Spectrophotometric analysis of two All-Ceramic materials

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Spectrophotometric analysis of two All-Ceramic
materials

• Varun Singh Barath
• University of Cologne, Germany

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Dilemma
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Esthetic Dentistry

• Since ancient times teeth have been an integral
  part of the face
• Animal teeth and Ivory all carved in the form of
  human teeth
• Early 16th Century Mineral teeth

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John Greenwood
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Esthetic Dentistry

• Metal Ceramic restorations 4 decades ago were
  the State of Art
• All-Ceramic restorations advancements in last
  decade have made them popular
• Increase in strength
• Better biocompatiblity
• Excellent optical properties

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• PART 1 Spectrophotometric analysis of two
  All-Ceramic materials with the effect of the
  background shade on the final shade
• PART 2 Proposed Model for Color Prediction using
  Kubelka-Munk theory and Artificial Neural Networks

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Spectrophotometric analysis of two All-Ceramic
materials with the effect of the background shade
on the final shade
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Some aspects of Color

• Color is the perception of light by the mind in
  response to a stimuli from the eye
• It is a visual sensation
• Different colors have different wavelengths
• Visible part of the spectrum 380 750 nm

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Some aspects of Color
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Color systems

• Numerical representation of Color
• International Commission of Illumination
  (Commission Internationale de lEclairage).
• Important colorimetric systems are RGB, XYZ,
  CIELAB, CMC, Munsell system, to name a few

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CIELAB system
Courtesy Handprint media
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CIELAB system

• Estd. 1976 (by the International Commission of
  Illumination (Commission Internationale de
  lEclairage))
• L - vertical, achromatic coordinate
• 0 (black) to 100 (white)
• a - horizontal, green/red coordinate,
• -80 (green) to 80 (red)
• b - horizontal, blue/yellow coordinate
• -80 (blue) to 80 (yellow)

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CIELAB system
Courtesy Handprint media
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CIELAB system

• C - saturation, representing the difference of
  a specific color in relation to gray color of
  the same lightness
• H - hue is represented in the ab plane
• H0 corresponds to red color,
• H90 corresponds to yellow,
• H180 corresponds to green,
• H270 corresponds to blue color

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(No Transcript)
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Experimental Design

• Aim to study the effect of background shade on
  the final shade of All-Ceramic Systems (In-Ceram
  Alumina, Empress2)
• Shades chosen lighter than the lightest, darker
  than the darkest and one from the middle
• Luting Agents ZnPO4 , GIC, RLA
• Background Standard black and white

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Armamentarium

• Ceramic samples as clinical units

In-Ceram Alumina, 1,0 mm
In-Ceram Alumina, 1,4 mm
Empress 2, 1,4 mm
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Armamentarium

• Cements

Luting agent Shade Commercial name Manufacturer
Zinc Phosphate Cement Neutral PhosphaCEM PL Vivadent Ets. Lichtenstein
Glass Ionomer Cement Universal Ketac-Cem radiopaque ESPE Dental AG, Germany
Composite Luting agent A3 Compolute Aplicap ESPE Dental AG, Germany
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Armamentarium

• Micrometer (Mitutoyo, Japan)

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Armamentarium

• Sample Preparation (Simulating a clinical
  All-Ceramic restoration)

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Armamentarium

• Spectrophotometer (Dr. Lange GmBH, Berlin,
  Germany)

Spectral Range 380 720nm Viewing Geometry d/8
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Armamentarium

• Standard Black and White Backgrounds

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Formula for color difference

• ?E (L w L b)2 (a w a b)2 (b w b b)2 ½
• ?L L w L b
• ?a a w a b
• ?b b w bb

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Clinically significant color differences

• ?E gt 3.7 Very Poor match (Johnston and Kao,
  1989)
• ?E gt 2 Clinically not acceptable (Touati et
  al, 1993)
• ?E 2 Clinically acceptable (OBrien et al,
  1990)
• ?E lt 1 Not appriciable (Kuehni and Marcus,
  1990)

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Results
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Empress2 ?L
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Empress2 ?a
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Empress2 ?b
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Empress2 ?E
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Inceram Alumina ?l 1,40mm
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Inceram Alumina ?a 1,40mm
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Inceram Alumina ?b 1,40mm
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Inceram Alumina ?E 1,40mm
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Inceram Alumina ?l 1,00mm
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Inceram Alumina ?a 1,00mm
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Inceram Alumina ?b 1,00mm
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Inceram Alumina ?E 1,00mm
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Correlation ?Lwb and ?Ebcwc(of translucency
with the color change due to luting agent)

• Pearsons correlation (r)
• Compolute 0.13 p 0.38 0.21 0.05 mm
• GIC 0.05 p 0.76 0.24 0.04 mm
• ZnPO 0.82 p 0.00 0.24 0.10 mm

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Cements ZnPO, GIC, RLA
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Cements ZnPO, GIC, RLA
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Conclusions

• All-Ceramics due to their translucency have an
  effect of the luting agents and background shade
  (dentine/discolored tooth/post) on the final
  shade
• The two All-Ceramics examined showed a shift in
  the the ?a values due to black background (shift
  towards red) (reflection curves at various
  wavelengths to be investigated)

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Conclusions

• As ceramic thickness increases the effect of
  luting agent and background decreases
• Depending on the luting agent the background
  shade can be partially masked
• Luting agents have an effect on the final color

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Conclusions

• The outcome of the ceramic restorations cannot be
  predicted with accuracy
• Not only the color, that is percieved by the eye
  is important but also the optical properties of
  the materials shoud be studied for predicting the
  outcome of the all ceramic restorations

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Future Work
Model for Color Prediction using Kubelka-Munk
theory and Artificial Neural Networks for all
ceramic restorations
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Kubelka-Munk theory

• color mixing model which describes the
  reflectance and transmittance of a color sample
  with respect to the absorption and scattering
  spectra of the material
• mathematical model used to describe the
  reflectance
• considers the absorption and scattering in a
  colored sample of fixed thickness

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Kubelka-Munk theory

• four factors
• an absorption spectrum K(? )
• a scattering spectrum S(?)
• the sample thickness X
• the reflectance spectrum of the substrate or
  backing Rp(? )

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Kubelka-Munk (KM) theory

• Has been used to measure the reflectance of
  All-Ceramic materials (Miyagawa and Powers,
  (1982) Woolsey, G. D., W. M. Johnston, et al.
  (1984) Cook and McAree, (1985)
  ......................................... Davis,
  B. K., W. M. Johnston, et al. (1994))
• The data on the absorption/scattering
  coefficient ratio (K/S values) at certain
  wavelengths are necessary for the creation of a
  computer database and as well as for the computer
  color prescription (Paravina R.D, (1999) )

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Artificial Neural Network (ANN)

• The ANN technology is a computer system solution
  with a surprising capacity to learn from input
  data
• computer-based algorithms which are modeled on
  the structure and behaviour of neurons in the
  human brain and can be trained to recognize and
  categorize complex patterns.

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Artificial Neural Network (ANN)

• Neural networks are well suited for data mining
  tasks due to their ability to model complex,
  multi-dimensional data
• Some applications of ANN.
• Stock market prediction
• Weather prediciton
• Speech recognition
• Face recognition.........................

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Artificial Neural Network (ANN)
Threshold Logical Unit
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Artificial Neural Network
Feed forward fully connected back propagation
algorithm for weight adjustments
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CIELab for ANN ??

• ADVANTAGES
• Easier access to CIELab data
• Already existing databases
• DISADVANTAGES
• More experimental work required
• Does not predict the reflectance spectra at
  various thickness

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Software engineeringWaterfall Model
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ColPres (Color Prescription)

• Development of an algorithm
• Development of test Database (MySQL)
• Testing the algorithm
• Development of a Complete Database (MySQL)
• Full implementaion of the algorithm (Java)

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Clinical Implication of ColPres
ShadeEye-NCC
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Clinical Implication of ColPres
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Million dollar Smile
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Thank you for your attention.