Imaging of Primary Brain Tumors and Metastases with Fast Quantitative 3-Dimensional Magnetization Transfer Meritxell Garcia ∗ , Monika Gloor ∗ , Oliver Bieri, Ernst-Wilhelm Radue, Johanna M. Lieb, Dominik Cordier, Christoph Stippich From the Division of Diagnostic & Interventional Neuroradiology, Department of Radiology, Clinic for Radiology & Nuclear Medicine, University of Basel Hospital, Basel, Switzerland (MG, JML, CS); Division of Radiological Physics, Department of Radiology, Clinic for Radiology & Nuclear Medicine, University of Basel Hospital, Basel, Switzerland (MG, OB); Medical Imaging Analysis Center, University of Basel Hospital, Basel, Switzerland (EWR); and Department of Neurosurgery, University of Basel Hospital, Basel, Switzerland (DC).
ABSTRACT BACKGROUND AND PURPOSE: This study assesses whether magnetization transfer (MT) imaging provides additive information to conventional MRI in brain tumors. METHODS: MT data of 26 patients with neoplastic and metastatic brain tumors were analyzed at 1.5 T. For the 3 largest tumor groups investigated in this study—glioblastoma multiforme (GBM), meningiomas, and metastases—statistical comparisons were performed. Analyzed MT parameters included the magnetization transfer ratio (MTR) and 4 quantitative MT parameters (qMT): Relaxation times (T1, T2), exchange rate (kf), and macromolecular content (F). Total imaging time of high-resolution whole brain MTR and qMT imaging with balanced steady-state free precession required 9 minutes. Five ROIs were chosen: Contrastenhancing (T1W-CE), noncontrast-enhancing (T1W-non-CE), proximal hyperintensity (T2W-pSI), distal hyperintensity (T2W-dSI), and a reference (ref). RESULTS: Pathologies showed significant (P < .05) MT changes (MTR and qMT) compared to the reference. The T1W-CE, T1W-non-CE, and T2W-pSI ROIs of GBMs, meningiomas, and metastases showed significant differences in MTR and qMT estimates. Similar MTR with significant different qMT values were observed in several ROIs among different lesions. MT maps (MTR and qMT) indicated changes in tissue appearing unaffected on MRI in most glial tumors. CONCLUSIONS: MTR and qMT imaging enables a better differentiation between brain tumors and provides additive information to MRI. Keywords: Magnetic resonance imaging, magnetization transfer contrast imaging, neuroimaging, primary brain neoplasms, metastases. Acceptance: Received July 3, 2014, and in revised form December 4, 2014. Accepted for publication December 10, 2014. Correspondence: Address correspondence to Meritxell Garcia, University of Basel Hospital, Division of Diagnostic & Interventional Neuroradiology, Petersgraben 4, Basel, Switzerland, 4031. E-mail: [email protected]. ∗
Contributed equally to this article.
J Neuroimaging 2015;25:1007-1014. DOI: 10.1111/jon.12222
T2w imaging, qMT imaging provides absolute T1 and T2 values, hereby providing different information from conventional sequences. Recently, it has been shown that 2 tissues may generate a similar MTR though having a different amount of fractional macromolecular protons.17 Thus, simple MTR analysis might overlook potentially essential information for pathophysiological processes. The disadvantage of qMT imaging over MTR, however, is the need of the acquisition of extensive data and a much longer acquisition time (TA), as well as a sophisticated model analysis. The drawback of low resolution has been addressed by a novel MT-sensitized method using balanced steady-state free precession (bSSFP),18–21 providing whole brain isotropic MTR and qMT parameter maps, which, however, until recently still required TAs of about 30 minutes. The advantages of MT imaging (MTR and qMT) with bSSFP over common spoiled gradient echo (SPGR) sequences,4,8,22–24 has previously been analyzed in normal brain structures.17,25,26 In general, qMT parameters obtained with bSSFP were in good accordance with prior studies and, in contrast to studies using SPGR sequences for MT assessment, the bSSFP method allowed the analysis
Background and Purpose Magnetization transfer (MT) analyses tissue beyond conventional T1 and T2 weighting,1 and has been shown to be beneficial for the characterization of both normal2–4 and pathologic brain tissue, such as infarction,5,6 and white matter (WM) lesions.7–9 For brain tumors, the MT literature is limited to a few studies only,6,10,11 based on the simple assessment of the magnetization transfer ratio (MTR)6,7,11–14 or of quantitative MT (qMT) analysis in animals,15 principally because of the required extensive scanning times and the limited resolution of MT imaging (MTR and qMT) with conventional MT sequences. MT refers to the exchange of magnetization between “mobile” protons within free water (“free” proton pool) and protons bound to macromolecules (“bound” proton pool).16 The easiest method to get information from the bound protons is by performing 2 measurements: 1 with and 1 without presaturation of the macromolecular protons, so that an MTR image is obtained.16 This method is quite fast, however, only qualitative as MTR is composed of various sequence parameters and tissue-related qMT parameters, such as the macromolecular content (F), exchange rate (kf), and relaxation properties (T1, T2).16 Thus, contrary to conventional T1w and Copyright
◦ 2015 by the American Society of Neuroimaging C
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of even small brain structures due to its high resolution and provided a higher signal-to-noise ratio. Thanks to technical improvement and persevering sequence optimization, the TA for the assessment of MTR and qMT estimates altogether with bSSFP could be reduced to below 10 minutes by now.27 As conventional MRI has its limitations for tumor characterization, the aim of this study was to analyze the feasibility of fast whole brain MT-bSSFP imaging (MTR and qMT) for the characterization of brain tumors and metastases, and to assess whether additional information to conventional T1w and T2w imaging can be obtained with this advanced imaging technique.
alone, and 1 patient was not followed in our hospital after biopsy. MT imaging included the following: For relaxometry, 2 SPGR sequences with variable flip angles (FA; 3° and 17°; TR = 9.8 ms/TE 4.77 ms) were used for T1 mapping,28,29 and 2 bSSFP sequences with variable FA (15° and 35°) for T2 mapping. Quantitative MT parameters were based on 8 bSSFP sequences with different radiofrequency (RF) pulse durations (TRF = 230-2,100 μs; TR 2.68-4.55 ms) for estimation of F, kf, and MTR. A B1 map with 16 slices of 5 mm thickness was used for FA correction. Overall, relaxometry, qMT, and MTR imaging was completed in 9 minutes with an isotropic resolution of 1.3 mm.20,27 The study protocol was reviewed and approved by the Institutional Review Board.
Methods Subjects and Image Acquisition
Image Postprocessing
MR data of 26 patients (mean age 57 years, age range 32-81 years; 14 males, 12 females) receiving a standard tumor imaging protocol plus MT-bSSFP (MTR and qMT) at 1.5T (Avanto, Siemens) were retrospectively analyzed. Pathologies included 9 glioblastoma multiforme (GBMs; WHO IV), 4 meningiomas without anaplastic features, 7 metastases, and 6 glial tumors of intermediate malignancy (WHO II or III; 1 oligodendroglioma, 2 glial tumors with anaplastic features, 1 diffuse astrocytoma without definite signs of anaplasia, 2 anaplastic astrocytomas). Final diagnosis was based on histopathology of the cerebral lesions except for 4 lesions: For 1 small homogeneous dura-based mass, which remained unchanged on follow-up MRIs and was most suggestive for a meningioma, and in 3 patients with multiple lesions suggestive for metastases, whereby in 2 cases the primary tumor was confirmed by histology. The other patient in whom a gastric tumor was suspected and who showed multiple (>40) round lesions compatible with metastases was no longer followed as he was flown to his home country for palliative therapy. The time interval between initial diagnosis and the time point of the study was below 2.5 months, except for 2 meningiomas, whose time point of initial diagnosis could not be confidently assured. None of the patients had been operated or had received radiation or chemotherapy before the time point of the study. As far as followed in our hospital, the treatments after the study were the following for the respective patients: (A) For the GBMs: 3 x radiation and chemotherapy, 3 x aimed complete resection with following radiation and chemotherapy, 1 x radiation alone, 1 x partial resection followed by radiation, and 1 patient who was considered not operable and for whom a combined treatment with radiation and chemotherapy was suggested was not further followed in our hospital. (B) For the meningiomas: 3 x total resection with no definite signs of residual in follow-up MRIs, and 1 patient was not treated and showed a stable lesion on follow-up MRIs. (C) For the metastases: 1 x resection with suggested further oncologic therapy in another hospital (patient no longer followed), 3 x resection with following radiation therapy in 2 patients and combined radiation and chemotherapy in 1 patient, 2 patients with palliative radiation therapy, and 1 patient with palliative radiation and chemotherapy. (D) For the mixed glial tumors: 3 x resection with following radiation and chemotherapy in 2 patients (1 patient was no longer followed), 1 x radiation and chemotherapy, 1 patient radiation 1008
Image registration and brain segmentation were performed with the software FSL30 and AFNI.31 The MATLAB-based custom software was applied for FA correction and T1 and T2 determination.28,29 The “free” proton pool relaxation times are assumed to be T1,f = T1 and T2,f = T220 and are used for a pixel-by-pixel nonlinear least-squares fitting of F and kf.20,27 Five different regions of interest (ROIs) were manually drawn by an experienced neuroradiologist: (1) Contrastenhancing region (T1W-CE) (Fig 1); (2) Noncontrast-enhancing area (T1W-non-CE): Hypointense on T1w, isointense on T2w, and located next to the contrast-enhancing ROI (i.e. within or adjacent to the tumor core); (3) Proximate hyperintensity on T2w (T2W-pSI): Next to the contrast-enhancing tissue and thus within or as close to the tumor core as possible; (4) Distal hyperintensity on T2w (T2W-dSI): Most distant from the contrast-enhancing tissue as possible, and hence close to the normal appearing tissue; and (5) A reference ROI (ref): In the nonaffected WM, and drawn in the contralateral hemisphere except in some bilateral lesions where it was located in the less affected hemisphere farthest from the pathology. Due to the inhomogeneous appearance and different extent of the lesions to select an identical ROI for the respective regions of each lesion was not possible. Therefore, the ROIs had to be applied accordingly to the individual case, whereby they were defined as similar as possible. Hereby, the proximal 2 mm of the selected intensity area abutting the adjacent intensity areas were not included in the ROI in order to avoid partial volume effects. The set of ROIs was overlaid onto MTR and each individual quantitative parameter map to obtain mean values and standard deviations of MTR, T1, T2, F, and kf, according to Gloor et al.13
Statistical Analyses The Wilcoxon Mann-Whitney Test was applied for the evaluation of statistical significance (P < .05) between the different ROIs using MATLAB. GBMs, meningiomas, and metastases were included in the intertumoral statistical analysis (R Development Core Team, 2011). Hereby, a linear model was fitted for each combination of parameter and ROI. The response variable was the parameter (T1, T2, kf, F, MTR), the only explanatory variable consisting in the categorical variable indicating the tumor type. In tumors with repeated measurements, generalized estimating equations were used to obtain more reliable standard errors for the model coefficients.
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Fig 1. Representative region of interest (ROI) placed in the contrast-enhancing region on a T1w sequence with contrast (T1wCE) of a patient with a meningioma. The T1W-CE ROI is superimposed on the individual qMT maps for calculation of MTR (28.4% ± 1.2), T1 (1,101 ms ± 41), T2 (107 ms ± 13), kf (1.1 s−1 ± 0.1), and F (3.3% ± 0.5). Compared to the T1wCE image, more inhomogeneous signal alteration within and around the tumor core can be observed in the individual MT maps.
Fig 2. Conventional images (T1wCE and T2w-FLAIR) and MT maps (MTR, F, kf) of a patient with a malignant pleomorphic glial tumor in the left temporal and occipital lobes showing contralateral tumor extension via the splenium of the corpus callosum. Abnormal MT values can be discerned ventrally and laterally to the altered looking tissue on conventional MRI (black arrows).
An ANOVA (or rather an “Analysis of ‘Wald statistic”’) table was compiled for the fitted model and a χ 2 statistic was calculated in order to test for an overall effect of the type of tumor on the measured parameter. For the pairwise comparisons, Tukey’s family-wise 95% confidence intervals and the corresponding adjusted P-values were calculated.
Results Compared to conventional MRI, much more inhomogeneous signal alterations could be detected for MTR and each individual qMT map for all tumor types as verified by 2 neuroradiologists in consensus (Figs 1 and 2). The pathologic-appearing tumor ROIs showed lower MTR, kf, and F and higher relaxation times than the reference ROI (P < .01). The effect that some
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Table 1. Mean and Standard Errors of the Mean for the Different MT Parameters of GBMs, Meningiomas, and Metastases
T1 (ms) GBMs (n = 9) Meningiomas (n = 4) Metastases (n = 6) T2 [ms] GBMs Meningiomas Metastases MTR [%] GBMs Meningiomas Metastases kf [s−1 ] GBMs Meningiomas Metastases F [%] GBMs Meningiomas Metastases
T1W-CE
T1W-non-CE
T2W-pSI
T2W-dSI
Ref
1,795 ± 38 1,274 ± 63 1,554 ± 52
1,327 ± 30 1,388 ± 32 1,249 ± 33
1,821 ± 54 1,478 ± 54 1,561 ± 52
1,260 ± 38 1,187 ± 29 1,233 ± 64
806 ± 36 873 ± 44 839 ± 21
168 ± 14 100 ± 14 121 ± 12
90 ± 4 104 ± 5 86 ± 3
192 ± 11 147 ± 19 163 ± 10
101 ± 5 102 ± 4 106 ± 10
64 ± 23 64 ± 4 66 ± 1
25.2 ± 0.6 30.5 ± 1.2 27.4 ± 1.0
33.8 ± 1.2 28.9 ± 1.6 35.1 ± 0.5
29.0 ± 0.9 33.5 ± 1.7 33.4 ± 1.4
35.2 ± 0.8 36.2 ± 0.3 36.1 ± 0.8
41.8 ± 0.7 41.5 ± 0.7 41.2 ± 0.6
0.6 ± 0.0 1.1 ± 0.1 0.8 ± 0.1
1.5 ± 0.1 1.1 ± 0.1 1.6 ± 0.1
0.7 ± 0.0 1.2 ± 0.3 0.9 ± 0.1
1.5 ± 0.1 1.7 ± 0.0 1.6 ± 0.1
3.3 ± 0.2 3.1 ± 0.2 3.1 ± 0.1
2.1 ± 0.2 5.4 ± 0.9 3.4 ± 0.2
5.6 ± 0.2 3.6 ± 0.4 7.2 ± 0.7
3.3 ± 0.2 5.8 ± 1.6 4.8 ± 0.3
7.1 ± 0.5 6.3 ± 0.9 6.7 ± 0.4
13.3 ± 0.6 12.2 ± 1.1 13.4 ± 1.3
regions showed signal alterations in MT parameter maps (MTR and qMT) appearing unaffected in conventional MRI was observed in 7 of 9 GBMs and in 4 of 6 intermediate-grade glial tumors (Fig 2), but not in any meningioma (Fig 1) or metastasis.
T2W-pSI ROI
GBMs, Meningiomas, and Metastases
T1W-non-CE ROI
GBMs showed the lowest F, kf, and MTR and highest T1 and T2 values in the T1W-CE and T2W-pSI regions, while showing intermediate values in the T1W-non-CE regions. In contrast, meningiomas showed the highest F, kf, and MTR and lowest T1 and T2 values in the T1W-CE and T2W-pSI ROIs, whereas the opposite applied to the T1W-non-CE ROIs. Metastases showed the lowest values for T1 and T2 and highest values for MTR, F, and kf in the T1W-non-CE regions, whereas all parameters showed intermediate values in the T1W-CE and T2W-pSI regions (Table 1). Significant differences (P < .05) between the T2W-pSI and the T2W-dSI ROIs were obtained for MTR and all qMT parameters in GBMs and for qMT parameters in metastases. For the ref ROI, no significant differences for any of the parameters (MTR or qMT) between the 3 lesions were observed. The MTR and qMT values by opposing the 3 different types of tumors against each other are shown in Figure 3.
Significant differences for the T1W-non-CE tumor areas were observed between metastases and meningiomas for all qMT estimates: T1 (P = .029), T2 (P = .041), F (P = < .001), kf (P = .014), and MTR (P = .01). A significant difference was observed for F between GBMs and metastases (P = .032) and meningiomas (P = .003), respectively.
T1W-CE ROI
From the limited number of intermediate glial tumors showing a T1W-CE ROI (2 glial tumors with anaplastic features and 1 diffuse astrocytoma without definite signs of anaplasia) qMT data approximated the respective values found in GBMs or metastases.
Significant differences for the T1W-CE regions between the 3 pairs of tumors (metastases vs. meningioma, metastases vs. GBMs, meningioma vs. GBMs) were seen for T1 (P = .007, P = .003, P < .001) and kf (P = .033, P = .028, P = < .001). For F, differences were observed between GBMs and metastases (P = .001) and meningiomas (P = .006), respectively. For T2, values reached a significant difference between GBMs and meningiomas (P = .01) and metastases (P = .036), respectively. MTR was only significant between GBMs and meningiomas (P = .004). Thus, significant differences in qMT estimates were observed between metastases and GBMs for all quantitative parameters (F, kf, T1, and T2), and between metastases and meningiomas for kf and T1, despite similar MTR. 1010
Significant differences were observed between metastases and GBMs for F (P = .002), T1 (P = .005), and MTR (P = .025).
T2W-dSI and Ref ROIs No significant differences for any parameter (MTR and qMT) between any opposed tumor pairs were found.
Intermediate-Grade Glial Tumors The resulting MTR and qMT values of the 6 intermediate-grade glial tumors not included in the statistical analysis are shown in Table 2.
T1W-CE ROI
T2W-pSI ROI For the oligodendroglioma, all values for MTR and qMT approximated those found in GBMs. For the 2 anaplastic astrocytomas, 4 of the 5 investigated MT parameters (T1, MTR, kf, and F) were closest to those observed in GBMs. For the 2 glial tumors with signs of anaplasia T1 and T2 approximated the respective values found in GBMs, while MTR and kf values were closest to those found in metastases.
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Fig 3. P-values of pairwise comparisons (metastases vs. meningioma, metastases vs. GBM, and meningioma vs. GBM) using Tukey’s honest significant difference. The vertical blue lines represent the .05% significance border. The red circles lying to the left of the blue vertical lines represent significant values. T1 and T2 are given in ms, MTR and F in%, and kf in s−1 . Table 2. Mean and Standard Errors of the Mean for the Different MT Parameters of the Intermediate Tumors
T1 [ms] O (n = 1) AA (n = 2) Glial tumor with anaplasia (n = 2) Diffuse A without anaplasia (n = 1) T2 [ms] O AA Glial tumor with anaplasia Diffuse A without anaplasia MTR [%] O AA Glial tumor with anaplasia Diffuse A without anaplasia kf [s−1 ] O AA Glial tumor with anaplasia Diffuse A without anaplasia F [%] O AA Glial tumor with anaplasia Diffuse A without anaplasia
T1W-CE
T1W-non-CE
n/a n/a 1,792 ± 45 1,557 ± 37
n/a 1,241 ± 56 1,338 ± 26 n/a
T2W-pSI
T2W-dSI
Ref
1,957 1,760 1,700 1,400
± ± ± ±
75 98 97 87
1,268 1,252 1,215 1,337
± ± ± ±
5 81 41 57
845 792 752 808
± ± ± ±
104 56 40 129
60 64 61 65
± ± ± ±
6 6 4 18
n/a n/a 121 ± 10 160 ± 2
n/a 69 ± 5 92 ± 3 n/a
218 158 192 123
± ± ± ±
33 11 19 16
104 91 113 101
± ± ± ±
7 8 5 4
n/a n/a 30.6 ± 1.8 25.3 ± 0.3
n/a 34.5 ± 1.7 37.0 ± 0.4 n/a
28.2 26.4 31.9 35.6
± ± ± ±
1.6 1.4 1.5 1.5
35.9 35.7 34.9 35.6
± ± ± ±
1.0 2.0 1.2 1.0
41.7 40.8 42.0 41.2
± ± ± ±
2.9 2.2 1.1 4.3
n/a n/a 0.9 ± 0.1 0.6 ± 0
n/a 2 ± 0.3 1.6 ± 0.1 n/a
0.6 0.7 0.9 1.4
± ± ± ±
0.1 0.1 0.1 0.3
1.5 1.6 1.6 1.7
± ± ± ±
0.2 0.2 0.1 0.1
3.2 3.2 3.7 3.2
± ± ± ±
0.7 0.4 0.5 0.6
n/a n/a 2.8 ± 0.6 2.2 ± 0.2
n/a 5.2 ± 0.6 6.5 ± 0.2 n/a
2.4 2.0 5.4 5.6
± ± ± ±
0.6 0.4 1.1 0.7
6.2 6.8 6.2 3.9
± ± ± ±
0.8 1.5 0.2 0.8
13.5 13.1 13.7 15.3
± ± ± ±
3.3 3.0 2.6 5.9
A = astrocytoma; AA = anaplastic astrocytoma; O = oligodendroglioma.
For the diffuse astrocytoma without definite signs of anaplasia, however, all MT parameters (MTR and qMT) showed values closest to those obtained from meningiomas.
2 anaplastic astrocytomas), MTR and qMT parameters were closer to the respective values found in metastases and GBMs than to those found in meningiomas.
T1W-non-CE ROI For the intermediate glial tumors in which a T1W-non-CE ROI could be identified (2 glial tumors with anaplastic features, and
Discussion Tumor evaluation with MRI is challenged by the frequently encountered similar appearance of neoplasms on conventional
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sequences. For example, the hyperintensity in T2w may be related to vasogenic edema, tumor invasion, or post-therapeutical changes.32 Advanced MRI methods such as DWI, PWI, MRS, and fMRI have increased the diagnostic tumor imaging potential.32–36 Little is known about MT imaging (MTR and qMT) in brain tumors, limited to MTR assessment22 with lower spatial resolution and inconsistent results.6,10,11,13,14 In this study, in addition to MTR, qMT parameters were assessed with fast high-resolution 3-dimensional bSSFP. Although 9 minutes may still be considered a long scanning time, this is by far shorter than conventional MT methods.3,4,24,37 In general, a stronger inhomogeneity of tumor regions was observed on qMT and MTR maps compared to conventional imaging. This could be an indicator for the high sensitivity of qMT parameters on tissue integrity. However, it could be argued that unwanted effects such as intrascanner variability, noise, or unstable signal modeling lead to heterogeneity in qMT maps. Intrascanner variations for qMT parameters obtained with bSSFP have been shown to be very low,20 and the good reproducibility of MTR using bSSFP has been discussed in Ref 21. BSSFP sequences have an exceptionally high signal-tonoise ratio and therefore qMT and MTR maps are not expected to be prone to noise problems. Stability of qMT signal modeling was controlled by several single-voxel parameter estimations per patient as described in Ref 20. Thereby, pixel estimates were found to be reliable, and corresponding fitting residuals were mostly within a 95% confidence interval of the predicted data. The homogeneous MT values (MTR and qMT) obtained with the bSSFP method25,26 in the ref ROIs corresponded to those known from the literature arguing for the reproducibility of the data. In general, MTR values within the lesions showed the same tendencies as F and kf with opposite tendencies for T1 and T2 (Tables 1 and 2), according to findings from qMT analysis in patients with MS7–9 and ischemia.5 The similar MTR values between metastases and GBMs or meningiomas in the T1W-CE, and between GBMs and meningiomas or metastases in the T1W-non-CE tissue, which significantly differed in 1 or more of the 4 qMT estimates, suggest that qMT enables a more subtle differentiation between tumors. GBMs showed the most abnormal and meningiomas the least abnormal MT values (MTR and qMT) in the T1W-CE and T2W-pSI ROIs, probably reflecting a decomposition of WM integrity, as to nuclear cell turnover and free water content.6,11,13 A differentiation between meningiomas from other glial tumors or metastases is possible in the majority of cases by conventional T1w and T2w imaging alone. However, a differentiation of higher-graded glial tumors, such as a GBM, from a single metastasis can be challenging in conventional sequences. In general, for the T1W-CE and T1W-non-CE ROIs the significant differences were less pronounced between GBMs and metastases than between GBMs and meningiomas, which might be attributed to the grade of malignancy, as meningiomas were the least aggressive lesions investigated. However, the significant differences in the quantitative parameters between GBMs and metastases in the T1W-CE ROI, despite similar MTR, indicate the additive information that can be obtained from particularly quantitative parameter assessment for the differentiation of aggressive lesions in comparison to conventional T1w or T2w imaging. This observation is strengthened by the significantly different values for F, T1, and MTR in the T2W-pSI between these 1012
2 lesions. Less pronounced significant differences, however, were also observed between metastases and meningiomas for kf in the T1W-CE, so that the true cause of the different extent in significant difference is still unknown. Furthermore, in general, more significant differences were found for kf and F (n = 10) than for T1 and T2 (n = 8) or MTR (n = 3) indicating that the most useful parameters for tumor assessment and differentiation are kf and F (Fig 3). When including the borderline significant differences (circles touching the P = .05 line from the right) the number increases to n = 13 for kf and F altogether, whereby the borderline data only apply to kf. Two of the borderline significant differences for kf (metastases vs. GBM, and meningioma vs. GBM) go along with significant differences for F for the respective pair of lesion oppositions (Fig 3). This underlines the same similar directions and potency of these 2 quantitative parameters. For MTR, 2 borderline significant differences could be observed (Fig 3), whereas no borderline significant differences were observed for T1 and T2 (Fig 3). To summarize, the numbers of significant differences argue for a high potential of F and kf for lesion characterization. In the T1W-non-CE regions, however, MTR and qMT parameters were “farthest from the reference” in meningiomas. This was surprising as meningiomas were the most confined and benign tumors investigated. However, all assessed T1W-non-CE areas were either intermingled within the main T1W-CE tumor mass or located between the T1W-CE areas and the T2W-pSI ROI, but not beyond the T2W-pSI area. Even if the significance of this hypointense tissue in meningiomas remains unclear, the adjacent MT values (MTR and qMT) in the T1W-CE and T2W-pSI ROIs, which were most proximate to the ref values, argue against an invasive component within this hypointense tissue. Most likely, the latter can be attributed to mass effect and edema in WM tracts. Nevertheless, due to the restricted knowledge of the pathophysiologic MT processes in tumors, further studies are required to specify the observed MT changes in brain tumors more closely. The significantly different MT values (MTR and qMT) between the T2W-pSI and T2W-dSI ROIs in GBMs and metastases imply that areas looking similar on T2w can be distinguished by MT imaging (MTR and qMT). This indicates that MT imaging (MTR and qMT) may differentiate between different types of hyperintense tissue on T2w, suggesting that for GBMs and metastases the hyperintensity remote from the tumor core might reflect edema while the proximal hyperintensity may rather not. This observation might be helpful for tumor characterization and risk assessment of tumor invasion adjunctive to the traditional concept that relies on T1w contrast-enhancing tissue. GBMs are the most likely tumors to recur and invade adjacent tissue, and for metastases adjacent tissue infiltration and invasion has also been described.38–40 For meningiomas, tissue invasion is much less likely, except for anaplastic ones41 which were not included in this study. For the meningiomas, there was no significant difference between the 2 T2w hyperintense ROIs (respecting the limited number of cases as a hyperintense ROI was not always present), and possibly MT variations (MTR and qMT) in the T2W-pSI ROIs may reflect mass effect and WM tract affection through the meningiomas themselves. Less congruent MT information was obtained from the single intermediate-grade glial tumors. For the T1W-CE and
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T1W-non-CE areas, MT values (MTR and qMT) were in general closer to those observed in GBMs and metastases (Table 2). However, a respective ROI in these areas was not available for all intermediate-grade glial tumors, so that no sufficient conclusion can be drawn from these results. However, a T2W-pSI ROI was available for all 6 intermediate-grade glial tumors. Here, most of the MT values (MTR and/or qMT estimates) of the higher-graded intermediate-grade glial tumors showing anaplastic features were closest to the respective values found in GBMs, whereas MTR and qMT values of the diffuse astrocytoma without anaplastic features were closest to those found in meningiomas. This observation corroborates that the T2W-pSI region may possibly reflect some degree of malignancy. Similar to GBMs, meningiomas and metastases, also for the intermediate-grade glial tumors no significant differences in MT (MTR and qMT) from the reference could be found for the T2W-dSI ROI indicating that the remote hyperintense tissue cannot sufficiently differentiate between different kind of brain tumors and metastases and might probably reflect edema. Certainly, this assumption cannot be generalized due to the limited number of intermediate glial tumors included. The abnormal MT values (MTR and qMT) in tissues beyond areas appearing pathological on conventional MRI, only observed in higher-graded glial tumors, may reflect the aggressive nature of these lesions, indicating that in conventional MRI the “true” extension of the lesion might be underestimated in higher-graded lesions. These first data of fast bSSFP MT imaging (MTR and qMT) in brain tumors show that this technique can be implemented in the clinical routine due to its shorter acquisition times and indicate that in particular assessment of qMT provides information from brain tumors and metastases that cannot be derived by simple MTR or conventional MRI. Differences in MTR and qMT in areas appearing similar on conventional MRI may account for a more subtle differentiation between brain tumors. The abnormal signal in the T2W-pSI areas of GBMs and metastases argues for an infiltrative nature of the tissue surrounding the tumor core, which with qMT could be differentiated from the remote signal hyperintensity. Even if these initial MT data (MTR and qMT) seem promising, the results need further validation in larger patient cohorts together with a proof of the diagnostic value of MT imaging (MTR and qMT) in brain tumors. Future studies correlating MT imaging (MTR and qMT) with histopathology and other advanced imaging techniques, such as DWI or PWI are necessary to more specifically characterize the benefit of the assessment of MTR and qMT imaging.
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27. Gloor M, Scheffler K, Bieri O. Accelerated quantitative magnetization transfer imaging using balanced SSFP. Proc 25th Meeting ESMRM 2008:254. 28. Homer J, Roberts JK. Conditions for the driven equilibrium single pulse observation of spin-lattice relaxation times. J Magn Reson 1987;74:424-32. 29. Deoni SC, Peters TM, Rutt BK. High resolution T1 and T2 mapping of the brain in a clinically acceptable time with DESPOT1 and DESPOT2. Magn Reson Med 2005;53:237-41. 30. Smith SM, Jenkinson M, Woolrich MW, et al. Advances in functional and structural MR image analysis and implementation as FSL. Neuroimage 2004;23(S1):208-19. 31. Cox RW. AFNI: software for analysis and visualization of functional magnetic resonance neuroimages. Comput Biomed Res 1996;29:162-73. 32. Arvinda HR, Kesavadas C, Sama PS, et al. Glioma grading: sensitivity, specificity, positive and negative predictive values of diffusion and perfusion imaging. J Neurooncol 2009;94:89-96. 33. Zonari P, Baraldi P, Crisi G. Multimodal MRI in the characterization of glial neoplasms: the combined role of single-voxel MR spectroscopy, diffusion imaging and echo-planar perfusion imaging. Neuroradiology 2007;49:795-803.
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Journal of Neuroimaging Vol 25 No 6 November/December 2015
ABSTRACT BACKGROUND AND PURPOSE: This study assesses whether magnetization transfer (MT) imaging provides additive information to conventional MRI in brain tumors. METHODS: MT data of 26 patients with neoplastic and metastatic brain tumors were analyzed at 1.5 T. For the 3 largest tumor groups investigated in this study—glioblastoma multiforme (GBM), meningiomas, and metastases—statistical comparisons were performed. Analyzed MT parameters included the magnetization transfer ratio (MTR) and 4 quantitative MT parameters (qMT): Relaxation times (T1, T2), exchange rate (kf), and macromolecular content (F). Total imaging time of high-resolution whole brain MTR and qMT imaging with balanced steady-state free precession required 9 minutes. Five ROIs were chosen: Contrastenhancing (T1W-CE), noncontrast-enhancing (T1W-non-CE), proximal hyperintensity (T2W-pSI), distal hyperintensity (T2W-dSI), and a reference (ref). RESULTS: Pathologies showed significant (P < .05) MT changes (MTR and qMT) compared to the reference. The T1W-CE, T1W-non-CE, and T2W-pSI ROIs of GBMs, meningiomas, and metastases showed significant differences in MTR and qMT estimates. Similar MTR with significant different qMT values were observed in several ROIs among different lesions. MT maps (MTR and qMT) indicated changes in tissue appearing unaffected on MRI in most glial tumors. CONCLUSIONS: MTR and qMT imaging enables a better differentiation between brain tumors and provides additive information to MRI. Keywords: Magnetic resonance imaging, magnetization transfer contrast imaging, neuroimaging, primary brain neoplasms, metastases. Acceptance: Received July 3, 2014, and in revised form December 4, 2014. Accepted for publication December 10, 2014. Correspondence: Address correspondence to Meritxell Garcia, University of Basel Hospital, Division of Diagnostic & Interventional Neuroradiology, Petersgraben 4, Basel, Switzerland, 4031. E-mail: [email protected]. ∗
Contributed equally to this article.
J Neuroimaging 2015;25:1007-1014. DOI: 10.1111/jon.12222
T2w imaging, qMT imaging provides absolute T1 and T2 values, hereby providing different information from conventional sequences. Recently, it has been shown that 2 tissues may generate a similar MTR though having a different amount of fractional macromolecular protons.17 Thus, simple MTR analysis might overlook potentially essential information for pathophysiological processes. The disadvantage of qMT imaging over MTR, however, is the need of the acquisition of extensive data and a much longer acquisition time (TA), as well as a sophisticated model analysis. The drawback of low resolution has been addressed by a novel MT-sensitized method using balanced steady-state free precession (bSSFP),18–21 providing whole brain isotropic MTR and qMT parameter maps, which, however, until recently still required TAs of about 30 minutes. The advantages of MT imaging (MTR and qMT) with bSSFP over common spoiled gradient echo (SPGR) sequences,4,8,22–24 has previously been analyzed in normal brain structures.17,25,26 In general, qMT parameters obtained with bSSFP were in good accordance with prior studies and, in contrast to studies using SPGR sequences for MT assessment, the bSSFP method allowed the analysis
Background and Purpose Magnetization transfer (MT) analyses tissue beyond conventional T1 and T2 weighting,1 and has been shown to be beneficial for the characterization of both normal2–4 and pathologic brain tissue, such as infarction,5,6 and white matter (WM) lesions.7–9 For brain tumors, the MT literature is limited to a few studies only,6,10,11 based on the simple assessment of the magnetization transfer ratio (MTR)6,7,11–14 or of quantitative MT (qMT) analysis in animals,15 principally because of the required extensive scanning times and the limited resolution of MT imaging (MTR and qMT) with conventional MT sequences. MT refers to the exchange of magnetization between “mobile” protons within free water (“free” proton pool) and protons bound to macromolecules (“bound” proton pool).16 The easiest method to get information from the bound protons is by performing 2 measurements: 1 with and 1 without presaturation of the macromolecular protons, so that an MTR image is obtained.16 This method is quite fast, however, only qualitative as MTR is composed of various sequence parameters and tissue-related qMT parameters, such as the macromolecular content (F), exchange rate (kf), and relaxation properties (T1, T2).16 Thus, contrary to conventional T1w and Copyright
◦ 2015 by the American Society of Neuroimaging C
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of even small brain structures due to its high resolution and provided a higher signal-to-noise ratio. Thanks to technical improvement and persevering sequence optimization, the TA for the assessment of MTR and qMT estimates altogether with bSSFP could be reduced to below 10 minutes by now.27 As conventional MRI has its limitations for tumor characterization, the aim of this study was to analyze the feasibility of fast whole brain MT-bSSFP imaging (MTR and qMT) for the characterization of brain tumors and metastases, and to assess whether additional information to conventional T1w and T2w imaging can be obtained with this advanced imaging technique.
alone, and 1 patient was not followed in our hospital after biopsy. MT imaging included the following: For relaxometry, 2 SPGR sequences with variable flip angles (FA; 3° and 17°; TR = 9.8 ms/TE 4.77 ms) were used for T1 mapping,28,29 and 2 bSSFP sequences with variable FA (15° and 35°) for T2 mapping. Quantitative MT parameters were based on 8 bSSFP sequences with different radiofrequency (RF) pulse durations (TRF = 230-2,100 μs; TR 2.68-4.55 ms) for estimation of F, kf, and MTR. A B1 map with 16 slices of 5 mm thickness was used for FA correction. Overall, relaxometry, qMT, and MTR imaging was completed in 9 minutes with an isotropic resolution of 1.3 mm.20,27 The study protocol was reviewed and approved by the Institutional Review Board.
Methods Subjects and Image Acquisition
Image Postprocessing
MR data of 26 patients (mean age 57 years, age range 32-81 years; 14 males, 12 females) receiving a standard tumor imaging protocol plus MT-bSSFP (MTR and qMT) at 1.5T (Avanto, Siemens) were retrospectively analyzed. Pathologies included 9 glioblastoma multiforme (GBMs; WHO IV), 4 meningiomas without anaplastic features, 7 metastases, and 6 glial tumors of intermediate malignancy (WHO II or III; 1 oligodendroglioma, 2 glial tumors with anaplastic features, 1 diffuse astrocytoma without definite signs of anaplasia, 2 anaplastic astrocytomas). Final diagnosis was based on histopathology of the cerebral lesions except for 4 lesions: For 1 small homogeneous dura-based mass, which remained unchanged on follow-up MRIs and was most suggestive for a meningioma, and in 3 patients with multiple lesions suggestive for metastases, whereby in 2 cases the primary tumor was confirmed by histology. The other patient in whom a gastric tumor was suspected and who showed multiple (>40) round lesions compatible with metastases was no longer followed as he was flown to his home country for palliative therapy. The time interval between initial diagnosis and the time point of the study was below 2.5 months, except for 2 meningiomas, whose time point of initial diagnosis could not be confidently assured. None of the patients had been operated or had received radiation or chemotherapy before the time point of the study. As far as followed in our hospital, the treatments after the study were the following for the respective patients: (A) For the GBMs: 3 x radiation and chemotherapy, 3 x aimed complete resection with following radiation and chemotherapy, 1 x radiation alone, 1 x partial resection followed by radiation, and 1 patient who was considered not operable and for whom a combined treatment with radiation and chemotherapy was suggested was not further followed in our hospital. (B) For the meningiomas: 3 x total resection with no definite signs of residual in follow-up MRIs, and 1 patient was not treated and showed a stable lesion on follow-up MRIs. (C) For the metastases: 1 x resection with suggested further oncologic therapy in another hospital (patient no longer followed), 3 x resection with following radiation therapy in 2 patients and combined radiation and chemotherapy in 1 patient, 2 patients with palliative radiation therapy, and 1 patient with palliative radiation and chemotherapy. (D) For the mixed glial tumors: 3 x resection with following radiation and chemotherapy in 2 patients (1 patient was no longer followed), 1 x radiation and chemotherapy, 1 patient radiation 1008
Image registration and brain segmentation were performed with the software FSL30 and AFNI.31 The MATLAB-based custom software was applied for FA correction and T1 and T2 determination.28,29 The “free” proton pool relaxation times are assumed to be T1,f = T1 and T2,f = T220 and are used for a pixel-by-pixel nonlinear least-squares fitting of F and kf.20,27 Five different regions of interest (ROIs) were manually drawn by an experienced neuroradiologist: (1) Contrastenhancing region (T1W-CE) (Fig 1); (2) Noncontrast-enhancing area (T1W-non-CE): Hypointense on T1w, isointense on T2w, and located next to the contrast-enhancing ROI (i.e. within or adjacent to the tumor core); (3) Proximate hyperintensity on T2w (T2W-pSI): Next to the contrast-enhancing tissue and thus within or as close to the tumor core as possible; (4) Distal hyperintensity on T2w (T2W-dSI): Most distant from the contrast-enhancing tissue as possible, and hence close to the normal appearing tissue; and (5) A reference ROI (ref): In the nonaffected WM, and drawn in the contralateral hemisphere except in some bilateral lesions where it was located in the less affected hemisphere farthest from the pathology. Due to the inhomogeneous appearance and different extent of the lesions to select an identical ROI for the respective regions of each lesion was not possible. Therefore, the ROIs had to be applied accordingly to the individual case, whereby they were defined as similar as possible. Hereby, the proximal 2 mm of the selected intensity area abutting the adjacent intensity areas were not included in the ROI in order to avoid partial volume effects. The set of ROIs was overlaid onto MTR and each individual quantitative parameter map to obtain mean values and standard deviations of MTR, T1, T2, F, and kf, according to Gloor et al.13
Statistical Analyses The Wilcoxon Mann-Whitney Test was applied for the evaluation of statistical significance (P < .05) between the different ROIs using MATLAB. GBMs, meningiomas, and metastases were included in the intertumoral statistical analysis (R Development Core Team, 2011). Hereby, a linear model was fitted for each combination of parameter and ROI. The response variable was the parameter (T1, T2, kf, F, MTR), the only explanatory variable consisting in the categorical variable indicating the tumor type. In tumors with repeated measurements, generalized estimating equations were used to obtain more reliable standard errors for the model coefficients.
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Fig 1. Representative region of interest (ROI) placed in the contrast-enhancing region on a T1w sequence with contrast (T1wCE) of a patient with a meningioma. The T1W-CE ROI is superimposed on the individual qMT maps for calculation of MTR (28.4% ± 1.2), T1 (1,101 ms ± 41), T2 (107 ms ± 13), kf (1.1 s−1 ± 0.1), and F (3.3% ± 0.5). Compared to the T1wCE image, more inhomogeneous signal alteration within and around the tumor core can be observed in the individual MT maps.
Fig 2. Conventional images (T1wCE and T2w-FLAIR) and MT maps (MTR, F, kf) of a patient with a malignant pleomorphic glial tumor in the left temporal and occipital lobes showing contralateral tumor extension via the splenium of the corpus callosum. Abnormal MT values can be discerned ventrally and laterally to the altered looking tissue on conventional MRI (black arrows).
An ANOVA (or rather an “Analysis of ‘Wald statistic”’) table was compiled for the fitted model and a χ 2 statistic was calculated in order to test for an overall effect of the type of tumor on the measured parameter. For the pairwise comparisons, Tukey’s family-wise 95% confidence intervals and the corresponding adjusted P-values were calculated.
Results Compared to conventional MRI, much more inhomogeneous signal alterations could be detected for MTR and each individual qMT map for all tumor types as verified by 2 neuroradiologists in consensus (Figs 1 and 2). The pathologic-appearing tumor ROIs showed lower MTR, kf, and F and higher relaxation times than the reference ROI (P < .01). The effect that some
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Table 1. Mean and Standard Errors of the Mean for the Different MT Parameters of GBMs, Meningiomas, and Metastases
T1 (ms) GBMs (n = 9) Meningiomas (n = 4) Metastases (n = 6) T2 [ms] GBMs Meningiomas Metastases MTR [%] GBMs Meningiomas Metastases kf [s−1 ] GBMs Meningiomas Metastases F [%] GBMs Meningiomas Metastases
T1W-CE
T1W-non-CE
T2W-pSI
T2W-dSI
Ref
1,795 ± 38 1,274 ± 63 1,554 ± 52
1,327 ± 30 1,388 ± 32 1,249 ± 33
1,821 ± 54 1,478 ± 54 1,561 ± 52
1,260 ± 38 1,187 ± 29 1,233 ± 64
806 ± 36 873 ± 44 839 ± 21
168 ± 14 100 ± 14 121 ± 12
90 ± 4 104 ± 5 86 ± 3
192 ± 11 147 ± 19 163 ± 10
101 ± 5 102 ± 4 106 ± 10
64 ± 23 64 ± 4 66 ± 1
25.2 ± 0.6 30.5 ± 1.2 27.4 ± 1.0
33.8 ± 1.2 28.9 ± 1.6 35.1 ± 0.5
29.0 ± 0.9 33.5 ± 1.7 33.4 ± 1.4
35.2 ± 0.8 36.2 ± 0.3 36.1 ± 0.8
41.8 ± 0.7 41.5 ± 0.7 41.2 ± 0.6
0.6 ± 0.0 1.1 ± 0.1 0.8 ± 0.1
1.5 ± 0.1 1.1 ± 0.1 1.6 ± 0.1
0.7 ± 0.0 1.2 ± 0.3 0.9 ± 0.1
1.5 ± 0.1 1.7 ± 0.0 1.6 ± 0.1
3.3 ± 0.2 3.1 ± 0.2 3.1 ± 0.1
2.1 ± 0.2 5.4 ± 0.9 3.4 ± 0.2
5.6 ± 0.2 3.6 ± 0.4 7.2 ± 0.7
3.3 ± 0.2 5.8 ± 1.6 4.8 ± 0.3
7.1 ± 0.5 6.3 ± 0.9 6.7 ± 0.4
13.3 ± 0.6 12.2 ± 1.1 13.4 ± 1.3
regions showed signal alterations in MT parameter maps (MTR and qMT) appearing unaffected in conventional MRI was observed in 7 of 9 GBMs and in 4 of 6 intermediate-grade glial tumors (Fig 2), but not in any meningioma (Fig 1) or metastasis.
T2W-pSI ROI
GBMs, Meningiomas, and Metastases
T1W-non-CE ROI
GBMs showed the lowest F, kf, and MTR and highest T1 and T2 values in the T1W-CE and T2W-pSI regions, while showing intermediate values in the T1W-non-CE regions. In contrast, meningiomas showed the highest F, kf, and MTR and lowest T1 and T2 values in the T1W-CE and T2W-pSI ROIs, whereas the opposite applied to the T1W-non-CE ROIs. Metastases showed the lowest values for T1 and T2 and highest values for MTR, F, and kf in the T1W-non-CE regions, whereas all parameters showed intermediate values in the T1W-CE and T2W-pSI regions (Table 1). Significant differences (P < .05) between the T2W-pSI and the T2W-dSI ROIs were obtained for MTR and all qMT parameters in GBMs and for qMT parameters in metastases. For the ref ROI, no significant differences for any of the parameters (MTR or qMT) between the 3 lesions were observed. The MTR and qMT values by opposing the 3 different types of tumors against each other are shown in Figure 3.
Significant differences for the T1W-non-CE tumor areas were observed between metastases and meningiomas for all qMT estimates: T1 (P = .029), T2 (P = .041), F (P = < .001), kf (P = .014), and MTR (P = .01). A significant difference was observed for F between GBMs and metastases (P = .032) and meningiomas (P = .003), respectively.
T1W-CE ROI
From the limited number of intermediate glial tumors showing a T1W-CE ROI (2 glial tumors with anaplastic features and 1 diffuse astrocytoma without definite signs of anaplasia) qMT data approximated the respective values found in GBMs or metastases.
Significant differences for the T1W-CE regions between the 3 pairs of tumors (metastases vs. meningioma, metastases vs. GBMs, meningioma vs. GBMs) were seen for T1 (P = .007, P = .003, P < .001) and kf (P = .033, P = .028, P = < .001). For F, differences were observed between GBMs and metastases (P = .001) and meningiomas (P = .006), respectively. For T2, values reached a significant difference between GBMs and meningiomas (P = .01) and metastases (P = .036), respectively. MTR was only significant between GBMs and meningiomas (P = .004). Thus, significant differences in qMT estimates were observed between metastases and GBMs for all quantitative parameters (F, kf, T1, and T2), and between metastases and meningiomas for kf and T1, despite similar MTR. 1010
Significant differences were observed between metastases and GBMs for F (P = .002), T1 (P = .005), and MTR (P = .025).
T2W-dSI and Ref ROIs No significant differences for any parameter (MTR and qMT) between any opposed tumor pairs were found.
Intermediate-Grade Glial Tumors The resulting MTR and qMT values of the 6 intermediate-grade glial tumors not included in the statistical analysis are shown in Table 2.
T1W-CE ROI
T2W-pSI ROI For the oligodendroglioma, all values for MTR and qMT approximated those found in GBMs. For the 2 anaplastic astrocytomas, 4 of the 5 investigated MT parameters (T1, MTR, kf, and F) were closest to those observed in GBMs. For the 2 glial tumors with signs of anaplasia T1 and T2 approximated the respective values found in GBMs, while MTR and kf values were closest to those found in metastases.
Journal of Neuroimaging Vol 25 No 6 November/December 2015
Fig 3. P-values of pairwise comparisons (metastases vs. meningioma, metastases vs. GBM, and meningioma vs. GBM) using Tukey’s honest significant difference. The vertical blue lines represent the .05% significance border. The red circles lying to the left of the blue vertical lines represent significant values. T1 and T2 are given in ms, MTR and F in%, and kf in s−1 . Table 2. Mean and Standard Errors of the Mean for the Different MT Parameters of the Intermediate Tumors
T1 [ms] O (n = 1) AA (n = 2) Glial tumor with anaplasia (n = 2) Diffuse A without anaplasia (n = 1) T2 [ms] O AA Glial tumor with anaplasia Diffuse A without anaplasia MTR [%] O AA Glial tumor with anaplasia Diffuse A without anaplasia kf [s−1 ] O AA Glial tumor with anaplasia Diffuse A without anaplasia F [%] O AA Glial tumor with anaplasia Diffuse A without anaplasia
T1W-CE
T1W-non-CE
n/a n/a 1,792 ± 45 1,557 ± 37
n/a 1,241 ± 56 1,338 ± 26 n/a
T2W-pSI
T2W-dSI
Ref
1,957 1,760 1,700 1,400
± ± ± ±
75 98 97 87
1,268 1,252 1,215 1,337
± ± ± ±
5 81 41 57
845 792 752 808
± ± ± ±
104 56 40 129
60 64 61 65
± ± ± ±
6 6 4 18
n/a n/a 121 ± 10 160 ± 2
n/a 69 ± 5 92 ± 3 n/a
218 158 192 123
± ± ± ±
33 11 19 16
104 91 113 101
± ± ± ±
7 8 5 4
n/a n/a 30.6 ± 1.8 25.3 ± 0.3
n/a 34.5 ± 1.7 37.0 ± 0.4 n/a
28.2 26.4 31.9 35.6
± ± ± ±
1.6 1.4 1.5 1.5
35.9 35.7 34.9 35.6
± ± ± ±
1.0 2.0 1.2 1.0
41.7 40.8 42.0 41.2
± ± ± ±
2.9 2.2 1.1 4.3
n/a n/a 0.9 ± 0.1 0.6 ± 0
n/a 2 ± 0.3 1.6 ± 0.1 n/a
0.6 0.7 0.9 1.4
± ± ± ±
0.1 0.1 0.1 0.3
1.5 1.6 1.6 1.7
± ± ± ±
0.2 0.2 0.1 0.1
3.2 3.2 3.7 3.2
± ± ± ±
0.7 0.4 0.5 0.6
n/a n/a 2.8 ± 0.6 2.2 ± 0.2
n/a 5.2 ± 0.6 6.5 ± 0.2 n/a
2.4 2.0 5.4 5.6
± ± ± ±
0.6 0.4 1.1 0.7
6.2 6.8 6.2 3.9
± ± ± ±
0.8 1.5 0.2 0.8
13.5 13.1 13.7 15.3
± ± ± ±
3.3 3.0 2.6 5.9
A = astrocytoma; AA = anaplastic astrocytoma; O = oligodendroglioma.
For the diffuse astrocytoma without definite signs of anaplasia, however, all MT parameters (MTR and qMT) showed values closest to those obtained from meningiomas.
2 anaplastic astrocytomas), MTR and qMT parameters were closer to the respective values found in metastases and GBMs than to those found in meningiomas.
T1W-non-CE ROI For the intermediate glial tumors in which a T1W-non-CE ROI could be identified (2 glial tumors with anaplastic features, and
Discussion Tumor evaluation with MRI is challenged by the frequently encountered similar appearance of neoplasms on conventional
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sequences. For example, the hyperintensity in T2w may be related to vasogenic edema, tumor invasion, or post-therapeutical changes.32 Advanced MRI methods such as DWI, PWI, MRS, and fMRI have increased the diagnostic tumor imaging potential.32–36 Little is known about MT imaging (MTR and qMT) in brain tumors, limited to MTR assessment22 with lower spatial resolution and inconsistent results.6,10,11,13,14 In this study, in addition to MTR, qMT parameters were assessed with fast high-resolution 3-dimensional bSSFP. Although 9 minutes may still be considered a long scanning time, this is by far shorter than conventional MT methods.3,4,24,37 In general, a stronger inhomogeneity of tumor regions was observed on qMT and MTR maps compared to conventional imaging. This could be an indicator for the high sensitivity of qMT parameters on tissue integrity. However, it could be argued that unwanted effects such as intrascanner variability, noise, or unstable signal modeling lead to heterogeneity in qMT maps. Intrascanner variations for qMT parameters obtained with bSSFP have been shown to be very low,20 and the good reproducibility of MTR using bSSFP has been discussed in Ref 21. BSSFP sequences have an exceptionally high signal-tonoise ratio and therefore qMT and MTR maps are not expected to be prone to noise problems. Stability of qMT signal modeling was controlled by several single-voxel parameter estimations per patient as described in Ref 20. Thereby, pixel estimates were found to be reliable, and corresponding fitting residuals were mostly within a 95% confidence interval of the predicted data. The homogeneous MT values (MTR and qMT) obtained with the bSSFP method25,26 in the ref ROIs corresponded to those known from the literature arguing for the reproducibility of the data. In general, MTR values within the lesions showed the same tendencies as F and kf with opposite tendencies for T1 and T2 (Tables 1 and 2), according to findings from qMT analysis in patients with MS7–9 and ischemia.5 The similar MTR values between metastases and GBMs or meningiomas in the T1W-CE, and between GBMs and meningiomas or metastases in the T1W-non-CE tissue, which significantly differed in 1 or more of the 4 qMT estimates, suggest that qMT enables a more subtle differentiation between tumors. GBMs showed the most abnormal and meningiomas the least abnormal MT values (MTR and qMT) in the T1W-CE and T2W-pSI ROIs, probably reflecting a decomposition of WM integrity, as to nuclear cell turnover and free water content.6,11,13 A differentiation between meningiomas from other glial tumors or metastases is possible in the majority of cases by conventional T1w and T2w imaging alone. However, a differentiation of higher-graded glial tumors, such as a GBM, from a single metastasis can be challenging in conventional sequences. In general, for the T1W-CE and T1W-non-CE ROIs the significant differences were less pronounced between GBMs and metastases than between GBMs and meningiomas, which might be attributed to the grade of malignancy, as meningiomas were the least aggressive lesions investigated. However, the significant differences in the quantitative parameters between GBMs and metastases in the T1W-CE ROI, despite similar MTR, indicate the additive information that can be obtained from particularly quantitative parameter assessment for the differentiation of aggressive lesions in comparison to conventional T1w or T2w imaging. This observation is strengthened by the significantly different values for F, T1, and MTR in the T2W-pSI between these 1012
2 lesions. Less pronounced significant differences, however, were also observed between metastases and meningiomas for kf in the T1W-CE, so that the true cause of the different extent in significant difference is still unknown. Furthermore, in general, more significant differences were found for kf and F (n = 10) than for T1 and T2 (n = 8) or MTR (n = 3) indicating that the most useful parameters for tumor assessment and differentiation are kf and F (Fig 3). When including the borderline significant differences (circles touching the P = .05 line from the right) the number increases to n = 13 for kf and F altogether, whereby the borderline data only apply to kf. Two of the borderline significant differences for kf (metastases vs. GBM, and meningioma vs. GBM) go along with significant differences for F for the respective pair of lesion oppositions (Fig 3). This underlines the same similar directions and potency of these 2 quantitative parameters. For MTR, 2 borderline significant differences could be observed (Fig 3), whereas no borderline significant differences were observed for T1 and T2 (Fig 3). To summarize, the numbers of significant differences argue for a high potential of F and kf for lesion characterization. In the T1W-non-CE regions, however, MTR and qMT parameters were “farthest from the reference” in meningiomas. This was surprising as meningiomas were the most confined and benign tumors investigated. However, all assessed T1W-non-CE areas were either intermingled within the main T1W-CE tumor mass or located between the T1W-CE areas and the T2W-pSI ROI, but not beyond the T2W-pSI area. Even if the significance of this hypointense tissue in meningiomas remains unclear, the adjacent MT values (MTR and qMT) in the T1W-CE and T2W-pSI ROIs, which were most proximate to the ref values, argue against an invasive component within this hypointense tissue. Most likely, the latter can be attributed to mass effect and edema in WM tracts. Nevertheless, due to the restricted knowledge of the pathophysiologic MT processes in tumors, further studies are required to specify the observed MT changes in brain tumors more closely. The significantly different MT values (MTR and qMT) between the T2W-pSI and T2W-dSI ROIs in GBMs and metastases imply that areas looking similar on T2w can be distinguished by MT imaging (MTR and qMT). This indicates that MT imaging (MTR and qMT) may differentiate between different types of hyperintense tissue on T2w, suggesting that for GBMs and metastases the hyperintensity remote from the tumor core might reflect edema while the proximal hyperintensity may rather not. This observation might be helpful for tumor characterization and risk assessment of tumor invasion adjunctive to the traditional concept that relies on T1w contrast-enhancing tissue. GBMs are the most likely tumors to recur and invade adjacent tissue, and for metastases adjacent tissue infiltration and invasion has also been described.38–40 For meningiomas, tissue invasion is much less likely, except for anaplastic ones41 which were not included in this study. For the meningiomas, there was no significant difference between the 2 T2w hyperintense ROIs (respecting the limited number of cases as a hyperintense ROI was not always present), and possibly MT variations (MTR and qMT) in the T2W-pSI ROIs may reflect mass effect and WM tract affection through the meningiomas themselves. Less congruent MT information was obtained from the single intermediate-grade glial tumors. For the T1W-CE and
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T1W-non-CE areas, MT values (MTR and qMT) were in general closer to those observed in GBMs and metastases (Table 2). However, a respective ROI in these areas was not available for all intermediate-grade glial tumors, so that no sufficient conclusion can be drawn from these results. However, a T2W-pSI ROI was available for all 6 intermediate-grade glial tumors. Here, most of the MT values (MTR and/or qMT estimates) of the higher-graded intermediate-grade glial tumors showing anaplastic features were closest to the respective values found in GBMs, whereas MTR and qMT values of the diffuse astrocytoma without anaplastic features were closest to those found in meningiomas. This observation corroborates that the T2W-pSI region may possibly reflect some degree of malignancy. Similar to GBMs, meningiomas and metastases, also for the intermediate-grade glial tumors no significant differences in MT (MTR and qMT) from the reference could be found for the T2W-dSI ROI indicating that the remote hyperintense tissue cannot sufficiently differentiate between different kind of brain tumors and metastases and might probably reflect edema. Certainly, this assumption cannot be generalized due to the limited number of intermediate glial tumors included. The abnormal MT values (MTR and qMT) in tissues beyond areas appearing pathological on conventional MRI, only observed in higher-graded glial tumors, may reflect the aggressive nature of these lesions, indicating that in conventional MRI the “true” extension of the lesion might be underestimated in higher-graded lesions. These first data of fast bSSFP MT imaging (MTR and qMT) in brain tumors show that this technique can be implemented in the clinical routine due to its shorter acquisition times and indicate that in particular assessment of qMT provides information from brain tumors and metastases that cannot be derived by simple MTR or conventional MRI. Differences in MTR and qMT in areas appearing similar on conventional MRI may account for a more subtle differentiation between brain tumors. The abnormal signal in the T2W-pSI areas of GBMs and metastases argues for an infiltrative nature of the tissue surrounding the tumor core, which with qMT could be differentiated from the remote signal hyperintensity. Even if these initial MT data (MTR and qMT) seem promising, the results need further validation in larger patient cohorts together with a proof of the diagnostic value of MT imaging (MTR and qMT) in brain tumors. Future studies correlating MT imaging (MTR and qMT) with histopathology and other advanced imaging techniques, such as DWI or PWI are necessary to more specifically characterize the benefit of the assessment of MTR and qMT imaging.
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