The method of integrative anatomical assessment of the foot

Purpose of research. Foot, computer plantography, radiography, integrative research, multimodal data, orthopedics, anatomy. Introduction. Integrative diagnostic methods of the foot, combining X-ray and computer plantography data, allow us to obtain a holistic view of the morphology, condition of the joints and the nature of the contact of the foot with the support in the static. The development of such methods is relevant to increase the information content and accuracy of anatomical assessment of the foot. The purpose of the work is to develop a methodology for integrative anatomical assessment of the foot.

Methods. The study was performed on 50 patients aged 18-70 years who underwent computer plantography and radiography of the foot in a direct projection. During the research, radiopaque metal markers were used for spatial image binding. The plantograms were processed using previously developed software.

Results. A three-stage method of integrative foot examination has been developed, including performing plantography and radiography using metal markers on the foot, image processing and their layered combination during analysis. The technique ensures accurate alignment of images through the use of markers, as well as unification of data visualization and reproducibility of the study. A set of 50 integrative foot studies was obtained. As a result of the integrative approach, the accuracy of localization of anatomical structures increases and the possibilities of complex analysis expand, which is important for planning orthopedic treatment and monitoring its effectiveness.

Conclusion. The proposed technique is of interest for scientific research and clinical practice in view of obtaining a unified result of two different studies – plantography and radiography of the foot. It can be used for in-depth analysis of structural changes in the foot, evaluation of the effectiveness of therapeutic and orthopedic interventions, and the resulting dataset of integrative results can be used in educational programs and further research. The technique also opens up new perspectives for the development of artificial intelligence models in the analysis of multimodal medical data, which is especially important in the context of the development of personalized medicine.

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