Deformable registration of preoperative MR and intraoperative long-length tomosynthesis images for guidance of spine surgery via image synthesis.

PURPOSE: Improved integration and use of preoperative imaging during surgery hold significant potential for enhancing treatment planning and instrument guidance through surgical navigation. Despite its prevalent use in diagnostic settings, MR imaging is rarely used for navigation in spine surgery. This study aims to leverage MR imaging for intraoperative visualization of spine anatomy, particularly in cases where CT imaging is unavailable or when minimizing radiation exposure is essential, such as in pediatric surgery. METHODS: This work presents a method for deformable 3D-2D registration of preoperative MR images with a novel intraoperative long-length tomosynthesis imaging modality (viz., Long-Film [LF]). A conditional generative adversarial network is used to translate MR images to an intermediate bone image suitable for registration, followed by a model-based 3D-2D registration algorithm to deformably map the synthesized images to LF images. The algorithm's performance was evaluated on cadaveric specimens with implanted markers and controlled deformation, and in clinical images of patients undergoing spine surgery as part of a large-scale clinical study on LF imaging. RESULTS: The proposed method yielded a median 2D projection distance error of 2.0 mm (interquartile range [IQR]: 1.1-3.3 mm) and a 3D target registration error of 1.5 mm (IQR: 0.8-2.1 mm) in cadaver studies. Notably, the multi-scale approach exhibited significantly higher accuracy compared to rigid solutions and effectively managed the challenges posed by piecewise rigid spine deformation. The robustness and consistency of the method were evaluated on clinical images, yielding no outliers on vertebrae without surgical instrumentation and 3% outliers on vertebrae with instrumentation. CONCLUSIONS: This work constitutes the first reported approach for deformable MR to LF registration based on deep image synthesis. The proposed framework provides access to the preoperative annotations and planning information during surgery and enables surgical navigation within the context of MR images and/or dual-plane LF images.

Subchondral bone in knee osteoarthritis: bystander or treatment target?

The subchondral bone is an important structural component of the knee joint relevant for osteoarthritis (OA) incidence and progression once disease is established. Experimental studies have demonstrated that subchondral bone changes are not simply the result of altered biomechanics, i.e., pathologic loading. In fact, subchondral bone alterations have an impact on joint homeostasis leading to articular cartilage loss already early in the disease process. This narrative review aims to summarize the available and emerging imaging techniques used to evaluate knee OA-related subchondral bone changes and their potential role in clinical trials of disease-modifying OA drugs (DMOADs). Radiographic fractal signature analysis has been used to quantify OA-associated changes in subchondral texture and integrity. Cross-sectional modalities such as cone-beam computed tomography (CT), contrast-enhanced cone beam CT, and micro-CT can also provide high-resolution imaging of the subchondral trabecular morphometry. Magnetic resonance imaging (MRI) has been the most commonly used advanced imaging modality to evaluate OA-related subchondral bone changes such as bone marrow lesions and altered trabecular bone texture. Dual-energy X-ray absorptiometry can provide insight into OA-related changes in periarticular subchondral bone mineral density. Positron emission tomography, using physiological biomarkers of subchondral bone regeneration, has provided additional insight into OA pathogenesis. Finally, artificial intelligence algorithms have been developed to automate some of the above subchondral bone measurements. This paper will particularly focus on semiquantitative methods for assessing bone marrow lesions and their utility in identifying subjects at risk of symptomatic and structural OA progression, and evaluating treatment responses in DMOAD clinical trials.

Musculoskeletal CT Imaging: State-of-the-Art Advancements and Future Directions.

CT is one of the most widely used modalities for musculoskeletal imaging. Recent advancements in the field include the introduction of four-dimensional CT, which captures a CT image during motion; cone-beam CT, which uses flat-panel detectors to capture the lower extremities in weight-bearing mode; and dual-energy CT, which operates at two different x-ray potentials to improve the contrast resolution to facilitate the assessment of tissue material compositions such as tophaceous gout deposits and bone marrow edema. Most recently, photon-counting CT (PCCT) has been introduced. PCCT is a technique that uses photon-counting detectors to produce an image with higher spatial and contrast resolution than conventional multidetector CT systems. In addition, postprocessing techniques such as three-dimensional printing and cinematic rendering have used CT data to improve the generation of both physical and digital anatomic models. Last, advancements in the application of artificial intelligence to CT imaging have enabled the automatic evaluation of musculoskeletal pathologies. In this review, the authors discuss the current state of the above CT technologies, their respective advantages and disadvantages, and their projected future directions for various musculoskeletal applications.

Combining physics-based models with deep learning image synthesis and uncertainty in intraoperative cone-beam CT of the brain.

BACKGROUND: Image-guided neurosurgery requires high localization and registration accuracy to enable effective treatment and avoid complications. However, accurate neuronavigation based on preoperative magnetic resonance (MR) or computed tomography (CT) images is challenged by brain deformation occurring during the surgical intervention. PURPOSE: To facilitate intraoperative visualization of brain tissues and deformable registration with preoperative images, a 3D deep learning (DL) reconstruction framework (termed DL-Recon) was proposed for improved intraoperative cone-beam CT (CBCT) image quality. METHODS: The DL-Recon framework combines physics-based models with deep learning CT synthesis and leverages uncertainty information to promote robustness to unseen features. A 3D generative adversarial network (GAN) with a conditional loss function modulated by aleatoric uncertainty was developed for CBCT-to-CT synthesis. Epistemic uncertainty of the synthesis model was estimated via Monte Carlo (MC) dropout. Using spatially varying weights derived from epistemic uncertainty, the DL-Recon image combines the synthetic CT with an artifact-corrected filtered back-projection (FBP) reconstruction. In regions of high epistemic uncertainty, DL-Recon includes greater contribution from the FBP image. Twenty paired real CT and simulated CBCT images of the head were used for network training and validation, and experiments evaluated the performance of DL-Recon on CBCT images containing simulated and real brain lesions not present in the training data. Performance among learning- and physics-based methods was quantified in terms of structural similarity (SSIM) of the resulting image to diagnostic CT and Dice similarity metric (DSC) in lesion segmentation compared to ground truth. A pilot study was conducted involving seven subjects with CBCT images acquired during neurosurgery to assess the feasibility of DL-Recon in clinical data. RESULTS: CBCT images reconstructed via FBP with physics-based corrections exhibited the usual challenges to soft-tissue contrast resolution due to image non-uniformity, noise, and residual artifacts. GAN synthesis improved image uniformity and soft-tissue visibility but was subject to error in the shape and contrast of simulated lesions that were unseen in training. Incorporation of aleatoric uncertainty in synthesis loss improved estimation of epistemic uncertainty, with variable brain structures and unseen lesions exhibiting higher epistemic uncertainty. The DL-Recon approach mitigated synthesis errors while maintaining improvement in image quality, yielding 15%-22% increase in SSIM (image appearance compared to diagnostic CT) and up to 25% increase in DSC in lesion segmentation compared to FBP. Clear gains in visual image quality were also observed in real brain lesions and in clinical CBCT images. CONCLUSIONS: DL-Recon leveraged uncertainty estimation to combine the strengths of DL and physics-based reconstruction and demonstrated substantial improvements in the accuracy and quality of intraoperative CBCT. The improved soft-tissue contrast resolution could facilitate visualization of brain structures and support deformable registration with preoperative images, further extending the utility of intraoperative CBCT in image-guided neurosurgery.

Sensitivity of the stress field of the proximal femur predicted by CT-based FE analysis to modeling uncertainties.

Proximal femur anatomy and bone mineral density vary widely among individuals, precluding the use of one predefined finite element (FE) model to determine the stress field for all proximal femurs. This variability poses a challenge in current prosthetic hip design approach. Given the numerous options for generating computed tomography (CT)-based FE models, selecting the best methods for defining the mechanical behavior of the proximal femur is difficult. In this study, a combination of computational and experimental approaches was used to explore the susceptibility of the predicted stress field of the proximal femur to different combinations of density-elasticity relationships, element type, element size, and calibration error. Our results suggest that FE models with first-order voxelized elements generated by the Keyak and Falkinstein density-elasticity relationship or quadratic tetrahedral elements generated by the Morgan density-elasticity relationship lead to accurate estimations of the mechanical behavior of human femurs. Other combinations of element size, element type, and mathematical relationships produce less accurate results, especially in the cortical bone of the femoral neck and calcar region. The voxelized model was more susceptible to variation of element size and density-elasticity relationships than FE models with quadratic tetrahedral elements. Regardless of element type, the stress fields predicted by the Keyak and Falkinstein and the Morgan relationships were the most robust to calibration error when deriving material density from CT-generated Hounsfield data. These results provide insight into the implementation of a robust platform for designing patient-specific implants capable of maintaining or modifying the stress in bones.

Association Between Knee Anatomic Metrics and Biomechanics for Male Soldiers Landing With Load.

BACKGROUND: Anterior cruciate ligament (ACL) injury is a military occupational hazard that may be attributed to an individual's knee biomechanics and joint anatomy. This study sought to determine if greater flexion when landing with load resulted in knee biomechanics thought to decrease ACL injury risk and whether knee biomechanics during landing relate to knee anatomic metrics. HYPOTHESIS: Anatomic metrics regarding the slope and concavity of the tibial plateau will exhibit a significant relation to the increased anterior shear force on the knee and decreased knee flexion posture during landing with body-borne load. STUDY DESIGN: Descriptive laboratory study. METHODS: Twenty male military personnel completed a drop landing task with 3 load conditions: light (~6 kg), medium (15% body weight), and heavy (30% body weight). Participants were divided into groups based on knee flexion exhibited when landing with the heavy load (high- and low-Δflexion). Tibial slopes and depth were measured on weightbearing volumetric images of the knee obtained with a prototype cone beam computed tomography system. Knee biomechanics were submitted to a linear mixed model to evaluate the effect of landing group and load, with the anatomic metrics considered covariates. RESULTS: Load increased peak proximal anterior tibial shear force (P = .034), knee flexion angle (P = .024), and moment (P = .001) during landing. Only the high flexion group increased knee flexion (P < .001) during weighted landings with medium and heavy loads. The low flexion group used greater knee abduction angle (P = .030) and peak proximal anterior tibial shear force (P = .034) when landing with load. Anatomic metrics did not differ between groups, but ratio of medial-to-lateral tibial slope and medial tibial depth predicted peak proximal anterior tibial shear force (P = .009) and knee flexion (P = .034) during landing, respectively. CONCLUSION: Increasing knee flexion is an attainable strategy to mitigate risk of ACL injury, but certain individuals may be predisposed to knee forces and biomechanics that load the ACL during weighted landings. CLINICAL RELEVANCE: The ability to screen individuals for anatomic metrics that predict knee flexion may identify soldiers and athletes who require additional training to mitigate the risk of lower extremity injury.

Cone-beam CT measurements of distal tibio-fibular syndesmosis in asymptomatic uninjured ankles: does weight-bearing matter?

OBJECTIVE: To evaluate the influence of weight-bearing (WB) load in standard axial ankle syndesmotic measurements using cone beam CT (CBCT) examination of asymptomatic uninjured ankles. MATERIALS AND METHODS: In this IRB approved, prospective study, patients with previous unilateral ankle fractures were recruited. We simultaneously scanned the injured ankles and asymptomatic contralateral ankles of 27 patients in both WB and NWB modes. For this study, only asymptomatic contralateral ankles with normal plain radiographs were included. Twelve standardized syndesmosis measurements at two axial planes (10 mm above the tibial plafond and 5 mm below the talar dome) were obtained by two expert readers using a custom CBCT viewer with the capability for geometric measurements between user-identified anatomical landmarks. Inter-reader reliability between two readers was obtained using the intra-class correlation coefficient (ICC). We compared the WB and NWB measurements using paired t test. RESULTS: Significant agreement was observed between two readers for both WB and NWB measurements (p <0.05). ICC values for WB and NWB measurements had a range of 50-95 and 31-71 respectively. Mean values of the medial clear space on WB images (1.75, 95% confidence interval [95% CI]: 1.6, 1.9) were significantly lower than on NWB images (2.05, 95% CI: 1.8, 2.2) measurements (p <0.001). There was no significant difference between the remaining WB and NWB measurements. CONCLUSION: Measurements obtained from WB images are reliable. Except for the medial clear space, no significant difference in syndesmotic measurements were observed during the WB mode of CBCT acquisition, implying that the tibio-fibular relationship remains unchanged when the physiological axial weight-bearing load is applied.

Flexible Adult Acquired Flatfoot Deformity: Comparison Between Weight-Bearing and Non-Weight-Bearing Measurements Using Cone-Beam Computed Tomography.

BACKGROUND: The 3-dimensional nature of adult acquired flatfoot deformity can be challenging to characterize using radiographs. We tested the hypothesis that measurements on weight-bearing (WB) cone-beam computed tomography (CT) images were more useful for demonstrating the severity of the deformity than non-weight-bearing (NWB) measurements. METHODS: We prospectively enrolled 12 men and 8 women (mean age, 52 years; range, 20 to 88 years) with flexible adult acquired flatfoot deformity. The subjects underwent cone-beam CT while standing (WB) and seated (NWB), and images were assessed in the sagittal, coronal, and axial planes by 3 independent observers who performed multiple measurements. Intraobserver and interobserver reliabilities were assessed with the Pearson or Spearman correlation and the intraclass correlation coefficient (ICC), respectively. Measurements were compared using paired Student t tests or Wilcoxon rank-sum tests. P < 0.05 was considered significant. RESULTS: We found that overall the measurements had substantial intraobserver and interobserver reliability on both the NWB images (mean ICC, 0.80; range, 0.49 to 0.99) and the WB images (mean ICC, 0.81; range, 0.39 to 0.99). Eighteen of 19 measurements differed between WB and NWB cone-beam CT images, with more pronounced deformities on the WB images. The most reliable measurements, based on intraobserver and interobserver reliabilities and the difference between WB and NWB images, were the medial cuneiform-to-floor distance, which averaged 29 mm (95% confidence interval [CI] = 28 to 31 mm) on the NWB images and 18 mm (95% CI = 17 to 19 mm) on the WB images, and the forefoot arch angle (mean, 13° [95% CI = 12° to 15°] and 3.0° [95% CI = 1.4° to 4.6°], respectively) in the coronal view and the cuboid-to-floor distance (mean, 22 mm [95% CI = 21 to 23 mm] and 17 mm [95% CI = 16 to 18 mm], respectively) and the navicular-to-floor distance (mean, 38 mm [95% CI = 36 to 40 mm] and 23 mm [95% CI = 22 to 25 mm], respectively) in the sagittal view. CONCLUSIONS: Measurements analogous to traditional radiographic parameters of adult acquired flatfoot deformity are obtainable using high-resolution cone-beam CT. Compared with NWB images, WB images better demonstrated the severity of osseous derangement in patients with flexible adult acquired flatfoot deformity. LEVEL OF EVIDENCE: Diagnostic Level II. See Instructions for Authors for a complete description of levels of evidence.

Image quality of cone beam computed tomography for evaluation of extremity fractures in the presence of metal hardware: visual grading characteristics analysis.

OBJECTIVE: To evaluate image quality and interobserver reliability of a novel cone-beam CT (CBCT) scanner in comparison with plain radiography for assessment of fracture healing in the presence of metal hardware. METHODS: In this prospective institutional review board-approved Health Insurance Portability and Accountability Act of 1996-complaint study, written informed consent was obtained from 27 patients (10 females and 17 males; mean age 44 years, age range 21-83 years) with either upper or lower extremity fractures, and with metal hardware, who underwent CBCT scans and had a clinical radiograph of the affected part. Images were assessed by two independent observers for quality and interobserver reliability for seven visualization tasks. Visual grading characteristic (VGC) curve analysis determined the differences in image quality between CBCT and plain radiography. Interobserver agreement was calculated using Pearson's correlation coefficient. RESULTS: VGC results displayed preference of CBCT images to plain radiographs in terms of visualizing (1) cortical and (2) trabecular bones; (3) fracture line; (4) callus formation; (5) bridging ossification; and (6) screw thread-bone interface and its inferiority to plain radiograph in the visualization of (7) large metallic side plate contour with strong interobserver correlation (p-value < 0.05), except for visualizing large metallic side plate contour. CONCLUSION: For evaluation of fracture healing in the presence of metal hardware, CBCT image quality is preferable to plain radiograph for all visualization tasks, except for large metallic side plate contours. Advances in knowledge: CBCT has the potential to be a good diagnostic alternative to plain radiographs in evaluation of fracture healing in the presence of metal hardware.