1. L Castelletti, M Bendini, L Saitta, L Bonzano, F Di Paola, L Castellan
Contribution of Diffusion MRI in the differentiation of intracranial meningiomas and correlation with immunohistochemistry
L Castelletti, M Bendini, L Saitta, L Bonzano, F Di Paola, L Castellan
Departments of Neuroradiology
S. Martino University Hospital - Genoa
Cà Foncello Hospital - Treviso
Italy

2. Meningiomas
the most frequent extra-axial brain tumours (24-30% of all primary intracranial tumors);
symptoms highly dependent on tumor site and size;
30% asymptomatic (first diagnosis on CT scans obtained for different reasons).
Meningioma is the most frequent extraxial brain tumor, Spesific defisits depend on size and site of meningioma. One third of meningiomas area asymptomatic and are occasional discovery at imaging

3. WHO classification and recurrence rate
recurrence I Typical % %
II Atypical % %
III Anaplastic % <80%
According to the WHO classification meningiomas are divided in to 3 tipes: tipical (the most frequent) and at e mal

4. Histological grade is the most relevant prognostic factor and is also associated with survival period
Atipical with a mortality rate of 21% at 5 years
Anaplastic with a median survival time of 2 years
So Histology is related to proGnosis and survival time in particular Ki 67 labeling index is an indipendent predictor of both tumor recurrence and overall survival as reported in this paper
Bruna J, Brell M, Ferrer I, Gimene-Bonafe P, Tortosa A Ki-67 proliferative index predicts clinical outcome in patient with atypical or anaplastic meningioma Neuropathology 2007; 27,

5. Neuroradiological conventional imaging
High sensibility (99%)
Low specificity for histolgical grading
Neuroradiological non conventional imaging
The contribution of diffusion-weighted MR imaging (DWI) in differentianting typical meningiomas from atypical/malignant meningiomas varies in the literature
Conventional MR has pruvd high sensibility, but low specifisity for histological grading
Whail DWI sims to be able to provide more specific information about grading

6. The purpose of our study was to investigate the contribution of diffusion-weighted MR imaging to differentiating typical and atypical meningiomas.
A preoperative reliable characterization of meningiomas would be of paramount importance for a tailored surgical or treatment planning.
The eim of ouer study is the correlation between grading and DWI becuase it’s very important for treatment planning

7. (Magnetom Siemens & Signa GE)
Materials and Methods
PATIENTS
MENINGIOMAS
MEAN
AGE
MAGNET 84
(34 ♂ & 50 ♀) 87
61.6
1.5
(Magnetom Siemens & Signa GE)
Eighty for Petients were preoperative evaluated with one point five Tesla equipments
DWI
b values: 0/500/1000
ADC TR TE
NEX
MATRIX
FOV
SLICES THICKNESS
SLICES
GAP
10000
126 2
128x128
24x36
5 mm
1 mm
ADC maps were automatically generated on Siemens and manually with the Functool software program on GE. The mean ADC values was calculated by means of software Analyze Mayo Clinic.

8. ROI area ranged between 0.5 and 30 mm2.
The mean ADC value was calculated from a region of interest (ROI), manually drawn within the solid part of the tumour.
ROIs were traced avoiding cystic and necrotic areas, which were identified on CT, T2* and post-contrast T1 images on MR.
ROI area ranged between 0.5 and 30 mm2.
Here is an example of hauw we placed the roi in the solid part of the meningioma in ADC maps

9. Pathological data Statistical Analysis
the WHO 2007 grading criteria (mostly based on morphological cellular atypia) [qualitative analysis];
proliferative index determined by Ki 67 (antigen identified by monoclonal Ab)[semi-quantitative analysis]
Statistical Analysis
ADC WHO Grading (U Mann-Whitney)
ADC Ki-67 (Spearman’s rho)
So, after surgery the pathologist assigned (assaind) a WHO grade e KI67 index to all lesions
Then a statistical analysis was performed to asses correlation between ADC veliu and greding, and between tumor grade and Ki67

10. Results Grade I* n=56 Grade II N=28 Grade III N=3 % ADC (10-3 mm2/s)
64.4
32.2
3.4
ADC
(10-3 mm2/s)
mean
1.01
0.71
0.68
Sd (range)
±0.21(min 0.75max1.72)
±0.06 (min 0.56max0.82)
±0.09(min
0.61max0.78)
KI 67 (%)
2.80
10. 51
28.33 sd
±1.82 (min 0 max7)
±5.82(min 2 max 25)
±10.41 (min 20 max 40)
This table sammaraises the risolts Here are the risalts of Istologi and the mean ADC value for ich grup
*24 meningothelial; 13 transitional; 11 fibrous;
3 angiomatous, 3 psammomatosus; 1 mixomatous and
1 secretory

11. WHO I WHO II ADC 0.94x10-3 mm2/sec ADC 0.64x10-3 mm2/sec
This is an example of hauw DWI edds important information to conventional MRI
ADC
0.64x10-3 mm2/sec
WHO II

12. The risolts shown the siGnificantli different ADC velius between tipical and atipical/anaplastic meningiomas
Test U Mann-Whitney: ADC significantly different between typical and atypical/malignant (p<0.001)

13. Spearman’s rho: significant linear correlation between ADC and KI67(%)
And here you can see a strong linear correlation between Ki67 and mean ADC value.
p=valore di significatività
r= coefficiente di correlazione () strong correlation coeffiscientthe
Spearman’s rho: significant linear correlation between ADC and KI67(%)
(r = -0.65, p<0.001)

14. AUTHORS
N° TUMORS
ADC TYPICAL
ADC ATYPICAL
MR FIELD
KI- 67
CORRELATION
GRADE/ADC
Filippi
AJNR 2001 17
13T+4A
1.03±0.29
0.62±1.8
1.5 NO
YES
Hakyemez
Neuroradiology 2006 39
32T+7A
1.17±0.21
0.75±0.21
Nagar
AJNR 2008 48
23T+25A
0.88±0.08
0.66±0.13
Castelletti 87
56T+31A
1.01±0.21
0.71±0.06
Cabada
Radiologìa 2009 30
22T+8A
0.92±0.13
0.82±0.13
Santelli
Acta Neurochir 2010
102
79T+23A
0.96±0.19
0.92±0.08 1
To the best of Auar (our) noleg (knowledge) there are five publishd studis exploring the relationship between meningioma grade and ADC values risolts, shown here in the middle, are in line with this studies in which correlation was found, but two ricent stadis did not find this correlation This discripansy amon (g) stadis
Up to date five studies have used mean diffusivity to grade meningiomas, producing controversial results

15. In these studies the different results of these could be related to:
limited series of patients and a few high grade meningiomas in all studies
different MR equipment
different post-processing techniques (ROI placement)
only our study has investigated correlation with Ki-67
Coud bi rileited to sam limitations: a low number of petients appart from the most recent study of the Padua grup

16. Conclusions
Our series suggests significant correlation between ADC and tumor grading as reported in some previous study
ADC values correlate with Ki67 index
Data could be of paramount importance for treatment planning and prediction of prognosis
In conclusion we faund a siGnificant correlation between ADC and Ki67 index and a significant difference in ADC values in the different histological grading.
We biliv (believe) that our data can be …
Clinical outcome