospectively studied 8 patients (62 ± 13 years old) with suspected CAD, who underwent first-pass perfusion CMR imaging at rest and stress prior to angiography. Myocardial blood flow (MBF) and myocardial perfusion reserve index (MPRI) were estimated using both the NTHf and the conventional adiabatic approximation of the TH models. Coronary artery lesions detected at angiography were clinically assigned to one of three categories of stenosis severity ('insignificant', 'mild to moderate' and 'severe') and related to corresponding myocardial territories.

Results

The mean MBF (ml/g/min) at rest/stress and MPRI were 0.80 ± 0.33/1.25 ± 0.45 and 1.68 ± 0.54 in the insignificant regions, 0.74 ± 0.21/1.09 ± 0.28 and 1.54 ± 0.46 in the mild to moderate regions, and 0.79 ± 0.28/0.63 ± 0.34 and 0.85 ± 0.48 in the severe regions, respectively. The correlation coefficients of MBFs at rest/stress and MPRI between the NTHf and AATH models were r = 0.97/0.93 and r = 0.91, respectively.

Conclusions

The proposed NTHf model allows efficient quantitative analysis of the transit of tracer through tissue, particularly at higher flow. Results of initial application to MRI of myocardial perfusion in CAD are encouraging.

SUBMITTER: Chung S

PROVIDER: S-EPMC5008793 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Quantitative Perfusion Analysis of First-Pass Contrast Enhancement Kinetics: Application to MRI of Myocardial Perfusion in Coronary Artery Disease.

Chung Sohae S Shah Binita B Storey Pippa P Iqbal Sohah S Slater James J Axel Leon L

PloS one 20160901 9

<h4>Purpose</h4>Perfusion analysis from first-pass contrast enhancement kinetics requires modeling tissue contrast exchange. This study presents a new approach for numerical implementation of the tissue homogeneity model, incorporating flexible distance steps along the capillary (NTHf).<h4>Methods</h4>The proposed NTHf model considers contrast exchange in fluid packets flowing along the capillary, incorporating flexible distance steps, thus allowing more efficient and stable calculations of the ...[more]

PMID: 27583385

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Project description:BACKGROUND:Quantitative myocardial perfusion cardiac MRI can provide a fast and robust assessment of myocardial perfusion status for the noninvasive diagnosis of myocardial ischemia while being more objective than visual assessment. However, it currently has limited use in clinical practice due to the challenging postprocessing required, particularly the segmentation. PURPOSE:To evaluate the efficacy of an automated deep learning (DL) pipeline for image processing prior to quantitative analysis. STUDY TYPE:Retrospective. POPULATION:In all, 175 (350 MRI scans; 1050 image series) clinical patients under both rest and stress conditions (135/10/30 training/validation/test). FIELD STRENGTH/SEQUENCE:3.0T/2D multislice saturation recovery T1 -weighted gradient echo sequence. ASSESSMENT:Accuracy was assessed, as compared to the manual operator, through the mean square error of the distance between landmarks and the Dice similarity coefficient of the segmentation and bounding box detection. Quantitative perfusion maps obtained using the automated DL-based processing were compared to the results obtained with the manually processed images. STATISTICAL TESTS:Bland-Altman plots and intraclass correlation coefficient (ICC) were used to assess the myocardial blood flow (MBF) obtained using the automated DL pipeline, as compared to values obtained by a manual operator. RESULTS:The mean (SD) error in the detection of the time of peak signal enhancement in the left ventricle was 1.49 (1.4) timeframes. The mean (SD) Dice similarity coefficients for the bounding box and myocardial segmentation were 0.93 (0.03) and 0.80 (0.06), respectively. The mean (SD) error in the RV insertion point was 2.8 (1.8) mm. The Bland-Altman plots showed a bias of 2.6% of the mean MBF between the automated and manually processed MBF values on a per-myocardial segment basis. The ICC was 0.89, 95% confidence interval = [0.87, 0.90]. DATA CONCLUSION:We showed high accuracy, compared to manual processing, for the DL-based processing of myocardial perfusion data leading to quantitative values that are similar to those achieved with manual processing. LEVEL OF EVIDENCE:3 Technical Efficacy Stage: 1 J. Magn. Reson. Imaging 2020;51:1689-1696.

Project description:ObjectivesThis study sought to assess the performance of cardiovascular magnetic resonance (CMR) myocardial perfusion mapping against invasive coronary physiology reference standards for detecting coronary artery disease (CAD, defined by fractional flow reserve [FFR] ≤0.80), microvascular dysfunction (MVD) (defined by index of microcirculatory resistance [IMR] ≥25) and the ability to differentiate between the two.BackgroundDifferentiation of epicardial (CAD) and MVD in patients with stable angina remains challenging. Automated in-line CMR perfusion mapping enables quantification of myocardial blood flow (MBF) to be performed rapidly within a clinical workflow.MethodsFifty patients with stable angina and 15 healthy volunteers underwent adenosine stress CMR at 1.5T with quantification of MBF and myocardial perfusion reserve (MPR). FFR and IMR were measured in 101 coronary arteries during subsequent angiography.ResultsTwenty-seven patients had obstructive CAD and 23 had nonobstructed arteries (7 normal IMR, 16 abnormal IMR). FFR positive (epicardial stenosis) areas had significantly lower stress MBF (1.47 ± 0.48 ml/g/min) and MPR (1.75 ± 0.60) than FFR-negative IMR-positive (MVD) areas (stress MBF: 2.10 ± 0.35 ml/g/min; MPR: 2.41 ± 0.79) and normal areas (stress MBF: 2.47 ± 0.50 ml/g/min; MPR: 2.94 ± 0.81). Stress MBF ≤1.94 ml/g/min accurately detected obstructive CAD on a regional basis (area under the curve: 0.90; p < 0.001). In patients without regional perfusion defects, global stress MBF <1.82 ml/g/min accurately discriminated between obstructive 3-vessel disease and MVD (area under the curve: 0.94; p < 0.001).ConclusionsThis novel automated pixel-wise perfusion mapping technique can be used to detect physiologically significant CAD defined by FFR, MVD defined by IMR, and to differentiate MVD from multivessel coronary disease. A CMR-based diagnostic algorithm using perfusion mapping for detection of epicardial disease and MVD warrants further clinical validation.

Dataset Information

Quantitative Perfusion Analysis of First-Pass Contrast Enhancement Kinetics: Application to MRI of Myocardial Perfusion in Coronary Artery Disease.

Purpose

Methods

Results

Conclusions

Publications

Quantitative Perfusion Analysis of First-Pass Contrast Enhancement Kinetics: Application to MRI of Myocardial Perfusion in Coronary Artery Disease.

Similar Datasets

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