1. Introduction
Caries lesions can be arrested by the preferential deposition of mineral
at the lesion surface that inhibits diffusion of fluids [1-4]. Since
arrested lesions do not need further intervention, the assessment of
lesion activity is essential for clinical diagnosis. Conventional visual
and tactile methods of lesion activity assessment are not reliable
[5]. Gold standards for lesion assessment such as transverse
microradiography (TMR) and polarized light microscopy (PLM) either
require destruction of the tooth, or in the case of microcomputed
tomography (microCT) are not suitable for use in-vivo .
Non-destructive diagnostic tools are needed that can assess lesion
activity in a single visit. New optical diagnostic technologies that can
monitor optical changes in the light scattering of lesion structures
have great potential for assessing activity. Optical coherence
tomography (OCT) can be used to assess lesion activity in a single
measurement nondestructively in vivo; however such systems are expensive
and there are no systems currently available for clinical use. OCT is
capable of detecting the presence of a highly mineralized surface zone
near the lesion surface which appears as a transparent surface zone due
to the reduced reflectivity [4, 6, 7]. Short wavelength infrared
(SWIR) imaging offers a novel and complementary approach that exploit
changes in light scattering and absorption that occur in the lesion
during the loss of water from the lesion structure [8, 9].
When lesions become arrested by mineral deposition, or remineralization
of the outer layers of the lesion, the diffusion of fluids into the
lesion are inhibited. Hence, the rate of water diffusion out of the
lesion or the evaporation kinetics or dynamics reflects the degree of
lesion activity. Since arrested lesions are less permeable to water due
to the highly mineralized surface layer, changes in the rate of water
loss can be related to changes in lesion structure and porosity. Changes
in fluorescence loss [10-12], thermal emission, and SWIR reflectance
[8, 9, 13-17] during lesion dehydration have been investigated as
methods for assessing lesion activity. Sound enamel is transparent at
SWIR wavelengths, whereas early demineralization causes increased SWIR
reflectance due to scattering [18]. Water in the pores at the
surface of the lesion absorbs the incident SWIR light, particularly at
wavelengths greater than 1400 nm, reducing surface scattering and lesion
contrast [19, 20]. Loss of that water due to evaporation produces a
marked increase in reflectivity and lesion contrast. In-vivostudies have been published utilizing the fluorescence loss of white
spot lesions on coronal surfaces [12] and thermal imaging to assess
root caries during dehydration [21]. There is a negative association
between the surface zone thickness and lesion permeability; a small
increase in the surface layer thickness of less than 20 µm can lead to a
marked decrease in permeability [22]. In addition, in a closely
related study the surface zone was removed from arrested lesions
producing a corresponding rise in the permeability providing further
confirmation of the role of the surface zone in arresting lesions
[23]. Recent studies have shown that the water absorption bands at
1450 and 1950 nm are advantageous for SWIR reflectance dehydration
measurements and produce higher contrast between sound and demineralized
enamel [24, 25].
The first clinical study to utilize SWIR reflectance dehydration
measurements was recently carried out on the occlusal surfaces of
primary teeth using a compact InGaAs camera and 1400-1750 nm light
[26]. The presence of a highly mineralized transparent surface zone
was also assessed using cross polarization optical coherence tomography
(CP-OCT). The SWIR imaging results were promising showing that the delay
between the application of the forced air and the rise in reflectivity
is a good indicator of lesion activity. However, there was difficulty
fully dehydrating the lesions in the pits and fissures and acquiring
curves suitable for complete analysis of the dehydration kinetics. That
study indicated that additional work is needed to improve the
acquisition of dehydration curves in vivo and further develop
methods for analysis of dehydration curves acquired from the pits and
fissures of the occlusal surfaces. In this study, we choose to use the
1450 nm water absorption band for imaging as opposed to the 1950 nm
water absorption band because compact extended range InGaAs cameras
suitable for clinical use operating beyond 1750 nm are not yet available
and our goal was to assess the performance of a handheld system that can
be used clinically at this time.
Multiple parameters describing the shape of the curves representing the
rate of intensity change during dehydration can be derived from these
curves including delay, ΔI, %Ifin, and rate [25].
Delay represents the initial delay between the time air is applied and
the rise in intensity, ΔI is the change in intensity before and after
dehydration, the rate represents the shape of the rise in intensity and
once the rise begins that typically takes a sigmoidal shape for active
lesions, and %Ifin represents the fraction of the
intensity rise that occurs after the most rapid change in intensity. For
active lesions there is typically an initial delay before the rise in
intensity occurs because the water in the pores near the lesion surface
absorb the incident SWIR light. The curves for active lesions experience
a rapid/steep rise in intensity (high rate) to quickly plateau in
intensity (low %Ifin) since the water in the body of
the lesion can more rapidly escape through the open pores. For arrested
lesions there is a minimal delay since the highly mineralized surface
layer lacks porosity and water. Dehydration occurs slowly (low rate)
because the highly mineralized surface layer blocks the pores in the
lesion and inhibits the loss of water and much of the intensity change
occurs slowly in the tail of the curve (high %Ifin).
The rate of increase in intensity was assessed using the Hill equation
that was developed to assess ligand binding in biochemistry [27].
Previous studies used the sigmoid function to calculate an overall
growth rate (OGR) calculated from two coefficients [8, 9] but we
found that better fits could be achieved using the Hill equation. Both
functions were designed to fit sigmoidal shaped curves. The Hill
equation is given by equation 1.