The metabolic epicenter of supratentorial gliomas: a 1H-MRSI study.
BACKGROUND
Assessing the impact of glioma location on prognosis remains elusive. We approached the problem using multivoxel proton magnetic resonance spectroscopic imaging (1H-MRSI) to define a tumor "metabolic epicenter", and examined the relationship of metabolic epicenter location to survival and histopathological grade.


METHODS
We studied 54 consecutive patients with a supratentorial glioma (astrocytoma or oligodendroglioma, WHO grades II-IV). The metabolic epicenter in each tumor was defined as the 1H-MRSI voxel containing maximum intra-tumoral choline on preoperative imaging. Tumor location was considered the X-Y-Z coordinate position, in a standardized stereotactic space, of the metabolic epicenter. Correlation between epicenter location and survival or grade was assessed.


RESULTS
Metabolic epicenter location correlated significantly with patient survival for all tumors (r2 = 0.30, p = 0.0002) and astrocytomas alone (r2 = 0.32, p = 0.005). A predictive model based on both metabolic epicenter location and histopathological grade accounted for 70% of the variability in survival, substantially improving on histology alone to predict survival. Location also correlated significantly with grade (r2 = 0.25, p = 0.001): higher grade tumors had a metabolic epicenter closer to the midpoint of the brain.


CONCLUSIONS
The concept of the metabolic epicenter eliminates several problems related to existing methods of classifying glioma location. The location of the metabolic epicenter is strongly correlated with overall survival and histopathological grade, suggesting that it reflects biological factors underlying glioma growth and malignant dedifferentiation. These findings may be clinically relevant to predicting patterns of local glioma recurrence, and in planning resective surgery or radiotherapy.
Sankar
Tejas
T
Division of Neurological Surgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, Arizona 85013, USA.
Kuznetsov
Yevgeniy E
YE
Ryan
Robert W
RW
Caramanos
Zografos
Z
Antel
Samson B
SB
Arnold
Douglas L
DL
Preul
Mark C
MC
D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000704:Analysis of Variance; D001224:Aspartic Acid / Q000378:metabolism; D016009:Chi-Square Distribution; D002794:Choline / Q000378:metabolism; D005260:Female; D005910:Glioma / Q000175:diagnosis*; D006801:Humans; D008279:Magnetic Resonance Imaging; D009682:Magnetic Resonance Spectroscopy / Q000379:methods; D008297:Male; D008875:Middle Aged; D016016:Proportional Hazards Models; D011522:Protons; D012189:Retrospective Studies; D015173:Supratentorial Neoplasms / Q000175:diagnosis* / Q000378:metabolism*; D014057:Tomography, X-Ray Computed / Q000379:methods; D055815:Young Adult
D011522:Protons; D001224:Aspartic Acid; D002794:Choline