Novosti
Khirurgii

 This journal is
indexed in Scopus
journal cover
android icon Android Applicaion

Year 2020 Vol. 28 No 6

GENERAL & SPECIAL SURGERY

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 62.5±12 years (M±σ). 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
References
  1. Kim Y, Ejaz A, Tayal A, Spolverato G, Bridges JFP, Anders RA, Pawlik, TM. Temporal trends in population-based death rates associated with chronic liver disease and liver cancer in the United States over the last 30 years. Cancer. 2014 Oct 1;120(19):3058-65. Published online 2014 Jun 10. doi: 10.1002/cncr.28843
  2. Podymova SD. The modern view on pathogenesis and treatment of nonalcoholic fatty liver disease. Eksperim i Klin Gastroenterologiia. 2016;(5):74-82. https://elibrary.ru/item.asp?id=26540630 (In Russ.)
  3. Anstee QM, Targher G, Day CP. Progression of NAFLD to diabetes mellitus, cardiovascular disease or cirrhosis. Nat Rev Gastroenterol Hepatol. 2013 Jun;10(6):330-44. doi: 10.1038/nrgastro.2013.41
  4. European Association for the Study of the Liver (EASL); European Association for the Study of Diabetes (EASD); European Association for the Study of Obesity (EASO). EASL-EASD-EASO Clinical Practice Guidelines for the management of non-alcoholic fatty liver disease. J Hepatol. 2016 Jun;64(6):1388-402. doi: 10.1016/j.jhep.2015.11.004
  5. Ivashkin VT, Mayevskaya MV, Pavlov CS, Tikhonov IN, Shirokova YN, Buyeverov AO, Drapkina OM, Shulpekova YuO, Tsukanov VV, Mammayev SN, Mayev IV, Palgova LK. Diagnostics and treatment of non-alcoholic fatty liver disease: clinical guidelines of the Russian Scientific Liver Society and the Russian gastroenterological association. Russian Journal of Gastroenterology, Hepatology, Coloproctology. 2016;26(2):24-42. doi: 10.22416/1382-4376-2016-26-2-24-42 (In Russ.)
  6. Ratziu V, Charlotte F, Heurtier A, Gombert S, Giral P, Bruckert E, Grimaldi A, Capron F, Poynard T. Sampling variability of liver biopsy in nonalcoholic fatty liver disease. Gastroenterology. 2005 Jun;128(7):1898-906. doi: 10.1053/j.gastro.2005.03.084
  7. Zeb I, Li D, Nasir K, Katz R, Larijani VN, Budoff MJ. Computed tomography scans in the evaluation of fatty liver disease in a population based study: the multi-ethnic study of atherosclerosis. Acad Radiol. 2012 Jul;19(7):811-18. doi: 10.1016/j.acra.2012.02.022
  8. Chen X, Li K, Yip R, Perumalswami P, Branch AD, Lewis S, Del Bello D, Becker BJ, Yankelevitz DF, Henschke C. Hepatic steatosis in participants in a program of low-dose CT screening for lung cancer. Eur J Radiol. 2017 Sep;94:174-179. doi: 10.1016/j.ejrad.2017.06.024
  9. Okhrimenko SE, Ilin LA, Korenkov IP, Morozov SP, Biriukov AP, Gombolevskii VA, Prokhorov NI, Lantukh ZA, Ryzhov SA, Soldatov IV, Fomin AA. Optimization of radiation doses to patients in x-ray diagnostics. Gigiena i Sanitariia. 2019;98(12):1331-37. doi: 10.18821/0016-9900-2019-98-12-1331-1337 ((In Russ.)
  10. Kauczor HU, Baird AM, Blum TG, Bonomo L, Bostantzoglou C, Burghuber O, Čepická B, Comanescu A, Couraud S, Devaraj A, Jespersen V, Morozov S, Agmon IN, Peled N, Powell P, Prosch H, Ravara S, Rawlinson J, Revel MP, Silva M, Snoeckx A, van Ginneken B, van Meerbeeck JP, Vardavas C, von Stackelberg O, Gaga M; European Society of Radiology (ESR) and the European Respiratory Society (ERS). ESR/ERS statement paper on lung cancer screening. Eur Radiol. 2020 Jun;30(6):3277-94. doi: 10.1007/s00330-020-06727-7
  11. Kul’berg NS, Elizarov AB, Kovbas VS. Programma segmentacii izobrazhenija pecheni i opredelenija rentgenovskoj plotnosti pecheni CTLiverExam: svidetel’stvo o gos registracii programmy dlja JeVM; RU 2019660983 2019 Avg 15 https://elibrary.ru/item.asp?id=39321074 (In Russ.)
  12. Liao M, Zhao Y, Liu X, Zeng Y, Zou B, Wang X, Shih FY. Automatic liver segmentation from abdominal CT volumes using graph cuts and border marching. Comput Meth Prog Bio. 2017 May;143:1-12. doi: 10.1016/j.cmpb.2017.02.015
  13. Wu W, Zhou Z, Wu S, Zhang Y. Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts. Comput Math Methods Med. 2016;2016:9093721. doi: 10.1155/2016/9093721
  14. Kullberg J, Hedström A, Brandberg J, Strand R, Johansson L, Bergström G, Ahlström H. Automated analysis of liver fat, muscle and adipose tissue distribution from CT suitable for large-scale studies. Sci Rep. 2017 Sep 5;7(1):10425. doi: 10.1038/s41598-017-08925-8
  15. Jirapatnakul A, Reeves AP, Lewis S, Chen X, Ma T, Yip R, Chin X, Liu S, Perumalswami PV, Yankelevitz DF, Crane M, Branch AD, Henschke CI. Automated measurement of liver attenuation to identify moderateto-severe hepatic steatosis from chest CT scans. Eur J Rdiol. 2020 Jan;122:108723. doi: 10.1016/j.ejrad.2019.108723
  16. Heimann T, van Ginneken B, Styner MA, Arzhaeva Y, Aurich V, Bauer C, Beck A, Becker C, Beichel R, Bekes G, Bello F, Binnig G, Bischof H, Bornik A, Cashman PM, Chi Y, Cordova A, Dawant BM, Fidrich M, Furst JD, Furukawa D, Grenacher L, Hornegger J, Kainmüller D, Kitney RI, Kobatake H, Lamecker H, Lange T, Lee J, Lennon B, Li R, Li S, Meinzer HP, Nemeth G, Raicu DS, Rau AM, van Rikxoort EM, Rousson M, Rusko L, Saddi KA, Schmidt G, Seghers D, Shimizu A, Slagmolen P, Sorantin E, Soza G, Susomboon R, Waite JM, Wimmer A, Wolf I. Comparison and evaluation of methods for liver segmentation from CT datasets. IEEE Trans Med Imaging. 2009 Aug;28(8):1251-65. doi: 10.1109/TMI.2009.2013851
  17. Gromov AI, Petraikin AV, Kulberg NS, Kim SYu, Morozov SP, Sergunova KA, Usanov MS. The Problem of X-Ray Attenuation Estimation Accuracy in Multislice Computed Tomography. Med Visualization. 2016;(6):133-142. https://medvis.vidar.ru/jour/article/view/368 (In Russ.)
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.
Contacts | ©Vitebsk State Medical University, 2007-2023