Background: Flat feet increase the risk of knee osteoarthritis and contribute to frailty, which may lead to worse life prognoses. The influence of the foot skeletal structure on flat feet is not yet entirely understood. Footprints are often used to evaluate feet. However, footprint-based measurements do not reflect the underlying structures of feet and are easily confounded by soft tissue. Three-dimensional evaluation of the foot shape can reveal the characteristics of flat feet. Therefore, foot shape evaluations have garnered increasing research interest. This study aimed to determine the correlation between the three-dimensional (3D) features of the foot and the measurement results of footprint and to predict the evaluation results of flat feet from the footprint based on the 3D features. Finally, the three-dimensional characteristics of flat feet, which cannot be revealed by footprint, were determined.
Methods: A total of 403 individuals (40-89 years) participated in this study. The proposed system was developed to identify seven skeletal features that were expected to be associated with flat feet. The loads on the soles of the feet were measured in a static standing position and with a digital footprint device. Specifically, two footprint indices were calculated: the Chippaux-Smirak index (CSI) and the Staheli index (SI). In the analysis, comparisons between male and female measurement variables were performed using the Student's t test. The relationships between the 3D foot features and footprint index parameters were determined by employing the Pearson correlation coefficient. Multiple linear regression was utilized to identify 3D foot features that were strongly associated with the CSI and SI. Foot features identified as significant in the multivariate regression analysis were compared based on a one-way analysis of variance (ANOVA) with Tukey's post hoc test.
Results: The CSI and SI were highly correlated with the instep height (IH) and navicular height (NH) of the 3D foot scanning system and were also derived from multiple regression analysis. In addition to the NH and IH, the indicators of the forefoot, transverse arch width, and transverse arch height were considered. In the flat foot group with CSI values above 62.7%, NH was 13.5% (p < 0.001) for males and 14.9% (p = 0.01) for females, and the axis of the bone distance was 5.3% (p = 0.05) for males and 4.9% (p = 0.10) for females. In particular, for CSI values above 62.7% and NH values below 13%, the axis of the bone distance was large and the foot skeleton was deformed.
Conclusions: Decreased navicular bone height could be evaluated with the 3D foot scanning system even when flat feet were not detected from the footprint. The results indicate that the use of quantitative indices for 3D foot measurements is important when evaluating the flattening of the foot. Trial registration number UMIN000037694. Name of the registry: University Hospital Medical Information Network Registry. Date of registration: August 15, 2019.
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http://dx.doi.org/10.1186/s12938-022-01021-7 | DOI Listing |
Biomed Eng Lett
January 2025
Department of Biomedical Engineering, Asan Medical Institute of Convergence Science and Technology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea.
Unlabelled: A weight-bearing lateral radiograph (WBLR) of the foot is a gold standard for diagnosing adult-acquired flatfoot deformity. However, it is difficult to measure the major axis of bones in WBLR without using auxiliary lines. Herein, we develop semantic segmentation with a deep learning model (DLm) on the WBLR of the foot for enhanced diagnosis of pes planus and pes cavus.
View Article and Find Full Text PDFAm J Med Genet A
January 2025
Department of Pediatrics, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Gait disturbance is a common motor symptom in Angelman syndrome (AS), but its characteristics have been poorly studied quantitatively. This study aimed to analyze gait characteristics in school-age children with AS using three-dimensional gait analysis (3DGA). Patients with clinically and genetically confirmed AS and healthy children aged 6-15 years were included.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Orthopedics, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, P. R. China.
Purpose: The present study is to explore the appropriate plantar support force for its effect on improving the collapse of the medial longitudinal arch with flexible flatfoot.
Methods: A finite element model with the plantar fascia attenuation was constructed simulating as flexible flatfoot. The appropriate plantar support force was evaluated.
World J Orthop
December 2024
Department of Orthopaedic Surgery, Massachusetts General Hospital, Boston, MA 02114, United States.
Background: Pes planus (flatfoot) and pes cavus (high arch foot) are common foot deformities, often requiring clinical and radiographic assessment for diagnosis and potential subsequent management. Traditional diagnostic methods, while effective, pose limitations such as cost, radiation exposure, and accessibility, particularly in underserved areas.
Aim: To develop deep learning algorithms that detect and classify such deformities using smartphone cameras.
Background: Pediatric flexible flatfoot (FFF) is a common condition characterized by the collapse of the medial longitudinal arch, which can lead to pain and functional impairment in a subset of patients. Subtalar arthroereisis (AR) is a minimally invasive procedure that corrects FFF by limiting excessive pronation of the subtalar joint. Two main techniques exist: endosinotarsal AR, which involves placing an implant in the sinus tarsi, and exosinotarsal AR, which uses a screw external to the sinus tarsi.
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