Robotic intrafractional US guidance for liver SABR: System design, beam avoidance, and clinical imaging.

PURPOSE: To present a system for robotic 4D ultrasound (US) imaging concurrent with radiotherapy beam delivery and estimate the proportion of liver stereotactic ablative body radiotherapy (SABR) cases in which robotic US image guidance can be deployed without interfering with clinically used VMAT beam configurations. METHODS: The image guidance hardware comprises a 4D US machine, an optical tracking system for measuring US probe pose, and a custom-designed robot for acquiring hands-free US volumes. In software, a simulation environment incorporating the LINAC, couch, planning CT, and robotic US guidance hardware was developed. Placement of the robotic US hardware was guided by a target visibility map rendered on the CT surface by using the planning CT to simulate US propagation. The visibility map was validated in a prostate phantom and evaluated in patients by capturing live US from imaging positions suggested by the visibility map. In 20 liver SABR patients treated with VMAT, the simulation environment was used to virtually place the robotic hardware and US probe. Imaging targets were either planning target volumes (PTVs, range 5.9-679.5 ml) or gross tumor volumes (GTVs, range 0.9-343.4 ml). Presence or absence of mechanical interference with LINAC, couch, and patient body as well as interferences with treated beams was recorded. RESULTS: For PTV targets, robotic US guidance without mechanical interference was possible in 80% of the cases and guidance without beam interference was possible in 60% of the cases. For the smaller GTV targets, these proportions were 95% and 85%, respectively. GTV size (1/20), elongated shape (1/20), and depth (1/20) were the main factors limiting the availability of noninterfering imaging positions. The robotic US imaging system was deployed in two liver SABR patients during CT simulation with successful acquisition of 4D US sequences in different imaging positions. CONCLUSIONS: This study indicates that for VMAT liver SABR, robotic US imaging of a relevant internal target may be possible in 85% of the cases while using treatment plans currently deployed in the clinic. With beam replanning to account for the presence of robotic US guidance, intrafractional US may be an option for 95% of the liver SABR cases.

Interactive initialization of 2D/3D rigid registration.

PURPOSE: Registration is one of the key technical components in an image-guided navigation system. A large number of 2D/3D registration algorithms have been previously proposed, but have not been able to transition into clinical practice. The authors identify the primary reason for the lack of adoption with the prerequisite for a sufficiently accurate initial transformation, mean target registration error of about 10 mm or less. In this paper, the authors present two interactive initialization approaches that provide the desired accuracy for x-ray/MR and x-ray/CT registration in the operating room setting. METHODS: The authors have developed two interactive registration methods based on visual alignment of a preoperative image, MR, or CT to intraoperative x-rays. In the first approach, the operator uses a gesture based interface to align a volume rendering of the preoperative image to multiple x-rays. The second approach uses a tracked tool available as part of a navigation system. Preoperatively, a virtual replica of the tool is positioned next to the anatomical structures visible in the volumetric data. Intraoperatively, the physical tool is positioned in a similar manner and subsequently used to align a volume rendering to the x-ray images using an augmented reality (AR) approach. Both methods were assessed using three publicly available reference data sets for 2D/3D registration evaluation. RESULTS: In the authors' experiments, the authors show that for x-ray/MR registration, the gesture based method resulted in a mean target registration error (mTRE) of 9.3 ± 5.0 mm with an average interaction time of 146.3 ± 73.0 s, and the AR-based method had mTREs of 7.2 ± 3.2 mm with interaction times of 44 ± 32 s. For x-ray/CT registration, the gesture based method resulted in a mTRE of 7.4 ± 5.0 mm with an average interaction time of 132.1 ± 66.4 s, and the AR-based method had mTREs of 8.3 ± 5.0 mm with interaction times of 58 ± 52 s. CONCLUSIONS: Based on the authors' evaluation, the authors conclude that the registration approaches are sufficiently accurate for initializing 2D/3D registration in the OR setting, both when a tracking system is not in use (gesture based approach), and when a tracking system is already in use (AR based approach).

Multiple-object 2-D-3-D registration for noninvasive pose identification of fracture fragments.

This paper presents a multiple-object 2-D-3-D registration technique for noninvasively identifying the poses of fracture fragments in the space of a preoperative treatment plan. The plan is made by manipulating and aligning computer models of individual fracture fragments that are segmented from a diagnostic computed tomography. The registration technique iteratively updates the treatment plan and matches its digitally reconstructed radiographs to a small number of intraoperative fluoroscopic images. The proposed approach combines an image similarity metric that integrates edge information with mutual information, and a global-local optimization scheme, to deal with challenges associated with the registration of multiple small fragments and limited imaging orientations in the operating room. The method is easy to use as minimum user interaction is required. Experiments on simulated fractures and two distal radius fracture phantoms demonstrate clinically acceptable target registration errors with capture range as large as 10 mm.

A new representation of intensity atlas for GPU-accelerated instance generation.

Fast instance generation is a key requirement in atlas-based registration and other problems that need a large number of atlas instances. This paper describes a new method to represent and construct intensity atlases. Both geometry and intensity information are represented using B-spline deformation lattices; intensities are approximated using the multi-level B-spline approximation algorithm during model creation and the parallel computation capability of modern graphics processing units is used to accelerate the process of instance generation. Experiments with distal radius CTs show that, with a coefficients-to-voxels ratio of 0.16, intensities can be approximated up to an average accuracy of 2 ± 17 grey-levels (out of 3072 total grey-levels), and instances of resolution 256×256×200 can be produced in a rate of 25 instances per second with a GeForce GTX 285 video card, which is about 500 times performance improvement over the traditional method that uses plain CPU.

Registration of a statistical shape model of the lumbar spine to 3D ultrasound images.

MOTIVATION: Spinal needle injections are technically demanding procedures. The use of ultrasound image guidance without prior CT and MR imagery promises to improve the efficacy and safety of these procedures in an affordable manner. METHODOLOGY: We propose to create a statistical shape model of the lumbar spine and warp this atlas to patient-specific ultrasound images during the needle placement procedure. From CT image volumes of 35 patients, statistical shape model of the L3 vertebra is built, including mean shape and main modes of variation. This shape model is registered to the ultrasound data by simultaneously optimizing the parameters of the model and its relative pose. Ground-truth data was established by printing 3D anatomical models of 3 patients using a rapid prototyping. CT and ultrasound data of these models were registered using fiducial markers. RESULTS: Pairwise registration of the statistical shape model and 3D ultrasound images led to a mean target registration error of 3.4 mm, while 81% of all cases yielded clinically acceptable accuracy below the 3.5 mm threshold.

Prediction of the repair surface over cartilage defects: a comparison of three methods in a sheep model.

Defects in articular cartilage can be repaired through osteochondral transplantation (mosaic arthroplasty), where osteochondral plugs from non-weight-bearing areas of the joint are transferred to the defect site. Incongruity between the plug surface and the adjacent cartilage results in increased contact pressures and poorer outcomes. We compare three methods to predict the desired repair surface for use in computer-assisted mosaic arthroplasty: manual estimation, a cubic spline surface, and a statistical shape atlas of the knee. The cubic spline was found to most accurately match the pre-impact cartilage surface; the atlas was found to match least accurately.

A robust technique for 2D-3D registration.

A robust 2D-3D registration method with a wide capture range is presented. The method registers pre-operatively collected 3D computed tomography (CT) data sets of a single bone fragment to its intra-operative fluoroscope images. The registration technique relies on hardware rendering of CT data on consumer-grade graphics cards to generate digitally reconstructed radiographs (DRRs) in real time. We also employ unscented Kalman filter to solve for the non-linear dynamics governing this 2D-3D registration problem. The method is validated on phantom models of three different anatomies, namely scaphoid, pelvis and femur. We show that, under the same testing conditions, our proposed technique outperforms the conventional simplex-based method in capture range and robustness while providing comparable accuracy and computation time.

A new method for CT to fluoroscope registration based on unscented Kalman filter.

We propose a new method for CT to fluoroscope registration which is very robust and has a wide capture range. The method relies on the Unscented Kalman Filter to search for an optimal registration solution and on modern commodity graphics cards for fast generation of digitally reconstructed radiographs. We extensively test our method using three different anatomical data sets and compare it with an implementation of the commonly used simplex-based method. The experimental results firmly support that, under the same testing conditions, our proposed technique outperforms the simplex-based method in capture range while providing comparable accuracy and computation time.