Haptic computer-assisted patient-specific preoperative planning for orthopedic fractures surgery.

PURPOSE: The aim of orthopedic trauma surgery is to restore the anatomy and function of displaced bone fragments to support osteosynthesis. For complex cases, including pelvic bone and multi-fragment femoral neck and distal radius fractures, preoperative planning with a CT scan is indicated. The planning consists of (1) fracture reduction-determining the locations and anatomical sites of origin of the fractured bone fragments and (2) fracture fixation-selecting and placing fixation screws and plates. The current bone fragment manipulation, hardware selection, and positioning processes based on 2D slices and a computer mouse are time-consuming and require a technician. METHODS: We present a novel 3D haptic-based system for patient-specific preoperative planning of orthopedic fracture surgery based on CT scans. The system provides the surgeon with an interactive, intuitive, and comprehensive, planning tool that supports fracture reduction and fixation. Its unique features include: (1) two-hand haptic manipulation of 3D bone fragments and fixation hardware models; (2) 3D stereoscopic visualization and multiple viewing modes; (3) ligaments and pivot motion constraints to facilitate fracture reduction; (4) semiautomatic and automatic fracture reduction modes; and (5) interactive custom fixation plate creation to fit the bone morphology. RESULTS: We evaluate our system with two experimental studies: (1) accuracy and repeatability of manual fracture reduction and (2) accuracy of our automatic virtual bone fracture reduction method. The surgeons achieved a mean accuracy of less than 1 mm for the manual reduction and 1.8 mm (std [Formula: see text] 1.1 mm) for the automatic reduction. CONCLUSION: 3D haptic-based patient-specific preoperative planning of orthopedic fracture surgery from CT scans is useful and accurate and may have significant advantages for evaluating and planning complex fractures surgery.

Anatomical structures segmentation by spherical 3D ray casting and gradient domain editing.

Fuzzy boundaries of anatomical structures in medical images make segmentation a challenging task. We present a new segmentation method that addresses the fuzzy boundaries problem. Our method maps the lengths of 3D rays cast from a seed point to the unit sphere, estimates the fuzzy boundaries location by thresholding the gradient magnitude of the rays lengths, and derives the true boundaries by Laplacian interpolation on the sphere. Its advantages are that it does not require a global shape prior or curvature based constraints, that it has an automatic stopping criteria, and that it is robust to anatomical variability, noise, and parameters values settings. Our experimental evaluation on 23 segmentations of kidneys and on 16 segmentations of abdominal aortic aneurysms (AAA) from CT scans yielded an average volume overlap error of 12.6% with respect to the ground-truth. These results are comparable to those of other segmentation methods without their underlying assumptions.

Non-parametric iterative model constraint graph min-cut for automatic kidney segmentation.

We present a new non-parametric model constraint graph min-cut algorithm for automatic kidney segmentation in CT images. The segmentation is formulated as a maximum a-posteriori estimation of a model-driven Markov random field. A non-parametric hybrid shape and intensity model is treated as a latent variable in the energy functional. The latent model and labeling map that minimize the energy functional are then simultaneously computed with an expectation maximization approach. The main advantages of our method are that it does not assume a fixed parametric prior model, which is subjective to inter-patient variability and registration errors, and that it combines both the model and the image information into a unified graph min-cut based segmentation framework. We evaluated our method on 20 kidneys from 10 CT datasets with and without contrast agent for which ground-truth segmentations were generated by averaging three manual segmentations. Our method yields an average volumetric overlap error of 10.95%, and average symmetric surface distance of 0.79 mm. These results indicate that our method is accurate and robust for kidney segmentation.

The T cell receptor V alpha 3 gene segment is associated with reactivity to p-azobenzenearsonate.

The murine T cell receptor V alpha 3 gene segment is associated with reactivity to p-azobenzenearsonate, as indicated by several independent lines of evidence. First, three out of four arsonate-reactive T cell clones tested (two I-Ad-and one I-Ak-restricted) utilized V alpha 3. Second, bulk splenic cultures enriched for arsonate/H-2d and arsonate/H-2k responsive T cells showed increased expression of V alpha 3 mRNA. Third, a V alpha 3-containing alpha chain (Ar-5: arsonate/I-Ad) transferred arsonate responsiveness to an appropriate recipient T cell (O3: ovalbumin/I-Ad). Fourth, an independently derived V alpha 3-expressing T cell clone (2C: alloreactive to Ld) showed a response to arsonate/Ld. Thus, a V alpha 3 gene segment, in conjunction with at least two different J alpha segments (J alpha 20'(Ar-5) and J alpha pHDS58(2C)) and at least three different beta chains (V beta 2(Ar-5), V beta 6(O3), and V beta 8(2C], confers reactivity to arsonate in association with at least three different MHC proteins (I-Ad, I-Ak, and Ld). We suggest that V alpha 3 encodes a protein sequence with a binding site for the arsonate hapten.