Absolute cerebral blood flow measured by dynamic susceptibility contrast MRI: a direct comparison with Xe-133 SPECT

Pattern recognition analysis of dynamic susceptibility contrast (DSC)‐MRI curves automatically segments tissue areas with intact blood–brain barrier in a rat stroke model: A feasibility and comparison study

Background

The manual segmentation of intact blood–brain barrier (BBB) regions in the stroke brain is cumbersome, due to the coexistence of infarction, large blood vessels, ventricles, and intact BBB regions, specifically in areas with weak signal enhancement following contrast agent injection.

Hypothesis

That from dynamic susceptibility contrast (DSC)‐MRI alone, without user intervention, regions of weak BBB damage can be segmented based on the leakage‐related parameter K 2 and the extent of intact BBB regions, needed to estimate K 2 values, determined.

Study Type

Feasibility.

Animal Model

Ten female Sprague–Dawley rats (SD, 200–250g) underwent 1‐hour middle carotid artery occlusion (MCAO) and 1‐day reperfusion. Two SD rats underwent 1‐hour MCAO with 3‐day and 5‐day reperfusion.

Field Strength/Sequence

7T; ADC and T1 maps using diffusion‐weighted echo planar imaging (EPI) and relaxation enhancement (RARE) with variable repetition time (TR), respectively. dynamic contrast‐enhanced (DCE)‐MRI using FLASH. DSC‐MRI using gradient‐echo EPI.

Assessment

Constrained nonnegative matrix factorization (cNMF) was applied to the dynamic ‐curves of DSC‐MRI (<4 min) in a BBB‐disrupted rat model. Areas of voxels with intact BBB, classified by automated cNMF analyses, were then used in estimating K 1 and K 2 values, and compared with corresponding values from manually‐derived areas.

Statistical Tests

Mean ± standard deviation of ΔT1‐differences between ischemic and healthy areas were displayed with unpaired Student's t‐tests. Scatterplots were displayed with slopes and intercepts and Pearson's r values were evaluated between K 2 maps obtained with automatic (cNMF)‐ and manually‐derived regions of interest (ROIs) of the intact BBB region.

Results

Mildly BBB‐damaged areas (indistinguishable from DCE‐MRI (10 min) parameters) were automatically segmented. Areas of voxels with intact BBB, classified by automated cNMF, matched closely the corresponding, manually‐derived areas when respective areas were used in estimating K 2 maps (Pearson's r = 0.97, 12 slices).

Data Conclusion

Automatic segmentation of short DSC‐MRI data alone successfully identified areas with intact and compromised BBB in the stroke brain and compared favorably with manual segmentation.

Level of Evidence: 3

Technical Efficacy: Stage 1

J. Magn. Reson. Imaging 2020;51:1369–1381.

25 Years of Contrast-Enhanced MRI: Developments, Current Challenges and Future Perspectives

In 1988, the first contrast agent specifically designed for magnetic resonance imaging (MRI), gadopentetate dimeglumine (Magnevist(®)), became available for clinical use. Since then, a plethora of studies have investigated the potential of MRI contrast agents for diagnostic imaging across the body, including the central nervous system, heart and circulation, breast, lungs, the gastrointestinal, genitourinary, musculoskeletal and lymphatic systems, and even the skin. Today, after 25 years of contrast-enhanced (CE-) MRI in clinical practice, the utility of this diagnostic imaging modality has expanded beyond initial expectations to become an essential tool for disease diagnosis and management worldwide. CE-MRI continues to evolve, with new techniques, advanced technologies, and novel contrast agents bringing exciting opportunities for more sensitive, targeted imaging and improved patient management, along with associated clinical challenges. This review aims to provide an overview on the history of MRI and contrast media development, to highlight certain key advances in the clinical development of CE-MRI, to outline current technical trends and clinical challenges, and to suggest some important future perspectives.

FUNDING

Bayer HealthCare.

Arterial input function and gray matter cerebral blood volume measurements in children

Purpose

To investigate how arterial input functions (AIFs) vary with age in children and compare the use of individual and population AIFs for calculating gray matter CBV values. Quantitative measures of cerebral blood volume (CBV) using dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI) require measurement of an AIF. AIFs are affected by numerous factors including patient age. Few data presenting AIFs in the pediatric population exists.

Materials and Methods

Twenty‐two previously treated pediatric brain tumor patients (mean age, 6.3 years; range, 2.0–15.3 years) underwent DSC‐MRI scans on a 3T MRI scanner over 36 visits. AIFs were measured in the middle cerebral artery. A functional form of an adult population AIF was fitted to each AIF to obtain parameters reflecting AIF shape. The relationship between parameters and age was assessed. Correlations between gray matter CBV values calculated using the resulting population and individual patient AIFs were explored.

Results

There was a large variation in individual patient AIFs but correlations between AIF shape and age were observed. The center (r = 0.596, P < 0.001) and width of the first‐pass peak (r = 0.441, P = 0.007) were found to correlate significantly with age. Intrapatient coefficients of variation were significantly lower than interpatient values for all parameters (P < 0.001). Differences in CBV values calculated with an overall population and age‐specific population AIF compared to those calculated with individual AIFs were 31.3% and 31.0%, respectively.

Conclusion

Parameters describing AIF shape correlate with patient age in line with expected changes in cardiac output. In pediatric DSC‐MRI studies individual patient AIFs are recommended. J. Magn. Reson. Imaging 2016;43:981–989

Automated macrovessel artifact correction in dynamic susceptibility contrast magnetic resonance imaging using independent component analysis

Dynamic susceptibility contrast-MRI is the most commonly used functional MRI-based method for studying changes in cerebral perfusion. However, several studies indicated a systematic overestimation of perfusion parameters compared with other imaging modalities related to the high sensitivity of dynamic susceptibility contrast-MRI for blood flow in large vessels. In this study, we therefore suggest an improved, automated, robust, and efficient method allowing for generating hemodynamic parameter maps where signal influence from large vessels is minimized. Based on independent component analysis, this fully automated approach corrects dynamic susceptibility contrast-MRI data without any user interaction, thus making a clinical applicability possible. The accuracy of the proposed method was tested in 10 patients with cerebrovascular disease. Application of our correction algorithm resulted in a significant reduction of the effect of macrovessel signal on hemodynamic parameters like the cerebral blood flow and the cerebral blood volume compared with uncorrected data. As desired, our method specifically corrected for macrovessel artifacts in cortical grey matter tissue, leaving white matter tissue parameters largely unaffected. This may increase sensitivity and reliability of detecting perfusion abnormalities in patient groups, in particular with regard to stroke and other cerebrovascular disorders.

Quantitative blood flow measurements in the small animal cardiopulmonary system using digital subtraction angiography

PURPOSE

The use of preclinical rodent models of disease continues to grow because these models help elucidate pathogenic mechanisms and provide robust test beds for drug development. Among the major anatomic and physiologic indicators of disease progression and genetic or drug modification of responses are measurements of blood vessel caliber and flow. Moreover, cardiopulmonary blood flow is a critical indicator of gas exchange. Current methods of measuring cardiopulmonary blood flow suffer from some or all of the following limitations--they produce relative values, are limited to global measurements, do not provide vasculature visualization, are not able to measure acute changes, are invasive, or require euthanasia.

METHODS

In this study, high-spatial and high-temporal resolution x-ray digital subtraction angiography (DSA) was used to obtain vasculature visualization, quantitative blood flow in absolute metrics (ml/min instead of arbitrary units or velocity), and relative blood volume dynamics from discrete regions of interest on a pixel-by-pixel basis (100 x 100 microm2).

RESULTS

A series of calibrations linked the DSA flow measurements to standard physiological measurement using thermodilution and Fick's method for cardiac output (CO), which in eight anesthetized Fischer-344 rats was found to be 37.0 +/- 5.1 ml/min. Phantom experiments were conducted to calibrate the radiographic density to vessel thickness, allowing a link of DSA cardiac output measurements to cardiopulmonary blood flow measurements in discrete regions of interest. The scaling factor linking relative DSA cardiac output measurements to the Fick's absolute measurements was found to be 18.90 x CODSA = COFick.

CONCLUSIONS

This calibrated DSA approach allows repeated simultaneous visualization of vasculature and measurement of blood flow dynamics on a regional level in the living rat.

Absolute quantification of cerebral blood flow in normal volunteers: correlation between Xe-133 SPECT and dynamic susceptibility contrast MRI

PURPOSE

To compare absolute cerebral blood flow (CBF) estimates obtained by dynamic susceptibility contrast MRI (DSC-MRI) and Xe-133 SPECT.

MATERIALS AND METHODS

CBF was measured in 20 healthy volunteers using DSC-MRI at 3T and Xe-133 SPECT. DSC-MRI was accomplished by gradient-echo EPI and CBF was calculated using a time-shift-insensitive deconvolution algorithm and regional arterial input functions (AIFs). To improve the reproducibility of AIF registration the time integral was rescaled by use of a venous output function. In the Xe-133 SPECT experiment, Xe-133 gas was inhaled over 8 minutes and CBF was calculated using a biexponential analysis.

RESULTS

The average whole-brain CBF estimates obtained by DSC-MRI and Xe-133 SPECT were 85 +/- 23 mL/(min 100 g) and 40 +/- 8 mL/(min 100 g), respectively (mean +/- SD, n = 20). The linear CBF relationship between the two modalities showed a correlation coefficient of r = 0.76 and was described by the equation CBF(MRI) = 2.4 . CBF(Xe)-7.9 (CBF in units of mL/(min 100 g)).

CONCLUSION

A reasonable positive linear correlation between MRI-based and SPECT-based CBF estimates was observed after AIF time-integral correction. The use of DSC-MRI typically results in overestimated absolute perfusion estimates and the present study indicates that this trend is further enhanced by the use of high magnetic field strength (3T).

Hemodynamic studies on brain CT perfusion imaging with varied injection rates

OBJECTIVE

This study aimed to determine a contrast medium injection rate that ensures both accuracy for data and safety for operation by comparing hemodynamic parameters of brain CT perfusion imaging with varied injection rates.

METHODS

Twenty-four healthy volunteers were divided into three groups based on contrast medium injection rates (4.5, 6.0, and 7.5 ml/s). For all subjects, CT perfusion scanning was started at 4 s after antecubital venous bolus of contrast media injection. A perfusion-analyzing software package was used to produce a time-density curve in the anterior cerebral artery and the superior sagittal sinus and calculate the regional cerebral blood flow (rCBF) in the gray matter and the white matter. The hemodynamic indices were compared among the three groups, and statistical analysis was carried out using the F test.

RESULTS

The time for the arterial rise to reach the peak value for the 7.5-ml/s group was only 0.2 s ahead of the initiation time for the rise of the superior sagittal sinus. The differences of rCBF in the gray matter and the white matter among the three groups were statistically significant. rCBF in the gray matter and the white matter for the 7.5-ml/s group was 52.8 ml x min(-1) 100 g(-1) . (+/-3.1) and 21.9 ml x min(-1) . 100 g(-1) (+/-2.4), respectively.

CONCLUSIONS

The use of the 7.5-ml/s injection rate can meet the prerequisite of the maximum slope model, and the resulting rCBF can be very close to that measured by positron emission tomography. Therefore, 7.5 ml/s was an ideal contrast medium injection rate.

Regional cerebral blood flow and blood volume in patients with subcortical arteriosclerotic encephalopathy (SAE)

The aim of the present study was a detailed analysis of the regional cerebral blood flow and blood volume in patients with subcortical arteriosclerotic encephalopathy (SAE) by means of functional magnetic resonance imaging (MRI). A group of 26 patients with SAE and a group of 16 age-matched healthy volunteers were examined. Using a well-established dynamic susceptibility contrast-enhanced MRI method, the regional cerebral blood flow (rCBF) and blood volume (rCBV) were quantified for each subject in 12 different regions in the brain parenchyma. As compared to healthy volunteers, patients with SAE showed significantly reduced rCBF and rCBV values in white matter regions and in the occipital cortex. Regions containing predominantly grey matter show almost normal rCBF and rCBV values. In conclusion, quantitative analysis of rCBF and rCBV values demonstrates clearly that SAE is a disease that is associated with a reduced microcirculation predominantly in white matter.

Calculation of cerebral perfusion parameters using regional arterial input functions identified by factor analysis

PURPOSE

To calculate regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and regional mean transit time (rMTT) accurately, an arterial input function (AIF) is required. In this study we identified a number of AIFs using factor analysis of dynamic studies (FADS), and performed the cerebral perfusion calculation pixel by pixel using the AIF that was located geometrically closest to a certain voxel.

MATERIALS AND METHODS

To verify the robustness of the method, simulated images were generated in which dispersion or delay was added in some arteries and in the corresponding cerebral gray matter (GM), white matter (WM), and ischemic tissue. Thereafter, AIFs were determined using the FADS method and simulations were performed using different signal-to-noise ratios (SNRs). Simulations were also carried out using an AIF from a single pixel that was manually selected. In vivo results were obtained from normal volunteers and patients.

RESULTS

The FADS method reduced the underestimation of rCBF due to dispersion or delay that often occurs when only one AIF represents the entire brain.

CONCLUSION

This study indicates that the use of FADS and the nearest-AIF method is preferable to manual selection of one single AIF.

Magnetic resonance brain perfusion imaging with voxel-specific arterial input functions

PURPOSE

To propose an automatic method for estimating voxel-specific arterial input functions (AIFs) in dynamic contrast brain perfusion imaging.

MATERIALS AND METHODS

Voxel-specific AIFs were estimated blindly using the theory of homomorphic transformations and complex cepstrum analysis. Wiener filtering was used in the subsequent deconvolution. The method was verified using simulated data and evaluated in 10 healthy adults.

RESULTS

Computer simulations accurately estimated differently shaped, normalized AIFs. Simple Wiener filtering resulted in underestimation of flow values. Preliminary in vivo results showed comparable cerebral flow value ratios between gray matter (GM) and white matter (WM) when using blindly estimated voxel-specific AIFs or a single manually selected AIF. Significant differences (P < or = 0.0125) in mean transit time (MTT) and time-to-peak (TTP) in GM compared to WM was seen with the new method.

CONCLUSION

Initial results suggest that the proposed method can replace the tedious and difficult task of manually selecting an AIF, while simultaneously providing better differentiation between time-dependent hemodynamic parameters.

Association between supine cerebral perfusion and symptomatic orthostatic hypotension

The goal of this study was to investigate whether the supine resting perfusion of brain tissue in symptomatic patients suffering from orthostatic hypotension (OH) is changed compared to control subjects and whether an association exists between the resting perfusion and the severity of OH. Ten symptomatic OH patients and 8 control subjects were included in this study. One patient was retrospectively excluded because he suffered from multiple system atrophy. Systolic and diastolic blood pressure changes were measured during a tilting bed procedure. Cerebral blood flow, cerebral blood volume and mean transit time were determined by bolus-tracking perfusion MRI and correlated with blood pressure changes. Cerebral blood volume was significantly increased in OH patients compared with control subjects for white matter (P = 0.019) and the mean transit time was significantly increased for gray (P = 0.010) and white matter (P = 0.015). The cerebral blood flow of the gray (r = 0.74, P = 0.022) and white matter (r = 0.75, P = 0.020) was significantly, positively correlated with systolic blood pressure changes. The mean transit time in white matter was significantly, negatively correlated with systolic blood pressure changes (r = -0.68, P = 0.045). This study suggests that in symptomatic patients with OH the cerebral perfusion of the brain in the resting, supine position correlates with the severity of OH as measured by postural changes in blood pressure.

The impact of partial-volume effects in dynamic susceptibility contrast magnetic resonance perfusion imaging

PURPOSE

To demonstrate the degree of the cerebral blood flow (CBF) estimation bias that could arise from distortion of the arterial input function (AIF) as a result of partial-volume effects (PVEs) in dynamic susceptibility contrast (DSC) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

A model of the volume fraction an artery occupies in a voxel was devised, and a mathematical relationship between the amount of PVE and the measured baseline MR signal intensity was derived. Based on this model, simulation studies were performed to assess the impact of PVE on CBF. Furthermore, the effectiveness of linear PVE compensation approaches on the concentration function was investigated.

RESULTS

Simulation results showed a nonlinear relationship between PVE and the resulting CBF measurement error. In addition to AIF underestimation, PVE also causes distortions of AIF frequency characteristics, leading to CBF errors varying with mean transit time (MTT). An uncorrected AIF measured at a voxel with a partial-volume fraction of <or=50% could produce a CBF overestimation of more than fourfold. Linear compensation of the concentration curves did not produce correct CBF estimates.

CONCLUSION

PVE can induce significant CBF estimation biases. In addition, the MTT dependence of CBF accuracy raises doubts of the validity of adopting a single cross-calibration factor (i.e., setting normal white matter to 22 mL minute(-1) (100 g)(-1)) to obtain CBF values with absolute units. The impact of PVE may be reduced by decreasing the maximum arterial signal drop in the perfusion images. To correct the AIF distortions introduced by PVE, the nonlinear relationship between the impact of PVE on MR signal intensity and contrast concentration function must be considered.

Aspects on the accuracy of cerebral perfusion parameters obtained by dynamic susceptibility contrast MRI: a simulation study

Several studies have indicated that deconvolution based on singular value decomposition (SVD) is a robust concept for retrieval of cerebral blood flow in dynamic susceptibility contrast (DSC) MRI. However, the behavior of the technique under typical experimental conditions has not been completely investigated. In the present study, cerebral perfusion was simulated using different temporal resolutions, different signal-to-noise ratios (S/Ns), different shapes of the arterial input function (AIF), different signal drops, and different cut-off levels in the SVD deconvolution. Using Zierler's area-to-height relationship in combination with the central volume theorem, calculations of regional cerebral blood volume (rCBV), regional cerebral blood flow (rCBF), and regional mean transit time (rMTT) were accomplished, based on simulated DSC-MRI signal curves corresponding to artery, gray matter (GM), white matter (WM), and ischemic tissue. Gaussian noise was added to the noise-free signal curves to generate different S/Ns. We studied image time intervals of 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 s, as well as different degrees of signal decrease. The singular-value threshold in the SVD procedure and the shape of the AIF were also varied. Increased rCBF was seen when noise was added, especially for rCBF in WM at the larger image time intervals. The rCBF showed large standard deviations using a low threshold value. A prolonged time interval led to a lower absolute value of rCBF both in GM and WM, and a low/broad AIF also underestimated the rCBF. When a larger maximal signal decrease was assumed, smaller standard deviations were observed. No systematic change of the average rCBV was observed with increasing noise or with increasing image time interval. At S/N = 40, a low cut-off value resulted in an rCBF that was closer to the true value. Furthermore, at low S/N it was difficult to differentiate ischemic tissue from WM.

Cerebral perfusion assessment by bolus tracking using hyperpolarized13C

Cerebral perfusion was assessed with 13C MRI in a rat model after intravenous injections of the 13C-labeled compound bis-1,1-(hydroxymethyl)-1-13C-cyclopropane-D8 in aqueous solutions hyperpolarized by dynamic nuclear polarization (DNP). Since the tracer acted as a direct signal source, several of the problems associated with techniques based on traditional dynamic susceptibility contrast (DSC) MRI contrast agents were avoided. Maps of cerebral blood flow (CBF), cerebral blood volume (CBV), and mean transit time (MTT) were calculated. The MTT was determined to be 2.8 +/- 0.8 sec. However, arterial partial-volume effects in the animal model prevented accurate absolute quantification of CBF and CBV. It was demonstrated that depolarization of the hyperpolarized 13C tracer via relaxation and the imaging sequence had little influence on CBF assessment when the time resolution of the imaging sequence was short compared to the MTT. However, CBV and MTT were increasingly underestimated as MTT or the depolarization rate increased if depolarization was not taken into account. With a modified bolus-tracking theory depolarization could be compensated for, assuming that the depolarization rate was known. Three separate compensation methods were investigated experimentally and by numerical simulations.

Absolute quantification of cerebral blood flow with magnetic resonance, reproducibility of the method, and comparison with H2(15)O positron emission tomography

While H2(15)O positron emission tomography (PET) is still the gold standard in the quantitative assessment of cerebral perfusion (rCBF), its technical challenge, limited availability, and radiation exposure are disadvantages of the method. Recent work demonstrated the feasibility of magnetic resonance (MR) for quantitative cerebral perfusion imaging. There remain open questions, however, especially regarding reproducibility. The main purpose of this study was to assess the accuracy and reproducibility of MR-derived flow values to those derived from H2(15)O PET. Positron emission tomography and MR perfusion imaging was performed in 20 healthy male volunteers, who were chronic smokers, on day 1 and day 3 of a 4-day hospitalization. Subjects were randomly assigned to one of two groups, each with 10 subjects. One group was allowed to smoke as usual during the hospitalization, while the other group stopped smoking from day 2. Positron emission tomography and MR images were coregistered and rCBF was determined in two regions of interest, defined over gray matter (gm) and white matter (wm), yielding rCBF(PET)gm, rCBF(MR)gm, rCBF(PET)wm, and rCBF(MR)wm. Bland-Altman analysis was used to investigate reproducibility by assessing the difference rCBFday3 - rCBFday1 in eight continual-smoker volunteers. The analysis showed a good reproducibility for PET, but not for MR. Mean +/- SD of the difference rCBFday3 - rCBFday1 in gray matter was 6.35 +/- 21.06 and 0.49 +/- 5.27 mL x min(-1) x 100 g(-1) for MR and PET, respectively; the corresponding values in white matter were 2.60 +/- 15.64 and -1.14 +/- 4.16 mL x min(-1) x 100 g(-1). The Bland-Altman analysis was also used to assess MRI and PET agreement comparing rCBF measured on day 1. The analysis demonstrated a reasonably good agreement of MR and PET in white matter (rCBF(PET)wm - rCBF(MR)wm; -0.09 +/- 7.23 mL x min(-1) x 100 g(-1)), while in gray matter a reasonable agreement was only achieved after removing vascular artifacts in the MR perfusion maps (rCBF(PET)gm - rCBF(MR)gm; -11.73 +/- 14.52 mL x min(-1) x 100 g(-1)). In line with prior work, these results demonstrate that reproducibility was overall considerably better for PET than for MR. Until reproducibility is improved and vascular artifacts are efficiently removed, MR is not suitable for reliable quantitative perfusion measurements.

Different time evolution of oxyhemoglobin and deoxyhemoglobin concentration changes in the visual and motor cortices during functional stimulation: a near-infrared spectroscopy study

Neurovascular coupling is the generic term for changes in cerebral metabolic rate of oxygen (CMRO(2)), cerebral blood flow, and cerebral blood volume related to brain activity. The goal of this paper is to better understand the effects of neurovascular coupling in the visual and motor cortices using frequency-domain near-infrared spectroscopy. Maps of concentration changes in oxyhemoglobin [O(2)Hb], deoxyhemoglobin [HHb], and total hemoglobin of the visual and motor cortices were generated during stimulation using a reversing checkerboard screen and palm-squeezing, respectively. Seven healthy volunteers of 18-37 years of age were included. In the visual cortex the patterns of [O(2)Hb] and [HHb] were strongly linearly correlated (r(2) > 0.8 in 13 of a total of 24 locations). In 20 locations the change in [O(2)Hb] was larger than 0.25 microM. The mean slope of the linear regression between [O(2)Hb] and [HHb] was -3.93 +/- 0.31 (SE). The patterns of the [O(2)Hb] and [HHb] traces over the motor cortex looked different. The [O(2)Hb] reached its maximum change a few seconds before the [HHb] reached its minimum. This was confirmed by the linear regression analysis (r(2) > 0.8 in none of 40 locations). In 20 locations the change in [O(2)Hb] was larger than 0.25 microM. The mean slope of the regression line was -1.76 +/- 0.20, which is significantly higher than that in the motor cortex (P < 0.0000001). Patterns of [O(2)Hb] and [HHb] differ among cortex areas. This implies that the regulation of perfusion in the visual cortex is different from that in the motor cortex. There is evidence that the CMRO(2) increases substantially in the visual cortex, while this is not the case for the motor cortex.

Quantification of perfusion using bolus tracking magnetic resonance imaging in stroke: assumptions, limitations, and potential implications for clinical use

BACKGROUND

MR techniques have been very powerful in providing indicators of tissue perfusion, particularly in studies of cerebral ischemia. There is considerable interest in performing absolute perfusion measurements, with the aim of improving the characterization of tissue "at risk" of stroke. However, some important caveats relating to absolute measurements need to be taken into account. The purpose of this article is to discuss some of the issues involved and the potential implications for absolute cerebral blood flow measurements in clinical use.

SUMMARY OF COMMENT

In bolus tracking MRI, deconvolution of the concentration-time course can in theory provide accurate quantification. However, there are several important assumptions in the tracer kinetic model used, some of which may be invalid in cerebral ischemia. These can introduce significant errors in perfusion quantification.

CONCLUSIONS

Although we believe that bolus tracking MRI is a powerful technique for the evaluation of perfusion in cerebral ischemia, interpretation of perfusion maps requires caution; this is particularly true when absolute quantification is attempted. Work is currently under way in a number of centers to address these problems, and with appropriate modeling they may be overcome in the future. In the interim, we believe that it is necessary for users of bolus tracking perfusion data to be aware of the current technical limitations if they are to avoid misinterpretation or overinterpretation of their findings.

Is quantification of bolus tracking MRI reliable without deconvolution?

Bolus tracking data obtained with paramagnetic intravascular tracers are commonly analyzed and quantified by the direct measurement of properties of the tissue concentration-time curve (e.g., time to peak (TTP)). The measurement of these "summary parameters" is used as an accessible alternative approach to the complex deconvolution procedure, and provides indirect measures of perfusion. However, summary parameters do not take into account differences in arterial input functions (AIFs) or residue functions (R(t)) between patients or studies. Simulations were performed to assess the variability of summary parameters over a realistic range of AIFs and for differing R(t), to establish whether they can be used as reliable measures of tissue perfusion status. Results showed that the value of each summary parameter investigated is highly dependent upon both the AIF and R(t). The referencing of summary parameters to their corresponding value in the AIF or in normal tissue is a method commonly used to normalize results, but this approach did not lead to any measures that were independent of both the AIF and R(t) in this study. The results presented here show that the use of summary parameters requires considerable caution, since tissue or patient types can easily be incorrectly classified due to the effect of variations in patient AIF and R(t).