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Preliminary study for differential diagnosis of intracranial tumors using in vivo quantitative proton MR spectroscopy with correction for T2 relaxation time
Radiography 21 (2015) 42e46
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Preliminary study for differential diagnosis of intracranial tumors using in vivo quantitative proton MR spectroscopy with correction for T2 relaxation time Tomonori Isobe a, *, Tetsuya Yamamoto b, Hiroyoshi Akutsu b, Masanari Shiigai c, Yasushi Shibata b, Kenta Takada a, Tomohiko Masumoto c, Izumi Anno d, Akira Matsumura b a
Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, Japan c Department of Radiology, Faculty of Medicine, University of Tsukuba, Japan d Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 November 2012 Received in revised form 29 May 2014 Accepted 3 June 2014 Available online 21 June 2014
Introduction: The intent of this study was to differentiate intracranial tumors using the metabolite concentrations obtained by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton magnetic resonance spectroscopy (MRS). Methods: All proton MRS studies were performed on a clinical 1.5T MR system. 7 normal volunteers and 57 patients (gliomas, metastases, meningiomas, acoustic neuromas, and pituitary adenomas) underwent single voxel proton MRS with different echo times (TE: 68, 136, 272 ms) for T2 correction of signal derived from metabolites and tissue water. With tissue water employed as an internal reference, the concentrations of metabolite (i.e. N-acetylaspartate (NAA), total creatine (t-Cr) and choline-containing compounds (Cho)) were calculated. Moreover, proton MRS data of previously published typical literatures were critically reviewed and compared with our data. Results: Extramedullary tumors were characterized by absence of NAA compared with intramedullary tumors. High-grade glioma differed from low-grade glioma by lower t-Cr concentrations. Metastasis differed from cystic glioblastoma by higher Cho concentrations, lower t-Cr concentrations, an absence of NAA, and a prominent Lipids peak. Based on these results and review of previous reports, we suggest a clinical pathway for the differentiation of intracranial tumors. Conclusion: The metabolite concentrations obtained by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton MRS is useful for the diagnosis of the intracranial tumors. © 2014 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
Keywords: MRS Tumor Metabolite Quantification T2 relaxation time
Introduction Differential diagnosis of intracranial tumors is an ongoing issue in neuroradiology. As a noninvasive method allowing inspection of intratumoral biochemical changes, proton magnetic resonance spectroscopy (MRS) has been reported to be useful in neurological differential diagnosis.1e5 For example, it has been reported that
* Corresponding author. Graduate School of Comprehensive Human Sciences, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan. Tel.: þ81 29 853 7834; fax: þ81 29 853 7102. E-mail address: [email protected] (T. Isobe).
most intracranial tumors can be reliably classified by their spectral pattern at either long echo time (TE) or short TE,6,7 and that an increase in the choline-containing compounds (Cho)/total creatine (t-Cr) ratio is consistent with tumor malignancy.8,9 Most previous proton MRS studies have focused on the qualitative (e.g. spectral pattern) or semi-quantitative (e.g. metabolite ratio) features of the tumors. Nevertheless, neither spectral pattern nor metabolite ratio is able to provide precise identification. The exact quantitative determination for metabolism is necessary to classify the tumors. Recently there have been some reports regarding quantitative proton MRS of brain tumors.10e13 However, some ambiguities in quantification such as the influence of the
http://dx.doi.org/10.1016/j.radi.2014.06.002 1078-8174/© 2014 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
T. Isobe et al. / Radiography 21 (2015) 42e46
pathologically changed metabolite T2 relaxation time have not yet been clarified. The intent of the present study was to differentiate intracranial tumors using the metabolite concentrations by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton MRS. This differentiation was to include three major issues: intramedullary tumors vs. extramedullary tumors, low-grade glioma vs. high-grade glioma, and glioblastoma (GBM) vs. metastasis. Materials and methods Subjects Seven normal volunteers (3 males and 4 females, age range 20e26 years) were examined as a control. Proton MRS was performed twice on the control subjects at different times (the time interval was 14 days), so the control group was counted as 14 cases. Fifty-seven patients (25 males and 32 females, age range 26e64 years) with intracranial tumors were included in the study. Surgery and pathological studies confirmed the presence of 13 high-grade gliomas (3 anaplastic gliomas of grade III and 10 GBM of grade IV), 10 low-grade gliomas (grade I and II), 6 metastases, 16 meningiomas, 7 acoustic neuromas, and 5 pituitary adenomas. These were classified into histological types according to the World Health Organization 2007 classification of brain tumors.14 Signed informed consents were obtained from all patients before the study. This was retrospective study on a part of the data from institutional review-board -approved prospective study on proton MRS of brain tumors. Proton MRS Proton MRS studies were performed on a clinical 1.5 T MR whole body system (GYROSCAN Intera 1.5T, Philips Medical Systems) with a circularly polarized head coil. T2-weighted MR imaging was first carried out in three orthogonal planes to define the volume of interest (VOI). Single voxel proton MRS was performed using the point-resolved spectroscopy (PRESS) sequence. For volunteers, a voxel of 8 ml was placed in the parieto-occipital white matter. For patients, the voxel size ranged from 1 to 12 ml in order to contain as large an area as possible of the solid part of the tumor while avoiding contamination of the necrotic part or neighboring normal tissues. However, it was not always possible to avoid contamination for GBM and metastasis in which cystic changes were common. Before the spectroscopic measurements were obtained, the field homogeneity was optimized over the selected VOI by observing the proton MR signal of the tissue water with the spatially selective PRESS sequence by automatic shimming. The typical full width achieved was half of the maximum 5 Hz in most examinations. Water suppression was not performed when the measurement of tissue water was desired. When measuring the metabolites, water suppression was accomplished by chemical-shift-selective (CHESS) pulses with a bandwidth of 60 Hz. The parameters of the PRESS sequence were as follows: TR/TE ¼ 2000/68, 136 and 272 ms; spectral width ¼ 1000 Hz; data points ¼ 512; number of signals averaged (NSA) 128 in metabolites and 16 in tissue water. With the standard Philips software on console, raw spectral data were zero-filled to 1024 points, filtered by a Gaussian of width 3 Hz and an exponential of characteristic length 1 Hz (negative), Fourier transformed, and manually corrected for zero-order phase and chemical shift with the water peak as the reference. The spectrum peaks were confirmed as: water at 4.7 ppm, N-acetylaspartate (NAA) at 2.02 ppm, t-Cr at 3.02 ppm, Cho at 3.22 ppm, lactate (Lac)
43
at 1.33 ppm, and lipids (Lip) from 0.9 ppm to 1.4 ppm by means of standard Phillips software. The differential diagnosis by a spectrum used patient information as the blind, and was performed by one neurosurgeon and one radiologist. Calculation of metabolite concentrations We have previously discussed the methods to calculate metabolite concentrations.15 Metabolite concentrations (NAA, t-Cr and Cho) were calculated using a tissue water concentration of 64.6% (35 mol/kg wet weight) as an internal reference. The concentrations of metabolites in vivo were calculated using the following equation (1):
2 S metsbolite n Swater TE TR exp 1exp T2metabolite T1water TE TR exp 1exp T2water T1metabolite
Cmetabolite ¼ Cwater
(1)
where Cmetabolite is the metabolite concentration (mmol/kg wet weight), Cwater is the water concentration (35 mol/kg wet weight), Smetabolite is the signal intensity of the metabolite, Swater is the signal intensity of water, n is the number of protons in a given metabolite, TE is the actually used TE (136 ms), TR is the actually used TR (2000 ms), T1water is water T1 relaxation time, T1metobolite is metabolite T1 relaxation time, T2water is water T2 relaxation time, and T2metobolite is metabolite T2 relaxation time. Spectra acquired using a TR of 2000 ms and TE of 136 ms were used in the calculations of metabolite concentrations. Metabolite and tissue water peaks were corrected for the number of contributing protons, and T2 relaxation times were measured in each VOI separately. Since T1 relaxation is very time consuming, it is not realistic to measure it in the clinical limited time. Moreover, when data acquisition is carried out with TR 2000 ms, simulation suggests that calculated metabolite concentrations are in error by less than 10%. Therefore, we did not perform patient-specific T1 compensation, but instead performed compensation using average T1 values from the normal volunteers.15 For the T2 relaxation time measurement, TR of 2000 ms and TE of 68 ms, 136 ms, 272 ms were used. The T2 relaxation time of metabolites and water were calculated by fitting them to the curve of the spin echo sequence using the following equation (2):
TE MS ¼ M0 exp T2
(2)
where MS denotes the signal intensity of the measurement at a given TE, M0 denotes the signal intensity at a TE of 0, and t denotes TE/2. For this 3-point T2 measurement, about 20 min in all are required for the time of pre-scan. Results The result obtained in this study, which are existence of metabolites and quantitative value of metabolites in tumors, are presented in Tables 1 and 2, respectively. Moreover, we showed the spectrum of low-grade glioma as one example of intramedullary tumor (Fig. 1), and the spectrum of meningioma as one example of extramedullary tumor (Fig. 2). The average concentrations of NAA, t-Cr and Cho in the normal white matter (NWM) were 10.78, 7.73
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T. Isobe et al. / Radiography 21 (2015) 42e46
Table 1 Existence of metabolite in normal brain and various brain tumors. Diagnosis
Number of cases
NAA (þ)a
t-Cr (þ)a
Cho (þ)a
Lac (þ)a
Lip (þ)a
Normal brain Low-grade glioma High-grade glioma Metastasis Meningioma Acoustic neuroma Pituitary adenoma All glioma Glioblastoma
7 10 13 6 16 7 5 23 10
7 10 10 0 0 0 0 20 7
7 10 13 3 7 2 0 23 10
7 10 13 6 16 7 5 23 10
0 2 13 6 0 0 0 15 10
0 0 13 6 0 0 0 13 10
a
(þ): It is shown that each metabolite exists.
and 2.10 mmol/kg wet weight, respectively.15 Moreover, in NWM, Lac or Lip was observed in no cases. As compared with NWM, decreased NAA and t-Cr and elevated Cho were found to be characteristic of glioma. Lac and/or Lip were observed in 2/10 cases lowgrade glioma and 13/13 cases high-grade glioma. Both Cho and t-Cr concentrations of high-grade glioma compared with low-grade glioma were significantly lower by 35% (P < 0.01) and 28% (P < 0.001), respectively. NAA concentrations of high-grade glioma compared with low-grade glioma were also lower, but the statistical significance was not confirmed. As compared with NWM, metastasis had significantly (P < 0.001) elevated Cho. Although t-Cr was detected with 3/6 cases, only 1 case of them could be reliably quantified. In metastasis, NAA was absent in all cases. Moreover, Lac and/or Lip have a prominent peak in all cases. Meningioma and acoustic neurinoma had similar spectra demonstrating significantly elevated Cho and decreased or absent t-Cr. Moreover, Lac or Lip was observed in no cases. Pituitary adenoma demonstrated a prominent Cho peak with an absence of t-Cr and NAA.
Figure 1. Proton MRS of low-grade glioma. (a): T1-weighted axial images (TR 500 ms/ TE 15 ms) after administration of Gd-DTPA does not show the enhancement. (b): T2weighted images (TR 2000 ms/TE 80 ms) show high signal intensity. A black line is VOI of proton MRS. VOI size is 1.5 cm 1.2 cm 1.5 cm (c): Proton MRS was acquired TR/TE ¼ 2000 ms/136 ms. Decreased NAA and t-Cr and elevated Cho were found to be characteristic of low-grade glioma. Lac and/or Lip were not observed at all or were increasing slightly.
Discussion In this study, we analyzed the existence of metabolites (NAA, tCr, Cho, Lac, Lip) and a quantitative value of metabolites (NAA, t-Cr, Cho) in various tumors. First, we were able to acquire quantitative value of the metabolites (NAA, t-Cr and Cho) which were calculated using metabolites and tissue water (internal reference) corrected T2 relaxation time. Secondary, NAA was absent in extramedullary tumors (meningiomas, acoustic neuromas, and pituitary adenomas) different from intramedullary tumor (gliomas). Thirdly, the quantitative value of t-Cr in high-grade glioma was significantly
Table 2 Quantitative value of metabolite in normal brain and various brain tumors. Diagnosis
NAA
t-Cr
Normal brain (n ¼ 14)a,b Low-grade glioma (n ¼ 10)b High-grade glioma (n ¼ 13)b Metastasis (n ¼ 6) Meningioma (n ¼ 16) Acoustic neuroma (n ¼ 7) Pituitary adenoma (n ¼ 5) All gliomac (n ¼ 23) Glioblastoma (n ¼ 10)
10.78 ± 0.40 3.87 ± 1.33** 2.64 ± 1.71** e e e e 3.27 ± 1.64 2.64 ± 1.88
7.73 6.03 4.33 0.79 1.86 1.13 e 5.13 4.20
Cho ± ± ± ± ± ±
0.40 0.64** 0.60** 1.94** 2.36** 1.78**
± 1.04** ± 0.54**
2.10 4.00 2.58 4.35 4.59 4.46 8.15 3.25 2.60
± ± ± ± ± ± ± ± ±
0.13 1.04** 0.58* 1.49** 1.65** 1.30** 3.58** 1.05** 0.64*
Values (mmol/kg wet weight) are mean ± SD. e: not detected ManneWhitney, *P < 0.01, **P < 0.001 relative to normal brain. a Since two measurement was performed by seven normal volunteers, respectively, it was set to n ¼ 14. b Our published data (ref. 15). c All glioma means the summation of low-grade and high-grade gliomas.
lower than in low-grade glioma. Fourthly, in metastasis compared with GBM, we discovered the feature that NAA is absent, Cho is high and Lip is very large. It has been demonstrated that tissue water T2 relaxation time changes during various pathological processes.16e18 Because different pathological processes result in different intra-cellular environments, paramagnetic materials, and magnetic susceptibility, metabolite T2 susceptible to these factors may also be changed.15,19,20 As such, it is clinically meaningful to measure the individual tissue water T2 relaxation time and metabolite T2 relaxation time from two expectations. First, measurement and correction of T2 relaxation time benefits a reliable calculation of metabolite concentration. Second, characterization of tissues by individual T2 relaxation time may provide useful, tissue-specific information for differentiation. We therefore used three TEs of 68, 136 and 272 ms among which T2 decay data were contained. To our knowledge, we are the first to use individually corrected T2 relaxation time for in vivo quantitative proton MRS study of intracranial tumors. We did not use the short TE series in order to avoid the baseline distortion of spectra in that case, but this was at the cost that signals from short-TE metabolites such as Lip, inositol, and glutamine/glutamate may not be well-detected. We therefore excluded inositol and glutamine/glutamate from further analysis, but we still retained Lip for the qualitative study. We considered the measurement of MRS by TE of 3 points. Lip has a large resonance frequency and overlaps a Lac peak. T2 relaxation time of Lac is long. T2 relaxation time of Lip is very short. Therefore, two peaks are separable with the difference of the T2 relaxation time of Lac and
T. Isobe et al. / Radiography 21 (2015) 42e46
Figure 2. Proton MRS of meningioma. (a): T1-weighted axial images (TR 500 ms/TE 15 ms) after administration of Gd-DTPA show the enhancement in the un-uniformity. (b): T2-weighted images (TR 2000 ms/TE 80 ms) show iso-high signal intensity. A black line is VOI of proton MRS. VOI size is 1.3 cm 1.6 cm 1.4 cm (c): Proton MRS was acquired TR/TE ¼ 2000 ms/136 ms. In meningioma, the increase in Cho and the decreased or absent of t-Cr were caught.
Lip. Separation of Lip and Lac cannot be performed in the MRS measurement by TE of 1 point. Moreover, in the MRS measurement by TE of 3points, it becomes possible to find T2 relaxation time of metabolite. We think that T2 relaxation time has a clinical meaning. Moreover, in this measurement, VOI was set up and measured as much as possible into the real portion of the tumor. However, since the minimum voxel size in proton MRS measurement is decided by balance of data acquisition time and a signal to noise ratio, it also has the technical limit in the measurement itself. In the present study, NAA was absent in all 28 extramedullary tumors (16 meningiomas, 7 acoustic neuromas, and 5 pituitary adenomas), while it was observed in most (20/23) intramedullary tumor (gliomas). This result is in agreement with the previous reports.21,22 Therefore, proton MRS is thought to be useful in the differentiation of intra- and extramedullary tumors by the detection of NAA. However, it has been reported that contamination of neighboring brain tissue into the VOI of extramedullary tumor might result in a NAA peak.23 On the other hand, in our study there were 3 high-grade gliomas in which NAA was not detected, probably due to the complete destruction of neurons or to necrosis within the tumor. For both cases, differentiation by proton MRS could be difficult. Our quantitative studies indicated that the Cho and t-Cr concentrations may provide helpful information. Compared with all gliomas, Cho concentrations of meningioma were 41% higher (P < 0.01), acoustic neurinoma were 34% higher (P < 0.05), and pituitary adenoma were 250% (P < 0.001) higher, respectively. Conversely t-Cr concentrations were 64% (P < 0.01) lower in meningioma and 78% lower (P < 0.001) in acoustic neurinoma than in all gliomas. Namely, the Cho concentrations were
45
found to be higher, while the t-Cr concentrations were lower in extramedullary tumors than in intramedullary tumors. This explained by individual metabolite changes why Cho/t-Cr was higher in meningioma than in glioma in previous semi-quantified studies.24,25 Originally, since it is biologically various, low-grade glioma and high-grade glioma cannot be simply divided into two kinds. Quantitative evaluation by using proton MRS enabled us to inspect the change in Cho and t-Cr separately. As we had anticipated, t-Cr concentrations of high-grade glioma were significantly lower than in low-grade glioma. On the other hand, contrary to our expectation, Cho concentrations of high-grade glioma were significantly lower than in low-grade glioma. This result could be explained by the contamination of necrotic area within the VOI of some GBM cases. GBM tends to include necrosis and that contamination of necrotic parts cannot always be avoided, therefore, we conclude that the major contributor of increased Cho/t-Cr in high-grade glioma (especially in GBM) as compared to low-grade glioma is the significantly decreased t-Cr, instead of increased Cho. This means that high-grade glioma contains the area of impaired energy metabolism, which was verified by the high appearance rate of Lac and/or Lip (13/13) among cases of high-grade glioma, and also by another quantitative proton MRS study.12 In addition, there was no significant difference in NAA concentrations between high- and low-grade glioma, thus NAA concentration is not applicable for their differentiation. Our findings are consistent with in vitro, highresolution proton MRS study of brain tumor specimens,21 but partially dispute other research using external calibration10 or without T2 relaxation time correction.11 NAA was absent in all 6 metastases and 3/10 GBM. t-Cr was observed in all 6 GBM but only 3/6 metastases. t-Cr peaks of metastasis were around noise level, and in only 1 case could be reliably quantified. It is considered that the Lip peak of metastasis was more robust than that of GBM, but quantified analysis was not performed. Quantitative analysis showed that Cho concentrations of metastasis were significantly (P < 0.01) higher than those of GBM. Differentiation of cystic GBM from solitary metastasis has always been a challenge for clinical diagnosis.26,27 Both GBM and metastasis demonstrate cystic mass, ring-like enhancement and extensive peri-tumoral edema. They also have some similar spectral features like increased Cho and decreased t-Cr, usually paired with Lac and/or Lip. It has previously been reported that metastasis is characterized by the absence of NAA and t-Cr, and much more prominent Lip compared with GBM.28e30 Our result is consistent with these findings. Other research has focused on the peri-tumoral region of edema, and it has been reported that Cho/t-Cr of metastasis in this region remains normal, while it increases in GBM.31e33 We did not perform additional measurements in such regions either due to the small size of many metastases, or to the ambiguity between tumor and peritumoral regions. However, our quantitative study indicated that Cho concentrations of metastasis were significantly higher than those of GBM, whereas the t-Cr concentrations were significantly lower. Thus quantitative proton MRS is also useful in neurological differential diagnosis. These findings are also consistent with in vitro, high-resolution proton MRS study of brain tumor specimens21 but are in conflict with other research that found no significant difference.12 Perfusion MRI may be used for the differential diagnosis of a brain tumor.32 However, perfusion MRI is evaluation of blood flow. MRS is evaluating the metabolism of an organization. We consider that the metabolic turnover change can catch the state of organization change more sharply than blood-flow change. Based on our results and review of previous reports,10e12,21e33 we propose a clinical pathway for the differential diagnosis of intracranial tumors (Fig. 3). In this clinical pathway, NAA plays a
46
T. Isobe et al. / Radiography 21 (2015) 42e46
Figure 3. Proposed a clinical pathway for the differential diagnosis of intracranial tumors. This figure is the classification of a brain tumor on the existence and increase/ decrease of metabolites. When NAA exists, we classify a tumor into intramedullary tumors (glioma). On the other hand, if NAA does not exist, we classify a tumor into extramedullary. If the decrease of t-Cr is large in Glioma, we will judge it as high-grade. If Lac and/or Lip exists in extramedullary tumors, we will classify it into metastasis. On the other hand, if Lac and/or Lip does not exist, we classify it into meningioma, acoustic neuromas and pituitary adenoma.
major role in the differentiation between intra- and extramedullary tumors. Lac and/or Lip are indicative of metastasis because they appear far more frequently in metastasis than in other extramedullary tumors. In meningioma, there is a report that Lac and/or Lip were detected.34,35 However, in those reports, it is atypical meningioma, or since tumor size is large, lactate is detected. We created Fig. 3 by typical meningioma. In contrast with previous studies assuming that t-Cr remains stable, our study demonstrated that both t-Cr concentrations and t-Cr T2 are always changing under different pathological conditions. Therefore, t-Cr can play a potential role in the differential diagnosis of intracranial tumors, especially in the grading of glioma. By using this proposed proton MRS pathway, differentiation between intracranial tumors can be performed simply and we expect that proton MRS may be more widely used in clinical diagnosis of intracranial tumors. Conclusion We aimed at the differential diagnosis of the intracranial tumor by proton MRS. Metabolite concentrations obtained by quantification with corrected T2 relaxation time and the spectral peak generated by the existence of metabolites in proton MRS is useful in the differential diagnosis of intracranial tumors. We suggest a new clinical pathway for the simplified diagnosis of these tumors. Funding No financial support for this study was provided. Conflict of interest statement The authors report no conflicts of interest. References 1. Kugel H, Heindel W, Ernestus RI, et al. Human brain tumors: spectral patterns detected with localized H-1MR spectroscopy. Radiology 1992;183:701e9. 2. Falini A, Calabrese G, Origgi D, et al. Proton magnetic resonance spectroscopy and intracranial tumors: clinical perspectives. J Neurol 1996;243:706e14. 3. Preul MC, Caramanos Z, Collins DL, et al. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy. Nat Med 1996;2:323e5. 4. Ott D, Hennig J, Ernst T. Human brain tumors: assessment with in vivo proton MR spectroscopy. Radiology 1993;186:745e52.
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Preoperative grading of gliomas by using metabolite quantification with high-spatial-resolution proton MR spectroscopic imaging. Radiology 2006;238:958e69. 11. Tong Z, Yamaki T, Harada K, et al. In vivo quantification of the metabolites in normal brain and brain tumors by proton MR spectroscopy using water as an internal standard. Magn Reson Imaging 2004;22:1017e24. 12. Howe FA, Barton SJ, Cudlip SA, et al. Metabolic profiles of human brain tumors using quantitative in vivo 1H magnetic resonance spectroscopy. Magn Reson Med 2003;49:223e32. 13. Panigrahy A, Krieger MD, Gonzalez-Gomez I, et al. Quantitative short echo time 1 H-MR spectroscopy of untreated pediatric brain tumors: preoperative diagnosis and characterization. AJNR Am J Neuroradiol 2006;27:560e72. 14. Louis DN, Ohgaki H, Wiestler OD, et al. The 2007 WHO classification of tumors of the central nervous system. Acta Neuropathol 2007;114:97e109. 15. Isobe T, Matsumura A, Anno I, et al. Quantification of cerebral metabolites in glioma patients with proton MR spectroscopy using T2 relaxation time correction. Magn Reson Imaging 2002;20:343e9. 16. Komiyama M, Yagura H, Baba M, et al. MR imaging: possibility of tissue characterization of brain tumors using T1 and T2 values. AJNR Am J Neuroradiol 1987;8:65e70. 17. Cameron IL, Ord VA, Fullerton GD. Characterization of proton NMR relaxation times in normal and pathological tissues by correlation with other tissue parameters. Magn Reson Imaging 1984;2:97e106. 18. Kiricuta Jr IC, Simplaceanu V. Tissue water content and nuclear magnetic resonance in normal and tumor tissues. Cancer Res 1975;35:1164e7. 19. Stubbs M, Veech RL, Griffiths JR. Tumor metabolism: the lessons of magnetic resonance spectroscopy. Adv Enzyme Regul 1995;35:101e15. 20. Kayama T, Yoshimoto T, Fujimoto S, et al. Intratumoral oxygen pressure in malignant brain tumor. J Neurosurg 1991;74:55e9. 21. Kinoshita Y, Yokota A. Absolute concentrations of metabolites in human brain tumors using in vitro proton magnetic resonance spectroscopy. NMR Biomed 1997;10:2e12. 22. Poptani H, Gupta RK, Roy R, et al. Characterization of intracranial mass lesions with in vivo proton MR spectroscopy. AJNR Am J Neuroradiol 1995;16: 593e1603. 23. Castillo M, Kwock L, Mukherji SK, et al. Clinical applications of proton MR spectroscopy. AJNR Am J Neuroradiol 1996;7:1e15. 24. Harada M, Tanouchi M, Nishitani H, et al. Non-invasive characterization of brain tumor by in-vivo proton magnetic resonance spectroscopy. Jpn J Cancer Res 1995;86:329e32. 25. Kumar A, Kaushik S, Tripathi RP, et al. Role of in vivo proton MR spectroscopy in the evaluation of adult brain lesions: our preliminary experience. Neurol India 2003;1:474e8. 26. Burtscher IM, Holtas S. Proton magnetic resonance spectroscopy in brain tumors: clinical applications. Neuroradiology 2001;43:345e52. 27. Gajewicz W, Papierz W, Szymczak W, et al. The use of proton MRS in the differential diagnosis of brain tumors and tumor-like processes. Med Sci Monit 2003;9:MT97e105. 28. Opstad KS, Murphy MM, Wilkins PR, et al. Differentiation of metastases from high-grade gliomas using short echo time 1H spectroscopy. J Magn Reson Imaging 2004;20:187e92. 29. Kimura T, Sako K, Gotoh T, et al. In vivo single-voxel proton MR spectroscopy in brain lesions with ring-like enhancement. NMR Biomed 2001;14:339e49. 30. Ishimaru H, Morikawa M, Iwanaga S, et al. Differentiation between high-grade glioma and metastatic brain tumor using single-voxel proton MR spectroscopy. Eur Radiol 2001;11:1784e91. 31. Fan G, Sun B, Wu Z, et al. In vivo single-voxel proton MR spectroscopy in the differentiation of high-grade gliomas and solitary metastases. Clin Radiol 2004;9:77e85. 32. Law M, Cha S, Knopp EA, et al. High-grade gliomas and solitary metastases: differentiation by using perfusion and proton spectroscopic MR imaging. Radiology 2002;222:715e21. 33. 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Preliminary study for differential diagnosis of intracranial tumors using in vivo quantitative proton MR spectroscopy with correction for T2 relaxation time Tomonori Isobe a, *, Tetsuya Yamamoto b, Hiroyoshi Akutsu b, Masanari Shiigai c, Yasushi Shibata b, Kenta Takada a, Tomohiko Masumoto c, Izumi Anno d, Akira Matsumura b a
Graduate School of Comprehensive Human Sciences, University of Tsukuba, Japan Department of Neurosurgery, Faculty of Medicine, University of Tsukuba, Japan c Department of Radiology, Faculty of Medicine, University of Tsukuba, Japan d Department of Radiological Sciences, Ibaraki Prefectural University of Health Sciences, Japan b
a r t i c l e i n f o
a b s t r a c t
Article history: Received 9 November 2012 Received in revised form 29 May 2014 Accepted 3 June 2014 Available online 21 June 2014
Introduction: The intent of this study was to differentiate intracranial tumors using the metabolite concentrations obtained by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton magnetic resonance spectroscopy (MRS). Methods: All proton MRS studies were performed on a clinical 1.5T MR system. 7 normal volunteers and 57 patients (gliomas, metastases, meningiomas, acoustic neuromas, and pituitary adenomas) underwent single voxel proton MRS with different echo times (TE: 68, 136, 272 ms) for T2 correction of signal derived from metabolites and tissue water. With tissue water employed as an internal reference, the concentrations of metabolite (i.e. N-acetylaspartate (NAA), total creatine (t-Cr) and choline-containing compounds (Cho)) were calculated. Moreover, proton MRS data of previously published typical literatures were critically reviewed and compared with our data. Results: Extramedullary tumors were characterized by absence of NAA compared with intramedullary tumors. High-grade glioma differed from low-grade glioma by lower t-Cr concentrations. Metastasis differed from cystic glioblastoma by higher Cho concentrations, lower t-Cr concentrations, an absence of NAA, and a prominent Lipids peak. Based on these results and review of previous reports, we suggest a clinical pathway for the differentiation of intracranial tumors. Conclusion: The metabolite concentrations obtained by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton MRS is useful for the diagnosis of the intracranial tumors. © 2014 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
Keywords: MRS Tumor Metabolite Quantification T2 relaxation time
Introduction Differential diagnosis of intracranial tumors is an ongoing issue in neuroradiology. As a noninvasive method allowing inspection of intratumoral biochemical changes, proton magnetic resonance spectroscopy (MRS) has been reported to be useful in neurological differential diagnosis.1e5 For example, it has been reported that
* Corresponding author. Graduate School of Comprehensive Human Sciences, University of Tsukuba , 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan. Tel.: þ81 29 853 7834; fax: þ81 29 853 7102. E-mail address: [email protected] (T. Isobe).
most intracranial tumors can be reliably classified by their spectral pattern at either long echo time (TE) or short TE,6,7 and that an increase in the choline-containing compounds (Cho)/total creatine (t-Cr) ratio is consistent with tumor malignancy.8,9 Most previous proton MRS studies have focused on the qualitative (e.g. spectral pattern) or semi-quantitative (e.g. metabolite ratio) features of the tumors. Nevertheless, neither spectral pattern nor metabolite ratio is able to provide precise identification. The exact quantitative determination for metabolism is necessary to classify the tumors. Recently there have been some reports regarding quantitative proton MRS of brain tumors.10e13 However, some ambiguities in quantification such as the influence of the
http://dx.doi.org/10.1016/j.radi.2014.06.002 1078-8174/© 2014 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.
T. Isobe et al. / Radiography 21 (2015) 42e46
pathologically changed metabolite T2 relaxation time have not yet been clarified. The intent of the present study was to differentiate intracranial tumors using the metabolite concentrations by quantification with correction for T2 relaxation time, and to analyze whether the spectrum peak was generated by the existence of metabolites in proton MRS. This differentiation was to include three major issues: intramedullary tumors vs. extramedullary tumors, low-grade glioma vs. high-grade glioma, and glioblastoma (GBM) vs. metastasis. Materials and methods Subjects Seven normal volunteers (3 males and 4 females, age range 20e26 years) were examined as a control. Proton MRS was performed twice on the control subjects at different times (the time interval was 14 days), so the control group was counted as 14 cases. Fifty-seven patients (25 males and 32 females, age range 26e64 years) with intracranial tumors were included in the study. Surgery and pathological studies confirmed the presence of 13 high-grade gliomas (3 anaplastic gliomas of grade III and 10 GBM of grade IV), 10 low-grade gliomas (grade I and II), 6 metastases, 16 meningiomas, 7 acoustic neuromas, and 5 pituitary adenomas. These were classified into histological types according to the World Health Organization 2007 classification of brain tumors.14 Signed informed consents were obtained from all patients before the study. This was retrospective study on a part of the data from institutional review-board -approved prospective study on proton MRS of brain tumors. Proton MRS Proton MRS studies were performed on a clinical 1.5 T MR whole body system (GYROSCAN Intera 1.5T, Philips Medical Systems) with a circularly polarized head coil. T2-weighted MR imaging was first carried out in three orthogonal planes to define the volume of interest (VOI). Single voxel proton MRS was performed using the point-resolved spectroscopy (PRESS) sequence. For volunteers, a voxel of 8 ml was placed in the parieto-occipital white matter. For patients, the voxel size ranged from 1 to 12 ml in order to contain as large an area as possible of the solid part of the tumor while avoiding contamination of the necrotic part or neighboring normal tissues. However, it was not always possible to avoid contamination for GBM and metastasis in which cystic changes were common. Before the spectroscopic measurements were obtained, the field homogeneity was optimized over the selected VOI by observing the proton MR signal of the tissue water with the spatially selective PRESS sequence by automatic shimming. The typical full width achieved was half of the maximum 5 Hz in most examinations. Water suppression was not performed when the measurement of tissue water was desired. When measuring the metabolites, water suppression was accomplished by chemical-shift-selective (CHESS) pulses with a bandwidth of 60 Hz. The parameters of the PRESS sequence were as follows: TR/TE ¼ 2000/68, 136 and 272 ms; spectral width ¼ 1000 Hz; data points ¼ 512; number of signals averaged (NSA) 128 in metabolites and 16 in tissue water. With the standard Philips software on console, raw spectral data were zero-filled to 1024 points, filtered by a Gaussian of width 3 Hz and an exponential of characteristic length 1 Hz (negative), Fourier transformed, and manually corrected for zero-order phase and chemical shift with the water peak as the reference. The spectrum peaks were confirmed as: water at 4.7 ppm, N-acetylaspartate (NAA) at 2.02 ppm, t-Cr at 3.02 ppm, Cho at 3.22 ppm, lactate (Lac)
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at 1.33 ppm, and lipids (Lip) from 0.9 ppm to 1.4 ppm by means of standard Phillips software. The differential diagnosis by a spectrum used patient information as the blind, and was performed by one neurosurgeon and one radiologist. Calculation of metabolite concentrations We have previously discussed the methods to calculate metabolite concentrations.15 Metabolite concentrations (NAA, t-Cr and Cho) were calculated using a tissue water concentration of 64.6% (35 mol/kg wet weight) as an internal reference. The concentrations of metabolites in vivo were calculated using the following equation (1):
2 S metsbolite n Swater TE TR exp 1exp T2metabolite T1water TE TR exp 1exp T2water T1metabolite
Cmetabolite ¼ Cwater
(1)
where Cmetabolite is the metabolite concentration (mmol/kg wet weight), Cwater is the water concentration (35 mol/kg wet weight), Smetabolite is the signal intensity of the metabolite, Swater is the signal intensity of water, n is the number of protons in a given metabolite, TE is the actually used TE (136 ms), TR is the actually used TR (2000 ms), T1water is water T1 relaxation time, T1metobolite is metabolite T1 relaxation time, T2water is water T2 relaxation time, and T2metobolite is metabolite T2 relaxation time. Spectra acquired using a TR of 2000 ms and TE of 136 ms were used in the calculations of metabolite concentrations. Metabolite and tissue water peaks were corrected for the number of contributing protons, and T2 relaxation times were measured in each VOI separately. Since T1 relaxation is very time consuming, it is not realistic to measure it in the clinical limited time. Moreover, when data acquisition is carried out with TR 2000 ms, simulation suggests that calculated metabolite concentrations are in error by less than 10%. Therefore, we did not perform patient-specific T1 compensation, but instead performed compensation using average T1 values from the normal volunteers.15 For the T2 relaxation time measurement, TR of 2000 ms and TE of 68 ms, 136 ms, 272 ms were used. The T2 relaxation time of metabolites and water were calculated by fitting them to the curve of the spin echo sequence using the following equation (2):
TE MS ¼ M0 exp T2
(2)
where MS denotes the signal intensity of the measurement at a given TE, M0 denotes the signal intensity at a TE of 0, and t denotes TE/2. For this 3-point T2 measurement, about 20 min in all are required for the time of pre-scan. Results The result obtained in this study, which are existence of metabolites and quantitative value of metabolites in tumors, are presented in Tables 1 and 2, respectively. Moreover, we showed the spectrum of low-grade glioma as one example of intramedullary tumor (Fig. 1), and the spectrum of meningioma as one example of extramedullary tumor (Fig. 2). The average concentrations of NAA, t-Cr and Cho in the normal white matter (NWM) were 10.78, 7.73
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Table 1 Existence of metabolite in normal brain and various brain tumors. Diagnosis
Number of cases
NAA (þ)a
t-Cr (þ)a
Cho (þ)a
Lac (þ)a
Lip (þ)a
Normal brain Low-grade glioma High-grade glioma Metastasis Meningioma Acoustic neuroma Pituitary adenoma All glioma Glioblastoma
7 10 13 6 16 7 5 23 10
7 10 10 0 0 0 0 20 7
7 10 13 3 7 2 0 23 10
7 10 13 6 16 7 5 23 10
0 2 13 6 0 0 0 15 10
0 0 13 6 0 0 0 13 10
a
(þ): It is shown that each metabolite exists.
and 2.10 mmol/kg wet weight, respectively.15 Moreover, in NWM, Lac or Lip was observed in no cases. As compared with NWM, decreased NAA and t-Cr and elevated Cho were found to be characteristic of glioma. Lac and/or Lip were observed in 2/10 cases lowgrade glioma and 13/13 cases high-grade glioma. Both Cho and t-Cr concentrations of high-grade glioma compared with low-grade glioma were significantly lower by 35% (P < 0.01) and 28% (P < 0.001), respectively. NAA concentrations of high-grade glioma compared with low-grade glioma were also lower, but the statistical significance was not confirmed. As compared with NWM, metastasis had significantly (P < 0.001) elevated Cho. Although t-Cr was detected with 3/6 cases, only 1 case of them could be reliably quantified. In metastasis, NAA was absent in all cases. Moreover, Lac and/or Lip have a prominent peak in all cases. Meningioma and acoustic neurinoma had similar spectra demonstrating significantly elevated Cho and decreased or absent t-Cr. Moreover, Lac or Lip was observed in no cases. Pituitary adenoma demonstrated a prominent Cho peak with an absence of t-Cr and NAA.
Figure 1. Proton MRS of low-grade glioma. (a): T1-weighted axial images (TR 500 ms/ TE 15 ms) after administration of Gd-DTPA does not show the enhancement. (b): T2weighted images (TR 2000 ms/TE 80 ms) show high signal intensity. A black line is VOI of proton MRS. VOI size is 1.5 cm 1.2 cm 1.5 cm (c): Proton MRS was acquired TR/TE ¼ 2000 ms/136 ms. Decreased NAA and t-Cr and elevated Cho were found to be characteristic of low-grade glioma. Lac and/or Lip were not observed at all or were increasing slightly.
Discussion In this study, we analyzed the existence of metabolites (NAA, tCr, Cho, Lac, Lip) and a quantitative value of metabolites (NAA, t-Cr, Cho) in various tumors. First, we were able to acquire quantitative value of the metabolites (NAA, t-Cr and Cho) which were calculated using metabolites and tissue water (internal reference) corrected T2 relaxation time. Secondary, NAA was absent in extramedullary tumors (meningiomas, acoustic neuromas, and pituitary adenomas) different from intramedullary tumor (gliomas). Thirdly, the quantitative value of t-Cr in high-grade glioma was significantly
Table 2 Quantitative value of metabolite in normal brain and various brain tumors. Diagnosis
NAA
t-Cr
Normal brain (n ¼ 14)a,b Low-grade glioma (n ¼ 10)b High-grade glioma (n ¼ 13)b Metastasis (n ¼ 6) Meningioma (n ¼ 16) Acoustic neuroma (n ¼ 7) Pituitary adenoma (n ¼ 5) All gliomac (n ¼ 23) Glioblastoma (n ¼ 10)
10.78 ± 0.40 3.87 ± 1.33** 2.64 ± 1.71** e e e e 3.27 ± 1.64 2.64 ± 1.88
7.73 6.03 4.33 0.79 1.86 1.13 e 5.13 4.20
Cho ± ± ± ± ± ±
0.40 0.64** 0.60** 1.94** 2.36** 1.78**
± 1.04** ± 0.54**
2.10 4.00 2.58 4.35 4.59 4.46 8.15 3.25 2.60
± ± ± ± ± ± ± ± ±
0.13 1.04** 0.58* 1.49** 1.65** 1.30** 3.58** 1.05** 0.64*
Values (mmol/kg wet weight) are mean ± SD. e: not detected ManneWhitney, *P < 0.01, **P < 0.001 relative to normal brain. a Since two measurement was performed by seven normal volunteers, respectively, it was set to n ¼ 14. b Our published data (ref. 15). c All glioma means the summation of low-grade and high-grade gliomas.
lower than in low-grade glioma. Fourthly, in metastasis compared with GBM, we discovered the feature that NAA is absent, Cho is high and Lip is very large. It has been demonstrated that tissue water T2 relaxation time changes during various pathological processes.16e18 Because different pathological processes result in different intra-cellular environments, paramagnetic materials, and magnetic susceptibility, metabolite T2 susceptible to these factors may also be changed.15,19,20 As such, it is clinically meaningful to measure the individual tissue water T2 relaxation time and metabolite T2 relaxation time from two expectations. First, measurement and correction of T2 relaxation time benefits a reliable calculation of metabolite concentration. Second, characterization of tissues by individual T2 relaxation time may provide useful, tissue-specific information for differentiation. We therefore used three TEs of 68, 136 and 272 ms among which T2 decay data were contained. To our knowledge, we are the first to use individually corrected T2 relaxation time for in vivo quantitative proton MRS study of intracranial tumors. We did not use the short TE series in order to avoid the baseline distortion of spectra in that case, but this was at the cost that signals from short-TE metabolites such as Lip, inositol, and glutamine/glutamate may not be well-detected. We therefore excluded inositol and glutamine/glutamate from further analysis, but we still retained Lip for the qualitative study. We considered the measurement of MRS by TE of 3 points. Lip has a large resonance frequency and overlaps a Lac peak. T2 relaxation time of Lac is long. T2 relaxation time of Lip is very short. Therefore, two peaks are separable with the difference of the T2 relaxation time of Lac and
T. Isobe et al. / Radiography 21 (2015) 42e46
Figure 2. Proton MRS of meningioma. (a): T1-weighted axial images (TR 500 ms/TE 15 ms) after administration of Gd-DTPA show the enhancement in the un-uniformity. (b): T2-weighted images (TR 2000 ms/TE 80 ms) show iso-high signal intensity. A black line is VOI of proton MRS. VOI size is 1.3 cm 1.6 cm 1.4 cm (c): Proton MRS was acquired TR/TE ¼ 2000 ms/136 ms. In meningioma, the increase in Cho and the decreased or absent of t-Cr were caught.
Lip. Separation of Lip and Lac cannot be performed in the MRS measurement by TE of 1 point. Moreover, in the MRS measurement by TE of 3points, it becomes possible to find T2 relaxation time of metabolite. We think that T2 relaxation time has a clinical meaning. Moreover, in this measurement, VOI was set up and measured as much as possible into the real portion of the tumor. However, since the minimum voxel size in proton MRS measurement is decided by balance of data acquisition time and a signal to noise ratio, it also has the technical limit in the measurement itself. In the present study, NAA was absent in all 28 extramedullary tumors (16 meningiomas, 7 acoustic neuromas, and 5 pituitary adenomas), while it was observed in most (20/23) intramedullary tumor (gliomas). This result is in agreement with the previous reports.21,22 Therefore, proton MRS is thought to be useful in the differentiation of intra- and extramedullary tumors by the detection of NAA. However, it has been reported that contamination of neighboring brain tissue into the VOI of extramedullary tumor might result in a NAA peak.23 On the other hand, in our study there were 3 high-grade gliomas in which NAA was not detected, probably due to the complete destruction of neurons or to necrosis within the tumor. For both cases, differentiation by proton MRS could be difficult. Our quantitative studies indicated that the Cho and t-Cr concentrations may provide helpful information. Compared with all gliomas, Cho concentrations of meningioma were 41% higher (P < 0.01), acoustic neurinoma were 34% higher (P < 0.05), and pituitary adenoma were 250% (P < 0.001) higher, respectively. Conversely t-Cr concentrations were 64% (P < 0.01) lower in meningioma and 78% lower (P < 0.001) in acoustic neurinoma than in all gliomas. Namely, the Cho concentrations were
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found to be higher, while the t-Cr concentrations were lower in extramedullary tumors than in intramedullary tumors. This explained by individual metabolite changes why Cho/t-Cr was higher in meningioma than in glioma in previous semi-quantified studies.24,25 Originally, since it is biologically various, low-grade glioma and high-grade glioma cannot be simply divided into two kinds. Quantitative evaluation by using proton MRS enabled us to inspect the change in Cho and t-Cr separately. As we had anticipated, t-Cr concentrations of high-grade glioma were significantly lower than in low-grade glioma. On the other hand, contrary to our expectation, Cho concentrations of high-grade glioma were significantly lower than in low-grade glioma. This result could be explained by the contamination of necrotic area within the VOI of some GBM cases. GBM tends to include necrosis and that contamination of necrotic parts cannot always be avoided, therefore, we conclude that the major contributor of increased Cho/t-Cr in high-grade glioma (especially in GBM) as compared to low-grade glioma is the significantly decreased t-Cr, instead of increased Cho. This means that high-grade glioma contains the area of impaired energy metabolism, which was verified by the high appearance rate of Lac and/or Lip (13/13) among cases of high-grade glioma, and also by another quantitative proton MRS study.12 In addition, there was no significant difference in NAA concentrations between high- and low-grade glioma, thus NAA concentration is not applicable for their differentiation. Our findings are consistent with in vitro, highresolution proton MRS study of brain tumor specimens,21 but partially dispute other research using external calibration10 or without T2 relaxation time correction.11 NAA was absent in all 6 metastases and 3/10 GBM. t-Cr was observed in all 6 GBM but only 3/6 metastases. t-Cr peaks of metastasis were around noise level, and in only 1 case could be reliably quantified. It is considered that the Lip peak of metastasis was more robust than that of GBM, but quantified analysis was not performed. Quantitative analysis showed that Cho concentrations of metastasis were significantly (P < 0.01) higher than those of GBM. Differentiation of cystic GBM from solitary metastasis has always been a challenge for clinical diagnosis.26,27 Both GBM and metastasis demonstrate cystic mass, ring-like enhancement and extensive peri-tumoral edema. They also have some similar spectral features like increased Cho and decreased t-Cr, usually paired with Lac and/or Lip. It has previously been reported that metastasis is characterized by the absence of NAA and t-Cr, and much more prominent Lip compared with GBM.28e30 Our result is consistent with these findings. Other research has focused on the peri-tumoral region of edema, and it has been reported that Cho/t-Cr of metastasis in this region remains normal, while it increases in GBM.31e33 We did not perform additional measurements in such regions either due to the small size of many metastases, or to the ambiguity between tumor and peritumoral regions. However, our quantitative study indicated that Cho concentrations of metastasis were significantly higher than those of GBM, whereas the t-Cr concentrations were significantly lower. Thus quantitative proton MRS is also useful in neurological differential diagnosis. These findings are also consistent with in vitro, high-resolution proton MRS study of brain tumor specimens21 but are in conflict with other research that found no significant difference.12 Perfusion MRI may be used for the differential diagnosis of a brain tumor.32 However, perfusion MRI is evaluation of blood flow. MRS is evaluating the metabolism of an organization. We consider that the metabolic turnover change can catch the state of organization change more sharply than blood-flow change. Based on our results and review of previous reports,10e12,21e33 we propose a clinical pathway for the differential diagnosis of intracranial tumors (Fig. 3). In this clinical pathway, NAA plays a
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T. Isobe et al. / Radiography 21 (2015) 42e46
Figure 3. Proposed a clinical pathway for the differential diagnosis of intracranial tumors. This figure is the classification of a brain tumor on the existence and increase/ decrease of metabolites. When NAA exists, we classify a tumor into intramedullary tumors (glioma). On the other hand, if NAA does not exist, we classify a tumor into extramedullary. If the decrease of t-Cr is large in Glioma, we will judge it as high-grade. If Lac and/or Lip exists in extramedullary tumors, we will classify it into metastasis. On the other hand, if Lac and/or Lip does not exist, we classify it into meningioma, acoustic neuromas and pituitary adenoma.
major role in the differentiation between intra- and extramedullary tumors. Lac and/or Lip are indicative of metastasis because they appear far more frequently in metastasis than in other extramedullary tumors. In meningioma, there is a report that Lac and/or Lip were detected.34,35 However, in those reports, it is atypical meningioma, or since tumor size is large, lactate is detected. We created Fig. 3 by typical meningioma. In contrast with previous studies assuming that t-Cr remains stable, our study demonstrated that both t-Cr concentrations and t-Cr T2 are always changing under different pathological conditions. Therefore, t-Cr can play a potential role in the differential diagnosis of intracranial tumors, especially in the grading of glioma. By using this proposed proton MRS pathway, differentiation between intracranial tumors can be performed simply and we expect that proton MRS may be more widely used in clinical diagnosis of intracranial tumors. Conclusion We aimed at the differential diagnosis of the intracranial tumor by proton MRS. Metabolite concentrations obtained by quantification with corrected T2 relaxation time and the spectral peak generated by the existence of metabolites in proton MRS is useful in the differential diagnosis of intracranial tumors. We suggest a new clinical pathway for the simplified diagnosis of these tumors. Funding No financial support for this study was provided. Conflict of interest statement The authors report no conflicts of interest. References 1. Kugel H, Heindel W, Ernestus RI, et al. Human brain tumors: spectral patterns detected with localized H-1MR spectroscopy. Radiology 1992;183:701e9. 2. Falini A, Calabrese G, Origgi D, et al. Proton magnetic resonance spectroscopy and intracranial tumors: clinical perspectives. J Neurol 1996;243:706e14. 3. Preul MC, Caramanos Z, Collins DL, et al. Accurate, noninvasive diagnosis of human brain tumors by using proton magnetic resonance spectroscopy. Nat Med 1996;2:323e5. 4. Ott D, Hennig J, Ernst T. Human brain tumors: assessment with in vivo proton MR spectroscopy. Radiology 1993;186:745e52.
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