DOI:10.2214/AJR.07.2660
AJR 2008; 190:W365-W369
© American Roentgen Ray Society
18F-FDG PET of Common Enhancing Malignant Brain Tumors
Nobuyuki Kosaka1,
Tatsuro Tsuchida1,
Hidemasa Uematsu1,
Hirohiko Kimura1,
Hidehiko Okazawa2 and
Harumi Itoh1
1 Department of Radiology, Faculty of Medical Sciences, University of Fukui,
23-3 Matsuoka-Shimoaizuki, Eiheiji-cho, Yoshida-gun, Fukui 910-1193,
Japan.
2 Biomedical Imaging Research Center, University of Fukui, Fukui, Japan.
Received June 1, 2007;
accepted after revision January 3, 2008.
Address correspondence to N. Kosaka
(nkosaka{at}u-fukui.ac.jp).
Supported in part by the 21st Century COE Biomedical Imaging Technology
Integration Program from the Japan Society for the Promotion of Science
(JSPS).
CME This article is available for CME credit. See
www.arrs.org
for more information.
WEB This is a Web exclusive article.
FOR YOUR INFORMATION
This article is available for CME credit. See
www.arrs.org
for more information.
Abstract
OBJECTIVE. The purpose of our study was to determine whether
18F-FDG PET can be used to differentiate among common enhancing
brain tumors such as lymphoma, high-grade glioma, and metastatic brain
tumor.
MATERIALS AND METHODS. We evaluated 34 patients with an enhancing
brain tumor on MRI, including seven lymphomas, nine high-grade gliomas, and 18
metastatic tumors. All patients also underwent FDG PET. For PET image
analysis, regions of interest were placed over the tumor (T), contralateral
cortex (C), and white matter (WM). Average and maximum pixel values were
determined at each site. On the basis of these measurements, average and
maximum standard uptake values (SUVavg and SUVmax) were
calculated, along with activity ratios (T/Cavg, T/WMavg,
T/WMmax, and T/Cmax), and comparisons among lesions were
then made.
RESULTS. All parameters were significantly higher for lymphoma than
for other tumors (p < 0.01). High-grade gliomas showed
significantly higher SUVavg and SUVmax than metastatic
tumors (p < 0.05). Other parameters did not differ between lesion
types. SUVmax was the most accurate parameter for distinguishing
lymphomas. Using an SUVmax of 15.0 as a cutoff for diagnosing CNS
lymphoma, only one high-grade glioma was found as a false-positive
(SUVmax, 18.8).
CONCLUSION. FDG PET may be useful for differentiating common
enhancing malignant brain tumors, particularly lymphoma versus high-grade
glioma and metastatic tumor. FDG PET can provide useful information for
distinguishing between lymphoma and other malignant enhancing brain tumors and
is recommended when differential diagnoses are difficult to narrow using MRI
alone.
Keywords: brain tumor • FDG • nuclear imaging • PET
Introduction
CNS lymphoma, high-grade glioma, and metastatic brain tumor are all
examples of common enhancing malignant brain tumors on MRI. Although
radiologic features of these brain tumors are well known, accurate diagnosis
remains difficult in some cases on conventional MRI. Because the therapeutic
approaches for intracerebral tumors differ considerably according to tumor
type, several investigators have attempted to differentiate tumors using
advanced MRI techniques such as perfusion-weighted MRI, diffusion-weighted
MRI, and MR spectroscopy
[1-3].
The use of 18F-FDG PET allows the evaluation of lesions on the
basis of metabolic activity and has been successfully applied for brain tumor
imaging in a wide variety of indications, including diagnosis, prognosis, and
assessment of response to therapy
[4-7].
However, to our knowledge, the contribution of FDG PET to the differential
diagnosis of common enhancing malignant brain tumors has not yet been
evaluated. Accordingly, the present study retrospectively examined whether FDG
PET can be used to differentiate common enhancing malignant brain tumors such
as CNS lymphoma, high-grade glioma, and metastatic brain tumor, all of which
show enhancement on MRI.
Materials and Methods
Patients
We selected 39 consecutive patients from our departmental database of FDG
PET examinations for patients diagnosed with CNS lymphoma, high-grade glioma
(World Health Organization [WHO] grades III and IV), or metastatic brain
tumors using keywords of these entities. All CNS lymphomas and high-grade
gliomas were diag nosed by biopsy, whereas metastatic brain tumors were
diagnosed either by biopsy or on the basis of clinical and radiologic
follow-up. On their first visits, all patients provided consent for the use of
clinical and radiologic information by clinical investigators. From this
patient group, we also referred to medical charts to select patients who were
examined by both FDG PET and contrast-enhanced MRI before biopsy and chemo
therapy or radiation therapy; two patients with metastatic brain tumors were
excluded from this study because of preceding biopsy or chemo therapy. MRI of
patients was then reviewed, and patients with enhancing brain tumors were
deter mined by the same experienced neuro radiologist. Enhancing brain tumor
was defined as nodular enhancement > 1 cm in diameter or ring en hancement
> 1 cm thick in the marginal solid portion. Three patients with brain
tumors (two metastatic brain tumors and one lymphoma) were excluded from this
study after not meeting this criterion.
View larger version (112K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 1 —Example of region of interest (ROI) placed on necrotic tumor
in 47-year-old man. Apparent low accumulation of 18F-FDG at center
of tumor is excluded from ROI, which represents necrotic portion. This patient
was revealed as having metastatic brain tumor (squamous cell carcinoma).
|
|
A total of 34 patients (17 women, 17 men; mean age, 64.2 years; range,
17-87 years) with an enhancing brain tumor on MRI were included in this study.
These patients displayed seven CNS lymphomas, nine high-grade gliomas, and 18
metastatic brain tumors. Of these, eight patients (lymphoma, n = 2;
glioma, n = 2; metastatic tumor, n = 4) were administered
dexamethasone at 2-6 mg/d to relieve brain edema before PET. No patients with
diabetes mellitus or acquired immune deficiency syndrome were included in this
patient group because no patients with these entities in our database matched
the patient selection criteria we have described.
The seven patients with CNS lymphoma were all proven to have large B-cell
lymphoma on biopsy. Appropriate surveys failed to detect any other lesion in
all patients. The nine patients with high-grade glioma included two cases of
anaplastic astrocytoma (WHO grade III) and seven cases of glioblastoma
multiforme (WHO grade IV), all of which were confirmed on biopsy.
Tumors in the 18 patients with brain metastases included 12
adenocarcinomas, three squamous cell carcinomas, two small cell carcinomas,
and one transitional cell carcinoma, as well as primary lesions involving the
lung (n = 10), breast (n = 3), esophagus (n = 1),
ureter (n = 1), prostate (n = 1), ovary (n = 1),
and unknown (n = 1). Although nine cases were confirmed by biopsy,
the other nine cases were diagnosed on the basis of clinical and radiologic
follow-up.
MRI
All tumors were imaged using a 1.5-T MRI scanner (Horizon, GE Healthcare)
or a 3.0-T MRI scanner (Signa Excite, GE Healthcare). After the IV injection
of 0.1 mmol/kg of body weight of gadopentetate dimeglumine (Magnevist, Nihon
Schering), contrast-enhanced axial T1-weighted MRI was performed using a
spin-echo sequence (TR/TE, 333/14) with a 1.5-T scanner, or 3D spoiled
gradient-recalled acquisition (SPGR) sequence (11.848/5.26) with a 3.0-T
scanner.
PET
FDG PET examinations were performed using a PET camera (Advance, GE
Healthcare) for 12 patients (lymphoma, n = 2; glioma, n = 4;
metastatic tumor, n = 6) or a PET/CT camera (Discovery LS, GE
Healthcare) for the remaining 22 patients (lymphoma, n = 5; glioma,
n = 5; metastatic tumor, n = 12). All PET studies were
performed as full head-to-thigh oncology scans because these scans had been
requested to check for other lesions rather than to evaluate the brain tumor
itself. After the patients had fasted for at least 6 hours, FDG PET images
were obtained 50 minutes after the IV injection of 185 MBq of FDG, and
germanium-68 or CT-based attenuation corrections were performed. For both
scanners, acquisition and reconstruction parameters of FDG PET were 2-minute
emission per bed position (i.e., total brain acquisition time, 2 minutes),
seven bed positions, 2D acquisition, 50-cm axial field of view, and an
ordered-subsequent expectation maximization iterative reconstruction (subsets,
14; number of iterations, 2) with 7-mm slice thickness. Finally,
reconstruction images were converted to standard uptake value (SUV) images,
using the following equation:
 |
Image Analysis
For FDG PET image analysis, single regions of interest (ROIs) as large as
possible were placed over the tumor using information obtained from
contrast-enhanced MRI by the consensus of two experienced nuclear medicine
physicians. Slices display ing maximum tumor activity were selected. In the
case of multiple tumors, the largest tumor was selected for analysis. Because
the accumulations of FDG were apparently low at the center of the tumors in
six patients (glioma, n = 4; metastatic tumor, n = 2), which
represented the necrotic portions, these portions were excluded from the ROI
(Fig. 1). Areas of ROIs over
tumors were between 1.17 and 14.12 cm2 (mean, 4.49 cm2;
median, 3.77 cm2). ROIs over the contralateral cortex and
contralateral white matter were also placed following the method described by
Delbeke et al. [5]. No fused
images were used for these procedures.
Average SUV (SUVavg) and maximum SUV (SUVmax) of
tumors were obtained on the basis of pixel values for every ROI. Average
counts per pixel of tumor, white matter, and cortex, and counts of maximum
pixels of tumor were also available and were used to generate activity ratios.
On the basis of these measurements, the following parameters were generated:
the SUVavg and SUVmax, the average tumor-to-cortex
activity ratio (T/Cavg), the average tumor-to-white matter activity
ratio (T/WMavg), the ratio of the count of maximum pixels in the
tumor to the average count per pixel in the cortex (T/Cmax), and
the ratio of the count of maximum pixels in the tumor to the average count per
pixel in the white matter (T/WMmax). T, C, and WM denote tumor,
cortex, and white matter.
Statistical Analysis
Statistical analyses were performed using GraphPad Instat for Windows
software (2003, version 3.06, GraphPad Software). First, for statistical
testing of normality and verifying the homogeneity of variances, the
Kolmogorov-Smirnov test and Bartlett test were performed for each parameter.
One-way analysis of variance was then performed to compare means of each
parameter among the three groups. Finally, when one-way analysis of variance
yielded significant results, means of each parameter were compared among all
groups using the Tukey-Kramer multiple comparisons test. Values of p
< 0.05 were considered statistically significant.
Results
Mean values and SDs of all parameters in each group are summarized in
Table 1, and the scatterplots
are shown in Figures 2A,
2B and
2C. All CNS lymphoma parameters
calculated here were significantly higher than those of other tumors
(p < 0.01). High-grade gliomas showed significantly higher
SUVavg and SUVmax than metastatic tumors (p
< 0.05), but no other parameters differed between groups. Representative
cases of each tumor are shown in Figures
3A,
3B,
4A,
4B,
5A and
5B.
View larger version (15K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 2A —Scatterplots of 18F-FDG uptake in lesions.
Scatterplots show average and maximum standard uptake values
(SUVavg and SUVmax) (A), average tumor-to-cortex
activity ratio (T/Cavg) and ratio of count of maximum pixels in
tumor to average count per pixel in cortex (T/Cmax) (B), and
average tumor-to-white matter activity ratio (T/WMavg) and ratio of
count of maximum pixels in tumor to average count per pixel in white matter
(T/WMmax) (C). L denotes CNS lymphoma; G, high-grade glioma;
and M, metastatic brain tumor. Mean values and SDs are also shown. Dashed
lines indicate lowest values for each CNS lymphoma parameter. When these
values are used as cutoff levels to distinguish CNS lymphomas from other
tumors, SUVmax is the most accurate parameter. Using
SUVmax of 15.0 as cutoff level, only one high-grade glioma was
found to be false-positive (SUVmax, 18.8) in our patient group.
|
|
View larger version (14K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 2B —Scatterplots of 18F-FDG uptake in lesions.
Scatterplots show average and maximum standard uptake values
(SUVavg and SUVmax) (A), average tumor-to-cortex
activity ratio (T/Cavg) and ratio of count of maximum pixels in
tumor to average count per pixel in cortex (T/Cmax) (B), and
average tumor-to-white matter activity ratio (T/WMavg) and ratio of
count of maximum pixels in tumor to average count per pixel in white matter
(T/WMmax) (C). L denotes CNS lymphoma; G, high-grade glioma;
and M, metastatic brain tumor. Mean values and SDs are also shown. Dashed
lines indicate lowest values for each CNS lymphoma parameter. When these
values are used as cutoff levels to distinguish CNS lymphomas from other
tumors, SUVmax is the most accurate parameter. Using
SUVmax of 15.0 as cutoff level, only one high-grade glioma was
found to be false-positive (SUVmax, 18.8) in our patient group.
|
|
View larger version (15K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 2C —Scatterplots of 18F-FDG uptake in lesions.
Scatterplots show average and maximum standard uptake values
(SUVavg and SUVmax) (A), average tumor-to-cortex
activity ratio (T/Cavg) and ratio of count of maximum pixels in
tumor to average count per pixel in cortex (T/Cmax) (B), and
average tumor-to-white matter activity ratio (T/WMavg) and ratio of
count of maximum pixels in tumor to average count per pixel in white matter
(T/WMmax) (C). L denotes CNS lymphoma; G, high-grade glioma;
and M, metastatic brain tumor. Mean values and SDs are also shown. Dashed
lines indicate lowest values for each CNS lymphoma parameter. When these
values are used as cutoff levels to distinguish CNS lymphomas from other
tumors, SUVmax is the most accurate parameter. Using
SUVmax of 15.0 as cutoff level, only one high-grade glioma was
found to be false-positive (SUVmax, 18.8) in our patient group.
|
|
View larger version (76K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 3B —76-year-old woman with CNS lymphoma. Corresponding axial
18F-FDG PET image shows FDG accumulation (arrow) is
visually higher than in other tumors (Figs.
4B and
5B). Parameters of this
patient were average standard uptake value (SUVavg), 17.51; maximum
SUV (SUVmax), 27.20; average tumor-to-cortex activity ratio
(T/Cavg), 3.37; ratio of count of maximum pixels in tumor to
average count per pixel in cortex (T/Cmax), 5.24; average
tumor-to-white matter activity ratio (T/WMavg), 5.43; and ratio of
count of maximum pixels in tumor to average count per pixel in white matter
(T/WMmax), 8.43.
|
|
View larger version (79K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 4B —17-year-old girl with glioblastoma multiforme. Corresponding
axial 18F-FDG PET image shows moderate FDG accumulation
(arrow). Parameters of this patient were average standard uptake
value (SUVavg), 11.25; maximum SUV (SUVmax), 13.73;
average tumor-to-cortex activity ratio (T/Cavg), 1.84; ratio of
count of maximum pixels in tumor to average count per pixel in cortex
(T/Cmax), 2.25; average tumor-to-white matter activity ratio
(T/WMavg), 3.84; and ratio of count of maximum pixels in tumor to
average count per pixel in white matter (T/WMmax),4.68.
|
|
View larger version (67K):
[in this window]
[in a new window]
[as a PowerPoint slide]
|
Fig. 5B —69-year-old man with metastatic adenocarcinoma from lung
cancer. Corresponding axial 18F-FDG PET image shows moderate FDG
accumulation (arrow). Parameters of this patient were average
standard uptake value (SUVavg), 6.17; maximum SUV
(SUVmax), 9.17; average tumor-to-cortex activity ratio
(T/Cavg), 1.52; ratio of count of maximum pixels in tumor to
average count per pixel in cortex (T/Cmax), 2.26; average
tumor-to-white matter activity ratio (T/WMavg), 2.28; and ratio of
count of maximum pixels in tumor to average count per pixel in white matter
(T/WMmax), 3.38.
|
|
When the lowest values of each CNS lymphoma parameter were used as cutoff
levels to distinguish CNS lymphomas from other tumors (i.e., 100%
sensitivity), SUVmax was the most accurate parameter (Fig.
2A,
2B,
2C). Using an SUVmax
of 15.0 as a cutoff for diagnosing CNS lymphoma, only one high-grade glioma
(SUVmax, 18.8; Fig.
2A) was found to be false-positive in our patient group.
Specificity and accuracy were not calculated in this study because no healthy
human patients or other conditions were included.
Discussion
Our results revealed FDG accumulation in common enhancing malignant brain
tumors, suggesting that FDG PET may be useful in distinguishing among these
brain tumors, particularly for distinguishing CNS lymphoma from high-grade
gliomas and metastatic brain tumors. We also found that SUVmax was
the most accurate parameter for distinguishing CNS lymphoma from other brain
tumors in our patient group.
Several indications for FDG PET have been suggested in patients with
malignant lymphoma. Useful roles for FDG PET have been established in staging,
evaluation of early response to chemotherapy, assessment of end response to
therapy, planning of radiation therapy, and follow-up
[8]. Regarding CNS lymphoma,
FDG PET is also reportedly useful for detecting tumors and distinguishing
lymphoma from other lesions showing marked FDG accumulation, particularly in
patients with AIDS [6,
9-13].
Our results are in accordance with those of previous reports, suggesting that
high FDG accumulation may indicate CNS lymphoma.
However, Rosenfeld et al.
[10] reported different
results that showed similar FDG accumulation between CNS lymphoma and
high-grade gliomas. They evaluated the activity ratios of FDG PET in 10
patients with CNS lymphoma and made comparisons with the ratios from 13
patients with high-grade glioma. That study found no significant differences
between ratios of CNS lymphoma and high-grade glioma, whereas our results
showed that all parameters were significantly higher for CNS lymphoma than for
high-grade glioma (p < 0.01). One possible explanation for this
discrepancy is that their study included more patients with steroid-treated
CNS lymphoma (seven of 10 patients) than our patient group did (two of seven
patients). Because steroids are known to have a cytotoxic effect in lymphoma
and are also known to reduce FDG accumulation in CNS lymphoma
[10], such steroid
administrations might have influenced FDG accumulation in the CNS lymphoma
group. In addition, opposite hemisphere ROIs in that study were placed in the
contralateral homologous region, including both cortex and white matter,
whereas our opposite hemisphere ROIs were placed over the contralateral cortex
and white matter separately. This difference in ROI placement on the opposite
hemisphere might have influenced activity ratios in both studies.
Hustinx et al. [14]
previously evaluated SUVs and activity ratios in primary brain tumors on FDG
PET and concluded that SUV measurements of brain tumor were influenced by a
wide variety of factors, such as plasma glucose level, steroid treatment,
tumor size and heterogeneity, time after injection, and previous irradiation;
and that SUV measurements appeared to be of limited value in characterizing
brain tumors compared with the measurement of activity ratios and visual
assessment. However, our results indicate that measurement of SUV is also
useful in distinguishing newly diagnosed brain tumors. Compared with the
results of Hustinx et al., SUVavg and SUVmax values in
our results were generally high because our patient group included CNS
lymphomas and metastatic brain tumors, which were not included in their study,
and our high-grade glioma group included a high proportion of glioblastoma
multiforme (seven of nine patients). Furthermore, most of their patients (22
of 27 patients) had been treated by irradiation before PET studies, whereas
none of our patients had been. We suppose that their mentioned influences in
SUV measurement may have been reduced in our study because of this relatively
higher SUV value.
Our study used the lowest values of each CNS lymphoma parameter as cutoff
levels to distinguish CNS lymphomas from other tumors, and we identified
SUVmax as the most accurate parameter to distinguish among lesions.
In malignant brain tumors, areas of necrosis are often identified throughout
the tumor, so we excluded apparent necrotic portions from the ROI because
necrotic portions show considerably less FDG accumulation and influence
average counts inside the ROI. However, excluding small foci of necrosis from
the ROI was impossible, and this might have influenced average counts in
tumors. Furthermore, excluding all normal or edematous brain tissue is
virtually impossible when drawing an ROI on a tumor. Using counts of the
maximum pixel can limit the importance of this factor. Also, SUVmax
may not be influenced by the variety of FDG accumulation in contralateral
brain tissue, which may vary with age
[15] or underlying diseases.
These factors might explain why SUVmax was the most accurate
parameter for distinguishing CNS lymphomas from other tumors in our study. Our
experiences also led us to the conclusion that SUVmax may be easier
to measure than activity ratio in clinical settings because we do not have to
exclude the necrotic portion of the tumor in the ROI and do not have to
measure the FDG accumulation in the contralateral brain tissue.
Using the cutoff level suggested in this study, the possibility of lymphoma
can be excluded, and the differential diagnosis can be narrowed to high-grade
glioma and metastatic brain tumor. Between these two tumors, we also found
that high-grade gliomas show significantly higher SUVavg and
SUVmax than metastatic tumors. However, considerable overlap exists
between these tumor types (Fig.
2A), which are thus unlikely to be distinguished by FDG
accumulation alone in clinical settings. In this regard, Jeong et al.
[16] showed that whole-body
FDG PET is useful for detecting primary lesions in patients with suspected
metastatic brain tumors and can be helpful in differentiating metastatic brain
tumor from primary brain tumor. Such whole-body screening is one of the
advantages of FDG PET compared with MRI.
The following limitations were identified in our study. First, the study
was retrospective and the number of patients was limited. Furthermore, all
entities other than lymphoma, high-grade glioma, and metastatic brain tumor
were excluded; and no patients displayed metastatic tumor from melanoma, which
is well known to show high FDG accumulation. If a prospective study with a
large number of patients can be undertaken, nontumorous enhancing brain
lesions (such as inflammation, demyelination, and subacute infarction), benign
brain tumors, and other types of metastatic brain tumors should be taken into
account and evaluated. Second, we used ROI-based analysis in this study. ROIs
were placed by the consensus of two nuclear medicine physicians, but they were
operator-dependent, which might have influenced the mean values in this study.
Fusion of PET with MRI would provide the best view for drawing tumor regions,
but that technique is not currently available at our institution. Third, two
attenuation corrections were used in this study (i.e., PET camera and PET/CT
camera). Nakamoto et al. [17]
previously evaluated the comparison of quantitative tracer uptake between
68Ge and CT transmission attenuation-corrected images in various
organs and concluded that quantitative radioactivity values are generally
comparable between CT- and 68Ge-corrected PET images except bone
lesions. This limitation is thus unlikely to have been crucial in the present
study. Finally, eight patients in this study were given a steroid to relieve
brain edema before their PET examination. As mentioned, steroids are known to
reduce FDG accumulation in CNS lymphoma
[10]. FDG accumulation in CNS
lymphoma would thus have been influenced by steroid administration in this
study. However, the use of steroids is unavoidable in clinical settings
because brain edema is a crucial problem in some patients. These steroid
administrations can thus be considered to correspond to typical clinical
situations.
In conclusion, FDG PET appears to provide additional useful information for
distinguishing lymphoma from other malignant enhancing brain tumors. We
consider that FDG PET should be recommended when difficulty is encountered in
narrowing the differential diagnosis on the basis of MRI alone.
References
- Bulakbasi N, Kocaoglu M, Ors F, Tayfun C, Ucoz T. Combination of
single-voxel proton MR spectroscopy and apparent diffusion coefficient
calculation in the evaluation of common brain tumors. Am J
Neuroradiol 2003; 24:225
-233[Abstract/Free Full Text]
- Calli C, Kitis O, Yunten N, Yurtseven T, Islekel S, Akalin T.
Perfusion and diffusion MR imaging in enhancing malignant cerebral tumors.
Eur J Radiol 2006;58
: 394-403[CrossRef][Medline]
- Hakyemez B, Erdogan C, Bolca N, Yildirim N, Gokalp G, Parlak M.
Evaluation of different cerebral mass lesions by perfusion-weighted MR
imaging. J Magn Reson Imaging 2006;24
: 817-824[CrossRef][Medline]
- Barker FG 2nd, Chang SM, Valk PE, Pounds TR, Prados MD.
18-Fluorodeoxyglucose uptake and survival of patients with suspected recurrent
malignant glioma. Cancer 1997;79
: 115-126[CrossRef][Medline]
- Delbeke D, Meyerowitz C, Lapidus RL, et al. Optimal cutoff levels
of F-18 fluorodeoxyglucose uptake in the differentiation of low-grade from
high-grade brain tumors with PET. Radiology1995; 195:47
-52[Abstract/Free Full Text]
- Palmedo H, Urbach H, Bender H, et al. FDG-PET in immunocompetent
patients with primary central nervous system lymphoma: correlation with MRI
and clinical follow-up. Eur J Nucl Med Mol Imaging2006; 33:164
-168[CrossRef][Medline]
- Charnley N, West CM, Barnett CM, et al. Early change in glucose
metabolic rate measured using FDG-PET in patients with high-grade glioma
predicts response to temozolomide but not temozolomide plus radiotherapy.
Int J Radiat Oncol Biol Phys 2006;66
: 331-338[Medline]
- Hoskin PJ. PET in lymphoma: what are the oncologist's needs?
Eur J Nucl Med Mol Imaging 2003;30
[suppl 1]:S37
-S41[Medline]
- O'Doherty MJ, Barrington SF, Campbell M, Lowe J, Bradbeer CS. PET
scanning and the human immunodeficiency virus-positive patient. J
Nucl Med 1997; 38:1575
-1583[Abstract/Free Full Text]
- Rosenfeld SS, Hoffman JM, Coleman RE, Glantz MJ, Hanson MW, Schold
SC. Studies of primary central nervous system lymphoma with
fluorine-18-fluorodeoxyglucose positron emission tomography. J Nucl
Med 1992; 33:532
-536[Abstract/Free Full Text]
- Villringer K, Jager H, Dichgans M, et al. Differential diagnosis of
CNS lesions in AIDS patients by FDG-PET. J Comput Assist
Tomogr 1995; 19:532
-536[Medline]
- Hoffman JM, Waskin HA, Schifter T, et al. FDG-PET in
differentiating lymphoma from nonmalignant central nervous system lesions in
patients with AIDS. J Nucl Med 1993;34
: 567-575[Abstract/Free Full Text]
- Kuwabara Y, Ichiya Y, Otsuka M, et al. High [18F] FDG uptake in
primary cerebral lymphoma: a PET study. J Comput Assist
Tomogr 1988; 12:47
-48[Medline]
- Hustinx R, Smith RJ, Benard F, Bhatnagar A, Alavi A. Can the
standardized uptake value characterize primary brain tumors on FDG-PET?
Eur J Nucl Med 1999;26
: 1501-1509[CrossRef][Medline]
- Loessner A, Alavi A, Lewandrowski KU, Mozley D, Souder E, Gur RE.
Regional cerebral function determined by FDG-PET in healthy volunteers: normal
patterns and changes with age. J Nucl Med1995; 36:1141
-1149[Abstract/Free Full Text]
- Jeong HJ, Chung JK, Kim YK, et al. Usefulness of whole-body
(18)F-FDG PET in patients with suspected metastatic brain tumors. J
Nucl Med 2002; 43:1432
-1437[Abstract/Free Full Text]
- Nakamoto Y, Osman M, Cohade C, et al. PET/CT: comparison of
quantitative tracer uptake between germanium and CT transmission
attenuation-corrected images. J Nucl Med2002; 43:1137
-1143[Abstract/Free Full Text]
CiteULike 
Complore 
Connotea 
Del.icio.us 
Digg 
Reddit 
Technorati What's this?
Top
Abstract
Introduction
