Volume 10, Issue 2 - Proceedings of the CURAC 2023 Annual Meeting, Basel, August 24–26, 2023

Statistical shape models (SSMs) allow the compact description of the variability of object shapes within a given sample set. They are commonly used in medical imaging to model and analyse the shape of anatomical structures such as organs. The generation of a SSM mainly consists of the calculation of the average shape and the main directions of variation of the data set. Usually, structured point clouds are used as shape representations. A crucial step in the calculation of the average shape of the data set represents the transformation of the objects into a common reference space in order to average coordinates of corresponding points. When using unstructured point clouds without explicitly defined landmarks, the matching of correspondences remains a challenge. We propose a novel solution for a spatially-constrained keypoint matching (FPFH++). It is based on a first attempt of a feature-based registration using Fast Point Feature Histograms (FPFH) compared to a baseline approach utilizing Coherent Point Drift (CPD).

A proposed solution to address increasing scarcity of operating room (OR) nurses is the deployment of robotic scrub nurses (RSNs). One of the primary responsibilities of these robots is the handover of surgical instruments to the surgeon. Despite this tasks’ apparent simplicity, it requires great precision and timing, while seamless execution is essential for the surgical workflow. This paper outlines the unique challenges of the instrument handover process between a RSN and a surgeon taking place during laparoscopic surgery. After customizing existing solutions from different domains to meet the specific needs of laparoscopic surgery, we introduced these solutions to medical professionals in a simulated OR scenario, and performed a utility analysis to identify the most suitable solutions.

Anterior clinoidectomy is a surgical procedure used to access the central skull base, providing access to sellar and parasellar pathologies and vascular lesions in and around the cavernous sinus. However, the procedure is challenging and risky due to limited working space, restricted surgical view, and proximity to critical anatomical structures such as the carotid artery, oculomotor nerve, and optic nerve.

This study proposes an additional feature of optical coherence tomography (OCT) as a guidance system for laser surgery, aiming to enhance ablation efficiency during laser osteotomy. A long-range Bessel-like beam OCT system is integrated with an Er:YAG laser. The signal sensitivity of the OCT system is measured under various conditions encountered during laser osteotomy. The results demonstrate that the OCT sensitivity decreases from 87.53 dB to 79.54 dB and 68.93 dB in the presence of debris and water, respectively. These findings highlight the potential application signal sensitivity of OCT as a criterion for detecting the accumulation of water and debris, which could lead to a reduction in ablation efficiency during laser osteotomy using Er:YAG laser.

Swallowing problems (dysphagia) is associated with significant morbidity and mortality therefore diagnosis and treatment of dysphagia is important. Diagnostic tests include screening procedures, clinical swallowing examinations, and instrumental examination procedures. A non-invasive diagnostic option is auscultation of the swallowing act. However, there are different statements about the reliability and validity of the manual execution of this test. We developed a mobile hardware system to record cervical sounds using two microphones on the neck to acquire audio a data set. To generate ground truth data, fiberendoscopic swallow examinations were performed simultaneously to identify dysphagia. In order to diagnostically assess the swallowing sounds a spectrogram based classification pipeline was developed. In a first step this enabled us to identify different swallowing patterns in healthy individuals. With an accuracy of ~95%, we were able to reliably detect swallows within audio recordings, while the classification of types of swallow (dry, water, solid food) indicate the need for further improvements within the project ahead. In the future, we anticipate AI based analysis of auscultated swallowing sounds to detect swallowing disorders and aspirations.

Brain biopsies are necessary in cases of unclear lesions on imaging studies to establish a treatment plan based on the histologic diagnosis. A previous study investigated the potential of lasers to make brain biopsies less invasive, faster and safer. The study demonstrated that lasers can create highly precise burr holes which themselves can act as a sufficient guide for the biopsy needle. Furthermore, lasers can create tangential canals in the bone which allows to biopsy brain regions that are usually impossible or hazardous to access. Building upon the results of the previous study, further research and technological advancements were pursued. This includes a biopsy needle attachment for the robot, which will be used to simulate brain biopsies using CARLO© (Cold Ablation Robot-guided Laser Osteotome) with its Er:YAG laser and navigated robotic guiding system. The study utilizes five freshly frozen skulls, which are immobilized using a Mayfield clamp. Prior to conducting the experiment, the NeuroPlan© software is employed to plan the path and angle of the biopsies. To align the preexperimental CT with the skull, referencing points on the skull and its surface are registered using a pointer. A small skin incision is performed to reach the area of bone where the laser ablates the bone for the biopsy. Preliminary experimental results suggest that the combined use of laser ablation and a guidance device enables precise bone ablation and accurate needle guidance for biopsies. These initial results demonstrate the potential of integrating laser technology and robotics in neurosurgery, potentially enabling less invasive, faster and safer biopsies, ultimately leading to better patient outcomes.

3D ultrasound imaging is a promising modality for therapy guidance, e.g. in radiation therapy. It is able to provide volumetric soft tissue images in real-time. However, due to low image quality, high noise ratio and high data dimensionality, real-time capable US image processing methods like target tracking are challenging. In this study, a feature-based tracking approach is investigated. The FAST feature detector is used to detect local image features in 3D ultrasound images. Two different feature descriptors are tested and evaluated in terms of target tracking: The BRIEF descriptor as well as a slicedwasserstein autoencoder. On the basis of a feature matching algorithm, tracking experiments are executed and evaluated using eight labeled 3D US sequences. The mean tracking error measured is 2.08±1.50mm and 2.29±1.59mm using the autoencoder and the BRIEF descriptor, respectively. The results indicate that using an autoencoder for feature description improves the tracking performance compared to a binary descriptor. The proposed tracking method could be executed in fast runtimes of 137 ms and 256 ms per image on average making it real-time capable.

During neuroradiological interventions such as treating intracranial aneurysms, neuroradiologists have to navigate a catheter in the 3D anatomy while watching a 2D projection of the vessels. To train this visuospatial ability, we present a virtual reality application where the user has to identify anatomically relevant positions on the Circle of Willis based on a 2D projection image. This image is generated based on a 3D model using a Fresnel shader. To increase motivation, which is an important aspect of training, we included several game elements. We qualitatively evaluated our application with two neuroradiologists. Although they rated our implementation of the task as difficult due to the small image section, both participants emphasized the importance of this training. Even small changes that have been suggested can adjust the difficulty, leading to an appropriate training that could be integrated into the curriculum. The results also indicate that the included game elements are motivating and that the application in general has a high usability. The proposed immersive virtual reality application provides training for visuospatial ability in a concrete medical context. Due to gamification, fun, and motivation are increased, which are two important factors of training affecting the frequency of use and outcome.

In radiation therapy, breathing and other influences cause a constant movement of the tissue to be irradiated. Thus, a continuous position control is required which could be handled by the usage of 3D ultrasound imaging. For this purpose, two approaches for target tracking in 3D ultrasound (US) sequences of the liver are analyzed in this study. Therefore, an image-by-image localization of the target is performed using a deep localization network. A singletarget and a multiple-target approach are investigated where deep localization networks are trained for locating one specific and multiple specific targets, respectively. Training the networks and evaluating the tracking algorithm is performed on the basis of a labeled 3D US liver data set in 2-fold crossvalidation experiments. The single-target and multiple-target approaches performed comparable with a mean tracking error of 2.28±1.20mm and 2.23±1.28 mm, respectively. The proposed tracking algorithm is real-time capable with a mean runtime per 3D ultrasound image of 68ms.

The increase in staff shortage, particularly in urgently needed care professions, is becoming an immense problem in the German healthcare system. This critical issue is further intensified by the fact that the healthcare system is still a strongly human-dependent and often insufficiently interconnected environment. Automation, medical robotics and the concept of model-based medicine can play a key role not only in addressing these issues and supporting clinical staff, but also in enabling new applications to improve patient care. While many existing approaches aim to tackle these challenges, they are generally based on current network architectures and standards and are thus constrained by the limitations of these networks. This article highlights the need for a new network approach such as 6G, which offers flexible, dynamic structures, new communication classes and many other new features in order to leverage the true potential of these new technologies.

This paper describes how automatic speech recognition (ASR) can be used to explore electronic patient records (EPR) in a sterile environment. As an information display, we used a system that was developed for the presentation of patient data and for supporting surgical hand disinfection. The speech recognition was performed using the Mozilla Web Speech API. A room microphone, a Jabra Box, and a directional microphone, a RØDE NT-USB Mini, were tested at various positions. Interactions with the EPR are triggered with a list of commands. The interaction was working as indented and test persons reported the system as intuitive.

Suturing is an integral part of surgery. Specialized instrumentation facilitates manual needle handling to support laparoscopic suturing tasks, e.g. uterine closure, in minimally invasive surgery. Current solutions for robotassisted laparoscopy lack the possibility to integrate these instruments, making them suitable only for conventional laparoscopic surgery. This paper introduces a novel end effector design actuating a conventional suturing instrument. The end effector is integrated into the DLR MiroSurge system to facilitate telemanipulated suturing. The mechanical properties of the end effector are characterized and its feasibility for use in robot-assisted laparoscopy is demonstrated.

Ultrasound gel is used as a coupling medium in ultrasound procedures, thereby ensuring the entry of sound waves into the body of the patient and providing ultrasound images of high quality. In this paper, we present an approach to automatically supply ultrasound gel during robot guided ultrasound examinations. For this purpose, we combine a simple mechanical design consisting of a gel tube and a push mechanism with a specialized control strategy exploiting the robotic nullspace of 7 DoF redundant manipulator. Functionality is demonstrated by robotic ultrasound scans on phantoms, with gel being automatically applied when needed.

In neuroendoscopy, an assistant surgeon holds the endoscope while the operating surgeon performs brain surgery using surgical instruments in both hands. The assistant surgeon’s task can be strenuous over time, especially in long surgeries, and unsteadiness or tremor might affect the visualization quality that the operating surgeon depends upon. Existing mechanical and pneumatic arms offer limited flexibility. We propose a robotic assistant as a third hand to the surgeon. It holds the endoscope and can be moved freely or held in place. As a proof of concept, we attached a neuroendoscope to an offthe- shelf robot with a custom handle, including a force/torque (F/T) sensor. We qualitatively identified the requirements for the third hand with a surgeon as a participant. We also quantitatively identified the range of forces applied by the endoscope to act as a retractor on two brain phantoms while visualizing the surgical site. With our proof of concept study, we could show the feasibility of robotic assistance in neuroendoscopy. Based on our observations, we found that an intuitive input device to switch the different robot modes, a second F/T sensor to measure the surgeon’s input and tissue interaction separately, and a differently shaped precision grip handle represent promising improvements to our third hand prototype.

The surgical procedure known as optic nerve unroofing plays a vital role in skull base surgery. This critical intervention focuses on relieving pressure and decompressing the optic nerve to safeguard vision, restore optimal nerve function, and enhance the surgical view during aneurysm therapy. Nevertheless, the surgical procedure presents inherent challenges and risks due to factors like limited working space, restricted surgical view, and the proximity to critical anatomical structures, including the optic nerve, carotid artery and oculomotor nerve. Significant advancements in medical robotics technology hold promise for addressing these challenges and potentially enhancing multiple aspects of neurosurgery. The objective of this study was to evaluate the feasibility and precision of utilizing CARLO © (Cold Ablation Roboterguided Laser Osteotome) for delineating the boundaries of the optical canal. Additionally, the investigation involved the insertion of a thermal probe into the optical canal to assess the occurrence of significant heat damage resulting from the removal of the optic roof. Success was defined as the accurate excavation of the optical canal, which was confirmed through post-experimental CT scans and photographic documentation. The experiment utilized five fresh frozen skulls, securely fixed in a Mayfield clamp to ensure a stable experimental setup. Prior to the procedure, preoperative planning was conducted using NeuroPlan © , which accurately segmented crucial anatomical structures and devised trajectories with a safety margin of 2mm from high-risk areas. A navigation system and additional referencing screws were employed to achieve precise bone ablation. The target structure was accessed through a pterional craniotomy and the optical canal was prepared extradurally. While data evaluation is ongoing, preliminary results indicate a successful delineation of the optical roof without significant heat damage while preserving vital anatomical structures. These initial findings have the potential to stimulate further investigation into the applications of robotic and laser technologies in the realm of neurosurgery. The study emphasizes the feasibility and exceptional precision of robotic technology, which can be utilized to advance the development of additional procedures to improve patient outcomes and reduce perioperative risks in neurosurgical interventions.

To help with the critical nurse staffing shortages in hospitals worldwide, robotic assistants are designed to handle frequently required tasks in the digital operating room (DOR), such as the guidance of the laparoscopic camera. To enable fluent collaboration between robots and clinicians, an intuitive and efficient communication interface is needed to allow for interaction using natural language. However, the demanding requirements of the surgical domain make it challenging to develop suitable solutions. A variety of different vocabulary or phrases may be used for expressing the same command. At the same time, surgical workflows may be highly dynamic - especially in emergency situations - and thus the system must be able to grasp the user’s intent both quickly and with high accuracy. This is especially true as only some clinicians may be authorized to request certain tasks, depending on their rank or field of expertise. To solve these challenges, our proposed communication system uses the fine-tuned deep learning model to recognize the speaker information, and the robot assistant takes action only when it detects the commands from the responsible clinician. Also, our proposed conversational functions enable the finetuned large language models to understand the current natural language command given previous command history. In this work, we present a communication system to recognize the speaking person and understand the intent of conversational commands quickly and accurately.

Endotracheal intubation is a medical procedure to secure a patient’s airways, which can be challenging in emergency situations due to an individual’s anatomy. Intubation blades can benefit from an adjustable design with shape memory alloys. We present a novel blade design with two degrees of freedom, continuously transforming a straight into a curved blade. Our demonstrators reached mean angular deflections up to 16∘ without exceeding outer blade temperatures of 40∘C. Mean forces of almost 24N were applicable. This approach has the potential to reduce the complexity of intubation procedures and increase the success rate, especially in time-critical emergency situations.

Haptic feedback of gripping forces during robotassisted surgery can benefit the surgical outcome by means of reduced forces applied to the tissue. A custom-designed haptic user interface allows to control four degrees of freedom of the instrument’s endeffector and to display gripping forces. System-centered evaluation is performed to assess its capability of displaying feedback with high mechanical bandwidth. In addition, the perception of gripping forces is evaluated using task-centered methods. Two tasks were performed by ten participants to assess the perceived feedback regarding size and stiffness of grasped objects. Maximum feedback forces of 4.3N and a mechanical bandwidth of 73.5 Hz are achieved. Tests with participants showed promising results regarding the discrimination of size and stiffness of grasped objects.

Advancements in personalized medicine, threedimensional (3D) printing, miniaturization, and robot-assisted surgery are driving innovation in tissue engineering. A novel approach, known as in situ printing, focuses on the direct deposition of materials at the surgical site. Using the in situ printing approach, bone and/or cartilage defects can be addressed with high precision. Furthermore, highly customized 3D printed tissue constructs or implants can be deposited directly inside the body. Currently, most applications of in situ printing are limited to areas near the skin or open surgeries. Even though a minimally invasive approach would bring clinical benefits, only a few research groups have focused on this field. In this scoping review, we provide an overview of the current state of in situ minimally invasive 3D printing technology for bone and cartilage regeneration and discuss its advantages and current challenges.

The proposed system aims at reproducibility in ultrasound follow-up examinations by storing the position of the ultrasound transducer in relation to acquired images. The system utilizes an electromagnetic tracking system. It includes a guidance feature to assist in placing the transducer correctly on the patient. Evaluation of the system involved technical accuracy tests on a phantom and accuracy tests on human subjects. The results showed that the technical accuracy of the system met the required criteria, but the transducer positioning error in realistic scenarios was above the threshold. Usability testing indicated potential benefits for medical training and provided suggestions for improving the user interface. Overall, the system shows promise for further development and can already be used for training ultrasound examinations.

Correctly torquing bone screws is important to achieve good patient outcomes. An automated system has been previously proposed that may allow more objective torquing of bone screws. Here the system is tested vs. a static torque limit in pig bone. 5 screws were first inserted until stripping to calibrate the dynamic and static limits. Then 6 were inserted limited to 80% of the mean stripping torque. Then 7 were inserted using 80% of the dynamic model-predicted stripping torque. The pull-out strength of the dynamic and static insertions were compared and no statistically significant difference was found. Future work should consider at using larger screws and different bone samples, with more repetitions to try and obtain a statistically significant result.

An atraumatic approach to the inner ear is an important goal in the future development of cochlear implant surgery, as the current surgical procedure for electrode insertion is highly invasive. To reduce invasiveness, minimally invasive surgical options are being explored, such as the insertion of one or more drill channels. Due to the proximity to critical structures, a temperature sensor is incorporated into the medical drill for process parallel temperature monitoring to prevent thermal damage. The temperature data is sent to the analysis hardware via Bluetooth BLE. This requires a power supply for the electronics on the drill. There are a number of limitations to the design of such a power supply. For one, the drill is rotating. Therefore, the energy generation must be contactless. Secondly, the energy generation should not depend on the rotation of the drill, so that the temperature can be measured even without the drill rotating and the rotational speed of the drill is not limited. In this paper, we propose a solution for a contactless energy transmission system (ETS) based on inductive coupling. Considering the dimensional limitations of attaching the electronics to the drill shaft, a multilayer PCB coil with multiple contacts for different number of turns is developed. The electrical circuit is simulated and the best settings are identified. The power supply is validated according to the predefined requirements. In the future, the medical drill will be built with the newly developed ETS. Sterilization and wear tests are performed to confirm the suitability of the drill with integrated temperature sensor for the operating room.

Digital radiography in medicine is a widely used imaging method for obtaining visual information about the inside of a body. To prepare the acquired raw image for diagnostic evaluation, the contrast must be adjusted depending on the examined part of the body and the reason of acquisition. The contrast enhancement of an image can be considered as a style transfer or an image-to-image translation which is an important field in deep learning. Based on common methods like the pix2pix network that only translate from one domain into one other, we propose a method (cc-pix2pix) for translating into multiple domains in one training. We provide additional information about the examination to the network for a specific contrast adjustment. Compared to the pix2pix network, the ccpix2pix reduces the mean squared error by a factor of six and achieves an improvement of approximately seven percentage points based on the histogram intersection of source and target images.

Intracranial mirror aneurysms are pathologic dilatations of cerebral arteries that occur at identical locations in both hemispheres. They do not always have identical sizes, shapes, or rupture states, despite identical patient-specific risk factors. As a subgroup of multiple aneurysms and thus small amounts of data, clinical research about their causes and development has not been conclusive. Using eight patients with 16 mirror aneurysms with different rupture states, we investigated differences between the hemispheres. We virtually performed stitching: detaching the aneurysm domes to place them on the opposite parent vessel to assess the influence of aneurysm morphology and upstream parent vessel shape on hemodynamics. In the unaltered datasets, we found that blood flow within aneurysms in the left hemisphere has higher wall shear stress and velocity. After stitching, we found that both upstream parent vessel as well as aneurysm morphology influence hemodynamics. Morphologic parameters like size, undulation index, and aneurysm angle had a higher influence. In a short rupture risk analysis we found a correlation between rupture and aspect ratio and non-sphericity index. Overall, we found possible indicators for mirror aneurysm analysis that illustrated the importance of morphological analysis, though more datasets are necessary for conclusive statements about special treatment for mirror aneurysms.

This paper focuses on determining the cable tension required for a cable-driven endoscopic manipulator to reach a given position under an external load at the end effector. The aim is to restore the initial position of the end effector without an external force. A simulation was performed using MATLAB, where mathematical models and algorithms were used to calculate the required tension. The mathematical model, based on Optimized Motion Estimation Analysis, considers the joint stiffness and the influence of gravity, in addition to the cable tensions and external load. The algorithm minimizes the sum of moments to achieve a stable position. An optical tracking system was used to validate the simulation results against experimental data. The manipulator successfully compensated for an external load of 1.96N and returned to its initial position with adjusted cable tensions. The results showed that the manipulator was deformed by an external load, highlighting the need to adjust the cable tension for position compensation. The discrepancies between the experimental and simulation results were due to factors such as marker size, as well as joint imperfections due to manufacturing and friction effects. Nevertheless, the proposed method proved to be effective in compensating for external loads and restoring the manipulator to the desired position.

Training and prototype development in robotassisted surgery requires appropriate and safe environments for the execution of surgical procedures. Current dry lab laparoscopy phantoms often lack the ability to mimic complex, interactive surgical tasks. This work presents an interactive surgical phantom for the cholecystectomy. The phantom enables the removal of the gallbladder during cholecystectomy by allowing manipulations and cutting interactions with the synthetic tissue. The force-displacement behavior of the gallbladder is modelled based on retraction demonstrations. The force model is compared to the force model of ex-vivo porcine gallbladders and evaluated on its ability to estimate retraction forces.

Soft tissue elasticity is directly related to different stages of diseases and can be used for tissue identification during minimally invasive procedures. By palpating a tissue with a robot in a minimally invasive fashion force-displacement curves can be acquired. However, force-displacement curves strongly depend on the tool geometry which is often complex in the case of medical tools. Hence, a tool calibration procedure is desired to directly map force-displacement curves to the corresponding tissue elasticity.We present an experimental setup for calibrating medical tools with a robot. First, we propose to estimate the elasticity of gelatin phantoms by spherical indentation with a state-of-the-art contact model. We estimate force-displacement curves for different gelatin elasticities and temperatures. Our experiments demonstrate that gelatin elasticity is highly dependent on temperature, which can lead to an elasticity offset if not considered. Second, we propose to use a more complex material model, e.g., a neural network, that can be trained with the determined elasticities. Considering the temperature of the gelatin sample we can represent different elasticities per phantom and thereby increase our training data.We report elasticity values ranging from 10 to 40 kPa for a 10% gelatin phantom, depending on temperature.

Concentric tube robots (CTR) have gained popularity in robotic research due to their potential for smaller instrument sizes, enhanced dexterity and reduced trauma. However, CTR control can be complex, with tip direction and curvature being kinematically coupled. To address this, a symmetric eccentric tube robot (ETR) is presented, where three identical pre-curved wires are arranged in parallel and constrained by an outer sheath. Instrument curvature is controlled by a single input angle. This study aims to demonstrate the suitability as manually actuated instrument. A model for curvature as a function of input angle is presented, and a prototype ETR with an outer diameter of 1 mm is assembled and evaluated. The results show that the ETR follows the expected shape, the curvature decreasing with the separation angle in an almost linear way that may be perceived as intuitive and predictable by the human user. However, some unsteady behavior (snapping) is observed, which may be addressed by preventing torsion of the wires through mechanical means. The simplified model neglecting the sheath stiffness provides precise enough predictions for the working space of a manual ETR. The findings suggest that manual ETRs have potential applications in superficial interventions, such as injections, arthroscopy, or ophthalmic surgery, where their curved section can be beneficial in comparison to current straight needles. Further research could explore interlocking mechanical designs to prevent torsion or modular setups for enhanced functionality.

To automate surgical (sub-)tasks in robotic surgery, the knowledge of the exact pose of the instrument is mandatory. The application of Optical Coherence Tomography (OCT) to the problem of pose measurement appears promising due to its advantages of 3D imaging and micron-scale resolution. To investigate this, 175 image sequences of the EndoWrist Round Tip Scissor Tool were acquired with an OCT system. The images differ in the opening angles of the scissor blades and the rotation angles of the entire instrument about its central axis. These image sequences were further processed through computer vision methods of the individual images followed by point cloud generation. For pose estimation, an Iterative Closest Point algorithm was implemented to register the acquired point clouds to reference point clouds created from the instrument CAD file. The implemented algorithm was able to determine the opening angle with an overall error of 2∘ ± 1.3∘ and the rotation angle with a standard deviation between several runs of 0.6∘ ±2.8∘. However, the overall processing time of (39 ± 17)s on a standard PC leaves room for further investigations.

Training helps to maintain and improve sufficient muscle function, body control, and body coordination. These are important to reduce the risk of fracture incidents caused by falls, especially for the elderly or people recovering from injury. Virtual reality training can offer a cost-effective and individualized training experience. We present an application for the HoloLens 2 to enable musculoskeletal training for elderly and impaired persons to allow for autonomous training and automatic progress evaluation. We designed a virtual downhill skiing scenario that is controlled by body movement to stimulate balance and body control. By adapting the parameters of the ski slope, we can tailor the intensity of the training to individual users. In this work, we evaluate whether the movement data of the HoloLens 2 alone is sufficient to control and predict body movement and joint angles during musculoskeletal training.We record the movements of 10 healthy volunteers with external tracking cameras and track a set of body and joint angles of the participant during training. We estimate correlation coefficients and systematically analyze whether whole body movement can be derived from the movement data of the HoloLens 2. No participant reports movement sickness effects and all were able to quickly interact and control their movement during skiing. Our results show a high correlation between HoloLens 2 movement data and the external tracking of the upper body movement and joint angles of the lower limbs.

High navigation accuracy is a prerequisite for tailored and safe tumor resections. However, in posterior fossa surgery, especially in the semi-sitting position, navigation is often considered to be non-useful due to limited accuracy caused by gravitational effects and brain-shift. To enable navigation in these surgical approaches intraoperative evaluation of accuracy and navigation update strategies are required. Navigated intraoperative ultrasound (iUS) might serve as valuable tool to quantify navigation accuracy and even update navigation to gain higher accuracy. Data of 23 patients (28 lesions) undergoing navigation supported surgery in the posterior fossa with application of navigated iUS including acquisition of a 3D iUS data set were evaluated retrospectively based on intraoperative ratings on accuracy and tumor segmentation based on preoperative magnetic resonance imaging (MRI) and iUS data. In nine cases (eleven lesions) navigation was rated “insufficient” leading to a navigation update by manually outlining the tumor volumes within the iUS data set, whereas in all other cases navigation accuracy was rated “sufficient” with no need for further updates. Tumor volume was comparable between MRIand iUS-based segmentation. IUS was successfully applied in navigation-supported surgery in the posterior fossa in the semisitting position enabling continuous navigation-support throughout surgery by evaluation of navigation accuracy and navigation updates, supporting safe maximum tumor resection.