1. MR Perfusion and Diffusion Values in Gliomas
XIX Symposium Neuroradiologicum
Perifocal
MR Perfusion and Diffusion
Values in Gliomas
Z. Rumboldt, M.V. Spampinato, P. Morgan,
C. Schiarelli, C. Rorden, J. Fridriksson
Medical University of South Carolina
Charleston, SC, USA

2. Background
New therapies for gliomas highlight the limits of conventional imaging as a tool to assess tumor extension and progression
Growing interest in advanced MR techniques such as perfusion and diffusion imaging to develop better ways to assess treatment response and prognosis
Henson et al. AJNR Am J Neuroradiol Mar; 29(3):
Dhermain FG et. Lancet Neurol Sep;9(9):906-20

3. MR Perfusion
High grade gliomas characterized by increased neovascularization
rCBV is a parameter correlating with the amount of capillaries within the tumor
High-grade gliomas are characterised by an increased
macrovasculature and microvasculature compared with
those in healthy tissue. The amount of hyperperfusion is a
marker of the biological behaviour and aggressiveness of
the tumour, and the estimated relative cerebral blood
volume (CBV) is a semiquantitative parameter that
correlates with the amount of capillaries. Relative CBV
can be used to assess perfusion characteristics (fi gure 2),
and such perfusion imaging techniques require bolus
tracking after gadolinium injection with a T2* dynamic
susceptibility-contrast technique. Integration of the area
under the signal curve gives an estimate of CBV, which
correlates with increased vascularisation.
Aronen, Neuroimaging Clin N Am Nov;12(4):501-23

4. ADC Role of diffusion-weighted MRI in grading gliomas
Pre- and post-treatment DWI data could assist in predicting response to
anti-VEFG
Arvinda HR et Al. J Neurooncol 2009; 94: 87–96
Pope WB et Al. Radiology 2009; 252: 182–89
Wu J et Al. J Clin Oncol 2010; 28 (suppl)

5. Purpose Validation Study Hypothesis:
Measurements of rCBV and ADC within the
tissue beyond the abnormality seen on
conventional MR imaging may provide relevant
information regarding the biological behavior of
cerebral gliomas
These data could help predicting the
aggressiveness of a neoplasm, determining
treatment response, and establishing prognosis

6. Materials and Methods 11 patients with cerebral glioma
(5 WHO grade IV, 1 grade III, 5 grade II)
– 6 progressed in 6 mos
- 5 stable for 2 years
- 4 oligodendroglial (3 low, 1 high grade)
- 1.5T MR scanners (pre or post treatment)
- ADC
- rCBV

7. Materials and Methods rCBV analyzed off-line using the Java
Image software package (
- Deconvolution of the arterial input function from the tissue response function according to the method described by Ostergaard et al.
Ostergaard et Al. Magn. Reson. Med. 36: (1996).

8. Materials and Methods
JIM software rCBV maps and rCBV maps processed using different vendors’ software were compared
Image quality was rated in consensus by two neuroradiologists (random order, using a 3-point scale)

9. Materials and Methods
-Tumor delineation: VOIs were drawn on all relevant FLAIR images using MRIcron (
VOI overlaid on the ADC and rCBV maps

10. Materials and Methods In addition to the lesion VOI, mean values
also obtained from incrementally dilated regions
automatically defined using MRIcron software
Dilation bands in 3D ranges away from
the lesion at predefined distances:
0-4mm, 5-9mm, 10-14mm, 15-19mm
Dilation constrained to ipsilateral hemisphere
Ventricles excluded

11. Materials and Methods

12. MR (2/12/2010)
62 yo male with history of GBM with clinical progression 6 month prior to the MRI.

13. Materials and Methods Statistical Analysis Kruskal Wallis
Grouping variable: progression
rCBV
ADC absolute values

14. Results rCBV images processed by Java Image software package:
- superior in 6 cases
- equal in 5 cases

15. Results

16. Results

17. Results Chi-Square p-value rCBV core 1.750 .186 rCBV 0-4mm 5.143 .023
7.000
.008
rCBV mm
rCBV mm
2.893
.089
ADC core
.000
1.000
ADC 0-4mm
5.143
.023
ADC 5-9mm
6.036
.014
ADC 10-14mm
ADC 15-19mm
7.000
.008

18. Results - rCBV Progression Stable 1.29 0.69 0.9 3.23 0.83 0.7 0-4mm
core
1.29
0.69
0.9
3.23
0.83
0.7
0-4mm
1.28
1.01
1.61
1.58
1.14
1.25
5-9mm
1.31
1.07
1.39
1.52
1.2
1.47
10-14mm
1.18
1.02
1.21
1.13
1.65
15-19mm
1.12 1
1.19
1.78
Stable
core
0.64
0.71
0.97
0.58
0-4mm
0.82
0.86
1.03
0.76
5-9mm
0.88
0.95 1
0.75
10-14mm
0.79
1.04
0.68
15-19mm
0.85
1.12
1.08
0.72

19. Results - ADC Progression Stable Perifocal ADC values Dropping 0-4mm
core
1.182
1.222
1.267
1.254
0.965
1.149
0-4mm
1.337
1.237
0.882
1.218
1.147
1.02
5-9mm
1.241
1.29
0.874
1.18
1.207
1.064
10-14mm
1.171
1.242
0.883
1.278
1.197
1.148
15-19mm
1.161
1.275
0.907
1.245
1.24
1.208
contralateral (core)
1.16
0.701
1.158
0.925
1.001
Stable
core
1.275
1.118
1.564
1.267
1.214
0-4mm
1.099
0.995
1.375
0.882
1.124
5-9mm
1.084
0.962
1.103
0.874
1.007
10-14mm
0.999
1.067
0.883
1.029
15-19mm
1.008
0.959
1.075
0.907
1.054
contralateral (core)
1.03
0.924
0.701
0.998
Perifocal
ADC values
Dropping

20. Conclusion Java Image (JIM) software package
can be used for brain MR perfusion analysis
MRIcron may be a powerful tool
for evaluation of perifocal tissue in brain gliomas
ADC is routinely obtained, no postprocessing needed
Perifocal absolute ADC values
appear to discriminate as well as rCBV

21. Conclusion rCBV and ADC values in perifocal dilated regions
may provide additional information that can assist in tissue characterization
Further prospective investigations are necessary
May make substantial contributions to treatment response and prognosis prediction