| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
|
|
|
|||||||
|
|||||||||
1
Department of Radiology, Duke University Medical Center, Box 3808, Durham, NC
27710.
2
Department of Radiology, Massachusetts General Hospital, 55 Fruit St., Boston
MA 02114.
Received April 18, 2001;
accepted after revision September 14, 2001.
Presented at the annual meeting of the American Roentgen Ray Society,
Seattle, April—May 2001.
Abstract
 Top Abstract IntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
MATERIALS AND METHODS. Twelve patients with biopsy-proven high-grade neoplasms and 10 patients with biopsy-proven low-grade neoplasms underwent dynamic susceptibility contrast MR perfusion imaging (TR/TE, 1500/80) after bolus infusion of 0.2 mmol/kg of MR contrast material. Color-coded permeability-weighted maps were created using a model that weights relative contributions to signal intensity from intravascular T2* effects and extravascular T1 effects from blood-brain barrier permeability. Two measures of permeability were performed: mean value of highest permeability found on three images through the tumor (mean regional value) and highest value found at any region of interest in the tumor (single area of maximum permeability). Depending on the normality of the data sets, we used the Wilcoxon's rank sum test or the two-tailed Student's t test for statistical analysis.
RESULTS. For low-grade tumors, the range was 0.006-0.041, and the median of the mean regional value for each image was 0.017. For high-grade tumors, the range was 0.005-0.092, and the median of the mean regional value was 0.035 (p = 0.025). For low-grade tumors, the range was 0.008-0.045, and the mean of the single area of maximum values was 0.02. For high-grade tumors, the range was 0.007-0.136, and the mean of the single area of maximum values was 0.054 (p = 0.018).
CONCLUSION. Permeability values for high-grade tumors obtained using a T2*-weighted method were significantly greater than those for low-grade tumors and are consistent with previous studies reporting results using T1-weighted methods.
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
All patients underwent MR imaging using dynamic susceptibility contrast imaging with a spin-echo echoplanar technique (TR/TE, 1500/80). Slice thickness was 5 mm with a 2.5-mm interslice gap. This technique typically provided between seven and nine images through the brain per 1.5-sec interval and allowed coverage of the entire tumor in all cases. All examinations were performed using a power injection of 0.2 mmol/kg of gadopentetate dimeglumine at an injection rate of 5 mL/sec through a 20-gauge IV line.
Permeability maps were generated on an Advantage Windows workstation
(version 3.1; General Electric Medical Systems, Milwaukee, WI) using a
"K2 analysis" approach hand-ported into
Functool software (General Electric Medical Systems). Permeability images were
derived from T2*-weighted data using the method described by
Weisskoff et al. [4], which
weighs the relative contributions of T1-weighted effects and T2-weighted
effects to the signal change observed during rapid passage of MR contrast
material. The observed signal, 
R2obs, is a
weighted linear combination of the T2-weighted intravascular effects and the
T1-weighted extravascular effects of a gadolinium-based contrast agent, as
illustrated in the equation.
 |
R2 is assumed to be proportional to local blood volume.
K1 represents the weighting of the intravascular
component, and K2 represents the weighting of the
extravascular component. R2avg is computed
by averaging R2obs for all nonenhancing
pixels in the brain, defined by signal enhancement no greater than 1 standard
deviation above baseline. For each pixel in the brain, K1
and K2 are determined by a least-squares fit to
the equation, which allowed determination of permeability weighting
(K2). In the original formulation of this model, a preinfusion loading dose of contrast material was used to keep T1-enhancement rates below 30%. This preinfusion loading dose was not performed in our series for practical reasons related to imaging of patients with brain tumor in a clinical environment.
Permeability measurements were obtained by simultaneously viewing axial contrast-enhanced T1-weighted images and corresponding permeability-weighted images on the workstation. The T1-weighted images were used as a guide for the location of the tumor because on some permeability maps showing relatively normal permeability in tumors, the tumor was not obvious against normal background. The T1-weighted images were not used as a specific guide for placement of regions of interest (ROIs) in a tumor after the tumor was identified on a permeability map. Rather, ROIs were moved in the confines of the tumor (whose borders were identified on the T1-weighted image) until regions having highest permeability values for that slice were identified. Three permeability measures in the tumor were obtained for each patient in the following manner. First, an ROI varying between 57 and 63 mm3 was placed on each of three consecutive permeability images that showed the tumor. In a few instances, all three images were not on consecutive slices. On each of these three images, the maximum permeability was sought using manual placement of the ROI (using the T1-weighted image as a guide), and the maximum permeability value was recorded. The average of these three permeability values (termed "mean regional permeability value") was recorded for each tumor. The distribution of the mean regional permeability values was compared between groups. For each image, the highest permeability value in a normal-appearing thalamus in the contralateral thalamus was recorded as a control value. Second, the highest permeability value at any ROI in the tumor (termed "single area of maximum permeability") was recorded.
We assumed that permeability effects are due to leakage of contrast material from small vessels (e.g., arterioles and capillaries) that are not visible on MR images. On this basis, we assumed that permeability measurements in ROIs that contained visible vessels would not differ from those that did not contain visible vessels. To test this assumption, smaller ROIs were drawn in regions of highest permeability values. Specifically, small ROIs were drawn that were placed on vessels. Permeability values in these ROIs were then compared with values in ROIs that were placed adjacent to vessels. These measurements showed that permeability values were similar between ROIs placed on vessels and those placed adjacent to vessels.
For all data sets, the Kolmogorov-Smirnov test of normality was used to determine whether the distribution of values was normal (p > 0.05) or not normal (p < 0.05) and to indicate whether parametric or nonparametric statistical analysis should be used to analyze test results. Non—normally distributed data would be analyzed by the Wilcoxon's rank sum test, and normally distributed data would be analyzed using two-tailed independent samples t test. The mean regional permeability value for high-grade tumors was compared with that for low-grade tumors, and both were compared with the mean value in the thalamus.
Thalamic values were measured as an internal reference point for permeability measurements in normal tissue and to allow comparison between patients. Thalamic values were assessed to determine whether distribution was normal or not normal using the Kolmogorov-Smirnov test of normality. To determine whether thalamic values differed from zero, data that were normally distributed would be analyzed using a paired t test, and data that were not normally distributed would be analyzed using the Wilcoxon's signed rank test. Thalamic values in patients with high-grade tumors were compared with thalamic values in patients with low-grade tumors using the two-tailed independent samples t test.
Mean regional permeability values were correlated with the mean single area of maximum permeability values using Spearman's correlation (because data were not normally distributed) to determine whether expression of one of these measurements might prove representative of tumor permeability.
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
|
The Kolmogorov-Smirnov test of normality showed that the distribution of the mean regional permeability data set was not normal (high-grade, p = 0.2; low-grade, p = 0.007). For this reason, the Wilcoxon's rank sum test was chosen for statistical assessment. For low-grade tumors, the range was 0.006-0.041, and the median of the mean regional permeability value was 0.017. For high-grade tumors, the range was 0.005-0.092, and the median of the mean regional permeability value was 0.03. This difference between the two sample distributions was statistically significant at p equal to 0.025 (Fig. 1).
The Kolmogorov-Smirnov test of normality showed that the single area of maximum permeability data set was normally distributed (high-grade, p = 0.2; low-grade, p = 0.2). For this reason, the two-tailed independent samples t test was chosen for statistical assessment. For low-grade tumors, the range was 0.008-0.045, and the mean of the single area of maximum values was 0.023. For high-grade tumors, the range was 0.007-0.136, and the mean of the single area of maximum values was 0.054. This difference between the two sample distributions was statistically significant at p = 0.018. The Spearman's correlation test comparing mean regional permeability values and single area of maximum permeability values showed that the correlation coefficient was 0.974 with a p value of 0.000.
A side-by-side graphic representation of mean regional permeability values is seen in Figure 2. This plot shows mild overlap between the two populations of tumors. Using an arbitrary threshold of 0.03, we saw that nine high-grade tumors had permeability values above this threshold, and three high-grade tumors had permeability measurements below this threshold. Nine low-grade tumors had permeability values below this threshold, and one low-grade tumor had a permeability measurement above this threshold. Therefore, the positive predictive value for a permeability value of 0.03 was 90%, and the negative predictive value was 75%.
|
High permeability values were evident on color-coded permeability maps as conspicuous regions that were red or yellow (Fig. 3A,3B). On permeability maps of patients with low-grade tumors, permeability in tumors did not differ from values seen in normal tissue (Fig. 4A,4B). The low-grade tumor with permeability values above the 0.03 threshold is depicted in Figure 5A,5B. This tumor had mean regional permeability values of 0.041 and a single area of maximal permeability value of 0.045. Although this lesion was characterized as low-grade (World Health Organization grade II), the neuropathologist noted that the MIB-1 index, which is a monoclonal antibody directed against recombinant parts of the Ki-67 antigen and is a measure of mitotic activity, was particularly high at 5-10% (compared with a typical 1% index in low-grade tumors). On this basis, the neuropathologist suggested that this tumor likely represented a more aggressive tumor than a typical low-grade neoplasm. As this case shows, high permeability values can be seen even in regions that do not densely contrast enhance on conventional T1-weighted images.
|
|
|
|
|
|
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
If analysis of changes in permeability is to play an important role in trials of antiangiogenesis therapies for brain tumors, it is important that MR measurements of permeability be compared with tumor grade and, ultimately, with histologic characteristics of angiogenesis. Dynamic contrast-enhanced MR imaging can provide information on the permeability of the vasculature to the contrast material (given by the product of permeability times and surface area) and the availability of the extracellular extravascular space into which the contrast material can extravasate. Encouraging results have been seen in organs systems other than the central nervous system. For instance, MR derived parameters have been correlated with histologic measures of angiogenesis in cervical cancer [9] and breast cancer [10]. In comparison, experience with MR permeability imaging of human brain tumors is limited, although animal models have correlated permeability*surface area product with histopathologic tumor grade using a macromolecular contrast medium (albumin-labeled gadopentetate dimeglumine) [11]. In one study of human brain tumors, MR permeability imaging using a dynamic T1-weighted method showed that permeability measurements correlate relatively well with histologic grade of tumor [3].
The purpose of our study was to determine whether the positive association between tumor grade and degree of permeability (reported using a T1-weighted method) could be reproduced using measurements obtained from dynamic susceptibility contrast T2*-weighted images. Permeability measurements can be obtained from T2*-weighted techniques using a calculation that allows separate analysis of T1-weighted effects [4]. This method has the advantage of derivation of both a cerebral blood volume—weighted image and a permeability-weighted image, thereby providing two distinct types of information from one data set. The model used by Weisskoff et al. [4] used a preimaging infusion of a small loading dose of MR contrast material (0.05 mmol/kg). This infusion was performed to preload tissues in an attempt to decrease the likelihood of large (i.e., <30%) degrees of T1-enhancement. For practical reasons related to patient care, we did not use a preinfusion loading dose of contrast material.
Our study showed that mean permeability values measured using the T2*-weighted method were significantly higher in high-grade tumors than those in low-grades tumors. This result was found whether analysis was performed by using the mean of highest values on three separate images or by comparing highest values in the entire tumor between the two populations. Overall, only a small amount of overlap was seen between high-grade and low-grade tumors on mean regional permeability measurements (Fig. 1). The permeability values used in our study are relative; the approach used here measures the permeability—surface area product, which has the same units as flow. In comparison, one previous study of tumor permeability used a dynamic T1-weighted method that allowed derivation of microvascular permeability measured as the transendothelial transfer constant KPS [3]. In that study, mean microvascular permeability was measured as 6.32 mL/100 cm3 per minute for high-grade (World Health Organization grade III or IV) tumors compared with 1.63 mL/100 cm3 per minute for low-grade tumors (i.e., permeability values in high-grade tumors were approximately four times those seen in low-grade tumors). The permeability values found in our high-grade tumors using a T2*-weighted technique were also substantially greater than those in low-grade tumors, being approximately twice those seen in low-grade tumors. The differences between the permeability values in tumor types in the two studies may reflect differences in pulse sequences used to obtain permeability data, differences between patient populations, or other (as yet) undetermined factors. A direct comparison between T1-weighted and T2*-weighted techniques would be the most appropriate method to determine whether the differences between our study and previously published T1-weighted permeability results were solely due to differences in patient populations.
Previous studies using dynamic MR imaging to examine rate of leakage of MR contrast material across the blood—brain barrier in humans have predominantly involved T1-weighted methods [2, 3]. In one previous study, a dynamic T1-weighted fast spin-echo technique was used to study rates of contrast enhancement as a means to distinguish treatment-related changes from primary brain tumors [2]. However, correlation between rates of contrast enhancement and tumor grade was not a part of the study design. In another study, a T1-weighted permeability technique was successfully used to show that permeability surface area significantly correlates with tumor grade [3]. Our study using a T2*-weighted technique verifies these results and provides an alternative means of measuring permeability in tumors. The technique used in our study has been previously used to study permeability in a small sample of patients with brain tumor [12]. In that study, substantial decreases in permeability in brain tumors were seen after dexamethasone administration, presumed to be the result of stabilization of the blood—brain barrier by corticosteroid treatment.
We recognize that a selection bias was present in our study population because most high-grade tumors were residual tumors after surgery, and all low-grade tumors were preoperative lesions. Therefore, if factors related to surgery increased tumor permeability, differences between high-grade and low-grade tumors could be related to surgery rather than strictly to tumor grade. However, we are presently performing forming a study comparing mean regional permeability in unresected high-grade tumors and resected high-grade tumors. Preliminary data from this comparison show that permeability values are similar between the two groups. Therefore, we believe that it is unlikely that surgical status substantially influences permeability, and it is likely that tumor grade is the predominant factor influencing tumor permeability. Another potential limitation of our study was the fact that a preloading dose of contrast material, such as was used in the initial formulation of the T2*-weighted permeability model [4], was not used because it would limit the practical utility of the method. The effect of deletion of the preloading dose is difficult to assess because the conditions under which tumors have an enhancement rate greater than 30% is not known. Future studies to assess the effect of a preloading dose on tumor permeability imaging are indicated. Finally, an important limitation of our study is the assumption we have made about the link between permeability, angiogenesis, and malignancy. Although our data suggest that permeability is correlated with malignancy, this suggestion does not establish a link between angiogenesis and permeability or angiogenesis and malignancy. Animal models showing angiogenesis independent of permeability changes [13] have highlighted this potential limitation. Whether permeability and angiogenesis and malignancy are dependent in humans will require further study.
The exact relative merits of T2*-weighted dynamic susceptibility contrast techniques and T1-weighted techniques for evaluation of hemodynamic alterations in tumors are still a matter of debate. The T1-weighted pulse sequences used to derive permeability data in previous human studies vary in duration from approximately 3 to 5 min and use a dose of 0.1 mmol/kg of MR contrast material via either a hand bolus or power injection [2, 3]. T1-weighted techniques provide permeability measurements but not relative cerebral blood volume. The T2*-weighted method optimally uses a power injection of 0.2 mmol/kg of MR contrast material with rapid imaging performed over the period of 1 min. Both permeability and relative cerebral blood volume can be obtained. However, in clinical studies, an additional contrast-enhanced T1-weighted sequence should be obtained for anatomic images; this additional sequence essentially offsets part of the time savings provided by the T2*-weighted sequence.
In summary, our findings indicate that permeability measurements in high-grade tumors obtained using a T2* technique are significantly higher than those in low-grade tumors. Future studies directly comparing permeability measures obtained using T2*-weighted techniques and T1-weighted techniques are warranted. At present, to our knowledge, no published data exist that assess change in permeability values in response to chemotherapy or antiangiogenesis agents. Future studies should address the use of this method to follow tumor response. Furthermore, because it is impossible to tell whether lack of a preloading dose of contrast material affected our results, future studies to address the effect of a preloading dose on permeability measurements are warranted.
|
TopAbstractIntroductionMaterials and MethodsResultsDiscussionReferences |
|---|
CiteULike 
Complore 
Connotea 
Del.icio.us 
Digg 
Reddit 
Technorati What's this?
This article has been cited by other articles:
|
|
 |
|
  R. Jain, S.K. Ellika, L. Scarpace, L.R. Schultz, J.P. Rock, J. Gutierrez, S.C. Patel, J. Ewing, and T. Mikkelsen Quantitative Estimation of Permeability Surface-Area Product in Astroglial Brain Tumors Using Perfusion CT and Correlation with Histopathologic Grade AJNR Am. J. Neuroradiol., April 1, 2008; 29(4): 694 - 700. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
H. Lu, E. Pollack, R. Young, J.S. Babb, G. Johnson, D. Zagzag, R. Carson, J.H. Jensen, J.A. Helpern, and M. Law Predicting Grade of Cerebral Glioma Using Vascular-Space Occupancy MR Imaging AJNR Am. J. Neuroradiol., February 1, 2008; 29(2): 373 - 378. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J.M. Lupo, S. Cha, S.M. Chang, and S.J. Nelson Analysis of Metabolic Indices in Regions of Abnormal Perfusion in Patients with High-Grade Glioma AJNR Am. J. Neuroradiol., September 1, 2007; 28(8): 1455 - 1461. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Cha, J.M. Lupo, M.-H. Chen, K.R. Lamborn, M.W. McDermott, M.S. Berger, S.J. Nelson, and W.P. Dillon 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 AJNR Am. J. Neuroradiol., June 1, 2007; 28(6): 1078 - 1084. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 P. McConville, D. Hambardzumyan, J. B. Moody, W. R. Leopold, A. R. Kreger, M. J. Woolliscroft, A. Rehemtulla, B. D. Ross, and E. C. Holland Magnetic Resonance Imaging Determination of Tumor Grade and Early Response to Temozolomide in a Genetically Engineered Mouse Model of Glioma Clin. Cancer Res., May 15, 2007; 13(10): 2897 - 2904. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Provenzale Imaging of Angiogenesis: Clinical Techniques and Novel Imaging Methods Am. J. Roentgenol., January 1, 2007; 188(1): 11 - 23. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Cao, V. Nagesh, D. Hamstra, C. I. Tsien, B. D. Ross, T. L. Chenevert, L. Junck, and T. S. Lawrence The Extent and Severity of Vascular Leakage as Evidence of Tumor Aggressiveness in High-Grade Gliomas. Cancer Res., September 1, 2006; 66(17): 8912 - 8917. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. M. Provenzale, S. Mukundan, and D. P. Barboriak Diffusion-weighted and Perfusion MR Imaging for Brain Tumor Characterization and Assessment of Treatment Response. Radiology, June 1, 2006; 239(3): 632 - 649. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
F. Chen, X. Sun, F. De Keyzer, J. Yu, R. Peeters, W. Coudyzer, V. Vandecaveye, W. Landuyt, H. Bosmans, P. Van Hecke, et al. Liver Tumor Model with Implanted Rhabdomyosarcoma in Rats: MR Imaging, Microangiography, and Histopathologic Analysis Radiology, May 1, 2006; 239(2): 554 - 562. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 Y. Cao, P. C. Sundgren, C. I. Tsien, T. T. Chenevert, and L. Junck Physiologic and Metabolic Magnetic Resonance Imaging in Gliomas J. Clin. Oncol., March 10, 2006; 24(8): 1228 - 1235. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Cha Update on Brain Tumor Imaging: From Anatomy to Physiology AJNR Am. J. Neuroradiol., March 1, 2006; 27(3): 475 - 487. [Full Text] [PDF]
|
|
|
|
|
|
S. Cha, L. Yang, G. Johnson, A. Lai, M.-H. Chen, T. Tihan, M. Wendland, and W.P. Dillon Comparison of Microvascular Permeability Measurements, Ktrans, Determined with Conventional Steady-State T1-Weighted and First-Pass T2*-Weighted MR Imaging Methods in Gliomas and Meningiomas. AJNR Am. J. Neuroradiol., February 1, 2006; 27(2): 409 - 417. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. H. Lev and L. Vedolin Permeability versus Cerebral Blood Volume Measurement in Brain Tumor Evaluation: Comparative Clinical Value and Advice to Authors. AJNR Am. J. Neuroradiol., February 1, 2006; 27(2): 418 - 419. [Full Text] [PDF]
|
|
|
|
|
|
T. F. Patankar, H. A. Haroon, S. J. Mills, D. Baleriaux, D. L. Buckley, G. J.M. Parker, and A. Jackson Is Volume Transfer Coefficient (Ktrans) Related to Histologic Grade in Human Gliomas? AJNR Am. J. Neuroradiol., November 1, 2005; 26(10): 2455 - 2465. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
N. Bulakbasi, M. Kocaoglu, A. Farzaliyev, C. Tayfun, T. Ucoz, and I. Somuncu Assessment of Diagnostic Accuracy of Perfusion MR Imaging in Primary and Metastatic Solitary Malignant Brain Tumors AJNR Am. J. Neuroradiol., October 1, 2005; 26(9): 2187 - 2199. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
J. M. Lupo, S. Cha, S. M. Chang, and S. J. Nelson Dynamic Susceptibility-Weighted Perfusion Imaging of High-Grade Gliomas: Characterization of Spatial Heterogeneity AJNR Am. J. Neuroradiol., June 1, 2005; 26(6): 1446 - 1454. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
A. C. M. Maia Jr, S. M. F. Malheiros, A. J. da Rocha, C. J. da Silva, A. A. Gabbai, F. A. P. Ferraz, and J. N. Stavale MR Cerebral Blood Volume Maps Correlated with Vascular Endothelial Growth Factor Expression and Tumor Grade in Nonenhancing Gliomas AJNR Am. J. Neuroradiol., April 1, 2005; 26(4): 777 - 783. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
L. M. Brubaker, J. K. Smith, Y. Z. Lee, W. Lin, and M. Castillo Hemodynamic and Permeability Changes in Posterior Reversible Encephalopathy Syndrome Measured by Dynamic Susceptibility Perfusion-Weighted MR Imaging AJNR Am. J. Neuroradiol., April 1, 2005; 26(4): 825 - 830. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
C. Manka, F. Traber, J. Gieseke, H. H. Schild, and C. K. Kuhl Three-dimensional Dynamic Susceptibility-weighted Perfusion MR Imaging at 3.0 T: Feasibility and Contrast Agent Dose Radiology, March 1, 2005; 234(3): 869 - 877. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. J. Covarrubias, B. R. Rosen, and M. H. Lev Dynamic Magnetic Resonance Perfusion Imaging of Brain Tumors Oncologist, September 1, 2004; 9(5): 528 - 537. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Law, K. Kazmi, S. Wetzel, E. Wang, C. Iacob, D. Zagzag, J. G. Golfinos, and G. Johnson Dynamic Susceptibility Contrast-Enhanced Perfusion and Conventional MR Imaging Findings for Adult Patients with Cerebral Primitive Neuroectodermal Tumors AJNR Am. J. Neuroradiol., June 1, 2004; 25(6): 997 - 1005. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
M. Law, S. Yang, J. S. Babb, E. A. Knopp, J. G. Golfinos, D. Zagzag, and G. Johnson Comparison of Cerebral Blood Volume and Vascular Permeability from Dynamic Susceptibility Contrast-Enhanced Perfusion MR Imaging with Glioma Grade AJNR Am. J. Neuroradiol., May 1, 2004; 25(5): 746 - 755. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
S. Yang, M. Law, D. Zagzag, H. H. Wu, S. Cha, J. G. Golfinos, E. A. Knopp, and G. Johnson Dynamic Contrast-Enhanced Perfusion MR Imaging Measurements of Endothelial Permeability: Differentiation between Atypical and Typical Meningiomas AJNR Am. J. Neuroradiol., September 1, 2003; 24(8): 1554 - 1559. [Abstract] [Full Text] [PDF]
|
|
| |||||||||||||||||||||||||
