A system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images

This paper presents a system for 3-D reconstruction of a patient-specific surface model from calibrated X-ray images. Our system requires two X-ray images of a patient with one acquired from the anterior-posterior direction and the other from the axial direction. A custom-designed cage is utilized in our system to calibrate both images. Starting from bone contours that are interactively identified from the X-ray images, our system constructs a patient-specific surface model of the proximal femur based on a statistical model based 2D/3D reconstruction algorithm. In this paper, we present the design and validation of the system with 25 bones. An average reconstruction error of 0.95 mm was observed.

Patient-specific finite-element simulation of the human cornea: A clinical validation study on cataract surgery

The planning of refractive surgical interventions is a challenging task. Numerical modeling has been proposed as a solution to support surgical intervention and predict the visual acuity, but validation on patient specific intervention is missing. The purpose of this study was to validate the numerical predictions of the post-operative corneal topography induced by the incisions required for cataract surgery. The corneal topography of 13 patients was assessed preoperatively and postoperatively (1-day and 30-day follow-up) with a Pentacam tomography device. The preoperatively acquired geometric corneal topography – anterior, posterior and pachymetry data – was used to build patient-specific finite element models. For each patient, the effects of the cataract incisions were simulated numerically and the resulting corneal surfaces were compared to the clinical postoperative measurements at one day and at 30-days follow up. Results showed that the model was able to reproduce experimental measurements with an error on the surgically induced sphere of 0.38D one day postoperatively and 0.19D 30 days postoperatively. The standard deviation of the surgically induced cylinder was 0.54D at the first postoperative day and 0.38D 30 days postoperatively. The prediction errors in surface elevation and curvature were below the topography measurement device accuracy of ±5μm and ±0.25D after the 30-day follow-up. The results showed that finite element simulations of corneal biomechanics are able to predict post cataract surgery within topography measurement device accuracy. We can conclude that the numerical simulation can become a valuable tool to plan corneal incisions in cataract surgery and other ophthalmosurgical procedures in order to optimize patients' refractive outcome and visual function.

Intraoperative fabrication of patient-specific moulded implants for skull reconstruction: single-centre experience of 28 cases

BACKGROUND Intraoperatively fabricated polymethylmethacrylate (PMMA) implants based on computer-designed moulds were used to improve cosmetic results after hard tissue replacement. To assess the implant's cosmetic and functional results we performed both subjective and objective assessments. METHODS This retrospective analysis was performed using a cohort of 28 patients who received PMMA implants between February 2009 and March 2012. The cosmetic and functional results were assessed using a patient questionnaire. Furthermore an objective volumetric subtraction score (0-100) was applied and implant thickness, as well as gaps and tiers, were measured. RESULTS Patients mainly judged their cosmetic result as "good". Two of the 28 patients found their cosmetic result unfavourable. The functional result and stability was mainly judged to be good. Measurements of implant thickness showed a very high correlation with the thickness of the contralateral bone. Volumetric subtraction led to a median quality of 80 on a scale from 0 to 100. Median gaps around the margins of the implant were 1.5 mm parietally, 1.7 mm frontally and 3.5 mm fronto-orbitally, and median tiers were 1.2 mm, 0 mm and 0 mm respectively. The overall rate of surgical revisions was 10.7 % (three patients). Two patients suffered from wound healing disturbances (7.1 %). The overall complication rate was comparable to other reports in the literature. CONCLUSIONS Implantation of intraoperatively fabricated patient-specific moulded implants is a cost-effective and safe technique leading to good clinical results with a low complication rate.

A patient-specific study of type-B aortic dissection: evaluation of true-false lumen blood exchange

BACKGROUND Aortic dissection is a severe pathological condition in which blood penetrates between layers of the aortic wall and creates a duplicate channel - the false lumen. This considerable change on the aortic morphology alters hemodynamic features dramatically and, in the case of rupture, induces markedly high rates of morbidity and mortality. METHODS In this study, we establish a patient-specific computational model and simulate the pulsatile blood flow within the dissected aorta. The k-ω SST turbulence model is employed to represent the flow and finite volume method is applied for numerical solutions. Our emphasis is on flow exchange between true and false lumen during the cardiac cycle and on quantifying the flow across specific passages. Loading distributions including pressure and wall shear stress have also been investigated and results of direct simulations are compared with solutions employing appropriate turbulence models. RESULTS Our results indicate that (i) high velocities occur at the periphery of the entries; (ii) for the case studied, approximately 40% of the blood flow passes the false lumen during a heartbeat cycle; (iii) higher pressures are found at the outer wall of the dissection, which may induce further dilation of the pseudo-lumen; (iv) highest wall shear stresses occur around the entries, perhaps indicating the vulnerability of this region to further splitting; and (v) laminar simulations with adequately fine mesh resolutions, especially refined near the walls, can capture similar flow patterns to the (coarser mesh) turbulent results, although the absolute magnitudes computed are in general smaller. CONCLUSIONS The patient-specific model of aortic dissection provides detailed flow information of blood transport within the true and false lumen and quantifies the loading distributions over the aorta and dissection walls. This contributes to evaluating potential thrombotic behavior in the false lumen and is pivotal in guiding endovascular intervention. Moreover, as a computational study, mesh requirements to successfully evaluate the hemodynamic parameters have been proposed.

Patient-specific spinal stiffness in AIS: a preoperative and noninvasive method.

INTRODUCTION The clinical tests currently used to assess spinal biomechanics preoperatively are unable to assess true mechanical spinal stiffness. They rely on spinal displacement without considering the force required to deform a patient's spine. We propose a preoperative method for noninvasively quantifying the three-dimensional patient-specific stiffness of the spines of adolescent idiopathic scoliosis patients. METHODS The technique combines a novel clinical test with numerical optimization of a finite element model of the patient's spine. RESULTS A pilot study conducted on five patients showed that the model was able to provide accurate 3D reconstruction of the spine's midline and predict the spine's stiffness for each patient in flexion, bending, and rotation. Statistically significant variation of spinal stiffness was observed between the patients. CONCLUSION This result confirms that spinal biomechanics is patient-specific, which should be taken into consideration to individualize surgical treatment.

Patient-Specific Semi-Supervised Learning for Postoperative Brain Tumor Segmentation

In contrast to preoperative brain tumor segmentation, the problem of postoperative brain tumor segmentation has been rarely approached so far. We present a fully-automatic segmentation method using multimodal magnetic resonance image data and patient-specific semi-supervised learning. The idea behind our semi-supervised approach is to effectively fuse information from both pre- and postoperative image data of the same patient to improve segmentation of the postoperative image. We pose image segmentation as a classification problem and solve it by adopting a semi-supervised decision forest. The method is evaluated on a cohort of 10 high-grade glioma patients, with segmentation performance and computation time comparable or superior to a state-of-the-art brain tumor segmentation method. Moreover, our results confirm that the inclusion of preoperative MR images lead to a better performance regarding postoperative brain tumor segmentation.

Landmark Detection for Fusion of Fundus and MRI Towards a Patient-Specific Multi-Modal Eye Model

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise e.g., Fundus photography, Optical Coherence Tomography (OCT), Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The presented article’s goal is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI which was not visible before like vessels and the macula. This article’s contributions include automatic detection of the optic disc, the fovea, the optic axis and an automatic segmentation of the vitreous humor of the eye.