Dataset Information

Current and emerging brain applications of MR-guided focused ultrasound.

ABSTRACT: MRI guided focused ultrasound is an emerging technique that uses acoustic energy to noninvasively treat intracranial disorders. At high frequencies, it can be used to raise tissue temperatures and ablate discrete brain targets with sub-millimeter accuracy. This application is currently under investigation for a broad range of clinical applications, including brain tumors, movement disorders, and psychiatric conditions. At low frequencies MRI guided focused ultrasound can be used to modulate neuronal activity and in conjunction with injected microbubbles, can open the blood-brain barrier to enhance the delivery of therapeutic compounds. The last decade has seen dramatic advances in the science of MRI guided focused ultrasound, helping elucidate both its mechanisms and potential in pre-clinical models, and its translational promise across myriad clinical applications. This review provides an update of current and emerging MRI guided focused ultrasound applications for intracranial disorders and describes future directions and challenges for the field.

SUBMITTER: Meng Y

PROVIDER: S-EPMC5629772 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Current and emerging brain applications of MR-guided focused ultrasound.

Meng Ying Y Suppiah Suganth S Mithani Karim K Solomon Benjamin B Schwartz Michael L ML Lipsman Nir N

Journal of therapeutic ultrasound 20171005

MRI guided focused ultrasound is an emerging technique that uses acoustic energy to noninvasively treat intracranial disorders. At high frequencies, it can be used to raise tissue temperatures and ablate discrete brain targets with sub-millimeter accuracy. This application is currently under investigation for a broad range of clinical applications, including brain tumors, movement disorders, and psychiatric conditions. At low frequencies MRI guided focused ultrasound can be used to modulate neur ...[more]

PMID: 29034095

Similar Datasets

Project description:IntroductionMagnetic-resonance-guided focused ultrasound (MRgFUS) thalamotomy uses multiple converging high-energy ultrasonic beams to produce thermal lesions in the thalamus. Early postoperative MR imaging demonstrates the location and extent of the lesion, but there is no consensus on the utility or frequency of postoperative imaging. We aimed to evaluate the evolution of MRgFUS lesions and describe the incidence, predictors, and clinical effects of lesion persistence in a large patient cohort.MethodsA total of 215 unilateral MRgFUS thalamotomy procedures for essential tremor (ET) by a single surgeon were retrospectively analyzed. All patients had MR imaging 1 day postoperatively; 106 had imaging at 3 months and 32 had imaging at 1 year. Thin cut (2 mm) axial and coronal T2-weighted MRIs at these timepoints were analyzed visually on a binary scale for lesion presence and when visible, lesion volumes were measured. SWI and DWI sequences were also analyzed when available. Clinical outcomes including tremor scores and side effects were recorded at these same time points. We analyzed if patient characteristics (age, skull density ratio), preoperative tremor score, and sonication parameters influenced lesion evolution and if imaging characteristics correlated with clinical outcomes.ResultsVisible lesions were present in all patients 1 day post- MRgFUS and measured 307.4 ± 128.7 mm3. At 3 months, residual lesions (excluding patients where lesions were not visible) were 83.6% smaller and detectable in only 54.7% of patients (n = 58). At 1 year, residual lesions were detected in 50.0% of patients (n = 16) and were 90.7% smaller than 24 h and 46.5% smaller than 3 months. Lesions were more frequently visible on SWI (100%, n = 17), DWI (n = 38, 97.4%) and ADC (n = 36, 92.3%). At 3 months, fewer treatment sonications, higher maximum power, and greater distance between individual sonications led to larger lesion volumes. Volume at 24 h did not predict if a lesion was visible later. Lesion visibility at 3 months predicted sensory side effects but was not correlated with tremor outcomes.DiscussionOverall, lesions are visible on T2-weighted MRI in about half of patients at both 3 months and 1 year post-MRgFUS thalamotomy. Certain sonication parameters significantly predicted persistent volume, but residual lesions did not correlate with tremor outcomes.

Project description:Background and purposeTranscranial MR imaging-guided focused ultrasound is a promising novel technique to treat multiple disorders and diseases. Planning for transcranial MR imaging-guided focused ultrasound requires both a CT scan for skull density estimation and treatment-planning simulation and an MR imaging for target identification. It is desirable to simplify the clinical workflow of transcranial MR imaging-guided focused ultrasound treatment planning. The purpose of this study was to examine the feasibility of deep learning techniques to convert MR imaging ultrashort TE images directly to synthetic CT of the skull images for use in transcranial MR imaging-guided focused ultrasound treatment planning.Materials and methodsThe U-Net neural network was trained and tested on data obtained from 41 subjects (mean age, 66.4 ± 11.0 years; 15 women). The derived neural network model was evaluated using a k-fold cross-validation method. Derived acoustic properties were verified by comparing the whole skull-density ratio from deep learning synthesized CT of the skull with the reference CT of the skull. In addition, acoustic and temperature simulations were performed using the deep learning CT to predict the target temperature rise during transcranial MR imaging-guided focused ultrasound.ResultsThe derived deep learning model generates synthetic CT of the skull images that are highly comparable with the true CT of the skull images. Their intensities in Hounsfield units have a spatial correlation coefficient of 0.80 ± 0.08, a mean absolute error of 104.57 ± 21.33 HU, and a subject-wise correlation coefficient of 0.91. Furthermore, deep learning CT of the skull is reliable in the skull-density ratio estimation (r = 0.96). A simulation study showed that both the peak target temperatures and temperature distribution from deep learning CT are comparable with those of the reference CT.ConclusionsThe deep learning method can be used to simplify workflow associated with transcranial MR imaging-guided focused ultrasound.

Dataset Information

Current and emerging brain applications of MR-guided focused ultrasound.

Publications

Current and emerging brain applications of MR-guided focused ultrasound.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets