The Use of Magnetic Resonance Imaging in Radiation Therapy Treatment Simulation and Planning.

Ever since its introduction as a diagnostic imaging tool the potential of magnetic resonance imaging (MRI) in radiation therapy (RT) treatment simulation and planning has been recognized. Recent technical advances have addressed many of the impediments to use of this technology and as a result have resulted in rapid and growing adoption of MRI in RT. The purpose of this article is to provide a broad review of the multiple uses of MR in the RT treatment simulation and planning process, identify several of the most used clinical scenarios in which MR is integral to the simulation and planning process, highlight existing limitations and provide multiple unmet needs thereby highlighting opportunities for the diagnostic MR imaging community to contribute and collaborate with our oncology colleagues. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 5.

Evaluating a radiotherapy deep learning synthetic CT algorithm for PET-MR attenuation correction in the pelvis.

BACKGROUND: Positron emission tomography-magnetic resonance (PET-MR) attenuation correction is challenging because the MR signal does not represent tissue density and conventional MR sequences cannot image bone. A novel zero echo time (ZTE) MR sequence has been previously developed which generates signal from cortical bone with images acquired in 65 s. This has been combined with a deep learning model to generate a synthetic computed tomography (sCT) for MR-only radiotherapy. This study aimed to evaluate this algorithm for PET-MR attenuation correction in the pelvis. METHODS: Ten patients being treated with ano-rectal radiotherapy received a [Formula: see text]F-FDG-PET-MR in the radiotherapy position. Attenuation maps were generated from ZTE-based sCT (sCTAC) and the standard vendor-supplied MRAC. The radiotherapy planning CT scan was rigidly registered and cropped to generate a gold standard attenuation map (CTAC). PET images were reconstructed using each attenuation map and compared for standard uptake value (SUV) measurement, automatic thresholded gross tumour volume (GTV) delineation and GTV metabolic parameter measurement. The last was assessed for clinical equivalence to CTAC using two one-sided paired t tests with a significance level corrected for multiple testing of [Formula: see text]. Equivalence margins of [Formula: see text] were used. RESULTS: Mean whole-image SUV differences were -0.02% (sCTAC) compared to -3.0% (MRAC), with larger differences in the bone regions (-0.5% to -16.3%). There was no difference in thresholded GTVs, with Dice similarity coefficients [Formula: see text]. However, there were larger differences in GTV metabolic parameters. Mean differences to CTAC in [Formula: see text] were [Formula: see text] (± standard error, sCTAC) and [Formula: see text] (MRAC), and [Formula: see text] (sCTAC) and [Formula: see text] (MRAC) in [Formula: see text]. The sCTAC was statistically equivalent to CTAC within a [Formula: see text] equivalence margin for [Formula: see text] and [Formula: see text] ([Formula: see text] and [Formula: see text]), whereas the MRAC was not ([Formula: see text] and [Formula: see text]). CONCLUSION: Attenuation correction using this radiotherapy ZTE-based sCT algorithm was substantially more accurate than current MRAC methods with only a 40 s increase in MR acquisition time. This did not impact tumour delineation but did significantly improve the accuracy of whole-image and tumour SUV measurements, which were clinically equivalent to CTAC. This suggests PET images reconstructed with sCTAC would enable accurate quantitative PET images to be acquired on a PET-MR scanner.

Region of interest focused MRI to synthetic CT translation using regression and segmentation multi-task network.

Objective. In MR-only clinical workflow, replacing CT with MR image is of advantage for workflow efficiency and reduces radiation to the patient. An important step required to eliminate CT scan from the workflow is to generate the information provided by CT via an MR image. In this work, we aim to demonstrate a method to generate accurate synthetic CT (sCT) from an MR image to suit the radiation therapy (RT) treatment planning workflow. We show the feasibility of the method and make way for a broader clinical evaluation.Approach. We present a machine learning method for sCT generation from zero-echo-time (ZTE) MRI aimed at structural and quantitative accuracies of the image, with a particular focus on the accurate bone density value prediction. The misestimation of bone density in the radiation path could lead to unintended dose delivery to the target volume and results in suboptimal treatment outcome. We propose a loss function that favors a spatially sparse bone region in the image. We harness the ability of the multi-task network to produce correlated outputs as a framework to enable localization of region of interest (RoI) via segmentation, emphasize regression of values within RoI and still retain the overall accuracy via global regression. The network is optimized by a composite loss function that combines a dedicated loss from each task.Main results. We have included 54 brain patient images in this study and tested the sCT images against reference CT on a subset of 20 cases. A pilot dose evaluation was performed on 9 of the 20 test cases to demonstrate the viability of the generated sCT in RT planning. The average quantitative metrics produced by the proposed method over the test set were-(a) mean absolute error (MAE) of 70 ± 8.6 HU; (b) peak signal-to-noise ratio (PSNR) of 29.4 ± 2.8 dB; structural similarity metric (SSIM) of 0.95 ± 0.02; and (d) Dice coefficient of the body region of 0.984 ± 0.Significance. We demonstrate that the proposed method generates sCT images that resemble visual characteristics of a real CT image and has a quantitative accuracy that suits RT dose planning application. We compare the dose calculation from the proposed sCT and the real CT in a radiation therapy treatment planning setup and show that sCT based planning falls within 0.5% target dose error. The method presented here with an initial dose evaluation makes an encouraging precursor to a broader clinical evaluation of sCT based RT planning on different anatomical regions.

Comprehensive dose evaluation of a Deep Learning based synthetic Computed Tomography algorithm for pelvic Magnetic Resonance-only radiotherapy.

BACKGROUND AND PURPOSE: Magnetic Resonance (MR)-only radiotherapy enables the use of MR without the uncertainty of MR-Computed Tomography (CT) registration. This requires a synthetic CT (sCT) for dose calculations, which can be facilitated by a novel Zero Echo Time (ZTE) sequence where bones are visible and images are acquired in 65 seconds. This study evaluated the dose calculation accuracy for pelvic sites of a ZTE-based Deep Learning sCT algorithm developed by GE Healthcare. MATERIALS AND METHODS: ZTE and CT images were acquired in 56 pelvic radiotherapy patients in the radiotherapy position. A 2D U-net convolutional neural network was trained using pairs of deformably registered CT and ZTE images from 36 patients. In the remaining 20 patients the dosimetric accuracy of the sCT was assessed using cylindrical dummy Planning Target Volumes (PTVs) positioned at four different central axial locations, as well as the clinical treatment plans (for prostate (n = 10), rectum (n = 4) and anus (n = 6) cancers). The sCT was rigidly and deformably registered, the plan recalculated and the doses compared using mean differences and gamma analysis. RESULTS: Mean dose differences to the PTV D98% were ≤ 0.5% for all dummy PTVs and clinical plans (rigid registration). Mean gamma pass rates at 1%/1 mm were 98.0 ± 0.4% (rigid) and 100.0 ± 0.0% (deformable), 96.5 ± 0.8% and 99.8 ± 0.1%, and 95.4 ± 0.6% and 99.4 ± 0.4% for the clinical prostate, rectum and anus plans respectively. CONCLUSIONS: A ZTE-based sCT algorithm with high dose accuracy throughout the pelvis has been developed. This suggests the algorithm is sufficiently accurate for MR-only radiotherapy for all pelvic sites.

Magnetic Resonance Imaging-Based Delineation of Organs at Risk in the Head and Neck Region.

Purpose: The aim of this article is to establish a comprehensive contouring guideline for treatment planning using only magnetic resonance images through an up-to-date set of organs at risk (OARs), recommended organ boundaries, and relevant suggestions for the magnetic resonance imaging (MRI)-based delineation of OARs in the head and neck (H&N) region. Methods and Materials: After a detailed review of the literature, MRI data were collected from the H&N region of healthy volunteers. OARs were delineated in the axial, coronal, and sagittal planes on T2-weighted sequences. Every contour defined was revised by 4 radiation oncologists and subsequently by 2 independent senior experts (H&N radiation oncologist and radiologist). After revision, the final structures were presented to the consortium partners. Results: A definitive consensus was reached after multi-institutional review. On that basis, we provided a detailed anatomic and functional description and specific MRI characteristics of the OARs. Conclusions: In the era of precision radiation therapy, the need for well-built, straightforward contouring guidelines is on the rise. Precise, uniform, delineation-based, automated OAR segmentation on MRI may lead to increased accuracy in terms of organ boundaries and analysis of dose-dependent sequelae for an adequate definition of normal tissue complication probability.

Zero-TE MRI: principles and applications in the head and neck.

Zero echo-time (ZTE) MRI is a novel imaging technique that utilizes ultrafast readouts to capture signal from short-T2 tissues. Additional sequence advantages include rapid imaging times, silent scanning, and artifact resistance. A robust application of this technology is imaging of cortical bone without the use of ionizing radiation, thus representing a viable alternative to CT for both rapid screening and "one-stop-shop" MRI. Although ZTE is increasingly used in musculoskeletal and body imaging, neuroimaging applications have historically been limited by complex anatomy and pathology. In this article, we review the imaging physics of ZTE including pulse sequence options, practical limitations, and image reconstruction. We then discuss optimization of settings for ZTE bone neuroimaging including acquisition, processing, segmentation, synthetic CT generation, and artifacts. Finally, we examine clinical utility of ZTE in the head and neck with imaging examples including malformations, trauma, tumors, and interventional procedures.

Motion corrected silent ZTE neuroimaging.

PURPOSE: To develop self-navigated motion correction for 3D silent zero echo time (ZTE) based neuroimaging and characterize its performance for different types of head motion. METHODS: The proposed method termed MERLIN (Motion Estimation & Retrospective correction Leveraging Interleaved Navigators) achieves self-navigation by using interleaved 3D phyllotaxis k-space sampling. Low resolution navigator images are reconstructed continuously throughout the ZTE acquisition using a sliding window and co-registered in image space relative to a fixed reference position. Rigid body motion corrections are then applied retrospectively to the k-space trajectory and raw data and reconstructed into a final, high-resolution ZTE image. RESULTS: MERLIN demonstrated successful and consistent motion correction for magnetization prepared ZTE images for a range of different instructed motion paradigms. The acoustic noise response of the self-navigated phyllotaxis trajectory was found to be only slightly above ambient noise levels (<4 dBA). CONCLUSION: Silent ZTE imaging combined with MERLIN addresses two major challenges intrinsic to MRI (i.e., subject motion and acoustic noise) in a synergistic and integrated manner without increase in scan time and thereby forms a versatile and powerful framework for clinical and research MR neuroimaging applications.

AZTEK: Adaptive zero TE k-space trajectories.

PURPOSE: Because of short signal lifetimes and respiratory motion, 3D lung MRI is still challenging today. Zero-TE (ZTE) pulse sequences offer promising solutions as they overcome the issue of short T2∗ . Nevertheless, as they rely on continuous readout gradients, the trajectories they follow in k-space are not adapted to retrospective gating and inferred motion correction. THEORY AND METHODS: We propose AZTEK (adaptive ZTE k-space trajectories), a set of 3D radial trajectories featuring three tuning parameters, to adapt the acquisition to any moving organ while keeping seamless transitions between consecutive spokes. Standard ZTE and AZTEK trajectories were compared for static and moving phantom acquisitions as well as for human thoracic imaging performed on 3 volunteers (1 healthy and 2 patients with lung cancer). RESULTS: For the static phantom, we observe comparable image qualities with standard and AZTEK trajectories. For the moving phantom, spatially coherent undersampling artifacts observed on gated images with the standard trajectory are alleviated with AZTEK. The same improvement in image quality is obtained in human, so details are more delineated in the lung with the use of the adaptive trajectory. CONCLUSION: The AZTEK technique opens the possibility for 3D dynamic ZTE lung imaging with retrospective gating. It enables us to uniformly sample the k-space for any arbitrary respiratory motion gate, while preserving static image quality, improving dynamic image quality and guaranteeing continuous readout gradient transitions between spokes, which makes it appropriate to ZTE.

Three-dimensional magnetic resonance imaging ultrashort echo-time cones for assessing lung density in pediatric patients.

BACKGROUND: MRI of lung parenchyma is challenging because of the rapid decay of signal by susceptibility effects of aerated lung on routine fast spin-echo sequences. OBJECTIVE: To assess lung signal intensity in children on ultrashort echo-time sequences in comparison to a fast spin-echo technique. MATERIALS AND METHODS: We conducted a retrospective study of lung MRI obtained in 30 patients (median age 5 years, range 2 months to 18 years) including 15 with normal lungs and 15 with cystic fibrosis. On a fast spin-echo sequence with radial readout and an ultrashort echo-time sequence, both lungs were segmented and signal intensities were extracted. We compared lung-to-background signal ratios and histogram analysis between the two patient cohorts using non-parametric tests and correlation analysis. RESULTS: On ultrashort echo-time the lung-to-background ratio was age-dependent, ranging from 3.15 to 1.33 with high negative correlation (Rs = -0.86). Signal in posterior dependent portions of the lung was 18% and 11% higher than that of the anterior lung for age groups 0-2 and 2-18 years, respectively. The fast spin-echo sequence showed no variation of signal ratios by age or location, with a median of 0.99 (0.98-1.02). Histograms of ultrashort echo-time slices between controls and children with aggravated cystic fibrosis with mucus plugging and wall thickening exhibited significant discrepancies that differentiated between normal and pathological lungs. CONCLUSION: Signal intensity of lung on ultrashort echo-time is higher than that on fast spin-echo sequences, is age-dependent and shows a gravity-dependent anterior to posterior gradient. This signal variation appears similar to lung density described on CT.

The impact of atlas-based MR attenuation correction on the diagnosis of FDG-PET/MR for Alzheimer's diseases- A simulation study combining multi-center data and ADNI-data.

BACKGROUND: The purpose of this study was to assess the impact of vendor-provided atlas-based MRAC on FDG PET/MR for the evaluation of Alzheimer's disease (AD) by using simulated images. METHODS: We recruited 47 patients, from two institutions, who underwent PET/CT and PET/MR (GE SIGNA) examination for oncological staging. From the PET raw data acquired on PET/MR, two FDG-PET series were generated, using vendor-provided MRAC (atlas-based) and CTAC. The following simulation steps were performed in MNI space: After spatial normalization and smoothing of the PET datasets, we calculated the error map for each patient, PETMRAC/PETCTAC. We multiplied each of these 47 error maps with each of the 203 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases after the identical normalization and smoothing. This resulted in 203*47 = 9541 datasets. To evaluate the probability of AD in each resulting image, a cumulative t-value was calculated automatically using commercially-available software (PMOD PALZ) which has been used in multiple large cohort studies. The diagnostic accuracy for the discrimination of AD and predicting progression from mild cognitive impairment (MCI) to AD were evaluated in simulated images compared with ADNI original images. RESULTS: The accuracy and specificity for the discrimination of AD-patients from normal controls were not substantially impaired, but sensitivity was slightly impaired in 5 out of 47 datasets (original vs. error; 83.2% [CI 75.0%-89.0%], 83.3% [CI 74.2%-89.8%] and 83.1% [CI 75.6%-88.3%] vs. 82.7% [range 80.4-85.0%], 78.5% [range 72.9-83.3%,] and 86.1% [range 81.4-89.8%]). The accuracy, sensitivity and specificity for predicting progression from MCI to AD during 2-year follow-up was not impaired (original vs. error; 62.5% [CI 53.3%-69.3%], 78.8% [CI 65.4%-88.6%] and 54.0% [CI 47.0%-69.1%] vs. 64.8% [range 61.5-66.7%], 75.7% [range 66.7-81.8%,] and 59.0% [range 50.8-63.5%]). The worst 3 error maps show a tendency towards underestimation of PET scores. CONCLUSION: FDG-PET/MR based on atlas-based MR attenuation correction showed similar diagnostic accuracy to the CT-based method for the diagnosis of AD and the prediction of progression of MCI to AD using commercially-available software, although with a minor reduction in sensitivity.

In-phase zero TE musculoskeletal imaging.

PURPOSE: To introduce a new method for in-phase zero TE (ipZTE) musculoskeletal MR imaging. METHODS: ZTE is a 3D radial imaging method, which is sensitive to chemical shift off-resonance signal interference, especially around fat-water tissue interfaces. The ipZTE method addresses this fat-water chemical shift artifact by acquiring each 3D radial spoke at least twice with varying readout gradient amplitude and hence varying effective sampling time. Using k-space-based chemical shift decomposition, the acquired data is then reconstructed into an in-phase ZTE image and an out-of-phase disturbance. RESULTS: The ipZTE method was tested for knee, pelvis, brain, and whole-body. The obtained images demonstrate exceptional soft-tissue uniformity free from out-of-phase disturbances apparent in the original ZTE images. The chemical shift decomposition was found to improve SNR at the cost of reduced image resolution. CONCLUSION: The ipZTE method can be used as an averaging mechanism to eliminate fat-water chemical shift artifacts and improve SNR. The method is expected to improve ZTE-based musculoskeletal imaging and pseudo CT conversion as required for PET/MR attenuation correction and MR-guided radiation therapy planning.

Developing an efficient phase-matched attenuation correction method for quiescent period PET in abdominal PET/MRI.

Respiratory motion causes misalignments between positron emission tomography (PET) and magnetic resonance (MR)-derived attenuation maps (µ-maps) in addition to artifacts on both PET and MR images in simultaneous PET/MRI for organs such as liver that can experience motion of several centimeters. To address this problem, we developed an efficient MR-based attenuation correction (MRAC) method to generate phase-matched µ-maps for quiescent period PET (PETQ) in abdominal PET/MRI. MRAC data was acquired with CIRcular Cartesian UnderSampling (CIRCUS) sampling during 100 s in free-breathing as an accelerated data acquisition strategy for phase-matched MRAC (MRACPM-CIRCUS). For comparison, MRAC data with raster (Default) k-space sampling was also acquired during 100 s in free-breathing (MRACPM-Default), and used to evaluate MRACPM-CIRCUS as well as un-matched MRAC (MRACUM) that was un-gated. We purposefully oversampled the MRACPM data to ensure we had enough information to capture all respiratory phases to make this comparison as robust as possible. The proposed MRACPM-CIRCUS was evaluated in 17 patients with 68Ga-DOTA-TOC PET/MRI exams, suspected of having neuroendocrine tumors or liver metastases. Effects of CIRCUS sampling for accelerating a data acquisition were evaluated by simulating the data acquisition time retrospectively in increments of 5 s. Effects of MRACPM-CIRCUS on PETQ were evaluated using uptake differences in the liver lesions (n = 35), compared to PETQ with MRACPM-Default and MRACUM. A Wilcoxon signed-rank test was performed to compare lesion uptakes between the MRAC methods. MRACPM-CIRCUS showed higher image quality compared to MRACPM-Default for the same acquisition times, demonstrating that a data acquisition time of 30 s was reasonable to achieve phase-matched µ-maps. Lesion update differences between MRACPM-CIRCUS (30 s) versus MRACPM-Default (reference, 100 s) were 0.1% ± 1.4% (range of -2.7% to 3.2%) and not significant (P > .05); while, the differences between MRACUM versus MRACPM-Default were 0.6% ± 11.4% with a large variation (range of -37% to 20%) and significant (P < .05). In conclusion, we demonstrated that a data acquisition of 30 s achieved phase-matched µ-maps when using specialized CIRCUS data sampling and phase-matched µ-maps improved PETQ quantification significantly.

Improving PET/MR brain quantitation with template-enhanced ZTE.

PURPOSE: The impact of MR-based attenuation correction on PET quantitation accuracy is an ongoing cause of concern for advanced brain research with PET/MR. The purpose of this study was to evaluate a new, template-enhanced zero-echo-time attenuation correction method for PET/MR scanners. METHODS: 30 subjects underwent a clinically-indicated 18F-FDG-PET/CT, followed by PET/MR on a GE SIGNA PET/MR. For each patient, a 42-s zero echo time (ZTE) sequence was used to generate two attenuation maps: one with the standard ZTE segmentation-based method; and another with a modification of the method, wherein pre-registered anatomical templates and CT data were used to enhance the segmentation. CT data, was used as gold standard. Reconstructed PET images were qualified visually and quantified in 68 volumes-of-interest using a standardized brain atlas. RESULTS: Attenuation maps were successfully generated in all cases, without manual intervention or parameter tuning. One patient was excluded from the quantitative analysis due to the presence of multiple brain metastases. The PET bias with template-enhanced ZTE attenuation correction was measured to be -0.9% ±â€¯0.9%, compared with -1.4% ±â€¯1.1% with regular ZTE attenuation correction. In terms of absolute bias, the new method yielded 1.1% ±â€¯0.7%, compared with 1.6% ±â€¯0.9% with regular ZTE. Statistically significant bias reduction was obtained in the frontal region (from -2.0% to -1.0%), temporal (from -1.2% to -0.2%), parietal (from -1.9% to -1.1%), occipital (from -2.0% to -1.1%) and insula (from -1.4% to -1.1%). CONCLUSION: These results indicate that the co-registration of pre-recorded anatomical templates to ZTE data is feasible in clinical practice and can be effectively used to improve the performance of segmentation-based attenuation correction.

Zero TE-based pseudo-CT image conversion in the head and its application in PET/MR attenuation correction and MR-guided radiation therapy planning.

PURPOSE: To describe a method for converting Zero TE (ZTE) MR images into X-ray attenuation information in the form of pseudo-CT images and demonstrate its performance for (1) attenuation correction (AC) in PET/MR and (2) dose planning in MR-guided radiation therapy planning (RTP). METHODS: Proton density-weighted ZTE images were acquired as input for MR-based pseudo-CT conversion, providing (1) efficient capture of short-lived bone signals, (2) flat soft-tissue contrast, and (3) fast and robust 3D MR imaging. After bias correction and normalization, the images were segmented into bone, soft-tissue, and air by means of thresholding and morphological refinements. Fixed Hounsfield replacement values were assigned for air (-1000 HU) and soft-tissue (+42 HU), whereas continuous linear mapping was used for bone. RESULTS: The obtained ZTE-derived pseudo-CT images accurately resembled the true CT images (i.e., Dice coefficient for bone overlap of 0.73 ± 0.08 and mean absolute error of 123 ± 25 HU evaluated over the whole head, including errors from residual registration mismatches in the neck and mouth regions). The linear bone mapping accounted for bone density variations. Averaged across five patients, ZTE-based AC demonstrated a PET error of -0.04 ± 1.68% relative to CT-based AC. Similarly, for RTP assessed in eight patients, the absolute dose difference over the target volume was found to be 0.23 ± 0.42%. CONCLUSION: The described method enables MR to pseudo-CT image conversion for the head in an accurate, robust, and fast manner without relying on anatomical prior knowledge. Potential applications include PET/MR-AC, and MR-guided RTP.

Hybrid ZTE/Dixon MR-based attenuation correction for quantitative uptake estimation of pelvic lesions in PET/MRI.

PURPOSE: This study introduces a new hybrid ZTE/Dixon MR-based attenuation correction (MRAC) method including bone density estimation for PET/MRI and quantifies the effects of bone attenuation on metastatic lesion uptake in the pelvis. METHODS: Six patients with pelvic lesions were scanned using fluorodeoxyglucose (18F-FDG) in an integrated time-of-flight (TOF) PET/MRI system. For PET attenuation correction, MR imaging consisted of two-point Dixon and zero echo-time (ZTE) pulse sequences. A continuous-value fat and water pseudoCT was generated from a two-point Dixon MRI. Bone was segmented from the ZTE images and converted to Hounsfield units (HU) using a continuous two-segment piecewise linear model based on ZTE MRI intensity. The HU values were converted to linear attenuation coefficients (LAC) using a bilinear model. The bone voxels of the Dixon-based pseudoCT were replaced by the ZTE-derived bone to produce the hybrid ZTE/Dixon pseudoCT. The three different AC maps (Dixon, hybrid ZTE/Dixon, CTAC) were used to reconstruct PET images using a TOF-ordered subset expectation maximization algorithm with a point-spread function model. Metastatic lesions were separated into two classes, bone lesions and soft tissue lesions, and analyzed. The MRAC methods were compared using a root-mean-squared error (RMSE), where the registered CTAC was taken as ground truth. RESULTS: The RMSE of the maximum standardized uptake values (SUVmax ) is 11.02% and 7.79% for bone (N = 6) and soft tissue lesions (N = 8), respectively, using Dixon MRAC. The RMSE of SUVmax for these lesions is significantly reduced to 3.28% and 3.94% when using the new hybrid ZTE/Dixon MRAC. Additionally, the RMSE for PET SUVs across the entire pelvis and all patients are 8.76% and 4.18%, for the Dixon and hybrid ZTE/Dixon MRAC methods, respectively. CONCLUSION: A hybrid ZTE/Dixon MRAC method was developed and applied to pelvic regions in an integrated TOF PET/MRI, demonstrating improved MRAC. This new method included bone density estimation, through which PET quantification is improved.

Zero TE MR bone imaging in the head.

PURPOSE: To investigate proton density (PD)-weighted zero TE (ZT) imaging for morphological depiction and segmentation of cranial bone structures. METHODS: A rotating ultra-fast imaging sequence (RUFIS) type ZT pulse sequence was developed and optimized for 1) efficient capture of short T2 bone signals and 2) flat PD response for soft-tissues. An inverse logarithmic image scaling (i.e., -log(image)) was used to highlight bone and differentiate it from surrounding soft-tissue and air. Furthermore, a histogram-based bias-correction method was developed for subsequent threshold-based air, soft-tissue, and bone segmentation. RESULTS: PD-weighted ZT imaging in combination with an inverse logarithmic scaling was found to provide excellent depiction of cranial bone structures. In combination with bias correction, also excellent segmentation results were achieved. A two-dimensional histogram analysis demonstrates a strong, approximately linear correlation between inverse log-scaled ZT and low-dose CT for Hounsfield units (HU) between -300 HU and 1,500 HU (corresponding to soft-tissue and bone). CONCLUSIONS: PD-weighted ZT imaging provides robust and efficient depiction of bone structures in the head, with an excellent contrast between air, soft-tissue, and bone. Besides structural bone imaging, the presented method is expected to be of relevance for attenuation correction in positron emission tomography (PET)/MR and MR-based radiation therapy planning.

Flexible, 31-Channel breast coil for enhanced parallel imaging performance at 3T.

PURPOSE: To design, build, and characterize the performance of a novel 3T, 31-channel breast coil. METHODS: A flexible breast coil, accommodating all breast sizes while preserving close to unity filling factors in all configurations, was designed and built. Its performance was compared to the performance of the current state-of-the-art, 16 channel breast coil (Sentinelle coil, Hologic, Bedford, MA, USA), in phantoms and in vivo. RESULTS: Better axilla coverage and lower inter-coil coupling (12% versus 26%, as characterized by the average off-diagonal elements of the noise correlation matrix) was exhibited by our 31-channel coil compared with the 16-channel coil. Breast area signal-to-noise ratio increases of 68% (phantom) and 28% ± 31% (in vivo) were observed when the 31-channel coil was used. For the 31-channel/16-channel arrays, respectively, two-dimensional acceleration factors of left/right × superior/inferior = 4.3 × 2.4 resulted in average g-factors of 1.10/1.68 (in vitro) and 1.28/2.75 (in vivo); acceleration factors of left/right × anterior/posterior = 3.0 × 2.8 resulted in average g-factors of 1.06/1.54 (in vitro) and 1.05/1.12 (in vivo). CONCLUSION: A high performance breast coil was built; its capabilities were demonstrated in phantom and normal volunteer imaging experiments.

Comparison of acquisition schemes for hyperpolarised ¹³C imaging.

The aim of this study was to characterise and compare widely used acquisition strategies for hyperpolarised (13)C imaging. Free induction decay chemical shift imaging (FIDCSI), echo-planar spectroscopic imaging (EPSI), IDEAL spiral chemical shift imaging (ISPCSI) and spiral chemical shift imaging (SPCSI) sequences were designed for two different regimes of spatial resolution. Their characteristics were studied in simulations and in tumour-bearing rats after injection of hyperpolarised [1-(13)C]pyruvate on a clinical 3-T scanner. Two or three different sequences were used on the same rat in random order for direct comparison. The experimentally obtained lactate signal-to-noise ratio (SNR) in the tumour matched the simulations. Differences between the sequences were mainly found in the encoding efficiency, gradient demand and artefact behaviour. Although ISPCSI and SPCSI offer high encoding efficiencies, these non-Cartesian trajectories are more prone than EPSI and FIDCSI to artefacts from various sources. If the encoding efficiency is sufficient for the desired application, EPSI has been proven to be a robust choice. Otherwise, faster spiral acquisition schemes are recommended. The conclusions found in this work can be applied directly to clinical applications.

Future image acquisition trends for PET/MRI.

Hybrid PET/MRI scanners have become commercially available in the past years but are not yet widely distributed. The combination of a state-of-the-art PET with a state-of-the-art MRI scanner provides numerous potential advantages compared with the established PET/CT hybrid systems, namely, increased soft tissue contrast; functional information from MRI such as diffusion, perfusion, and blood oxygenation level-dependent techniques; true multiplanar data acquisition; and reduced radiation exposure. On the contrary, current PET/MRI technology is hampered by several shortcomings compared with PET/CT, the most important issues being how to use MR data for PET attenuation correction and the low sensitivity of MRI for small-scale pulmonary pathologies compared with high-resolution CT. Moreover, the optimal choice for hybrid PET/MRI acquisition protocols needs to be defined providing the highest possible degree of sensitivity and specificity within the constraints of the available measurement time. A multitude of new acquisition strategies of PET and MRI not only offer to overcome current obstacles of hybrid PET/MRI but also provide deeper insights into the pathophysiology of oncological, inflammatory, or degenerative diseases from the combination of molecular and functional imaging techniques.

Anatomic evaluation of 3-dimensional ultrashort-echo-time bone maps for PET/MR attenuation correction.

UNLABELLED: Ultrashort-echo-time (UTE) sequences have been proposed in the past for MR-based attenuation correction of PET data, because of their ability to image cortical bone. In the present work we assessed the limitations of dual-echo UTE imaging for bone segmentation in head and neck imaging. Sequentially acquired MR and PET/CT clinical data were used for this purpose. METHODS: Twenty patients referred for a clinical oncology examination were scanned using a trimodality setup. Among the MR sequences, a dual-echo UTE acquisition of the head was acquired and used to create tissue R2 maps. The different undesired structures present in these maps were identified by an experienced radiologist. Global and local measurements of the overlap between R2-based and CT-based bone masks were computed. RESULTS: UTE R2 maps displayed a nonfunctional relation with CT data. The obtained bone masks showed acceptable overlap with the corresponding CT data, in the case of the skull itself (e.g., 47% mismatch for the parietal region), with decreased performance in the base of the skull and in the neck (e.g., 78% for the maxillary region). Unwanted structures were detected, both anatomic (e.g., sternocleidomastoid, temporal, and masseter muscles) and artifactual (e.g., dental implants and air-tissue interfaces). CONCLUSION: It is indeed possible to estimate the anatomic location of bone tissue using UTE sequences. However, using pure parametric maps for attenuation correction may lead to bias close to certain anatomic structures and areas of high magnetic field inhomogeneity. More sophisticated approaches are necessary to compensate for these effects.