Optimization of imaging parameter in contrast-enhanced ... - netkey.at

Optimization of imaging parameter in contrast-enhanced three-dimensional T1 weighted MRI with fat saturation for head disease Poster No.:

C-1450

Congress:

ECR 2015

Type:

Scientific Exhibit

Authors:

Y. Kanazawa , T. Miyati , H. Hayashi , A. Yagi , O. Sato ;

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Tokushima/JP, Kanazawa/JP, Kyoto/JP

Keywords:

MR physics, Head and neck, Contrast agents, MR, Contrast agentintravenous, Metastases

DOI:

10.1594/ecr2015/C-1450

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Aims and objectives Contrast-enhanced T1 weighted magnetic resonance (MR) images with fat-suppression is useful for detecting disease of skull and it's around, as brain tumor and metastasis of various malignancies, e.g. carcinoma of the lung, breast, and thyroid, renal cell carcinoma, and malignant melanoma, respectively. Fat-suppression technique is in general use to preparation pulse for chemical shift selective (CHESS) method on spinecho (SE), Fast SE (FSE), and gradient-echo sequence (GRE), respectively. The fat suppression method for the head and neck area (e.g., sinus, orbit, and internal auditory meatus) however have tended to be affected by the magnetic field inhomogeneity caused to variations in the shape of the structures [1]. Meanwhile, even when the uniformity of the radio frequency (RF) field could not be ensured, reported method using the adiabatic pulse that can uniformly conduct 90 or 180 degree excitation, and makes it possible to uniformity suppress the fat signal without affecting the RF penetration, i.e., spectral attenuated inversion recovery (SPAIR) method [2]. Recently, various three-dimensional (3D) acquired MR image techniques have extended widely in clinical usage because they have advantage for diagnosis and visualizing complex anatomy by generating multi planar reconstruction (MPR), e.g., magnetization prepared rapid acquisition GRE (MPRAGE) [3], sampling perfection with applicationoptimized contrasts by using different flip angle evolutions (SPACE) [4], and fast spoiled GRE (FSPGR) [5], respectively. MPRAGE imaging sequence, one of those them, is used especially for anatomical imaging of the whole brain with T1 contrast in clinical. The scan time, however, required much time as compared other methods due to set the optimized inversion time (TI) [6]. To overcome these problems, therefore, we had the idea of the optimization of imaging sequence in head, in which combined FSPGR and SPAIR methods, like technique using abdominal imaging, e.g., 3D-VIBE, THRIVE, and LAVA [7]. The purpose of this study is to assess skull tumor and intracranial meningeal disease in head; we optimized imaging parameter of 3D FSPGR with spectral adiabatic inversion recovery (3D-FSPGR-SPAIR) for contrast-enhanced T1 weighted MRI.

Methods and materials 3D-FSPGR-SPAIR sequences were performed in simulations, phantoms and a healthy volunteer study when changed each imaging parameter [reputation time (TR), flip angle (FA)]. This study was approved by the internal review board of Japanese Red Cross Society Kyoto Daiichi Hospital. Informed consent was obtained from a healthy volunteer and all patients.

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MR Imaging parameter for 3D-FSPGR-SPAIR sequence On 1.5 T MR scanner (Intera Achieva 1.5-T; Philips Medical Systems, Best, The Netherlands), we examined in this study using a body coil excitation and a quadrature coil as a receiver. Then, shimming the object over the whole slice was carried out, tuning in center frequency of water. The imaging parameters for the 3D-FSPGR-SPAIR sequence were shown in Table 1 on page 4 . The imaging parameters for TR and FA were varied; four repetition times (TR) 8.4 ms, 10 ms, 15 ms, and 20 ms respectively; three flip angle (FA) 10 degree, 15 degree, and 20 degree respectively. The other imaging parameters were echo time (TE) 4.1 ms, 20 turbo field echo (TFE) factor, 230 mm field of view (FOV), 243 x 256 matrix, 120 slices per 1 slab, 3 mm slice thickness (inter portion 1.5 mm), low-high k-space profile order (turbo direction Y), and band width ± 86 Hz, respectively. These imaging parameters applied to all study, i.e., simulation (TE, TR, and FA), phantom and healthy volunteer, respectively. Data analysis We measured and evaluated signal intensities (SIs) with setting regions of interest (ROI) on the acquired images of each phantom. Besides, contrast to noise ratios (CNR) between gray matter (GM) and white matter (WM) in phantom and healthy volunteer of each imaging parameter were calculated. CNR were calculated as follows equation (1) [8],

Fig. 13: Equation (1) References: Health Biosciences, Tokushima University - Tokushima/JP where SIWM is SI at white matter, SIGM is SI at gray matter, and SDBG is standard deviation (SD) in ROI at back ground (BG). Simulations Bloch simulations for the SPGR sequence were implemented as follows equation (2) [9];

Fig. 14: Equation (2) References: Health Biosciences, Tokushima University - Tokushima/JP

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where S is signal intensity (SI), M0 denotes the equilibrium magnetization, and # is FA. M0 was set in one in all simulations. T1 and T2* values were set in white matter (WM), gray matter (GM), and Gd-DTPA enhanced tissue value, respectively#These numerical values were shown in Table 2 on page 5 [10; 11]. Gd-DTPA enhanced tissue value was assumed intra-vascular [12]. Phantom study Schematic diagram of the phantom component is shown in Fig. 1 on page 6 . The relaxation times measured in each sample using mixed sequence is shown in Table 3 on page 7 . Each sample on the phantom composed solution of MnCl2 [(1) 0.064 g/L, (2) 0.032 g/L, (3) 0.0021 g/L, and (4) 0.0016 g/L], (5) oil, and Gd-DTPA [(6) 0.4 %, (7) 0.2 %, and (8) 0.1 %], respectively. After phantom images acquired in each imaging parameter were set in region of interests (ROIs) at each sample and BG, SI were measured. CNR, moreover, calculated using data of sample number "3" and "4", because there were nearly T1 value of WM and GM [10]. Additionally, we evaluated SPAIR TI with fixed parameter of data acquisition part, because SPAIR TI needed to be set fat null points to near center of k-space, i.e., lowfrequency domain [13]. Then, we acquired imaging data that SPAIR TI were varied between 0 to 300 ms at 30 ms intervals, and fixed parameters of acquisition part were set TR 10 ms, and FA 15 degree. The other imaging parameter were same above. Volunteer study 3D-FSPGR-SPAIR T1 weighted MR image for ROI analysis settings is shown in Fig. 2 on page 8 . A healthy volunteer was twenty-four-years-old male. After head images acquired in each imaging parameter were set in ROIs at GM, WM, and BG respectively, SIs were measured. CNR in each parameter moreover calculated using these data. Clinical applications We applied this optimized method in clinical cases of skull tumor and intracranial meningeal disease in head. We compared 3D-FSPGR-SPAIR images to various contrast images acquired in a series of scans. Images for this section:

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Table 1: Imaging parameters for 3D-FSPGR-SPAIR sequence in this study.

Fig. 13: Equation (1)

Fig. 14: Equation (2)

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Table 2: Relaxation times of each tissue in setting for simulation.

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Fig. 1: Schematic diagram of the phantom. Each sample in the phantom composed solution of MnCl2 [(1) 0.064 g/L, (2) 0.032 g/L, (3) 0.0021 g/L, and (4) 0.0016 g/L], (5) oil, and Gd-DTPA [(6) 0.4 %, (7) 0.2 %, and (8) 0.1 %], respectively#

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Table 3: Measured relaxation times of each sample in the phantom. They were measured using Mixed sequence.

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Fig. 2: 3D-FSPGR-SPAIR image for ROI analysis settings. Each ROI (yellow elliptical broken line) set GM, WM, and back ground respectively, and measured SI of there.

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Results Fig. 3 on page 10 shows simulated Bloch equation results graph of SI during SPGR sequence for each parameter. When TR became longer, the maximum SI (i.e., Ernst angle) of each tissue was shifted to higher FA. SIs of Gd-DTPA were shown highest values at each imaging parameter. Fig. 4 on page 11 and Fig. 5 on page 12 show the relation between SI and the concentration of MnCl2 or Gd-DTPA; these not linear. Fig. 6 on page 13 shows comparison of CNR between sample number "3" and "4" in phantom at each imaging parameter. It were showed the highest value in FA 20 degree and TR 20 ms, the lowest value in FA10 degree and TR 20 ms. Relation between SPAIR TI and SI is shown in Fig. 7 on page 14 . The SI of oil sample showed most low value in SPAIR TI 90 ms. By contrast, other SIs showed higher values according as SPAIR TI was longer. We therefore applied this value to the following volunteer study. The images of 3D-FSPGR-SPAIR at each imaging parameter are shown in Fig. 8 on page 15 . Fig. 9 on page 16 shows CNR between GM and WM in healthy volunteer at each imaging parameter. There were showed the highest value in FA 20 degree and TR 20 ms, the lowest value in FA 10 degree and TR 20 ms. MR images of three clinical cases are shown in Fig. 10 on page 17 , Fig. 11 on page 18 , and Fig. 12 on page 19 , respectively. Consequently, the imaging acquisitions were successfully performed for some patients. The applications of the optimized parameters (TR 10 ms and FA 15 degree) were acquired high contrast images of the lesion after Gd-DTPA injection to these cases, while maintaining the contrast between WM and GM, and suppressing fat signal. Images for this section:

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Fig. 3: Simulation of the MRI signal intensity during SPGR sequence for each parameters. X axis show FA, Y axis SI. Each parameter in figure (a), (b), (c) and (d) show TR of 8 ms, 10 ms, 15 ms, and 20 ms, respectively. Red lines, moreover, show GM, green lines WM, and blue lines GD-DTPA, respectively.

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Fig. 4: Relation between SI and concentration of MnCl2 in each imaging parameter of 3D-FSPGR-SPAIR. X axis show concentration of MnCl2, Y axis SI. Each parameter in figure (a), (b), (c) and (d) show TR of 8.4 ms, 10 ms, 15 ms, and 20 ms, respectively. Blue lines, moreover, show FA 10 degree, green lines FA 15 degree, and Red lines FA 20 degree, respectively.

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Fig. 5: Relation between SI and concentration of Gd-DTPA in each imaging parameter of 3D-FSPGR-SPAIR. X axis show concentration of Gd-DTPA, Y axis SI. Y axis SI. Each parameter in figure (a), (b), (c) and (d) show TR of 8.4 ms, 10 ms, 15 ms, and 20 ms, respectively. Blue lines, moreover, show FA 10 degree, green lines FA 15 degree, and Red lines FA 20 degree, respectively.

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Fig. 6: Comparison of CNR between sample number "3" and "4" of the phantom at each imaging parameter of 3D-FSPGR-SPAIR.

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Fig. 7: Relation between SPAIR TI and SI.

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Fig. 8: Comparison of CNR between GM and WM of healthy volunteer at each imaging parameter of 3D-FSPGR-SPAIR in a healthy volunteer.

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Fig. 9: Comparison with 3D-FSPGR-SPAIR T1 weighted axial MR images of each imaging parameter in brain of single volunteer (24-year-old male). Imaging parameters for TR and FA were varied respectively . (a)(b)(c) were TR = 8.4 ms (scan time = 3:12), (d)(e)(f) 10 ms (3:35), (g)(h)(i) 15 ms (4:44), and (j)(k)(l) 20 ms (5:53). Besides, (a)(d)(g) (h) were FA = 10 degree, (b)(e)(h)(k) 15 degree, and (c)(f)(i)(l) 20 degree.

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Fig. 10: A 45-year-old male with left basal ganglia tumor. (a)(b)(c) Pre-contrast FLAIR (a), Pre-contrast T1 weighted SE (b) and Post-contrast T1 weighted SE images showed no apparent meningeal abnormality. (d) Post-contrast 3D-FSPGR-SPAIR (d) image detected apparent leptomeningeal abnormality. Compared with the post-contrast T1 weighted image (c), the post-contrast 3D-FSPGR-SPAIR image provided additional information (yellow arrow). The contrast effect was clearly visualized disseminated disease along the meninges due to be suppressed the fat signal.

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Fig. 11: A 57-year-old male with left acoustic neuroma. (a)(b) Pre-contrast T2 weighted balanced steady-state free precession (B-SSFP) (a), T1 weighted SE (b) images. (c)(d) Post-contrast T1 weighted SE (c) and 3D-FSPGR-SPAIR (d) images. Compared with the post-contrast T1 weighted image (c), the post-contrast 3D-FSPGR-SPAIR image was clearly visualized the region of disease enhanced contrast effect, due to be suppressed the fat signal of bone marrow (yellow arrow).

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Fig. 12: Fig. 12 A 67-year-old male with malignant peripheral nerve sheath tumors of the trigeminal nerve. This case was examined to validation of residual disease after surgery. (a)(b) Pre-contrast T2 weighted balanced steady-state free precession (BSSFP) (a), T1 weighted SE (b) images. (c)(d) Post-contrast T1 weighted SE with SPAIR (c) and 3D-FSPGR-SPAIR (d) images. Compared with the post-contrast T1 weighted image with SPAIR (c), the post-contrast 3D-FSPGR-SPAIR image (d) was suppressed artifacts, i.e. venous pulsation artifacts in the posterior fossa, and susceptibility artifacts by inhomogeneity of spheroidal sinus. This method moreover was revealed the presence of residual disease in more detail (yellow arrow), because to be acquired thinner slice image than other methods.

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Conclusion 3D-FSPGR-SPAIR makes it possible to acquire high contrast fat suppressed image and high spatial resolution image with fast scan. Moreover, this method may be useful in diagnosis of skull tumors and intracranial meningeal disease.

Personal information Yuki KANAZAWA, PhD, Assistant Professor Institute of Health Biosciences, Tokushima University Graduate School

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