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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.


Normalized saturation recovery myocardial signal (SR/PD) for b-SSFP protocol (Table 2) versus saturation delay (TS) for various values of tissue gadolinium concentration, [Gd] (left). With short TS protocols it is possible to acquire multiple slices per heart beat with T1 contrast. The contrast to noise ratio increases with TS, with increasing signal non-linearity and eventually at very long TS there is low contrast as the signal recovers. The CNR vs [Gd] is plotted for 2 values of TS (right) corresponding to T2 = 95 and 160 ms, corresponding to 3 and 2 slices/RR at a heart rate of 120 bpm. The increased TS can achieve approx. 40% higher CNR at the cost of less spatial coverage
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Fig3: Normalized saturation recovery myocardial signal (SR/PD) for b-SSFP protocol (Table 2) versus saturation delay (TS) for various values of tissue gadolinium concentration, [Gd] (left). With short TS protocols it is possible to acquire multiple slices per heart beat with T1 contrast. The contrast to noise ratio increases with TS, with increasing signal non-linearity and eventually at very long TS there is low contrast as the signal recovers. The CNR vs [Gd] is plotted for 2 values of TS (right) corresponding to T2 = 95 and 160 ms, corresponding to 3 and 2 slices/RR at a heart rate of 120 bpm. The increased TS can achieve approx. 40% higher CNR at the cost of less spatial coverage

Mentions: The duration of actual signal shot image was 70 ms for SSFP protocol using factor 3 acceleration and Partial Fourier factor of ¾ with the latter part of k-space omitted. There is a trade-off between contrast-to-noise ratio (CNR), spatial coverage (number of slices per RR), and linearity as illustrated in Fig. 3. The protocol was designed to work at a heart rate of 120 bpm which is commonly seen for patients under adenosine stress. It was possible to acquire the AIF plus 3 slices at 120 bpm with the proposed protocol using TS = 95 ms, or AIF plus 2 slices using TI = 160 with increased CNR. It is also possible to prescribe 2x the number of slices by acquiring slices at 2RR intervals. Although there is a gain CNR with longer TS, there is also a loss in performance when using 2RR sampling since there will be fewer samples of the myocardial signal during the first pass measurement.Fig. 3


Myocardial perfusion cardiovascular magnetic resonance: optimized dual sequence and reconstruction for quantification
Normalized saturation recovery myocardial signal (SR/PD) for b-SSFP protocol (Table 2) versus saturation delay (TS) for various values of tissue gadolinium concentration, [Gd] (left). With short TS protocols it is possible to acquire multiple slices per heart beat with T1 contrast. The contrast to noise ratio increases with TS, with increasing signal non-linearity and eventually at very long TS there is low contrast as the signal recovers. The CNR vs [Gd] is plotted for 2 values of TS (right) corresponding to T2 = 95 and 160 ms, corresponding to 3 and 2 slices/RR at a heart rate of 120 bpm. The increased TS can achieve approx. 40% higher CNR at the cost of less spatial coverage
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

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

Fig3: Normalized saturation recovery myocardial signal (SR/PD) for b-SSFP protocol (Table 2) versus saturation delay (TS) for various values of tissue gadolinium concentration, [Gd] (left). With short TS protocols it is possible to acquire multiple slices per heart beat with T1 contrast. The contrast to noise ratio increases with TS, with increasing signal non-linearity and eventually at very long TS there is low contrast as the signal recovers. The CNR vs [Gd] is plotted for 2 values of TS (right) corresponding to T2 = 95 and 160 ms, corresponding to 3 and 2 slices/RR at a heart rate of 120 bpm. The increased TS can achieve approx. 40% higher CNR at the cost of less spatial coverage
Mentions: The duration of actual signal shot image was 70 ms for SSFP protocol using factor 3 acceleration and Partial Fourier factor of ¾ with the latter part of k-space omitted. There is a trade-off between contrast-to-noise ratio (CNR), spatial coverage (number of slices per RR), and linearity as illustrated in Fig. 3. The protocol was designed to work at a heart rate of 120 bpm which is commonly seen for patients under adenosine stress. It was possible to acquire the AIF plus 3 slices at 120 bpm with the proposed protocol using TS = 95 ms, or AIF plus 2 slices using TI = 160 with increased CNR. It is also possible to prescribe 2x the number of slices by acquiring slices at 2RR intervals. Although there is a gain CNR with longer TS, there is also a loss in performance when using 2RR sampling since there will be fewer samples of the myocardial signal during the first pass measurement.Fig. 3

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.