development of differential criteria on tongue coating ... · tongue body for color, shape,...

ARTICLE IN PRESS+ModelYCTIM-1141; No. of Pages 7

Complementary Therapies in Medicine (2012) xxx, xxx—xxx

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Development of differential criteria on tonguecoating thickness in tongue diagnosis�

Jinsung Kima,∗, Ga-Jin Hana, Bin-Hye Choia, Jae-Woo Parka, Kyungmo Parkb,In-Kwon Yeoc, Bong-Ha Ryua

a Department of Gastroenterology, College of Oriental Medicine, Kyung Hee University, Seoul, Republic of Koreab Department of Biomedical Engineering, School of Electronics and Information, Kyung Hee University, Yongin, Kyunggi-do,Republic of Koreac Department of Statistics, Sookmyung Women’s University, Seoul, Republic of Korea

KEYWORDSTongue diagnosis;Tongue coating;Diagnostic criteria;Digital tongueimaging system;Proportional oddsmodel

SummaryObjective: To develop differential criteria on the tongue coating thickness (TCT), and especiallypropose the standard for judgment on thin and thick coating in tongue diagnosis.Methods: Sixty oriental medical doctors evaluated the TCT (none, thin, and thick coating) in 50realistic tongue photographs revealing from tip-to-root. The photographs were obtained witha digital tongue imaging system (DTIS) which measured the percentages of tongue coating onthe tongue surface. We calculated the match rate which is the ratio in which the assessor’sjudgment is consistent with the decision standard on the tongue coating, and then 24 assessors(≥80% match rate) were selected to improve the reliability of the decision. The agreement levelamong 24 assessors was examined to assess the inter-rater reliability. The correlation betweenTCT judgments and DTIS-measured values was examined to ascertain the reliability of DTISmeasurements. Finally, the assumption probability for the analysis of quantified characteristicsof the tongue coating was calculated with a proportional odds model.Results: The inter-rater reliability was assessed as moderate (� = 0.56) among 24 assessors,the level of correlation between TCT judgments and DTIS measurements in 24 assessors wasrelatively high (0.76, p < 0.01). As the analysis of the proportional odds model, 29.06% was acut-off point to separate no coating and thin coating, 63.51% was a cut-off point to separate

Please cite this article in press as: Kim J, et al. Development ofdiagnosis. Complement Ther Med (2012), doi:10.1016/j.ctim.2

thin and thick coating.Conclusions: The differential criteria for TCT in tongue diagnosis were suggested, and particu-larly thick coating is defined as one that tongue coating which tongue body is invisible, occupyapproximately more than two third areas on the tongue surface.© 2012 Elsevier Ltd. All rights re

� This research was supported by a grant KHU-20091418 from the KyunScience.

∗ Corresponding author at: Department of Gastroenterology, Kyung HeeDongdaemun-gu, Seoul 130-702, Republic of Korea. Tel.: +82 2 958 8895;

E-mail address: [email protected] (J. Kim).

0965-2299/$ — see front matter © 2012 Elsevier Ltd. All rights reserved.doi:10.1016/j.ctim.2012.03.004

differential criteria on tongue coating thickness in tongue012.03.004

served.

g Hee University Program for the Young Researcher in Medical

University Oriental Medicine Hospital, 1 Hoegi-dong, fax: +82 2 958 8895.

dx.doi.org/10.1016/j.ctim.2012.03.004

dx.doi.org/10.1016/j.ctim.2012.03.004

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dx.doi.org/10.1016/j.ctim.2012.03.004

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ongue diagnosis is a useful method to examine the physi-logic function and pathologic changes of the human bodyn Oriental Medicine (OM).1 It consists of visually inspectinghe tongue body for color, shape, moisture, and movementnd assessing tongue coating for color, thickness, distribu-ion, and characteristics at the root.2 The tongue coatingeflects the nature and location of the pathogenic factors,nd often indicates the state of some organs, particularlytomach function.3 Therefore, fastidious observation on thelteration of the tongue coating is particularly required inhe course of the diagnosis and the progress of gastrointesti-al diseases.

The conventional way for tongue diagnosis, including thevaluation of the tongue coating, is to look at the tonguefrom tip-to-root) directly by observers. The tongue coatinghickness (TCT) is expressed as no coating, thin coating, andhick coating. No coating is literally the absence of tongueoating, and the dividing standard between thin and thickoating is whether or not the bottom is visible (thin coating,hrough the tongue coating, one can vaguely see the tongueody; thick coating: through the tongue coating, one can-ot see the tongue body).3 However, these judging criterias insufficient and vague. Moreover, there is no distinct stan-ard with respect to the distribution of the coating on theongue surface. Therefore, in order to improve the low lev-ls of inter- and intra-practitioner agreements, it is requiredhat adequate operational definitions of the tongue charac-eristics including tongue coating.4,5 The inter-practitioneronsistency for the TCT was partially investigated in therevious studies,4,6 but there is no precise operational defi-itions concerning the judging criteria for the TCT.

A digital tongue imaging system (DTIS) was designed tobtain a digital image of the tongue surface, segment thisnto regions and extract the areas corresponding to theongue coating.7 We showed the new possibility that theongue coating can be quantitatively evaluated using theTIS.8 By starting from the percentage of the tongue coat-

ng area among the tongue surface analyzed by the DTIS,e attempted to suggest the differential criteria on theCT compared with three diagnostic endpoints (no coat-

ng, thin coating, and thick coating). First, we verified the0 assessors as to how well they evaluated the TCT usinghe conventional method of tongue diagnosis, we selectedeliable assessors and investigated inter-assessor reliability,hen confirmed the correlation between the TCT judgmentsnd the DTIS-measured values (percentages of tongue coat-ng). Finally, a proportional odds model was applied toalculate the assumption probability for the analysis ofuantified characteristics of the tongue coating.9 The aim ofhis study was to develop differential criteria for the TCT,nd especially propose the standard for judgment on thinoating and thick coating with the amount of tongue coatingn tongue diagnosis.

aterials and methods


ongue photographs and DTIS

e prepared 50 tongue photographs revealing the entireongue surface from tip-to-root. The photographs had high

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PRESSJ. Kim et al.

esolution which selected based on the clarity and realityf the image, depiction of different diagnostic characteris-ics, and diverse aspects of the tongue coating distribution.e used the DTIS to acquire the tongue photographs under

he same conditions and to measure the tongue coatinguantitatively.8

The DTIS consists of the exterior part with an interfaceor the patient’s face, image acquisition part with a high-esolution digital camera, illumination part, and softwareart (Fig. 1). In particular, the interface of the exteriorart was designed to block out outside light, and the DTISoftware controls image acquisition, locating an appropri-te region of the tongue, isolating this from the backgroundsing a snake algorithm, and extracting the areas of theongue coating from the tongue images.7,10,11 The tongueurface on the DTIS tongue images were divided into six sec-ions, as the method of Winkel et al.,12 and calculated theercentage of the tongue coating area for each section, andor the tongue as a whole (Fig. 2). Informed consent wasbtained from each patient before taking their tongue pho-ographs, as approved by the Institutional Review Board ofhe Kyung Hee University Oriental Medicine Hospital.

ssessors and procedures

ixty assessors were recruited to evaluate the tongue coat-ng in the study. They graduated from 6-year programs ofriental medical colleges in Korea, and were working forhe Kyung Hee University Oriental Medicine Hospital as clin-cians. They were reminded about the evaluation methoduch as how to differentiate the TCT and educated on how toivide the tongue surface into 6 areas before participating inhe study. The procedures were performed as two sessions.n the first session, the assessors rated the tongue coatings no coating = 0, thin coating = 1, and thick coating = 2, andated it again in each of 6 areas with the same method inhe second session (the results in the 2nd session will besed in the subsequent study on the relationship betweenhe decision for TCT and the regions of the tongue coat-ng). All data collection was conducted at the same locationnder identical conditions over 50 min. These photographsere presented with a picture viewer software on the LCDonitor (47′′ HD, Samsung, Korea). All assessments were

ndependent, and no assessors were color blind.

ata processing and assessors selection

he features of the TCT judgments on the 50 tonguehotographs were computed as frequency and modeccording to the classification of tongue coating and theTIS-measured values. We regarded the highest numberf the assessors’ choice (mode) as the decision standard.n order to select reliable assessors, we calculated theatch rate, which is the ratio that the assessor’s judgment

s consistent with the decision standard on the TCT (num-er of TCT judgments/50 photographs [%]). The reliablessessors were considered to be ≥80% match rates. The


greement level of the assessors’ judgment for each tonguehotograph was calculated as an agreement rate (numberf TCT judgments/reliable assessors [%]), and investigatedhe inter-rater reliability among the selected reliable

dx.doi.org/10.1016/j.ctim.2012.03.004

Please cite this article in press as: Kim J, et al. Development of differential criteria on tongue coating thickness in tonguediagnosis. Complement Ther Med (2012), doi:10.1016/j.ctim.2012.03.004


Differential Criteria on Tongue Coating Thickness 3

Figure 1 Overview of the digital tongue imaging system (DTIS) and scenes of measurement. In the left part, the lower right sideshows the exterior part of DTIS with interface for patient’s face designed for easy presentation of patient’s tongue to digital camera.The upper left and right sides show the internal composition of DTIS, which contains computer system and software, and parts forimage acquisition and illumination. The interface of the exterior part was designed to block out outside light (right part).

Figure 2 Digital tongue imaging system program display showing acquired tongue image (upper left), extracted tongue substanceimage (upper right), extracted tongue coating image (lower left), and percentage score diagram for tongue coating (lower right).

dx.doi.org/10.1016/j.ctim.2012.03.004


4 J. Kim et al.

Figure 3 Flow chart of data processing. Firstly, 50 tonguephotographs were analyzed as tongue coating percentages withDTIS. Secondly, 60 assessors evaluated TCT as none, thin andthick coating, and match rate was calculated to select reliableassessors. Thirdly, agreement rate was obtained to investigateinter-assessor reliability among assessors who have ≥80% matchrates. Fourthly, correlation between TCT judgments and tonguecoating percentages were compared. Lastly, proportional oddsmodel was applied to calculate assumption probability for anal-yt

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sis of quantified characteristics of tongue coating. DTIS; digitalongue imaging system. TCT; tongue coating thickness.

ssessors. Then, we calculated the correlation between theCT judgments and the DTIS-measured values to ascertainhe reliability of the DTIS measurements. Fig. 3 shows allata processing in the study.

ssumption probability for differential criteria onCT

he proportional odds model is a useful extension of theogistic regression model which allows more than twordered response categories. The model may be repre-ented by a series of logistic regressions with commonegression parameters reflecting the proportional oddsssumption.9

We can treat the DTIS-measured values as the explana-ory variable and the TCT judgments (0 = no coating, 1 = thinoating, and 2 = thick coating) as the response variable. Let


be the response variable and let �i(x) be the probabilityhat Y takes the value j, j = 0, 1, 2 when the DTIS-measuredalue is x. Because the TCT judgments are ordinal responses,

statistical way to model the relationship between Y and x

s≥i(

ents/50 photographs (%). Decision standard is the highestumber of the assessors’ choice (mode). Those who have ≥80%atch rates were regarded as reliable assessors.

s to use logits of cumulative probabilities �j = P[Y ≤ j|x] =1(x) + · · · + �j(x), j = 0, 1, 2. In order to estimate therobabilities �i’s, we used the proportional odds model inhich the cumulative probabilities are written as

j(x) = exp(˛j + ˇx)1 + exp(˛j + ˇx)

for j = 0, 1 and �3(x) = 1

here ˛j’s and ˇ are parameters to be estimated. Setting—1(x) = 0, we obtain the probability �j(x) = �j(x) = �j − 1(x)nd assign the TCT judgments to the coating degree whoserobability is maximum at x.

tatistical analysis

leiss’ � was used as a measure of inter-rater reliability ofhe decision on the TCT among the assessors. It measureshe overall agreements between all the assessors. Conven-ionally, a � of <0.2 is considered poor agreement; 0.21—0.4,air; 0.41—0.6, moderate; 0.61—0.8, strong; and more than.8 near complete agreement.13 Pearson’s correlation wassed to ascertain the relationship between the TCT judg-ents and the DTIS-measured values. The proportional oddsodel was applied to calculate the assumption probabil-

ty for the quantified analysis for the characteristics of theCT.9 Analyses were performed using SAS 9.1 software. Theignificance level was set at p-values equal to or less than.05.

esults

haracteristics of TCT judgments and DTISeasurements

he characteristics of the TCT judgments and the DTISeasurements according to the classification of the tongue

oating are shown Table 1. The match rates in 60 all asses-


ors are presented Fig. 4, and the reliable assessors who had80% match rates were 24 persons. The inter-rater reliabil-

ty was assessed as moderate (� = 0.56) among 24 assessorsTable 2), the frequency of the TCT judgments evaluated

dx.doi.org/10.1016/j.ctim.2012.03.004


Differential Criteria on Tongue Coating Thickness 5

Table 1 Characteristics of TCT judgments and DTIS measurements according to classification of tongue coating on 50 tonguephotographs in 60 assessors.

Classification of TCTa No coating Thin coating Thick coating

Frequency of TCT 8 30 12

DTIS measurementsbMean (%) 31.07 45.97 70.50Median (%) 31.61 47.99 71.06Standard deviation 12.61 11.27 8.27

a Tongue coating thickness.b Percentage of tongue coating measured by digital tongue imaging system.

Table 2 Inter-rater reliability of judgments on tongue coating thickness among 24 reliable assessors.

Variable (tonguecoating thickness)

Observation (numberof photographs)

Endpoints Overall �

of resultStandard error (95%confidence interval)

Assessmentof outcome

Among 24 50 3 0.5580 0.0065(0.5452—0.5708)

Moderate

Table 3 Analysis of maximum likelihood estimates basedon proportional odds model.

Parameter DF Estimate Standard error p-Value

˛1 1 5.0708 1.4233 <.0001

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assessors

by the selected reliable assessors are presented in Fig. 5.The DTIS measurements ranged from 14.8 to 83.0% (average,49.5%), the level of correlation between the TCT judgmentsand DTIS-measured values in 24 assessors was relatively high(0.76, p < 0.01).

Differential criteria on TCT calculated byproportional odds model

Table 1 showed that the thicker degree of the tongue coatingis, the higher the percentage of the tongue coating is, andthe majority of the thick group definitely has a higher per-centage than the 75th percentile of the thin classification.Table 3 shows the analysis of maximum likelihood estimatesbased on the proportional odds model.

According to the analysis, the cumulative probabilities�0(x) and �1(x) are respectively estimated by


�̂1(x) = exp(5.0708 − 0.1747x)1 + exp(5.0708 − 0.1747x)

and

�̂1(x) = exp(11.0995 − 0.1747x)1 + exp(11.0995 − 0.1747x)

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Figure 5 Frequency of TCT judgments according to classificatiotongue photographs. This figure shows assessors’ agreement levelscoating thickness.

˛2 1 11.0995 2.4208 <.0001 ̌ 1 −0.1747 0.0397 <.0001

ig. 6 showed that �̂0(x) < �̂1(x) for x ≥9.06 and �̂1(x) < �̂2(x) for x ≥ 63.51. This impliedhat the tongue coating were classified as no coating, thinoating, and thick coating when the percentages of theongue coating were as follows: [0,29.06); [29.06, 63.51);nd [63.51, 1], respectively.

iscussion


e suggested that the differential criteria for the TCT judg-ents, and especially the standard for judgment on thin

nd thick coating. In this study, we selected 24 assessorsho had ≥80% match rates to increase the reliability of the

n of tongue coating evaluated by 24 reliable assessors on 50 of TCT judgments on each tongue photograph. TCT; tongue

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Figure 6 Assumption probability of each classification oftngue coating at DTIS measurements. The estimates of the prob-abilities that TCT is j, j = 0, 1, 2 (0 = no coating, 1 = thin coating,at

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nd 2 = thick coating), �j(x). DTIS; digital tongue imaging sys-em. TCT; tongue coating thickness.

ecision, referring to the study that the authors used ≥80%or the inter-practitioner agreement of presence of tongueoating.4 The level of agreement among the 24 assessors onhe TCT judgments was moderate (� = 0.56), which was rel-tively high compared with the result of O’Brien et al. (fair,


= 0.22).6 In fact, the inter-practitioner consistency for TCTudgments was partially investigated in the previous studies.0 OM practitioners had a high level of agreement (≥80%)or the presence of tongue coating (yes/no choice) in all 10

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igure 7 Tongue photographs and percentage score diagram of tonmaging system. They are similar to borderline of no coating and th3.51% (lower) in 50 tongue photographs.

PRESSJ. Kim et al.

lides,4 and the level of agreement for TCT (4 endpoints)etween 3 practitioners was fair (Cohen’s � = 0.22) in the 45ealthy Australians with hypercholesterolemia.6 However,he former just used two endpoints, the latter investigatedhe agreements only between 3 practitioners.

In a previous study,8 the agreement between WTCI ratingsnd DTIS assessments was relatively high at r = 0.56 for onexaminer and r = 0.77 for the other (p < 0.01). In this study,he degree of correlation between the TCT judgments andhe DTIS-measured values in 24 assessors was 0.76 (p < 0.01).hus, we decided that we utilized DTIS measurements toevelop the differential criteria on the TCT.

The standard model for quantitative criteria is requiredecause improved consensus on OM diagnostic criteriaesults in an increased agreement level of diagnosis,14

o the proportional odds model was used for developinghe diagnostic standard of the TCT. 29.06% was the cut-ff point to divide into no coating and thin coating, and3.51% was the cut-off point to separate the thin coat-ng from the thick coating (Fig. 6). Among these results,he cut-off point between no coating and thin coatingas relatively high, because it is likely to be reflected

he tongue coating at the root of tongue. Most peopleenerally have tongue coating on the surroundings of circum-allate papillae. If the root of tongue is examined closely,


e can see a little tongue coating on it in spite of nooating. Fig. 7 is the tongue photographs which have thepproximate values of 29.01% and 63.51% in 50 tonguehotographs.

gue coating for differential criteria obtained with digital tonguein coating; 29.01% (upper) and thin coating and thick coating;

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Differential Criteria on Tongue Coating Thickness

The diagnostic criteria and the standard photographs ofthe tongue coating will be able to be used in the educa-tion of students and practitioners to improve the agreementlevel for the TCT judgment in tongue diagnosis. King et al.15

provided an example of this in their development of astandardized pulse-taking procedure and precise opera-tional definitions that resulted in ≥80% agreement between2 practitioners on 10 of 16 pulse categories. Of course,this is not the absolute criteria and needs to be verifiedin a range of clinical settings. However, our suggestionswere produced by credible assessors, so we can at leastestablish a guideline to differentiate the TCT. A few lim-itations of this study need to be acknowledged. First, weused the largest number of the assessors’ choice (mode)as the decision value in the tongue coating assessment,thus the reliability of the decision declined in case of thelow agreement level among the assessors. However, it wasinevitable because there is no absolute standard to evaluatethe TCT. Nevertheless, we could not discard the photographswhich had a low agreement level because the diverse sta-tus of the tongue coating should be reflected. Second,although the DTIS can discriminate between thin and thickanalyzed by color difference, it cannot distinguish heavy(thicker) from thick coating. Besides, it can be very sus-ceptible to differences in lighting when the image is taken.Thus, further work is needed to improve the algorithm anddevice for evaluating the tongue coating to ensure accurateassessments.

The present study is the first trial for the differ-ential criteria of the TCT, The data in our study wasobtained from relatively high reliable assessors selectedfrom well-educated and well-trained OM doctors and theDTIS verified in the previous study. However, our crite-ria are just suggestions based on the probability, so theyshould be verified by more reliable assessors in the clinicalsettings.

In conclusion, the thick coating is the case in whichtongue coating that pinkish tongue body is invisible, occupyapproximately more than two third areas on the tongue sur-face. This will contribute to one part of the standardizationand objectification in tongue diagnosis.


Conflict of interest statement

The authors have no personal or financial conflicts of interestassociated with this work.

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eferences

1. Anastasi JK, Currie LM, Kim GH. Understanding diagnostic rea-soning in TCM practice: tongue diagnosis. Altern Ther HealthMed 2009;15(3):18—28.

2. Chen Jia-xu. Chinese medicine study guide: diagnostics. Bei-jing: People’s medical publishing house; 2007. p. 40—1.

3. Fei Zhao-fu, Gu Yi-di. Mirror of health: tongue diagnosis inChinese medicine. Beijing: People’s Medical Publishing House;2007. p. 15—7.

4. Kim M, Cobbin D, Zaslawski C. Traditional Chinese medicinetongue inspection: an examination of the inter- and intraprac-titioner reliability for specific tongue characteristics. J AlternComplement Med 2008;14(5):527—36.

5. O’Brien KA, Birch S. A review of the reliability of traditionalEast Asian medicine diagnoses. J Altern Complement Med2009;15(4):353—66.

6. O’Brien KA, Abbas E, Zhang J, Guo ZX, Luo R, Bensoussan A,et al. Understanding the reliability of diagnostic variables ina Chinese Medicine examination. J Altern Complement Med2009;15(7):727—34.

7. Eo YH, Kim JG, Yoo HS, Kim JY, Park KM. Quantitative studyon tongue images according to exterior, interior, cold and heatpatterns. J Kor Oriental Med 2006;27(2):134—44.

8. Kim J, Jung Y, Park K, Park JW. A digital tongue imaging systemfor tongue coating evaluation in patients with oral malodour.Oral Dis 2009;15(8):565—9.

9. Brant R. Assessing proportionality in the proportionalodds model for ordinal logistic regression. Biometrics1990;46(4):1171—8.

0. Kass M, Witkin A, Terzopoulos D. Snakes: active contour models.Int J Comput Vis 1987;1(4):321—31.

1. Pang B, Wang K, Zhang D, Zhang F. On automated tongue imagesegmentation in Chinese medicine. In: Proceedings 16th inter-national conference on pattern recognition, 2002, vol. 1. 2002.p. 616—9.

2. Winkel EG, Roldan S, Van Winkelhoff AJ, Herrera D, Sanz M.Clinical effects of a new mouthrinse containing chlorhexidine,cetylpyridinium chloride and zinc-lactate on oral halitosis. Adual-center, double-blind placebo-controlled study. J Clin Peri-odontol 2003;30(4):300—6.

3. Fleiss J, Nee J, Landis J. Large sample variance of kappa in thecase of different sets of raters. Psycho Bull 1979;86:974—7.

4. Zhang GG, Singh B, Lee W, Handwerger B, Lao L, BermanB. Improvement of agreement in TCM diagnosis among TCMpractitioners for persons with the conventional diagnosis of


rheumatoid arthritis: effect of training. J Altern ComplementMed 2008;14(4):381—6.

5. King E, Cobbin D, Walsh S, Ryan D. The reliable measurement ofradial pulse characteristics. Acupunct Med 2002;20(4):150—9.

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