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PURPOSE: The study investigates the numerical modelling as well as experimental validation of magnetic susceptibility effects with respect to a 3D linearity phantom used for the quantification of MR image distortions. METHODS: Magnetic field numerical simulations based on finite difference methods were conducted to generate the susceptibility (χ) model of the MRID3D phantom. Experimental data was acquired and analyzed for eight different MR scanners to include a wide range of scanning parameters. Distortion vector fields were generated by applying a harmonic analysis based on finite elements methods. Phantom scans for the same setup but with opposite polarities of the frequency encoding gradient were processed in conjunction with the susceptibility modelling to separately quantify three field components due to gradient non-linearities (GNL), B0 inhomogeneities and χ perturbations. RESULTS: The numerical modelling showed a significant range of χ value of up to 8.23 ppm, with a mean value of 2.9 ppm. The χ perturbations were found to be mostly present at the end plates of the cylindrical phantom design. The simulations also showed that setup rotations of up to 10° introduced only negligible variations in the χ model of less than 0.1 ppm. This allows for a straightforward practical implementation of the modelling as a single lookup table. After correcting for the χ perturbations, the B0 inhomogeneities were derived and found to be in good agreement with either the MR system manufacturer specifications or experimental data available in the literature. CONCLUSIONS: It is possible to accurately model the magnetic susceptibility signature of a 3D linearity device and remove it as a post-processing correction step. This is important as the procedure unlocks the ability of determining both the GNL field and B0 map of the scanner without the need of extra acquisitions or phantoms.

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PURPOSE: Real-time magnetic resonance (MR) guidance is of interest to various groups globally because the superior soft tissue contrast MR images offer over other x-ray-based imaging modalities. Because of the precision required in proton therapy, proton therapy treatments rely heavily on image guidance. Integrating a magnetic resonance imaging (MRI) into a proton therapy treatment is a challenge. The charged particles (protons) used in proton therapy experience magnetic forces when travelling through the MRI magnetic fields. Given that it is desired that proton beams can be delivered with submillimeter accuracy, it is important that all potential sources of beam displacement are well modeled and understood. This study investigated the behavior of monoenergetic proton beams in the presence of a simulated set of realistic three-dimensional (3D) vector magnetic gradient fields required for spatial localization during imaging. This deflecting source has not been previously investigated. METHODS: Three-dimensional magnetic vector fields from a superconducting 0.5 T open bore MRI magnet model (previously developed in-house) and 3D magnetic fields from an in-house gradient coil model were applied to two types of computer simulations. In all simulations, monoenergetic proton pencil beams (from 80 to 250 MeV) were used. The initial directions of proton beams were varied. In all simulations, the orientation of the B0 field coincided with the positive z-axis in the simulation geometry. The first type of simulation is based on an analytic magnetic force equation (analytic simulations) while the second type is a full Monte Carlo (MC) simulation. The analytic simulations were limited to propagating the proton beams in vacuum but could be rapidly calculated in a desktop computer while the MC simulations were calculated in a cluster computer. The proton beam locations and dose profiles at the central plane (z = 0 cm) with or without magnetic fields were extracted and used to quantify the effect of the presence of the different magnetic fields on the proton beam. RESULTS: The analytic simulations agree with MC results within 0.025 mm, thus acting as the verification of MC calculations. The presence of the B0 field caused the beam to follow a helical trajectory which resulted in angular offsets of 4.9o , 3.6o , and 2.8o for the 80, 150, and 250 MeV, respectively. Magnetic field deflections caused by a rapid MRI sequence (bSSFP, with maximum gradient strength of 40 mT/m) show a pattern of distortion which remained spatially invariant in the MR's field of view. For the 80 MeV beam, this pattern shows a maximum ranged in the y direction of 1.5 mm. The presence of the B0 field during the bSSFP simulations adds the same beam rotation to the observed during the B0 only simulations. CONCLUSION: This investigation reveals that time-varying gradient magnetic fields required for image generation can cause a small spread in the proton beams used in the study which are independent of the effects arising from the B0 field. Further, studies where clinical beam kernels were convolved with this spread show that these magnetic fields are expected to have an insignificant impact on the beam's entrance dose.

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The recent interest in the integration of external beam radiotherapy with a magnetic resonance (MR) imaging unit offers the potential for real-time adaptive tumour tracking during radiation treatment. The tracking of large tumours which follow a rapid trajectory may best be served by the generation of a projection image from the perspective of the beam source, or 'beam's eye view' (BEV). This type of image projection represents the path of the radiation beam, thus enabling rapid compensations for target translations, rotations and deformations, as well time-dependent critical structure avoidance. MR units have been traditionally incapable of this type of imaging except through lengthy 3D acquisitions and ray tracing procedures. This work investigates some changes to the traditional MR scanner architecture that would permit the direct acquisition of a BEV image suitable for integration with external beam radiotherapy. Based on the theory presented in this work, a phantom was imaged with nonlinear encoding-gradient field patterns to demonstrate the technique. The phantom was constructed with agarose gel tubes spaced two cm apart at their base and oriented to converge towards an imaginary beam source 100 cm away. A corresponding virtual phantom was also created and subjected to the same encoding technique as in the physical demonstration, allowing the method to be tested without hardware limitations. The experimentally acquired and simulated images indicate the feasibility of the technique, showing a substantial amount of blur reduction in a diverging phantom compared to the conventional imaging geometry, particularly with the nonlinear gradients ideally implemented. The theory is developed to demonstrate that the method can be adapted in a number of different configurations to accommodate all proposed integration schemes for MR units and radiotherapy sources. Depending on the configuration, the implementation of this technique will require between two and four additional nonlinear encoding coils.

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PURPOSE: To investigate the relationship between the k-space sampling patterns used for compressed sensing MR spectroscopic imaging (CS-MRSI) and the modulation transfer function (MTF) of the metabolite maps. This relationship may allow the desired frequency content of the metabolite maps to be quantitatively tailored when designing an undersampling pattern. METHODS: Simulations of a phantom were used to calculate the MTF of Nyquist sampled (NS) 32 × 32 MRSI, and four-times undersampled CS-MRSI reconstructions. The dependence of the CS-MTF on the k-space sampling pattern was evaluated for three sets of k-space sampling patterns generated using different probability distribution functions (PDFs). CS-MTFs were also evaluated for three more sets of patterns generated using a modified algorithm where the sampling ratios are constrained to adhere to PDFs. RESULTS: Strong visual correlation as well as high R2 was found between the MTF of CS-MRSI and the product of the frequency-dependant sampling ratio and the NS 32 × 32 MTF. Also, PDF-constrained sampling patterns led to higher reproducibility of the CS-MTF, and stronger correlations to the above-mentioned product. CONCLUSIONS: The relationship established in this work provides the user with a theoretical solution for the MTF of CS MRSI that is both predictable and customizable to the user's needs.

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PURPOSE: This work examines the subject of contrast-to-noise ratio (CNR), specifically between tumor and tissue background, and its dependence on the MRI field strength, B0. This examination is motivated by the recent interest and developments in MRI/radiotherapy hybrids where real-time imaging can be used to guide treatment beams. The ability to distinguish a tumor from background tissue is of primary importance in this field, and this work seeks to elucidate the complex relationship between the CNR and B0 that is too often assumed to be purely linear. METHODS: Experimentally based models of B0-dependant relaxation for various tumor and normal tissues from the literature were used in conjunction with signal equations for MR sequences suitable for rapid real-time imaging to develop field-dependent predictions for CNR. These CNR models were developed for liver, lung, breast, glioma, and kidney tumors for spoiled gradient-echo, balanced steady-state free precession (bSSFP), and single-shot half-Fourier fast spin echo sequences. RESULTS: Due to the pattern in which the relaxation properties of tissues are found to vary over B0 field (specifically the T1 time), there was always an improved CNR at lower fields compared to linear dependency. Further, in some tumor sites, the CNR at lower fields was found to be comparable to, or sometimes higher than those at higher fields (i.e., bSSFP CNR for glioma, kidney, and liver tumors). CONCLUSIONS: In terms of CNR, lower B0 fields have been shown to perform as well or better than higher fields for some tumor sites due to superior T1 contrast. In other sites this effect was less pronounced, reversing the CNR advantage. This complex relationship between CNR and B0 reveals both low and high magnetic fields as viable options for tumor tracking in MRI/radiotherapy hybrids.

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The magnetic fields of linac-MR systems modify the path of contaminant electrons in photon beams, which alters patient entrance skin dose. Also, the increased SSD of linac-MR systems reduces the maximum achievable dose rate. To accurately quantify the changes in entrance skin dose, the authors use EGSnrc Monte Carlo calculations that incorporate 3D magnetic field of the Alberta 0.5 T longitudinal linac-MR system. The Varian 600C linac head geometry assembled on the MRI components is used in the BEAMnrc simulations for 6 MV and 10 MV beam models and skin doses are calculated at an average depth of 70 µm using DOSXYZnrc. 3D modeling shows that magnetic fringe fields decay rapidly and are small at the linac head. SSDs between 100 and 120 cm result in skin-dose increases of between ~6%-19% and ~1%-9% for the 6 and 10 MV beams, respectively. For 6 MV, skin dose increases from ~10.5% to ~1.5% for field-size increases of 5 × 5 cm(2) to 20 × 20 cm(2). For 10 MV, skin dose increases by ~6% for a 5 × 5 cm(2) field, and decreases by ~1.5% for a 20 × 20 cm(2) field. Furthermore, the proposed reshaped flattening filter increases the dose rate from the current 355 MU min(-1) to 529 MU min(-1) (6 MV) or 604 MU min(-1) (10 MV), while the skin-dose increases by only an additional ~2.6% (all percent increases in skin dose are relative to D max). This study suggests that there is minimal increase in the entrance skin dose and minimal/no decrease in the dose rate of the Alberta longitudinal linac-MR system. The even lower skin dose increase at 10 MV offers further advantages in future designs of linac-MR prototypes.

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PURPOSE: To investigate the modulation transfer function (MTF) behavior of compressed sensing (CS) MR spectroscopic imaging (MRSI) with regard to CS reconstruction weights and the acquired peak signal-to-noise ratio (SNR); which may have an effect on MTF due to the nonlinear nature of the CS reconstruction process. METHODS: A specially designed phantom consisting of wedges arranged in a fan pattern was used to calculate the MTF of the MRSI scans. Arc profiles of the phantom yield a square wave with a spatial frequency inversely proportional to the radius of the profile. The MTF was derived by considering the amplitude ratio of the fundamental frequency between the ideal square wave and the reconstructed output. As compressed sensing relies on nonlinear reconstruction and a minimization algorithm that requires the definition of reconstruction weights, the behavior of the MTF with respect to the choice of reconstruction weights and peak SNR is not intuitive. As such, simulations were used to investigate the response of the MTF to CS reconstruction weights at varying peak SNRs. The resulting optimized reconstruction weight was used to reconstruct an experimental CS-MRSI scan of the phantom and compare the corresponding MTF to those of a fully sampled dataset, and a time-equivalent Nyquist-sampled low-resolution dataset. RESULTS: Simulations showed that MTFs of CS-MRSI datasets varied widely with different reconstruction weights. Moreover, the response of the MTF to peak SNR was not consistent across the range of reconstruction weights. An optimized reconstruction weight was derived from the simulations and used in reconstructing the experimental dataset. The MTF of the experimental CS-MRSI dataset showed improvement over the equivalent Nyquist sampled dataset at the resolution limit of 0.1 MTF, while it suffered from reduced response at low resolutions between 0.4 and 0.8 lp/cm. CONCLUSIONS: The authors have shown that in certain cases small variations in the reconstruction weights yield a measureable effect on the CS reconstructed images, particularly with regard to MTF. Furthermore, it was found that peak SNR affects CS-MRSI MTF especially at higher wavelet reconstruction weights. Accordingly, prior knowledge of the expected peak SNR is essential to optimize the CS reconstruction process. Their phantom-MTF technique provides a quantitative performance measure of MRSI sequences, through which they were able to quantify a loss of 32.4% in spatial resolution for CS-MRSI at 0.1 MTF compared to a loss of 48.6% for the time-equivalent Nyquist-sampled low-resolution scans. They also showed that CS-MRSI suffered decreased low-resolution response as opposed to the equivalent low-resolution datasets.

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PURPOSE: MR image geometric integrity is one of the building blocks of MRI-guided radiotherapy. In particular, tissue magnetic susceptibility-induced effects are patient-dependent and their behavior is difficult to assess and predict. In this study, the authors investigated in detail the characteristics of susceptibility (χ) distortions in the context of MRIgRT, including the case of two common MR-linac system configurations. METHODS: The magnetic field distortions were numerically simulated for several imaging parameters and anatomical sites, i.e., brain, lung, pelvis (with air pockets), and prostate. The simulation process consisted of (a) segmentation of patient CT data into susceptibility relevant anatomical volumes (i.e., soft-tissue, bone and air∕lung), (b) conversion of CT data into susceptibility masks by assigning bulk χ values to the structures defined at (a), (c) numerical computations of the local magnetic fields by using a finite difference algorithm, and (d) generation of the geometric distortion maps from the magnetic field distributions. For each patient anatomy, the distortions were quantified at the interfaces of anatomical structures with significantly different χ values. The analysis was performed for two specific orientations of the external main magnetic field (B(0)) characteristic to the MR-linac systems, specifically along the z-axis for a bore MR scanner and in the (x,y)-plane for a biplanner magnet. The magnetic field local perturbations were reported in ppm. The metrics used to quantify the geometric distortions were the maximum, mean, and range of distortions. The numerical simulation algorithm was validated using phantom data measurements. RESULTS: Susceptibility-induced distortions were determined for both quadratic and patient specific geometries. The numerical simulations showed a good agreement with the experimental data. The measurements were acquired at 1.5 and 3 T and with an encoding gradient varying between 3 and 20 mT∕m by using an annular phantom mimicking the water-air and water-oil χ interfaces. For quadratic geometries, the magnitude of field distortion increased rapidly with the size of the inhomogeneity up to about 10 mm and then tended to plateau. This trend became more evident for materials with a larger Δχ relative to water. The simulations showed only a slight increase in the maximum distortion values when the B(0) orientation was varied with regard to the shape of the χ inhomogeneity. In the case of patient anatomy, the largest distortion values arose at the air-soft-tissue interface. Considering the two MR-linac system configurations and comparing the field distortion values corresponding to all organ structures, the distortions tended to be larger for the biplanar magnet. The authors provide a reference table with ppm values which can be used to easily evaluate the geometric distortions for patient data as a function of B(0) and the strength of the encoding gradient. CONCLUSIONS: The susceptibility distortions were quantified as a function of multiple parameters such as the χ inhomogeneity size and shape, the magnitude of B(0) and the readout gradient, and the orientation of B(0) with respect to the sample geometry. The analysis was performed for several anatomical sites and corresponding to two B(0) orientations as featured by MR-linac systems.

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PURPOSE: In integrated linac-MRI systems, the RF coils are exposed to the linac's pulsed radiation, leading to a measurable radiation induced current (RIC). This work (1) visualizes the RIC in MRI raw data and determines its effect on the MR image signal-to-noise ratio (SNR) (b) examines the effect of linac dose rate on SNR degradations, (c) examines the RIC effect on different MRI sequences, (d) examines the effect of altering the MRI sequence timing on the RIC, and (e) uses a postprocessing method to reduce the RIC signal from the MR raw data. METHODS: MR images were acquired on the linac-MR prototype system using various imaging sequences (gradient echo, spin echo, and bSSFP), dose rates (0, 50, 100, 150, 200, and 250 MU∕min) and repetition times (TR) with the gradient echo sequence. The images were acquired with the radiation beam either directly incident or blocked from the RF coils. The SNR was calculated for each of these scenarios, showing a loss in SNR due to RIC. Finally, a postprocessing method was applied to the image k-space data in order to remove partially the RIC signal and recover some of the lost SNR. RESULTS: The RIC produces visible spikes in the k-space data acquired with the linac's radiation incident on the RF coils. This RIC leads to a loss in imaging SNR that increases with increasing linac dose rate (15%-18% loss at 250 MU∕min). The SNR loss seen with increasing linac dose rate appears to be largely independent of the MR sequence used. Changing the imaging TR had interesting visual effects on the appearance of RIC in k-space due to the timing between the linac's pulsing and the MR sequence, but did not change the SNR loss for a given linac dose rate. The use of a postprocessing algorithm was able to remove much of the RIC noise spikes from the MR image k-space data, resulting in the recovery of a significant portion, up to 81% (Table II), of the lost image SNR. CONCLUSIONS: The presence of RIC in MR RF coils leads to a loss of SNR which is directly related to the linac dose rate. The RIC related loss in SNR is likely to increase for systems that are able to provide larger than 250 MU∕min dose. Some of this SNR loss can be recovered through the use of a postprocessing algorithm, which removes the RIC artefact from the image k-space.

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PURPOSE: This work investigates with simulation the effect of external stray magnetic fields on a recently reported MRI-linac hybrid, which by design will rotate about the patient axis during therapy. During rotation, interactions with magnetic fields from the earth or nearby ferromagnetic structures may cause unacceptable field distortions in the imaging field of view. Optimal approaches for passive shimming implementation, the degree and significance of residual distortion, and an analysis of the active shimming requirements for further correction are examined. METHODS: Finite element simulations were implemented on two representative types of biplanar magnet designs. Each of these magnet designs, consisting of a 0.2 T four-post and a 0.5 T C-type unit, was simulated with and without an external field on the order of the earth's field (0.5 G) over a range of rotated positions. Through subtraction, the field distribution resulting from the external field alone could be determined. These measured distributions were decomposed into spherical harmonic components, which were then used to investigate the effect of their selective removal to simulate the effects of passive and active shimming. Residual fields after different levels of shim treatment were measured and assessed in terms of their imaging consequence. RESULTS: For both magnet types, the overall success of a passive shim implementation was highly dependent on the orientation for which it was based. If this orientation was chosen incorrectly, the passive shim would correct for the induced fields at that location, but the overall maximal distortion at other locations was exacerbated by up to a factor of two. The choice of passive shim orientation with the least negative consequence was found to be that where the magnet B(0) axis and transaxial component of the external field were aligned. Residual fields after passive shimming and frequency offset were found to be low in the simulated scenarios, contributing to <1 mm of distortion for most standard imaging sequences (based on a 0.5 G external field). However, extremely rapid single-shot sequences could be distorted by these residual fields to well over 5 mm. These residuals when analyzed were found to correspond primarily to second-order spherical harmonic terms. One term in particular was found to account for the vast majority of these residual fields, defined by the product of the two axes perpendicular to the axis of rotation. The implementation of this term would allow the resulting geometric distortion to fall to the order of 1 mm, even for single-shot sequences. CONCLUSIONS: After appropriate passive shimming, the imaging distortion due to an external field of 0.5 G was found to be important only in rapid single-shot sequences, which are especially susceptible to field inhomogeneity. Should it be desirable to use these sequences for real-time tracking, made conceivable due to the lower susceptibility concerns at low field, these residual fields should be addressed. The ability to use only one second-order term for this correction will reduce the cost impact of this decision.

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Compressed Sensing MRSI (CS-MRSI) offers the ability to accelerate MRSI sequences while suffering minimal artifacts compared to conventional fast MRSI techniques. CS-MRSI exploits the inherent sparsity of MRSI images and incoherent artifacts of pseudo-random sub-Nyquist sampling of k-space combined with non-linear reconstruction to produces MRSI images. CS-MRSI can be used as an acceleration tool to decrease the scan time while maintaining acceptable spatial definition or to enable the acquisition of higher resolution scans while minimizing the associated time penalty. In this work we adopt the compressed sensing technique to accelerate a clinically relevant 2-D point resolved spectroscopy sequence. However, the process of weighing the cost and benefit of applying such a fast imaging technique is complicated due to the unique non-linear nature of the reconstruction process and has largely relied on qualitative assessments. Moreover, pseudo-random sub-Nyquist sampling of k-space can have unwanted effects on the modulation transfer function. In this work we set out to quantify the loss in image quality associated with CS-MRSI. We used simulations of a phantom based method to investigate the MTF behaviour of CS-MRSI with regard to different k-space sampling patterns. As expected, the k-space sampling patterns tested were found to have a direct effect on the MTFs. Moreover, limiting the deviation of the resulting k-space sampling pattern from the prescribed probability distribution function had a positive effect on the MTF overall. Not only was low-resolution response improved, but we also noticed an improvement of ∼ 26% in resolution at 0.1 MTF.

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PURPOSE: To quantitatively evaluate a lung tumour autocontouring algorithm using in-vivo lung cancer patient MR images with varying contrast to noise ratios (CNR) simulating images acquired at various MR field strengths. METHODS: A non small cell lung cancer patient with posterior lung tumour is imaged (sagittal plane) in a 3T MRI using a dynamic bSSFP sequence (FOV: 40×40cm2 , voxel size: 3.1×3.1×20mm3 , TE = 1.1ms. TR = 2.2ms, 275ms per image) under free breathing for approximately 3 minutes (650 images). Gaussian random noise is added to the 3T images to approximately simulate the equivalent CNR in images acquired at 1.5T, 1.0T, 0.5T, 0.3T and 0.2T. The moving tumour in all 3T images is contoured by a physician for reference. The first 20 of these manual contours are used for the parameters optimization of auto-contouring algorithm. The automatic contours from the remaining images are quantitatively compared with the physician's contours using the centroid's displacement and the Dice's coefficient (DC). RESULTS: The oncologist's contours of the 3T images show a maximum S-I motion of 26mm. Compared to the oncologist's contours, automatic contours have an average centroid displacement of 1.37mm, and an average DC of 0.881. The autocontouring algorithm's performance with images in the range of 1.5T to 0.5T equivalent CNRs is similar to that of the 3T data. However, for the lowest CNR datasets (0.2, 0.3T) an increase in centroid displacement and decrease in DC is observed, with mean displacements of 1.56mm, 1.71mm and DCs of 0.870, 0.836 for the 0.3T and 0.2T dataset, respectivelyConclusions: With in-vivo MR images, the autocontouring algorithm generated lung tumour contours similar to ones drawn by a physician (DC 〉 0.83). In this patient, additional CNR from 〉0.5T MRIs does not provide statistically significant improvement in the accuracy of our autocontouring software. E.Yip is supported by the Canadian Institutes of Health Research as well as Alberta Innovates - Health Solutions.

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PURPOSE: One of the recently published concepts that combine the soft-tissue imaging capabilities of MRI with external beam radiotherapy involves the rigid coupling of a linac with a rotating biplanar low-field MR imaging system. While such a system would prevent possible image distortion resulting from relative motion between the magnet and the linac, the rotation of the magnet around the patient can itself introduce possibilities for image distortion that need to be addressed. While there are straightforward techniques in the literature for correcting distortions from gradient nonlinearities and nonuniform magnetic fields during image reconstruction, the correction of distortions related to tissue magnetic susceptibility is more complex. This work investigates the extent of this latter distortion type under the regime of a rotating magnetic field. METHODS: CT images covering patient anatomy in the head, lung, and male pelvic regions were obtained and segmented into components of air, bone, and soft tissue. Each of these three components was assigned bulk magnetic susceptibility values in accordance with those found in the literature. A finite-difference algorithm was then implemented to solve for magnetic field distortion maps should the anatomies be placed in the uniform polarizing field of an MR system. The algorithm was repeated multiple times as the polarizing field was rotated axially about the virtual patient in 15 degrees increments. In this way, a map of maximum distortion, and the range of distortion as the magnetic field is rotated about each anatomical region could be determined. The consequence of these susceptibility distortions in terms of geometric signal shift was calculated for 0.2 T, as well as another low-field system (0.5 T), and a higher field 1.5 T system for comparison, using the assumption of a frequency encoding gradient strength of 5 mT/m. RESULTS: At 0.2 T, the susceptibility-related distortion was limited to less than 0.5 mm given an encoding gradient strength of 5 mT/m or higher. To maintain this same level of geometric accuracy, the 0.5 T system would require a moderately higher minimum gradient strength of 11 mT/m, and at a typical MR field strength of 1.5 T this minimum gradient strength would increase to 33 mT/m. The influence of magnetic susceptibility on mean frequency shift as the field orientation was rotated was also investigated and found to account for less than half a millimeter at 1.5 T, and negligible for low-field systems. CONCLUSIONS: A study of three sites (head, lung, and prostate) that are vulnerable to magnetic susceptibility-related distortions were studied, and showed that in the context of a rotating polarizing magnet, low-field systems can maintain geometric accuracy of 0.5 mm with at most moderate limitations on sequence parameters. This conclusion will likely apply only to endogenous tissues, as implanted materials such as titanium can create field distortions much in excess of what may normally be induced in the body. Items containing such materials (hip prostheses, for example) will require individual scrutiny.

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Postimplant evaluation of prostate brachytherapy using magnetic resonance imaging (MRI) at 1.5 T has met with some difficulties due to the uncertainty associated with seed localization despite the excellent anatomical delineation this imaging modality can achieve. Seeds in vascularized regions or outside the prostate, where signal heterogeneity or drop off can obscure their position, can be difficult to identify. The increase in SNR available at 3.0 T offers the potential to improve these issues with visualization. However, before moving directly to in vivo studies, it is important to investigate the effects of artifact size on the ability to localize multiple seeds in close proximity. These artifacts are of extra concern at higher field because of the increased induced field distortions surrounding the seeds. A single prostate brachytherapy seed (IMC6711, OncoSeed) and arrays of seed pairs were suspended in a porcine gel medium and imaged on 1.5 and 3 T MRI scanners for comparison. Two basic acquisition techniques utilized in a wide array of clinical sequences [spin-echo based and gradient-echo (GE) based] were investigated for the types of artifacts they produce, and their dependence on field. Analysis of the resulting voids was performed to determine the relative size of seeds as seen on the images, as well as the ability to distinguish seeds at close proximity. The seed voids at 3 T were only slightly larger than those obtained at 1.5 T (0.5 mm longer and wider) when using a spin-echo type sequence. For this work, the authors used a proton density fast spin-echo (FSE) sequence. These results are promising for the use of 3 T imaging for postimplant evaluation since the SNR will increase by roughly a factor of 2 with only a limited corresponding increase in artifact size. The minimum separation of the seeds to be completely distinguished using void analysis increased from between 1.5 and 3 mm to between 3 and 4.5 mm when going from 1.5 to 3 T FSE imaging. The minimum separation of the seeds for GE at the demonstration TE of 11 ms was found to be between 3 and 4.5 mm for 1.5 T and between 4.5 and 6 mm for 3 T. These GE artifact dimensions will scale down with TE and, as this happens, approach the dimensions of the FSE artifacts given above.

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Quantifying the relative levels of Choline (Cho) to N-Acetylaspartate (NAA) has been the method of choice by many groups as a mean to biologically identify tumors in the brain. Mcknight et al. have introduced an automatic technique for delineating tumors biologically using MRSI. A statistical model is used to separate tumors from normal tissue based on the relative concentrations of Choline and NAA in both tissue types; that method is commonly referred to as the Choline-to-NAA Index (CNI). In their work, it is assumed that the variation in the relative levels of Cho to NAA in normal brain is unnoticeable to within 2 standard deviations of the mean. However, developments in MRSI sequences have enabled the detectablity of more variations within the relative levels of Cho to NAA in normal tissue. With the uncertainty in the Cho to NAA levels of normal tissue increasing, it is essential to modify the CNI method to improve its specificity. This work introduces a modification to the CNI method developed by McKnight et al. that would address such increase in uncertainty. Instead of relying on an arbitrary CNI value of 2 to define the tumor boundaries, our method defines a high certainty tumor volume, surrounded by a region of uncertainty. Then based on their proximity to high certainty tumor regions, the voxels in the uncertainty region are segmented to either tumor or normal tissue. Preliminary results suggest that the proposed modified method decreases the number of false positive resulting from the original CNI method.

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MR images provide excellent diagnostic information; however, their treatment planning utility is limited due to geometric uncertainties from both system and patient related sources. Despite this concern, interest in developing MR-based treatment planning protocols is on the rise because of the ease with which clinically relevant structures can be identified in MR. Here we present our systematic approach to quantifying both machine (gradient non-linearity and B0 inhomogeneity) and patient (susceptibility and chemical shift) distortions. Gradient non-linearities were previously measured using a 3D grid phantom while the remaining types of distortion were measured using a double gradient echo scan to obtain a B0 distortion map specific to each object/patient. Distortion measurement and correction were validated on phantoms and then implemented on a volunteer. B0 inhomogeneity and susceptibility distortions were simulated by offsetting the x2 -y2 shims; maximum absolute distortion was reduced from 5.4 mm to 1.0 mm and mean (± standard deviation) was reduced from 1.7 ± 1.4 mm to 0.4 ± 0.2 mm. Chemical shift distortion was qualitatively evaluated using a phantom containing fat and water inserts; displacement of the fat signal was much improved following distortion correction. Intensity correction was validated using a uniformity phantom and undistorted image profiles were compared to distorted image profiles and to profiles corrected for geometric and geometric/intensity distortion; the need for intensity correction was clearly demonstrated. Once all types of distortion correction were validated on phantoms, the technique was implemented on a volunteer brain image. Both GE and multi-shot EPI images were corrected.

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At Cross Cancer Institute, we are investigating a novel MRI-linac system consisting of a bi-planar 0.2 T permanent magnet coupled with a 6 MV Linac. The system can freely revolve axially around the patient to deliver dose from any desired angle. For such a system, the radiation treatment planning procedure is expected to rely on the MR images only, i.e. MRI Simulation. Replacing the current CT/CT+MRI-based RTP procedure with MRI Simulation will eliminate the need for the planning CT scanning sessions (no additional x-ray exposure) and consequently the image fusion between MRI and planning CT. In this work, we propose a comprehensive MRI-based RTP procedure for an MRI-Linac system. Specifically, the method consists of a) data acquisition, b) analysis and correction of image artifacts caused by the scanner-related and patient-induced distortions, c) segmentation of organ structures relevant to dosimetric calculations (e.g. soft tissue, bone, air), d) conversion of MR images into CT-like images by assigning bulk electron density values to organ contours defined at step c), e) dose calculations in external magnetic field, and f) plan evaluation. Monte Carlo simulations were performed to determine the linac-MRI scanner's magnetic field induced effects on the dose deposited patterns using patient data. Specifically, we investigated the dosimetric differences between the corresponding MRI-based RT plans simulated at zero and 0.2 T. We found that the maximum percent differences for brain studies were within 4%. Most of these differences occurred at the inferior field edge and superficially at beam exits.

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Magnetic distortions surrounding a typical brachytherapy seed (IMC6711, OncoSeed) within a clinical magnetic resonance imager were modeled for a number of different seed orientations with respect to the main magnetic field. From these distortion maps, simulated images were produced. The simulated images were then compared to images experimentally acquired using a spin echo technique on a Philips 1.5 T magnetic resonance imaging scanner. The modeled images were found to conform very well to those acquired experimentally, thus allowing one to establish where the seed is positioned within the complex image distortion patterns. The artifact patterns were dependent on the orientation of the seed with the main magnetic field, as well as the direction of the read encode gradient. While all imaging schemes which employ a unidirectional linear read encode trajectory should produce the artifacts modeled in this article, sequences other than spin echo may produce additional artifacts. Gradient echo and steady-state free precession imaging techniques were also performed on the seed for comparison.

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To describe and evaluate a novel perfusion system developed to maintain excised tissue in a flowing, oxygenated bathing solution during acquisition of nuclear magnetic resonance (NMR) data, and in addition allow precise data to be acquired continuously while altering the composition of the bathing solution surrounding the tissue. A chamber to house the tissue sample was constructed of interlocking sections of polyethylene tubing, and had approximate internal dimensions of 4 mm in diameter and 4 mm in height. Temperature-controlled, physiologically appropriate buffer solution was pumped via an infusion pump through the chamber, entering and exiting by way of small openings on either end. Immediately surrounding the polyethylene chamber was a tight-fitting four-loop solenoid RF coil. Measured proton NMR parameters were found to be fairly insensitive to the flow rate of the buffer if this coil was used only for reception and a larger-volume transmit-only coil was used for excitation. Temperature control of the sample was successfully implemented between 25 and 40 degrees C. The perfusion system was found to be resistant to the effects of flow rate, as well as a useful tool for the administration of drugs or agents to the tissue. Changes in buffer composition could be performed on the fly without the need to reposition the sample each time a change was made. This avoidance of repositioning was found to yield a fivefold improvement in the precision of T(2) spectral parameters (using frog sciatic nerve as a sample).

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