Utility of zero echo time (ZTE) sequence for assessing bony lesions of skull base and calvarium.

Background: The emergence of zero echo time (ZTE) imaging has transformed bone imaging, overcoming historical limitations in capturing detailed bone structures. By minimizing the time gap between radiofrequency excitation and data acquisition, ZTE generates CT-like images. While ZTE has shown promise in various applications, its potential in assessing skull base and calvarium lesions remains unexplored.

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.

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.

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

. 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.

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.

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.

Attenuation Coefficient Estimation for PET/MRI With Bayesian Deep Learning Pseudo-CT and Maximum-Likelihood Estimation of Activity and Attenuation.

A major remaining challenge for magnetic resonance-based attenuation correction methods (MRAC) is their susceptibility to sources of magnetic resonance imaging (MRI) artifacts (e.g., implants and motion) and uncertainties due to the limitations of MRI contrast (e.

Unsupervised-learning-based method for chest MRI-CT transformation using structure constrained unsupervised generative attention networks.

The integrated positron emission tomography/magnetic resonance imaging (PET/MRI) scanner simultaneously acquires metabolic information via PET and morphological information using MRI. However, attenuation correction, which is necessary for quantitative PET evaluation, is difficult as it requires the generation of attenuation-correction maps from MRI, which has no direct relationship with the gamma-ray attenuation information. MRI-based bone tissue segmentation is potentially available for attenuation correction in relatively rigid and fixed organs such as the head and pelvis regions.

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.

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.

Silent zero TE MR neuroimaging: Current state-of-the-art and future directions.

Magnetic Resonance Imaging (MRI) scanners produce loud acoustic noise originating from vibrational Lorentz forces induced by rapidly changing currents in the magnetic field gradient coils. Using zero echo time (ZTE) MRI pulse sequences, gradient switching can be reduced to a minimum, which enables near silent operation.Besides silent MRI, ZTE offers further interesting characteristics, including a nominal echo time of TE = 0 (thus capturing short-lived signals from MR tissues which are otherwise MR-invisible), 3D radial sampling (providing motion robustness), and ultra-short repetition times (providing fast and efficient scanning).

Revealing the mechanisms behind novel auditory stimuli discrimination: An evaluation of silent functional MRI using looping star.

Looping Star is a near-silent, multi-echo, 3D functional magnetic resonance imaging (fMRI) technique. It reduces acoustic noise by at least 25dBA, with respect to gradient-recalled echo echo-planar imaging (GRE-EPI)-based fMRI. Looping Star has successfully demonstrated sensitivity to the cerebral blood-oxygen-level-dependent (BOLD) response during block design paradigms but has not been applied to event-related auditory perception tasks.

Zero Echo Time MRAC on FDG-PET/MR Maintains Diagnostic Accuracy for Alzheimer's Disease; A Simulation Study Combining ADNI-Data.

Aim: Attenuation correction using zero-echo time (ZTE) - magnetic resonance imaging (MRI) (ZTE-MRAC) has become one of the standard methods for brain-positron emission tomography (PET) on commercial PET/MR scanners. Although the accuracy of the net tracer-uptake quantification based on ZTE-MRAC has been validated, that of the diagnosis for dementia has not yet been clarified, especially in terms of automated statistical analysis. The aim of this study was to clarify the impact of ZTE-MRAC on the diagnosis of Alzheimer's disease (AD) by performing simulation study.

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 . 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.

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.

Silent myelin-weighted magnetic resonance imaging.

 Inhomogeneous Magnetization Transfer (ihMT) is an emerging, uniquely myelin-specific magnetic resonance imaging (MRI) contrast. Current ihMT acquisitions utilise fast Gradient Echo sequences which are among the most acoustically noisy MRI sequences, reducing patient comfort during acquisition. We sought to address this by modifying a near silent MRI sequence to include ihMT contrast.

Silent 3D MR sequence for quantitative and multicontrast T1 and proton density imaging.

This study aims to develop a silent, fast and 3D method for T1 and proton density (PD) mapping, while generating time series of T1-weighted (T1w) images with bias-field correction. Undersampled T1w images at different effective inversion times (TIs) were acquired using the inversion recovery prepared RUFIS sequence with an interleaved k-space trajectory. Unaliased images were reconstructed by constraining the signal evolution to a temporal subspace which was learned from the signal model.

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.

Looping Star fMRI in Cognitive Tasks and Resting State.

Background: Conventional T *-weighted functional magnetic resonance imaging (fMRI) is performed with echo-planar imaging (EPI) sequences that create substantial acoustic noise. The loud acoustic noise not only affects the activation of the auditory cortex, but may also interfere with resting state and task fMRI experiments.

Purpose: To demonstrate the feasibility of a novel, quiet, T *, whole-brain blood oxygenation level-dependent (BOLD)-fMRI method, termed Looping Star, compared to conventional multislice gradient-echo EPI.

Silent T mapping using the variable flip angle method with B correction.

Purpose: To compare the silent rotating ultrafast imaging sequence (RUFIS) to a traditional Cartesian spoiled gradient-echo (SPGR) acquisition scheme for variable flip angle (VFA) mapping.

Methods: A two-point VFA measurement was performed using RUFIS and Cartesian SPGR in a quantitative phantom and healthy volunteers. To correct for errors, a novel silent magnetization prepared map acquisition (SIMBA) was developed, which combined with RUFIS VFA allows for a completely silent mapping protocol.

Attenuation correction using 3D deep convolutional neural network for brain 18F-FDG PET/MR: Comparison with Atlas, ZTE and CT based attenuation correction.

One of the main technical challenges of PET/MRI is to achieve an accurate PET attenuation correction (AC) estimation. In current systems, AC is accomplished by generating an MRI-based surrogate computed tomography (CT) from which AC-maps are derived. Nevertheless, all techniques currently implemented in clinical routine suffer from bias.