Spectrophotometric analysis of two All-Ceramic materials

Varun Singh Barath

University of Cologne, Germany

Dilemma

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

John Greenwood

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

• 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

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

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

Some aspects of Color

Color systems

• Numerical representation of Color

• International Commission of Illumination (Commission Internationale de l’Eclairage).

• Important colorimetric systems are RGB, XYZ, CIELAB, CMC, Munsell system, to name a few

CIELAB system

Courtesy: Handprint media

CIELAB system

• Estd. 1976 (by the International Commission of Illumination (Commission Internationale de l’Eclairage))

• 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);

CIELAB system

Courtesy: Handprint media

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 H=0° corresponds to red color,

H=90° corresponds to yellow,

H=180° corresponds to green,

H=270° corresponds to blue color

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

Armamentarium

• Ceramic samples as clinical units

In-Ceram Alumina, 1,0 mm

In-Ceram Alumina, 1,4 mm

Empress 2, 1,4 mm

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

Armamentarium

• Micrometer (Mitutoyo, Japan)

Armamentarium

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

Armamentarium

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

Spectral Range: 380 – 720nm

Viewing Geometry: d/8°

Armamentarium

• Standard Black and White Backgrounds

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

Clinically significant color differences

• ∆E > 3.7 : Very Poor match (Johnston and Kao, 1989)

• ∆E > 2 : Clinically not acceptable (Touati et al, 1993)

• ∆E ≤ 2 : Clinically acceptable (O‘Brien et al, 1990)

• ∆E < 1 : Not appriciable (Kuehni and Marcus, 1990)

Results

Empress2 ∆L

151515N =

CORE

500300100

DLW

B

14

12

10

8

6

4

2

0-2

555 555 555N =

CORE

500300100

DLW

CB

C

16

14

12

10

8

6

4

2

0

-2

CEMENT

Compolut

GIC

ZnPO

Empress2 ∆a

151515N =

CORE

500300100

DA

WB

5

4

3

2

1

0

-1

555 555 555N =

CORE

500300100

DA

WC

BC

5,0

4,5

4,0

3,5

3,0

2,5

2,0

1,5

1,0

CEMENT

Compolut

GIC

ZnPO

Empress2 ∆b

151515N =

CORE

500300100

DB

WB

12

10

8

6

4

2

0-2

555 555 555N =

CORE

500300100

DB

WC

BC

14

12

10

8

6

4

2

0

CEMENT

Compolut

GIC

ZnPO

Empress2 ∆E

151515N =

CORE

500300100

DE

WB

20

10

0

555 555 555N =

CORE

500300100

DE

WC

BC

20

10

0

CEMENT

Compolut

GIC

ZnPO

42

Inceram Alumina ∆l 1,40mm

151515N =

CORE

al4al2al1

DLW

B

7

6

5

4

3

2

1

0

555 555 555N =

CORE

al4al2al1

DLW

CB

C

6

5

4

3

2

1

0

-1

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆a 1,40mm

151515N =

CORE

al4al2al1

DA

WB

2,8

2,6

2,4

2,2

2,0

1,8

1,6

1,4

1,2

1,0

555 555 555N =

CORE

al4al2al1

DA

WC

BC

2,5

2,0

1,5

1,0

,5

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆b 1,40mm

151515N =

CORE

al4al2al1

DB

WB

8

6

4

2

0

-2

555 555 555N =

CORE

al4al2al1

DB

WC

BC

6

5

4

3

2

1

0

CEMENT

Compolut

GIC

ZnPO

74

65

62

Inceram Alumina ∆E 1,40mm

151515N =

CORE

al4al2al1

DE

WB

10

8

6

4

2

0

555 555 555N =

CORE

al4al2al1

DE

WC

BC

8

7

6

5

4

3

2

1

0

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆l 1,00mm

151515N =

CORE

al4al2al1

DLW

B

12

10

8

6

4

2555 555 555N =

CORE

al4al2al1

DLW

CB

C

16

14

12

10

8

6

4

2

0-2

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆a 1,00mm

151515N =

CORE

al4al2al1

DA

WB

3,0

2,5

2,0

1,5

1,0

,5

0,0

46

555 555 555N =

CORE

al4al2al1

DA

WC

BC

3,5

3,0

2,5

2,0

1,5

1,0

,5

0,0

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆b 1,00mm

151515N =

CORE

al4al2al1

DB

WB

9

8

7

6

5

4

3555 555 555N =

CORE

al4al2al1

DB

WC

BC

10

8

6

4

2

0

CEMENT

Compolut

GIC

ZnPO

Inceram Alumina ∆E 1,00mm

151515N =

CORE

al4al2al1

DE

WB

14

12

10

8

6

4

555 555 555N =

CORE

al4al2al1

DE

WC

BC

16

14

12

10

8

6

4

2

0

CEMENT

Compolut

GIC

ZnPO

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

Cements: ZnPO, GIC, RLA

101010N =

CEMENT

ZnPOGICcompolut

DLW

B

60

50

40

30

20

10

0101010N =

CEMENT

ZnPOGICcompolutD

AW

B

4

3

2

1

0

-1

Cements: ZnPO, GIC, RLA

101010N =

CEMENT

ZnPOGICcompolut

DB

WB

18

16

14

12

10

8

6

4

20

101010N =

CEMENT

ZnPOGICcompolut

DE

WB

60

50

40

30

20

10

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)

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

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

Future Work

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

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

Kubelka-Munk theory

• four factors: – an absorption spectrum K(λ )– a scattering spectrum S(λ)– the sample thickness X– the reflectance spectrum of the substrate or

backing Rp(λ )

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) )

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.

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.........................

Artificial Neural Network (ANN)

Threshold Logical Unit

Artificial Neural Network

Feed forward fully connected back propagation algorithm for weight adjustments

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

Software engineeringWaterfall Model

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)

Clinical Implication of ColPres

ShadeEye-NCC™

Clinical Implication of ColPres

Million dollar Smile

Thank you for your attention.