Differentiation of cerebral tumors using multi-section echo planar MR perfusion imaging.
OBJECTIVE
We have investigated the performance of magnetic resonance (MR) perfusion imaging to differentiate between astrocytomas grade II, grade III and glioblastomas in a prospective study.


METHODS
In 33 patients with suspected supratentorial primary cerebral tumors we performed multi-section Echo Planar MR perfusion imaging. Regional cerebral blood volume (rCBV) maps were calculated and the maximum rCBV was determined from the entire lesion. This value was divided by the mean rCBV value from the contralateral side, which provided the rCBV index used in this study. The rCBV index was correlated with the histological tumor classification after stereotactic biopsy (n=7) or open resection (n=26).


RESULTS
The maximum rCBV index was 1.2+/-0.8 for grade II astrocytomas (n=3), 4.0+/-1.2 for grade III astrocytomas (n=13), and 10.3+/-3.3 for glioblastomas (n=17). The difference between grade III astrocytomas and glioblastomas was highly significant (P<0.001).


CONCLUSIONS
The rCBV index measured with multi-section Echo Planar MR perfusion is capable of differentiating grade III astrocytomas from glioblastomas. It serves as an additional parameter to establish a diagnosis in cases where it is not possible to clearly differentiate between these types of tumors on the basis of conventional MR imaging. MR perfusion imaging also provides information about spatial heterogeneities within a tumor which might improve diagnostic performance. This technology may also be of interest for follow-up examinations after histological diagnosis and further treatment.
Preul
Christoph
C
Klinik für Diagnostische Radiologie, Christian-Albrechts-Universität zu Kiel, Kiel, Germany. preul@cns.mpg.de
Kühn
Bernd
B
Lang
Erhard W
EW
Mehdorn
H Maximilian
HM
Heller
Martin
M
Link
Johann
J
D000328:Adult; D001254:Astrocytoma / Q000175:diagnosis*; D001810:Blood Volume; D001921:Brain / Q000473:pathology / Q000503:physiopathology; D001932:Brain Neoplasms / Q000175:diagnosis* / Q000503:physiopathology; D003937:Diagnosis, Differential; D017352:Echo-Planar Imaging / Q000379:methods* / Q000706:statistics & numerical data; D005260:Female; D005909:Glioblastoma / Q000175:diagnosis*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D018810:Magnetic Resonance Angiography / Q000379:methods* / Q000706:statistics & numerical data; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D018709:Statistics, Nonparametric