Novosti
Khirurgii
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Year 2020 Vol. 28 No 6

GENERAL & SPECIAL SURGERY

DOI: https://dx.doi.org/10.18484/2305-0047.2020.6.636   |  

A.P. GONCHAR 1, A. B. ELIZAROV 1, N. S. KULBERG 1, 2, M.M. SULEYMANOVA 3, T.I. ALEKSEEVA 4, D.A. CHERNYSHEV 5, M.Y. TITOV 6, V.Y. BOSIN 1, S.P. MOROZOV 1, V.A. GOMBOLEVSKIJ 1

AUTOMATIC MEASUREMENT OF LIVER DENSITY BY COMPUTED TOMOGRAPHY AND ULTRA-LOW-DOSE COMPUTED TOMOGRAPHY

Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow 1,
Federal Research Center "Institute of Management" RAS 2,
Central State Medical Academy of the Administrative Department of the President of the Russian Federation 3,
Center for Expertise and Quality Control of Medical Care 4
Pirogov Russian National Research Medical University 5,
City Clinical Hospital named after S.P. Botkin.
Department of Health of Moscow 6, Moscow,
The Russian Federation

Objective. To evaluate the possibilities of the developed method for the automatic liver density measurements according to the data of native ultra-low-dose and standard chest computed tomograms in the case when an upper segment of the abdomen is in the scanned zone.
Methods. Retrospective analysis of clinical data associated with patients (n=10,000) underwent ultra-low-dose computed tomography has been performed. The patients (n=100) were selected and additionally underwent standard computed tomography. The average age of patients was 62.512 years (Mσ). Manual measurement of the liver density was carried out in II, IV, VII-VIII segments. In addition the splenic density was measured. In the case of the liver density was <40 HU, liver-to-spleen ratio (L/S) <0.8-1.0, and the density difference was <10 HU hepatic steatosis was considered to be reliable. For automatic procedure a program for measurement of liver density including segmentation and the segmented density area was developed.
Results. A little difference was revealed in comparison of the automated and manual liver density measurement for standard computed tomography (51.43 vs. 50,37 HU, p=0.0192). For ultra-low-dose computed tomography the difference is slightly larger (54.90 and 55.60 HU, p=0.310). When assessing the difference between the compared methods for standard and ultra-low-dose computed tomography, no significant difference was found (p=0.0035). In comparison of manual and automated methods a larger number of the low liver density cases both for standard (10 vs. 6 cases, P(McNemar)=0.125) and ultra-low-dose tomograms (11 vs. 5 cases, P(McNemar)=0.0313) was detected. The agreement between two methods is considered to be satisfactory for both scanning protocols (kappa 0.726 vs. 0.593).
Conclusion. A good correlation between manual and automated methods for standard and ultra-low-dose computed tomography allows using the automatic method for analyzing a large amount of data and revealing the hepatic steatosis.

Keywords: X-ray liver density, computed tomography, ultra low-dose computed tomography, hepatic steatosis, nonalcoholic fatty liver disease
p. 636-647 of the original issue
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Address for correspondence:
125124, Russian Federation,
Moscow, Raskova Str., 16/26, 1,
Research and Practical Clinical Center
of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow,
the Department of Radiology Quality Development
tel. +7 962 967-50-71,
e-mail: anne.gonchar@gmail.com,
Gonchar Anna P.
Information about the authors:
Gonchar Anna P., Senior Researcher of the Department of Radiology Quality Development, Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
http://orcid.org/0000-0001-5161-6540
Elizarov Alexey B., PhD, Senior Researcher of the Department of the Development of Medical Imaging Tools, Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
http://orcid.org/0000-0003-3786-4171
Kulberg Nicholay S., PhD, Head of the Department of the Development of Medical Imaging Tools, Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
http://orcid.org/0000-0001-7046-7157
Suleymanova Maria M., Clinical Intern, Central State Medical Academy of the Management Department of the Presidential Administration of the Russian Federation, Moscow, Russian Federation.
https://orcid.org/0000-0002-5776-2693
Alekseeva Tatiana I., Specialist of the Department of Medical Security Standardization, Center for Healthcare Quality Assessment and Control, Moscow, Russian Federation.
http://orcid.org/0000-0003-3296-3250
Chernyshev Dmitry A., Clinical Intern, Pirogov Russian National Research Medical University, Moscow, Russian Federation.
https://orcid.org/0000-0002-6734-0531
Titov Mikhail Yu., Radiologist, City Clinical Hospital Named after S.P. Botkin, Department of Health of Moscow, Moscow, Russian Federation.
https://orcid.org/0000-0002-4933-6125
Bosin Victor Yu., MD, Professor, Chief Researcher of the Department of Radiology Quality Development, Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
http://orcid.org/0000-0002-4619-2744
Morozov Sergey P., MD, Professor, Head of the Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
http://orcid.org/0000-0001-6545-6170
Gombolevsky Victor A., PhD, Head of the Department of Radiology Quality Development, Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow, Moscow, Russian Federation.
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