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Spinal deformation during surgical intervention (caused by patient positioning and/or the correction of malalignment) confounds conventional navigation due to the assumptions of rigid transformation. Moreover, the ability to accurately quantify spinal alignment in the operating room would provide an assessment of the surgical product via metrics that correlate with clinical outcomes.A method for deformable 3D-2D registration of preoperative CT to intraoperative long-length tomosynthesis images is reported for an accurate 3D evaluation of device placement in the presence of spinal deformation and automated evaluation of global spinal alignment (GSA).Long-length tomosynthesis ("Long Film," LF) images were acquired using an O-arm imaging system (Medtronic, Minneapolis USA). A deformable 3D-2D patient registration was developed using multi-scale masking (proceeding from the full-length image to local subvolumes about each vertebra) to transform vertebral labels and planning information from preoperative CT to the LF images. Automatic measurement of GSA (main thoracic kyphosis [MThK] and lumbar lordosis [LL]) was obtained using a spline fit to registered labels. The "Known-Component Registration" method for device registration was adapted to the multi-scale process for 3D device localization from orthogonal LF images. The multi-scale framework was evaluated using a deformable spine phantom in which pedicle screws were inserted, and deformations were induced over a range in LL ∼25°-80°. Further validation was carried out in a cadaver study with implanted pedicle screws and a similar range of spinal deformation. The accuracy of patient and device registration was evaluated in terms of 3D translational error and target registration error, respectively, and the accuracies of automatic GSA measurements were compared to manual annotation.Phantom studies demonstrated accurate registration via the multi-scale framework for all vertebral levels in both the neutral and deformed spine: median (interquartile range, IQR) patient registration error was 1.1 mm (0.7-1.9 mm IQR). Automatic measures of MThK and LL agreed with manual delineation within -1.1° ± 2.2° and 0.7° ± 2.0° (mean and standard deviation), respectively. Device registration error was 0.7 mm (0.4-1.0 mm IQR) at the screw tip and 0.9° (1.0°-1.5°) about the screw trajectory. Deformable 3D-2D registration significantly outperformed conventional rigid registration (p 0.05), which exhibited device registration errors of 2.1 mm (0.8-4.1 mm) and 4.1° (1.2°-9.5°). Cadaver studies verified performance under realistic conditions, demonstrating patient registration error of 1.6 mm (0.9-2.1 mm); MThK within -4.2° ± 6.8° and LL within 1.7° ± 3.5°; and device registration error of 0.8 mm (0.5-1.9 mm) and 0.7° (0.4°-1.2°) for the multi-scale deformable method, compared to 2.5 mm (1.0-7.9 mm) and 2.3° (1.6°-8.1°) for rigid registration (p 0.05).The deformable 3D-2D registration framework leverages long-length intraoperative imaging to achieve accurate patient and device registration over the extended lengths of the spine (up to 64 cm) even with strong anatomical deformation. The method offers a new means for the quantitative validation of spinal correction (intraoperative GSA measurement) and the 3D verification of device placement in comparison to preoperative images and planning data.

BACKGROUND: Indirect detection flat-panel detectors (FPDs) consisting of hydrogenated amorphous silicon (a-Si:H) thin-film transistors (TFTs) are a prevalent technology for digital x-ray imaging. However, their performance is challenged in applications requiring low exposure levels, high spatial resolution, and high frame rate. Emerging FPD designs using metal oxide TFTs may offer potential performance improvements compared to FPDs based on a-Si:H TFTs. PURPOSE: This work investigates the imaging performance of a new indium gallium zinc oxide (IGZO) TFT-based detector in 2D fluoroscopy and 3D cone-beam CT (CBCT). METHODS: The new FPD consists of a sensor array combining IGZO TFTs with a-Si:H photodiodes and a 0.7-mm thick CsI:Tl scintillator. The FPD was implemented on an x-ray imaging bench with system geometry emulating intraoperative CBCT. A conventional FPD with a-Si:H TFTs and a 0.6-mm thick CsI:Tl scintillator was similarly implemented as a basis of comparison. 2D imaging performance was characterized in terms of electronic noise, sensitivity, linearity, lag, spatial resolution (modulation transfer function, MTF), image noise (noise-power spectrum, NPS), and detective quantum efficiency (DQE) with entrance air kerma (EAK) ranging from 0.3 to [Formula: see text]. 3D imaging performance was evaluated in terms of the 3D MTF and noise-equivalent quanta (NEQ), soft-tissue contrast-to-noise ratio (CNR), and image quality evident in anthropomorphic phantoms for a range of anatomical sites and dose, with weighted air kerma, [Formula: see text] , ranging from 0.8 to 4.9 mGy. RESULTS: The 2D imaging performance of the IGZO-based FPD exhibited up to [Formula: see text] lower electronic noise than the a-Si:H FPD at matched pixel pitch. Furthermore, the IGZO FPD exhibited ~27% increase in mid-frequency DQE [Formula: see text] at matched pixel size and dose [Formula: see text] and ~11% increase after adjusting for differences in scintillator thickness. 2D spatial resolution was limited by the scintillator for each FPD. The IGZO-based FPD demonstrated improved 3D NEQ at all spatial frequencies in both head [Formula: see text] increase for all dose levels) and body ([Formula: see text] increase for [Formula: see text]) imaging scenarios. These characteristics translated to improved low-contrast visualization in anthropomorphic phantoms, demonstrating [Formula: see text] improvement in CNR and extension of the low-dose range for which the detector is input-quantum limited. CONCLUSION: The IGZO-based FPD demonstrated improvements in electronic noise, image lag, and NEQ that translated to measurable improvements in 2D and 3D imaging performance compared to a conventional FPD based on a-Si:H TFTs. The improvements are most beneficial for 2D or 3D imaging scenarios involving low-dose and/or high-frame rate.

PURPOSE. Deep brain stimulation is a neurosurgical procedure used in treatment of a growing spectrum of movement disorders. Inaccuracies in electrode placement, however, can result in poor symptom control or adverse effects and confound variability in clinical outcomes. A deformable 3D-2D registration method is presented for high-precision 3D guidance of neuroelectrodes. METHODS. The approach employs a model-based, deformable algorithm for 3D-2D image registration. Variations in lead design are captured in a parametric 3D model based on a B-spline curve. The registration is solved through iterative optimization of 16 degrees-of-freedom that maximize image similarity between the 2 acquired radiographs and simulated forward projections of the neuroelectrode model. The approach was evaluated in phantom models with respect to pertinent imaging parameters, including view selection and imaging dose. RESULTS. The results demonstrate an accuracy of (0.2 ± 0.2) mm in 3D localization of individual electrodes. The solution was observed to be robust to changes in pertinent imaging parameters, which demonstrate accurate localization with ≥20° view separation and at 1/10(th) the dose of a standard fluoroscopy frame. CONCLUSIONS. The presented approach provides the means for guiding neuroelectrode placement from 2 low-dose radiographic images in a manner that accommodates potential deformations at the target anatomical site. Future work will focus on improving runtime though learning-based initialization, application in reducing reconstruction metal artifacts for 3D verification of placement, and extensive evaluation in clinical data from an IRB study underway.

PURPOSE: Manual surgical manipulation of the tibia and fibula is necessary to properly align and reduce the space in ankle fractures involving sprain of the distal tibiofibular syndesmosis. However, manual reduction is highly variable and can result in malreduction in about half of the cases. Therefore, we are developing an image-guided robotic assistant to improve reduction accuracy. The purpose of this study is to quantify the forces associated with reduction of the ankle syndesmosis to define the requirements for our robot design. METHODS: Using a cadaveric specimen, we designed a fixture jig to fix the tibia securely on the operating table. We also designed a custom fibula grasping plate to which a force–torque measuring device is attached. The surgeon manually reduced the fibula utilizing this construct while translational and rotational forces along with displacement were being measured. This was first performed on an intact ankle without ligament injury and after the syndesmosis ligaments were cut. RESULTS: Six manipulation techniques were performed on the three principal directions of reduction at the cadaveric ankle. The results demonstrated the maximum force applied to the lateral direction to be 96.0 N with maximum displacement of 8.5 mm, applied to the anterior–posterior direction to be 71.6 N with maximum displacement of 10.7 mm, and the maximum torque applied to external–internal rotation to be 2.5 Nm with maximum rotation of 24.6°. CONCLUSIONS: The specific forces needed to perform the distal tibiofibular syndesmosis manipulation are not well understood. This study quantified these manipulation forces needed along with their displacement for accurate reduction of ankle syndesmosis. This is a necessary first step to help us define the design requirements of our robotic assistance from the aspects of forces and displacements.