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Background Müller–Weiss disease (MWD), a rare dysplastic disorder of the foot, is characterized by deformity, sclerosis, and fragmentation of the lateral part of navicular bone. Arthrodesis is the mainstay treatment for MWD. Generally, arthrodesis can be achieved through internal fixation with metallic implants, and morselized chip bone may be packed into the gap for better bone union. However, with this procedure, the original foot size is not maintained and support for the foot arch is not provided. Sequela of short foot, or flatfoot is commonly observed even though these complications of surgery had not been reported with cases of MWD treated by arthrodesis. Herein, we present a retrospective analysis of treating MWD through midfoot and hindfoot arthrodesis combined with strut allograft. Methods From August 2006 to June 2019, 20 patients with MWD (mean age, 59.6 years; range, 40–80 years) underwent midfoot and hindfoot arthrodesis with strut bone allograft and were followed for at least 24 months. The patients were able to ambulate and participate in rehabilitation programs 3 months postoperatively. Results The used four radiographic parameters (Meary’s angle in anteroposterior and lateral view, talonavicular coverage angle, calcaneal pitch) demonstrated significant differences (P < .05) preoperatively and postoperatively, but those between the postoperative values and the values at the last follow-up session did not, indicating that strut allograft was able to maintain normal alignment. The mean American Orthopaedic Foot & Ankle Society Ankle-Hindfoot scores at 2 years postoperatively revealed significant improvement from baseline, from 60.2 to 84.2 (P < .05). The 12-item Short Form Health Survey scores also improved significantly (P < .05). All patients reported substantial pain relief and exhibited improved functional outcomes and gait patterns. Conclusions For advanced-stage MWD, arthrodesis with a precisely shaped, size-matched strut allograft provided strong support for biomechanical alignment and enhanced functional performance.

BackgroundDialysis-related destructive spondyloarthropathy caused by beta-2 microglobulin (β2M) amyloid deposits in intervertebral discs is a major burden for patients undergoing long-term dialysis. This study aimed to quantify the presence of β2M amyloid deposits in the intervertebral disc tissue of such patients and analyze whether there was a significant correlation between β2M accumulation and the duration of dialysis.MethodsTwo groups of patients who had undergone surgery for degenerative spinal pathologies were selected: the dialysis group (n = 29) with long-term dialysis and the control group (n = 10) with no renal impairment. Tissue sections were prepared from specimens of intervertebral disc tissue obtained during spinal surgery and analyzed via histological staining, including immunohistochemistry (IHC) and Congo red.ResultsThere was a statistically significant multifold increase of β2M expression in the disc tissue of long-term dialysis patients when compared to non-dialysis patients, as shown by both IHC (0.019 ± 0.023 μm2 vs. 0.00020 ± 0.00033 μm2, respectively; p = 0.012) and Congo red staining (0.027 ± 0.041 μm2 vs. 9.240 × 10−5 ± 5.261 × 10−5 μm2, respectively; p = 0.047). We also note a moderate strength positive correlation between the duration of dialysis and positive IHC (r = 0.39; p = 0.015) and Congo-red staining (r = 0.42; p = 0.007).ConclusionsThe problem of β2M amyloidosis in long-term dialysis patients remains unresolved even with predominant use of high-flux dialysis membranes. This highlights the insufficiency of current dialysis modalities to effectively filter β2M.

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In this paper, we propose a robust algorithm for 3D object pose estimation from a single 2D image. The proposed pose estimation algorithm is based on modifying the traditional image projection error function to a sum of squared image projection errors weighted by their associated distances. By using an Euler angle representation, we formulate the energy minimization for the pose estimation problem as searching a global minimum solution. Based on this framework, the proposed algorithm employs robust techniques to detect outliers in a coarse-to-fine fashion, thus providing very robust pose estimation. Our experiments show that the algorithm outperforms previous methods under noisy conditions.