東京大学 · 医学
Sekino教授の研究室は、神経刺激・診断技術の分野において、磁気を用いた高感度な生体計測技術と、生体適合性の高い有機エレクトロニクスの開発を柱としています。特に、がんのリンパ節マッピングに応用可能な磁性ナノ粒子検出プローブや、脳に高精度で局所的に刺激を届けるためのトランスクラニアル磁気刺激(TMS)の最適化技術が特徴です。また、神経インターフェースや神経イメージング技術との統合を視野に、柔軟で生体適合性に優れた有機デバイスの開発も進めています。
Figures are computed from collected data and may differ slightly.
The newly developed radioisotope-free technique based on magnetic nanoparticle detection using a magnetic probe is a promising method for sentinel lymph node biopsy. In this study, a novel handheld magnetic probe with a permanent magnet and magnetic sensor is developed to detect the sentinel lymph nodes in breast cancer patients. An outstanding feature of the probe is the precise positioning of the sensor at the magnetic null point of the magnet, leading to highly sensitive measurements unaffect
Organic electronic devices implemented on flexible thin films are attracting increased attention for biomedical applications because they possess extraordinary conformity to curved surfaces. A neuronal device equipped with an organic light-emitting diode (OLED), used in combination with animals that are genetically engineered to include a light-gated ion channel, would enable cell type-specific stimulation to neurons as well as conformal contact to brain tissue and peripheral soft tissue. This p
In this study, we investigated dependences of the current distribution in transcranial magnetic stimulation (TMS) on coil current intensity, coil diameter, and coil position, and compared the current distribution with that of electroconvulsive therapy (ECT). The head model consisted of 4-mm finite elements. In the ECT model, a voltage of 100 V was applied between a pair of electrodes place on the tempora. In the TMS model, eddy current distributions were obtained for figure-eight coils with diam
We compared current density distributions in electroconvulsive therapy (ECT) and transcranial magnetic stimulation (TMS) by numerical calculations. The model consisted of an air region and three types of tissues with different conductivities representing the brain, the skull, and the scalp. In the ECT model, electric currents were applied through electrodes with a voltage of 100 V. In the TMS model, a figure-eight coil (6 cm diameter per coil) was placed on the vertex of the head model. An alter
Conductivity tensor images of the rat brain were obtained by a method based on diffusion-weighted magnetic resonance imaging (MRI). Diffusion-weighted images were acquired by a 4.7 T MRI system with motion probing gradients (MPGs) applied in three directions. Conductivities in each MPG direction were calculated from the fast component of the apparent diffusion coefficient and the fraction of the fast component, and two-dimensional conductivity tensor was estimated. Regions of interest (ROIs) wer
This article reviews the evolution and recent developments of transcranial magnetic brain stimulation using figure-eight coils to stimulate localized areas in the human brain. Geometric variations of figure-eight coils and their characteristics are reviewed and discussed for applications in neuroscience and medicine. Recent topics of figure-eight coils, such as focality of figure-eight coils, tradeoff between depth and focality, and approaches for extending depth, are discussed.
Transcranial magnetic stimulation (TMS) is a non-invasive brain stimulation technique that has been clinically applied for neural modulation. Conventional TMS systems are restricted by the trade-off between depth penetration and the focality of the induced electric field. In this study, we integrated the concept of temporal interference (TI) stimulation, which has been demonstrated as a non-invasive deep-brain stimulation method, with magnetic stimulation in a four-coil configuration. The attenu
Conductivity tensor maps of the rat brain were obtained using diffusion magnetic resonance imaging (MRI). Signal attenuations in the cortex and the corpus callosum were measured using the stimulated echo acquisition mode (STEAM) sequence with b factors up to 6000 s/mm(2). Our previously published method was improved to infer 3 x 3 conductivity tensor at the low-frequency limit. The conductivity tensor of the tissue was inferred from the fast component of the diffusion tensor and a fraction of th
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