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Open Biomed Eng J. 2016 Jun 29;10:72-80. doi: 10.2174/1874120701610010072. eCollection 2016.

Engineering Approach to Identifying Patients with Colon Tumors on the Basis of Electrophotonic Imaging Technique Data.

Author information

1
Russian National Research Medical University, Moscow, Russia.
2
Saint Petersburg Federal University of Information Technologies, Mechanics and Optics, Russia.

Abstract

BACKGROUND:

Colonic neoplasms are quite a serious problem today. Screening methods play an important role in diagnosing the disease. Colorectal cancer screening is a complex undertaking, having various options, which require a lot of efforts both from the doctor and from the patient, including the use of sedatives and the necessity of the presence of an assistant for some procedures such as colonoscopy. This is why it is very important to find a method by which one can make a diagnosis quickly, easily, and painlessly.

METHODS:

The ability to identify patients with tumors of the colon using the Electrophotonic Imaging (EPI) technique, as well as using it for differential diagnosis of tumors of the colon by their morphology, size and quantity was investigated. Selection of the most significant parameters of the EPI-graphy for the separation of the control group and the group of patients with tumors of the colon was developed. 137 people were studied with the EPI camera, with ages ranging from 16 to 86 years, including 49 males and 88 females. Based on the results of the colonoscopy and histological findings all subjects were divided into 2 groups: control group of 55 people, 9 males, 46 females; and patients with tumors (benign or malignant) of the colon - 82 people; 40 males and 42 females. Then all subjects were divided into smaller groups based on morphology, size, number of tumors and localization.

RESULTS:

Based on the identified indicators decision rules to determine the patients with tumors of the colon were constructed. The specificity of the resulting function was 80.0% and sensitivity 75.6%. Decision rule was built as well with logistic regression. The specificity of the resulting function was 78.2% and sensitivity 90.0%. The accuracy of this approach was higher than using discriminant analysis.

CONCLUSIONS:

The results of this study have proven the ability to identify patients with tumors of the colon using EPI technology, as well as use it for differential diagnosis of tumors of the colon by their morphology, size and quantity. EPI testing is non-invasive, takes less than five minutes, and equipment is relatively cheap and accessible in mass production. This opens up good prospects for further research for implementation as a first step of the screening process. This paper presents the pilot study developing methodological approach to the GDV data processing. That is why we tried different methods of data processing. At the same time we do not pretend to develop a diagnostic method - sample size is too small for this, and other cancer types were not studied. Further research is needed.

KEYWORDS:

Colon tumors; Decision rules; Electrophotonic imaging; Image processing

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