Single fluoroscopic image based 2D/3D reconstruction of a scaled, patient-specific vertebral model

Purpose Accurate three-dimensional (3D) models of lumbar vertebrae can enable image-based 3D kinematic analysis. The common approach to derive 3D models is by direct segmentation of CT or MRI datasets. However, these have the disadvantages that they are expensive, timeconsuming and/or induce high-radiation doses to the patient. In this study, we present a technique to automatically reconstruct a scaled 3D lumbar vertebral model from a single two-dimensional (2D) lateral fluoroscopic image. Methods Our technique is based on a hybrid 2D/3D deformable registration strategy combining a landmark-to-ray registration with a statistical shape model-based 2D/3D reconstruction scheme. Fig. 1 shows different stages of the reconstruction process. Four cadaveric lumbar spine segments (total twelve lumbar vertebrae) were used to validate the technique. To evaluate the reconstruction accuracy, the surface models reconstructed from the lateral fluoroscopic images were compared to the associated ground truth data derived from a 3D CT-scan reconstruction technique. For each case, a surface-based matching was first used to recover the scale and the rigid transformation between the reconstructed surface model Results Our technique could successfully reconstruct 3D surface models of all twelve vertebrae. After recovering the scale and the rigid transformation between the reconstructed surface models and the ground truth models, the average error of the 2D/3D surface model reconstruction over the twelve lumbar vertebrae was found to be 1.0 mm. The errors of reconstructing surface models of all twelve vertebrae are shown in Fig. 2. It was found that the mean errors of the reconstructed surface models in comparison to their associated ground truths after iterative scaled rigid registrations ranged from 0.7 mm to 1.3 mm and the rootmean squared (RMS) errors ranged from 1.0 mm to 1.7 mm. The average mean reconstruction error was found to be 1.0 mm. Conclusion An accurate, scaled 3D reconstruction of the lumbar vertebra can be obtained from a single lateral fluoroscopic image using a statistical shape model based 2D/3D reconstruction technique. Future work will focus on applying the reconstructed model for 3D kinematic analysis of lumbar vertebrae, an extension of our previously-reported imagebased kinematic analysis. The developed method also has potential applications in surgical planning and navigation.

Using rapid prototyping molds to create patient specific polymethylmethacrylate implants in cranioplasty

Cranioplasty is a commonly performed procedure. Outcomes can be improved by the use of patient specific implants, however, high costs limit their accessibility. This paper presents a low cost alternative technique to create patient specific polymethylmethacrylate (PMMA) implants using rapid prototyped mold template. We used available patient's CT-scans, one dataset without craniotomy and one with craniotomy, for computer-assisted design of a 3D mold template, which itself can be brought into the operating room and be used for fast and easy building of a PMMA implant. We applied our solution to three patients with positive outcomes and no complications.

Coupling biomechanics to a cellular level model: An approach to patient-specific image driven multi-scale and multi-physics tumor simulation

Modeling of tumor growth has been performed according to various approaches addressing different biocomplexity levels and spatiotemporal scales. Mathematical treatments range from partial differential equation based diffusion models to rule-based cellular level simulators, aiming at both improving our quantitative understanding of the underlying biological processes and, in the mid- and long term, constructing reliable multi-scale predictive platforms to support patient-individualized treatment planning and optimization. The aim of this paper is to establish a multi-scale and multi-physics approach to tumor modeling taking into account both the cellular and the macroscopic mechanical level. Therefore, an already developed biomodel of clinical tumor growth and response to treatment is self-consistently coupled with a biomechanical model. Results are presented for the free growth case of the imageable component of an initially point-like glioblastoma multiforme tumor. The composite model leads to significant tumor shape corrections that are achieved through the utilization of environmental pressure information and the application of biomechanical principles. Using the ratio of smallest to largest moment of inertia of the tumor material to quantify the effect of our coupled approach, we have found a tumor shape correction of 20\% by coupling biomechanics to the cellular simulator as compared to a cellular simulation without preferred growth directions. We conclude that the integration of the two models provides additional morphological insight into realistic tumor growth behavior. Therefore, it might be used for the development of an advanced oncosimulator focusing on tumor types for which morphology plays an important role in surgical and/or radio-therapeutic treatment planning.

PS-GANS: A Patient-Specific, Gravity Assisted Navigation System for Acetabular Cup Placement

In this paper we propose a new system that allows reliable acetabular cup placement when the THA is operated in lateral approach. Conceptually it combines the accuracy of computer-generated patient-specific morphology information with an easy-to-use mechanical guide, which effectively uses natural gravity as the angular reference. The former is achieved by using a statistical shape model-based 2D-3D reconstruction technique that can generate a scaled, patient-specific 3D shape model of the pelvis from a single conventional anteroposterior (AP) pelvic X-ray radiograph. The reconstructed 3D shape model facilitates a reliable and accurate co-registration of the mechanical guide with the patient’s anatomy in the operating theater. We validated the accuracy of our system by conducting experiments on placing seven cups to four pelvises with different morphologies. Taking the measurements from an image-free navigation system as the ground truth, our system showed an average accuracy of 2.1 ±0.7 o for inclination and an average accuracy of 1.2 ±1.4 o for anteversion.

Intraoperative Patient-Specific Reconstruction of Partial Bone Flap Defects After Convexity Meningioma Resection

OBJECTIVE: To evaluate implant accuracy and cosmetic outcome of a new intraoperative patient-specific cranioplasty method after convexity meningioma resection. METHODS: The patient's own bone flap served as a template to mold a negative form with the use of polymethyl methacrylate (PMMA). The area of bone invasion was determined and broadly excised under white light illumination with a safety margin of at least 1 cm. The definitive replica was cast within the remaining bone flap frame and the imprint. Clinical and radiologic follow-up examinations were performed 3 months after surgery. RESULTS: Four women and two men (mean age 51.4 years ± 12.8) underwent reconstruction of bone flap defects after meningioma resection. Mean duration of intraoperative reconstruction of the partial bone flap defects was 19 minutes ± 4 (range 14-24 minutes). Implant sizes ranged from 17-35 cm(2) (mean size 22 cm(2) ± 8). Radiologic and clinical follow-up examinations revealed excellent implant alignment and favorable cosmesis (visual analogue scale for cosmesis [VASC] = 97 ± 5) in all patients. CONCLUSIONS: Patient-specific reconstruction of partial bone flap defects after convexity meningioma resection using the presented intraoperative PMMA cast method resulted in excellent bony alignment and a favorable cosmetic outcome. Relatively low costs and minimized operation time for adjustment and insertion of the cranioplasty implant justify use of this method in small bony defects as well.

Intraoperative template-molded bone flap reconstruction for patient-specific cranioplasty

Cranioplasty is a common neurosurgical procedure. Free-hand molding of polymethyl methacrylate (PMMA) cement into complex three-dimensional shapes is often time-consuming and may result in disappointing cosmetic outcomes. Computer-assisted patient-specific implants address these disadvantages but are associated with long production times and high costs. In this study, we evaluated the clinical, radiological, and cosmetic outcomes of a time-saving and inexpensive intraoperative method to mold custom-made implants for immediate single-stage or delayed cranioplasty. Data were collected from patients in whom cranioplasty became necessary after removal of bone flaps affected by intracranial infection, tumor invasion, or trauma. A PMMA replica was cast between a negative form of the patient's own bone flap and the original bone flap with exactly the same shape, thickness, and dimensions. Clinical and radiological follow-up was performed 2 months post-surgery. Patient satisfaction (Odom criteria) and cosmesis (visual analogue scale for cosmesis) were evaluated 1 to 3 years after cranioplasty. Twenty-seven patients underwent intraoperative template-molded patient-specific cranioplasty with PMMA. The indications for cranioplasty included bone flap infection (56%, n = 15), calvarian tumor resection (37%, n = 10), and defect after trauma (7%, n = 2). The mean duration of the molding procedure was 19 ± 7 min. Excellent radiological implant alignment was achieved in 94% of the cases. All (n = 23) but one patient rated the cosmetic outcome (mean 1.4 years after cranioplasty) as excellent (70%, n = 16) or good (26%, n = 6). Intraoperative cast-molded reconstructive cranioplasty is a feasible, accurate, fast, and cost-efficient technique that results in excellent cosmetic outcomes, even with large and complex skull defects.

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and point distribution model

Reconstruction of patient-specific 3D bone surface from 2D calibrated fluoroscopic images and a point distribution model is discussed. We present a 2D/3D reconstruction scheme combining statistical extrapolation and regularized shape deformation with an iterative image-to-model correspondence establishing algorithm, and show its application to reconstruct the surface of proximal femur. The image-to-model correspondence is established using a non-rigid 2D point matching process, which iteratively uses a symmetric injective nearest-neighbor mapping operator and 2D thin-plate splines based deformation to find a fraction of best matched 2D point pairs between features detected from the fluoroscopic images and those extracted from the 3D model. The obtained 2D point pairs are then used to set up a set of 3D point pairs such that we turn a 2D/3D reconstruction problem to a 3D/3D one. We designed and conducted experiments on 11 cadaveric femurs to validate the present reconstruction scheme. An average mean reconstruction error of 1.2 mm was found when two fluoroscopic images were used for each bone. It decreased to 1.0 mm when three fluoroscopic images were used.