Quantification of myocardial perfusion by MRI after coronary occlusion

Automatic in-line quantitative myocardial perfusion mapping: Processing algorithm and implementation

PURPOSE

Quantitative myocardial perfusion mapping has advantages over qualitative assessment, including the ability to detect global flow reduction. However, it is not clinically available and remains a research tool. Building upon the previously described imaging sequence, this study presents algorithm and implementation of an automated solution for inline perfusion flow mapping with step by step performance characterization.

METHODS

Proposed workflow consists of motion correction (MOCO), arterial input function blood detection, intensity to gadolinium concentration conversion, and pixel-wise mapping. A distributed kinetics model, blood-tissue exchange model, is implemented, computing pixel-wise maps of myocardial blood flow (mL/min/g), permeability-surface-area product (mL/min/g), blood volume (mL/g), and interstitial volume (mL/g).

RESULTS

Thirty healthy subjects (11 men; 26.4 ± 10.4 years) were recruited and underwent adenosine stress perfusion cardiovascular MR. Mean MOCO quality score was 3.6 ± 0.4 for stress and 3.7 ± 0.4 for rest. Myocardial Dice similarity coefficients after MOCO were significantly improved (P < 1e-6), 0.87 ± 0.05 for stress and 0.86 ± 0.06 for rest. Arterial input function peak gadolinium concentration was 4.4 ± 1.3 mmol/L at stress and 5.2 ± 1.5 mmol/L at rest. Mean myocardial blood flow at stress and rest were 2.82 ± 0.47 mL/min/g and 0.68 ± 0.16 mL/min/g, respectively. The permeability-surface-area product was 1.32 ± 0.26 mL/min/g at stress and 1.09 ± 0.21 mL/min/g at rest (P < 1e-3). Blood volume was 12.0 ± 0.8 mL/100 g at stress and 9.7 ± 1.0 mL/100 g at rest (P < 1e-9), indicating good adenosine vasodilation response. Interstitial volume was 20.8 ± 2.5 mL/100 g at stress and 20.3 ± 2.9 mL/100 g at rest (P = 0.50).

CONCLUSIONS

An inline perfusion flow mapping workflow is proposed and demonstrated on normal volunteers. Initial evaluation demonstrates this fully automated solution for the respiratory MOCO, arterial input function left ventricle mask detection, and pixel-wise mapping, from free-breathing myocardial perfusion imaging.

Models and methods for analyzing DCE-MRI: a review

PURPOSE

To present a review of most commonly used techniques to analyze dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), discusses their strengths and weaknesses, and outlines recent clinical applications of findings from these approaches.

METHODS

DCE-MRI allows for noninvasive quantitative analysis of contrast agent (CA) transient in soft tissues. Thus, it is an important and well-established tool to reveal microvasculature and perfusion in various clinical applications. In the last three decades, a host of nonparametric and parametric models and methods have been developed in order to quantify the CA's perfusion into tissue and estimate perfusion-related parameters (indexes) from signal- or concentration-time curves. These indexes are widely used in various clinical applications for the detection, characterization, and therapy monitoring of different diseases.

RESULTS

Promising theoretical findings and experimental results for the reviewed models and techniques in a variety of clinical applications suggest that DCE-MRI is a clinically relevant imaging modality, which can be used for early diagnosis of different diseases, such as breast and prostate cancer, renal rejection, and liver tumors.

CONCLUSIONS

Both nonparametric and parametric approaches for DCE-MRI analysis possess the ability to quantify tissue perfusion.

Development of a method for automated and stable myocardial perfusion measurement using coronary X-ray angiography images

The purpose of this study was to develop a method for automatic and stable determination of the optimal time range for fitting with a Patlak plot model in order to measure myocardial perfusion using coronary X-ray angiography images. A conventional two-compartment model is used to measure perfusion, and the slope of the Patlak plot is calculated to obtain a perfusion image. The model holds for only a few seconds while the contrast agent flows from artery to myocardium. Therefore, a specific time range should be determined for fitting with the model. To determine this time range, automation is needed for routine examinations. The optimal time range was determined to minimize the standard error between data points and their least-squares regression straight line in the Patlak plot. A total of 28 datasets were tested in seven porcine models. The new method successfully detected the time range when contrast agent flowed from artery to myocardium. The mean cross correlation in the linear regression analysis (R(2)) was 0.996 ± 0.004. The mean length of the optimal time range was 3.61 ± 1.29 frames (2.18 ± 1.40 s). This newly developed method can automatically determine the optimal time range for fitting with the model.

Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy

PURPOSE

To compare the diagnostic performance of four tracer kinetic analysis methods to quantify myocardial perfusion from magnetic resonance (MR) imaging cardiac perfusion data sets in terms of their ability to lead to the diagnosis of myocardial ischemia.

MATERIALS AND METHODS

The study was approved by the regional ethics committee, and all patients gave written consent. A representative sample of 50 patients with suspected ischemic heart disease was retrospectively selected from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease trial data set. Quantitative myocardial blood flow (MBF) was estimated from rest and adenosine stress MR imaging perfusion data sets by using four established methods. A matching diagnosis of both an inducible defect as assessed with single photon emission computed tomography and a luminal stenosis of 70% or more as assessed with quantitative x-ray angiography was used as the reference standard for the presence of myocardial ischemia. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for each method, with stress MBF and myocardial perfusion reserve (MPR) serving as continuous measures.

RESULTS

Area under the ROC curve with stress MBF and MPR as the outcome measures, respectively, was 0.86 and 0.92 for the Fermi model, 0.85 and 0.87 for the uptake model, 0.85 and 0.80 for the one-compartment model, and 0.87 and 0.87 for model-independent deconvolution. There was no significant difference between any of the models or between MBF and MPR, except that the Fermi model outperformed the one-compartment model if MPR was used as the outcome measure (P = .02).

CONCLUSION

Diagnostic performance of quantitative myocardial perfusion estimates is not affected by the tracer kinetic analysis method used.

Development of a theory for generating regional cardiac perfusion images during coronary angiography in the coronary angiography lab

The purpose of this study was to develop a novel theory and method for generating regional myocardial perfusion images using fluoroscopy in the coronary angiography lab. We modified the Kety model to introduce the Patlak plot method for two-dimensional fluoroperfusion (FP) imaging. For evaluation, seven porcine models of myocardial ischemia with stenosis in the left coronary artery were prepared. Rest and stress FP imaging were performed using cardiovascular X-ray imaging equipment during the injection of iopamidol via the left main coronary artery. Images were acquired and retrospectively ECG gated at 80 % of the R-R interval. FP myocardial blood flow (MBF) was obtained using the Patlak plot method applied to time-intensity curve data of the proximal artery and myocardium. The results were compared to microsphere MBF measurements. Time-intensity curves were also used to generate color-coded FP maps. There was a moderate linear correlation between the calculated FP MBF and the microsphere MBF (y = 0.9758x + 0.5368, R² = 0.61). The color-coded FP maps were moderately correlated with the regional distribution of flow. This novel method of first-pass contrast-enhanced two-dimensional fluoroscopic imaging can quantify MBF and provide color coded FP maps representing regional myocardial perfusion.

Cardiac MR perfusion image processing techniques: a survey

First-pass cardiac MR perfusion (CMRP) imaging has undergone rapid technical advancements in recent years. Although the efficacy of CMRP imaging in the assessment of coronary artery diseases (CAD) has been proven, its clinical use is still limited. This limitation stems, in part, from manual interaction required to quantitatively analyze the large amount of data. This process is tedious, time-consuming, and prone to operator bias. Furthermore, acquisition and patient related image artifacts reduce the accuracy of quantitative perfusion assessment. With the advent of semi- and fully automatic image processing methods, not only the challenges posed by these artifacts have been overcome to a large extent, but a significant reduction has also been achieved in analysis time and operator bias. Despite an extensive literature on such image processing methods, to date, no survey has been performed to discuss this dynamic field. The purpose of this article is to provide an overview of the current state of the field with a categorical study, along with a future perspective on the clinical acceptance of image processing methods in the diagnosis of CAD.

Comparison of intravascular and extracellular contrast media for absolute quantification of myocardial rest-perfusion using high-resolution MRI

PURPOSE

To use the contrast agent gadofosveset for absolute quantification of myocardial perfusion and compare it with gadobenate dimeglumine (Gd-BOPTA) using a high-resolution generalized autocalibrating partially parallel acquisition (GRAPPA) sequence.

MATERIALS AND METHODS

Ten healthy volunteers were examined twice at two different dates with a first-pass perfusion examination at rest using prebolus technique. We used a 1.5 T scanner and a 32 channel heart-array coil with a steady-state free precession (SSFP) true fast imaging with steady state precession (trueFISP) GRAPPA sequence (acceleration-factor 3). Manual delineation of the myocardial contours was performed and absolute quantification was performed after baseline and contamination correction. At the first appointment, 1cc/4cc of the extracellular contrast agent Gd-BOPTA were administered, on the second date, 1cc/4cc of the blood pool contrast agent (CA) gadofosveset. At each date the examination was repeated after a 15-minute time interval.

RESULTS

Using gadofosveset perfusion the value (in cc/g/min) at rest was 0.66 ± 0.25 (mean ± standard deviation) for the first, and 0.55 ± 0.24 for the second CA application; for Gd-BOPTA it was 0.62 ± 0.25 and 0.45 ± 0.23. No significant difference was found between the acquired perfusion values. The apparent mean residence time in the myocardium was 23 seconds for gadofosveset and 19.5 seconds for Gd-BOPTA. Neither signal-to-noise ratio (SNR) nor subjectively rated image contrast showed a significant difference.

CONCLUSION

The application of gadofosveset for an absolute quantification of myocardial perfusion is possible. Yet the acquired perfusion values show no significant differences to those determined with Gd-BOPTA, maintained the same SNR and comparable perfusion values, and did not picture the expected concentration time-course for an intravasal CA in the first pass.

Quantification of myocardial blood flow using model based analysis of first-pass perfusion MRI: extraction fraction of Gd-DTPA varies with myocardial blood flow in human myocardium

For the absolute quantification of myocardial blood flow (MBF), Patlak plot-derived K1 need to be converted to MBF by using the relation between the extraction fraction of gadolinium contrast agent and MBF. This study was conducted to determine the relation between extraction fraction of Gd-DTPA and MBF in human heart at rest and during stress. Thirty-four patients (19 men, mean age of 66.5 ± 11.0 years) with normal coronary arteries and no myocardial infarction were retrospectively evaluated. First-pass myocardial perfusion MRI during adenosine triphosphate stress and at rest was performed using a dual bolus approach to correct for saturation of the blood signal. Myocardial K1 was quantified by Patlak plot method. Mean MBF was determined from coronary sinus flow measured by phase contrast cine MRI and left ventricle mass measured by cine MRI. The extraction fraction of Gd-DTPA was calculated as the K1 divided by the mean MBF. The extraction fraction of Gd-DTPA was 0.46 ± 0.22 at rest and 0.32 ± 0.13 during stress (P < 0.001). The relationship between extraction fraction (E) and MBF in human myocardium can be approximated as E = 1 - exp(-(0.14 × MBF + 0.56)/MBF). The current results indicate that MBF can be accurately quantified by Patlak plot method of first-pass myocardial perfusion MRI by performing a correction of extraction fraction.

Comparison of myocardial perfusion estimates from dynamic contrast-enhanced magnetic resonance imaging with four quantitative analysis methods

Dynamic contrast-enhanced MRI has been used to quantify myocardial perfusion in recent years. Published results have varied widely, possibly depending on the method used to analyze the dynamic perfusion data. Here, four quantitative analysis methods (two-compartment modeling, Fermi function modeling, model-independent analysis, and Patlak plot analysis) were implemented and compared for quantifying myocardial perfusion. Dynamic contrast-enhanced MRI data were acquired in 20 human subjects at rest with low-dose (0.019 +/- 0.005 mmol/kg) bolus injections of gadolinium. Fourteen of these subjects were also imaged at adenosine stress (0.021 +/- 0.005 mmol/kg). Aggregate rest perfusion estimates were not significantly different between all four analysis methods. At stress, perfusion estimates were not significantly different between two-compartment modeling, model-independent analysis, and Patlak plot analysis. Stress estimates from the Fermi model were significantly higher (approximately 20%) than the other three methods. Myocardial perfusion reserve values were not significantly different between all four methods. Model-independent analysis resulted in the lowest model curve-fit errors. When more than just the first pass of data was analyzed, perfusion estimates from two-compartment modeling and model-independent analysis did not change significantly, unlike results from Fermi function modeling.

Quantitative analysis of first-pass contrast-enhanced myocardial perfusion MRI using a Patlak plot method and blood saturation correction

The objectives of this study were to develop a method for quantifying myocardial K(1) and blood flow (MBF) with minimal operator interaction by using a Patlak plot method and to compare the MBF obtained by perfusion MRI with that from coronary sinus blood flow in the resting state. A method that can correct for the nonlinearity of the blood time-signal intensity curve on perfusion MR images was developed. Myocardial perfusion MR images were acquired with a saturation-recovery balanced turbo field-echo sequence in 10 patients. Coronary sinus blood flow was determined by phase-contrast cine MRI, and the average MBF was calculated as coronary sinus blood flow divided by left ventricular (LV) mass obtained by cine MRI. Patlak plot analysis was performed using the saturation-corrected blood time-signal intensity curve as an input function and the regional myocardial time-signal intensity curve as an output function. The mean MBF obtained by perfusion MRI was 86 +/- 25 ml/min/100 g, showing good agreement with MBF calculated from coronary sinus blood flow (89 +/- 30 ml/min/100 g, r = 0.74). The mean coefficient of variation for measuring regional MBF in 16 LV myocardial segments was 0.11. The current method using Patlak plot permits quantification of MBF with operator interaction limited to tracing the LV wall contours, registration, and time delays.

Quantification of absolute myocardial blood flow by magnetic resonance perfusion imaging

By serially imaging the myocardium during the initial transit of gadolinium contrast, magnetic resonance perfusion imaging can accurately assess relative reductions in regional myocardial blood flow and identify hemodynamically significant coronary artery disease. Models can be used to quantify myocardial blood flow (in milliliters/minute/gram) on the basis of dynamic signal changes within the myocardium and left ventricular cavity. Although the mathematical modeling involved in this type of analysis adds complexity, the benefits of absolute blood flow quantification might improve clinical diagnosis and have important implications for cardiovascular research.

Estimating myocardial perfusion from dynamic contrast-enhanced CMR with a model-independent deconvolution method

BACKGROUND

Model-independent analysis with B-spline regularization has been used to quantify myocardial blood flow (perfusion) in dynamic contrast-enhanced cardiovascular magnetic resonance (CMR) studies. However, the model-independent approach has not been extensively evaluated to determine how the contrast-to-noise ratio between blood and tissue enhancement affects estimates of myocardial perfusion and the degree to which the regularization is dependent on the noise in the measured enhancement data. We investigated these questions with a model-independent analysis method that uses iterative minimization and a temporal smoothness regularizer. Perfusion estimates using this method were compared to results from dynamic 13N-ammonia PET.

RESULTS

An iterative model-independent analysis method was developed and tested to estimate regional and pixelwise myocardial perfusion in five normal subjects imaged with a saturation recovery turboFLASH sequence at 3 T CMR. Estimates of myocardial perfusion using model-independent analysis are dependent on the choice of the regularization weight parameter, which increases nonlinearly to handle large decreases in the contrast-to-noise ratio of the measured tissue enhancement data. Quantitative perfusion estimates in five subjects imaged with 3 T CMR were 1.1 +/- 0.8 ml/min/g at rest and 3.1 +/- 1.7 ml/min/g at adenosine stress. The perfusion estimates correlated with dynamic 13N-ammonia PET (y = 0.90x + 0.24, r = 0.85) and were similar to results from other validated CMR studies.

CONCLUSION

This work shows that a model-independent analysis method that uses iterative minimization and temporal regularization can be used to quantify myocardial perfusion with dynamic contrast-enhanced perfusion CMR. Results from this method are robust to choices in the regularization weight parameter over relatively large ranges in the contrast-to-noise ratio of the tissue enhancement data.

Quantification of MRI measured myocardial perfusion reserve in healthy humans: a comparison with positron emission tomography

PURPOSE

To validate a noninvasive quantitative MRI technique, the K(i) perfusion method, for myocardial perfusion in humans using (13)N-ammonia PET as a reference method.

MATERIALS AND METHODS

Ten healthy males (64 +/- 8 years) were examined with combined PET and MRI perfusion imaging at rest and during stress induced by dipyridamole in order to determine the myocardial perfusion reserve. Myocardial and blood time concentration curves obtained by Gd-DTPA-enhanced MRI and (13)N-ammonia PET were fitted by a two-compartment perfusion model.

RESULTS

Mean perfusion values (+/-SD) derived from the MRI method at rest and at hyperemia were 80 +/- 20 and 183 +/- 56 mL/min/100 g, respectively. The same data for PET were 71 +/- 16 and 203 +/- 67 mL/min/100 g. A linear relationship was observed between MRI and PET-derived myocardial perfusion reserve for regional and global data. Linear regression for the global absolute perfusion reserve gave a correlation coefficient of 0.96 (P < 0.004, y=0.83x-6.9). A good agreement between the two methods to determine low or high perfusion reserves was found.

CONCLUSION

Our data provide validation of the perfusion marker K(i) derived by the MRI method as a quantitative marker for myocardial perfusion in healthy humans.

Myocardial perfusion assessment by use of system identification method in a one-compartment model

Cardiovascular magnetic resonance has been shown to provide high data quality for myocardial perfusion assessment. However, to analyze the perfusion data, some signal processing and modeling is needed to correct for motion related artifacts and limited spatial resolution. This study describes a method based on system identification, allowing, after a first step of image registration, to integrate and correct the partial volume effect in the myocardium perfusion quantification. This method is then applied to patients with coronary artery disease or hypertrophic obstructive cardiomyopathy.

Evaluation of three different kinetic models for use with myocardial perfusion MRI data

Coronary artery disease (CAD), a leading cause of death in the US and worldwide, can be effectively diagnosed and assessed using non-invasive myocardial perfusion MRI. Tracer kinetic models play a crucial role in the analysis and quantification of perfusion. In this work, we evaluate the performance of 3 different kinetic models used to analyze perfusion: (a) a modified 2-compartment model (b) the Johnson-Wilson (JW) model and (c) a modified JW model. We hypothesized that three different models would give statistically different results and that the modified JW model would be better than the other two because it would most closely model the underlying physiological processes. Results indicate that the models are statistically different from each other but the 2-compartment model is more stable than both models (b) and (c) and that the modified JW model is the most sensitive to ischemia as compared to the others.

Model-based registration for dynamic cardiac perfusion MRI

PURPOSE

To assess the accuracy of a model-based approach for registration of myocardial dynamic contrast-enhanced (DCE)-MRI corrupted by respiratory motion.

MATERIALS AND METHODS

Ten patients were scanned for myocardial perfusion on 3T or 1.5T scanners, and short- and long-axis slices were acquired. Interframe registration was done using an iterative model-based method in conjunction with a mean square difference metric. The method was tested by comparing the absolute motion before and after registration, as determined from manually registered images. Regional flow indices of myocardium calculated from the manually registered data were compared with those obtained with the model-based registration technique.

RESULTS

The mean absolute motion of the heart for the short-axis data sets over all the time frames decreased from 5.3+/-5.2 mm (3.3+/-3.1 pixels) to 0.8+/-1.3 mm (0.5+/-0.7 pixels) in the vertical direction, and from 3.0+/-3.7 mm (1.7+/-2.1 pixels) to 0.9+/-1.2 mm (0.5+/-0.7 pixels) in the horizontal direction. A mean absolute improvement of 77% over all the data sets was observed in the estimation of the regional perfusion flow indices of the tissue as compared to those obtained from manual registration. Similar results were obtained with two-chamber-view long-axis data sets.

CONCLUSION

The model-based registration method for DCE cardiac data is comparable to manual registration and offers a unique registration method that reduces errors in the quantification of myocardial perfusion parameters as compared to those obtained from manual registration.

T1 measurement using a short acquisition period for quantitative cardiac applications

Myocardial signal intensity curves for myocardial perfusion studies may be made quantitative by the use of T1 measurements made after the first-pass of contrast agent. A short data acquisition method for T1 mapping is presented in which all data for each T1 map are acquired in a short breath hold, and the slice geometry and timing in the cardiac cycle exactly match that of the dynamic first-pass perfusion sequence. This allows accurate image registration of the T1 map with the first-pass series of images. The T1 method is based on varying the preparation-pulse delay time of a saturation recovery sequence, and in this implementation employs an ECG-triggered, single-shot, spoiled gradient echo technique with SENSE reconstruction. The method allows T1 estimates of three slices to be made in fifteen heartbeats. For a range of samples with T1 values equivalent to those found in the myocardium during the first-pass of contrast agent, T1 estimates were accurate to within 6%, and the variation between slices was 2% or less.

Evaluation of heart perfusion in patients with acute myocardial infarction using dynamic contrast-enhanced magnetic resonance imaging

PURPOSE

To investigate the diagnostic ability of quantitative magnetic resonance imaging (MRI) heart perfusion in acute heart patients, a fast, multislice dynamic contrast-enhanced MRI sequence was applied to patients with acute myocardial infarction.

MATERIALS AND METHODS

Seven patients with acute transmural myocardial infarction were studied using a Turbo-fast low angle shot (FLASH) MRI sequence to monitor the first pass of an extravascular contrast agent (CA), gadolinium diethylene triamine pentaacetic acid (Gd-DTPA). Quantitation of perfusion, expressed as Ki (mL/100 g/minute), in five slices, each having 60 sectors, provided an estimation of the severity and extent of the perfusion deficiency. Reperfusion was assessed both by noninvasive criteria and by coronary angiography (CAG).

RESULTS

The Ki maps clearly delineated the infarction in all patients. Thrombolytic treatment was clearly beneficial in one case, but had no effect in the two other cases. Over the time-course of the study, normal perfusion values were not reestablished following thrombolytic treatment in all cases investigated.

CONCLUSION

This study shows that quantitative MRI perfusion values can be obtained from acutely ill patients following acute myocardial infarction. The technique provides information on both the volume and severity of affected myocardial tissue, enabling the power of treatment regimes to be assessed objectively, and this approach should aid individual patient stratification and prognosis.

Inflow effect correction in fast gradient-echo perfusion imaging

The purposes of this study were to assess the extent of the inflow effect on signal intensity (SI) for fast gradient-recalled-echo (GRE) sequences used to observe first-pass perfusion, and to develop and validate a correction method for this effect. A phantom experiment with a flow apparatus was performed to determine SI as a function of Gd-DTPA concentration for various velocities. Subsequently a flow-sensitive calibration method was developed, and validated on bolus injections into an open-circuit flow apparatus and in vivo. It is shown that calibration methods based on static phantoms are not appropriate for accurate signal-to-concentration conversion in images affected by high flow. The flow-corrected calibration method presented here can be used to improve the accuracy and robustness of the arterial input function (AIF) determination for tissue perfusion quantification using MRI and contrast media.

Inflow effect in first-pass cardiac and renal MRI

PURPOSE

To estimate the effect of the inflow effect on the arterial input function in vivo in cardiac and renal MR perfusion imaging using fast gradient echo (GRE) sequences and contrast media.

MATERIALS AND METHODS

The MR exam protocol was designed to acquire images at different phases of the cardiac cycle. The arterial input was thus influenced by various blood flow velocities.

RESULTS

It was found that the inflow effect was negligible in the left ventricle of the heart, while it was significantly higher in the aorta for the kidney perfusion measurement. This was principally due to the higher through-the-plane component of the blood flow velocity in the aorta than in the left ventricle.

CONCLUSION

The inflow effect can be neglected in the heart cavity, but should be taken into account in renal perfusion.

Comparison of temporal filtering methods for dynamic contrast MRI myocardial perfusion studies

Dynamic contrast myocardial perfusion studies may benefit from methods that speed up the acquisition. Unaliasing by Fourier encoding the overlaps using the temporal dimension (UNFOLD), and a similar linear interpolation method have been shown to be effective at reducing the number of phase encodes needed for cardiac wall motion studies by using interleaved sampling and temporal filtering. Here such methods are evaluated in cardiac dynamic contrast studies, with particular regard to the effects of the choice of filter and the interframe motion. Four different filters were evaluated using a motion-free canine study. Full k-space was acquired and then downsampled to allow for a measure of truth. The different filters gave nearly equivalent images and quantitative flow estimates compared to full k-space. The effect of respiratory motion on these schemes was graphically depicted, and the performance of the four temporal filters was evaluated in seven human subjects with respiratory motion present. The four filters provided images of similar quality. However, none of the filters were effective at eliminating motion artifacts. Motion registration methods or motion-free acquisitions may be necessary to make these reduced FOV approaches clinically useful.

Estimation of kinetic parameters without input functions: analysis of three methods for multichannel blind identification

Compartment modeling of dynamic medical image data implies that the concentration of the tracer over time in a particular region of the organ of interest is well modeled as a convolution of the tissue response with the tracer concentration in the blood stream. The tissue response is different for different tissues while the blood input is assumed to be the same for different tissues. The kinetic parameters characterizing the tissue responses can be estimated by multichannel blind identification methods. These algorithms use the simultaneous measurements of concentration in separate regions of the organ; if the regions have different responses, the measurement of the blood input function may not be required. Three blind identification algorithms are analyzed here to assess their utility in medical imaging: eigenvector-based algorithm for multichannel blind deconvolution; cross relations; and iterative quadratic maximum-likelihood (IQML). Comparisons of accuracy with conventional (not blind) identification techniques where the blood input is known are made as well. Tissue responses corresponding to a physiological two-compartment model are primarily considered. The statistical accuracies of estimation for the three methods are evaluated and compared for multiple parameter sets. The results show that IQML gives more accurate estimates than the other two blind identification methods.

Restoration of myocardial blood flow following percutaneous coronary balloon dilatation and stent implantation: assessment with qualitative and quantitative contrast-enhanced magnetic resonance imaging

AIM

To examine the serial use of magnetic resonance imaging (MRI) to evaluate regional myocardial perfusion changes following percutaneous coronary angioplasty and stent implantation (PTCA).

MATERIALS AND METHODS

Six patients with single vessel coronary artery disease (CAD) underwent contrast-enhanced first pass MRI immediately prior to (visit A) and within 7 days after (visit B) PTCA. Three sequential short axis slices were obtained after gadodiamide (Gd) bolus (0.025 mmol/kg(-1)) at rest and during adenosine. Each short axis was divided radially into eight regions of interest (ROIs). ROIs were anatomically assigned to a coronary artery territory (CAT). Stress and rest qualitative and quantitative (unidirectional extraction fraction constant (K(i)); index of myocardial perfusion reserve (MPRI) = stressK(i) / restK(i)) perfusion parameters were determined for ROI supplied by remote and stenosed/stented vessels for each visit.

RESULTS

In stented ROIs the number of ROIs demonstrating normal perfusion, as opposed to reversible perfusion deficits, increased. Qualitative perfusion assessment in remote CATs was unchanged. MPRI in stenotic CATs was lower than in remote CATs at visit A (P < 0.001). Following PTCA, MPRI increased in stented CATs (P < 0.001) but was unchanged in remote CATs.

CONCLUSION

Restoration of myocardial perfusion following PTCA can be delineated with qualitative and quantitative perfusion MRI. Although at present the investigation is technically complex and not perfectly sensitive or specific, MRI has the potential to be a valuable tool for patient follow-up and evaluation of revascularization strategy efficacy.

Myocardial blood flow quantification with MRI by model-independent deconvolution

Magnetic resonance (MR) imaging during the first pass of an injected contrast agent has been used to assess myocardial perfusion, but the quantification of blood flow has been generally judged as too complex for its clinical application. This study demonstrates the feasibility of applying model-independent deconvolution to the measured tissue residue curves to quantify myocardial perfusion. Model-independent approaches only require minimal user interaction or expertise in modeling. Monte Carlo simulations were performed with contrast-to-noise ratios typical of MR myocardial perfusion studies to determine the accuracy of the resulting blood flow estimates. With a B-spline representation of the tissue impulse response and Tikhonov regularization, the bias of blood flow estimates obtained by model-independent deconvolution was less than 1% in all cases for peak contrast to noise ratios in the range from 15:1 to 20:1. The relative dispersion of blood flow estimates in Monte Carlo simulations was less than 7%. Comparison of MR blood flow estimates against measurements with radio-isotope labeled microspheres indicated excellent linear correlation (R2 = 0.995, slope: 0.96, intercept: 0.06). It can be concluded from these studies that the application of myocardial blood flow quantification with MRI can be performed with model-independent methods, and this should support a more widespread use of blood flow quantification in the clinical environment.

Factor analysis of medical image sequences improves evaluation of first-pass MR imaging acquisitions for myocardial perfusion

RATIONALE AND OBJECTIVES

Factor analysis of medical image sequences (FAMIS) applied to gadolinium chelate-enhanced subsecond magnetic resonance (MR) imaging was evaluated as a postprocessing method for assessing myocardial perfusion in coronary artery disease (CAD).

MATERIALS AND METHODS

To assess the accuracy of motion correction, five normal volunteers underwent MR imaging at rest. Thirteen patients with well-documented CAD and no myocardial infarction underwent MR imaging at rest and after dipyridamole administration. After motion correction, a single myocardial tissue factor (FAMISt) image was obtained with FAMIS for each raw MR imaging series acquisition. To evaluate how FAMIS could improve the analysis of these acquisitions, five readers visually assessed myocardial perfusion with FAMISt and raw MR images, and a multicase, multireader receiver operating characteristic analysis was performed.

RESULTS

FAMISt images significantly improved detection of the perfusion defects when compared with raw MR images (P = .002). Areas under the receiver operating characteristic curves ranged from 0.84 to 0.93 with FAMISt images and from 0.48 to 0.85 with raw MR images.

CONCLUSION

FAMIS applied to first-pass MR imaging series provided myocardial perfusion images that improve the objective assessment of myocardial perfusion in patients with CAD.

FAST sequences optimization for contrast media pharmacokinetic quantification in tissue

The purpose of this study was to investigate the influence of the fast gradient-recalled echo (GRE) sequence parameters on the contrast dynamic range and signal sensitivity, to optimize the magnetic resonance (MR) sequence for contrast media pharmacokinetic assessment. Effects of the fast low-angle shot (FLASH), Fast acquisition at steady rate (FAST), and radiofrequency-spoiled (RF)-FAST sequence parameters were studied in vitro. The FAST sequence had the highest sensitivity in low gadolinium (Gd) concentration. The FLASH and RF-FAST sequences had a larger contrast dynamic range, but the FLASH images contained side band artifacts. Increasing the flip angle to 90 degrees raised the sensitivity of the FAST sequence and the contrast dynamic range of the RF-FAST sequence. The shortest possible TE was optimal for both contrast dynamics and imaging time. TI had an influence on the sensitivity of the FAST sequence only for small acquisition matrices. This study indicates the optimal parameters for contrast dynamics (RF-FAST, 90 degrees flip angle, shortest possible TE) and sensitivity (FAST, 90 degrees flip angle, long TI(eff)).

Method for quantitative mapping of dynamic MRI contrast agent uptake in human tumors

A method is presented for the acquisition and analysis of dynamic contrast-enhanced (DCE) MRI data, focused on the characterization of tumors in humans. Gadolinium (Gd) contrast was administered by bolus injection, and its effect was monitored in time by fast T1-weighted MRI. A simple algorithm was developed for automatic extraction of the arterial input function (AIF) from the DCE-MRI data. This AIF was used in the pixelwise pharmacokinetic determination of physiological vascular parameters in normal and tumor tissue. Maps were reconstructed to show the spatial distribution of parameter values. To test the reproducibility of the method 11 patients with different types of tumors were measured twice, and the rate of contrast agent uptake in the tumor was calculated. The results show that normalizing the DCE-MRI data using individual coregistered AIFs, instead of one common AIF for all patients, substantially reduces the variation between successive measurements. It is concluded that the proposed method enables the reproducible assessment of contrast agent uptake rates.

Gd-DTPA bolus tracking in the myocardium using T1 fast acquisition relaxation mapping (T1 FARM)

MRI methods currently used for bolus tracking in the myocardium, such as saturation recovery turbo-fast low-angle shot (FLASH) (srTFL), are limited by signal intensity (SI) saturation at high contrast agent (CA) concentrations. By using T1 fast acquisition relaxation mapping (T1 FARM), a Gd-DTPA bolus (0.075 vs. 0.025 mmol/kg) may be injected without causing saturation. This study tested the feasibility of in vivo T1 FARM bolus tracking under rest/stress conditions in seven beagles with multiple permanently occluded branches of the left anterior descending (LAD) coronary artery. Although it underestimated the myocardial perfusion reserve (MPR) measured ex vivo using radioactive microspheres (mean +/- SEM; 3.60 +/- 0.26), the MPR determined upon application of the modified Kety model (1.86 +/- 0.10) enabled distinction between normal and infarcted tissue. The partition coefficient (lambda) estimated at rest and stress using the modified Kety model underestimated ex vivo radioactive measurements in infarcted tissue (0.25 +/- 0.01 vs. 0.26 +/- 0.01 vs. 0.79 +/- 0.08 ml/g, P < 0.0001) yet was accurate in normal tissue (0.28 +/- 0.01 vs. 0.30 +/- 0.01 vs. 0.33 +/- 0.01 ml/g, P = NS). Thus, although unsuitable for myocardial viability assessment, T1 FARM bolus tracking shows potential for assessment of myocardial perfusion.

Quantification of the effect of water exchange in dynamic contrast MRI perfusion measurements in the brain and heart

Measurement of myocardial and brain perfusion when using exogenous contrast agents (CAs) such as gadolinium-DTPA (Gd-DTPA) and MRI is affected by the diffusion of water between compartments. This water exchange may have an impact on signal enhancement, or, equivalently, on the longitudinal relaxation rate, and could therefore cause a systematic error in the calculation of perfusion (F) or the perfusion-related parameter, the unidirectional influx constant over the capillary membranes (K(i)). The aim of this study was to quantify the effect of water exchange on estimated perfusion (F or K(i)) by using a realistic simulation. These results were verified by in vivo studies of the heart and brain in humans. The conclusion is that water exchange between the vascular and extravascular extracellular space has no effect on K(i) estimation in the myocardium when a normal dose of Gd-DTPA is used. Water exchange can have a significant effect on perfusion estimation (F) in the brain when using Gd-DTPA, where it acts as an intravascular contrast agent.

Myocardial flow reserve parametric map, assessed by first-pass MRI compartmental analysis at the chronic stage of infarction

Regional myocardial flow and flow reserve (MFR) were assessed by compartmental analysis of Gd-enhanced MRI first-pass data in 7 patients with atypical chest pain, and in 15 patients with previous transmural myocardial infarction. The FE product (Flow x Extraction coefficient), derived from the modified Kety equation, was measured in regions corresponding to the Tetrofosmine-SPECT fixed defect and in remote normal regions. The FE product at rest and hyperemic FE product were similar in healed revascularized tissues (70.5 +/- 15.6 and 112.5 +/- 19.5 ml/mn/100 g, respectively) and in normal myocardium (76.2 +/- 18.3 and 142.2 +/- 33.0, respectively). In contrast, the FE index (48.8 +/- 15.2 and 60.7 +/- 18.0, respectively, P < 0.01 versus the two previous groups) and the MFR (1.27 +/- 0.20 vs. 1.91 +/- 0.29 in normal regions) were reduced in healed fibrotic tissues when the infarct-related artery remained occluded. Myocardial flow reserve maps allowed correct identification of regions corresponding to an occluded infarct-related artery.

Limb and skeletal muscle blood flow measurements at rest and during exercise in human subjects

The aim of the present review is to present techniques used for measuring blood flow in human subjects and advice as to when they may be applicable. Since blood flow is required to estimate substrate fluxes, energy turnover and metabolic rate of skeletal muscle, accurate measurements of blood flow are of extreme importance. Several techniques have therefore been developed to enable estimates to be made of the arterial inflow to, venous outflow from, or local blood flow within the muscle. Regional measurements have been performed using electromagnetic flow meters, plethysmography, indicator methods (e.g. thermodilution and indo-cyanine green dye infusion), ultrasound Doppler, and magnetic resonance velocity imaging. Local estimates have been made using 133Xe clearance, microdialysis, near i.r. spectroscopy, positron emission tomography and laser Doppler. In principle, the aim of the study, the type of interventions and the limitations of each technique determine which method may be most appropriate. Ultrasound Doppler and continuous indo-cyanine green dye infusion gives the most accurate limb blood flow measurements at rest. Moreover, the ultrasound Doppler is unique, as it does not demand a steady-state, and because its high temporal resolution allows detection of normal physiological variations as well as continuous measurements during transitional states such as at onset of and in recovery from exercise. During steady-state exercise thermodilution can be used in addition to indo-cyanine green dye infusion and ultrasound Doppler, where the latter is restricted to exercise modes with a fixed vessel position. Magnetic resonance velocity imaging may in addition be used to determine blood flow within deep single vessels. Positron emission tomography seems to be the most promising tool for local skeletal muscle blood-flow measurements in relation to metabolic activity, although the mode and intensity of exercise will be restricted by the apparatus design.

Quantification of myocardial perfusion with FAST sequence and Gd bolus in patients with normal cardiac function

The present study reports on a new calibration of the magnetic resonance imaging (MRI) signal intensity of a fast gradient-echo sequence used for in vivo myocardial perfusion quantification in patients. The signal from a FAST sequence preceded by a arrhythmia-insensitive magnetization preparation was calibrated in vitro using tubes filled with various gadolinium (Gd) solutions. Single short-axis views of the heart were obtained in patients (n = 10) with normal cardiac function. Myocardial and blood signal intensity were converted to concentration of Gd according to the in vitro calibration curve and fitted by a one-compartment model. K1 [first-order transfer constant from the blood to the myocardium for the gadolinium-diethylenetriamine-pentaacetic acid (Gd-DTPA)] and Vd (distribution volume of Gd-DTPA in myocardium) obtained from the fit of the MRI-derived perfusion curves were 0.72+/-0.22 (mL/min/g) and 15.3+/-5.22%. These results were in agreement with previous observations on animals and demonstrated that a reliable measurement of myocardial perfusion can be obtained by MRI in patients with an in vitro calibration procedure.