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Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex.

ABSTRACT: Focused ultrasound (FUS) has recently been investigated as a new mode of non-invasive brain stimulation, which offers exquisite spatial resolution and depth control. We report on the elicitation of explicit somatosensory sensations as well as accompanying evoked electroencephalographic (EEG) potentials induced by FUS stimulation of the human somatosensory cortex. As guided by individual-specific neuroimage data, FUS was transcranially delivered to the hand somatosensory cortex among healthy volunteers. The sonication elicited transient tactile sensations on the hand area contralateral to the sonicated hemisphere, with anatomical specificity of up to a finger, while EEG recordings revealed the elicitation of sonication-specific evoked potentials. Retrospective numerical simulation of the acoustic propagation through the skull showed that a threshold of acoustic intensity may exist for successful cortical stimulation. The neurological and neuroradiological assessment before and after the sonication, along with strict safety considerations through the individual-specific estimation of effective acoustic intensity in situ and thermal effects, showed promising initial safety profile; however, equal/more rigorous precautionary procedures are advised for future studies. The transient and localized stimulation of the brain using image-guided transcranial FUS may serve as a novel tool for the non-invasive assessment and modification of region-specific brain function.

SUBMITTER: Lee W

PROVIDER: S-EPMC4348665 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature

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Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex.

Lee Wonhye W Kim Hyungmin H Jung Yujin Y Song In-Uk IU Chung Yong An YA Yoo Seung-Schik SS

Scientific reports 20150304

Focused ultrasound (FUS) has recently been investigated as a new mode of non-invasive brain stimulation, which offers exquisite spatial resolution and depth control. We report on the elicitation of explicit somatosensory sensations as well as accompanying evoked electroencephalographic (EEG) potentials induced by FUS stimulation of the human somatosensory cortex. As guided by individual-specific neuroimage data, FUS was transcranially delivered to the hand somatosensory cortex among healthy volu ...[more]

PMID: 25735418

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Project description:This work explored an elementwise approach to model transcranial MRI-guided focused ultrasound (TcMRgFUS) thermal ablation, a noninvasive approach to neurosurgery. Each element of the phased array transducer was simulated individually and could be simultaneously loaded into computer memory, allowing for rapid (~2.5 s) calculation of the pressure field for different phase offsets used for beam steering and aberration correction. We simulated the pressure distribution for 431 sonications in 32 patients, applied the phase and magnitude values used during treatment, and estimated the resulting temperature rise. We systematically varied the relationship between CT (computerized tomography)-derived skull density and the acoustic attenuation and sound speed to obtain the best agreement between the predictions and MR temperature imaging (MRTI). The optimization was validated with simulations of 396 sonications from 40 additional treatments. After optimization, the predicted and measured heating agreed well (R2: 0.74 patients 1-32; 0.71 patients 33-72). The dimensions and obliquity of the heating in the simulated temperature maps were correlated with the MRTI (R2: 0.62, 0.74, respectively), but the measured heating was more spatially diffuse. The energy needed to achieve ablation varied by an order of magnitude (3.3-36.1 kJ). While this elementwise approach required more computation time up front (the combined simulation matrices were approximately 4.6 times higher than a single large simulation), it could be performed in parallel on a computing cluster. It allows for rapid calculation of the three-dimensional heating at the focus for different phase and magnitude values on the array. We also show how this approach can be used to optimize the relationship between CT-derived skull density and acoustic properties. While the relationships found here need further validation in a larger patient population, these results demonstrate the promise of this approach to model TcMRgFUS.

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.

Project description:PurposeTranscranial focused ultrasound (FUS) is increasingly being explored to modulate neuronal activity. To target neuromodulation, researchers often localize the FUS beam onto the brain region(s) of interest using spatially tracked tools overlaid on pre-acquired images. Here, we quantify the accuracy of optically tracked image-guided FUS with magnetic resonance imaging (MRI) thermometry, evaluate sources of error and demonstrate feasibility of these procedures to target the macaque somatosensory region.MethodsWe developed an optically tracked FUS system capable of projecting the transducer focus onto a pre-acquired MRI volume. To measure the target registration error (TRE), we aimed the transducer focus at a desired target in a phantom under image guidance, heated the target while imaging with MR thermometry and then calculated the TRE as the difference between the targeted and heated locations. Multiple targets were measured using either an unbiased or bias-corrected calibration. We then targeted the macaque S1 brain region, where displacement induced by the acoustic radiation force was measured using MR acoustic radiation force imaging (MR-ARFI).ResultsAll calibration methods enabled registration with TRE on the order of 3 mm. Unbiased calibration resulted in an average TRE of 3.26 mm (min-max: 2.80-4.53 mm), which was not significantly changed by prospective bias correction (TRE of 3.05 mm; 2.06-3.81 mm, p = 0.55). Restricting motion between the transducer and target and increasing the distance between tracked markers reduced the TRE to 2.43 mm (min-max: 0.79-3.88 mm). MR-ARFI images showed qualitatively similar shape and extent as projected beam profiles in a living non-human primate.ConclusionsOur study describes methods for image guidance of FUS neuromodulation and quantifies errors associated with this method in a large animal. The workflow is efficient enough for in vivo use, and we demonstrate transcranial MR-ARFI in vivo in macaques for the first time.

Dataset Information

Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex.

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Image-guided transcranial focused ultrasound stimulates human primary somatosensory cortex.

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