Study of a spectroscopic electrical impedance tomography technique for the diagnosis of dental caries.

Project Details


The significant decline in the incidence of dental caries that is observed in the last two decades, also seems to be accompanied by a distinctive change in lesion morphology. In particular, the phenomenon of slowly progressing dentinal lesions, obscured by apparently intact enamel, renders the established diagnostic procedures of visual examination and intra-oral radiography, ineffective. However, reliable detection at an early stage of the carious progression remains crucial to allow for an appropriate preventive or minimal invasive treatment.
Extraordinary sensitivity scores, however, have been achieved with diagnostic methods based on the premise that demineralized lesions show a significant higher electrical conductivity than healthy tissue, due to the phenomenon of increased pore volume. Even more impressive results were attaind by means of spectroscopic conductance measurements. Clinical application of these electrical conductivity methods, unfortunately seems to be hampered by a lack of reproducibility. Variations in conductivity readings makes it very difficult, if not impossible, to define generally applicable diagnostic thresholds for discriminating among carious involvement. It may be hypothesized, that this problem is related to the very nature of the 2-point measurement configuration underlying all of the experimental methods, described in the literature as today. This study instead, aims to develop and evaluate a new method of spectroscopic Electrical Impedance Tomography (EIT), capable of reconstructing cross-sectional maps of the coronal tooth structure, depicting site-specific electrical impedance spectra. The resulting method promises to improve upon existing electrical caries detection methods, both in terms of its improved cross-sectional sampling strategy, dispensing with the need to rely on visual surface indications to determine appropriate measurement sites, and its immunity with regard to the natural variability in electrical conductance between individual teeth. Tomographic representation of the measurement results will allow the diagnostic interpretation to proceed on the basis of relative changes in tissue impedance among different spatial locations, instead of being dependent on a single quantitative interpretation.
The suggested spectroscopic extension of the established method of EIT, together with the particularly difficult measurement conditions created by the insulating properties of the outer enamel layer, will pose some very specific problems as to the mathematical demands on the reconstruction algorithms. Therefore, the study and evaluation of non-linear reconstruction algorithms for the inverse conductivity problem of EIT, based on concepts drawn from numerical algebra, will constitute the major contribution in this research proposal. Despite the fact that evaluation of the algorithmic developments will be limited to numerical simulation and in vitro experiments, design of the newly developed method will be such, that its essential properties can be expected to transfer straightforwardly to the clinical setting.
To gain a more fundamental understanding of the electrical conduction phenomena taking place in dental structures, a first, morphological accurate, numerical simulation model of a whole tooth will be built. The detailed morphological input data for this model will be derived from micro-Computed Tomography (micro-CT) scans, acquired with a microfocal desktop-sized measurement system. Cross-sectional images acquired in this way, will be processed by an automatic segmentation procedure, before being converted into a 3D Finite Element (FE) mesh. Such a mesh description allows to build up the actual volumetric simulation model.
Effective start/end date1/01/0431/12/07


  • inverse problems
  • caries diagnosis
  • Electrical Impedance Tomography
  • dental
  • spectroscopy

Flemish discipline codes

  • Electrical and electronic engineering
  • Mathematical sciences
  • Basic sciences
  • (Bio)medical engineering