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Purpose: In mandibular reconstructive surgery with free fibula flap, 3D-printed patient-specific cutting guides are the current state of the art. Although these guides enable accurate transfer of the virtual surgical plan to the operating room, disadvantages include long waiting times until surgery and the inability to change the virtual plan intraoperatively in case of tumor growth. Alternatively, (electromagnetic) surgical navigation combined with a non-patient-specific cutting guide could be used, requiring accurate image-to-patient registration. In this phantom study, we evaluated the accuracy of a hybrid registration method for the fibula and the additional error that is caused by navigating with a prototype of a novel non-patient-specific cutting guide to virtually planned osteotomy planes., Methods: The accuracy of hybrid registration and navigation was assessed in terms of target registration error (TRE), angular difference, and length difference of the intended fibula segments using three 3D-printed fibular phantoms with assessment points on osteotomy planes. Using electromagnetic tracking, hybrid registration was performed with point registration followed by surface registration on the lateral fibular surface. The fibula was fixated in the non-patient-specific cutting guide to navigate to planned osteotomy planes after which the accuracy was assessed., Results: Registration was achieved with a mean TRE, angular difference, and segment length difference of 2.3 ± 0.9 mm, 2.1 ± 1.4°, and 0.3 ± 0.3 mm respectively after hybrid registration. Navigation with the novel cutting guide increased the length difference (0.7 ± 0.6 mm), but decreased the angular difference (1.8 ± 1.3°)., Conclusion: Hybrid registration showed to be a feasible and noninvasive method to register the fibula in phantom setup and could be used for electromagnetically navigated osteotomies with a novel non-patient-specific cutting guide. Future studies should focus on testing this registration method in clinical setting., Competing Interests: Declarations. Conflict of interest: The authors declare that they have no conflict of interest. Ethics approval: Not applicable. Consent to participate: Not applicable. Consent for publication: Not applicable. Informed consent: For this type of study, formal consent is not required., (© 2024. CARS.)

Purpose: Resection of pediatric osteosarcoma in the extremities with soft tissue involvement presents surgical challenges due to difficult visualization and palpation of the tumor. Therefore, an adequate image-guided surgery (IGS) system is required for more accurate tumor resection. The use of a 3D model in combination with intraoperative tracked ultrasound (iUS) may enhance surgical decision making. This study evaluates the clinical feasibility of iUS as a surgical tool using a porcine cadaver model., Methods: First, a 3D model of the porcine lower limb was created based on preoperative scans. Second, the bone surface of the tibia was automatically detected with an iUS by a sweep on the skin. The bone surface of the preoperative 3D model was then matched with the bone surface detected by the iUS. Ten artificial targets were used to calculate the target registration error (TRE). Intraoperative performance of iUS IGS was evaluated by six pediatric surgeons and two pediatric oncologic orthopedists. Finally, user experience was assessed with a post-procedural questionnaire., Results: Eight registration procedures were performed with a mean TRE of 6.78 ± 1.33 mm. The surgeons agreed about the willingness for clinical implementation in their current clinical practice. They mentioned the additional clinical value of iUS in combination with the 3D model for the localization of the soft tissue components of the tumor. The concept of the proposed IGS system is considered feasible by the clinical panel, but the large TRE and degree of automation need to be addressed in further work., Conclusion: The participating pediatric surgeons and orthopedists were convinced of the clinical value of the interaction between the iUS and the 3D model. Further research is required to improve the surgical accuracy and degree of automation of iUS-based registration systems for the surgical management of pediatric osteosarcoma., (© 2023. The Author(s).)

Purpose: Abnormalities in the bladder wall require careful investigation regarding type, spatial position and invasiveness. Construction of a 3-D model of the bladder is helpful to ensure adequate coverage of the scanning procedure, quantitative comparison of bladder wall textures between successive sessions and finding back previously discovered abnormalities., Methods: Videos of both an in vivo bladder and a textured bladder phantom were acquired. Structure-from-motion and bundle adjustment algorithms were used to construct a 3-D point cloud, approximate it by a surface mesh, texture it with the back-projected camera frames and draw the corresponding 2-D atlas. Reconstructions of successive sessions were compared; those of the bladder phantom were co-registered, transformed using 3-D thin plate splines and post-processed to highlight significant changes in texture., Results: The reconstruction algorithms of the presented workflow were able to construct 3-D models and corresponding 2-D atlas of both the in vivo bladder and the bladder phantom. For the in vivo bladder the portion of the reconstructed surface area was 58% and 79% for the pre- and post-operative scan, respectively. For the bladder phantom the full surface was reconstructed and the mean reprojection error was 0.081 mm (range 0-0.79 mm). In inter-session comparison the changes in texture were correctly indicated for all six locations., Conclusion: The proposed proof of concept was able to perform 3-D and 2-D reconstruction of an in vivo bladder wall based on a set of monocular images. In a phantom study the computer vision algorithms were also effective in co-registering reconstructions of successive sessions and highlighting texture changes between sessions. These techniques may be useful for detecting, monitoring and revisiting suspicious lesions., (© 2023. The Author(s).)

Purpose: The biopsy procedure is an important phase in breast cancer diagnosis. Accurate breast imaging and precise needle placement are crucial in lesion targeting. This paper presents an end-effector (EE) for robotic 3D ultrasound (US) breast acquisitions and US-guided breast biopsies. The EE mechanically guides the needle to a specified target within the US plane. The needle is controlled in all degrees of freedom (DOFs) except for the direction of insertion, which is controlled by the radiologist. It determines the correct needle depth and stops the needle accordingly., Method: In the envisioned procedure, a robotic arm performs localization of the breast, 3D US volume acquisition and reconstruction, target identification and needle guidance. Therefore, the EE is equipped with a stereo camera setup, a picobeamer, US probe holder, a three-DOF needle guide and a needle stop. The design was realized by prototyping techniques. Experiments were performed to determine needle placement accuracy in-air. The EE was placed on a seven-DOF robotic manipulator to determine the biopsy accuracy on a cuboid phantom., Results: Needle placement accuracy was 0.3 ± 1.5 mm in and 0.1 ± 0.36 mm out of the US plane. Needle depth was regulated with an accuracy of 100 µm (maximum error 0.89 mm). The maximum holding force of the stop was approximately 6 N. The system reached a Euclidean distance error of 3.21 mm between the needle tip and the target and a normal distance of 3.03 mm between the needle trajectory and the target., Conclusion: An all in one solution was presented which, attached to a robotic arm, assists the radiologist in breast cancer imaging and biopsy. It has a high needle placement accuracy, yet the radiologist is in control like in the conventional procedure.

Purpose: Patient-specific biomedical modeling of the breast is of interest for medical applications such as image registration, image guided procedures and the alignment for biopsy or surgery purposes. The computation of elastic properties is essential to simulate deformations in a realistic way. This study presents an innovative analytical method to compute the elastic modulus and evaluate the elasticity of a breast using magnetic resonance (MRI) images of breast phantoms., Methods: An analytical method for elasticity computation was developed and subsequently validated on a series of geometric shapes, and on four physical breast phantoms that are supported by a planar frame. This method can compute the elasticity of a shape directly from a set of MRI scans. For comparison, elasticity values were also computed numerically using two different simulation software packages., Results: Application of the different methods on the geometric shapes shows that the analytically derived elongation differs from simulated elongation by less than 9% for cylindrical shapes, and up to 18% for other shapes that are also substantially vertically supported by a planar base. For the four physical breast phantoms, the analytically derived elasticity differs from numeric elasticity by 18% on average, which is in accordance with the difference in elongation estimation for the geometric shapes. The analytic method has shown to be multiple orders of magnitude faster than the numerical methods., Conclusion: It can be concluded that the analytical elasticity computation method has good potential to supplement or replace numerical elasticity simulations in gravity-induced deformations, for shapes that are substantially supported by a planar base perpendicular to the gravitational field. The error is manageable, while the calculation procedure takes less than one second as opposed to multiple minutes with numerical methods. The results will be used in the MRI and Ultrasound Robotic Assisted Biopsy (MURAB) project.