Simultaneous mapping of blood volume and endothelial permeability surface area product in gliomas using iterative analysis of first-pass dynamic contrast enhanced MRI data

A Novel Multi-Model High Spatial Resolution Method for Analysis of DCE MRI Data: Insights from Vestibular Schwannoma Responses to Antiangiogenic Therapy in Type II Neurofibromatosis

This study aimed to develop and evaluate a new DCE-MRI processing technique that combines LEGATOS, a dual-temporal resolution DCE-MRI technique, with multi-kinetic models. This technique enables high spatial resolution interrogation of flow and permeability effects, which is currently challenging to achieve. Twelve patients with neurofibromatosis type II-related vestibular schwannoma (20 tumours) undergoing bevacizumab therapy were imaged at 1.5 T both before and at 90 days following treatment. Using the new technique, whole-brain, high spatial resolution images of the contrast transfer coefficient (Ktrans), vascular fraction (vp), extravascular extracellular fraction (ve), capillary plasma flow (Fp), and the capillary permeability-surface area product (PS) could be obtained, and their predictive value was examined. Of the five microvascular parameters derived using the new method, baseline PS exhibited the strongest correlation with the baseline tumour volume (p = 0.03). Baseline ve showed the strongest correlation with the change in tumour volume, particularly the percentage tumour volume change at 90 days after treatment (p < 0.001), and PS demonstrated a larger reduction at 90 days after treatment (p = 0.0001) when compared to Ktrans or Fp alone. Both the capillary permeability-surface area product (PS) and the extravascular extracellular fraction (ve) significantly differentiated the 'responder' and 'non-responder' tumour groups at 90 days (p < 0.05 and p < 0.001, respectively). These results highlight that this novel DCE-MRI analysis approach can be used to evaluate tumour microvascular changes during treatment and the need for future larger clinical studies investigating its role in predicting antiangiogenic therapy response.

Role of MRI-Based Functional Imaging in Improving the Therapeutic Index of Radiotherapy in Cancer Treatment

Advances in radiation technology, such as intensity-modulated radiation therapy (IMRT), have largely enabled a biological dose escalation of the target volume (TV) and reduce the dose to adjacent tissues or organs at risk (OARs). However, the risk of radiation-induced injury increases as more radiation dose utilized during radiation therapy (RT), which predominantly limits further increases in TV dose distribution and reduces the local control rate. Thus, the accurate target delineation is crucial. Recently, technological improvements for precise target delineation have obtained more attention in the field of RT. The addition of functional imaging to RT can provide a more accurate anatomy of the tumor and normal tissues (such as location and size), along with biological information that aids to optimize the therapeutic index (TI) of RT. In this review, we discuss the application of some common MRI-based functional imaging techniques in clinical practice. In addition, we summarize the main challenges and prospects of these imaging technologies, expecting more inspiring developments and more productive research paths in the near future.

A Novel Statistical Optimization Algorithm for Estimating Perfusion Curves in Susceptibility Contrast-Enhanced MRI

Dynamic susceptibility contrast-enhanced magnetic resonance imaging is an important tool for evaluating intravascular indicator dynamics, which in turn is valuable for understanding brain physiology and pathophysiology. This procedure usually involves fitting a gamma-variate function to observed concentration-time curves in order to eliminate undesired effects of recirculation and the leakage of contrast agents. Several conventional curve-fitting approaches are routinely applied. The nonlinear optimization methods typically are computationally expensive and require reliable initial values to guarantee success, whereas a logarithmic linear least-squares (LL-LS) method is more stable and efficient, and does not suffer from the initial-value problem, but it can show degraded performance, especially when a few data or outliers are present. In this paper, we demonstrate, that the original perfusion curve-fitting problem can be transformed into a gamma-distribution-fitting problem by treating the concentration-time curves as a random sample from a gamma distribution with time as the random variable. A robust maximum-likelihood estimation (MLE) algorithm can then be readily adopted to solve this problem. The performance of the proposed method is compared with the nonlinear Levenberg-Marquardt (L-M) method and the LL-LS method using both synthetic and real data. The results show that the performance of the proposed approach is far superior to those of the other two methods, while keeping the advantages of the LL-LS method, such as easy implementation, low computational load, and dispensing with the need to guess the initial values. We argue that the proposed method represents an attractive alternative option for assessing intravascular indicator dynamics in clinical applications. Moreover, we also provide valuable suggestions on how to select valid data points and set the initial values in the two traditional approaches (LL-LS and nonlinear L-M methods) to achieve more reliable estimations.

Application of Distributed Parameter Model to Assessment of Glioma IDH Mutation Status by Dynamic Contrast-Enhanced Magnetic Resonance Imaging

Previous studies using contrast-enhanced imaging for glioma isocitrate dehydrogenase (IDH) mutation assessment showed promising yet inconsistent results, and this study attempts to explore this problem by using an advanced tracer kinetic model, the distributed parameter model (DP). Fifty-five patients with glioma examined using dynamic contrast-enhanced imaging sequence at a 3.0 T scanner were retrospectively reviewed. The imaging data were processed using DP, yielding the following parameters: blood flow F, permeability-surface area product PS, fractional volume of interstitial space Ve, fractional volume of intravascular space Vp, and extraction ratio E. The results were compared with the Tofts model. The Wilcoxon test and boxplot were utilized for assessment of differences of model parameters between IDH-mutant and IDH-wildtype gliomas. Spearman correlation r was employed to investigate the relationship between DP and Tofts parameters. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis and quantified using the area under the ROC curve (AUC). Results showed that IDH-mutant gliomas were significantly lower in F (P = 0.018), PS (P < 0.001), Vp (P < 0.001), E (P < 0.001), and Ve (P = 0.002) than IDH-wildtype gliomas. In differentiating IDH-mutant and IDH-wildtype gliomas, Vp had the best performance (AUC = 0.92), and the AUCs of PS and E were 0.82 and 0.80, respectively. In comparison, Tofts parameters were lower in K^trans (P = 0.013) and Ve (P < 0.001) for IDH-mutant gliomas. No significant difference was observed in Kep (P = 0.525). The AUCs of K^trans, Ve, and Kep were 0.69, 0.79, and 0.55, respectively. Tofts-derived Ve showed a strong correlation with DP-derived Ve (r > 0.9, P < 0.001). K^trans showed a weak correlation with F (r < 0.3, P > 0.16) and a very weak correlation with PS (r < 0.06, P > 0.8), both of which were not statistically significant. The findings by DP revealed a tissue environment with lower vascularity, lower vessel permeability, and lower blood flow in IDH-mutant than in IDH-wildtype gliomas, being hostile to cellular differentiation of oncogenic effects in IDH-mutated gliomas, which might help to explain the better outcomes in IDH-mutated glioma patients than in glioma patients of IDH-wildtype. The advantage of DP over Tofts in glioma DCE data analysis was demonstrated in terms of clearer elucidation of tissue microenvironment and better performance in IDH mutation assessment.

Blood-brain barrier permeability of normal-appearing white matter in patients with vestibular schwannoma: A new hybrid approach for analysis of T1 -W DCE-MRI

PURPOSE

To develop and assess a "hybrid" method that combines a first-pass analytical approach and the Patlak plot (PP) to improve assessment of low blood-brain barrier permeability from dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) data.

MATERIALS AND METHODS

Seven patients with vestibular schwannoma were enrolled. T1 -W DCE imaging was acquired on a 1.5T scanner. Normal-appearing white matter (NAWM) was divided into four regions of interest (ROIs) based on the magnitude of changes in longitudinal relaxation rate (ΔR1) after gadolinium administration. Kinetic analysis of ROI-averaged contrast agent concentration curves was performed using both the conventional PP and the hybrid method. Computer simulated uptake curves that resemble those from NAWM were analyzed with both methods. Percent deviations (PD) of the "measured" values from the "true" values were calculated to evaluate accuracy and precision of the two methods.

RESULTS

The simulation showed that, at a noise level of 4% (a noise level similar to the in vivo data) and using a signal intensity (SI) averaging scheme, the new hybrid method achieved a PD of 0.9 ± 2.7% for vp , and a PD of -5.4 ± 5.9% for Ktrans . In comparison, the PP method obtained a PD of 3.6 ± 11.3% for vp , and -8.3 ± 12.8% for Ktrans . One-way analyses of variance (ANOVAs) showed significant variations from the four WM regions (P < 10-15 for ΔR1; P < 10-6 for Ktrans ; P < 10-4 for vp ).

CONCLUSION

Both computer simulation and in vivo studies demonstrate improved reliability in vp and Ktrans estimates with the hybrid method.

LEVEL OF EVIDENCE

3 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:79-93.

A continuous-infusion dynamic MRI model at 3.0 Tesla for the serial quantitative evaluation of microvascular proliferation in an animal model of glioblastoma multiforme

PURPOSE

To develop a continuous-infusion dynamic MRI technique to characterize tumor-associated microvascular proliferation (MVP) in a rat brain model of glioblastoma multiforme.

METHODS

The proposed model assumes effects due to tumor-associated MVP (eg, vascular permeability, K^trans ; intravascular plasma fraction, v_p ) cannot be individually separated and solves for a single parameter (k^vasc ) that quantifies the T₁ -weighted contrast enhancement from dynamic images acquired during continuous contrast agent (CA) infusion. Untreated C6 tumor-bearing animals (N = 6) were serially imaged on postoperative days (PODs) 14 and 18 with a 3 Tesla clinical scanner utilizing a dynamic spatial and temporal resolution of 0.38 × 0.38 × 1.5 mm³ and 3.47 s, respectively.

RESULTS

An association was present between PODs 14 and 18 for median tumor k^vasc (Pearson's r = 0.94, P = 0.0052) and CA concentration ([CA], derived from pre- and postcontrast R₁ maps; r = 0.94, P = 0.0054). On POD 18, there was a voxel-based association between k^vasc and [CA] within each tumor (0.45 < r < 0.82, P < 0.001). However, voxel-based subregions demonstrated a reduced association between k^vasc and [CA] (N = 5; -0.08 < r < 0.22, P > 0.05) or an inverse association (N = 1; r = -0.28, P = 0.001), indicating differences between locations of vascular permeability and subsequent CA pooling in tumors.

CONCLUSION

The continuous-infusion method may provide a quantitative measure for characterizing and monitoring tumor-associated MVP. Magn Reson Med 78:1824-1838, 2017. © 2017 International Society for Magnetic Resonance in Medicine.

Visualization of Inflammation at Early Stage of Lung Cancer in Xenografted Temporally Immunosuppression Rats by Ferrioxamine Magnetic Resonance Imaging

Physiological responses such as chronic inflammation and angiogenesis could be used as biomarkers for early detection of cancer with noninvasive imaging modalities. The present study reports the application of magnetic resonance imaging instrument to image the binding of ferrioxamine with hemin that allows visualizing the chronic inflammation foci of lung tissue of immunocompromised rats xenografted using small cell lung carcinoma. A low concentration of ferrioxamine (0.05 ± 0.02 μM·kg⁻¹ of rat weight) deposited on tissue outside the vasculature was found to diffuse across the capillary walls to the interstitial space and inflammation foci, which provided a clear enhancement of T1-weighted gradient-echo sequence images. Ferrioxamine imaging allowed the determination of inflammatory sites and their localization in 3D fat-suppressed maximum intensity projections. The smallest dimension of foci that can be clearly determined is about 0.1 mm³. In concomitant to the in vivo imaging, analysis of histological tissue section showed the development of inflammatory sites. This study provides evidence that medical imaging instrument such as MRI scanner allows researchers to correlate images taken with MRI with those using high-resolution microscopy. Moreover, ferrioxamine is a useful molecular probe for determining chronic inflammation particularly at the very early stages of cancer.

Quantifying Intracranial Plaque Permeability with Dynamic Contrast-Enhanced MRI: A Pilot Study

BACKGROUND AND PURPOSE

Intracranial atherosclerotic disease plaque hyperintensity and/or gadolinium contrast enhancement have been studied as imaging biomarkers of acutely symptomatic ischemic presentations using single static MR imaging measurements. However, the value in modeling the dynamics of intracranial plaque permeability has yet to be evaluated. The purpose of this study was to use dynamic contrast-enhanced MR imaging to quantify the contrast permeability of intracranial atherosclerotic disease plaques in symptomatic patients and to compare these parameters against existing markers of plaque volatility using black-blood MR imaging pulse sequences.

MATERIALS AND METHODS

We performed a prospective study of contrast uptake dynamics in the major intracranial vessels proximal and immediately distal to the circle of Willis using dynamic contrast-enhanced MR imaging, specifically in patients with symptomatic intracranial atherosclerotic disease. Using the Modified Tofts model, we extracted the volume transfer constant (K^trans) and fractional plasma volume (V_p) parameters from plaque-enhancement curves. Using regression analyses, we compared these parameters against time from symptom onset as well as intraplaque hyperintensity and postcontrast enhancement derived from T1 SPACE, a black-blood MR vessel wall imaging sequence.

RESULTS

We completed analysis in 10 patients presenting with symptomatic intracranial atherosclerotic disease. K^trans and V_p measurements were higher in plaques versus healthy white matter and similar or less than values in the choroid plexus. Only K^trans correlated significantly with time from symptom onset (P = .02). Dynamic contrast-enhanced MR imaging parameters were not found to correlate significantly with intraplaque enhancement or intraplaque hyperintensity (P = .4 and P = .17, respectively).

CONCLUSIONS

Elevated K^trans and V_p values found in intracranial atherosclerotic disease plaques versus healthy white matter suggest that dynamic contrast-enhanced MR imaging is a feasible technique for studying vessel wall and plaque characteristics in the proximal intracranial vasculature. Significant correlations between K^trans and symptom onset, which were not observed on T1 SPACE-derived metrics, suggest that K^trans may be an independent imaging biomarker of acute and symptom-associated pathologic changes in intracranial atherosclerotic disease plaques.

Prospective glioma grading using single-dose dynamic contrast-enhanced perfusion MRI

AIM

To evaluate the sensitivity and specificity of single-dose dynamic contrast-enhanced (DCE) perfusion magnetic resonance imaging (MRI) in prospective evaluation of glioma grading and to correlate the relative cerebral blood volume (rCBV) values with mitotic and ki-67 indexes obtained at histopathology.

MATERIALS AND METHODS

A total of 53 histologically proven patients with glioma were included in this study. DCE-MRI perfusion with a single dose of contrast medium was included in brain tumour protocol and prospective grading of glioma into low and high grade was done based on a previously reported rCBV cut-off value of 3. Tumours with rCBV ≥ 3 were considered to be high grade and rCBV < 3 were considered to be low grade. The sensitivity and specificity of the cut-off value were estimated. Ki-67 and mitotic indexes were also obtained on histopathological analysis along with histological grading.

RESULTS

Based on pre-defined rCBV cut-off values, prospective grading of low- and high-grade glioma was achieved with a sensitivity and specificity of 97.22% and 100%, respectively. Significant correlation was found between the mitotic/ki-67 indexes and rCBV values when data for high- and low-grade tumours was combined.

CONCLUSION

DCE-MRI performed with a single dose of contrast medium is as effective as a protocol with a double-dose of contrast medium for glioma grading using 3 T MRI and could be added to the routine evaluation protocol of brain tumours.

Quantifying Intracranial Aneurysm Wall Permeability for Risk Assessment Using Dynamic Contrast-Enhanced MRI: A Pilot Study

BACKGROUND AND PURPOSE

Pathological changes in the intracranial aneurysm wall may lead to increases in its permeability; however the clinical significance of such changes has not been explored. The purpose of this pilot study was to quantify intracranial aneurysm wall permeability (K(trans), VL) to contrast agent as a measure of aneurysm rupture risk and compare these parameters against other established measures of rupture risk. We hypothesized K(trans) would be associated with intracranial aneurysm rupture risk as defined by various anatomic, imaging, and clinical risk factors.

MATERIALS AND METHODS

Twenty-seven unruptured intracranial aneurysms in 23 patients were imaged with dynamic contrast-enhanced MR imaging, and wall permeability parameters (K(trans), VL) were measured in regions adjacent to the aneurysm wall and along the paired control MCA by 2 blinded observers. K(trans) and VL were evaluated as markers of rupture risk by comparing them against established clinical (symptomatic lesions) and anatomic (size, location, morphology, multiplicity) risk metrics.

RESULTS

Interobserver agreement was strong as shown in regression analysis (R(2) > 0.84) and intraclass correlation (intraclass correlation coefficient >0.92), indicating that the K(trans) can be reliably assessed clinically. All intracranial aneurysms had a pronounced increase in wall permeability compared with the paired healthy MCA (P < .001). Regression analysis demonstrated a significant trend toward an increased K(trans) with increasing aneurysm size (P < .001). Logistic regression showed that K(trans) also predicted risk in anatomic (P = .02) and combined anatomic/clinical (P = .03) groups independent of size.

CONCLUSIONS

We report the first evidence of dynamic contrast-enhanced MR imaging-modeled contrast permeability in intracranial aneurysms. We found that contrast agent permeability across the aneurysm wall correlated significantly with both aneurysm size and size-independent anatomic risk factors. In addition, K(trans) was a significant and size-independent predictor of morphologically and clinically defined high-risk aneurysms.

Effects of guided random sampling of TCCs on blood flow values in CT perfusion studies of lung tumors

RATIONALE AND OBJECTIVES

Tissue perfusion is commonly used to evaluate lung tumor lesions through dynamic contrast-enhanced computed tomography (DCE-CT). The aim of this study was to improve the reliability of the blood flow (BF) maps by means of a guided sampling of the tissue time-concentration curves (TCCs).

MATERIALS AND METHODS

Fourteen selected CT perfusion (CTp) examinations from different patients with lung lesions were considered, according to different degrees of motion compensation. For each examination, two regions of interest (ROIs) referring to the target lesion and the arterial input were manually segmented. To obtain the perfusion parameters, we computed the maximum slope of the Hill equation, describing the pharmacokinetics of the contrast agent, and the TCC was fitted for each voxel. A guided iterative approach based on the Random Sample Consensus method was used to detect and exclude samples arising from motion artifacts through the assessment of the confidence level of each single temporal sample of the TCC compared to the model. Removing these samples permits to refine the model fitting, thus exploiting more reliable data. Goodness-of-fit measures of the fitted TCCs to the original data (eg, root mean square error and correlation distance) were used to assess the reliability of the BF values, so as to preserve the functional structure of the resulting perfusion map. We devised a quantitative index, the local coefficient of variation (lCV), to measure the spatial coherence of perfusion maps, from local to regional and global resolution. The effectiveness of the algorithm was tested under three different degrees of motion yielded by as many alignment procedures.

RESULTS

At pixel level, the proposed approach improved the reliability of BF values, quantitatively assessed through the correlation index. At ROI level, a comparative analysis emphasized how our approach "replaced" the noisy pixels, providing smoother parametric maps while preserving the main functional structure. Moreover, the implemented algorithm provides a more meaningful effect in correspondence of a higher motion degree. This was confirmed both quantitatively, using the lCV, and qualitatively, through visual inspection by expert radiologists.

CONCLUSIONS

Perfusion maps achieved with the proposed approach can now be used as a valid tool supporting radiologists in DCE-CTp studies. This represents a step forward to clinical utilization of these studies for staging, prognosis, and monitoring values of therapeutic regimens.

Advanced MR imaging of gliomas: an update

Recent advances in the treatment of cerebral gliomas have increased the demands on noninvasive neuroimaging for the diagnosis, therapeutic planning, tumor monitoring, and patient outcome prediction. In the meantime, improved magnetic resonance (MR) imaging techniques have shown much potentials in evaluating the key pathological features of the gliomas, including cellularity, invasiveness, mitotic activity, angiogenesis, and necrosis, hence, further shedding light on glioma grading before treatment. In this paper, an update of advanced MR imaging techniques is reviewed, and their potential roles as biomarkers of tumor grading are discussed.

Subcompartmentalization of extracellular extravascular space (EES) into permeability and leaky space with local arterial input function (AIF) results in improved discrimination between high- and low-grade glioma using dynamic contrast-enhanced (DCE) MRI

PURPOSE

To modify the generalized tracer kinetic model (GTKM) by introducing an additional tissue uptake leakage compartment in extracellular extravascular space (LTKM). In addition, an implicit determination of voxel-wise local arterial input function (AIF) Cp (t) was performed to see whether these changes help in better discrimination between low- and high-grade glioma using dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

MATERIALS AND METHODS

The modified model (LTKM) was explored and fitted to the concentration-time curve C(t) of each voxel, in which the local AIF Cp (t) could be estimated by a time invariant convolution approximation based on a separately measured global AIF Ca (t). A comparative study of tracer kinetic analysis was performed on 184 glioma patients using DCE-MRI data on 1.5T and 3T MRI systems.

RESULTS

The LTKM analysis provided more accurate pharmacokinetic parameters as evidenced by their relative constancy with respect to the length of concentration-time curve used. In addition, LTKM with local AIF resulted in improved discrimination between low-grade and high-grade gliomas.

CONCLUSION

LTKM with local AIF provides more accurate estimation of physiological parameters and improves discrimination between low-grade and high-grade gliomas as compared with GTKM.

Imaging biomarkers of angiogenesis and the microvascular environment in cerebral tumours

Conventional contrast-enhanced CT and MRI are now in routine clinical use for the diagnosis, treatment and monitoring of diseases in the brain. The presence of contrast enhancement is a proxy for the pathological changes that occur in the normally highly regulated brain vasculature and blood-brain barrier. With recognition of the limitations of these techniques, and a greater appreciation for the nuanced mechanisms of microvascular change in a variety of pathological processes, novel techniques are under investigation for their utility in further interrogating the microvasculature of the brain. This is particularly important in tumours, where the reliance on angiogenesis (new vessel formation) is crucial for tumour growth, and the resulting microvascular configuration and derangement has profound implications for diagnosis, treatment and monitoring. In addition, novel therapeutic approaches that seek to directly modify the microvasculature require more sensitive and specific biological markers of baseline tumour behaviour and response. The currently used imaging biomarkers of angiogenesis and brain tumour microvascular environment are reviewed.

MR imaging of neoplastic central nervous system lesions: review and recommendations for current practice

MR imaging is the preferred technique for the diagnosis, treatment planning, and monitoring of patients with neoplastic CNS lesions. Conventional MR imaging, with gadolinium-based contrast enhancement, is increasingly combined with advanced, functional MR imaging techniques to offer morphologic, metabolic, and physiologic information. This article provides updated recommendations to neuroradiologists, neuro-oncologists, neurosurgeons, and radiation oncologists on the practical applications of MR imaging of neoplastic CNS lesions in adults, with particular focus on gliomas, based on a review of the clinical trial evidence and personal experiences shared at a recent international meeting of experts in neuroradiology, neuro-oncology, neurosurgery, and radio-oncology.

Fundamentals of tracer kinetics for dynamic contrast-enhanced MRI

Tracer kinetic methods employed for quantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) share common roots with earlier tracer studies involving arterial-venous sampling and other dynamic imaging modalities. This article reviews the essential foundation concepts and principles in tracer kinetics that are relevant to DCE MRI, including the notions of impulse response and convolution, which are central to the analysis of DCE MRI data. We further examine the formulation and solutions of various compartmental models frequently used in the literature. Topics of recent interest in the processing of DCE MRI data, such as the account of water exchange and the use of reference tissue methods to obviate the measurement of an arterial input, are also discussed. Although the primary focus of this review is on the tracer models and methods for T(1) -weighted DCE MRI, some of these concepts and methods are also applicable for analysis of dynamic susceptibility contrast-enhanced MRI data.

T(1)- and T(2)(*)-dominant extravasation correction in DSC-MRI: part II-predicting patient outcome after a single dose of cediranib in recurrent glioblastoma patients

A 'vascular normalization index' (VNI) based on the changes in the magnetic resonance imaging (MRI) parameters K(trans) and cerebral blood volume (CBV), combined with blood sampling, has been shown to correlate with patient outcome in recurrent glioblastoma after a single dose of antiangiogenic therapy. Here, by applying a novel contrast agent extravasation correction method insensitive to variations in tissue mean transit time, we show that a similar VNI parameter can be derived from a single dynamic susceptibility contrast MR acquisition rather than the three parameters shown previously. Our results show that this new VNI parameter, which combines changes in tumoral CBV and an apparent transfer constant from our leakage correction method, may provide prognostic information in an even simpler manner than prior efforts.

Measuring the integrity of the human blood-brain barrier using magnetic resonance imaging

The evaluation of blood-brain barrier (BBB) integrity with contrast-enhanced magnetic resonance imaging (MRI) may prove valuable in the setting of certain brain pathologies, such as brain tumors and acute ischemic stroke. Various MRI protocols have been developed to explore the integrity of the BBB by monitoring the leakage of intravenously administered contrast medium into the brain parenchyma. In its simplest form, BBB integrity is assessed qualitatively, by determining the presence or absence of contrast-enhancement on a structural MR image. When a dynamic contrast-enhanced (DCE) MRI protocol is combined with a suitable pharmacokinetic model, DCE-MRI can map the spatial distribution of BBB integrity throughout the brain and assist with evaluating the effects of therapy. Several model-free surrogate measures of BBB permeability have been recently proposed, all of which can be readily computed from standard dynamic susceptibility contrast MRI perfusion scans. Contrast-enhanced MRI offers multiple strategies for evaluating BBB integrity.

Advanced imaging techniques in brain tumors

Perfusion, permeability and magnetic resonance spectroscopy (MRS) are now widely used in the research and clinical settings. In the clinical setting, qualitative, semi-quantitative and quantitative approaches such as review of color-coded maps to region of interest analysis and analysis of signal intensity curves are being applied in practice. There are several pitfalls with all of these approaches. Some of these shortcomings are reviewed, such as the relative low sensitivity of metabolite ratios from MRS and the effect of leakage on the appearance of color-coded maps from dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging and what correction and normalization methods can be applied. Combining and applying these different imaging techniques in a multi-parametric algorithmic fashion in the clinical setting can be shown to increase diagnostic specificity and confidence.

Quantitative permeability magnetic resonance imaging in acute ischemic stroke: how long do we need to scan?

Blood-brain barrier (BBB) permeability estimation with dynamic contrast-enhanced MRI (DCE-MRI) has shown significant potential for predicting hemorrhagic transformation (HT) in patients presenting with acute ischemic stroke (AIS). In this work, the effects of scan duration on quantitative BBB permeability estimates (KPS) were investigated. Data from eight patients (three with HT) aged 37-93 years old were retrospectively studied by directly calculating the standard deviation of KPS as a function of scan time. The uncertainty in KPS was reduced only slightly for a scan time of 3 min and 30 s (4% reduction in P value from .047 to .045). When more than 3 min and 30 s of data were used, quantitative permeability MRI was able to separate those patients who proceeded to HT from those who did not (P value <.05). Our findings indicate that reducing permeability acquisition times is feasible in keeping with the need to maintain time-efficient MR protocols in the setting of AIS.

Quantitative analysis of CT-perfusion parameters in the evaluation of brain gliomas and metastases

BACKGROUND

The paper reports a quantitative analysis of the perfusion maps of 22 patients, affected by gliomas or by metastasis, with the aim of characterizing the malignant tissue with respect to the normal tissue. The gold standard was obtained by histological exam or nuclear medicine techniques. The perfusion scan provided 11 parametric maps, including Cerebral Blood Volume (CBV), Cerebral Blood Flow (CBF), Average Perfusion (Pmean) and Permeability-surface area product (PS).

METHODS

The perfusion scans were performed after the injection of 40 ml of non-ionic contrast agent, at an injection rate of 8 ml/s, and a 40 s cine scan with 1 s interval was acquired. An expert radiologist outlined the region of interest (ROI) on the unenhanced CT scan, by using a home-made routine. The mean values with their standard deviations inside the outlined ROIs and the contralateral ROIs were calculated on each map. Statistical analyses were used to investigate significant differences between diseased and normal regions. Receiving Operating Characteristic (ROC) curves were also generated.

RESULTS

Tumors are characterized by higher values of all the perfusion parameters, but after the statistical analysis, only the PS, PatRsq (Patlak Rsquare) and Tpeak (Time to Peak) resulted significant. ROC curves, confirmed both PatRsq and PS as equally reliable metrics for discriminating between malignant and normal tissues, with areas under curves (AUCs) of 0.82 and 0.81, respectively.

CONCLUSION

CT perfusion is a useful and non invasive technique for evaluating brain neoplasms. Malignant and normal tissues can be accurately differentiated using perfusion map, with the aim of performing tumor diagnosis and grading, and follow-up analysis.

Relative cerebral blood volume values to differentiate high-grade glioma recurrence from posttreatment radiation effect: direct correlation between image-guided tissue histopathology and localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging measurements

BACKGROUND AND PURPOSE

Differentiating tumor growth from posttreatment radiation effect (PTRE) remains a common problem in neuro-oncology practice. To our knowledge, useful threshold relative cerebral blood volume (rCBV) values that accurately distinguish the 2 entities do not exist. Our prospective study uses image-guided neuronavigation during surgical resection of MR imaging lesions to correlate directly specimen histopathology with localized dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC) measurements and to establish accurate rCBV threshold values, which differentiate PTRE from tumor recurrence.

MATERIALS AND METHODS

Preoperative 3T gradient-echo DSC and contrast-enhanced stereotactic T1-weighted images were obtained in patients with high-grade glioma (HGG) previously treated with multimodality therapy. Intraoperative neuronavigation documented the stereotactic location of multiple tissue specimens taken randomly from the periphery of enhancing MR imaging lesions. Coregistration of DSC and stereotactic images enabled calculation of localized rCBV within the previously recorded specimen locations. All tissue specimens were histopathologically categorized as tumor or PTRE and were correlated with corresponding rCBV values. All rCBV values were T1-weighted leakage-corrected with preload contrast-bolus administration and T2/T2*-weighted leakage-corrected with baseline subtraction integration.

RESULTS

Forty tissue specimens were collected from 13 subjects. The PTRE group (n = 16) rCBV values ranged from 0.21 to 0.71, tumor (n = 24) values ranged from 0.55 to 4.64, and 8.3% of tumor rCBV values fell within the PTRE group range. A threshold value of 0.71 optimized differentiation of the histopathologic groups with a sensitivity of 91.7% and a specificity of 100%.

CONCLUSIONS

rCBV measurements obtained by using DSC and the protocol we have described can differentiate HGG recurrence from PTRE with a high degree of accuracy.

Imaging hemodynamics

Microvascular permeability is a pharmacologic indicator of tumor response to therapy, and it is expected that this biomarker will evolve into a clinical surrogate endpoint and be integrated into protocols for determining patient response to antiangiogenic or antivascular therapies. This review discusses the physiological context of vessel permeability in an imaging setting, how it is affected by active and passive transport mechanisms, and how it is described mathematically for both theoretical and complex dynamic microvessel membranes. Many research groups have established dynamic-enhanced imaging protocols for estimating this important parameter. This review discusses those imaging modalities, the advantages and disadvantages of each, and how they compare in terms of their ability to deliver information about therapy-associated changes in microvessel permeability in humans. Finally, this review discusses future directions and improvements needed in these areas.

[Value of relative cerebral blood volume measurement using perfusion MRI in glioma management]

INTRODUCTION

Neoangiogenesis is a critical feature that can differentiate high-grade from low-grade glioma. Conventional MR imaging does not assess this histological feature accurately. The goal of this study was to evaluate the gain in relative cerebral blood volume measurement using perfusion MRI in the management of cerebral gliomas.

MATERIALS AND METHODS

Between 1998 and 2001, 32 histologically proven glial tumors were assessed by perfusion MRI using echoplanar imaging (EPI) and gradient-echo techniques. Relative cerebral blood volume (rCBV) was measured in all patients and compared to histological data.

RESULTS

rCBV values were significantly correlated to histological grading in all 32 patients (P<0.001). Mean rCBV values were 8.74 (+/-3.79) for glioblastomas, 7.37 (+/-2.83) for anaplastic gliomas and 0.84 (+/-0.61) for low-grade gliomas. Mean rCBV values were significantly different between low- and high-grade gliomas, making it possible to determine a threshold (2.5-3) that can separate these two types of lesion. In determining the histological grading, rCBV was shown to be significantly more accurate than conventional MRI (P<0.005).

CONCLUSION

Perfusion MRI using the EPI technique reliably assesses tumoral neoangiogenesis in gliomas preoperatively. The specificity and sensitivity of this technique make this radiological modality a valuable tool in the assessment of cerebral gliomas.

Assessment of therapeutic response in brain tuberculomas using serial dynamic contrast-enhanced MRI

AIM

To assess the most useful dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) index in the evaluation of the therapeutic response in brain tuberculoma (BT) patients.

SUBJECTS AND METHODS

Twenty-three patients with 25 BT lesions were serially evaluated using DCE MRI. All lesions were classified into two groups: group I (n=15) included patients who showed clinical, as well as imaging, improvement; and group II (n=10) included patients with either clinical or radiological deterioration. The group I and group II lesions were examined for up to 12 months at 4 monthly intervals. However, the lesions in five patients of group II were excised following clinical deterioration after 4 months of therapy. The perfusion indices, i.e., relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), permeability (k(trans)), and leakage (v(e)), were quantified at each time point. The cellular, necrotic, and total volumes of lesion, together with the oedema volume, were also calculated.

RESULTS

All patients in group I and three in group II showed a significant decrease in all perfusion indices, together with the oedema volume, after 1 year. In these three patients in group II, increase in rCBV was associated with increased cellular volume fraction whereas the k(trans), v(e), and oedema volume decreased significantly after 4 months. In five patients in group II who underwent excision of the lesion after 4 months of therapy due to clinical deterioration, the decrease in rCBV was associated with significant increase in k(trans) and oedema volume without any significant change in lesion volume. The rCBV correlated significantly with the cellular volume, whereas k(trans) showed a significant correlation with the v(e) and oedema volume at each time point.

CONCLUSION

In BT, changes in k(trans) and oedema volume are associated with a therapeutic response at 4 months, even when there is a paradoxical increase in the lesion volume.

A prospective study on the added value of pulsed arterial spin-labeling and apparent diffusion coefficients in the grading of gliomas

BACKGROUND AND PURPOSE

The purpose of this study was to determine whether qualitative and quantitative measures obtained with pulsed arterial spin-labeling (PASL) and apparent diffusion coefficients (ADC) improve glioma grading compared with conventional MR images.

MATERIALS AND METHODS

We prospectively performed 2 qualitative consensus reviews in 33 suspected gliomas: 1) conventional MR images alone and 2) conventional MR images with PASL and ADC. To calculate the diagnostic performance parameters of PASL and ADC, we used a qualitative scoring system on the basis of the tumor perfusion signal intensity (sTP) and visual ADC scoring (sADC). We then analyzed quantitative regions of interest and calculated the ratio of the maximum tumor perfusion signal intensity (rTPmax) and the minimum ADC value (mADC).

RESULTS

Two observers diagnosed accurate tumor grades in 23 of 33 (70%) lesions in the first review and in 29 of 33 (88%) lesions in the second review. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for determining a glioma grading by using combined sTP and sADC scoring were 90.9, 90.9, 95.2, and 83.3%, respectively. Statistical analysis gave a threshold value of 1.24 for rTPmax and 0.98 x 10(-3) mm/s(2) for mADC to provide a sensitivity, specificity, PPV, and NPV of 95.5, 81.8, 91.3, and 90.1% and 90.9, 81.8, 90.9, and 81.8%, respectively. The receiver operator characteristic curve analyses showed no significant difference between the quantitative and combined qualitative parameters.

CONCLUSION

PASL and ADC significantly improve the diagnostic accuracy of glioma grading compared with conventional imaging.

Differentiation of glioblastoma multiforme and single brain metastasis by peak height and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging

BACKGROUND AND PURPOSE

Glioblastoma multiforme (GBM) and single brain metastasis (MET) are the 2 most common malignant brain tumors that can appear similar on anatomic imaging but require vastly different treatment strategy. The purpose of our study was to determine whether the peak height and the percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced (DSC) perfusion MR imaging could differentiate GBM and MET.

MATERIALS AND METHODS

Forty-three patients with histopathologic diagnosis of GBM (n=27) or MET (n=16) underwent DSC perfusion MR imaging in addition to anatomic MR imaging before surgery. Regions of interest were drawn around the nonenhancing peritumoral T2 lesion (PTL) and the contrast-enhancing lesion (CEL). T2* signal intensity-time curves acquired during the first pass of gadolinium contrast material were converted to the changes in relaxation rate to yield T2* relaxivity (Delta R2*) curve. The peak height of maximal signal intensity drop and the percentage of signal intensity recovery at the end of first pass were measured for each voxel in the PTL and CEL regions of the tumor.

RESULTS

The average peak height for the PTL was significantly higher (P=.04) in GBM than in MET. The average percentage of signal intensity recovery was significantly reduced in PTL (78.4% versus 82.8%; P=.02) and in CEL (62.5% versus 80.9%, P<.01) regions of MET compared with those regions in the GBM group.

CONCLUSIONS

The findings of our study show that the peak height and the percentage of signal intensity recovery derived from the Delta R2* curve of DSC perfusion MR imaging can differentiate GBM and MET.

Comparison of cerebral blood volume maps generated fromT2* andT1weighted MRI data in intra-axial cerebral tumours

We compared parametric maps, measured values and value distributions of cerebral blood volume (CBV) derived from (1) first pass T1 weighted dynamic contrast-enhanced (DCE) data (T1-CBV) using the recently described leakage profile model and (2) conventional T2* weighted DCE data (T2*-CBV) using a conventional curve fitting technique, in nine patients with intraaxial tumours. Regions of interest were defined around enhancing tumour tissue on matched slices. Median tumour values and conspicuity indexes of CBV from the two techniques were compared, demonstrating good correlation (r = 0.667,p<0.05) in enhancing tumour and no significant difference in conspicuity. Pixel-by-pixel scattergrams of values in normal brain in a representative matched slice were produced for each case, which showed excellent correlation (r = 0.96,p<0.001). Distortion of blood vessels around susceptibility interfaces was evident on T2* CBV but not on T1 CBV maps. Leakage-free T1 CBV maps do not suffer from the susceptibility artifacts seen in T2* CBV maps, although they present comparable biological information.

Quantification of physiological and hemodynamic indices usingT1 dynamic contrast-enhanced MRI in intracranial mass lesions

PURPOSE

To estimate precontrast tissue parameter (T(10)) using fast spin echo (FSE) and to quantify physiological and hemodynamic parameters with leakage correction using T(1)-weighted dynamic contrast-enhanced (DCE) perfusion imaging.

MATERIALS AND METHODS

Voxel-wise T(10) computation was performed followed by the analysis of T(1)-weighted DCE perfusion data for the conversion of signal intensity time curve to concentration time curve, estimation of hemodynamic and physiological perfusion indices, and a method for leakage correction. Validations of accuracy of the computations have also been carried out.

RESULTS

The computed T(10) and hemodynamic perfusion indices in normal white and gray matter were in good agreement with the literature values. Physiological perfusion indices in these regions were found negligible, validating computations. Cerebral blood volume (CBV) values change negligibly over the length of concentration time curve in white matter, gray matter, and lesion (CBV(corrected)), while CBV(uncorrected) (lesion) shows linear increase over time.

CONCLUSION

T(1)-weighted DCE perfusion data along with FSE-based T(1) estimation can be used for an accurate estimation of hemodynamic and physiological perfusion indices.

Correlation of Relative Permeability and Relative Cerebral Blood Volume in High-Grade Cerebral Neoplasms

OBJECTIVE

The purpose of this study was to correlate the degree of contrast enhancement on dynamic contrast-enhanced T1-weighted MRI and the relative cerebral blood volume (rCBV) values on T2*-weighted MRI in patients with high-grade brain neoplasms.

SUBJECTS AND METHODS

Ten patients with biopsy-proven high-grade gliomas underwent dynamic contrast-enhanced MRI using T1-weighted fast spoiled gradient-echo technique (TR/TE, 8.3/1.5) during i.v. infusion of 0.1 mmol/kg of MR contrast medium. This sequence was followed within 5 minutes by dynamic susceptibility contrast (DSC) imaging (1,500/80) during i.v. infusion of 0.2 mmol/kg of MR contrast medium. Dynamic contrast-enhanced analysis was performed using the maximum-signal-intensity algorithm, and DSC analysis was performed using the negative enhancement integral program. For each tumor, we performed two comparisons: first, the average dynamic contrast-enhanced and rCBV values within a region of interest drawn around the entire contrast-enhancing tumor on a single image through the center of the lesion and, second, the highest dynamic contrast-enhanced and highest rCBV values within each tumor. Statistical analyses of the first comparison were performed using Pearson's correlation coefficient, R2 correlation coefficient, and Spearman's rank correlation and for the second comparison using Kendall's tau correlation.

RESULTS

The mean signal intensity values ranged between 3.48 and 7.16 SDs above baseline values (mean, 4.89 SDs). The mean rCBV values ranged between 57.9% and 122.7% of the normal lentiform nucleus (mean, 76.6%). The Pearson's correlation coefficient was 0.867, the R2 correlation coefficient was 0.752, and the Spearman's rank correlation was 0.794 (p = 0.001). Dynamic contrast-enhanced values from the region of highest signal intensity ranged between 7.7 and 48.6 SDs above baseline values (mean, 17.3 SDs). The highest rCBV values ranged between 105% and 400% of the normal lentiform nucleus (mean, 292%). The correlation was estimated to be 0.7778 and was statistically significant at the 0.01 level of statistical significance (p = 0.0035).

CONCLUSION

We found a high correlation between degree of contrast enhancement on dynamic contrast-enhanced images and rCBV values in whole tumors and in regions having the highest degree of contrast enhancement in this small study. Our findings, which suggest that relative permeability and rCBV values may be correlated in high-grade glial neoplasms, deserve further study in a larger patient population.

Diffusion-weighted and perfusion MR imaging for brain tumor characterization and assessment of treatment response

Diffusion-weighted magnetic resonance (MR) imaging and perfusion MR imaging are advanced techniques that provide information not available from conventional MR imaging. In particular, these techniques have a number of applications with regard to characterization of tumors and assessment of tumor response to therapy. In this review, the authors describe the fundamental principles of diffusion-weighted and perfusion MR imaging and provide an overview of the ways in which these techniques are being used to characterize tumors by helping distinguish tumor types, assess tumor grade, and attempt to determine tumor margins. In addition, the role of these techniques for evaluating response to tumor therapy is outlined.

The Role of Blood-Brain Barrier Permeability in Brain Tumor Imaging and Therapeutics

OBJECTIVE

Our purpose is to describe methods of assessing leakiness of the blood-brain barrier and explain mechanisms for exploiting the blood-brain barrier for therapeutic purposes.

CONCLUSION

Knowledge of the workings of the blood-brain barrier is important for an understanding of the ways in which blood-brain barrier permeability may be used as a surrogate marker for drug therapeutic response. Manipulation of the blood-brain barrier may provide a means for selectively targeting tumors for drug delivery.

Imaging angiogenesis: applications and potential for drug development

Recognition of the importance of angiogenesis to tumor growth and metastasis has led to efforts to develop new drugs that are targeted to angiogenic vasculature. Clinical trials of these agents are challenging, both because there is no agreed upon method of establishing the correct dosage for drugs whose mechanism of action is not primarily cytotoxic and because of the long time it takes to determine whether such drugs have a clinical effect. Therefore, there is a need for rapid and effective biomarkers to establish drug dosage and monitor clinical response. This review addresses the potential of imaging as a way to accurately and reliably assess changes in angiogenic vasculature in response to therapy. We describe the advantages and disadvantages of several imaging modalities, including positron emission tomography, x-ray computed tomography, magnetic resonance imaging, ultrasound, and optical imaging, for imaging angiogenic vasculature. We also discuss the analytic methods used to derive blood flow, blood volume, empirical semiquantitative hemodynamic parameters, and quantitative hemodynamic parameters from pharmacokinetic modeling. We examine the validity of these methods, citing studies that test correlations between data derived from imaging and data derived from other established methods, their reproducibility, and correlations between imaging-derived hemodynamic parameters and other pathologic indicators, such as microvessel density, pathology score, and disease outcome. Finally, we discuss which imaging methods are most likely to have the sensitivity and reliability required for monitoring responses to cancer therapy and describe ways in which imaging has been used in clinical trials to date.

Comparative study of methods for determining vascular permeability and blood volume in human gliomas

PURPOSE

To characterize human gliomas using T1-weighted dynamic contrast-enhanced MRI (DCE-MRI), and directly compare three pharmacokinetic analysis techniques: a conventional established technique and two novel techniques that aim to reduce erroneous overestimation of the volume transfer constant between plasma and the extravascular extracellular space (EES) (Ktrans) in areas of high blood volume.

MATERIALS AND METHODS

Eighteen patients with high-grade gliomas underwent DCE-MRI. Three kinetic models were applied to estimate Ktrans and fractional blood plasma volume (vp). We applied the Tofts and Kermode (TK) model without arterial input function (AIF) estimation, the TK model modified to include vp and AIF estimation (mTK), and a "first pass" variant of the TK model (FP).

RESULTS

KTK values were considerably higher than KmTK and KFP values (P <0.001). KmTK and KFP were more comparable and closely correlated (rho=0.744), with KmTK generally higher than KFP (P <0.001). Estimates of vp(mTK) and vp(FP) also showed a significant difference (P <0.001); however, these values were very closely correlated (rho=0.901). KTK parameter maps showed "pseudopermeability" effects displaying numerous vessels. These were not visualized on KmTK and KFP maps but appeared on the corresponding vp maps, indicating a failure of the TK model in commonly occurring vascular regions.

CONCLUSION

Both of the methods that incorporate a measured AIF and an estimate of vp provide similar pathophysiological information and avoid erroneous overestimation of Ktrans in areas of significant vessel density, and thus allow a more accurate estimation of endothelial permeability.

Measuring blood volume and vascular transfer constant from dynamic, T(2)*-weighted contrast-enhanced MRI

Dynamic, contrast-enhanced MRI (deMRI) is increasingly being used to evaluate cerebral microcirculation. There are two different approaches for analyzing deMRI data. Intravascular indicator dilution theory has been used to estimate blood volume (and perfusion), usually from T(2)- or T(2) (*)-weighted images of the first pass of the bolus. However, the theory assumes that the tracer (i.e., contrast agent) remains intravascular, which is often not the case when the blood-brain barrier (BBB) is damaged. Furthermore, the method provides no information on the vascular transfer constant. Pharmacokinetic modeling analyses of T(1)-weighted images after first pass do give values of the vascular transfer constant and the volume of the extravascular, extracellular space (EES), but they generally are unable to give estimates of blood volume. In this study we apply pharmacokinetic modeling to dynamic T(2) (*)-weighted imaging of the first pass of a tracer bolus. This method, which we call first-pass pharmacokinetic modeling (FPPM), gives an estimate of the blood volume, vascular transfer constant, and EES volume. The method was applied to a group of 26 patients with surgically proven tumors (10 glioblastomas multiforme (GBMs), six lymphomas, and 10 meningiomas). The measurements of the blood volume and transfer constant were consistent with the known physiology of these tumors.

A comparison of Ktransmeasurements obtained with conventional and first pass pharmacokinetic models in human gliomas

PURPOSE

To compare in a group of patients with cerebral gliomas the estimates of Ktrans between a conventionally established pharmacokinetic model and a recently developed first pass method.

MATERIALS AND METHODS

Glioma patients (23) were studied using T1-weighted dynamic contrast-enhanced magnetic resonance imaging (MRI), and two alternative pharmacokinetic models were used for analysis to derive the volume transfer constant Ktrans. These were a modified version of the established model (yielding KTK) and a recently published method based on first pass leakage profile (FP) of contrast bolus (yielding Kfp).

RESULTS

We found a strong correlation between intra-tumoral median KTK and Kfp (rho = 0.650, P < 0.01), but the values from the conventional model were consistently and significantly higher (mean of inter-tumoral Kfp and KTK medians were 0.018 minute(-1) and 0.284 minute(-1), respectively, P < 0.001). The spatial distribution of KTK and Kfp showed poor correlation in the presence of large vascular structures and good correlation elsewhere.

CONCLUSION

KTK and Kfp produce similar biologic information within voxels not dominated by vascular tissue. The FP method avoids erroneous overestimation of Ktrans in areas of significant intravascular contrast. Findings are in keeping with the predictions of previous mathematical simulations.

Application of new MR techniques in pediatric patients

Pediatric neuroradiology is a fascinating and challenging field because there are normal changes associated with normal development and unique and unusual pathologies that occur in this population. The numerous new MR techniques first applied in the adult population are appropriate for use in the pediatric population, often with minimal modification of parameters. These new techniques will undoubtedly contribute significantly to use of pediatric neuroimaging, but the adult experience is not always directly transferable. The pediatric brain, particularly the immature brain is different in structure, has predilection for different types of disease processes, and may react differently to insults than the adult brain. As a result, the role of these techniques needs to be evaluated in the context of the pediatric brain and common pediatric disease processes.

New hybrid technique for accurate and reproducible quantitation of dynamic contrast-enhanced MRI data

The accuracy and precision of two major approaches for analyzing dynamic MRI data from the first passage of a Gd-DTPA contrast bolus are examined, using a Monte Carlo simulation. Method 1 fits the contrast concentration curve of the first pass to a two-compartment kinetic model to determine the tissue pharmacokinetic parameters. Method 2 decomposes intravascular and interstitial components of the first-pass curve based on a leakage profile (LP) model. Based on the results of these Monte Carlo simulations, a new "hybrid" method is proposed that combines both analytical approaches to optimize accuracy and precision of estimates of K(trans), v(e), and v(p). The new method was evaluated by computer simulation and used on experimental results from a patient with primary brain tumors. The new method has the potential to provide more accurate quantification of tissue plasma volume and vessel permeability.