Histopathological validation of a three-dimensional magnetic resonance spectroscopy index as a predictor of tumor presence.
OBJECTIVE
Data obtained preoperatively from three-dimensional (3D)/proton magnetic resonance (MR) spectroscopy were compared with the results of histopathological assays of tissue biopsies obtained during surgery to verify the sensitivity and specificity of a choline-containing compound-N-acetylaspartate index (CNI) used to distinguish tumor from nontumorous tissue within T2-hyperintense and contrast-enhancing lesions of patients with untreated gliomas. The information gleaned from the biopsy correlation study was used to test the hypothesis that there is metabolically active tumor in nonenhancing regions of the T2-hyperintense lesion that can be detected using MR spectroscopy.


METHODS
Patients suspected of harboring a glioma underwent 3D MR spectroscopy during their preoperative MR imaging examination. Surgical navigation techniques were used to record the location of tissue biopsies collected during open resection of the tumor. A receiver operating curve analysis of the CNI and histological characteristics of specimens at each biopsy location was performed to determine the optimal threshold of the CNI required to separate tumor from nontumorous tissue. Histograms of the CNIs within enhancing and nonenhancing regions of lesions appearing on MR images were generated to determine the spatial distribution of CNIs consistent with tumor.


CONCLUSIONS
Biopsy samples containing tumor were distinguished from those containing a mixture of normal, edematous, gliotic, and necrotic tissue with 90% sensitivity and 86% specificity by using a CNI threshold of 2.5. The CNIs of nontumorous specimens were significantly different from those of biopsy specimens containing Grade II (p < 0.03), Grade III (p < 0.005), and Grade IV (p < 0.01) tumors. On average, one third to one half of the T2-hyperintense lesion outside the contrast-enhancing lesion contained CNI greater than 2.5.
McKnight
Tracy R
TR
Department of Radiology, Biostatistics Core, Comprehensive Cancer Center, University of California, San Francisco 94143, USA. mcknight@mrsc.ucsf.edu
von dem Bussche
Mary H
MH
Vigneron
Daniel B
DB
Lu
Ying
Y
Berger
Mitchel S
MS
McDermott
Michael W
MW
Dillon
William P
WP
Graves
Edward E
EE
Pirzkall
Andrea
A
Nelson
Sarah J
SJ
D001224:Aspartic Acid / Q000031:analogs & derivatives* / Q000032:analysis; D001706:Biopsy; D001932:Brain Neoplasms / Q000473:pathology* / Q000601:surgery; D002794:Choline / Q000032:analysis; D005910:Glioma / Q000473:pathology* / Q000601:surgery; D006801:Humans; D009682:Magnetic Resonance Spectroscopy / Q000379:methods / Q000592:standards*; D011237:Predictive Value of Tests; D015203:Reproducibility of Results; D025321:Surgery, Computer-Assisted
D001224:Aspartic Acid; C000179:N-acetylaspartate; D002794:Choline