Use of fractional anisotropy for determination of the cut-off value in 11C-methionine positron emission tomography for glioma
Introduction
Recent developments in magnetic resonance imaging (MRI) and positron emission tomography (PET) have enabled visualization of the biological and physiological characteristics of the brain in ways that have been impossible in the past. The development in functional MRI has enabled imaging of the anatomical location of the activated brain cortex under certain tasks (Price, 2007) and the development of diffusion tensor imaging (DTI) has allowed delineation of white matter neural fiber tracts in a non-invasive manner (Bello et al., 2008, Kamada et al., 2005a, Kamada et al., 2005b, Kinoshita et al., 2005, Mikuni et al., 2007, Nimsky et al., 2005, Nimsky et al., 2006a, Nimsky et al., 2006b). On the other hand, various radio-labeled tracers have been developed for visualization by PET of the metabolic status of both normal and pathological brain, including ischemic, neurodegenerative and neoplastic diseases (Chen, 2007, Herholz et al., 1998, Kato et al., 2008, Kracht et al., 2004, Pirotte et al., 2004, Stadlbauer et al., 2008).
Today, in the field of neuro-oncology, in order to achieve maximum tumor resection while preserving as much neural function as possible, multimodal radiological assessment is performed for surgical planning. DTI has been used with the combined use of neuro-navigation systems to visualize white matter fiber tracts adjacent to the tumor (Bello et al., 2008, Kamada et al., 2005a, Kamada et al., 2005b, Kinoshita et al., 2005, Mikuni et al., 2007, Nimsky et al., 2005, Nimsky et al., 2006a, Nimsky et al., 2006b) and 18F-fluorodeoxyglucose or 11C-methionine PET have been used for delineation of the extent of tumor cell invasion into the white matter (Pirotte et al., 2004). In addition, DTI has also been used to assess tumor cell invasion at the tumor border (Stadlbauer et al., 2007). A decrease of fractional anisotropy (FA) has been reported to be a useful marker for detecting tumor cell invasion into the white matter (Stadlbauer et al., 2007). However, both imaging techniques present difficulties in delineation of the tumor border, as universal agreement of the normal to abnormal cut-off values has not been established, although several authors have circumvented this issue by histological evaluation of the obtained images (Herholz et al., 1998, Kracht et al., 2004, Stadlbauer et al., 2006).
In the present study, we investigated the possibility of the combined use of DTI and PET images to “automatically” calculate the cut-off values in patients harboring malignant gliomas. As both FA and 11C-methionine PET can be useful modalities to detect the tumor border, we hypothesized that the combined use of these two modalities would allow each to compensate for the other's inadequacies, thereby allowing calculation of the cut-off values for detection of the tumor border.
Section snippets
Patient selection
We collected data from 11 patients harboring gliomas who underwent both DTI and 11C-methionine PET studies as presurgical examination at the Osaka University Hospital from 2007 to 2008. DTI was performed using 3.0- or1.5-T magnetic resonance imaging (MRI). Post-surgical histological examination revealed 1 grade II, 3 grade III and 7 grade IV glioma patients. Detailed information of all 11 patients is listed in Table 1.
Diffusion tensor imaging
All images were obtained using a 3.0-T or 1.5-T (Signa, GE Medical Systems,
Scatter plot of FA as a function of the SUV of 11C-methionine PET shows a peculiar pattern
As shown in the left bottom corner of Fig. 2, when the FA values of each voxel were plotted as a function of the standard uptake value (SUV) of 11C-methionine PET (MET-PET), the data plots showed a peculiar pattern. It is easily appreciated that the data plots can be sectioned into 3 groups, i.e. a high FA and low MET-PET, group, a low FA and low MET-PET group, and finally a low FA and high MET-PET group. When the biological implications of each study are taken into consideration, the high FA
Discussion
With the continuing development of technologies in neuroradiology, it is now possible to non-invasively visualize and understand the biological characteristics of malignant brain tumors and the conditions of the surrounding tissues in a way not possible in the past. As the primary goal in the treatment of malignant gliomas is to maximize tumor resection, it is crucial to presurgically obtain information on the extent of tumor cell invasion. In order to pursue this goal, multimodal imagining of
Acknowledgments
This investigation was supported by a Grant-in-Aid for Scientific Research from the Ministry of Education, Science and Culture of Japan (subject numbers; 18591589 and 19790997).
References (31)
- et al.
Estimation of the effective self-diffusion tensor from the NMR spin echo
J. Magn. Reson., Ser. B.
(1994) - et al.
MR diffusion tensor spectroscopy and imaging
Biophys. J.
(1994) - et al.
Motor and language DTI fiber tracking combined with intraoperative subcortical mapping for surgical removal of gliomas
NeuroImage
(2008) - et al.
Fractional anisotropy value by diffusion tensor magnetic resonance imaging as a predictor of cell density and proliferation activity of glioblastomas
Surg. Neurol.
(2005) - et al.
Automated synthesis of 11C-labelled radiopharmaceuticals: imipramine, chlorpromazine, nicotine and methionine
Int. J. Appl. Radiat. Isot.
(1979) - et al.
Determination of language dominance with synthetic aperture magnetometry: comparison with the Wada test
NeuroImage
(2004) - et al.
Fiber-tracking does not accurately estimate size of fiber bundle in pathological condition: initial neurosurgical experience using neuronavigation and subcortical white matter stimulation
NeuroImage
(2005) - et al.
Fractional anisotropy and tumor cell density of the tumor core show positive correlation in diffusion tensor magnetic resonance imaging of malignant brain tumors
NeuroImage
(2008) - et al.
Intraoperative visualization of the pyramidal tract by diffusion-tensor-imaging-based fiber tracking
NeuroImage
(2006) - et al.
Diffusion tensor imaging and optimized fiber tracking in glioma patients: histopathologic evaluation of tumor-invaded white matter structures
NeuroImage
(2007)