Influence of unstable ankle fracture (type Weber C), osteosynthesis and syndesmotic transfixation on position of fibula in tibiofibular notch: a cadaveric study.

PURPOSE: The aim of the cadaveric study was to determine the effects of an unstable ankle fracture on the position of the fibula in the incisural notch and subsequently to evaluate the alterations resulting from the individual steps of a guideline-based osteosynthesis. METHODS: In a specimen model with 20 uninjured fresh-frozen lower legs with induced unstable fracture of the fibula (type Weber C), a guideline-based osteosynthesis was performed. The distances between the anterior and posterior edges of the tibia and fibula and in the center of the incisural notch, as well as the rotation angle of the fibula, were measured in the acquired 3D image data sets and were compared with the intact condition of the ankle mortise. RESULTS: The dissection of the syndesmosis and osteotomy of the fibula results in an external rotation the fibula by 3.6° (p = 0.000), while the distance between the anterior edge of the tibia and the fibula widens by 1.86 mm (p = 0.000). After osteosynthesis of the fibula and transfixation of the syndesmotic region using a positioning screw, the posterior distance is no longer substantially increased by 0.22 mm (p = 0.103) but also reduced by 0.1 mm (p = 0.104) in the tibiofibular notch. The external rotation of the fibula remains slightly increased by just 0.45° (p = 0.009). CONCLUSION: The results indicate that there is a tendency for over-compression when adjusting the tibiofibular distance and that the fibula in the tibiofibular notch tends to remain slightly rotated externally.

Software-Based Method for Automated Segmentation and Measurement of Wounds on Photographs Using Mask R-CNN: a Validation Study.

In clinical routine, wound documentation is one of the most important contributing factors to treating patients with acute or chronic wounds. The wound documentation process is currently very time-consuming, often examiner-dependent, and therefore imprecise. This study aimed to validate a software-based method for automated segmentation and measurement of wounds on photographic images using the Mask R-CNN (Region-based Convolutional Neural Network). During the validation, five medical experts manually segmented an independent dataset with 35 wound photographs at two different points in time with an interval of 1 month. Simultaneously, the dataset was automatically segmented using the Mask R-CNN. Afterwards, the segmentation results were compared, and intra- and inter-rater analyses performed. In the statistical evaluation, an analysis of variance (ANOVA) was carried out and dice coefficients were calculated. The ANOVA showed no statistically significant differences throughout all raters and the network in the first segmentation round (F = 1.424 and p > 0.228) and the second segmentation round (F = 0.9969 and p > 0.411). The repeated measure analysis demonstrated no statistically significant differences in the segmentation quality of the medical experts over time (F = 6.05 and p > 0.09). However, a certain intra-rater variability was apparent, whereas the Mask R-CNN consistently provided identical segmentations regardless of the point in time. Using the software-based method for segmentation and measurement of wounds on photographs can accelerate the documentation process and improve the consistency of measured values while maintaining quality and precision.

Computer-assisted contralateral side comparison of the ankle joint using flat panel technology.

PURPOSE: Reduction and osteosynthesis of ankle fractures is a challenging surgical procedure when it comes to the verification of the reduction result. Evaluation is conducted using intra-operative imaging of the injured ankle and depends on the expertise of the surgeon. Studies suggest that intra-individual variance of the ankle bone shape and pose is considerably lower than the inter-individual variance. It stands to reason that the information gain from the healthy contralateral side can help to improve the evaluation. METHOD: In this paper, an assistance system is proposed that provides a side-to-side view of the two ankle joints for visual comparison and instant evaluation using only one 3D C-arm image. Two convolutional neural networks (CNN) are employed to extract the relevant image regions and pose information of each ankle so that they can be aligned with each other. A first U-Net uses a sliding window to predict the location of each ankle. The standard plane estimation is formulated as segmentation problem so that a second U-Net predicts the three viewing planes for alignment. RESULTS: Experiments were conducted to assess the accuracy of the individual steps on 218 unilateral ankle datasets as well as the overall performance on 7 bilateral ankle datasets. The experiments on unilateral ankles yield a median position-to-plane error of [Formula: see text] mm and a median angular error between 2.98[Formula: see text] and 3.71[Formula: see text] for the plane normals. CONCLUSION: Standard plane estimation via segmentation outperforms direct pose regression. Furthermore, the complete pipeline was evaluated including ankle detection and subsequent plane estimation on bilateral datasets. The proposed pipeline enables a direct contralateral side comparison without additional radiation. This has the potential to ease and improve the intra-operative evaluation for the surgeons in the future and reduce the need for revision surgery.