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Related Experiment Video

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Visualization Method for Proprioceptive Drift on a 2D Plane Using Support Vector Machine
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Dynamic Distance Mapping Enhances Hallux Valgus Progression Visualization.

Dror Robinson1, Hamza Murad1, Muhammad Khatib1

  • 1Department of Orthopedics, Hasharon Hospital, 7 Kakal Str., Petah Tikwa 4937211, Israel.

Diagnostics (Basel, Switzerland)
|November 13, 2025
PubMed
Summary
This summary is machine-generated.

A new dynamic distance mapping technique offers a novel way to visualize hallux valgus (HV) progression and severity. This method shows significant correlations with key angular measurements, aiding surgical planning for this common foot deformity.

Keywords:
computational biologydynamic mappingfoot deformitieshallux valgusmorphometric analysisorthopedic proceduresradiography

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Area of Science:

  • Orthopedics
  • Radiology
  • Biomechanical Engineering

Background:

  • Hallux valgus (HV) is a prevalent foot deformity challenging traditional quantification beyond angular measurements.
  • Existing methods lack comprehensive visualization of HV progression and spatial feature identification related to severity.

Purpose of the Study:

  • To introduce and evaluate a novel dynamic distance mapping technique for visualizing hallux valgus progression.
  • To identify spatial features correlated with hallux valgus severity using this new mapping method.

Main Methods:

  • Retrospective analysis of 335 feet from 178 patients undergoing hallux valgus surgery.
  • Custom Python software used to annotate 24 landmarks on preoperative radiographs, generating 276 normalized Euclidean distances.
  • Pearson correlation analysis performed between distances and hallux valgus angles (HVA, IMA, DMAA, HIA).

Main Results:

  • Significant negative and positive correlations (r > 0.4, p < 0.05) were found between seven distances and HVA, involving distal phalanx, sesamoids, and second metatarsal.
  • Eleven distances showed strong positive correlation (r > 0.4, p < 0.05) with IMA, indicating displacement patterns.
  • Moderate correlations were observed with DMAA and HIA, with visualizations highlighting progressive spatial changes.

Conclusions:

  • Dynamic distance mapping offers valuable insights into hallux valgus progression and severity, correlating significantly with HVA and IMA.
  • The technique shows potential utility in surgical planning for hallux valgus.
  • Further validation using weightbearing computed tomography (WBCT) is recommended to assess its ability to capture 3D deformities.