Transceive phase mapping using the PLANET method and its application for conductivity mapping in the brain.

PURPOSE: To demonstrate feasibility of transceive phase mapping with the PLANET method and its application for conductivity reconstruction in the brain. METHODS: Accuracy and precision of transceive phase (ϕ± ) estimation with PLANET, an ellipse fitting approach to phase-cycled balanced steady state free precession (bSSFP) data, were assessed with simulations and measurements and compared to standard bSSFP. Measurements were conducted on a homogeneous phantom and in the brain of healthy volunteers at 3 tesla. Conductivity maps were reconstructed with Helmholtz-based electrical properties tomography. In measurements, PLANET was also compared to a reference technique for transceive phase mapping, i.e., spin echo. RESULTS: Accuracy and precision of ϕ± estimated with PLANET depended on the chosen flip angle and TR. PLANET-based ϕ± was less sensitive to perturbations induced by off-resonance effects and partial volume (e.g., white matter + myelin) than bSSFP-based ϕ± . For flip angle = 25° and TR = 4.6 ms, PLANET showed an accuracy comparable to that of reference spin echo but a higher precision than bSSFP and spin echo (factor of 2 and 3, respectively). The acquisition time for PLANET was ~5 min; 2 min faster than spin echo and 8 times slower than bSSFP. However, PLANET simultaneously reconstructed T1 , T2 , B0 maps besides mapping ϕ± . In the phantom, PLANET-based conductivity matched the true value and had the smallest spread of the three methods. In vivo, PLANET-based conductivity was similar to spin echo-based conductivity. CONCLUSION: Provided that appropriate sequence parameters are used, PLANET delivers accurate and precise ϕ± maps, which can be used to reconstruct brain tissue conductivity while simultaneously recovering T1 , T2 , and B0 maps.

On the accuracy and precision of PLANET for multiparametric MRI using phase-cycled bSSFP imaging.

PURPOSE: In this work we demonstrate how sequence parameter settings influence the accuracy and precision in T1 , T2 , and off-resonance maps obtained with the PLANET method for a single-component signal model. In addition, the performance of the method for the particular case of a two-component relaxation model for white matter tissue was assessed. METHODS: Numerical simulations were performed to investigate the influence of sequence parameter settings on the accuracy and precision in the estimated parameters for a single-component model, as well as for a two-component white matter model. Phantom and in vivo experiments were performed for validation. In addition, the effects of Gibbs ringing were investigated. RESULTS: By making a proper choice for sequence parameter settings, accurate and precise parameter estimation can be achieved for a single-component signal model over a wide range of relaxation times at realistic SNR levels. Due to the presence of a second myelin-related signal component in white matter, an underestimation of approximately 30% in T1 and T2 was observed, predicted by simulations and confirmed by measurements. Gibbs ringing artifacts correction improved the precision and accuracy of the parameter estimates. CONCLUSION: For a single-component signal model there is a broad "sweet spot" of sequence parameter combinations for which a high accuracy and precision in the parameter estimates is achieved over a wide range of relaxation times. For a multicomponent signal model, the single-component PLANET reconstruction results in systematic errors in the parameter estimates as expected.

Investigation of the influence of B0 drift on the performance of the PLANET method and an algorithm for drift correction.

PURPOSE: The PLANET method was designed to simultaneously reconstruct maps of T1 and T2 , the off-resonance, the RF phase, and the banding free signal magnitude. The method requires a stationary B0 field over the course of a phase-cycled balanced SSFP acquisition. In this work we investigated the influence of B0 drift on the performance of the PLANET method for single-component and two-component signal models, and we propose a strategy for drift correction. METHODS: The complex phase-cycled balanced SSFP signal was modeled with and without frequency drift. The behavior of the signal influenced by drift was mathematically interpreted as a sum of drift-dependent displacement of the data points along an ellipse and drift-dependent rotation around the origin. The influence of drift on parameter estimates was investigated experimentally on a phantom and on the brain of healthy volunteers and was verified by numerical simulations. A drift correction algorithm was proposed and tested on a phantom and in vivo. RESULTS: Drift can be assumed to be linear over the typical duration of a PLANET acquisition. In a phantom (a single-component signal model), drift induced errors of 4% and 8% in the estimated T1 and T2 values. In the brain, where multiple components are present, drift only had a minor effect. For both single-component and two-component signal models, drift-induced errors were successfully corrected by applying the proposed drift correction algorithm. CONCLUSION: We have demonstrated theoretically and experimentally the sensitivity of the PLANET method to B0 drift and have proposed a drift correction method.

PLANET: An ellipse fitting approach for simultaneous T1 and T2 mapping using phase-cycled balanced steady-state free precession.

PURPOSE: To demonstrate the feasibility of a novel, ellipse fitting approach, named PLANET, for simultaneous estimation of relaxation times T1 and T2 from a single 3D phase-cycled balanced steady-state free precession (bSSFP) sequence. METHODS: A method is presented in which the elliptical signal model is used to describe the phase-cycled bSSFP steady-state signal. The fitting of the model to the acquired data is reformulated into a linear convex problem, which is solved directly by a linear least squares method, specific to ellipses. Subsequently, the relaxation times T1 and T2 , the banding free magnitude, and the off-resonance are calculated from the fitting results. RESULTS: Maps of T1 and T2 , as well as an off-resonance and a banding free magnitude can be simultaneously, quickly, and robustly estimated from a single 3D phase-cycled bSSFP sequence. The feasibility of the method was demonstrated in a phantom and in the brain of healthy volunteers on a clinical MR scanner. The results were in good agreement for the phantom, but a systematic underestimation of T1 was observed in the brain. CONCLUSION: The presented method allows for accurate mapping of relaxation times and off-resonance, and for the reconstruction of banding free magnitude images at realistic signal-to-noise ratios. Magn Reson Med 79:711-722, 2018. © 2017 The Authors Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. on behalf of International Society for Magnetic Resonance in Medicine. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

A multipurpose, adolescent idiopathic scoliosis-specific, short MRI protocol: A feasibility study in volunteers.

INTRODUCTION: Visualization of scoliosis typically requires ionizing radiation (radiography and CT) to visualize bony anatomy. MRI is often additionally performed to screen for neural axis abnormalities. We propose a 14-minutes radiation-free scoliosis-specific MRI protocol, which combines MRI and MRI-based synthetic CT images to visualize soft and osseous structures in one examination. We assess the ability of the protocol to visualize landmarks needed to detect 3D patho-anatomical changes, screen for neural axis abnormalities, and perform surgical planning and navigation. METHODS: 18 adult volunteers were scanned on 1.5 T MR-scanner using 3D T2-weighted and synthetic CT sequences. A predefined checklist of relevant landmarks was used for the parameter assessment by three readers. Parameters included Cobb angles, rotation, torsion, segmental height, area and centroids of Nucleus Pulposus and Intervertebral Disc. Precision, reliability and agreement between the readers measurements were evaluated. RESULTS: 91 % of Likert-based questions scored ≥ 4, indicating moderate to high confidence. Precision of 3D dot positioning was 1.0 mm. Precision of angle measurement was 0.6° (ICC 0.98). Precision of vertebral and IVD height measurements was 0.4 mm (ICC 0.99). Precision of area measurement for NP was 8 mm2 (ICC 0.55) and for IVD 18 mm2 (ICC 0.62) for IVD. Precision of centroid measurement for NP was 1.3 mm (ICC 0.88-0.92) and for IVD 1.1 mm (ICC 0.88-91). CONCLUSIONS: The proposed MRI protocol with synthetic CT reconstructions, has high precision, reliability and agreement between the readers for multiple scoliosis-specific measurements. It can be used to study scoliosis etiopathogenesis and to assess 3D spinal morphology.

Automatic generation of subject-specific finite element models of the spine from magnetic resonance images.

The generation of subject-specific finite element models of the spine is generally a time-consuming process based on computed tomography (CT) images, where scanning exposes subjects to harmful radiation. In this study, a method is presented for the automatic generation of spine finite element models using images from a single magnetic resonance (MR) sequence. The thoracic and lumbar spine of eight adult volunteers was imaged using a 3D multi-echo-gradient-echo sagittal MR sequence. A deep-learning method was used to generate synthetic CT images from the MR images. A pre-trained deep-learning network was used for the automatic segmentation of vertebrae from the synthetic CT images. Another deep-learning network was trained for the automatic segmentation of intervertebral discs from the MR images. The automatic segmentations were validated against manual segmentations for two subjects, one with scoliosis, and another with a spine implant. A template mesh of the spine was registered to the segmentations in three steps using a Bayesian coherent point drift algorithm. First, rigid registration was applied on the complete spine. Second, non-rigid registration was used for the individual discs and vertebrae. Third, the complete spine was non-rigidly registered to the individually registered discs and vertebrae. Comparison of the automatic and manual segmentations led to dice-scores of 0.93-0.96 for all vertebrae and discs. The lowest dice-score was in the disc at the height of the implant where artifacts led to under-segmentation. The mean distance between the morphed meshes and the segmentations was below 1 mm. In conclusion, the presented method can be used to automatically generate accurate subject-specific spine models.

Visualization of gold fiducial markers in the prostate using phase-cycled bSSFP imaging for MRI-only radiotherapy.

In this work, we present a new method for visualization of fiducial markers (FMs) in the prostate for MRI-only radiotherapy with a positive contrast directly at the MR console. The method is based on high bandwidth phase-cycled balanced steady-state free precession (bSSFP) sequence, which is available on many clinical scanners, does not require any additional post-processing or software, and has a higher signal-to-noise (SNR) compared to conventional gradient-echo (GE) imaging. Complex phase-cycled bSSFP data is acquired with different RF phase increment settings such that the manifestation of the artifacts around FMs in the acquired complex images is different for each dynamic acquisition and depends on the RF phase increment used. First, we performed numerical simulations to investigate the complex-valued phase-cycled bSSFP signal in the presence of a gold FM, and to investigate the relation of the true physical location of the FM with the geometrical manifestation of the artifacts. Next, to validate the simulations, we performed phantoms and in vivo studies and compared the experimentally obtained artifacts with those predicted in simulations. The accuracy of the method was assessed by comparing the distances between the FM's centers and the center of mass of FMs system measured using phase-cycled bSSFP MR images and using reference CT (or MRI-only) images. The results show accurate (within 1 mm) matching of FMs localization between CT and MR images on five patients, proving the feasibility of in vivo FMs detection on MR images only. The FMs show a positive contrast with respect to the prostate background on real/imaginary phase-cycled bSSFP images, which was confirmed by simulations. The proposed method facilitates robust FMs visualization with positive contrast directly at the MR console, allowing RT technicians to obtain immediate feedback on the anticipated feasibility of accurate FMs localization while the patient is being scanned.