MITK-OpenIGTLink for combining open-source toolkits in real-time computer-assisted interventions

Open-source navigation system for tracking dissociated parts with multi-registration

PURPOSE

During reconstructive surgery, knee and hip replacements, and orthognathic surgery, small misalignments in the pose of prosthesis and bones can lead to severe complications. Hence, the translational and angular accuracies are critical. However, traditional image-based surgical navigation lacks orientation data between structures, and imageless systems are unsuitable for cases of deformed anatomy. We introduce an open-source navigation system using a multiple registration approach that can track instruments, implants, and bones to precisely guide the surgeon in emulating a preoperative plan.

METHODS

We derived the analytical error of our method and designed a set of phantom experiments to measure its precision and accuracy. Additionally, we trained two classification models to predict the system reliability from fiducial points and surface matching registration data. Finally, to demonstrate the procedure feasibility, we conducted a complete workflow for a real clinical case of a patient with fibrous dysplasia and anatomical misalignment of the right femur using plastic bones.

RESULTS

The system is able to track the dissociated fragments of the clinical case and average alignment errors in the anatomical phantoms of [Formula: see text]  mm and [Formula: see text]. While the fiducial-points registration showed satisfactory results given enough points and covered volume, we acknowledge that the surface refinement step is mandatory when attempting surface matching registrations.

CONCLUSION

We believe that our device could bring significant advantages for the personalized treatment of complex surgical cases and that its multi-registration attribute is convenient for intraoperative registration loosening cases.

Breast MRI texture analysis for prediction of BRCA-associated genetic risk

Background

BRCA1/2 deleterious variants account for most of the hereditary breast and ovarian cancer cases. Prediction models and guidelines for the assessment of genetic risk rely heavily on criteria with high variability such as family cancer history. Here we investigated the efficacy of MRI (magnetic resonance imaging) texture features as a predictor for BRCA mutation status.

Methods

A total of 41 female breast cancer individuals at high genetic risk, sixteen with a BRCA1/2 pathogenic variant and twenty five controls were included. From each MRI 4225 computer-extracted voxels were analyzed. Non-imaging features including clinical, family cancer history variables and triple negative receptor status (TNBC) were complementarily used. Lasso-principal component regression (L-PCR) analysis was implemented to compare the predictive performance, assessed as area under the curve (AUC), when imaging features were used, and lasso logistic regression or conventional logistic regression for the remaining analyses.

Results

Lasso-selected imaging principal components showed the highest predictive value (AUC 0.86), surpassing family cancer history. Clinical variables comprising age at disease onset and bilateral breast cancer yielded a relatively poor AUC (~ 0.56). Combination of imaging with the non-imaging variables led to an improvement of predictive performance in all analyses, with TNBC along with the imaging components yielding the highest AUC (0.94). Replacing family history variables with imaging components yielded an improvement of classification performance of ~ 4%, suggesting that imaging compensates the predictive information arising from family cancer structure.

Conclusions

The L-PCR model uncovered evidence for the utility of MRI texture features in distinguishing between BRCA1/2 positive and negative high-risk breast cancer individuals, which may suggest value to diagnostic routine. Integration of computer-extracted texture analysis from MRI modalities in prediction models and inclusion criteria might play a role in reducing false positives or missed cases especially when established risk variables such as family history are missing.

Measuring bone defects for acetabular revision surgery for choosing an appropriate reconstruction strategy: A concept study on plastic models

BACKGROUND

Bone defects can be filled with autografts, allografts and artificial bone-materials. The aim of this study was to evaluate whether the digitization of known defect models with a navigation system is a reliable measurement method for estimating the size of a bone defect.

METHODS

Six preformed, cylindrical and cone-shaped defects on an artificial hip-bone were digitalized by six different observers. Reference volumes were gathered by measuring the depth of the defects, using an alginate impression material to fill out the defects and calculating the volumes from a CT scan.

RESULTS

One out of the six preformed defects showed a statistically significant difference between the digitalization and the calculation, four showed a significant difference between the digitalization and the mould as well as between the digitalization and the CT calculation.

CONCLUSIONS

This technique offers satisfactory results and consistent reproducibility when digitalizing big defects with relatively simple shape. Decreasing size and increasing complexity of the defects leads to more imprecise measurements.

Computed tomography data collection of the complete human mandible and valid clinical ground truth models

Image-based algorithmic software segmentation is an increasingly important topic in many medical fields. Algorithmic segmentation is used for medical three-dimensional visualization, diagnosis or treatment support, especially in complex medical cases. However, accessible medical databases are limited, and valid medical ground truth databases for the evaluation of algorithms are rare and usually comprise only a few images. Inaccuracy or invalidity of medical ground truth data and image-based artefacts also limit the creation of such databases, which is especially relevant for CT data sets of the maxillomandibular complex. This contribution provides a unique and accessible data set of the complete mandible, including 20 valid ground truth segmentation models originating from 10 CT scans from clinical practice without artefacts or faulty slices. From each CT scan, two 3D ground truth models were created by clinical experts through independent manual slice-by-slice segmentation, and the models were statistically compared to prove their validity. These data could be used to conduct serial image studies of the human mandible, evaluating segmentation algorithms and developing adequate image tools.

Polhemus EM tracked Micro Sensor for CT-guided interventions

PURPOSE

Electromagnetic (EM) tracking is a key technology in image-guided therapy. A new EM Micro Sensor was presented by Polhemus Inc.; it is the first to enable localization of medical instruments through their trackers. Different field generators (FGs) are available by Polhemus, one being almost as small as a sugar cube. As accuracy and robustness of tracking are known challenges to using EM trackers in clinical environments, the goal of this study was a standardized assessment of the Micro Sensor in both a laboratory (lab) and a computed tomography (CT) environment.

METHODS

The Micro Sensor was assessed by means of Hummel et al.'s standardized protocol; it was assessed in conjunction with a Polhemus Liberty tracker and three FGs - with edge lengths of 1 (TX1), 2 (TX2), and 4 (TX4) inches. Precision as well as positional and rotational accuracy were determined in a lab and a CT suite. Distortions by four different metallic cylinders and tracking of two typical medical instruments - a hypodermic needle and a flexible endoscope - were also tested.

RESULTS

A jitter of 0.02 mm or less was found for all FGs in the different environments, except for the TX2 FG for which no valid data could be obtained in the CT. Errors of 5 cm distance measurements were 0.6 mm or less for all FGs in the lab. While the distance errors of the TX1 FG were only slightly increased up to 1.6 mm in the CT, those of the TX4 FG were found to be up to around 10% of the measured distance (5.4 mm on average). The mean orientation error was found to be 0.9^° /0.5^° /0.1^° for the TX4/TX2/TX1 FG in the lab. In the CT environment, rotation errors were in the same range: less than 1.2^° /0.1^° for the TX4/TX1 FG. Deviation under the presence of metallic cylinders stayed below 1 mm in most cases. Precision and orientational accuracy do not seem to be affected by instrument tracking and stayed in the same range as for the other measurements whereas distance errors were slightly increased up to 1.7 mm.

CONCLUSION

This study shows that accurate tracking of medical instruments is possible with the new Micro Sensor; it demonstrated a jitter of 0.01 mm or less, position errors below 2 mm, and rotation errors of less than 0.3^° . As with other EM trackers, errors increase when large tracking volumes with ranges of up to 50 cm are required in clinical environments. For smaller tracking volumes with ranges of up to 15 cm, a high accuracy and robustness was found. This is interesting especially for the TX1 FG which can easily be placed in close vicinity to the region of interest.

ROS-IGTL-Bridge: an open network interface for image-guided therapy using the ROS environment

PURPOSE

With the growing interest in advanced image-guidance for surgical robot systems, rapid integration and testing of robotic devices and medical image computing software are becoming essential in the research and development. Maximizing the use of existing engineering resources built on widely accepted platforms in different fields, such as robot operating system (ROS) in robotics and 3D Slicer in medical image computing could simplify these tasks. We propose a new open network bridge interface integrated in ROS to ensure seamless cross-platform data sharing.

METHODS

A ROS node named ROS-IGTL-Bridge was implemented. It establishes a TCP/IP network connection between the ROS environment and external medical image computing software using the OpenIGTLink protocol. The node exports ROS messages to the external software over the network and vice versa simultaneously, allowing seamless and transparent data sharing between the ROS-based devices and the medical image computing platforms.

RESULTS

Performance tests demonstrated that the bridge could stream transforms, strings, points, and images at 30 fps in both directions successfully. The data transfer latency was <1.2 ms for transforms, strings and points, and 25.2 ms for color VGA images. A separate test also demonstrated that the bridge could achieve 900 fps for transforms. Additionally, the bridge was demonstrated in two representative systems: a mock image-guided surgical robot setup consisting of 3D slicer, and Lego Mindstorms with ROS as a prototyping and educational platform for IGT research; and the smart tissue autonomous robot surgical setup with 3D Slicer.

CONCLUSION

The study demonstrated that the bridge enabled cross-platform data sharing between ROS and medical image computing software. This will allow rapid and seamless integration of advanced image-based planning/navigation offered by the medical image computing software such as 3D Slicer into ROS-based surgical robot systems.

HTC Vive MeVisLab integration via OpenVR for medical applications

Virtual Reality, an immersive technology that replicates an environment via computer-simulated reality, gets a lot of attention in the entertainment industry. However, VR has also great potential in other areas, like the medical domain, Examples are intervention planning, training and simulation. This is especially of use in medical operations, where an aesthetic outcome is important, like for facial surgeries. Alas, importing medical data into Virtual Reality devices is not necessarily trivial, in particular, when a direct connection to a proprietary application is desired. Moreover, most researcher do not build their medical applications from scratch, but rather leverage platforms like MeVisLab, MITK, OsiriX or 3D Slicer. These platforms have in common that they use libraries like ITK and VTK, and provide a convenient graphical interface. However, ITK and VTK do not support Virtual Reality directly. In this study, the usage of a Virtual Reality device for medical data under the MeVisLab platform is presented. The OpenVR library is integrated into the MeVisLab platform, allowing a direct and uncomplicated usage of the head mounted display HTC Vive inside the MeVisLab platform. Medical data coming from other MeVisLab modules can directly be connected per drag-and-drop to the Virtual Reality module, rendering the data inside the HTC Vive for immersive virtual reality inspection.