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

View Article: PubMed Central - PubMed

ABSTRACT

Background: Quantification 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.

Methods: A 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.

Results: For 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.

Conclusions: A 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 material: The online version of this article (doi:10.1186/s12968-017-0355-5) contains supplementary material, which is available to authorized users.

No MeSH data available.


Example AIF images for stress study showing echo 1 and 2 images at baseline and peak enhancement of right ventricle (RV), left ventricle (LV) and myocardium (myo)
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Fig9: Example AIF images for stress study showing echo 1 and 2 images at baseline and peak enhancement of right ventricle (RV), left ventricle (LV) and myocardium (myo)

Mentions: Adenosine stress studies were conducted on 29 normal healthy volunteers. The peak [Gd] was 3.5 ± 1.2 mmol/L (m ± SD) for stress and 4.4 ± 1.2 mmol/L for rest as measured in the AIF. The T2* in the LV blood pool at peak AIF [Gd] was 10.0 ± 2.4 ms at stress and 9.9 ± 1.7 ms at rest. The duration of the 1st pass was 10.3 ± 2.1 s at stress and 14.7 ± 3.2 s at rest. Example AIF images for echo 1 and echo 2 are shown in Fig. 9 for stress, and normalized AIF signal curves are shown in Fig. 10. In this example, the T2* corrected signal was approximately 8% higher than the echo 1 peak signal, which led to approximately 10% greater [Gd] after LUT correction. For 29 subjects, the peak to valley ratio was 5.6 for the raw signal intensities without correction, and was 8.3 for the LUT corrected AIF in gadolinium concentration units. The valley is indicated by the arrow in Fig. 10 stress signal intensity plot. This represents approximately 48% improvement in linearity.Fig. 9


Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification
Example AIF images for stress study showing echo 1 and 2 images at baseline and peak enhancement of right ventricle (RV), left ventricle (LV) and myocardium (myo)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC5383963&req=5

Fig9: Example AIF images for stress study showing echo 1 and 2 images at baseline and peak enhancement of right ventricle (RV), left ventricle (LV) and myocardium (myo)
Mentions: Adenosine stress studies were conducted on 29 normal healthy volunteers. The peak [Gd] was 3.5 ± 1.2 mmol/L (m ± SD) for stress and 4.4 ± 1.2 mmol/L for rest as measured in the AIF. The T2* in the LV blood pool at peak AIF [Gd] was 10.0 ± 2.4 ms at stress and 9.9 ± 1.7 ms at rest. The duration of the 1st pass was 10.3 ± 2.1 s at stress and 14.7 ± 3.2 s at rest. Example AIF images for echo 1 and echo 2 are shown in Fig. 9 for stress, and normalized AIF signal curves are shown in Fig. 10. In this example, the T2* corrected signal was approximately 8% higher than the echo 1 peak signal, which led to approximately 10% greater [Gd] after LUT correction. For 29 subjects, the peak to valley ratio was 5.6 for the raw signal intensities without correction, and was 8.3 for the LUT corrected AIF in gadolinium concentration units. The valley is indicated by the arrow in Fig. 10 stress signal intensity plot. This represents approximately 48% improvement in linearity.Fig. 9

View Article: PubMed Central - PubMed

ABSTRACT

Background: Quantification 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.

Methods: A 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.

Results: For 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.

Conclusions: A 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 material: The online version of this article (doi:10.1186/s12968-017-0355-5) contains supplementary material, which is available to authorized users.

No MeSH data available.