Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification

Abstract

BackgroundQuantification of myocardial blood flow requires knowledge of the amount of contrast agent in the myocardial tissue and the arterial input function (AIF) driving the delivery of this contrast agent. Accurate quantification is challenged by the lack of linearity between the measured signal and contrast agent concentration. This work characterizes sources of non-linearity and presents a systematic approach to accurate measurements of contrast agent concentration in both blood and myocardium.MethodsA dual sequence approach with separate pulse sequences for AIF and myocardial tissue allowed separate optimization of parameters for blood and myocardium. A systems approach to the overall design was taken to achieve linearity between signal and contrast agent concentration. Conversion of signal intensity values to contrast agent concentration was achieved through a combination of surface coil sensitivity correction, Bloch simulation based look-up table correction, and in the case of the AIF measurement, correction of T2* losses. Validation of signal correction was performed in phantoms, and values for peak AIF concentration and myocardial flow are provided for 29 normal subjects for rest and adenosine stress.ResultsFor phantoms, the measured fits were within 5% for both AIF and myocardium. In healthy volunteers the peak [Gd] was 3.5 ± 1.2 for stress and 4.4 ± 1.2 mmol/L for rest. The T2* in the left ventricle blood pool at peak AIF was approximately 10 ms. The peak-to-valley ratio was 5.6 for the raw signal intensities without correction, and was 8.3 for the look-up-table (LUT) corrected AIF which represents approximately 48% correction. Without T2* correction the myocardial blood flow estimates are overestimated by approximately 10%. The signal-to-noise ratio of the myocardial signal at peak enhancement (1.5 T) was 17.7 ± 6.6 at stress and the peak [Gd] was 0.49 ± 0.15 mmol/L. The estimated perfusion flow was 3.9 ± 0.38 and 1.03 ± 0.19 ml/min/g using the BTEX model and 3.4 ± 0.39 and 0.95 ± 0.16 using a Fermi model, for stress and rest, respectively.ConclusionsA dual sequence for myocardial perfusion cardiovascular magnetic resonance and AIF measurement has been optimized for quantification of myocardial blood flow. A validation in phantoms was performed to confirm that the signal conversion to gadolinium concentration was linear. The proposed sequence was integrated with a fully automatic in-line solution for pixel-wise mapping of myocardial blood flow and evaluated in adenosine stress and rest studies on N = 29 normal healthy subjects. Reliable perfusion mapping was demonstrated and produced estimates with low variability.Electronic supplementary materialThe online version of this article (doi:10.1186/s12968-017-0355-5) contains supplementary material, which is available to authorized users.

Accelerated, first‐pass cardiac perfusion pulse sequence with radial k‐space sampling, compressed sensing, and k‐space weighted image contrast reconstruction tailored for visual analysis and quantification of myocardial blood flow

“…A dual‐bolus technique is not practical in a clinical setting, because it requires accurate preparation of 2 different concentrations at equal volumes and a complex setup to prevent backflow in the injector apparatus . A dual‐imaging approach requires extensive pulse sequence development to include a dedicated AIF acquisition where all of its parameters are known . In this study, we elected to use a synthetic dual‐imaging approach in conjunction with image acceleration provided by CS.…”

Combined Assessment of Stress Myocardial Perfusion Cardiovascular Magnetic Resonance and Flow Measurement in the Coronary Sinus Improves Prediction of Functionally Significant Coronary Stenosis Determined by Fractional Flow Reserve in Multivessel Disease

“…In addition, quantitative assessment is time consuming and might be dependent on image quality and the presence of prior infarction. Currently, Kellman et al demonstrated in‐line automated and reliable perfusion mapping, which may increase the applicability of the technology in clinical and research settings 25. On the other hand, an advantage of blood flow assessment in the CS is that hemodynamic data can be derived from phase‐contrast images alone with additional imaging time of 2 breath‐holds and postprocessing time of a few minutes.…”

Quantitative 3D myocardial perfusion with an efficient arterial input function

“…The arterial input function (AIF) should be measured to support quantitative analysis of first‐pass perfusion . In practice, most approaches extract both the AIF and the tissue signal from the same set of images .…”