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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.


Related in: MedlinePlus

Illustration of first-pass contrast enhanced myocardial perfusion imaging showing different phases of image contrast during passage of the bolus for a subject with single vessel disease. Proton density weighted images are acquired at the start of acquisition prior to administering the contrast agent bolus. The complete time series of images are automatically processed to estimate pixel-wise myocardial blood flow maps which show regions of low flow in different color than normal flow, thereby reducing the time required to analyze the raw images. The time intensity signals represent the intensities of RV blood pool (blue), LV blood pool (red), and myocardium (black) regions. Note that flow map values are only valid for myocardium tissue and not blood pool regions or in non-tissue
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Fig1: Illustration of first-pass contrast enhanced myocardial perfusion imaging showing different phases of image contrast during passage of the bolus for a subject with single vessel disease. Proton density weighted images are acquired at the start of acquisition prior to administering the contrast agent bolus. The complete time series of images are automatically processed to estimate pixel-wise myocardial blood flow maps which show regions of low flow in different color than normal flow, thereby reducing the time required to analyze the raw images. The time intensity signals represent the intensities of RV blood pool (blue), LV blood pool (red), and myocardium (black) regions. Note that flow map values are only valid for myocardium tissue and not blood pool regions or in non-tissue

Mentions: A saturation recovery (SR) sequence was used for myocardial perfusion imaging during the passage of a bolus of gadolinium based contrast agent as depicted in Fig. 1 which is illustrated for a subject with single vessel disease. Baseline images were acquired prior to bolus administration and continued through the first pass. Typically, images were acquired for 60-90 heartbeats depending on the cardiac output. Proton density (PD) weighted images were acquired at the start.Fig. 1


Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification
Illustration of first-pass contrast enhanced myocardial perfusion imaging showing different phases of image contrast during passage of the bolus for a subject with single vessel disease. Proton density weighted images are acquired at the start of acquisition prior to administering the contrast agent bolus. The complete time series of images are automatically processed to estimate pixel-wise myocardial blood flow maps which show regions of low flow in different color than normal flow, thereby reducing the time required to analyze the raw images. The time intensity signals represent the intensities of RV blood pool (blue), LV blood pool (red), and myocardium (black) regions. Note that flow map values are only valid for myocardium tissue and not blood pool regions or in non-tissue
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig1: Illustration of first-pass contrast enhanced myocardial perfusion imaging showing different phases of image contrast during passage of the bolus for a subject with single vessel disease. Proton density weighted images are acquired at the start of acquisition prior to administering the contrast agent bolus. The complete time series of images are automatically processed to estimate pixel-wise myocardial blood flow maps which show regions of low flow in different color than normal flow, thereby reducing the time required to analyze the raw images. The time intensity signals represent the intensities of RV blood pool (blue), LV blood pool (red), and myocardium (black) regions. Note that flow map values are only valid for myocardium tissue and not blood pool regions or in non-tissue
Mentions: A saturation recovery (SR) sequence was used for myocardial perfusion imaging during the passage of a bolus of gadolinium based contrast agent as depicted in Fig. 1 which is illustrated for a subject with single vessel disease. Baseline images were acquired prior to bolus administration and continued through the first pass. Typically, images were acquired for 60-90 heartbeats depending on the cardiac output. Proton density (PD) weighted images were acquired at the start.Fig. 1

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.


Related in: MedlinePlus