This article describes a worm-like soft robot capable of operating in complicated tubular environments, such as the complex pipeline with different diameters, water, oil, and gas environments, or the clinical application in natural orifice transluminal endoscopic surgery. The robot is completely soft and robust, and consists of one multidegree of freedom (DoF) extension module and two clampers for locomotion and steering. The multi-DoF extension module is able to adjust the heading direction in the three-dimensional space. The clamper has a basic expansion module structure and detachable sucking module structure. The combined clamping principle for sticking to the inner wall can be reconfigurable to adapt the tubes with multiple tubular scales and super elastic materials. For fabrication of the mechanical structure, a low-cost and time-efficient method is proposed in this article. Based on our proposed robot, a series of phantom and application experiments are performed. The results demonstrate that the soft robot can freely bend and elongate with the entire soft body, and pass through tubes with changing diameters or branches, dry tubes, liquid environments, hard surfaces, and even soft deformable tubes. It has the ability to remove a load of >10 times its own weight. In addition, an additional visualization unit, biopsy, and electromagnetic sensor are mounted on the robot tip for the real-time image inspection, manipulation, and robot tracking. The proposed worm-like soft robot is compact, flexible-actuated, and sufficiently safe, as well as extensible. Its ability to move in the complex unstructured environment shows a great potential for search and medical applications.

PurposeTo develop a 3D multitasking multi‐echo (MT‐ME) technique for the comprehensive characterization of liver tissues with 5‐min free‐breathing acquisition; whole‐liver coverage; a spatial resolution of 1.5 × 1.5 × 6 mm3; and simultaneous quantification of T1, water‐specific T1 (T1w), proton density fat fraction (PDFF), and .MethodsSix‐echo bipolar spoiled gradient echo readouts following inversion recovery preparation was performed to generate T1, water/fat, and contrast. MR multitasking was used to reconstruct the MT‐ME images with 3 spatial dimensions: 1 T1 recovery dimension, 1 multi‐echo dimension, and 1 respiratory dimension. A basis function–based approach was developed for T1w quantification, followed by the estimation of and T1‐corrected PDFF. The intrasession repeatability and agreement against references of MT‐ME measurements were tested on a phantom and 15 clinically healthy subjects. In addition, 4 patients with confirmed liver diseases were recruited, and the agreement between MT‐ME measurements and references was assessed.ResultsMT‐ME produced high‐quality, coregistered T1, T1w, PDFF, and maps with good intrasession repeatability and substantial agreement with references on phantom and human studies. The intra‐class coefficients of T1, T1w, PDFF, and from the repeat MT‐ME measurements on clinically healthy subjects were 0.989, 0.990, 0.999, and 0.988, respectively. The intra‐class coefficients of T1, PDFF, and between the MT‐ME and reference measurements were 0.924, 0.987, and 0.975 in healthy subjects and 0.980, 0.999, and 0.998 in patients. The T1w was independent to PDFF (R = −0.029, P = .904).ConclusionThe proposed MT‐ME technique quantifies T1, T1w, PDFF, and simultaneously and is clinically promising for the comprehensive characterization of liver tissue properties.

Purpose To develop a new technique that enables simultaneous quantification of whole‐brain T1, T2, T2∗, as well as susceptibility and synthesis of six contrast‐weighted images in a single 9.1‐minute scan. Methods The technique uses hybrid T2‐prepared inversion‐recovery pulse modules and multi‐echo gradient‐echo readouts to collect k‐space data with various T1, T2, and T2∗ weightings. The underlying image is represented as a six‐dimensional low‐rank tensor consisting of three spatial dimensions and three temporal dimensions corresponding to T1 recovery, T2 decay, and multi‐echo behaviors, respectively. Multiparametric maps were fitted from reconstructed image series. The proposed method was validated on phantoms and healthy volunteers, by comparing quantitative measurements against corresponding reference methods. The feasibility of generating six contrast‐weighted images was also examined. Results High quality, co‐registered T1, T2, and T2∗ susceptibility maps were generated that closely resembled the reference maps. Phantom measurements showed substantial consistency (R2 > 0.98) with the reference measurements. Despite the significant differences of T1 (p < .001), T2 (p = .002), and T2∗ (p = 0.008) between our method and the references for in vivo studies, excellent agreement was achieved with all intraclass correlation coefficients greater than 0.75. No significant difference was found for susceptibility (p = .900). The framework is also capable of synthesizing six contrast‐weighted images. Conclusion The MR Multitasking–based 3D brain mapping of T1, T2, T2∗, and susceptibility agrees well with the reference and is a promising technique for multicontrast and quantitative imaging.