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Convolution Neural Networks and Targeted Fluorescent Nanoparticles to Detect and ICDAS Score Caries.

Kai A Jones1,2, Nathan Jones3, Livia Maria Andalo Tenuta4

  • 1Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.

Caries Research
|September 26, 2022
PubMed
Summary

Artificial intelligence (AI) combined with targeted fluorescent starch nanoparticles (TFSNs) shows promise for detecting and scoring dental caries. This novel approach accurately identifies lesion severity and activity, aiding dental diagnostics.

Keywords:
Caries detectionImage analysisMachine learningNanoparticlesNoncavitated caries lesions

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Area of Science:

  • Biomaterials Science
  • Artificial Intelligence
  • Dental Diagnostics

Background:

  • Targeted fluorescent starch nanoparticles (TFSNs) have demonstrated utility in labeling subsurface carious lesions.
  • Accurate diagnosis of dental caries, including severity and activity, is crucial for effective treatment planning.

Purpose of the Study:

  • To evaluate the efficacy of artificial intelligence (AI) in detecting and scoring carious lesions using ICDAS (International Caries Detection and Assessment System) with fluorescent imaging.
  • To assess the performance of AI in determining lesion severity and surface porosity (activity) in conjunction with TFSNs.

Main Methods:

  • 130 extracted human teeth with ICDAS scores (0-6) were imaged under white light and blue light after TFSN application.
  • Convolutional neural networks (CNNs) were trained to detect, locate, and score lesions, and identify surface porosity.
  • A 30-fold cross-validation was employed for model testing on white light, blue light, and combined image datasets.

Main Results:

  • AI models achieved high sensitivity (80.26%) and positive predictive value (76.36%) for carious lesion detection.
  • AI demonstrated potential in determining lesion severity via ICDAS scoring with 72% accuracy.
  • AI accurately detected lesion surface porosity, an indicator of activity, with 90% accuracy.

Conclusions:

  • The combination of TFSNs and AI offers a promising approach for enhanced dental caries diagnosis.
  • This technology has the potential to improve the accuracy and efficiency of identifying lesion severity and activity.
  • The synergistic application of targeted nanoparticles and imaging AI holds broad applicability for future research and clinical use.