Characteristics and Future Direction of Tibialis Posterior Tendinopathy Research: A Scoping Review

Morphological changes in flatfoot: a 3D analysis using weight-bearing CT scans

BACKGROUND

Flatfoot is a condition resulting from complex three-dimensional (3D) morphological changes. Most Previous studies have been constrained by using two-dimensional radiographs and non-weight-bearing conditions. The deformity in flatfoot is associated with the 3D morphology of the bone. These morphological changes affect the force line conduction of the hindfoot/midfoot/forefoot, leading to further morphological alterations. Given that a two-dimensional plane axis overlooks the 3D structural information, it is essential to measure the 3D model of the entire foot in conjunction with the definition under the standing position. This study aims to analyze the morphological changes in flatfoot using 3D measurements from weight-bearing CT (WBCT).

METHOD

In this retrospective comparative our CT database was searched between 4-2021 and 3-2022. Following inclusion criteria were used: Patients were required to exhibit clinical symptoms suggestive of flatfoot, including painful swelling of the medial plantar area or abnormal gait, corroborated by clinical examination and confirmatory radiological findings on CT or MRI. Healthy participants were required to be free of any foot diseases or conditions affecting lower limb movement. After applying the exclusion criteria (Flatfoot with other foot diseases), CT scans (mean age = 20.9375, SD = 16.1) confirmed eligible for further analysis. The distance, angle in sagittal/transverse/coronal planes, and volume of the two groups were compared on reconstructed 3D models using the t-test. Logistic regression was used to identify flatfoot risk factors, which were then analyzed using receiver operating characteristic curves and nomogram.

RESULT

The flatfoot group exhibited significantly lower values for calcaneofibular distance (p = 0.001), sagittal and transverse calcaneal inclination angle (p < 0.001), medial column height (p < 0.001), sagittal talonavicular coverage angle (p < 0.001), and sagittal (p < 0.001) and transverse (p = 0.015) Hibb angle. In contrast, the sagittal lateral talocalcaneal angle (p = 0.013), sagittal (p < 0.001) and transverse (p = 0.004) talocalcaneal angle, transverse talonavicular coverage angle (p < 0.001), coronal Hibb angle (p < 0.001), and sagittal (p < 0.001) and transverse (p = 0.001) Meary's angle were significantly higher in the flatfoot group. The sagittal Hibb angle (B =  - 0.379, OR = 0.684) and medial column height (B =  - 0.990, OR = 0.372) were identified as significant risk factors for acquiring a flatfoot.

CONCLUSION

The findings validate the 3D spatial position alterations in flatfoot. These include the abduction of the forefoot and prolapse of the first metatarsal proximal, the arch collapsed, subluxation of the talonavicular joint in the midfoot, adduction and valgus of the calcaneus, adduction and plantar ward movement of the talus in the hindfoot, along with the first metatarsal's abduction and dorsiflexion in the forefoot.

A Novel Model Based on CNN-ViT Fusion and Ensemble Learning for the Automatic Detection of Pes Planus

Background: Pes planus, commonly known as flatfoot, is a condition in which the medial arch of the foot is abnormally low or absent, leading to the inner part of the foot having less curvature than normal. Symptom recognition and errors in diagnosis are problems encountered in daily practice. Therefore, it is important to improve how a diagnosis is made. With the availability of large datasets, deep neural networks have shown promising capabilities in recognizing foot structures and accurately identifying pes planus. Methods: In this study, we developed a novel fusion model by combining the Vgg16 convolutional neural network (CNN) model with the vision transformer ViT-B/16 to enhance the detection of pes planus. This fusion model leverages the strengths of both the CNN and ViT architectures, resulting in improved performance compared to that in reports in the literature. Additionally, ensemble learning techniques were employed to ensure the robustness of the model. Results: Through a 10-fold cross-validation, the model demonstrated high sensitivity, specificity, and F1 score values of 97.4%, 96.4%, and 96.8%, respectively. These results highlight the effectiveness of the proposed model in quickly and accurately diagnosing pes planus, making it suitable for deployment in clinics or healthcare centers. Conclusions: By facilitating early diagnosis, the model can contribute to the better management of treatment processes, ultimately leading to an improved quality of life for patients.

EURO-MUSCULUS/USPRM Dynamic Ultrasound Protocols for Ankle/Foot

ABSTRACT

In this dynamic scanning protocol, ultrasound examination of the ankle is described using various maneuvers to assess different conditions. Real-time patient examination and scanning videos are used for better simulation of daily clinical practice. The protocol is prepared by several/international experts in the field of musculoskeletal ultrasound and within the umbrella of European Musculoskeletal Ultrasound Study Group in Physical and Rehabilitation Medicine/Ultrasound Study Group of the International Society of Physical and Rehabilitation Medicine.