Improving the accuracy of PGSE DTI experiments using the spatial distribution of b matrix

Diffusion tensor imaging metrics as natural markers of multiple sclerosis-induced brain disorders with a low Expanded Disability Status Scale score

Non-invasive and effective differentiation along with determining the degree of deviations compared to the healthy cohort is important in the case of various brain disorders, including multiple sclerosis (MS). Evaluation of the effectiveness of diffusion tensor metrics (DTM) in 3T DTI for recording MS-related deviations was performed using a time-acceptable MRI protocol with unique comprehensive detection of systematic errors related to spatial heterogeneity of magnetic field gradients. In a clinical study, DTMs were acquired in segmented regions of interest (ROIs) for 50 randomly selected healthy controls (HC) and 50 multiple sclerosis patients. Identical phantom imaging was performed for each clinical measurement to estimate and remove the influence of systematic errors using the b-matrix spatial distribution in the DTI (BSD-DTI) technique. In the absence of statistically significant differences due to age in healthy volunteers and patients with multiple sclerosis, the existence of significant differences between groups was proven using DTM. Moreover, a statistically significant impact of spatial systematic errors occurs for all ROIs and DTMs in the phantom and for approximately 90 % in the HC and MS groups. In the case of a single patient measurement, this appears for all the examined ROIs and DTMs. The obtained DTMs effectively discriminate healthy volunteers from multiple sclerosis patients with a low mean score on the Expanded Disability Status Scale. The magnitude of the group differences is typically significant, with an effect size of approximately 0.5, and similar in both the standard approach and after elimination of systematic errors. Differences were also observed between metrics obtained using these two approaches. Despite a small alterations in mean DTMs values for groups and ROIs (1-3 %), these differences were characterized by a huge effect (effect size ∼0.8 or more). These findings indicate the importance of determining the spatial distribution of systematic errors specific to each MR scanner and DTI acquisition protocol in order to assess their impact on DTM in the ROIs examined. This is crucial to establish accurate DTM values for both individual patients and mean values for a healthy population as a reference. This approach allows for an initial reliable diagnosis based on DTI metrics.

Restricted diffusion characteristics in oscillating gradient spin echo with mesoscopic phantom

In diffusion magnetic resonance imaging, oscillating gradient spin echo (OGSE) has an extremely short diffusion time if motion probing gradient (MPG) is applied to the waveform. Further, it can detect microstructural specificity. OGSE changes sensitivity to spin displacement velocity based on the MPG phase. The current study aimed to investigate the restricted diffusion characteristics of each OGSE waveform using the capillary phantom with various b-values, frequencies, and MPG phases. We performed OGSE (b-value = 300, 500, 800, 1200, 1600, and 2000 s/mm2) for the sine and cosine waveforms using the capillary phantom (6, 12, 25, 50, and 100 μm and free water) with a 9.4-T experimental magnetic resonance imaging system and a solenoid coil. We evaluated the axial and radial diffusivity (AD, RD) of each structure size. The output current of the MPG was assessed with an oscilloscope and analyzed with the gradient modulation power spectra by fast Fourier transform. In sine, the sidelobe spectrum was enhanced with increasing frequency, and the central spectrum slightly increased. The difference in RD was detected at 6 and 12 μm; however, it did not depend on the structure scale at 50 or 100 μm and free water. In cosine, the diffusion spectrum was enhanced, whereas the central spectrum decreased with increasing frequency. Both AD and RD in cosine had a frequency dependence, and AD and RD increased with a higher frequency regardless of structure size. AD and RD in either sine or cosine had no evident b-value dependence. We evaluated the OGSE-restricted diffusion characteristics. The measurements obtained diffusion information similar to the pulsed gradient spin echo. Hence, the cosine measurements indicated that a higher frequency could capture faster diffusion within the diffusion phenomena.

Retrospective Motion Artifact Reduction by Spatial Scaling of Liver Diffusion-Weighted Images

Cardiac motion causes unpredictable signal loss in respiratory-triggered diffusion-weighted magnetic resonance imaging (DWI) of the liver, especially inside the left lobe. The left liver lobe may thus be frequently neglected in the clinical evaluation of liver DWI. In this work, a data-driven algorithm that relies on the statistics of the signal in the left liver lobe to mitigate the motion-induced signal loss is presented. The proposed data-driven algorithm utilizes the exclusion of severely corrupted images with subsequent spatially dependent image scaling based on a signal-loss model to correctly combine the multi-average diffusion-weighted images. The signal in the left liver lobe is restored and the liver signal is more homogeneous after applying the proposed algorithm. Furthermore, overestimation of the apparent diffusion coefficient (ADC) in the left liver lobe is reduced. The proposed algorithm can therefore contribute to reduce the motion-induced bias in DWI of the liver and help to increase the diagnostic value of DWI in the left liver lobe.

The Role of Magnetic Resonance Imaging and Computed Tomography in Spinal Cord Injury

Traumatic injuries of the spine are associated with long-term morbidity and mortality. Timely diagnosis and appropriate management of mechanical instability and spinal cord injury are important to prevent further neurologic deterioration. Spine surgeons require an understanding of the essential imaging techniques concerning the diagnosis, management, and prognosis of spinal cord injury. We present a review in the role of computed tomography (CT) including advancements in multidetector CT (MDCT), dual energy CT (DECT), and photon counting CT, and how it relates to spinal trauma. We also review magnetic resonance imaging (MRI) and some of the developed MRI based classifications for prognosticating the severity and outcome of spinal cord injury, such as diffusion weighted imaging (DWI), diffusion tractography (DTI), functional MRI (fMRI), and perfusion MRI.

The Value of Various Post-Processing Modalities of Diffusion Weighted Imaging in the Detection of Multiple Sclerosis

Diffusion tensor imaging (DTI) showed its adequacy in evaluating the normal-appearing white matter (NAWM) and lesions in the brain that are difficult to evaluate with routine clinical magnetic resonance imaging (MRI) in multiple sclerosis (MS). Recently, MRI systems have been developed with regard to software and hardware, leading to different proposed diffusion analysis methods such as diffusion tensor imaging, q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, and axonal diameter measurement. These methods have the ability to better detect in vivo microstructural changes in the brain than DTI. These different analysis modalities could provide supplementary inputs for MS disease characterization and help in monitoring the disease’s progression as well as treatment efficacy. This paper reviews some of the recent diffusion MRI methods used for the assessment of MS in vivo.

Deep Learning-Based Auto-Segmentation of Spinal Cord Internal Structure of Diffusion Tensor Imaging in Cervical Spondylotic Myelopathy

Cervical spondylotic myelopathy (CSM) is a chronic disorder of the spinal cord. ROI-based features on diffusion tensor imaging (DTI) provide additional information about spinal cord status, which would benefit the diagnosis and prognosis of CSM. However, the manual extraction of the DTI-related features on multiple ROIs is time-consuming and laborious. In total, 1159 slices at cervical levels from 89 CSM patients were analyzed, and corresponding fractional anisotropy (FA) maps were calculated. Eight ROIs were drawn, covering both sides of lateral, dorsal, ventral, and gray matter. The UNet model was trained with the proposed heatmap distance loss for auto-segmentation. Mean Dice coefficients on the test dataset for dorsal, lateral, and ventral column and gray matter were 0.69, 0.67, 0.57, 0.54 on the left side and 0.68, 0.67, 0.59, 0.55 on the right side. The ROI-based mean FA value based on segmentation model strongly correlated with the value based on manual drawing. The percentages of the mean absolute error between the two values of multiple ROIs were 0.07, 0.07, 0.11, and 0.08 on the left side and 0.07, 0.1, 0.1, 0.11, and 0.07 on the right side. The proposed segmentation model has the potential to offer a more detailed spinal cord segmentation and would be beneficial for quantifying a more detailed status of the cervical spinal cord.

Effective Connectivity during an Avoidance-Based Pavlovian-to-Instrumental Transfer Task

Pavlovian-to-instrumental transfer (PIT) refers to a phenomenon whereby a classically conditioned stimulus (CS) impacts the motivational salience of instrumental behavior. We examined behavioral response patterns and functional magnetic resonance imaging (fMRI) based effective connectivity during an avoidance-based PIT task. Eleven participants (8 females; Mage = 28.2, SD = 2.8, range = 25-32 years) completed the task. Effective connectivity between a priori brain regions engaged during the task was determined using hemodynamic response function group iterative multiple model estimation (HRF-GIMME). Participants exhibited behavior that was suggestive of specific PIT, a CS previously associated with a reinforcing outcome increased instrumental responding directed at the same outcome. We did not find evidence for general PIT; a CS did not significantly increase instrumental responding towards a different but related outcome. Using HRF-GIMME, we recovered effective connectivity maps among corticostriatal circuits engaged during the task. Group-level paths revealed directional effects from left putamen to right insula and from right putamen to right cingulate. Importantly, a direct effect of specific PIT stimuli on blood-oxygen-level-dependent (BOLD) activity in the left putamen was found. Results provide initial evidence of effective connectivity in key brain regions in an avoidance-based PIT task network. This study adds to the literature studying PIT effects in humans and employing GIMME models to understand how psychological phenomena are supported in the brain.

A 16-Channel Dipole Antenna Array for Human Head Magnetic Resonance Imaging at 10.5 Tesla

For ultra-high field and frequency (UHF) magnetic resonance imaging (MRI), the associated short wavelengths in biological tissues leads to penetration and homogeneity issues at 10.5 tesla (T) and require antenna transmit arrays for efficiently generated 447 MHz B₁⁺ fields (defined as the transmit radiofrequency (RF) magnetic field generated by RF coils). Previously, we evaluated a 16-channel combined loop + dipole antenna (LD) 10.5 T head array. While the LD array configuration did not achieve the desired B₁⁺ efficiency, it showed an improvement of the specific absorption rate (SAR) efficiency compared to the separate 8-channel loop and separate 8-channel dipole antenna arrays at 10.5 T. Here we compare a 16-channel dipole antenna array with a 16-channel LD array of the same dimensions to evaluate B₁⁺ efficiency, 10 g SAR, and SAR efficiency. The 16-channel dipole antenna array achieved a 24% increase in B₁⁺ efficiency in the electromagnetic simulation and MR experiment compared to the LD array, as measured in the central region of a phantom. Based on the simulation results with a human model, we estimate that a 16-channel dipole antenna array for human brain imaging can increase B₁⁺ efficiency by 15% with similar SAR efficiency compared to a 16-channel LD head array.

Effective Connectivity Analysis of Brain Activated Regions during Distracted Driving

This study aims to use functional magnetic resonance imaging (fMRI) to assess the effective connectivity between the regions of the brain activated when driving and performing a secondary task (addition task). The subjects used an MR-compatible driving simulator ㅊ to manipulate the driving wheel with both hands and control the pedals (accelerator and brake) with their right foot as if they were driving in an actual environment. Effective connectivity analysis was performed for three regions of the right and the left hemispheres with the highest z-scores, and six of the regions of the entire brain (right and left hemisphere) activated during driving by dynamic causal modeling (DCM). In the right hemisphere, a motor control pathway related to movement control for driving performance was discovered; in the left hemisphere, the pathways in the regions related to movement control for driving performance, starting with the region associated with the secondary task, were discovered. In the whole brain, connectivity was discovered in each of the right and left hemispheres. The motor network of declarative memory, which is the connectivity of the right thalamus, left lingual gyrus, and right precentral gyrus, was worth noting. These results seem meaningful, as they demonstrate the connectivity associated with the control of voluntary movement related to memory from human experience, although limited to driving tasks.

Diffusion Kurtosis Imaging Fiber Tractography of Major White Matter Tracts in Neurosurgery

Diffusion tensor imaging (DTI)-based fiber tractography is routinely used in clinical applications to visualize major white matter tracts, such as the corticospinal tract (CST), optic radiation (OR), and arcuate fascicle (AF). Nevertheless, DTI is limited due to its capability of resolving intra-voxel multi-fiber populations. Sophisticated models often require long acquisition times not applicable in clinical practice. Diffusion kurtosis imaging (DKI), as an extension of DTI, combines sophisticated modeling of the diffusion process with short acquisition times but has rarely been investigated in fiber tractography. In this study, DTI- and DKI-based fiber tractography of the CST, OR, and AF was investigated in healthy volunteers and glioma patients. For the CST, significantly larger tract volumes were seen in DKI-based fiber tractography. Similar results were obtained for the OR, except for the right OR in patients. In the case of the AF, results of both models were comparable with DTI-based fiber tractography showing even significantly larger tract volumes in patients. In the case of the CST and OR, DKI-based fiber tractography contributes to advanced visualization under clinical time constraints, whereas for the AF, other models should be considered.

Diffusion Tensor Imaging of the Sciatic Nerve as a Surrogate Marker for Nerve Functionality of the Upper and Lower Limb in Patients With Diabetes and Prediabetes

Background

Nerve damage in diabetic neuropathy (DN) is assumed to begin in the distal legs with a subsequent progression to hands and arms at later stages. In contrast, recent studies have found that lower limb nerve lesions in DN predominate at the proximal sciatic nerve and that, in the upper limb, nerve functions can be impaired at early stages of DN.

Materials and Methods

In this prospective, single-center cross-sectional study, participants underwent diffusion-weighted 3 Tesla magnetic resonance neurography in order to calculate the sciatic nerve’s fractional anisotropy (FA), a surrogate parameter for structural nerve integrity. Results were correlated with clinical and electrophysiological assessments of the lower limb and an examination of hand function derived from the Purdue Pegboard Test.

Results

Overall, 71 patients with diabetes, 11 patients with prediabetes and 25 age-matched control subjects took part in this study. In patients with diabetes, the sciatic nerve’s FA showed positive correlations with tibial and peroneal nerve conduction velocities (r = 0.62; p < 0.001 and r = 0.56; p < 0.001, respectively), and tibial and peroneal nerve compound motor action potentials (r = 0.62; p < 0.001 and r = 0.63; p < 0.001, respectively). Moreover, the sciatic nerve’s FA was correlated with the Pegboard Test results in patients with diabetes (r = 0.52; p < 0.001), prediabetes (r = 0.76; p < 0.001) and in controls (r = 0.79; p = 0.007).

Conclusion

This study is the first to show that the sciatic nerve’s FA is a surrogate marker for functional and electrophysiological parameters of both upper and lower limbs in patients with diabetes and prediabetes, suggesting that nerve damage in these patients is not restricted to the level of the symptomatic limbs but rather affects the entire peripheral nervous system.

Effects of Lifelong Musicianship on White Matter Integrity and Cognitive Brain Reserve

There is a significant body of research that has identified specific, high-end cognitive demand activities and lifestyles that may play a role in building cognitive brain reserve, including volume changes in gray matter and white matter, increased structural connectivity, and enhanced categorical perception. While normal aging produces trends of decreasing white matter (WM) integrity, research on cognitive brain reserve suggests that complex sensory–motor activities across the life span may slow down or reverse these trends. Previous research has focused on structural and functional changes to the human brain caused by training and experience in both linguistic (especially bilingualism) and musical domains. The current research uses diffusion tensor imaging to examine the integrity of subcortical white matter fiber tracts in lifelong musicians. Our analysis, using Tortoise and ICBM-81, reveals higher fractional anisotropy, an indicator of greater WM integrity, in aging musicians in bilateral superior longitudinal fasciculi and bilateral uncinate fasciculi. Statistical methods used include Fisher’s method and linear regression analysis. Another unique aspect of this study is the accompanying behavioral performance data for each participant. This is one of the first studies to look specifically at musicianship across the life span and its impact on bilateral WM integrity in aging.

Tractography-Based Analysis of Morphological and Anatomical Characteristics of the Uncinate Fasciculus in Human Brains

(1) Background: The uncinate fasciculus (UF) is a white matter bundle connecting the prefrontal cortex and temporal lobe. The functional role of the uncinate fasciculus is still uncertain. The role of the UF is attributed to the emotional empathy network. The present study aimed to more accurately the describe anatomical variability of the UF by focusing on the volume of fibers and testing for correlations with sex and age. (2) Material and Methods: Magnetic resonance imaging of adult patients with diffusion tensor imaging (DTI) was performed on 34 patients. The total number of fibers, volume of UF, and number of tracts were processed using DSI studio software. The DSI studio allows for mapping of different nerve pathways and visualizing of the obtained results using spatial graphics. (3) Results: The total number of UF tracts was significantly higher in the right hemisphere compared to the left hemisphere (right M ± SD = 52 ± 24; left: 39 ± 25, p < 0.05). A hook-shaped UF was the most common variant (91.7%). The UF volumes were larger in men (1410 ± 150.7 mm³) as compared to women (1325 ± 133.2 mm³) (p < 0.05). The mean fractional anisotropy (FA) values of the UF were significantly larger on the left side 0.597, while the right UF had an average of 0.346 (p < 0.05). Patients older than 50 years old had a significantly higher value of mean diffusivity (MD) (p = 0.034). In 73.5% of patients, a greater number of fibers terminated in the inferior part of the inferior frontal gyrus. (4) Conclusions: The morphological characteristics of the UF, unlike the shape, are associated with sex and are characterized by hemispheric dominance. These findings confirm the results of the previous studies. Future research should examine the potential correlation among the UF volume, number of fibers, and total brain volume in both sexes and patient psychological state.

Towards the precise microstructural mapping. Testing new anisotropic phantoms with layered and capillary geometries

In pursuance of an accurate reality description, more and more physical theories and models are being developed. MRI techniques have superiority in terms of sensitivity to the specific tissue features and their variations. Thus, very precise determination of relaxation and diffusive properties in biological systems may enhance the cellular-level mapping. In this work we present new anisotropic phantoms with layered and capillary geometries, which can contribute to the characterization of biological samples far below the voxel size. Highly advanced manufacturing technique allowed us to obtain well-defined, stable structures, which is undisputable advantage of these models. The phantoms were tested in terms of relaxation and diffusion behavior of water in 50 mT and 0.6 T magnetic field strength. 1D and 2D relaxation experiments revealed many relaxation mechanisms. Diffusion Weighted Imaging confirmed speculations about heterogeneous diffusion coefficient, despite application of the recently proposed BSD-DTI method.

Influence of Acquisition Time on MR Image Quality Estimated with Nonparametric Measures Based on Texture Features

Correlation of parametrized image texture features (ITF) analyses conducted in different regions of interest (ROIs) overcomes limitations and reliably reflects image quality. The aim of this study is to propose a nonparametrical method and classify the quality of a magnetic resonance (MR) image that has undergone controlled degradation by using textural features in the image. Images of 41 patients, 17 women and 24 men, aged between 23 and 56 years were analyzed. T2-weighted sagittal sequences of the lumbar spine, cervical spine, and knee and T2-weighted coronal sequences of the shoulder and wrist were generated. The implementation of parallel imaging with the use of GRAPPA2, GRAPPA3, and GRAPPA4 led to a substantial reduction in the scanning time but also degraded image quality. The number of degraded image textural features was correlated with the scanning time. Longer scan times correlated with markedly higher ITF image persistence in comparison with images computed with reduced scan times. Higher ITF preservation was observed in images of bones in the spine and femur as compared to images of soft tissues, i.e., tendons and muscles. Finally, a nonparametrized image quality assessment based on an analysis of the ITF, computed for different tissues, correlating with the changes in acquisition time of the MR images, was successfully developed. The correlation between acquisition time and the number of reproducible features present in an MR image was found to yield the necessary assumptions to calculate the quality index.

Assessment of the systematic errors caused by diffusion gradient inhomogeneity in DTI-computer simulations

Diffusion tensor imaging (DTI) is a powerful MRI modality that allows the investigation of the microstructure of tissues both in vivo and noninvasively. Its reliability is strictly dependent on the performance of diffusion-sensitizing gradients, of which spatial nonuniformity is a known issue in the case of virtually all clinical MRI scanners. The influence of diffusion gradient inhomogeneity on the accuracy of the diffusion tensor imaging was investigated by means of computer simulations supported by an MRI experiment performed at the isocenter and 15 cm away. The DTI measurements of two diffusion phantoms were simulated assuming a nonuniform diffusion-sensitizing gradient and various levels of noise. Thereafter, the tensors were calculated by two methods: (i) assuming a spatially constant b-matrix (standard DTI) and (ii) applying the b-matrix spatial distribution in the DTI (BSD-DTI) technique, a method of indicating the b-matrix for each voxel separately using an anisotropic phantom as a standard of diffusion. The average eigenvalues and fractional anisotropy across the homogeneous region of interest were calculated and compared with the expected values. Diffusion gradient inhomogeneity leads to overestimation of the largest eigenvalue, underestimation of the smallest one and thus overestimation of fractional anisotropy. The effect is similar to that caused by noise; however, it could not be corrected by increasing SNR. The MRI measurements, performed using a 3 T clinical scanner, revealed that the split of the eigenvalues measured 15 cm away from the isocenter is significant (up to 25%). The BSD-DTI calibration allowed the reduction of the measured fractional anisotropy of the isotropic medium from 0.174 to 0.031, suggesting that gradient inhomogeneity was the main cause of this error. For the phantom measured at the isocenter, however, the split was almost not observed; the average eigenvalues were shifted from the expected value by ~ 5%.

Physical and numerical phantoms for the validation of brain microstructural MRI: A cookbook

Phantoms, both numerical (software) and physical (hardware), can serve as a gold standard for the validation of MRI methods probing the brain microstructure. This review aims to provide guidelines on how to build, implement, or choose the right phantom for a particular application, along with an overview of the current state-of-the-art of phantoms dedicated to study brain microstructure with MRI. For physical phantoms, we discuss the essential requirements and relevant characteristics of both the (NMR visible) liquid and (NMR invisible) phantom materials that induce relevant microstructural features detectable via MRI, based on diffusion, intra-voxel incoherent motion, magnetization transfer or magnetic susceptibility weighted contrast. In particular, for diffusion MRI, many useful phantoms have been proposed, ranging from simple liquids to advanced biomimetic phantoms consisting of hollow or plain microfibers and capillaries. For numerical phantoms, the focus is on Monte Carlo simulations of random walk, for which the basic principles, along with useful criteria to check and potential pitfalls are reviewed, in addition to a literature overview highlighting recent advances. While many phantoms exist already, the current review aims to stimulate further research in the field and to address remaining needs.

Analysis and correction of errors in DTI-based tractography due to diffusion gradient inhomogeneity

The DTI-based tractography, despite its restrictions, is the most widely utilized fiber tracking method in clinical practice. Its fidelity is strictly dependent on the precision and accuracy of the DTI measurement, which in turn is limited by the linearity of the diffusion sensitizing gradient. The influence of the gradient distortions on the differences between the real and measured orientation of fibers was investigated by computer simulations. In addition, the potential of the b-matrix Spatial Distribution in DTI (BSD-DTI) technique in correcting such kind of errors was demonstrated experimentally. The simulations revealed that the diffusion gradient inhomogeneity, if not corrected, leads to the erroneous indication of the fiber direction. The average and maximum deviations were about 1° and 15°, respectively. Remarkably, the deviation between the real and measured orientation of fibers is directionally dependent, what was confirmed in MRI measurement. The deviation errors can be effectively corrected by preceding the DTI measurement with the BSD-DTI calibration.

The generalized Stejskal-Tanner equation for non-uniform magnetic field gradients

The intensity of the diffusion weighted NMR signal is described by the Stejskal-Tanner equation, which was derived under the assumption that the gradients are uniform throughout the sample. Nevertheless, it has been demonstrated numerous times that this condition is not fulfilled in the cases of virtually any clinical or research MRI scanners. Therefore, technically, the Stejskal-Tanner equation is valid only for a very specific case of homogeneous gradients. In this paper the Stejskal-Tanner equation was derived for the general case on non-uniform diffusion gradients. To this end, the magnetic field was expressed as linear in a curvilinear coordinate system defined by a vector function p(r). Thereafter, the expression for the non-linear magnetic field was put into the Bloch-Torrey equation and solved. Moreover, the meaning of so-called coil tensor, which is used for the gradients inhomogeneity correction, was explained. It was proven that in the case of the spin echo-based sequences, the Stejskal-Tenner equation is still valid, even if the diffusion gradients are non-uniform. However, in such a case, the b-matrix should be derived for each voxel separately. For other sequence, the derived relation possesses an imaginary term, which corresponds do the phase shift of the diffusion weighted signal.

The b matrix calculation using the anisotropic phantoms for DWI and DTI experiments

B-matrix Spatial Distribution Diffusion Tensor Imaging (BSD-DTI) is a novel approach to imaging of the diffusion tensor. By means of the method a spatial distribution of the b matrices is determined and subsequently incorporated into diffusion tensor calculation. This paper presents experimental verification of the method. Statistical analysis of the results shows significant variation of the b matrix components through the slices and spatial b matrix maps depict inhomogeneity of the gradient distribution for MRI scanners equipped with wide bore magnets. The accuracy of the diffusion tensor determination was improved by the factor of about 3 for the isotropic phantom using the Spin Echo Diffusion sequence.

Innovative anisotropic phantoms for calibration of diffusion tensor imaging sequences

The paper describes a novel type of anisotropic phantoms designed for b-matrix spatial distribution diffusion tensor imaging (BSD-DTI). Cubic plate anisotropic phantom, cylinder capillary phantom and water reference phantom are described as a complete set necessary for calibration, validation and normalization of BSD-DTI. An innovative design of the phantoms basing on enclosing the anisotropic cores in glass balls filled with liquid made for the first time possible BSD calibration with usage of echo planar imaging (EPI) sequence. Susceptibility artifacts prone to occur in EPI sequences were visibly reduced in the central region of the phantoms. The phantoms were designed for usage in a clinical scanner's head coil, but can be scaled for other coil or scanner types. The phantoms can be also used for a pre-calibration of imaging of other types of phantoms having more specific applications.

Anisotropic phantoms in Magnetic Resonance Imaging

Even though Magnetic Resonance Imaging (MRI) gives possibility to obtain qualitatively very good images, most quantitative results obtained by means of MRI are biased with high dependence on particular hardware parameters, imaging sequence used, and properties of analysed sample. Thus to enable comparison between results obtained on different scanners a calibration is needed. In one of the approaches to Diffusion Tensor Imaging (DTI), a B-matrix Spatial Distribution DTI (BSD-DTI) anisotropic phantoms are crucial in precise determination of the diffusion tensor. Anisotropic phantoms can be also useful as a porosity models or rock models in geology. The paper focuses on characterization of several anisotropic phantoms and describes their applications in DTI, and other domains related to MRI.

Theoretical analysis of phantom rotations in BSD-DTI

A novel method of improving accuracy of diffusion tensor imaging (DTI), called BSD-DTI (B-spatial distribution in DTI), has been recently proposed. Determination of the b matrix components using an anisotropic phantom, and derivation of the spatial distribution are of the essence in this approach. So far, a sufficient uniformity of the diffusion properties across the entire phantom has been assumed. Nevertheless, BSD-DTI is not limited only to highly homogeneous phantoms. This study describes a procedure which allows to use basically any anisotropic phantom of a precisely defined structure.