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Related Experiment Video

Updated: Sep 17, 2025

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Intraoperative Assessment of Parathyroidectomy Outcomes via Autoencoder-Support-Vector-Machine-Assisted Label-Free

Tian-Yu Qiu1, Yan Ding1, Yao-Yu Huang2

  • 1Department of Forensic Medicine, Nanjing Medical University, Nanjing 211166, P. R. China.

Nano Letters
|June 30, 2025
PubMed
Summary

This study introduces a rapid, label-free differential surface-enhanced Raman spectroscopy (dSERS) platform with artificial intelligence for intraoperative parathyroidectomy assessment. The technology accurately differentiates complete from partial resections using minimal plasma, guiding precision endocrine surgery.

Keywords:
differential surface-enhanced Raman spectroscopyintraoperative guidancemachine learningparathyroidectomy

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Area of Science:

  • Biomedical Engineering
  • Spectroscopy
  • Artificial Intelligence in Medicine

Background:

  • Intraoperative guidance is crucial for surgical success and patient outcomes.
  • Current monitoring methods during surgery are often unreliable, posing a challenge.
  • Accurate assessment of parathyroidectomy is essential for preventing complications.

Purpose of the Study:

  • To develop a rapid, label-free platform for real-time intraoperative assessment of parathyroidectomy outcomes.
  • To differentiate between complete and partial parathyroid gland resection during surgery.
  • To provide a transformative tool for guiding precision endocrine surgery.

Main Methods:

  • Development of an autoencoder-support-vector-machine (SVM)-assisted label-free differential surface-enhanced Raman spectroscopy (dSERS) platform.
  • Utilized 2 μL of untreated plasma for analysis.
  • Employed differential spectral analysis comparing postoperative and preoperative spectra.
  • Real-time differentiation within 16 minutes.

Main Results:

  • The platform achieved 95.8% accuracy on an internal test set and 79% accuracy on an independent validation cohort (n=144 and 33 spectra).
  • Effectively minimized individual variability by leveraging differential spectral analysis.
  • Amplified surgery-induced molecular changes for improved detection.
  • Demonstrated rapid, microliter-scale sample requirements.

Conclusions:

  • The label-free dSERS-artificial intelligence platform offers a transformative approach to intraoperative surgical guidance.
  • The platform enables rapid and accurate assessment of parathyroidectomy outcomes.
  • This technology has the potential to significantly enhance precision in endocrine surgery.