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 »  Abstract
 » Introduction
 » Subjects and Methods
 » Results
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  Table of Contents  
ORIGINAL ARTICLE
Year : 2020  |  Volume : 57  |  Issue : 1  |  Page : 36-43
 

Percentage signal intensity recovery: A step ahead of rCBV in DSC MR perfusion imaging for the differentiation of common neoplasms of brain


Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka, India

Date of Submission29-Jun-2018
Date of Decision31-Dec-2018
Date of Acceptance16-Jan-2019
Date of Web Publication26-Feb-2020

Correspondence Address:
Sriram Patwari
Department of Radiology, Columbia Asia Referral Hospital, Bangalore, Karnataka
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/ijc.IJC_421_18

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 » Abstract 


Context: Relative cerebral blood volume (rCBV) and percentage signal recovery (PSR) obtained from T2* dynamic susceptibility contrast magnetic resonance imaging are important parameters for brain tumor assessment.
Aim: To study the accuracy of PSR in the differentiation of low-grade glioma, high-grade glioma, lymphoma, and metastases particularly in comparison to rCBV.
Settings and Design: Retrospective observational study.
Subjects and Methods: Study included pathologically confirmed cases of 10 low-grade glioma, 22 high-grade glioma, 6 lymphoma, and 12 metastases (Total 50). PSR, relative PSR (rPSR), and rCBV were calculated.
Statistical Analysis Used: Accuracy of these parameters studied statistically using analysis of variance and ROC (Receiver operating characteristic) curves.
Results: rCBV was higher in metastases (3.45 ± 2.82) and high-grade glioma (3.47 ± 1.62), whereas was low in lymphoma (1.03 ± 0.74) and low-grade glioma (1.43 ± 0.47) with P value of 0.030. PSR was low in metastases (48 ± 16.18), intermediate in glioma (73.24 ± 6.39 and 88.26 ± 6.05, high and low grade), and high in lymphoma (112.16 ± 10.57) with P value < 0.000. rPSR was higher for lymphoma (1.73 ± 0.57) than high-grade glioma (0.85 ± 0.11) and metastasis (0.69 ± 0.19) with P value <.000. Area under ROC for PSR was greater than rCBV in differentiating metastases from lymphoma (1.00 vs 0.13), high-grade glioma from lymphoma (1.00 vs 0.38), high-grade glioma from metastases (0.89 vs 0.58), and high-grade glioma from low-grade glioma (0.96 vs 0.03) with excellent curve characteristics. F values for PSR and rPSR from ANOVA analysis were 71.47 and 36.77, was better than rCBV (3.84) in differentiating these groups.
Conclusions: Percentage of signal recovery shows low recovery values in metastases, intermediate recovery values in glioma, and overshoot in lymphoma. PSR values show lower overlap than rCBV between lymphoma and metastases; and between high grade glioma and metastases. PSR difference is also higher than rCBV between low- and high-grade gliomas. Hence, PSR can potentially help as an additional perfusion parameter in the preoperative differentiation of these tumors.


Keywords: Brain tumors, dynamic susceptibility, MR perfusion, percentage signal recovery, Relative cerebral blood volume


How to cite this article:
Surendra K L, Patwari S, Agrawal S, Chadaga H, Nagadi A. Percentage signal intensity recovery: A step ahead of rCBV in DSC MR perfusion imaging for the differentiation of common neoplasms of brain. Indian J Cancer 2020;57:36-43

How to cite this URL:
Surendra K L, Patwari S, Agrawal S, Chadaga H, Nagadi A. Percentage signal intensity recovery: A step ahead of rCBV in DSC MR perfusion imaging for the differentiation of common neoplasms of brain. Indian J Cancer [serial online] 2020 [cited 2020 Apr 10];57:36-43. Available from: http://www.indianjcancer.com/text.asp?2020/57/1/36/274735





 » Introduction Top


Differentiation of common neoplastic lesions of the brain like glioma, metastases, and lymphoma may be challenging on standard magnetic resonance (MR) imaging due to similarities in their appearances. Preoperative differentiation and characterization of these lesions is important as management and hence prognosis can alter substantially based on the nature of lesion.

These tumors differ in hemodynamics in terms of endothelial hyperplasia, vascular density, capillary permeability, loss of blood brain barrier (BBB), integrity and neoangiogenesis.[1],[2] Various parameters of T2* dynamic susceptibility contrast magnetic resonance imaging (T2*DSC MRI) such as blood volume, blood flow, and transit time are used as a measure of tumour microcirculation and hemodynamics.[3],[4] Among these, relative cerebral blood volume (rCBV) is a widely used parameter which mainly reflects neovascularity of the lesion and does not provide information on capillary permeability. Relative CBV is higher for high-grade gliomas and metastases than low-grade gliomas and lymphomas. Such a difference may be attributed to the status of neovascularity which is lacking in the lymphomas and is lesser in the low-grade gliomas.[5],[6]

Percentage signal recovery (PSR), a novel perfusion parameter obtained from T2*DSC MR imaging, has been suggested to be better quantitative parameter than rCBV for the differentiation of these tumors.[7] PSR is a perfusion curve that represents the percentage of the signal intensity which is recovered from the base line at the end of the first pass of contrast material (base line being signal intensity before contrast administration). On administration of intravenous contrast, initially there will be drop in signal intensity which returns toward the baseline after first pass. The extent of this recovery is determined by many factors like rate of blood flow, volume of extravascular space, and contrast leak. Hence, PSR provides information on both neovascularity as well as capillary permeability.[8]

The objective of our study was to evaluate diagnostic performance and accuracy of PSR in the preoperative differentiation of common brain tumors including low-grade glioma, high-grade glioma, lymphoma, and metastases in comparison to rCBV using final histopathology as gold standard.


 » Subjects and Methods Top


Our retrospective study design and protocol was reviewed and approved by the institutional review board and need for informed consent was waived.

We included a total of 56 pathologically proven cases (n = 56, 24 women and 32 men, age range: 35–90 years) of common brain tumours who underwent MR perfusion imaging from January 2015 to August 2017 at our hospital. We excluded two patients with motion and susceptibility artefacts in perfusion data and one patient with poor arterial input function, which may render errors in calculation of perfusion parameters. We also excluded three cases of recurrence that were previously treated and did not undergo biopsy of the recurrent tumor. The 50 cases thus comprised of ten cases of low-grade glioma, 22 high-grade gliomas, 12 metastases (from lung, thyroid, renal, and ovarian carcinoma), and 6 cases of primary CNS (Central nervous system) lymphoma (all diffuse large cell B cell lymphoma). For the purpose of the study, WHO grade I and II gliomas were considered as low grade and WHO grade III and IV gliomas were considered as high grade.

Scanning protocol and contrast material injection

All MRI scans were performed using a 1.5 T MR system (Siemens, Erlangen, Germany) with a quadrature matrix head coil. Conventional sequences included were Axial T2 TSE and FLAIR, Sagittal T1 TSE, DWI with ADC, Axial GRE, Axial T1 fat suppressed and postcontrast fat-suppressed T1W images in three orthogonal planes. Using a gradient recalled T2*weighted echo planar imaging sequence (ep2d_perf), DSC imaging was performed. Parameters used were TR/TE 1840/36 ms, flip angle 90° and slice thickness 5 mm with no gap. The paramagnetic contrast material was administrated intravenously with 18 or 20 gauge needle using a power injector at the contrast injection rate of 4 mL/sec. Contrast material used was gadodiamide (Omni scan, GE) with dose of 0.2 mM/kg. Contrast administration was followed by a saline injection as bolus (About 20 ml at the rate of ~4 mL/sec).

Postprocessing

All perfusion data were transferred to a stand-alone workstation for postprocessing on diagnostic color display system using dedicated advanced software package (Syngo.via, Siemens). Postprocessing and selection of regions of interest on the perfusion maps was done by two experienced neuroradiologists. At the time of image evaluation and analysis, they were blinded to the histopathological data.

Perfusion measurements

Quantitative perfusion parameters including rCBV, PSR, and rPSR were measured and calculated.

CBV and rCBV measurements

From the processed perfusion images color-coded CBV maps were obtained. In order to calculate the maximum CBV value for each tumor, multiple regions of interest of 25–40 mm2 were manually drawn on the enhancing solid portion of the lesion. Of the several hot spots on the lesion, maximum CBV values were chosen. This method has been described as having better inter- and intraobserver agreement.[9] Each chosen maximum CBV value was normalised by drawing a similar sized ROI (Region of interest) on the contralateral normal white matter.

The rCBV values were obtained by dividing maximum lesion CBV value by normalised CBV value from contralateral white matter [rCBV = maximum lesion CBV value/normalised CBV value].

PSR and rPSR measurements

In order to obtain signal intensity curve, ROI of 25–40 mm2 was manually drawn on the postcontrast T1W images at enhancing solid portion of tumour carefully excluding areas of necrosis or hemorrhage. Highest recovered signal intensity curve was selected to calculate the PSR (PSR).

The PSR was calculated using formula described by Cha et al.[8]

PSR = 100% × [S1 - Smin]/[S0 - Smin].

Where S1 is post contrast T2*-weighted signal intensity, S0 is precontrast T2*-weighted signal intensity, and Smin is minimum T2*-weighted signal intensity [Figure 1]. For the normalisation, similar sized free hand ROI was drawn on the contralateral normal white matter and rPSR [rPSR = Highest lesional PSR/normalised PSR] was calculated.
Figure 1: Sample signal intensity curve obtained from T2*DSC MR perfusion data. S0 represents baseline precontrast T2*W signal intensity. S1 represents recovered post contrast T2*W signal intensity. Smin represent minimum T2*W signal intensity. Percentage of signal recovery in this sample curve is about 75%

Click here to view


Statistical analysis

Statistical analysis was done by using SPSS statistical software package version 22.0 with a P value <0.05 as the criteria for significance. Accuracy of all parameters was tested by area under ROC with respect to their ability to differentiate lymphoma from high-grade glioma, lymphoma from metastases, metastases from high-grade glioma and low-grade glioma from high-grade glioma. One-way ANOVA was performed on patient groups and analysis included the calculation of F-statistic which is a ratio of the variance between the sample means to variance within the sample. In addition, box plots were obtained for each type of tumors for the parameters rCBV, PSR, and rPSR.


 » Results Top


Relative CBV was higher in metastases (3.45 ± 2.82) and high-grade glioma (3.47 ± 1.62), whereas rCBV was low in lymphoma (1.03 ± 0.74) and low-grade glioma (1.43 ± 0.47) with P value of 0.030 [Table 1].
Table 1: Mean values and standard deviations of perfusion parameters (rCBV, PSR and rPSR) in differentiating common brain tumors

Click here to view


PSR was low in metastases (48 ± 16.18;

range 32 - 85), intermediate in high-grade glioma

(73.24 ± 6.39, range 61 - 86) and low-grade glioma (88.26 ± 6.05, range 79 - 69), whereas high in lymphoma (112.16 ± 10.57, range 103 - 132) with P< 0.000 [Table 1]. Amount of recovered signal intensity and shape of the signal intensity curve in the four different groups of lesions depicted characteristic features. After the first pass of contrast passage the recovered signal intensity returned above the baseline with lymphomas. In contrast, the signal intensity from other lesions did not return to the baseline, with low recovery for metastases (<50%) and average recovery for gliomas (>50%). Among the gliomas low-grade lesions showed more recovery than high-grade lesions [Figure 2], [Figure 3], [Figure 4], [Figure 5].{Table 1}
Figure 2: Axial T1w post-contrast image showing enhancing lesions in the brain (a) which is a known case of cerebral metastases. Yellow ROI placed on the enhancing lesion on CBV perfusion map shows about 48% signal intensity recovery in the recovery map. Golden color perfusion curve represent base line signal recovery (b and c)

Click here to view
Figure 3: Axial T1w post-contrast image showing markedly enhancing lesion in the right frontal and temporal lobe (a) in a known case of GBM (high-grade glioma). Yellow ROI placed on the enhancing portion of the lesion on CBV perfusion map shows about 73% signal intensity recovery in the recovery map. Orange color perfusion curve represent base line signal recovery (b and c)

Click here to view
Figure 4: Axial T1 post-contrast image showing enhancing lesion in the left frontal lobe (a) in a known case of low-grade glioma. Yellow ROI placed on the enhancing portion of the lesion on CBV perfusion map shows about 95% signal intensity recovery in the recovery map. Pink color perfusion curve represents base line signal recovery (b and c)

Click here to view
Figure 5: Axial T1 post-contrast image showing faintly enhancing lesion in the right frontal lobe (a) in a known case of lymphoma. Yellow ROI placed on the enhancing lesion on CBV perfusion map shows about 103% signal intensity recovery in the recovery map. Pink perfusion curve represents base line signal recovery (b and c)

Click here to view


rPSR was found to be useful to differentiate lymphoma from other lesions and was not sensitive enough to differentiate between the glioma and metastases. rPSR was higher for lymphoma (1.73 ± 0.57) than glioma (0.85 ± 0.11 and 0.86 ± 0.11) and metastases (0.69 ± 0.19) with P value < 0.000. Difference in rPSR was not statistically significant between high-grade glioma, low-grade glioma, and metastases [Table 1].

Area under ROC for PSR was better than rCBV in differentiating metastases from lymphoma (1.00 vs 0.13), high-grade glioma from lymphoma (1.00 vs 0.38), high-grade glioma from metastases (0.89 vs 0.58) and high-grade glioma from low-grade glioma (0.96 vs 0.03) with excellent curve characteristics [Figure 6] and [Table 2].
Figure 6: ROC for comparison of PSR and rCBV in an enhancing lesion for differentiation of lymphoma from metastases (a), high-grade glioma from lymphoma (b), high-grade glioma from metastases (c), and high-grade glioma from low grade glioma (d). In graph a and b, PSR lines are coinciding with outer box lines, hence appear indistinct

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Table 2: Area under ROC (Az) for rCBV and PSR

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ANOVA F-test values for PSR and rPSR were more than rCBV (71.47, 36.77 vs. 3.84) in differentiating four groups with significant P value [Table 3].
Table 3: The F-statistic obtained from one way ANOVA showed higher values for PSR and rPSR than rCBV with significant P (<0.05)

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Box plots depicting the variation in the rCBV, PSR, and rPSR [Figure 7] showed significant overlap of rCBV values among the groups [Figure 7]a. There was no significant overlap of PSR values noted among the groups [Figure 7]b. Significant overlap of rPSR values among the gliomas and metastases, but depicted high rPSR values for lymphoma [Figure 7]c.
Figure 7: Boxplots depicting variation in the rCBV, PSR, and rPSR in the differentiation of all four group of lesions. The solid line inside the box indicate median value, while the edges represent the 25th and 75th percentiles. Straight line (orange line) on each box indicate the range of data distribution. Solid circles represent outliers. Significant overlap of rCBV values noted among the groups (a). No significant overlap of PSR values among the groups (b). Significant overlap of rPSR values among the glioma and metastases with high rPSR values for lymphoma (c)

Click here to view



 » Discussion Top


PSR is a promising parameter obtained from T2*DSC MR imaging. In our study, we illustrate the utility of PSR as a problem-solving tool particularly in situ ations where there are similarities in the imaging characteristics on standard MR sequences. The calculation of PSR is simple and does not require elaborate postprocessing applications.[1],[2],[3]

PSR demonstrates distinct recovery characteristics as compared to rCBV. Overshoot from the baseline was seen in lymphoma, low PSR (lesser than half way from baseline) was observed in metastases and intermediate PSR (more than half way from baseline) is seen in gliomas. Low-grade gliomas typically showed higher recovery than high-grade gliomas.[4]

Although the imaging features of glioma, metastasis and lymphoma may be similar; histopathologically there are significant differences in the vascular morphology and neoangiogenesis. High-grade gliomas are characterized by severe cellular atypia, vascular hyperplasia, glomeruloid capillaries, and BBB disruption, whereas low-grade gliomas demonstrate lesser degree of vascular proliferation, cellular atypia, and BBB disruption. On the contrary, lymphomas have distinct histological features of angiogenic growth pattern in which tumor cells cluster around the preexisting brain vessels and also widened perivascular spaces leading to massive leak.[5],[6],[7] The capillaries in the metastatic lesions are similar to the capillaries of their primary malignancy with prominent endothelial gaps and absence of BBB components resulting in higher capillary permeability,[8],[9],[10] but the perivascular spaces may not be widened depending on the cellularity and hence modify the signal changes due to “Wash in” and “wash out” effects. DSC MR imaging assesses the neovascularity and capillary permeability. Relative CBV reflects neovascularity of the lesion and does not provide information on capillary permeability whereas PSR reflects an interplay of both, capillary density as well as permeability. However, rCBV calculations may be affected by leakage of contrast unless leakage correction methods like preloading with contrast are applied during the perfusion imaging.

Differentiation of lymphoma from others

Though lymphomas are relatively avascular, they demonstrate homogenous contrast enhancement on standard MR due to lack of BBB and can simulate other vascular tumors like glioma and metastases resulting in diagnostic dilemma.[11],[12],[13],[14] In our study, rCBV was found to be lesser for lymphoma than other lesions reflecting the poor vascularity; however, there was some overlap noted in the rCBV values between lymphomas and low-grade glioma as well as metastases. Lymphomas showed characteristic perfusion pattern with overshooting of signal intensity and high PSR values. The exact cause for this overshooting phenomenon is not fully known and may be due to extravasation of gadolinium in to the perivascular interstitial space and complex T1 and T2* effects. The T2* effect results in lower signal intensity recovery, whereas T1 effect results in higher signal recovery. Possibly for lymphomas, the T1 effect is dominant over T2* effect due to accumulation of gadolinium in the interstitial space. Other histological factors like the compact nature of cellularity, blood volume, and vascular permeability or interplay between these factors may also contribute to the high PSR.[14],[15] Similar to the results published in a study by Mangla et al.,[1] our study showed rPSR to be very sensitive and specific than rCBV for the differentiation of lymphoma from other lesions.

Differentiation of high-grade glioma from metastases

Due to the similar histological nature of high cellularity and neovascularity, high-grade gliomas and metastases may demonstrate similar imaging appearances on standard MR and similar rCBV measurements on perfusion MR, creating a diagnostic challenge especially when there is solitary metastasis.[16],[17],[18] In our study, rCBV was found to be not useful for the differentiation of high-grade glioma from metastases because of overlapping values with mean value of 3.47 ± 1.6 and 3.45 ± 2.8 respectively. In spite of overlapping in the PSR measurements, signal intensity recovery pattern is helpful for the differentiation of high-grade glioma from metastases with low PSR for metastases (48 ± 16.18) and intermediate PSR for gliomas (73.24 ± 6.39 for high-grade gliomas and 88.26 ± 6.05 for low-grade gliomas). In case of metastases, prominent capillary fenestration and absence of BBB components produces pronounced T2* effect resulting in low signal intensity recovery, whereas in case of high-grade glioma lesser capillary fenestration and partial disruption of BBB components produces moderate T2* effect resulting in intermediate signal intensity recovery. These results are similar to previous studies done by Mangla et al.[1] and Xing et al.[3]

However, there was considerable variation in the PSR values for different metastases with a range of 32 - 85. PSR range for brain metastases from lung malignancy was 32 - 56, thyroid malignancy was 42- 52, from ovarian carcinoma was 40-46 and from renal cell carcinoma was 62-85. These would be reflective of the interplay of the capillary densities and the rate of leakage as well as the cellularity of the primary tumors.

Differentiation of high-grade glioma from low-grade gliomas

Although high-grade gliomas have greater angiogenesis and vascular permeability, conventional MR imaging is moderately sensitive for the differentiation of high- and low-grade gliomas, contrast enhancement being not always accurate in predicting the glioma grade.[19] In our study, rCBV measurements were lower for low-grade gliomas than high-grade gliomas with some overlap. PSR measurements were higher for low-grade gliomas than high-grade gliomas.[20],[21] Thus, both rCBV and PSR were very helpful for their differentiation however, ROC demonstrated PSR to be more sensitive and specific than rCBV with higher area under curve and excellent curve characteristics. We believe that although these parameters suggest malignant or benign nature of the glioma, definitive in vivo differentiation, and prediction of absolute WHO grading may remain still a diagnostic challenge. These results were similar to the results published in a study by Aprile et al.[4]

Limitations

The limitations of our study are small sample size and the retrospective nature of the study design. The small sample size could be one of the reasons for an unduly high area under curve for PSR compared to rCBV. There may be a possibility of spuriously high statistical significance for PSR and rPSR. The significance of combined used of rCBV and PSR is also not evaluated in our study.

Perfusion imaging protocol did not include measures for leakage correction like contrast preloading, which can result in errors in computation of the rCBV in lesions with high leakage like lymphoma and high-grade glioma. Metastases lack BBB and hence would also have leakage.


 » Conclusion Top


Percentage of signal recovery shows low recovery values in metastases, intermediate recovery values in glioma, and overshoot in lymphoma. PSR values show lower overlap than rCBV betweenlymphoma and metastases; and between high grade glioma and metastases. PSR difference is also higher than rCBV between low- and high-grade gliomas. Hence, PSR can potentially help as an additional perfusion parameter in the preoperative differentiation of these tumors. However, larger randomized and prospective studies will be required to verify these findings and to assess the role of PSR in the differentiation of common brain tumors.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.



 
 » References Top

1.
Mangla R, Kolar B, Zhu T, Zhong J, Almast J, Ekholm S. Percentage signal recovery derived from MR dynamic susceptibility contrast imaging is useful to differentiate common enhancing malignant lesions of the rain. AJNR Am J Neuroradiol 2011;32:1004-10.  Back to cited text no. 1
    
2.
Smitha KA, Gupta AK, Jayasree RS. Relative percentage signal intensity recovery of perfusion metrics—an efficient tool for differentiating grades of glioma. Br J Radiol 2015;88:20140784.  Back to cited text no. 2
    
3.
Xing Z, Roger X, You J, Li, Liu Y, Cao D. Differentiation of primary central nervous system lymphomas from high-grade gliomas by rCBV and percentage of signal intensity recovery derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging. Clin Neuroradiol 2014; 24:329-36.  Back to cited text no. 3
    
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Aprile I, Giovannelli G, Fiaschini P, Muti M, Kouleridou A, Caputo N. High- and low-grade glioma differentiation: The role of percentage signal recovery evaluation in MR dynamic susceptibility contrast imaging. Radiol Med 2015;120:967-74.  Back to cited text no. 4
    
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Chakravorty A, Steel TR, Chaganti JR. Accuracy of percentage of signal intensity recovery and relative cerebral blood volume derived from dynamic susceptibility-weighted, contrast-enhanced MRI in the preoperative diagnosis of cerebral tumours. Neuroradiol J 2015;28:574-83.  Back to cited text no. 5
    
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Barajas RF, Cha S. Benefits of dynamic susceptibility-weighted contrast-enhanced perfusion MRI for glioma diagnosis and therapy. CNS Oncol 2014;3:407-19.  Back to cited text no. 6
    
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Chinchure S, Thomas B, Wangju S, Jolappara M, Kesavadas C, Kapilamoorthy TR, et al. Mean intensity curve on dynamic contrast-enhanced susceptibility-weighted perfusion MR imaging--review of a new parameter to differentiate intracranial tumors. J Neuroradiol 2011;38:199-206.  Back to cited text no. 7
    
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Cha S, Lupo JM, Chen MH, Lamborn KR, McDermott MW, Berger MS, et al. Differentiation of glioblastomamultiforme 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 2007;28:1078-84.  Back to cited text no. 8
    
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Wetzel SG, Cha S, Johnson G, Lee P, Law M, Kasow DL, et al. Relative cerebral blood volume measurementsin intracranial mass lesions: Interobserver and intraobserverreproducibilitystudy. Radiology 2002;224:797-803.  Back to cited text no. 9
    
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Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, Akalin T, et al. Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors. Eur J Radiol 2006;58:394-403.  Back to cited text no. 10
    
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Kuker W, Nagele T, Korfel A, Heckl S, Thiel E, Bamberg M, et al. Primary central nervous system lymphomas (PCNSL): MRI features at presentation in 100 patients. J Neurooncol 2005;72:169-77.  Back to cited text no. 11
    
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Buhring U, Herrlinger U, Krings T, Thiex R, Weller M, Küker W, et al. MRI features of primary central nervous system lymphomas at presentation. Neurology 2001;57:393-6.  Back to cited text no. 12
    
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Liao W, Liu Y, Wang X, Jiang X, Tang B, Fang J, et al. Differentiation of primary central nervous system lymphoma and high-grade glioma with dynamic susceptibility contrast-enhanced perfusion magnetic resonance imaging. Acta Radiol 2009;50:217-25.  Back to cited text no. 13
    
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Toh CH, Wei KC, Chang CN, Ng SH, Wong HF. Differentiation of primary central nervous system lymphomas and glioblastomas: Comparison of diagnostic performance of dynamic susceptibility contrast-enhanced perfusion MR imaging without and with contrast-leakage correction. Am J Neuroradiol 2013;34:1145-9.  Back to cited text no. 14
    
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Hartmann M, Heiland S, Harting I, Tronnier VM, Sommer C, Ludwig R, et al. Distinguishing of primary cerebral lymphoma from high-grade glioma with perfusion-weighted magnetic resonance imaging. Neurosci Lett 2003;338:119-22.  Back to cited text no. 15
    
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Lupo JM, Cha S, Chang SM, Nelson SJ. Dynamic susceptibility-weighted perfusion imaging of high-grade gliomas: Characterization of spatial heterogeneity. AJNR Am J Neuroradiol 2005;26:1446-54.  Back to cited text no. 16
    
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Law M, Cha S, Knopp EA, Johnson G, Arnett J, Litt AW, et al. High-grade gliomas and solitary metastases: Differentiation by using perfusion and proton spectroscopic MRimaging. Radiology 2002;222:715-21.  Back to cited text no. 17
    
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Schiff D. Single brain metastasis. Curr Treat Options Neurol 2001;3:89-99.  Back to cited text no. 18
    
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Knopp EA, Cha S, Johnson G, Mazumdar A, Golfinos JG, Zagzag D, et al. Glial neoplasms: Dynamic contrast-enhanced T2*-weighted MR imaging. Radiology 1999;211:791-8.  Back to cited text no. 19
    
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Weber MA, Zoubaa S, Schlieter M, Jüttler E, Huttner HB, Geletneky K, et al. Diagnostic performance of spectroscopic and perfusion MRI for distinction of brain tumors. Neurology 2006; 66:1899-906.  Back to cited text no. 20
    
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Provenzale JM, York G, Moya MG, Parks L, Choma M, Kealey S, et al. Correlation of relative permeability and relative cerebral blood volume in highgrade cerebral neoplasms. AJR Am J Roentegenol 2006;187:1036-42.  Back to cited text no. 21
    


    Figures

  [Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7]
 
 
    Tables

  [Table 1], [Table 2], [Table 3]



 

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