The aim of this project is to explore how children with physical disabilities could use a toy robot system for autonomous playing. Children with physical disabilities have difficulties interacting with the material environment and they have fewer pos

Recently, 3D printing has been widely used to fabricate medical imaging phantoms. So far, various rigid 3D printable materials have been investigated for their radiological properties and efficiency in imaging phantom fabrication. However, flexible, soft tissue materials are also needed for imaging phantoms for simulating several clinical scenarios where anatomical deformations is important. Recently, various additive manufacturing technologies have been used to produce anatomical models based on extrusion techniques that allow the fabrication of soft tissue materials. To date, there is no systematic study in the literature investigating the radiological properties of silicone rubber materials/fluids for imaging phantoms fabricated directly by extrusion using 3D printing techniques. The aim of this study was to investigate the radiological properties of 3D printed phantoms made of silicone in CT imaging. To achieve this goal, the radiodensity as described as Hounsfield Units (HUs) of several samples composed of three different silicone printing materials were evaluated by changing the infill density to adjust their radiological properties. A comparison of HU values with a Gammex Tissue Characterization Phantom was performed. In addition, a reproducibility analysis was performed by creating several replicas for specific infill densities. A scaled down anatomical model derived from an abdominal CT was also fabricated and the resulting HU values were evaluated. For the three different silicone materials, a spectrum ranging from -639 to +780 HU was obtained on CT at a scan setting of 120 kVp. In addition, using different infill densities, the printed materials were able to achieve a similar radiodensity range as obtained in different tissue-equivalent inserts in the Gammex phantom (238 HU to -673 HU). The reproducibility results showed good agreement between the HU values of the replicas compared to the original samples, confirming the reproducibility of the printed materials. A good agreement was observed between the HU target values in abdominal CT and the HU values of the 3D-printed anatomical phantom in all tissues.

Objective: This study aimed to prospectively assess the visibility of interstitial needles on transrectal ultrasound (TRUS) in cervical cancer brachytherapy patients and evaluate its impact on implant and treatment plan quality. Material and methods: TRUS was utilized during and after applicator insertion, with each needle’s visibility documented through axial images at the high-risk clinical target volume’s largest diameter. Needle visibility on TRUS was scored from 0 (no visibility) to 3 (excellent discrimination, margins distinct). Quantitative assessment involved measuring the distance between tandem and each needle on TRUS and comparing it to respective magnetic resonance imaging (MRI) measurements. Expected treatment plan quality based on TRUS images was rated from 1 (meeting all planning objectives) to 4 (violation of High-risk clinical target volume (CTV_HR) and/or organ at risk (OAR) hard constraints) and compared to the final MRI-based plan. Results: Analysis included 23 patients with local FIGO stage IB2-IVA, comprising 41 applications with a total of 230 needles. A high visibility rate of 99.1% (228/230 needles) was observed, with a mean visibility score of 2.5 ± 0.7 for visible needles. The maximum and mean difference between MRI and TRUS measurements were 8 mm and –0.1 ± 1.6 mm, respectively, with > 3 mm discrepancies in 3.5% of needles. Expected treatment plan quality after TRUS assessment exactly aligned with the final MRI plan in 28 out of 41 applications with only minor deviations in all other cases. Conclusion: Real-time TRUS-guided interstitial needle placement yielded high-quality implants, thanks to excellent needle visibility during insertion. This supports the potential of TRUS-guided brachytherapy as a promising modality for gynecological indications.

Silicone rubbers are relatively new in additive manufacturing, with only a few commercial printing services and reports on custom-built printers available. Publications and standards on calibration and accuracy assessment are especially lacking. In this study, the printhead calibration process of a custom-built silicone printer is explained, and a set of test objects is proposed and evaluated. The printer in use is based on an open-source filament printer, capable of multi-material printing with silicone rubbers and thermoplastic polymers. Three different high-viscosity single-component liquid silicone rubbers and one polylactic acid thermoplastic filament were used as printing materials. First, the calibration process of the silicone printhead was conducted, and the dependency of the dosing accuracy on silicone viscosity, nozzle diameter and extrusion speed was evaluated. Second, various test specimens were proposed and printed to characterize the accuracy and geometric limitations of this printer. These test parts contained features such as thin walls, slender towers, small holes and slots, unsupported overhangs and bridges. It was concluded that silicone viscosity strongly affects geometric inaccuracies. Design recommendations were deducted from the results, advising for wall thicknesses above 1 mm, slenderness ratios below 2, bridging lengths below 2 mm and unsupported overhang angles below 30°.

Precise micrometer-scale tissue manipulation is essential for successful microsurgery. Despite advancements in intraoperative sensing and instrument tracking, providing accurate real-time feedback on instrument positions relative to critical tissue structures remains challenging. This research aims to reliably reconstruct fine-grained anatomical surfaces intraoperatively using a smart instrument with fiber-based distance sensing. First, instrument-integrated optical coherence tomography sensor readings are integrated with instrument tracking to reconstruct accurate surface point clouds. Subsequently, radial basis functions, ordinary Kriging, and B-splines are utilized for surface modeling, employing tailored basis functions and smoothing parameters. The proposed methods are validated in the context of vitreoretinal surgery through simulations and with ex vivo studies involving porcine and human cadaver eyes. In simulations, radial basis function interpolation demonstrates the highest robustness across varying noise levels and eye shapes. In ex vivo studies, ordinary Kriging outperformed, yielding root mean square errors of 14.7 μm for the porcine eye and 38.1 μm for the human eye, with 99.7% and 96.5% of absolute errors below 100 μm. The proposed methods effectively model featurerich micro-anatomical surfaces and enable model-based assistance and automation, ultimately enhancing surgical precision in delicate ophthalmic procedures.