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Measuring Outcomes of Mohs Defect Reconstruction Using Eye-Tracking Technology.

Jacob K Dey1, Lisa E Ishii2, Kofi D O Boahene2

  • 1Department of Otolaryngology-Head and Neck Surgery, Mayo Clinic, Rochester, Minnesota.

JAMA Facial Plastic Surgery
|November 1, 2019
PubMed
Summary
This summary is machine-generated.

Mohs defects alter facial attention, drawing focus away from eyes. Reconstructive surgery helps normalize attention, especially for smaller defects, improving patient perception.

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Area of Science:

  • Ophthalmology and Visual Science
  • Plastic Surgery
  • Psychology and Behavioral Science

Background:

  • Mohs micrographic surgery defects can impact facial aesthetics and social perception.
  • Quantifying the attentional effects of these defects is crucial for patient outcomes.

Purpose of the Study:

  • To objectively measure how Mohs defect reconstruction influences casual observer attention using eye-tracking technology.
  • To assess the normalization of facial attention following reconstructive surgery for Mohs defects.

Main Methods:

  • An observational study involving 82 observers and 32 patients with Mohs facial defects.
  • Eye-tracking recorded attention patterns on pre- and post-reconstruction photos compared to control faces.
  • Mixed-effects linear regression analyzed the association between reconstruction and normalized facial attention.

Main Results:

  • Normal attention focuses on the central triangle (eyes, nose, mouth), with eyes being the primary focus (39% of total attention).
  • Mohs defects significantly altered attention patterns, with larger, central defects causing more distraction (up to 3693 ms).
  • Reconstruction improved attention deviations, normalizing eye focus for most defects, except large central ones.

Conclusions:

  • Mohs defects disrupt normal facial perception by diverting attention.
  • Reconstructive surgery can normalize attentional distraction for many Mohs defects.
  • Eye tracking is a valuable tool for assessing reconstructive surgery outcomes and predicting results based on defect characteristics.