Objectified study on tongue images of patients with lung cancer of different syndromes
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OriginalPaper|Updated:2021-08-27
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Objectified study on tongue images of patients with lung cancer of different syndromes
Objectified study on tongue images of patients with lung cancer of different syndromes
中国结合医学杂志(英文版)2011年17卷第4期 页码:272-276
Affiliations:
1. Department of Oncology, Longhua Hospital, Affiliated to Shanghai University of Traditional Chinese Medicine,Shanghai,China
2. Department of Traditional Chinese Medicine Diagnosis, Shanghai University of Traditional Chinese Medicine,Shanghai,China
Author bio:
Funds:
Supported by Pudong New Area Scientific and Technological Development Fund (No. PKJ2008-Y32), and Pudong New Area, XU Zhen-Ye Traditional Chinese Medicine Studio (No. PWZ2008-22-S02)
Su, W., Xu, Zy., Wang, Zq. et al. Objectified study on tongue images of patients with lung cancer of different syndromes., Chin. J. Integr. Med. 17, 272–276 (2011). https://doi.org/10.1007/s11655-011-0702-6
Wan Su, Zhen-ye Xu, Zhong-qi Wang, et al. Objectified study on tongue images of patients with lung cancer of different syndromes[J]. Chinese Journal of Integrative Medicine, 2011,17(4):272-276.
Su, W., Xu, Zy., Wang, Zq. et al. Objectified study on tongue images of patients with lung cancer of different syndromes., Chin. J. Integr. Med. 17, 272–276 (2011). https://doi.org/10.1007/s11655-011-0702-6DOI:
Wan Su, Zhen-ye Xu, Zhong-qi Wang, et al. Objectified study on tongue images of patients with lung cancer of different syndromes[J]. Chinese Journal of Integrative Medicine, 2011,17(4):272-276. DOI: 10.1007/s11655-011-0702-6.
Objectified study on tongue images of patients with lung cancer of different syndromes
摘要
To describe the characteristic of tongue images of patients with lung cancer of different Chinese medicine (CM) syndromes and to reveal the elemental rule on the changes of the tongue images. A total of 207 patients with lung cancer were divided into four syndrome groups according to the theory of CM: Fei (肺) and Shen (肾) deficiency syndrome (Group A
72 cases)
Pi (脾) deficiency and phlegm deficiency and phlegm) and Shen (deficiency and phlegm) deficiency syndrome (Group A
72 cases)
Pi (deficiency and phlegm) deficiency and phlegm dampness syndrome (Group B
57 cases)
phlegm-heat retention in Fei (Group C
36 cases) and yin asthenia generating intrinsic heat syndrome (Group D
42 cases). The tongue parameters were detected by tongue image digital analysis instrument
and the tongue images were described with qualitative
tongue color and quantitative analysis
respectively. The International Commission on Illumination (CIE) L·a·b (CIELAB) color model was used for the quantitative classification. There was a significant statistical difference between different syndrome groups of lung cancer on tongue color
coating color
and thickness of tongue coating (P<0.01)
and there was significant statistical difference between the four syndrome groups on Lab values of the tongue and coating (P<0.05). The correct identification rate of discriminant function on the raw data was 65.7%
including 72.2% for Group C
69.4% for Group A
69.0% for Group D and 54.4% for Group B. A tongue image digital analysis instrument can objectively describe the tongue features of patients with different syndromes of lung cancer. The tongue diagnosis is very important to syndrome differentiation in CM. Tongue diagnosis should be combined with some important characteristics of syndromes in the future to establish a “combination of four examination methods
including inspection
auscultation
interrogation
and pulse-feeling and palpation” in the tongue diagnostic system.
Abstract
To describe the characteristic of tongue images of patients with lung cancer of different Chinese medicine (CM) syndromes and to reveal the elemental rule on the changes of the tongue images. A total of 207 patients with lung cancer were divided into four syndrome groups according to the theory of CM: Fei (肺) and Shen (肾) deficiency syndrome (Group A
72 cases)
Pi (脾) deficiency and phlegm deficiency and phlegm) and Shen (deficiency and phlegm) deficiency syndrome (Group A
72 cases)
Pi (deficiency and phlegm) deficiency and phlegm dampness syndrome (Group B
57 cases)
phlegm-heat retention in Fei (Group C
36 cases) and yin asthenia generating intrinsic heat syndrome (Group D
42 cases). The tongue parameters were detected by tongue image digital analysis instrument
and the tongue images were described with qualitative
tongue color and quantitative analysis
respectively. The International Commission on Illumination (CIE) L·a·b (CIELAB) color model was used for the quantitative classification. There was a significant statistical difference between different syndrome groups of lung cancer on tongue color
coating color
and thickness of tongue coating (P<0.01)
and there was significant statistical difference between the four syndrome groups on Lab values of the tongue and coating (P<0.05). The correct identification rate of discriminant function on the raw data was 65.7%
including 72.2% for Group C
69.4% for Group A
69.0% for Group D and 54.4% for Group B. A tongue image digital analysis instrument can objectively describe the tongue features of patients with different syndromes of lung cancer. The tongue diagnosis is very important to syndrome differentiation in CM. Tongue diagnosis should be combined with some important characteristics of syndromes in the future to establish a “combination of four examination methods
including inspection
auscultation
interrogation
and pulse-feeling and palpation” in the tongue diagnostic system.
关键词
lung cancertongue diagnosissyndromes of Chinese medicinecomputer technologyobjectification
Keywords
lung cancertongue diagnosissyndromes of Chinese medicinecomputer technologyobjectification
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Department of Pharmacy, the Fourth People’s, Hospital of Ji’nan City, Ji’nan
Department of Respiratory, the Second Affiliated Hospital, College of Medicine of Xi’an Jiaotong University
Biomedicine and Health Research Center, Hangzhou Normal University
Department of Neurology, Beijing Tiantan Hospital, Capital Medical University