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Purpose <p>Ultrasound-guided radiofrequency ablation (RFA) of benign thyroid nodules is an effective, minimally invasive alternative to surgery but has a steep learning curve and limited formal training options. Toward addressing this gap, we developed a mixed reality simulator for thyroid nodule RFA.</p> Methods <p>We implemented a real-time, voxel-based heat-transfer model of a thyroid nodule that computes temperature, thermal damage, and temperature-dependent impedance within a mixed reality simulator. The model was calibrated and verified with published RFA data from a thermal property-matched thyroid phantom and validated against published ex vivo lesion volumes. The simulator provides configurable nodule size and location, renders RFA ultrasound artifacts and lesion visualization, computes quantitative ablation metrics, and includes an interactive virtual RFA generator interface.</p> Results <p>Simulated temperature–time curves matched phantom sensor readings with a root mean square error of 1.4&#xa0;°C. Simulated lesion volumes were within − 7.3% to + 0.9% of the ex vivo reference across 1.0–0.125 mm<sup>3</sup> voxel volumes and lesion aspect ratios were lower by 4.7–10.5%. In a post-use survey, a single expert clinician rated visual realism, feedback fidelity, and training utility favorably.</p> Conclusion <p>The simulator closely reproduced phantom temperature profiles and ex vivo lesion sizes. Its architecture is configurable and extensible to other organs and thermal ablation modalities. Formal educational studies are warranted to evaluate training effectiveness of the simulator.</p>

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Mixed reality simulator for ultrasound-guided thyroid nodule radiofrequency ablation: development and technical validation

  • 期刊论文

  • 发表日期：

    2026年3月11日

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  • Aidan Mather,
  • Joseph Zachary,
  • Naykky Singh Ospina,
  • Gonzalo J. Acosta,
  • Samsun Lampotang,
  • Christopher Samouce

摘要

Purpose

Ultrasound-guided radiofrequency ablation (RFA) of benign thyroid nodules is an effective, minimally invasive alternative to surgery but has a steep learning curve and limited formal training options. Toward addressing this gap, we developed a mixed reality simulator for thyroid nodule RFA.

Methods

We implemented a real-time, voxel-based heat-transfer model of a thyroid nodule that computes temperature, thermal damage, and temperature-dependent impedance within a mixed reality simulator. The model was calibrated and verified with published RFA data from a thermal property-matched thyroid phantom and validated against published ex vivo lesion volumes. The simulator provides configurable nodule size and location, renders RFA ultrasound artifacts and lesion visualization, computes quantitative ablation metrics, and includes an interactive virtual RFA generator interface.

Results

Simulated temperature–time curves matched phantom sensor readings with a root mean square error of 1.4 °C. Simulated lesion volumes were within − 7.3% to + 0.9% of the ex vivo reference across 1.0–0.125 mm3 voxel volumes and lesion aspect ratios were lower by 4.7–10.5%. In a post-use survey, a single expert clinician rated visual realism, feedback fidelity, and training utility favorably.

Conclusion

The simulator closely reproduced phantom temperature profiles and ex vivo lesion sizes. Its architecture is configurable and extensible to other organs and thermal ablation modalities. Formal educational studies are warranted to evaluate training effectiveness of the simulator.