Agar gels were previously proven capable of accurately replicating the acoustical and thermal properties of real tissue and widely used for the construction of tissue-mimicking phantoms (TMPs) for focused ultrasound (FUS) applications. Given the current popularity of magnetic resonance-guided FUS (MRgFUS), we have investigated the MR relaxation times T1 and T2 of different mixtures of agar-based phantoms. Nine TMPs were constructed containing agar as the gelling agent and various concentrations of silicon dioxide and evaporated milk. An agar-based phantom doped with wood powder was also evaluated. A series of MR images were acquired in a 1.5 T scanner for T1 and T2 mapping. T2 was predominantly affected by varying agar concentrations. A trend toward decreasing T1 with an increasing concentration of evaporated milk was observed. The addition of silicon dioxide decreased both relaxation times of pure agar gels.The proposed phantoms have great potential for use with the continuously emerging MRgFUS technology. The MR relaxation times of several body tissues can be mimicked by adjusting the concentration of ingredients, thus enabling more accurate and realistic MRgFUS studies.

Background Robotic‐assisted diagnostic and therapeutic modalities require a highly accurate performance to be certified for clinical application. In this paper, three simple methods for assessing the accuracy of motion of magnetic resonance‐guided focused ultrasound (MRgFUS) robotic systems are presented. Methods The accuracy of motion of a 4 degrees of freedom robotic system intended for preclinical use of MRgFUS was evaluated by calliper‐based and magnetic resonance imaging (MRI) methods, as well as visually by performing multiple ablations on a plastic film. Results The benchtop results confirmed a highly accurate motion in all axes of operation. The spatial positioning errors estimated by MRI evaluation were defined by the size of the imaging pixels. Lesions arrangement in discrete and overlapping patterns confirmed satisfactory alignment of motion trajectories. Conclusions We believe the methods presented here should serve as a standard for evaluating the accuracy of motion of MRgFUS robotic systems.