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Comprehensive evaluation chronic pelvic pain based on fuzzy matrix calculation
Neurocomputing 173 (2016) 2097–2101
Contents lists available at ScienceDirect
Neurocomputing journal homepage: www.elsevier.com/locate/neucom
Brief Papers
Comprehensive evaluation chronic pelvic pain based on fuzzy matrix calculation Xinghu Yu a, Wenfeng Meng b, Liangbi Xiang c,n a
Liaoning Medical University, No. 3-40, Songpo Road, Linghe District, Jinzhou, 121001, China School of Electronic Science and Engineering, Jilin University, No. 2699, Qian jin Street, Changchun 130012, China c Liaoning Medical University, No. 3-40, Songpo Road, Linghe District, Jinzhou, 121001, China b
art ic l e i nf o
a b s t r a c t
Article history: Received 4 July 2015 Received in revised form 22 September 2015 Accepted 2 October 2015 Available online 20 October 2015
The gynecological chronic pelvic pain (CPP) is characterized by complicated pathogenesis, diverse manifestation and high incidence rate, which can not only bring physical and psychological burdens to the patients, but also affect their lives and work seriously. Accurate pathological diagnosis, which has always been a difficult problem for clinicians, is critical for proper choice of next treatment. This paper proposed an approach of fuzzy comprehensive evaluation based on fuzzy matrix calculation to diagnose the causes of CPP. A study was carried out to evaluate the diagnostic value by comparing fuzzy comprehensive evaluation method with clinician experience-based diagnosis method which results in the diagnostic accuracy (72.5% vs 55.0%, Po 0.05). It shows that the fuzzy comprehensive evaluation is an effective method to diagnose causes of gynecologic chronic pelvic pain. & 2015 Elsevier B.V. All rights reserved.
Keywords: Chronic pelvic pain Gynecological diseases Fuzzy matrix calculation
1. Introduction With the life and work pressure aggravation, many people often feel slight pain in lower abdomen irregularly, which is defined as chronic pelvic pain in medicine. The pain is more widespread and severe in female patients, and the epidemiological surveys show that there is an upward trend of the morbidity of Chronic Pelvic Pain (CPP) in recent years, at the same time, including many unexplained gynecological CPP. CPP brings physical and psychological burdens to females and affects their lives and work seriously. Moreover, the inappropriate treatments will add more suffering to patients and waste lots of medical resources. Therefore, the research of correct diagnosis and suitable treatments has been a hot topic in recent years. Currently, the main diagnostic method is still based on the method of clinical experience. The clinicians obtain the diagnostic results by comprehensive analysis of symptoms, signs and many auxiliary examinations which mainly consist of blood detection, ultrasonography, pelvic computed tomography (CT), magnetic resonance imaging (MRI) and so on. For the time being, correct pathological diagnosis is the ultimate diagnostic work, which is the first step to guide the proper clinical treatments, but it has always been a difficult problem for clinicians [1]. With the application of laparoscope in recent years, we can take the doubted n
Corresponding author. E-mail address: [email protected] (L. Xiang).
http://dx.doi.org/10.1016/j.neucom.2015.10.003 0925-2312/& 2015 Elsevier B.V. All rights reserved.
tissue under observation to do pathological examination. Diagnosis combining with pathological examination is considered as golden standard, but the patients should bear the risk and trauma caused by surgery. At the same time, postoperative chronic inflammation and tissue adhesion can arouse the pain again. Therefore, some patients would endure the pain rather than simply accept a laparoscope examination [2,3]. It is universally acknowledged that the symptoms and signs are subjective and fuzzy and accurate diagnosis depends mostly on experience of clinicians and available examinations. Therefore, different clinicians may give different diagnostic results about a single kind of disease. So, if there is one more reasonable and convincible method to diagnose the causes of CPP, and if we can make an experts system which is combined with lots of pretty experienced doctors' knowledge and clinical data, we can form a diagnostic system to diagnose the causes of CPP. It will increase the level of diagnosis highly and improve the efficiency of patients' medical treatments. At present, the comprehensive evaluation that based on fuzzy matrix calculation is an efficient method to quantize the subjective and fuzzy medical phenomenon. Subsequently, computer-aided diagnosis (CAD) system based on the method is a practical innovation. At the beginning, the method was applied in the fields of gerontology, anesthesiology, medical informatics, and it gradually extended to Chinese medicine, surgical fractures [4–9], fetal intrauterine distress and premature monitoring, gynecological ultrasound exam, etc. [10,11]. Among the process, the method and
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X. Yu et al. / Neurocomputing 173 (2016) 2097–2101
CAD system were perfected step by step, and got lots of good evaluations for improving the diagnosis efficiency and quality. Now, more and more fields begin to explore and use them [12–14]. Recently, in addition to the above traditional diagnosis method, there is no other math methods or CAD systems to do the gynecological CPP diagnosis. Based on the above discussion, this paper puts forward the fuzzy comprehensive evaluation method that based on fuzzy matrix calculation, which could be used to find the gynecological causes of CPP in the aspect of clinical diagnosis. In this paper, we firstly analyze 460 clinical cases and extract the related statistical data to set up a fuzzy matrix. Secondly, we obtain weight value by averaging several experts experience, then we can get an exact figure by synthesizing fuzzy matrix and weight value according to fuzzy mathematics algorithm. At last, we evaluate the diagnostic value by comparing fuzzy comprehensive evaluation method with clinician experience-based diagnosis method. The paper is organized as follows. In Section 2, background of chronic pelvic pain is briefly outlined. In Section 3, we make an illustration of fuzzy matrix calculation and the detailed procedures. In Section 4, clinical application and diagnostic value evaluation are exploited to show the effectiveness of this approach. The conclusions are given in the Section 5.
2. Background of chronic pelvic pain (CPP)
calculation method [24,25]. The fuzzy comprehensive evaluation method is based on fuzzy calculation, it is a quantitative method to describe fuzzy phenomenon comparing with modern mathematics the clarity and accuracy. It builds up the fuzzy matrix on the basis of the statistical data, then we can get precise conclusion through fuzzy mathematical algorithms, this is the basic principle of the method [26–29]. The detailed procedures of fuzzy comprehensive evaluation are as follows: 3.1. Define an evaluation factors U and evaluation sets V U ¼ fu1 ; u2 ; …; un g V ¼ fv1 ; v2 ; ⋯; vn g
ði ¼ 1; 2; ⋯; nÞ ðj ¼ 1; 2; ⋯; nÞ
ð1Þ ð2Þ
U stands for an evaluation factor set, it is comprised of many subsets, namely, ui , which show the typical symptoms, signs and many auxiliary examinations that collected from clinical data or the diagnostic golden standard. vj consists of evaluation sets V, which is extracted from generalized diseases. 3.2. Establish membership degree and fuzzy matrices Membership degree means the frequency that ui appears in vj , with r ij representative. Membership degree defines fuzzy phenomenon a quantitative description, it is usually constructed through the following several ways:
Definition of chronic pelvic pain by the American College of Obstetricians and Gynecologists [15–17] is no cyclical pain of at least 6 months duration that appears in locations of the pelvis, anterior abdominal wall, lower back or buttocks. Most of the patients take waist and abdomen pain as the main performance and the pain often aggravates during menstruation or labor, it can be associated with dyspareunia and infertility. The World Health Organization analysis report [1,18] shows that an estimated worldwide prevalence of CPP is 2.1–24%. However, this data may be underestimated because a large number of questionnaires show that up to 40% of the people do not seek medical diagnosis and treatments even they suffer from the pain. Currently, many physical or functional disabilities of abdominal viscera, as well as mental and neurological disorders can cause chronic pelvic pains [19–21], which often occur in the female reproductive system, urinary system, digestive system, musculoskeletal system, mental and neurological function system. The common gynecological diseases that cause CPP include (1) endometriosis; (2) adenomyosis; (3) chronic pelvic inflammatory disease; (4) pelvic adhesion; (5) ovarian tumor; (6) uterine tumor, etc. [2,22,23]. Some relative clinical manifestations include lower abdomen pain, menstruation and/or leucorrhea change, the change of size and/or character in uterus and its accessory, etc. Many of them are related to uterine or pelvic surgeries. The kinds of diseases and manifestations are so complicated which are difficult to diagnose. However, a firm diagnosis is the key to next clinical treatment. At present, the most common diagnostic methods are inquiry, physical examination and ultrasonic testing in hospitals with different levels of services. However, different clinicians may give different diagnostic results for the same patient because of their different clinical experience. From this perspective, traditional diagnostic method is subjective and low-efficiency. Therefore, comprehensive evaluation chronic pelvic pain that based on fuzzy matrix calculation is an significant exploration.
used to determine weight value. Each expert independently gives the weight value of each factor according to importanct degree of the U to V, then we take the average value as its final weight value. If there is the evaluation factor in a patient, we take the corresponding weight value. However, if there is none, we take it as zero.
3. Fuzzy matrix calculation
3.4. Synthesize the fuzzy matrix R with weight value set A
Fuzzy sets was established by Zadeh LA in 1965, it developed nearly half a century from the fuzzy logics theory to the fuzzy
We get B by applying algorithm "" to weight value set A and fuzzy matrix R (4 means take the smallest number, 3 means take
(1) Fuzzy statistics: through analysis of clinical data or other related database to determine membership degree. (2) Factor weight method: according to the significance of the evaluation factors to evaluation sets to determine membership degree. (3) Expert experience method: comprehensive analysis a number of specialists, it can avoid single subjective factor. (4) Analysis and reasoning method: according to mathematical reasoning method and model to determine membership degree. In the above four ways, fuzzy statistics is a time-consuming but more scientific and efficient method, so it has been widely applied to determinate the membership degree. If we make a definition that t ij stands for the number of ui appears in vj , and T j is the total number of evaluation subset vj , we can get r ij by formula (3), and establish fuzzy matrices Rij t ij t ij r ij ¼ 0≦ ≦1 ð3Þ Tj Tj 3.3. Set weight value distribution in A A ¼ ða1 ; a2 ; …; an Þ
ði ¼ 1; 2; ⋯; nÞ
ð4Þ
A is a weight value set, ai A A, weight value (ai ) reflects the importance of the evaluation factor to the evaluation set, and n P ai ¼ 1ði ¼ 1; 2; ⋯; nÞ. Expert experience method is commonly i¼1
X. Yu et al. / Neurocomputing 173 (2016) 2097–2101
the biggest number [30]), then we get C by normalizing B (as show in formula (5) and (6)), B ¼ AΟR ¼ ðb1 ; b2 ; …; bn Þ; bj ¼ 3 ai 4 r ij ð5Þ C ¼ ðc1 ; c2 ; ⋯; c6 Þ; ci ¼ bi=
n X
bj ;
ði ¼ 1; 2; ⋯; 6Þ
ð6Þ
i¼1
3.5. Judge the maximum membership degree M ¼ maxðc1 ; c2 ; ⋯; c6 Þ
Table 1 Gynecological diseases statistics. Disease
Disease number
Percentage (%)
Endometriosis (ν1 ) Adenomyosis (ν2 ) Chronic pelvic inflammatory disease (ν3 ) Pelvic adhesion (v4 ) Ovarian tumor (v5 ) Uterine tumor ()
188 127 48 35 23 39
40.9 27.6 10.4 7.6 5.0 8.5
ð7Þ
M is the largest number in C set (formula (7)), the evaluation set that M corresponding to is the finally evaluation result, which is the most probable gynecological disease that causes CPP.
4. Procedures of CPP diagnosis by fuzzy matrix calculation We collected 460 clinical cases with a history of CPP. All the gynecological causes were identified by pathologic diagnosis (Table 1), and we extracted 17 kinds of significant evaluation factors subset, namely: (1) secondary dysmenorrheal; (2) irregular abdominal pain; (3) menstruation change; (4) infertility (primary or secondary); (5) large size/hard characteristics of uterus on palpation; (6) thickened/tenderness of accessory on palpation; (7) cervix change (erosion, polyp, hypertrophy, Naboth cyst, neoplasm, etc.); (8) large uterus/uneven echo of muscle layer under B ultrasound; (9) abnormal accessory echo under B ultrasound; (10) leucorrhea change; (11) elevated serum CA125 (Z35 U/ml); (12) history of uterine surgery (hysteromyomectomy, cesarean section, complete curettage of uterine cavity, etc.); (13) history of pelvic surgery; (14) low age (ager35 years); (15) middle age (age 36 years-pre-menopause); (16) post-menopause; (17) mental state or weight change, etc. Finally, by formula (3) we obtain every membership degree and establish fuzzy matrices R176 (as show in (8)). 0:195
0:216
0:125
0:171
0:116
0:177
0:143
0:103
0:227
0:171
0:224
0:132
0:097
0:288
0:147
0:120
0:143
0:205
0:268 0:106
0:012 0:301
0:381 0:111
0:261 0:133
0:000 0:109
0:078 0:240
0:238
0:060
0:210
0:211
0:196
0:076
0:147
0:255
0:221
0:118
0:077
0:182
0:140
0:283
0:091
0:142
0:130
0:214
R ¼ 0:235 0:166
0:089
0:212
0:179
0:202
0:083
0:140
0:370
0:001
0:095
0:228
0:198
0:258
0:113
0:164
0:201
0:066
0:133 0:120
0:212 0:231
0:174 0:079
0:178 0:180
0:117 0:228
0:186 0:162
0:290
0:026
0:183
0:207
0:202
0:092
0:119
0:224
0:166
0:156
0:128
0:198
0:050
0:085
0:071
0:098
0:437
0:25
0:132
0:158
0:373
0:121
0:096
0:114
¼ 17Ai =6
ð8Þ
5.1. Clinical application Case: female, 45 years old, childbearing history: 1-0-1-1, accepted curettage of uterine cavity at 27, gave birth to a daughter at 29 by cesarean section, menstrual cycle: 14 4–6/30, moderate menstrual volume, began to secondary dysmenorrheal since 5 years ago, and it aggravated gradually. Now the pain was so serious at menstrual period that affected the normal work and dai ly life. She needed to stay in bed and painkillers was inoperative. No abdominal pain at other time. Recently, the menstrual volume was more than before. Menstrual cycle and leucorrhea was normal. Gynecological examination: the uterine size was as large as 3 months pregnant, slight hard, no tenderness on palpation, mild cervical erosion. B ultrasound: uterine size 85 78 75 mm3 with uneven echo of muscle layer, no significant changes in body weight and mental state, serum CA125 64.02 U/ml. Diagnosis procedure: According to above procedures and formula (1)–(10), we got the results: A ¼ ð0:325; 0; 0; 0; 0:216; 0; 0; 0:248; 0; 0; 0:221; 0:240; 0:127; 0; 0:242; 0; 0Þ
ð11Þ
C ¼ 0:163=c1 ; 0:204=c2 ; 0:143=c3 ; 0:147=c4 ; 0:165=c5 ; 0:178=c6
B ¼ AοR ¼ ð0:198; 0:248; 0:174; 0:178; 0; 201; 0:216Þ
ð13Þ
M ¼ 0:204=c2
ð14Þ
Analyzed the final result that M ¼0.204/c2 , we inferred the cause of chronic pelvic pain was actinomycosis (c2 ). The patient accepted laparoscopic assisted vaginal hysterectomy (LAVH). The uterine size was increscent under laparoscope observation and accessories were normal. Adenomyosis and myoma of uterus were confirmed at the final pathological diagnosis, which was consistent with the result of fuzzy comprehensive evaluation. 5.2. Accuracy analysis
ð9Þ
A; ¼ 0:325; 0:199; 0:139; 0:046; 0:216; 0:232; 0:120; 0:248; 0:273; 0:030; 0:221; 0:240; 0:127; 0:135; 0:242; 0:012; 0:028Þ
5. Clinical application and evaluation
ð12Þ
Five clinical experienced attending doctors and chief physicians gave their independent results. If the number of evaluation factors was more, then ai is relatively small, we could adjust the Ai by formula (9), finally we got A; (formula (10)). A;i
2099
ð10Þ
Select another 40 cases with certain pathological results in CPP, compared the fuzzy comprehensive evaluation method with clinician experience-based method the diagnosis accuracy (show in Table 2). (1) Accuracy is quantized by rate of correct diagnosis, if n stands for number of correct diagnosis, N stands for number of total cases. Accuracy ¼
n 100% N
ð15Þ
According to formula (15), the accuracy of fuzzy comprehensive b evaluation method 72.5% (a þ N 100%) is higher than the accuracy þc of doctor experience-based method 55.0% (a N 100%). There is 2 statistically significant difference (x ¼ 4:0; P o 0:05). Therefore,
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Table 2 Diagnosis analysis between fuzzy comprehensive evaluation and clinicians experience-based method. Fuzzy comprehensive evaluation method
þ Total
Clinician experience-based method þ
21 (a) 1 (c) 22
8 (b) 10 (d) 18
Total
29 11 40 (N)
x2 ¼4.0, P o0.05.
the fuzzy comprehensive evaluation method in diagnosis of CPP is an efficient method. (2) Among the 40 cases, there are 10 cases inferred as the causes of chronic pelvic pain according to the fuzzy comprehensive evaluation method, but we are unable to get the pathological results. Then we compared inferred results with MRI, which is known as a highly accurate and non-invasive detection on diagnosis gynecological diseases. There are 7 cases are consistent with the results of MRI. We think the speculation accuracy is as high as 70%, so the fuzzy comprehensive evaluation method can predict the potential causes of chronic pelvic pain. 5.3. Discussion The usage of fuzzy comprehensive evaluation, which is based on fuzzy matrix calculation to diagnose the gynecological causes of CPP, is an initial investigation. It is hard to avoid subjectivity because of weight value assignment process combining with the subjective expert evaluation method. The relative methods to reduce the subjectivity of quantification process are as follow: (1) take multi-central cooperation, collect more information of the evaluation elements; (2) improve the present methods, integrate different mathematical models; and (3) increase the number of samples and evaluation experts. The investigation establishes a foundation for the next application in CAD system, its advantage will be gradually approved and be made use of comprehensively. Finally, it will not only improve doctors’ work efficiency, but also help patients achieve self-diagnosis of their diseases. According to the mode, when it uses the chief complaint and physical examination datum as the evaluation factor and the diseases as the evaluation set, it can be applied to the diagnosis of the diseases in general. When the complaints and examination datum obtain after drug treatments and we use curative effects as diagnosis results, it can be applied to drug effects assessment and drug dosage adjustment [31]. Normalized ci shows the probability of relative diseases and it makes a guidance in the study of the relationship between diseases and its molecular mechanisms. Modern evidence-based medicine advocates to use a lot of best evidences to get the best conclusions. It helps medicine realize a leap from traditional experience-based to modern evidence-based. The application of fuzzy comprehensive evaluation in medicine can be treated as a special mode of evidence-based medicine, because the method quantizes fuzzy diagnosis factors and completely avoids individual subjective experience in order to make it more objective. It provides gynecological disease diagnosis of a novel method.
6. Conclusion The paper preliminarily makes use of fuzzy comprehensive evaluation to analyze the gynecological diseases that take chronic
pelvic pain as the main symptoms. The final result is obtained by fuzzy matrix calculation and analysis of clinical datum with expert experience, and there is a higher diagnostic accuracy when compared with doctor experience-based method. Additionally, it also plays an important role in prediction. So, comprehensive evaluation based on fuzzy matrix calculation is an efficient and scientific method in diagnosis of gynecological diseases that causes CPP, and it also improves the breadth and depth of the comprehensive diagnosis. The next step is to establish CAD system make it extensively usage in clinic. Medical science will break through the bondage of narrow experience-based medicine, and develop towards the direction of quantitative, computable, controlled and predictable. With the influence of connection, permeation and transformation among many subjects, applied mathematics combining with the computer technology will promote medicine development better and faster in the future.
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Xinghu Yu was born in Yantai City, China, in 1988. He received the B.M. degree in clinical medicine from Binzhou Medical University. And now he is currently pursuing the M.M. degree in orthopeadic surgery from Liaoning Medical University, and Department of Orthopedics Surgery, General Hospital of Shenyang Military Area Command. His research interests include basic spinal diseases and spinal cord injury and its repair.
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Wenfeng Meng received his B.S. degree in electronics and information engineering from Harbin Institute of Technology, Harbin, China in 2007 and the M.S. degree in electronics and information engineering from Jilin University, Changchun, China in 2015, respectively. His research interest includes embedded system, direction of Multi-axis robots and Detection equipment.
Liangbi Xiang received the B.M. degree in clinical medicine from the Fourth Military Medical University in 1985. He is currently a chief physician and director of the Orthopedics Department in Shenyang Military Region General Hospital. He has accumulated rich clinical experience in the diagnosis and treatment of spinal disorders and limbs trauma, especially in the cervical spondylosis, thoracic diseases and the lower lumbar spine instability and limbs severe and complicated trauma with deep attainments.
Contents lists available at ScienceDirect
Neurocomputing journal homepage: www.elsevier.com/locate/neucom
Brief Papers
Comprehensive evaluation chronic pelvic pain based on fuzzy matrix calculation Xinghu Yu a, Wenfeng Meng b, Liangbi Xiang c,n a
Liaoning Medical University, No. 3-40, Songpo Road, Linghe District, Jinzhou, 121001, China School of Electronic Science and Engineering, Jilin University, No. 2699, Qian jin Street, Changchun 130012, China c Liaoning Medical University, No. 3-40, Songpo Road, Linghe District, Jinzhou, 121001, China b
art ic l e i nf o
a b s t r a c t
Article history: Received 4 July 2015 Received in revised form 22 September 2015 Accepted 2 October 2015 Available online 20 October 2015
The gynecological chronic pelvic pain (CPP) is characterized by complicated pathogenesis, diverse manifestation and high incidence rate, which can not only bring physical and psychological burdens to the patients, but also affect their lives and work seriously. Accurate pathological diagnosis, which has always been a difficult problem for clinicians, is critical for proper choice of next treatment. This paper proposed an approach of fuzzy comprehensive evaluation based on fuzzy matrix calculation to diagnose the causes of CPP. A study was carried out to evaluate the diagnostic value by comparing fuzzy comprehensive evaluation method with clinician experience-based diagnosis method which results in the diagnostic accuracy (72.5% vs 55.0%, Po 0.05). It shows that the fuzzy comprehensive evaluation is an effective method to diagnose causes of gynecologic chronic pelvic pain. & 2015 Elsevier B.V. All rights reserved.
Keywords: Chronic pelvic pain Gynecological diseases Fuzzy matrix calculation
1. Introduction With the life and work pressure aggravation, many people often feel slight pain in lower abdomen irregularly, which is defined as chronic pelvic pain in medicine. The pain is more widespread and severe in female patients, and the epidemiological surveys show that there is an upward trend of the morbidity of Chronic Pelvic Pain (CPP) in recent years, at the same time, including many unexplained gynecological CPP. CPP brings physical and psychological burdens to females and affects their lives and work seriously. Moreover, the inappropriate treatments will add more suffering to patients and waste lots of medical resources. Therefore, the research of correct diagnosis and suitable treatments has been a hot topic in recent years. Currently, the main diagnostic method is still based on the method of clinical experience. The clinicians obtain the diagnostic results by comprehensive analysis of symptoms, signs and many auxiliary examinations which mainly consist of blood detection, ultrasonography, pelvic computed tomography (CT), magnetic resonance imaging (MRI) and so on. For the time being, correct pathological diagnosis is the ultimate diagnostic work, which is the first step to guide the proper clinical treatments, but it has always been a difficult problem for clinicians [1]. With the application of laparoscope in recent years, we can take the doubted n
Corresponding author. E-mail address: [email protected] (L. Xiang).
http://dx.doi.org/10.1016/j.neucom.2015.10.003 0925-2312/& 2015 Elsevier B.V. All rights reserved.
tissue under observation to do pathological examination. Diagnosis combining with pathological examination is considered as golden standard, but the patients should bear the risk and trauma caused by surgery. At the same time, postoperative chronic inflammation and tissue adhesion can arouse the pain again. Therefore, some patients would endure the pain rather than simply accept a laparoscope examination [2,3]. It is universally acknowledged that the symptoms and signs are subjective and fuzzy and accurate diagnosis depends mostly on experience of clinicians and available examinations. Therefore, different clinicians may give different diagnostic results about a single kind of disease. So, if there is one more reasonable and convincible method to diagnose the causes of CPP, and if we can make an experts system which is combined with lots of pretty experienced doctors' knowledge and clinical data, we can form a diagnostic system to diagnose the causes of CPP. It will increase the level of diagnosis highly and improve the efficiency of patients' medical treatments. At present, the comprehensive evaluation that based on fuzzy matrix calculation is an efficient method to quantize the subjective and fuzzy medical phenomenon. Subsequently, computer-aided diagnosis (CAD) system based on the method is a practical innovation. At the beginning, the method was applied in the fields of gerontology, anesthesiology, medical informatics, and it gradually extended to Chinese medicine, surgical fractures [4–9], fetal intrauterine distress and premature monitoring, gynecological ultrasound exam, etc. [10,11]. Among the process, the method and
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CAD system were perfected step by step, and got lots of good evaluations for improving the diagnosis efficiency and quality. Now, more and more fields begin to explore and use them [12–14]. Recently, in addition to the above traditional diagnosis method, there is no other math methods or CAD systems to do the gynecological CPP diagnosis. Based on the above discussion, this paper puts forward the fuzzy comprehensive evaluation method that based on fuzzy matrix calculation, which could be used to find the gynecological causes of CPP in the aspect of clinical diagnosis. In this paper, we firstly analyze 460 clinical cases and extract the related statistical data to set up a fuzzy matrix. Secondly, we obtain weight value by averaging several experts experience, then we can get an exact figure by synthesizing fuzzy matrix and weight value according to fuzzy mathematics algorithm. At last, we evaluate the diagnostic value by comparing fuzzy comprehensive evaluation method with clinician experience-based diagnosis method. The paper is organized as follows. In Section 2, background of chronic pelvic pain is briefly outlined. In Section 3, we make an illustration of fuzzy matrix calculation and the detailed procedures. In Section 4, clinical application and diagnostic value evaluation are exploited to show the effectiveness of this approach. The conclusions are given in the Section 5.
2. Background of chronic pelvic pain (CPP)
calculation method [24,25]. The fuzzy comprehensive evaluation method is based on fuzzy calculation, it is a quantitative method to describe fuzzy phenomenon comparing with modern mathematics the clarity and accuracy. It builds up the fuzzy matrix on the basis of the statistical data, then we can get precise conclusion through fuzzy mathematical algorithms, this is the basic principle of the method [26–29]. The detailed procedures of fuzzy comprehensive evaluation are as follows: 3.1. Define an evaluation factors U and evaluation sets V U ¼ fu1 ; u2 ; …; un g V ¼ fv1 ; v2 ; ⋯; vn g
ði ¼ 1; 2; ⋯; nÞ ðj ¼ 1; 2; ⋯; nÞ
ð1Þ ð2Þ
U stands for an evaluation factor set, it is comprised of many subsets, namely, ui , which show the typical symptoms, signs and many auxiliary examinations that collected from clinical data or the diagnostic golden standard. vj consists of evaluation sets V, which is extracted from generalized diseases. 3.2. Establish membership degree and fuzzy matrices Membership degree means the frequency that ui appears in vj , with r ij representative. Membership degree defines fuzzy phenomenon a quantitative description, it is usually constructed through the following several ways:
Definition of chronic pelvic pain by the American College of Obstetricians and Gynecologists [15–17] is no cyclical pain of at least 6 months duration that appears in locations of the pelvis, anterior abdominal wall, lower back or buttocks. Most of the patients take waist and abdomen pain as the main performance and the pain often aggravates during menstruation or labor, it can be associated with dyspareunia and infertility. The World Health Organization analysis report [1,18] shows that an estimated worldwide prevalence of CPP is 2.1–24%. However, this data may be underestimated because a large number of questionnaires show that up to 40% of the people do not seek medical diagnosis and treatments even they suffer from the pain. Currently, many physical or functional disabilities of abdominal viscera, as well as mental and neurological disorders can cause chronic pelvic pains [19–21], which often occur in the female reproductive system, urinary system, digestive system, musculoskeletal system, mental and neurological function system. The common gynecological diseases that cause CPP include (1) endometriosis; (2) adenomyosis; (3) chronic pelvic inflammatory disease; (4) pelvic adhesion; (5) ovarian tumor; (6) uterine tumor, etc. [2,22,23]. Some relative clinical manifestations include lower abdomen pain, menstruation and/or leucorrhea change, the change of size and/or character in uterus and its accessory, etc. Many of them are related to uterine or pelvic surgeries. The kinds of diseases and manifestations are so complicated which are difficult to diagnose. However, a firm diagnosis is the key to next clinical treatment. At present, the most common diagnostic methods are inquiry, physical examination and ultrasonic testing in hospitals with different levels of services. However, different clinicians may give different diagnostic results for the same patient because of their different clinical experience. From this perspective, traditional diagnostic method is subjective and low-efficiency. Therefore, comprehensive evaluation chronic pelvic pain that based on fuzzy matrix calculation is an significant exploration.
used to determine weight value. Each expert independently gives the weight value of each factor according to importanct degree of the U to V, then we take the average value as its final weight value. If there is the evaluation factor in a patient, we take the corresponding weight value. However, if there is none, we take it as zero.
3. Fuzzy matrix calculation
3.4. Synthesize the fuzzy matrix R with weight value set A
Fuzzy sets was established by Zadeh LA in 1965, it developed nearly half a century from the fuzzy logics theory to the fuzzy
We get B by applying algorithm "" to weight value set A and fuzzy matrix R (4 means take the smallest number, 3 means take
(1) Fuzzy statistics: through analysis of clinical data or other related database to determine membership degree. (2) Factor weight method: according to the significance of the evaluation factors to evaluation sets to determine membership degree. (3) Expert experience method: comprehensive analysis a number of specialists, it can avoid single subjective factor. (4) Analysis and reasoning method: according to mathematical reasoning method and model to determine membership degree. In the above four ways, fuzzy statistics is a time-consuming but more scientific and efficient method, so it has been widely applied to determinate the membership degree. If we make a definition that t ij stands for the number of ui appears in vj , and T j is the total number of evaluation subset vj , we can get r ij by formula (3), and establish fuzzy matrices Rij t ij t ij r ij ¼ 0≦ ≦1 ð3Þ Tj Tj 3.3. Set weight value distribution in A A ¼ ða1 ; a2 ; …; an Þ
ði ¼ 1; 2; ⋯; nÞ
ð4Þ
A is a weight value set, ai A A, weight value (ai ) reflects the importance of the evaluation factor to the evaluation set, and n P ai ¼ 1ði ¼ 1; 2; ⋯; nÞ. Expert experience method is commonly i¼1
X. Yu et al. / Neurocomputing 173 (2016) 2097–2101
the biggest number [30]), then we get C by normalizing B (as show in formula (5) and (6)), B ¼ AΟR ¼ ðb1 ; b2 ; …; bn Þ; bj ¼ 3 ai 4 r ij ð5Þ C ¼ ðc1 ; c2 ; ⋯; c6 Þ; ci ¼ bi=
n X
bj ;
ði ¼ 1; 2; ⋯; 6Þ
ð6Þ
i¼1
3.5. Judge the maximum membership degree M ¼ maxðc1 ; c2 ; ⋯; c6 Þ
Table 1 Gynecological diseases statistics. Disease
Disease number
Percentage (%)
Endometriosis (ν1 ) Adenomyosis (ν2 ) Chronic pelvic inflammatory disease (ν3 ) Pelvic adhesion (v4 ) Ovarian tumor (v5 ) Uterine tumor ()
188 127 48 35 23 39
40.9 27.6 10.4 7.6 5.0 8.5
ð7Þ
M is the largest number in C set (formula (7)), the evaluation set that M corresponding to is the finally evaluation result, which is the most probable gynecological disease that causes CPP.
4. Procedures of CPP diagnosis by fuzzy matrix calculation We collected 460 clinical cases with a history of CPP. All the gynecological causes were identified by pathologic diagnosis (Table 1), and we extracted 17 kinds of significant evaluation factors subset, namely: (1) secondary dysmenorrheal; (2) irregular abdominal pain; (3) menstruation change; (4) infertility (primary or secondary); (5) large size/hard characteristics of uterus on palpation; (6) thickened/tenderness of accessory on palpation; (7) cervix change (erosion, polyp, hypertrophy, Naboth cyst, neoplasm, etc.); (8) large uterus/uneven echo of muscle layer under B ultrasound; (9) abnormal accessory echo under B ultrasound; (10) leucorrhea change; (11) elevated serum CA125 (Z35 U/ml); (12) history of uterine surgery (hysteromyomectomy, cesarean section, complete curettage of uterine cavity, etc.); (13) history of pelvic surgery; (14) low age (ager35 years); (15) middle age (age 36 years-pre-menopause); (16) post-menopause; (17) mental state or weight change, etc. Finally, by formula (3) we obtain every membership degree and establish fuzzy matrices R176 (as show in (8)). 0:195
0:216
0:125
0:171
0:116
0:177
0:143
0:103
0:227
0:171
0:224
0:132
0:097
0:288
0:147
0:120
0:143
0:205
0:268 0:106
0:012 0:301
0:381 0:111
0:261 0:133
0:000 0:109
0:078 0:240
0:238
0:060
0:210
0:211
0:196
0:076
0:147
0:255
0:221
0:118
0:077
0:182
0:140
0:283
0:091
0:142
0:130
0:214
R ¼ 0:235 0:166
0:089
0:212
0:179
0:202
0:083
0:140
0:370
0:001
0:095
0:228
0:198
0:258
0:113
0:164
0:201
0:066
0:133 0:120
0:212 0:231
0:174 0:079
0:178 0:180
0:117 0:228
0:186 0:162
0:290
0:026
0:183
0:207
0:202
0:092
0:119
0:224
0:166
0:156
0:128
0:198
0:050
0:085
0:071
0:098
0:437
0:25
0:132
0:158
0:373
0:121
0:096
0:114
¼ 17Ai =6
ð8Þ
5.1. Clinical application Case: female, 45 years old, childbearing history: 1-0-1-1, accepted curettage of uterine cavity at 27, gave birth to a daughter at 29 by cesarean section, menstrual cycle: 14 4–6/30, moderate menstrual volume, began to secondary dysmenorrheal since 5 years ago, and it aggravated gradually. Now the pain was so serious at menstrual period that affected the normal work and dai ly life. She needed to stay in bed and painkillers was inoperative. No abdominal pain at other time. Recently, the menstrual volume was more than before. Menstrual cycle and leucorrhea was normal. Gynecological examination: the uterine size was as large as 3 months pregnant, slight hard, no tenderness on palpation, mild cervical erosion. B ultrasound: uterine size 85 78 75 mm3 with uneven echo of muscle layer, no significant changes in body weight and mental state, serum CA125 64.02 U/ml. Diagnosis procedure: According to above procedures and formula (1)–(10), we got the results: A ¼ ð0:325; 0; 0; 0; 0:216; 0; 0; 0:248; 0; 0; 0:221; 0:240; 0:127; 0; 0:242; 0; 0Þ
ð11Þ
C ¼ 0:163=c1 ; 0:204=c2 ; 0:143=c3 ; 0:147=c4 ; 0:165=c5 ; 0:178=c6
B ¼ AοR ¼ ð0:198; 0:248; 0:174; 0:178; 0; 201; 0:216Þ
ð13Þ
M ¼ 0:204=c2
ð14Þ
Analyzed the final result that M ¼0.204/c2 , we inferred the cause of chronic pelvic pain was actinomycosis (c2 ). The patient accepted laparoscopic assisted vaginal hysterectomy (LAVH). The uterine size was increscent under laparoscope observation and accessories were normal. Adenomyosis and myoma of uterus were confirmed at the final pathological diagnosis, which was consistent with the result of fuzzy comprehensive evaluation. 5.2. Accuracy analysis
ð9Þ
A; ¼ 0:325; 0:199; 0:139; 0:046; 0:216; 0:232; 0:120; 0:248; 0:273; 0:030; 0:221; 0:240; 0:127; 0:135; 0:242; 0:012; 0:028Þ
5. Clinical application and evaluation
ð12Þ
Five clinical experienced attending doctors and chief physicians gave their independent results. If the number of evaluation factors was more, then ai is relatively small, we could adjust the Ai by formula (9), finally we got A; (formula (10)). A;i
2099
ð10Þ
Select another 40 cases with certain pathological results in CPP, compared the fuzzy comprehensive evaluation method with clinician experience-based method the diagnosis accuracy (show in Table 2). (1) Accuracy is quantized by rate of correct diagnosis, if n stands for number of correct diagnosis, N stands for number of total cases. Accuracy ¼
n 100% N
ð15Þ
According to formula (15), the accuracy of fuzzy comprehensive b evaluation method 72.5% (a þ N 100%) is higher than the accuracy þc of doctor experience-based method 55.0% (a N 100%). There is 2 statistically significant difference (x ¼ 4:0; P o 0:05). Therefore,
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Table 2 Diagnosis analysis between fuzzy comprehensive evaluation and clinicians experience-based method. Fuzzy comprehensive evaluation method
þ Total
Clinician experience-based method þ
21 (a) 1 (c) 22
8 (b) 10 (d) 18
Total
29 11 40 (N)
x2 ¼4.0, P o0.05.
the fuzzy comprehensive evaluation method in diagnosis of CPP is an efficient method. (2) Among the 40 cases, there are 10 cases inferred as the causes of chronic pelvic pain according to the fuzzy comprehensive evaluation method, but we are unable to get the pathological results. Then we compared inferred results with MRI, which is known as a highly accurate and non-invasive detection on diagnosis gynecological diseases. There are 7 cases are consistent with the results of MRI. We think the speculation accuracy is as high as 70%, so the fuzzy comprehensive evaluation method can predict the potential causes of chronic pelvic pain. 5.3. Discussion The usage of fuzzy comprehensive evaluation, which is based on fuzzy matrix calculation to diagnose the gynecological causes of CPP, is an initial investigation. It is hard to avoid subjectivity because of weight value assignment process combining with the subjective expert evaluation method. The relative methods to reduce the subjectivity of quantification process are as follow: (1) take multi-central cooperation, collect more information of the evaluation elements; (2) improve the present methods, integrate different mathematical models; and (3) increase the number of samples and evaluation experts. The investigation establishes a foundation for the next application in CAD system, its advantage will be gradually approved and be made use of comprehensively. Finally, it will not only improve doctors’ work efficiency, but also help patients achieve self-diagnosis of their diseases. According to the mode, when it uses the chief complaint and physical examination datum as the evaluation factor and the diseases as the evaluation set, it can be applied to the diagnosis of the diseases in general. When the complaints and examination datum obtain after drug treatments and we use curative effects as diagnosis results, it can be applied to drug effects assessment and drug dosage adjustment [31]. Normalized ci shows the probability of relative diseases and it makes a guidance in the study of the relationship between diseases and its molecular mechanisms. Modern evidence-based medicine advocates to use a lot of best evidences to get the best conclusions. It helps medicine realize a leap from traditional experience-based to modern evidence-based. The application of fuzzy comprehensive evaluation in medicine can be treated as a special mode of evidence-based medicine, because the method quantizes fuzzy diagnosis factors and completely avoids individual subjective experience in order to make it more objective. It provides gynecological disease diagnosis of a novel method.
6. Conclusion The paper preliminarily makes use of fuzzy comprehensive evaluation to analyze the gynecological diseases that take chronic
pelvic pain as the main symptoms. The final result is obtained by fuzzy matrix calculation and analysis of clinical datum with expert experience, and there is a higher diagnostic accuracy when compared with doctor experience-based method. Additionally, it also plays an important role in prediction. So, comprehensive evaluation based on fuzzy matrix calculation is an efficient and scientific method in diagnosis of gynecological diseases that causes CPP, and it also improves the breadth and depth of the comprehensive diagnosis. The next step is to establish CAD system make it extensively usage in clinic. Medical science will break through the bondage of narrow experience-based medicine, and develop towards the direction of quantitative, computable, controlled and predictable. With the influence of connection, permeation and transformation among many subjects, applied mathematics combining with the computer technology will promote medicine development better and faster in the future.
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Xinghu Yu was born in Yantai City, China, in 1988. He received the B.M. degree in clinical medicine from Binzhou Medical University. And now he is currently pursuing the M.M. degree in orthopeadic surgery from Liaoning Medical University, and Department of Orthopedics Surgery, General Hospital of Shenyang Military Area Command. His research interests include basic spinal diseases and spinal cord injury and its repair.
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Wenfeng Meng received his B.S. degree in electronics and information engineering from Harbin Institute of Technology, Harbin, China in 2007 and the M.S. degree in electronics and information engineering from Jilin University, Changchun, China in 2015, respectively. His research interest includes embedded system, direction of Multi-axis robots and Detection equipment.
Liangbi Xiang received the B.M. degree in clinical medicine from the Fourth Military Medical University in 1985. He is currently a chief physician and director of the Orthopedics Department in Shenyang Military Region General Hospital. He has accumulated rich clinical experience in the diagnosis and treatment of spinal disorders and limbs trauma, especially in the cervical spondylosis, thoracic diseases and the lower lumbar spine instability and limbs severe and complicated trauma with deep attainments.