No abstract

Cavus foot is a tri-planar deformity that requires correction in several bones and soft tissue. Minimally invasive surgeries are less aggressive, faster and easier to recover from. Here, we describe the initial results of a technique for percutaneous cavus foot correction. The procedure consists of calcaneal dorsal/lateral closing wedge osteotomy (with fixation), cuboid, medial cuneiform and first metatarsal closing wedge osteotomy (without fixation), and plantar fascia and tibialis posterior tenotomy with the patient in the prone position. Immediate weight bearing is permitted. Twenty patients were selected to undergo the procedure. The mean follow-up was 4.2 months and mean age 42.3 years. Eight of the 20 patients were submitted to cuboid and first metatarsal osteotomy, and 12 (60%) only calcaneal osteotomy. The median time for complete bone healing was 2.2 months. No wound complications were observed. No cases of non-consolidation of the cuboid or first metatarsal osteotomies were detected. The most common complication was sural nerve paresthesia. This is the first description of cavus foot correction using a minimally invasive technique. Complete bone healing is obtained even with immediate weight bearing and without cuboid and first metatarsal fixation.

Medializing calcaneal osteotomy is one of the most common procedures in flat foot alignment. Recently it has been done percutaneously with several different techniques, most of them made in lateral position. Our paper aims to describe the minimally invasive calcaneal medializing osteotomy in ventral position, easier for x-ray control, faster to patient positioning with technical tips to more precise bone cut and reduction. Between April 2019 and September 2019, 10 patients were operated using this technique. Patients in ventral position, sciatic nerve block, percutaneous Achilles lengthening, transcutaneous k-wire passage for drill cut control. Straight calcaneal cut, reduction in medial and plantar position and control both in lateral and axil views. 15 patients were operated using this technique. 67% were woman. Median age were 38.9 years and median BMI was 23.5.

Objective: To implement one analysis method of the ankle bone contour that could make a more precise ankle arthrodesis. Methods: Twenty tomographies were submitted to 3D reconstruction. Seven points of anatomic interest for ankle arthrodesis with the three screws technique were marked with a triplannar marker. The median of the position of markers was estimated, and the union of the seven median points allow the construction of one median ankle for that population. Using this median ankle, sizes and angles for the screws position were determined. Results: Two median ankles were reconstructed, left and right. The position of the screw passage were determined considering the anatomical parameters. In the right ankle the lateral to medial screw should enter 4.56 cm and 0.79 above and posterior to lateral malleolus, with one inclination of 17.34° in relation to tibial longitudinal axis; and 0° in relation to tibial axial plane. The position for the other two screws is also described. Conclusion: Our article is the first to presents one precise guide for ankle arthrodesis based on a populational assessment. Level of evidence II, Diagnostic Studies.

Ankle injuries caused by the Anterior Talofibular Ligament (ATFL) are the most common type of injury. Thus, finding new ways to analyze these injuries through novel technologies is critical for assisting medical diagnosis and, as a result, reducing the subjectivity of this process. As a result, the purpose of this study is to compare the ability of specialists to diagnose lateral tibial tuberosity advancement (LTTA) injury using computer vision analysis on magnetic resonance imaging (MRI). The experiments were carried out on a database obtained from the Vue PACS–Carestream software, which contained 132 images of ATFL and normal (healthy) ankles. Because there were only a few images, image augmentation techniques was used to increase the number of images in the database. Following that, various feature extraction algorithms (GLCM, LBP, and HU invariant moments) and classifiers such as Multi-Layer Perceptron (MLP), Support Vector Machine (SVM), k-Nearest Neighbors (kNN), and Random Forest (RF) were used. Based on the results from this analysis, for cases that lack clear morphologies, the method delivers a hit rate of 85.03% with an increase of 22% over the human expert-based analysis.