Youngseob Seo

A quality assurance protocol for diffusion tensor imaging using the head phantom from American College of Radiology

PURPOSE To propose a quality assurance procedure for routine clinical diffusion tensor imaging (DTI) using the widely available American College of Radiology (ACR) head phantom. METHODS Analysis was performed on the data acquired at 1.5 and 3.0 T on whole body clinical MRI scanners using the ACR phantom and included the following: (1) the signal-to-noise ratio (SNR) at the center and periphery of the phantom, (2) image distortion by EPI readout relative to spin echo imaging, (3) distortion of high-b images relative to the b= 0 image caused by diffusion encoding, and (4) determination of fractional anisotropy (FA) and mean diffusivity (MD) measured with region-of-interest (ROI) and pixel-based approaches. Reproducibility of the measurements was assessed by five repetitions of data acquisition on each scanner. RESULTS The SNR at the phantom center was approximately half of that near the periphery at both 1.5 and 3 T. The image distortion by the EPI readout was up to 7 mm at 1.5 T and 10 mm at 3 T. The typical distortion caused by eddy currents from diffusion encoding was on the order of 0.5 mm. The difference between ROI-based and pixel-based MD quantification was 1.4% at 1.5 T and 0.3% at 3 T. The ROI-based MD values were in close agreement (within 2%) with the reference values. The ROI-based FA values were approximately a factor of 10 smaller than pixel-based values and less than 0.01. The measurement reproducibility was sufficient for quality assurance (QA) purposes. CONCLUSIONS This QA approach is simple to perform and evaluates key aspects of the scanner performance for DTI data acquisition using a widely available phantom.

Minimum SNR and acquisition for bias-free estimation of fractional anisotropy in diffusion tensor imaging — a comparison of two analytical techniques and field strengths

Although it is known that low signal-to-noise ratio (SNR) can affect tensor metrics, few studies reporting disease or treatment effects on fractional anisotropy (FA) report SNR; the implicit assumption is that SNR is adequate. However, the level at which low SNR causes bias in FA may vary with tissue FA, field strength and analytical methodology. We determined the SNR thresholds at 1.5 T vs. 3 T in regions of white matter (WM) with different FA and compared FA derived using manual region-of-interest (ROI) analysis to tract-based spatial statistics (TBSS), an operator-independent whole-brain analysis tool. Using ROI analysis, SNR thresholds on our hardware-software magnetic resonance platforms were 25 at 1.5 T and 20 at 3 T in the callosal genu (CG), 40 at 1.5 and 3 T in the anterior corona radiata (ACR), and 50 at 1.5 T and 70 at 3 T in the putamen (PUT). Using TBSS, SNR thresholds were 20 at 1.5 T and 3 T in the CG, and 35 at 1.5 T and 40 at 3 T in the ACR. Below these thresholds, the mean FA increased logarithmically, and the standard deviations widened. Achieving bias-free SNR in the PUT required at least nine acquisitions at 1.5 T and six acquisitions at 3 T. In the CG and ACR, bias-free SNR was achieved with at least three acquisitions at 1.5 T and one acquisition at 3 T. Using diffusion tensor imaging (DTI) to study regions of low FA, e.g., basal ganglia, cerebral cortex, and WM in the abnormal brain, SNR should be documented. SNR thresholds below which FA is biased varied with the analytical technique, inherent tissue FA and field strength. Studies using DTI to study WM injury should document that bias-free SNR has been achieved in the region of the brain being studied as part of quality control.

Assessment of diffusion tensor image quality across sites and vendors using the American College of Radiology head phantom

The purpose of this study was to explore the feasibility of assessing quality of diffusion tensor imaging (DTI) from multiple sites and vendors using American College of Radiology (ACR) phantom. Participating sites (Siemens (n=2), GE (n=2), and Philips (n=4)) reached consensus on parameters for DTI and used the widely available ACR phantom. Tensor data were processed at one site. B0 and eddy current distortions were assessed using grid line displacement on phantom Slice 5; signal‐to‐noise ratio (SNR) was measured at the center and periphery of the b=0 image; fractional anisotropy (FA) and mean diffusivity (MD) were assessed using phantom Slice 7. Variations of acquisition parameters and deviations from specified sequence parameters were recorded. Nonlinear grid line distortion was higher with linear shimming and could be corrected using the 2nd order shimming. Following image registration, eddy current distortion was consistently smaller than acquisition voxel size. SNR was consistently higher in the image periphery than center by a factor of 1.3–2.0. ROI‐based FA ranged from 0.007 to 0.024. ROI‐based MD ranged from 1.90×10−3 to 2.33×10−3mm2/s(median=2.04×10−3mm2/s). Two sites had image void artifacts. The ACR phantom can be used to compare key quality measures of diffusion images acquired from multiple vendors at multiple sites. PACS number(s): 87.57.‐s, 87.19.lfThe purpose of this study was to explore the feasibility of assessing quality of diffusion tensor imaging (DTI) from multiple sites and vendors using American College of Radiology (ACR) phantom. Participating sites (Siemens (n=2), GE (n=2), and Philips (n=4)) reached consensus on parameters for DTI and used the widely available ACR phantom. Tensor data were processed at one site. B0 and eddy current distortions were assessed using grid line displacement on phantom Slice 5; signal-to-noise ratio (SNR) was measured at the center and periphery of the b=0 image; fractional anisotropy (FA) and mean diffusivity (MD) were assessed using phantom Slice 7. Variations of acquisition parameters and deviations from specified sequence parameters were recorded. Nonlinear grid line distortion was higher with linear shimming and could be corrected using the 2nd order shimming. Following image registration, eddy current distortion was consistently smaller than acquisition voxel size. SNR was consistently higher in the image periphery than center by a factor of 1.3-2.0. ROI-based FA ranged from 0.007 to 0.024. ROI-based MD ranged from 1.90×10-3 to 2.33×10-3mm2/s(median=2.04×10-3mm2/s). Two sites had image void artifacts. The ACR phantom can be used to compare key quality measures of diffusion images acquired from multiple vendors at multiple sites. PACS number(s): 87.57.-s, 87.19.lf.

MO-FG-CAMPUS-IeP3-01: Evaluation of Specific Absorption Rate and Temperature Increase Induced by Artificial Medical Implants During MRI Scan

PURPOSE Heating of patients or burning of biological tissues around medical implants by RF power during MRI scan is a significant patient safety concern. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation due to artificial hip joints during MRI scans. METHODS SAR measurement experiment was performed on three discrete manufacturers at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T2w inversion recovery, and T2w TSE) with imaging parameters were selected. A gelled saline phantom mimicking human body tissue was made (Fig.1). FDTD method was utilized to calculate the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located around two artificial hip joints inside the phantom. 56 Fiber Bragg Grating (FBG) temperature sensors (28 sensors on each artificial hip joint) were located on both left and right artificial hip joints to measure temperature change during MRI scan (Fig.1). Both E-field and FBG temperature sensors were calibrated with traceability at Korea Research Institute of Standards and Science (KRISS). RESULTS Simulation shows that high SAR values occur in the head and tail of the implanted artificial hip joints (Fig.1 lower right). 3T MRI scanner shows that the local averaged-SAR values measured by probe 1, 2, and 3 are 2.30, 2.77, and 1.68 W/kg, compared to MRI scanner-reported whole body SAR value (≤1.5 W/kg) for T1w TSE and T2w_IR (Table 1). The maximum temperature elevation measured by FBG sensors is 1.49°C at 1.5 T, 2.0°C at 3 T, and 2.56°C at 3 T for T1w TSE, respectively (Table 2). CONCLUSION It is essential to assess the safety of MRI system for patient with medical implant by measuring not only accurate SAR deposited in the body, but also temperature elevation due to the deposited SAR during clinical MRI.

Magnetic resonance thermal imaging combined with SMASH navigators in the presence of motion

This study develops and tests an MR thermometry method combined with SMASH navigators in phantom experiments mimicking human liver motion with the purpose of detecting and correcting motion artifacts in thermal MR images. Experimental data were acquired on a 3T MRI scanner. Motion artifacts of mobile phantoms mimicking human liver motion were detected and corrected using the SMASH navigators and then MR temperature maps were obtained using a proton resonant frequency (PRF) shift method with complex image subtraction. Temperature acquired by MR thermal imaging was compared to that measured via thermocouples. MR thermal imaging combined with the SMASH navigator technique resulted in accurate temperature maps of the mobile phantoms compared to temperatures measured using the thermocouples. The differences between the obtained and measured temperatures varied from 8.2°C to 14.2°C and 2.2°C to 4.9°C without and with motion correction, respectively. Motion correction improved the temperature acquired by MR thermal imaging by >55%. The combination of the MR thermal imaging and SMASH navigator technique will enable monitoring and controlling heat distribution and temperature change in tissues during thermal therapies and will be a very important tool for cancer treatment in mobile organs. PACS number: 87.57.‐s

Correcting B0 Field Distortions in MRI Caused by Stainless Steel Orthodontic Appliances at 1.5 T Using Permanent Magnets - A Head Phantom Study

Susceptibility artifacts caused by stainless steel orthodontic appliances (braces) pose significant challenges in clinical brain MRI examinations. We introduced field correction device (FCD) utilizing permanent magnets to cancel the induced B0 inhomogeneity and mitigate geometric distortions in MRI. We evaluated a prototype FCD using a 3D-printed head phantom in this proof of concept study. The phantom was compartmented into anterior frontal lobe, temporal lobe, fronto-parieto-occipital lobe, basal ganglia and thalami, brain stem, and cerebellum and had built-in orthogonal gridlines to facilitate the quantification of geometric distortions and volume obliterations. Stainless steel braces were mounted on dental models of three different sizes with total induced magnetic moment 0.15 to 0.17 A·m2. With braces B0 standard deviation (SD) ranged from 2.8 to 3.7 ppm in the temporal and anterior frontal lobes vs. 0.2 to 0.3 ppm without braces. The volume of brain regions in diffusion weighted imaging was obliterated by 32–38% with braces vs. 0% without braces in the cerebellum. With the FCD the SD of B0 ranged from 0.3 to 1.2 ppm, and obliterated volume ranged from 0 to 6% in the corresponding brain areas. These results showed that FCD can effectively decrease susceptibility artifacts from orthodontic appliances.

MRI scanner-independent specific absorption rate measurements using diffusion coefficients

Abstract Objective The purpose of this study was to measure specific absorption rate (SAR) during MRI scanning using a human torso phantom through quantification of diffusion coefficients independently of those reported by the scanner software for five 1.5 and 3 T clinical MRI systems from different vendors. Methods A quadrature body coil transmitted the RF power and a body array coil received the signals. With diffusion tensor imaging, SAR values for three MRI sequences were measured on the five scanners and compared to the nominal values calculated by the scanners. Results For the GE 1.5 T MRI system, the MRI scanner‐reported SAR value was 1.58 W kg‐1 and the measured SAR value was 1.38 W kg‐1. For the Philips 1.5 T MRI scanner, the MRI system‐reported SAR value was 1.48 W kg‐1 and the measured value was 1.39 W kg‐1. For the Siemens 3 T MRI system, the reported SAR value was 2.5 W kg‐1 and the measured SAR value was 1.96 W kg‐1. For two Philips 3 T MRI scanners, the reported SAR values were 1.5 W kg‐1 and the measured values were 1.94 and 1.96 W kg‐1. The percentage differences between the measured and reported SAR values on the GE 1.5 T, Philips 1.5 T, Siemens 3 T, and Philips 3 T were 13.5, 6.3, 24.2, 25.6, and 26.6% respectively. Conclusion The scanner‐independent SAR measurements using diffusion coefficients described in this study can play a significant role in estimating accurate SAR values as a standardized method.

An MRI scanner‐independent radiofrequency dosimeter for the estimation of RF power deposition with a human torso phantom

An assessment of radiofrequency (RF) power deposition independent of the information provided by MRI scanners is thus desirable. We developed a novel scanner-independent RF dosimeter based on measurements of the resistance of a thermistor that dissipates the RF power during scanning. With the RF dosimeter, the RF power deposition for four MRI sequences with specific absorption rate (SAR) values (0.1-3.3 W/kg) was measured on five different scanners and the correlation between the RF dosimeter reading and the SAR levels calculated by the scanners was investigated. The novel RF dosimeter showed a linear relationship between the RF power deposition and the scanner-reported whole-body averaged SAR for each scanner. However, there was a variability in the reading among different scanners. The RF dosimeter readings were 9.7 and 9.5 mW on GE 1.5 T (SAR=2.6 W/kg), 3.6 and 3.7 mW on Philips 1.5 T (SAR=3.3 W/kg), 9.5 and 8.6 mW on Siemens 3 T (SAR=3.0 W/kg), and 4.7 and 3.9 mW on Philips 3 T (SAR=2.6 W/kg), respectively. The scanner-independent RF dosimeter developed in this study can play a significant role in checking the accuracy of scanners’ SAR values as a standardized method for measuring the RF power deposition for MR safety.

SU-F-I-27: Measurement of SAR and Temperature Elevation During MRI Scans

PURPOSE The poor reliability and repeatability of the manufacturer-reported SAR values on clinical MRI systems have been acknowledged. The purpose of this study is to not only measure SAR values, but also RF-induced temperature elevation at 1.5 and 3T MRI systems. METHODS SAR measurement experiment was performed at 1.5 and 3T. Three MRI RF sequences (T1w TSE, T1w inversion recovery, and T2w TSE) with imaging parameters were selected. A hydroxyl-ethylcelluose (HEC) gelled saline phantom mimicking human body tissue was made. Human torso phantom were constructed, based on Korean adult standard anthropometric reference data (Fig.1). FDTD method was utilized to calculate the SAR distribution using Sim4Life software. Based on the results of the simulation, 4 electrical field (E-field) sensors were located inside the phantom. 55 Fiber Bragg Grating (FBG) temperature sensors (27 sensors in upper and lower cover lids, and one sensor located in the center as a reference) were located inside the phantom to measure temperature change during MRI scan (Fig.2). RESULTS Simulation shows that SAR value is 0.4 W/kg in the periphery and 0.001 W/kg in the center (Fig.2). One 1.5T and one of two 3T MRI systems represent that the measured SAR values were lower than MRI scanner-reported SAR values. However, the other 3T MRI scanner shows that the averaged SAR values measured by probe 2, 3, and 4 are 6.83, 7.59, and 6.01 W/kg, compared to MRI scanner-reported whole body SAR value (<1.5 W/kg) for T2w TSE (Table 1). The temperature elevation measured by FBG sensors is 5.2°C in the lateral shoulder, 5.1°C in the underarm, 4.7°C in the anterior axilla, 4.8°C in the posterior axilla, and 4.8°C in the lateral waist for T2w TSE (Fig.3). CONCLUSION It is essential to assess the safety of MRI system for patient by measuring accurate SAR deposited in the body during clinical MRI.