63 research outputs found
Eliciting Uncertain Resilience Information for Risk Mitigation
The literature of risk, mitigation, and resilience is rich in classifications and recommendations. The missing link is evaluation: ideally, data based; initially, based on expert judgment. We present a novel approach for eliciting probability distributions describing mitigation effectiveness. This approach can be used by subject matter experts (SMEs) who are not specialists in mathematics or engineering. A visual interface permits each expert to sketch a distribution by moving five colored dots on the user interface. The engine can weight and combine estimates from several SMEs into an aggregate density function suitable for presentation, and an aggregate cumulated distribution for use in Monte Carlo simulations. Additional supporting software adapts the tool for real-time support of virtual Delphi-type sessions involving multiple distributed experts. Use of the tool in a study aimed at controlling information and communication technology supply chain risks yields valuable information on those threats, and on the tool itself
DIAFILTRATION OF ULTRAFILTRATION RETENTATE OF WHEY FROM WHITE BRINED CHEESE
Whey diafiltration was carried out with a UF25-PAN polyacrylnitrilic membrane with 25 kDa molecular weight cut-off at volume reduction factors (VRF) VRF=2, VRF=4, VRF=6, VRF=8, VRF=10. The values of the principal components dry matter, protein, lactose and mineral substances in the retentates and permeate obtained were established. The relative shares of protein, lactose and mineral substances in the dry matter, the concentration factor (CF) values for dry matter, protein, lactose and mineral substances, and the protein retention factor (RF) were determined. Linear models were created for the CF of each investigated component according to the VRF, and a logarithmic model was developed for the protein RF according to the VRF. The results obtained demonstrated the efficiency of diafiltration for deep treatment aimed at a further elimination of lactose and mineral substances and subsequent utilization of the diafiltration concentrates low in lactose and mineral substances as a liquid supplement in the manufacture of extruded cereal products
Comparative study of quality characteristics of Kashkaval cheese from fresh and chilled curd
The influence of chilledcurd on Kashkavalcheese microbiological, functional, textural and sensorial characteristics was studied. It was found that salting the curd in a hot solution influenced to a greater degree the microflora reduction from the starter culture in Kashkaval cheese obtained fromfresh curd. In terms of species composition, Streptococcusssp. had a higher survival rate compared to Lactobacillusssp. During maturation, this trend changed and the number of Lactobacillusssp. increased, while that of Streptococcus ssp. remained constant and even slightly decreased in both studied samples. Melting and textural characteristics of the two studied cheese samples did not differ significantly at the end of the maturation process. The overall scores of the sensory profile were higher in the cheese obtained from fresh curd but no statistical differences (p>0.05) between separate sensory indices were established. The obtained results indicated that "Cagliata"can be successfully used as an alternative raw material for fresh curd in the production of Kashkaval cheese.publishedVersio
Agricultural Academy
Abstract MENKOV, N. D., K. DINKOV, A. DURAKOVA and N. TOSHKOV, 2009. Sorption characteristics of buckwheat grain. Bulg. J. Agric. Sci., Moisture equilibrium data (adsorption and desorption) of buckwheat grain were determined using the static gravimetric method of saturated salt solutions at three temperatures 10, 25 and 40Β°C. The range of water activities for each temperature was between 0.11 and 0.85. Equilibrium moisture content decreased with increase in storage temperature at constant water activity. A suitable model was selected to describe the water sorption isotherms. The monolayer moisture content of the grain was estimated and the optimal storage water activity was proposed
Project of Energy Supply of the URFU Observatory with a Res- Based Microgeneration Plant
Π ΡΡΠ°ΡΡΠ΅ ΡΠ°ΡΡΠΌΠ°ΡΡΠΈΠ²Π°ΡΡΡΡ ΠΏΠ΅ΡΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΈ ΡΠ½Π΅ΡΠ³ΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡΡΡ Π²ΠΌΠ΅ΡΡΠΎ Π³ΠΎΡΡΡΠΈΡ
ΠΈΡΠΊΠΎΠΏΠ°Π΅ΠΌΡΡ
; ΠΏΡΠΈΠ²ΠΎΠ΄ΠΈΡΡΡ Π°Π½Π°Π»ΠΈΠ· ΠΌΠ΅ΡΠ΅ΠΎΠ΄Π°Π½Π½ΡΡ
Π½Π° ΡΠ΅ΡΡΠΈΡΠΎΡΠΈΠΈ ΠΎΠ±ΡΠ΅ΡΠ²Π°ΡΠΎΡΠΈΠΈ; ΠΏΠΎΠΊΠ°Π·Π°Π½Ρ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ ΡΠ°ΡΡΠ΅ΡΠΎΠ² Π΄Π»Ρ ΡΡΡΠ°Π½ΠΎΠ²ΠΊΠΈ Π°Π»ΡΡΠ΅ΡΠ½Π°ΡΠΈΠ²Π½ΡΡ
ΠΈΡΡΠΎΡΠ½ΠΈΠΊΠΎΠ² ΡΠ½Π΅ΡΠ³ΠΈΠΈ Π½Π° ΠΎΠ±ΡΠ΅ΠΊΡΠ΅.The article discusses promising energy sources that can be used instead of fossil fuels; the analysis of meteorological data on the territory of the observatory is given; shows the results of calculations for the installation of alternative energy sources at the facility
Π£Π ΠΠΠΠ ΠΠΠΠ£Π§ΠΠΠΠ― ΠΠΠ¦ΠΠΠΠ’ΠΠ Π ΠΠΠΠΠΠΠΠ«Π ΠΠ£Π’Π ΠΠΠ’ΠΠΠΠΠΠ¦ΠΠ ΠΠΠ’-ΠΠΠΠΠΠΠ‘Π’ΠΠΠ Π Π ΠΠ‘Π‘ΠΠ
This study presents an overview of the most common positron emission tomography examinations in Russia, as well as the acquisition protocols and patient doses. The data collection was performed in 2012β2017 in 19 positron emission tomography departments in 12 regions of the Russian Federation by questioning the staff. The majority of the Russian positron emission tomography departments were equipped by modern positron emission tomography scanners combined with computed tomography. In each investigated department, data on all types of positron emission tomography examinations, radiopharmaceuticals, administered activities used for standard patient (body mass 70Β±5 kg) and parameters of computed tomography protocols was collected. The effective doses of patients from combined positron emission computed tomography examinations were estimated as a sum of the dose from the internal exposure (injected radiopharmaceutical) and the external exposure (computed tomography scan). Whole body positron emission tomography examinations in Russia were commonly performed with 18F-fluorodeoxyglucose (18F-FDG), 18F-choline, 11Π‘-choline, 68GaPSMA, 68Ga-DOTA-TATE, 68Ga-DOTA-NOC, brain examinations β 18F-FDG, 11Π‘-metionine, 18F-choline, 18F-tyrosine, myocardial perfusion β 13N-ammonie.The highest patient effective doses (about 17 mSv) were observed for whole-body positron emission computed tomography examinations; for brain examinations β 3,4 β 4,8 mSv; for myocardial perfusion β 2,8 mSv. The computed tomography scan contributes up to 65 β 95% to the total patient effective dose for whole body examinations; 20 β 30% for head examinations. For the multiphase computed tomography scan effective doses may be increased to: 15 mSv for head examinations, 25 β 30 mSv for whole body examinations and 35 β 40 mSv for myocardial examinations. A standardization of acquisition and processing protocols is necessary for optimization of positron emission tomography examinations in Russia and for the intercomparison of results obtained in different positron emission tomography departments. Low dose computed tomography protocols, justification of diagnostic and multiphase computed tomography protocols, application of tube current modulation system and modern reconstruction algorithms, education and training of the staff in the field of radiation protection should be used for optimization of radiation protection of patient.Β Π ΡΠ°Π±ΠΎΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½Ρ Π΄Π°Π½Π½ΡΠ΅ ΠΎ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΡΡ
ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΡΡ
ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡΡ
, ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠΌΡΡ
Π² Π ΠΎΡΡΠΈΠΈ, ΠΏΡΠΎΡΠΎΠΊΠΎΠ»Π°Ρ
ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π΄ΠΎΠ·Π°Ρ
ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². Π‘Π±ΠΎΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΡΡ ΠΏΡΡΡΠΌ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»Π° ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΠΉ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΠΎΠΉ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ Π² ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 2012 ΠΏΠΎ 2017 Π³. ΠΡΠ΅Π³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΎ 19 ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΠΉ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΠΎΠΉ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ ΠΈΠ· 12 ΡΠ΅Π³ΠΈΠΎΠ½ΠΎΠ² Π ΠΎΡΡΠΈΠΉΡΠΊΠΎΠΉ Π€Π΅Π΄Π΅ΡΠ°ΡΠΈΠΈ, Π΄Π΅Π²ΡΡΡ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΠΎΡΠ½Π°ΡΠ΅Π½Ρ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΡΠΌΠΈ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π° ΡΠ°Π΄ΠΈΠΎΠ½ΡΠΊΠ»ΠΈΠ΄ΠΎΠ² ΠΈ ΡΠ°Π΄ΠΈΠΎΡΠ°ΡΠΌΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠΎΠ². ΠΠΎΡΡΠΈ Π²ΡΠ΅ ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΠΎΠΉ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ Π² Π ΠΎΡΡΠΈΠΈ ΡΠΊΠΎΠΌΠΏΠ»Π΅ΠΊΡΠΎΠ²Π°Π½Ρ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΠΌΠΈ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΡΠΌΠΈ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΡΠΌΠΈ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠ°ΠΌΠΈ, ΡΠΎΠ²ΠΌΠ΅ΡΠ΅Π½Π½ΡΠΌΠΈ Ρ ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΡΠΊΠΈΠΌΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΡΠΌΠΈ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠ°ΠΌΠΈ, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΏΡΠ΅Π΄Π½Π°Π·Π½Π°ΡΠ΅Π½Ρ Π΄Π»Ρ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ Π΄Π²ΡΡ
ΠΏΡΠΎΡΠ΅Π΄ΡΡ Π² ΡΠ°ΠΌΠΊΠ°Ρ
ΠΎΠ΄Π½ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ. Π ΠΊΠ°ΠΆΠ΄ΠΎΠΌ ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΠΈ ΡΠΎΠ±ΠΈΡΠ°Π»Π°ΡΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΡ ΠΎ Π²ΠΈΠ΄Π°Ρ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΡ
ΡΠ°Π΄ΠΈΠΎΡΠ°ΡΠΌΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ°Ρ
ΠΈ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΡΡ
, Π²Π²ΠΎΠ΄ΠΈΠΌΡΡ
ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΠΎΠΌΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ (ΠΌΠ°ΡΡΠ° ΡΠ΅Π»Π° 70 Β± 5 ΠΊΠ³), Π° ΡΠ°ΠΊΠΆΠ΅ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠ°Ρ
ΠΏΡΠΎΡΠΎΠΊΠΎΠ»ΠΎΠ² ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ Π΄ΠΎΠ·Π°Ρ
ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². ΠΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ Π΄ΠΎΠ·Ρ, ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠ΅ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌΠΈ Π·Π° ΠΎΠ΄Π½ΠΎ ΡΠΎΠ²ΠΌΠ΅ΡΠ΅Π½Π½ΠΎΠ΅ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΠΎΠ΅ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΠΎΠ΅ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ΅ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅, ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈΡΡ ΠΊΠ°ΠΊ ΡΡΠΌΠΌΠ° Π΄ΠΎΠ· Π²Π½ΡΡΡΠ΅Π½Π½Π΅Π³ΠΎ ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΎΡ Π²Π²Π΅Π΄Π΅Π½Π½ΠΎΠ³ΠΎ ΡΠ°Π΄ΠΈΠΎΡΠ°ΡΠΌΠΏΡΠ΅ΠΏΠ°ΡΠ°ΡΠ° ΠΈ Π²Π½Π΅ΡΠ½Π΅Π³ΠΎ ΡΠ΅Π½ΡΠ³Π΅Π½ΠΎΠ²ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΏΡΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΌ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΌ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ. Π‘ΠΎΠ³Π»Π°ΡΠ½ΠΎ ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΌ Π΄Π°Π½Π½ΡΠΌ, Π² Π ΠΎΡΡΠΈΠΈ ΠΏΡΠΎΠ²ΠΎΠ΄ΡΡΡΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π²ΡΠ΅Π³ΠΎ ΡΠ΅Π»Π° Ρ 18F-ΡΡΠΎΡΠ΄Π΅Π·ΠΎΠΊΡΠΈΠ³Π»ΡΠΊΠΎΠ·ΠΎΠΉ, 18F-Ρ
ΠΎΠ»ΠΈΠ½, 11Π‘-Ρ
ΠΎΠ»ΠΈΠ½, 68Ga-PSMA, 68Ga-DOTA-TATE, 68Ga-DOTA-NOC, ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π³ΠΎΠ»ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ·Π³Π° Ρ 18F-Π€ΠΠ, 11Π‘-ΠΌΠ΅ΡΠΈΠΎΠ½ΠΈΠ½, 18F-Ρ
ΠΎΠ»ΠΈΠ½, 18F-ΡΠΈΡΠΎΠ·ΠΈΠ½, ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π° Ρ 13N-Π°ΠΌΠΌΠΎΠ½ΠΈΠΉ. ΠΠΎΠ·Ρ ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² ΠΎΡ ΡΠΎΠ²ΠΌΠ΅ΡΠ΅Π½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ Π»Π΅ΠΆΠ°Ρ Π² Π΄ΠΈΠ°ΠΏΠ°Π·ΠΎΠ½Π΅ 3β40 ΠΌΠΠ². ΠΠ°ΠΈΠ±ΠΎΠ»ΡΡΠΈΠ΅ Π΄ΠΎΠ·Ρ ΠΏΠΎΠ»ΡΡΠ°ΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΡ ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π²ΡΠ΅Π³ΠΎ ΡΠ΅Π»Π° β ΠΎΠΊΠΎΠ»ΠΎ 17 ΠΌΠΠ², ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π³ΠΎΠ»ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ·Π³Π° β 3,4β 4,8 ΠΌΠΠ², ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π° β 2,7 ΠΌΠΠ². ΠΡΠΈ ΡΡΠΎΠΌ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ΅ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅ Π²Π½ΠΎΡΠΈΡ ΠΎΡ 65% Π΄ΠΎ 95% Π² Π΄ΠΎΠ·Ρ ΠΎΠ±Π»ΡΡΠ΅Π½ΠΈΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ° ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π²ΡΠ΅Π³ΠΎ ΡΠ΅Π»Π° ΠΈ 20β30% ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π³ΠΎΠ»ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ·Π³Π°. ΠΡΠΈ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΡΡ
ΠΌΠ½ΠΎΠ³ΠΎΡΠ°Π·Π½ΡΡ
ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΡΡ
ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡΡ
Ρ Π²Π²Π΅Π΄Π΅Π½ΠΈΠ΅ΠΌ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΠΎΠ³ΠΎ Π²Π΅ΡΠ΅ΡΡΠ²Π° Π΄ΠΎΠ·Π° ΠΌΠΎΠΆΠ΅Ρ ΡΠ²Π΅Π»ΠΈΡΠΈΠ²Π°ΡΡΡΡ Π΄ΠΎ 15 ΠΌΠΠ² ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π³ΠΎΠ»ΠΎΠ²Π½ΠΎΠ³ΠΎ ΠΌΠΎΠ·Π³Π°, Π΄ΠΎ 25β30 ΠΌΠΠ² ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ Π²ΡΠ΅Π³ΠΎ ΡΠ΅Π»Π° ΠΈ Π΄ΠΎ 35β40 ΠΌΠΠ² ΠΏΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΈ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°. ΠΠ»Ρ ΠΎΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΠΈ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΡΡ
ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΡΡ
ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠΉ, ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ², ΠΏΠΎΠ»ΡΡΠ΅Π½Π½ΡΡ
Π² ΡΠ°Π·Π½ΡΡ
ΠΎΡΠ΄Π΅Π»Π΅Π½ΠΈΡΡ
ΠΏΠΎΠ·ΠΈΡΡΠΎΠ½Π½ΠΎΠΉ ΡΠΌΠΈΡΡΠΈΠΎΠ½Π½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ, ΠΈ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΡ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΡΠ΅Π½Π½ΠΎΡΡΠΈ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° Π² Π ΠΎΡΡΠΈΠΈ Π½Π΅ΠΎΠ±Ρ
ΠΎΠ΄ΠΈΠΌΠ° ΡΡΠ°Π½Π΄Π°ΡΡΠΈΠ·Π°ΡΠΈΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΡ
ΠΏΡΠΎΡΠΎΠΊΠΎΠ»ΠΎΠ² ΡΠ±ΠΎΡΠ° ΠΈ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ Π΄Π°Π½Π½ΡΡ
. ΠΠΏΡΠΈΠΌΠΈΠ·Π°ΡΠΈΡ ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π·Π°ΡΠΈΡΡ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π²ΠΎΠ·ΠΌΠΎΠΆΠ½Π° Π·Π° ΡΡΡΡ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π½ΠΈΠ·ΠΊΠΎΠ΄ΠΎΠ·ΠΎΠ²ΠΎΠ³ΠΎ ΡΠ΅ΠΆΠΈΠΌΠ° ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠ³ΠΎ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π²ΠΌΠ΅ΡΡΠΎ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ, ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠΏΠ΅ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΡΠΎΠΊΠΎΠ»ΠΎΠ² Π΄Π»Ρ ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΡ
Π³ΡΡΠΏΠΏ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΠΊΠΎΡΡΠ΅ΠΊΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΠΈΡΡΠ΅ΠΌΡ Π°Π²ΡΠΎΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΌΠΎΠ΄ΡΠ»ΡΡΠΈΠΈ ΡΠΈΠ»Ρ ΡΠΎΠΊΠ° (tube current modulation) ΠΈ ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΡΠ΅ΠΊΠΎΠ½ΡΡΡΡΠΊΡΠΈΠΈ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΡ; ΠΎΠ±ΡΡΠ΅Π½ΠΈΡ ΠΌΠ΅Π΄ΠΈΡΠΈΠ½ΡΠΊΠΎΠ³ΠΎ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»Π° ΡΠ΅Ρ
Π½ΠΈΡΠ΅ΡΠΊΠΈΠΌ ΠΏΡΠΈΡΠΌΠ°ΠΌ ΡΠ½ΠΈΠΆΠ΅Π½ΠΈΡ Π΄ΠΎΠ·Ρ ΠΈ Π·Π½Π°Π½ΠΈΡΠΌ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΡΠ°Π΄ΠΈΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ
Π‘ΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΡ ΠΈ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π»Π΅Π³ΠΊΠΈΡ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠ΅ΠΉ, Π²ΡΠ·Π²Π°Π½Π½ΠΎΠΉ COVID-19
The coronavirus infection (COVID-19) is characterized by a high incidence of pneumonia. Extensive damage, high mortality associated with COVID-19 make the rapid bedside diagnosis and dynamic monitoring of the volume and nature of lung tissue damage a challenge. Lung ultrasound examination can be used as a tool to answer it.The objective: to compare the signs detected by lung computed tomography and ultrasound and to assess the sensitivity and specificity of ultrasound in the diagnosis of pneumonia induced by COVID-19.Subjects and Methods. The observational prospective clinical study included 388 patients aged 18β75 years old; they had a confirmed diagnosis of pneumonia caused by COVID-19 or suspected COVID-19. Lung ultrasound was performed within 24 hours after computed tomography (CT) of the chest organs. During CT, pathological signs, infiltration and consolidation of the lungs were visualized which were documented by lung segments. Lung ultrasound was performed according to the Russian Protocol, ultrasound signs of B-lines and consolidation were also documented based on the projection of lung segments on the chest wall. The distributions of variables was analyzed, described and summarized. The sensitivity and specificity of ultrasound methods were evaluated on the basis of ROC analysis according to CT gold standard.Results. Bilateral involvement was found in 100% of cases. Typical CT signs of pneumonia caused by coronavirus infection were ground-glass opacity of the pulmonary parenchyma, thickened pleura, consolidation, interstitium, reticular induration, and cobblestone appearance. With ultrasound examination of the lungs and pleura, the detected signs corresponded to CT signs. B lines (multifocal, discrete or merging) and consolidation of various volumes of lung tissue were most common during ultrasound. The sign of consolidation was detected less frequently versus infiltration (p < 0.001). The sensitivity of lung ultrasound in the diagnosis of lung lesions was 95.3%, and the specificity was 85.4%, the area under the curve was 0.976 with a confidence interval of 0.961β0.991 (p < 0.001).Conclusion. The use of lung ultrasound during the COVID-19 pandemic makes it possible to identify, assess the volume and nature of lung damage. Lung ultrasound demonstrated accuracy comparable to CT of the chest organs in detecting pneumonia in patients with COVID-19.ΠΠΎΡΠΎΠ½Π°Π²ΠΈΡΡΡΠ½Π°Ρ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΡ (COVID-19) Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΠ΅ΡΡΡ Π²ΡΡΠΎΠΊΠΎΠΉ ΡΠ°ΡΡΠΎΡΠΎΠΉ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ. ΠΠΎΠ»ΡΡΠ°Ρ ΠΏΠ»ΠΎΡΠ°Π΄Ρ ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ, Π²ΡΡΠΎΠΊΠ°Ρ Π»Π΅ΡΠ°Π»ΡΠ½ΠΎΡΡΡ ΠΏΡΠΈ COVID-19 ΡΡΠ°Π²ΡΡ Π·Π°Π΄Π°ΡΡ Π±ΡΡΡΡΠΎΠΉ ΠΏΡΠΈΠΊΡΠΎΠ²Π°ΡΠ½ΠΎΠΉ Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠΈ ΠΈ Π΄ΠΈΠ½Π°ΠΌΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΌΠΎΠ½ΠΈΡΠΎΡΠΈΠ½Π³Π° ΠΎΠ±ΡΠ΅ΠΌΠ° ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠ° ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ Π»Π΅Π³ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ. Π’Π°ΠΊΠΈΠΌ ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½ΡΠΎΠΌ ΡΡΠ°Π»ΠΎ ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ (Π£ΠΠ) Π»Π΅Π³ΠΊΠΈΡ
.Π¦Π΅Π»Ρ: ΡΠΎΠΏΠΎΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ², Π²ΡΡΠ²Π»ΡΠ΅ΠΌΡΡ
ΠΏΡΠΈ ΠΊΠΎΠΌΠΏΡΡΡΠ΅ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ (ΠΠ’) ΠΈ Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
, ΠΈ ΠΎΡΠ΅Π½ΠΊΠ° ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠΈ Π£ΠΠ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ ΠΏΡΠΈ COVID-19.ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. Π ΠΎΠ±ΡΠ΅ΡΠ²Π°ΡΠΈΠΎΠ½Π½ΠΎΠ΅ ΠΏΡΠΎΡΠΏΠ΅ΠΊΡΠΈΠ²Π½ΠΎΠ΅ ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ Π²ΠΊΠ»ΡΡΠ΅Π½ΠΎ 388 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Π² Π²ΠΎΠ·ΡΠ°ΡΡΠ΅ 18β75 Π»Π΅Ρ Ρ ΠΏΠΎΠ΄ΡΠ²Π΅ΡΠΆΠ΄Π΅Π½Π½ΡΠΌ Π΄ΠΈΠ°Π³Π½ΠΎΠ·ΠΎΠΌ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ, Π²ΡΠ·Π²Π°Π½Π½ΠΎΠΉ COVID-19, ΠΈΠ»ΠΈ ΠΏΠΎΠ΄ΠΎΠ·ΡΠ΅Π½ΠΈΠ΅ΠΌ Π½Π° COVID-19. Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
Π²ΡΠΏΠΎΠ»Π½ΡΠ»ΠΈ Π² ΡΠ΅ΡΠ΅Π½ΠΈΠ΅ 24 Ρ ΠΏΠΎΡΠ»Π΅ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΡ ΠΠ’ ΠΎΡΠ³Π°Π½ΠΎΠ² Π³ΡΡΠ΄Π½ΠΎΠΉ ΠΊΠ»Π΅ΡΠΊΠΈ. ΠΡΠΈ ΠΠ’ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ»ΠΈ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΈΠ½ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠΈ ΠΈ ΠΊΠΎΠ½ΡΠΎΠ»ΠΈΠ΄Π°ΡΠΈΠΈ Π»Π΅Π³ΠΊΠΈΡ
, ΠΊΠΎΡΠΎΡΡΠ΅ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΈ ΠΏΠΎ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠ°ΠΌ Π»Π΅Π³ΠΊΠΈΡ
. Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ ΠΏΠΎ Β«ΡΡΡΡΠΊΠΎΠΌΡ ΠΏΡΠΎΡΠΎΠΊΠΎΠ»ΡΒ», ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ Π-Π»ΠΈΠ½ΠΈΠΉ ΠΈ ΠΊΠΎΠ½ΡΠΎΠ»ΠΈΠ΄Π°ΡΠΈΠΈ ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π³ΠΈΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΡΠΎΠ΅ΠΊΡΠΈΠΈ ΡΠ΅Π³ΠΌΠ΅Π½ΡΠΎΠ² Π»Π΅Π³ΠΊΠΈΡ
Π½Π° Π³ΡΡΠ΄Π½ΡΡ ΡΡΠ΅Π½ΠΊΡ. ΠΡΠΏΠΎΠ»Π½Π΅Π½ Π°Π½Π°Π»ΠΈΠ· Π΄Π»Ρ ΠΎΠΏΠΈΡΠ°Π½ΠΈΡ ΠΈ ΠΎΠ±ΠΎΠ±ΡΠ΅Π½ΠΈΡ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
. ΠΡΠ΅Π½ΠΊΡ ΡΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΠΈ, ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΠΈ ΡΠ»ΡΡΡΠ°Π·Π²ΡΠΊΠΎΠ²ΡΡ
ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΏΡΠΎΠ²ΠΎΠ΄ΠΈΠ»ΠΈ Π½Π° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ROC-Π°Π½Π°Π»ΠΈΠ·Π° ΠΏΠΎ Π·ΠΎΠ»ΠΎΡΠΎΠΌΡ ΡΡΠ°Π½Π΄Π°ΡΡΡ ΠΠ’.Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΠ²ΡΡΡΠΎΡΠΎΠ½Π½Π΅Π΅ Π²ΠΎΠ²Π»Π΅ΡΠ΅Π½ΠΈΠ΅ ΠΎΠ±Π½Π°ΡΡΠΆΠ΅Π½ΠΎ Π² 100% ΡΠ»ΡΡΠ°Π΅Π². Π₯Π°ΡΠ°ΠΊΡΠ΅ΡΠ½ΡΠΌΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌΠΈ Π΄Π»Ρ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ, Π²ΡΠ·Π²Π°Π½Π½ΠΎΠΉ ΠΊΠΎΡΠΎΠ½Π°Π²ΠΈΡΡΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΠΊΡΠΈΠ΅ΠΉ, Π½Π° ΠΠ’ ΡΡΠ°Π»ΠΈ ΡΠΏΠ»ΠΎΡΠ½Π΅Π½ΠΈΠ΅ Π»Π΅Π³ΠΎΡΠ½ΠΎΠΉ ΠΏΠ°ΡΠ΅Π½Ρ
ΠΈΠΌΡ ΠΏΠΎ ΡΠΈΠΏΡ Β«ΠΌΠ°ΡΠΎΠ²ΠΎΠ³ΠΎ ΡΡΠ΅ΠΊΠ»Π°Β», ΡΡΠΎΠ»ΡΠ΅Π½Π½Π°Ρ ΠΏΠ»Π΅Π²ΡΠ°, ΠΊΠΎΠ½ΡΠΎΠ»ΠΈΠ΄Π°ΡΠΈΡ, ΡΠ΅ΡΠΈΠΊΡΠ»ΡΡΠ½ΡΠ΅ ΡΠΏΠ»ΠΎΡΠ½Π΅Π½ΠΈΡ ΠΈΠ½ΡΠ΅ΡΡΡΠΈΡΠΈΡ, ΡΠΈΠΌΠΏΡΠΎΠΌ Β«Π±ΡΠ»ΡΠΆΠ½ΠΎΠΉ ΠΌΠΎΡΡΠΎΠ²ΠΎΠΉΒ». ΠΡΠΈ Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
ΠΈ ΠΏΠ»Π΅Π²ΡΡ Π²ΡΡΠ²Π»ΡΠ΅ΠΌΡΠ΅ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΡΠΎΠΎΡΠ²Π΅ΡΡΡΠ²ΠΎΠ²Π°Π»ΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠ°ΠΌ ΠΠ’. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΡΠ°ΡΡΠΎ ΠΏΡΠΈ Π£ΠΠ Π²ΡΡΡΠ΅ΡΠ°Π»ΠΈΡΡ B-Π»ΠΈΠ½ΠΈΠΈ (ΠΌΡΠ»ΡΡΠΈΡΠΎΠΊΠ°Π»ΡΠ½ΡΠ΅, Π΄ΠΈΡΠΊΡΠ΅ΡΠ½ΡΠ΅ ΠΈΠ»ΠΈ ΡΠ»ΠΈΠ²Π°ΡΡΠΈΠ΅ΡΡ) ΠΈ ΠΊΠΎΠ½ΡΠΎΠ»ΠΈΠ΄Π°ΡΠΈΡ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΎΠ±ΡΠ΅ΠΌΠΎΠΌ Π»Π΅Π³ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ. ΠΡΠΈΠ·Π½Π°ΠΊ ΠΊΠΎΠ½ΡΠΎΠ»ΠΈΠ΄Π°ΡΠΈΠΈ Π²ΡΡΠ²Π»ΡΠ»ΠΈ ΡΠ΅ΠΆΠ΅, ΡΠ΅ΠΌ ΠΏΡΠΈΠ·Π½Π°ΠΊ ΠΈΠ½ΡΠΈΠ»ΡΡΡΠ°ΡΠΈΠΈ (p < 0,001). Π§ΡΠ²ΡΡΠ²ΠΈΡΠ΅Π»ΡΠ½ΠΎΡΡΡ Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΠΏΠΎΡΠ°ΠΆΠ΅Π½ΠΈΡ Π»Π΅Π³ΠΊΠΈΡ
ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 95,3%, Π° ΡΠΏΠ΅ΡΠΈΡΠΈΡΠ½ΠΎΡΡΡ β 85,4%, ΠΏΠ»ΠΎΡΠ°Π΄Ρ ΠΏΠΎΠ΄ ΠΊΡΠΈΠ²ΠΎΠΉ ΡΠΎΡΡΠ°Π²ΠΈΠ»Π° 0,976 Ρ Π΄ΠΎΠ²Π΅ΡΠΈΡΠ΅Π»ΡΠ½ΡΠΌ ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»ΠΎΠΌ 0,961β0,991 (p < 0,001).ΠΠ°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠ΅. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
Π²ΠΎ Π²ΡΠ΅ΠΌΡ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π²ΡΡΠ²ΠΈΡΡ ΠΈ ΠΎΡΠ΅Π½ΠΈΡΡ ΠΎΠ±ΡΠ΅ΠΌ ΠΈ Ρ
Π°ΡΠ°ΠΊΡΠ΅Ρ ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ Π»Π΅Π³ΠΎΡΠ½ΠΎΠΉ ΡΠΊΠ°Π½ΠΈ. Π£ΠΠ Π»Π΅Π³ΠΊΠΈΡ
ΠΏΡΠΎΠ΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°Π»ΠΎ ΡΠΎΡΠ½ΠΎΡΡΡ, ΡΡΠ°Π²Π½ΠΈΠΌΡΡ Ρ ΠΠ’ ΠΎΡΠ³Π°Π½ΠΎΠ² Π³ΡΡΠ΄Π½ΠΎΠΉ ΠΊΠ»Π΅ΡΠΊΠΈ, ΠΏΡΠΈ Π²ΡΡΠ²Π»Π΅Π½ΠΈΠΈ ΠΏΠ½Π΅Π²ΠΌΠΎΠ½ΠΈΠΈ Ρ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ COVID-19
ΠΠ ΠΠΠΠΠΠΠΠ 3D-ΠΠΠΠΠΠΠ Π‘ΠΠ ΠΠ¦Π, Π‘ΠΠΠΠΠΠΠ«Π₯ ΠΠ ΠΠ‘ΠΠΠΠ DICOM-ΠΠΠΠΠ ΠΠΠΠΠΠ, Π ΠΠΠΠΠ¦ΠΠΠ‘ΠΠΠ ΠΠ ΠΠΠ’ΠΠΠ
Three-dimensional printing (3D printing, additive manufacturing, rapid prototyping) is a technology of a physical object creation fromΒ digital model by layered addition of material. Additive technologies differ from mass production by personalization, customization and relative simplicity of 3D-models creation. 3D models ability toΒ demonstrate heart anatomy is of use in cardiac surgery, primarily during theΒ educational process and preoperative planning and, less common, for implantable devices testing and hemodynamic modeling. AlthoughΒ the role of 3D models in clinical practice is not currently defined, 3D printing mass application can provide important advantages to solveΒ a number of diagnostic and therapeutic issues. The article presents the revue of scientific publications describing the use of physicalΒ three-dimensional heart models in cardiac surgery.Π’ΡΠ΅Ρ
ΠΌΠ΅ΡΠ½Π°Ρ ΠΏΠ΅ΡΠ°ΡΡ (3D-ΠΏΠ΅ΡΠ°ΡΡ, Π°Π΄Π΄ΠΈΡΠΈΠ²Π½ΠΎΠ΅ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²ΠΎ, Π±ΡΡΡΡΠΎΠ΅ ΠΏΡΠΎΡΠΎΡΠΈΠΏΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅) β ΡΡΠΎ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΡ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ ΠΎΠ±ΡΠ΅ΠΊΡΠ° ΠΈΠ· ΡΠΈΡΡΠΎΠ²ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΏΡΡΠ΅ΠΌ ΠΏΠΎΡΠ»ΠΎΠΉΠ½ΠΎΠ³ΠΎ Π΄ΠΎΠ±Π°Π²Π»Π΅Π½ΠΈΡ ΠΌΠ°ΡΠ΅ΡΠΈΠ°Π»Π°. ΠΡΠ½ΠΎΡΠΈΡΠ΅Π»ΡΠ½Π°Ρ ΠΏΡΠΎΡΡΠΎΡΠ° ΡΠΎΠ·Π΄Π°Π½ΠΈΡ 3D-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ, ΠΈΡ
ΠΈΠ½Π΄ΠΈΠ²ΠΈΠ΄ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΈ ΠΊΠ°ΡΡΠΎΠΌΠΈΠ·Π°ΡΠΈΡ ΠΎΡΠ»ΠΈΡΠ°ΡΡ Π°Π΄Π΄ΠΈΡΠΈΠ²Π½ΡΠ΅ ΡΠ΅Ρ
Π½ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΎΡ ΡΠ΅ΡΠΈΠΉΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΠΈΠ·Π²ΠΎΠ΄ΡΡΠ²Π°. ΠΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΡΒ Π΄Π΅ΠΌΠΎΠ½ΡΡΡΠΈΡΠΎΠ²Π°ΡΡ Π°Π½Π°ΡΠΎΠΌΠΈΡ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΏΠΎΠΌΠΎΡΡΡ 3D-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΠΎΠΏΡΠ΅Π΄Π΅Π»ΠΈΠ»Π° ΠΈΡ
Β ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π² ΠΊΠ°ΡΠ΄ΠΈΠΎΡ
ΠΈΡΡΡΠ³ΠΈΠΈ, Π² ΠΏΠ΅ΡΠ²ΡΡ ΠΎΡΠ΅ΡΠ΅Π΄Ρ, Π² Ρ
ΠΎΠ΄Π΅ ΠΎΠ±ΡΠ°Π·ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎΠ³ΠΎ ΠΏΡΠΎΡΠ΅ΡΡΠ° ΠΈΒ ΠΏΡΠ΅Π΄ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠ³ΠΎ ΠΏΠ»Π°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ, Π° ΡΠ°ΠΊΠΆΠ΅ Π΄Π»Ρ ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈΠΌΠΏΠ»Π°Π½ΡΠΈΡΡΠ΅ΠΌΡΡ
Β ΡΡΡΡΠΎΠΉΡΡΠ² ΠΈ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΡ Π³Π΅ΠΌΠΎΠ΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ. ΠΠ΅ΡΠΌΠΎΡΡΡ Π½Π° ΡΠΎ, ΡΡΠΎ ΡΠΎΠ»Ρ 3D-ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π² ΠΊΠ»ΠΈΠ½ΠΈΡΠ΅ΡΠΊΠΎΠΉΒ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ Π² Π½Π°ΡΡΠΎΡΡΠ΅Π΅Β Π²ΡΠ΅ΠΌΡ Π½Π΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π°, Π²Π½Π΅Π΄ΡΠ΅Π½ΠΈΠ΅ 3D-ΠΏΠ΅ΡΠ°ΡΠΈ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎ Π΄Π°ΡΡ Π²Π°ΠΆΠ½ΡΠ΅Β ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° Π² ΡΠ΅ΡΠ΅Π½ΠΈΠΈ ΡΡΠ΄Π° Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ Π»Π΅ΡΠ΅Π±Π½ΡΡ
Π·Π°Π΄Π°Ρ. Π ΡΡΠ°ΡΡΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΡΒ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΡ Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°ΡΡΠ½ΡΡ
ΡΡΠ°ΡΠ΅ΠΉ, ΠΏΠΎΡΠ²ΡΡΠ΅Π½Π½ΡΡ
ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ ΡΡΠ΅Ρ
ΠΌΠ΅ΡΠ½ΡΡ
ΡΠΈΠ·ΠΈΡΠ΅ΡΠΊΠΈΡ
Β ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ ΡΠ΅ΡΠ΄ΡΠ° Π² ΠΊΠ°ΡΠ΄ΠΈΠΎΡ
ΠΈΡΡΡΠ³ΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅
Π£ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½Π°Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎ-ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·Π° ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΡΡ ΠΌΡΡΡ Π»Π΅Π²ΠΎΠ³ΠΎ ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠ°
The aim of the study was to assess the opportunities and improve contrast-enhanced cardiac magnetic resonance imaging in the diagnosis of left ventricular papillary muscles scarring. Materials and methods. Contrast-enhanced cardiac magnetic resonance imaging was performed 68 patients after myocardial infarction. The advanced method uses short signal inversion time (150-180 ms) to increase the contrast of myocardial scar in the papillary muscles. Results. The signs of papillary muscles scarring were identified in 16 patients (23,5%) by advanced method and in 12 patient (17.6%) by standard method. The signs of mitral insufficiency was found only in 9 patients (13.2%) by echocardiography. Conlusion. Found that contrast-enhanced cardiac magnetic resonance imaging allows to visualize morphological changes in a papillary muscles before violation of their function and mitral insufficiency development. Using short signal inversion time (150-180ms) allows increase by 3.5 times the contrast of myocardial scar in the papillary muscles.Π¦Π΅Π»Ρ: ΠΎΡΠ΅Π½ΠΊΠ° Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠ΅ΠΉ ΠΈ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΠΠ Π’ Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ Π² Π΄ΠΈΠ°Π³Π½ΠΎΡΡΠΈΠΊΠ΅ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·Π° ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΡΡ
ΠΌΡΡΡ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ° ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠ΅ 1,5 Π’Π» ΠΠ Π’ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ Π±ΡΠ»Π° Π²ΡΠΏΠΎΠ»Π½Π΅Π½Π° 68 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°ΠΌ Ρ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΡΠΌ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·ΠΎΠΌ Π»Π΅Π²ΠΎΠ³ΠΎ ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠ°. Π£ΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½Π°Ρ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΎΡΡΡΠΎΡΠ΅Π½Π½ΠΎΠ³ΠΎ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΏΡΠ΅Π΄ΠΏΠΎΠ»Π°Π³Π°Π΅Ρ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΠΊΠΎΠ³ΠΎ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΠΈ ΡΠΈΠ³Π½Π°Π»Π° (150-180 ΠΌΡ) ΠΏΠΎΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠ½ΠΎΡΡΠ΅ΠΉ ΠΈΠ½Π²Π΅ΡΡΠΈΡ-Π²ΠΎΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΈΠ΅ Π΄Π»Ρ ΠΏΠΎΠ²ΡΡΠ΅Π½ΠΈΡ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΠΎΡΡΠΈ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·Π° Π² ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΡΡ
ΠΌΡΡΡΠ°Ρ
. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. ΠΡΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠΈ ΡΡΠΎΠ²Π΅ΡΡΠ΅Π½ΡΡΠ²ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·Π° ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΡΡ
ΠΌΡΡΡ Π±ΡΠ»ΠΈ Π²ΡΡΠ²Π»Π΅Π½Ρ Ρ 16 (23,5%) ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ², ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΠΎΠΉ ΠΌΠ΅ΡΠΎΠ΄ΠΈΠΊΠΈ - Ρ 12 (17,6%). ΠΡΠΈ ΡΡ
ΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΈ ΠΌΠΈΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎΡΡΠΈ Π±ΡΠ»ΠΈ Π²ΡΡΠ²Π»Π΅Π½Ρ ΡΠΎΠ»ΡΠΊΠΎ Ρ 9 (13,2%) ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ². ΠΡΠ²ΠΎΠ΄Ρ. Π£ΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΠΠ Π’ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°ΡΡ ΠΌΠΎΡΡΠΎΠ»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΈΠ΅ ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΡ ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΡΡ
ΠΌΡΡΡ Π΄ΠΎ Π½Π°ΡΡΡΠ΅Π½ΠΈΡ ΠΈΡ
ΡΡΠ½ΠΊΡΠΈΠΈ, Ρ.Π΅. Π΄ΠΎ ΡΠ°Π·Π²ΠΈΡΠΈΡ ΠΏΡΠΈΠ·Π½Π°ΠΊΠΎΠ² ΠΌΠΈΡΡΠ°Π»ΡΠ½ΠΎΠΉ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎΡΡΠΈ ΠΏΠΎ Π΄Π°Π½Π½ΡΠΌ ΡΡ
ΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΠ³ΡΠ°ΡΠΈΠΈ. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΊΠΎΡΠΎΡΠΊΠΎΠ³ΠΎ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ ΠΈΠ½Π²Π΅ΡΡΠΈΠΈ ΡΠΈΠ³Π½Π°Π»Π° ΠΏΡΠΈ ΠΎΡΡΡΠΎΡΠ΅Π½Π½ΠΎΠΌ ΡΠΊΠ°Π½ΠΈΡΠΎΠ²Π°Π½ΠΈΠΈ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ Π² 3,5 ΡΠ°Π·Π° ΠΏΠΎΠ²ΡΡΠΈΡΡ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΠΎΡΡΡ Π·ΠΎΠ½Ρ ΠΏΠΎΡΡΠΈΠ½ΡΠ°ΡΠΊΡΠ½ΠΎΠ³ΠΎ ΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΊΠ»Π΅ΡΠΎΠ·Π° Π² ΠΏΠ°ΠΏΠΈΠ»Π»ΡΡΠ½ΠΎΠΉ ΠΌΡΡΡΠ΅ Π½Π° ΡΠΎΠ½Π΅ ΠΏΠΎΠ»ΠΎΡΡΠΈ Π»Π΅Π²ΠΎΠ³ΠΎ ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠ° ΠΏΠΎ ΡΡΠ°Π²Π½Π΅Π½ΠΈΡ ΡΠΎ ΡΡΠ°Π½Π΄Π°ΡΡΠ½ΡΠΌ Π²ΡΠ΅ΠΌΠ΅Π½Π΅ΠΌ ΠΈΠ½Π²Π΅ΡΡΠΈΠΈ
ΠΡΡΠ΅ΡΠ°ΠΊΡΡ ΠΏΡΠΈ ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎ-ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΠ½ΠΎΠΉ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠΈΠΈ ΡΠ΅ΡΠ΄ΡΠ°: ΡΠΏΠΎΡΠΎΠ±Ρ ΡΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΈ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΠΈ
The aim of the study was to describe the cardiac magnetic resonance imaging artifacts and to develop ways to eliminate or interpret them. Materials and methods. 1,5 T contrast-enhanced cardiac magnetic resonance imaging was performed 156 patients with coronary artery disease. Technique of cardiac MRI included an assessment of left ventricular contractility, visualization of edema and acute myocardial damage, assessment of perfusion and myocardial scarring. Results. Various artifacts during cardiac MRI with contrast enhancement were visualized in almost every patient. The quality of cardiac magnetic resonance imaging depended on heart rate and blood flow in the cavities. In addition there were artifacts from the coronary stents, vascular clips, sternum's cerclage, as well as overlaying other organs and structures. During the study, were frequently observed βhyperintense endocardiumβ and βdark rimβ artifacts which simulated endocardial edema and myocardial perfusion defect. Conclusion. The study found that despite the presence of certain artifacts that can affect the quality of the images and their analysis, there are effective ways to eliminate or reduce them. βHyperintense endocardiumβ and βdark rimβ artifacts can be distinguished from true pathology.Π¦Π΅Π»Ρ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ: ΠΎΠΏΠΈΡΠ°Π½ΠΈΠ΅ Π°ΡΡΠ΅ΡΠ°ΠΊΡΠΎΠ² ΠΏΡΠΈ ΠΠ Π’ ΡΠ΅ΡΠ΄ΡΠ° ΠΈ ΡΠ°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΡΠΏΠΎΡΠΎΠ±ΠΎΠ² ΠΈΡ
ΡΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΈΠ»ΠΈ ΠΏΡΠ°Π²ΠΈΠ»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠ΅ΡΠΏΡΠ΅ΡΠ°ΡΠΈΠΈ. ΠΠ°ΡΠ΅ΡΠΈΠ°Π» ΠΈ ΠΌΠ΅ΡΠΎΠ΄Ρ. ΠΠ° ΠΌΠ°Π³Π½ΠΈΡΠ½ΠΎ-ΡΠ΅Π·ΠΎΠ½Π°Π½ΡΠ½ΠΎΠΌ ΡΠΎΠΌΠΎΠ³ΡΠ°ΡΠ΅ 1,5 Π’Π» ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΎ 156 ΠΏΠ°ΡΠΈΠ΅Π½ΡΠΎΠ² Ρ ΠΈΡΠ΅ΠΌΠΈΡΠ΅ΡΠΊΠΎΠΉ Π±ΠΎΠ»Π΅Π·Π½ΡΡ ΡΠ΅ΡΠ΄ΡΠ°. ΠΠ΅ΡΠΎΠ΄ΠΈΠΊΠ° ΠΠ Π’ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ Π²ΠΊΠ»ΡΡΠ°Π»Π° ΠΎΡΠ΅Π½ΠΊΡ ΡΠΎΠΊΡΠ°ΡΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΡΡΠ½ΠΊΡΠΈΠΈ Π»Π΅Π²ΠΎΠ³ΠΎ ΠΆΠ΅Π»ΡΠ΄ΠΎΡΠΊΠ°, Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΡ ΠΎΡΠ΅ΠΊΠ° ΠΈ ΠΎΡΡΡΠΎΠ³ΠΎ ΠΏΠΎΠ²ΡΠ΅ΠΆΠ΄Π΅Π½ΠΈΡ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°, ΠΎΡΠ΅Π½ΠΊΡ ΠΏΠ΅ΡΡΡΠ·ΠΈΠΈ ΠΈ ΡΡΠ±ΡΠΎΠ²ΡΡ
ΠΈΠ·ΠΌΠ΅Π½Π΅Π½ΠΈΠΉ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°. Π Π΅Π·ΡΠ»ΡΡΠ°ΡΡ. Π Π°Π·Π»ΠΈΡΠ½ΡΠ΅ Π°ΡΡΠ΅ΡΠ°ΠΊΡΡ ΠΏΡΠΈ ΠΏΡΠΎΠ²Π΅Π΄Π΅Π½ΠΈΠΈ ΠΠ Π’ ΡΠ΅ΡΠ΄ΡΠ° Ρ ΠΊΠΎΠ½ΡΡΠ°ΡΡΠ½ΡΠΌ ΡΡΠΈΠ»Π΅Π½ΠΈΠ΅ΠΌ Π±ΡΠ»ΠΈ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·ΠΈΡΠΎΠ²Π°Π½Ρ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Ρ ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΠΎΠ±ΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ ΠΏΠ°ΡΠΈΠ΅Π½ΡΠ°. ΠΠ°ΡΠ΅ΡΡΠ²ΠΎ Π²ΠΈΠ·ΡΠ°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠ΅ΡΠ΄ΡΠ° ΠΏΡΠΈ ΠΠ Π’ Π½Π°ΠΏΡΡΠΌΡΡ Π·Π°Π²ΠΈΡΠ΅Π»ΠΎ ΠΎΡ ΡΠ°ΡΡΠΎΡΡ ΡΠ΅ΡΠ΄Π΅ΡΠ½ΡΡ
ΡΠΎΠΊΡΠ°ΡΠ΅Π½ΠΈΠΉ ΠΈ ΡΠ΅Π³ΡΠ»ΡΡΠ½ΠΎΡΡΠΈ ΡΠΈΡΠΌΠ°. ΠΠ° ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ ΡΠ°ΠΊΠΆΠ΅ Π²Π»ΠΈΡΠ» ΡΠΎΠΊ ΠΊΡΠΎΠ²ΠΈ Π² ΠΏΠΎΠ»ΠΎΡΡΡΡ
ΡΠ΅ΡΠ΄ΡΠ° ΠΈ ΠΊΡΡΠΏΠ½ΡΡ
ΡΠΎΡΡΠ΄Π°Ρ
. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, Π²ΠΎΠ·Π½ΠΈΠΊΠ°Π»ΠΈ Π°ΡΡΠ΅ΡΠ°ΠΊΡΡ ΠΎΡ ΠΊΠΎΡΠΎΠ½Π°ΡΠ½ΡΡ
ΡΡΠ΅Π½ΡΠΎΠ², ΡΠΎΡΡΠ΄ΠΈΡΡΡΡ
ΠΊΠ»ΠΈΠΏΡ, ΡΠ΅ΡΠΊΠ»ΡΠΆΠ° Π³ΡΡΠ΄ΠΈΠ½Ρ, Π½Π°Π»ΠΎΠΆΠ΅Π½ΠΈΡ Π΄ΡΡΠ³ΠΈΡ
ΠΎΡΠ³Π°Π½ΠΎΠ². ΠΠΎ Π²ΡΠ΅ΠΌΡ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ ΡΠ°ΡΡΠΎ Π½Π°Π±Π»ΡΠ΄Π°Π»ΠΈΡΡ Π°ΡΡΠ΅ΡΠ°ΠΊΡΡ βΠ³ΠΈΠΏΠ΅ΡΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°β ΠΈ βΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΠ΄ΠΊΠ°β, ΠΊΠΎΡΠΎΡΡΠ΅ ΠΈΠΌΠΈΡΠΈΡΠΎΠ²Π°Π»ΠΈ ΠΎΡΠ΅ΠΊ ΡΠ½Π΄ΠΎΠΊΠ°ΡΠ΄Π° ΠΈ Π΄Π΅ΡΠ΅ΠΊΡ ΠΏΠ΅ΡΡΡΠ·ΠΈΠΈ ΠΌΠΈΠΎΠΊΠ°ΡΠ΄Π°. ΠΡΠ²ΠΎΠ΄Ρ. ΠΠ΅ΡΠΌΠΎΡΡΡ Π½Π° Π½Π°Π»ΠΈΡΠΈΠ΅ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½ΡΡ
Π°ΡΡΠ΅ΡΠ°ΠΊΡΠΎΠ², ΠΊΠΎΡΠΎΡΡΠ΅ ΠΌΠΎΠ³ΡΡ Π²Π»ΠΈΡΡΡ Π½Π° ΠΊΠ°ΡΠ΅ΡΡΠ²ΠΎ ΠΈΠ·ΠΎΠ±ΡΠ°ΠΆΠ΅Π½ΠΈΠΉ ΠΈ ΠΈΡ
Π°Π½Π°Π»ΠΈΠ·, ΡΡΡΠ΅ΡΡΠ²ΡΡΡ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½ΡΠ΅ ΡΠΏΠΎΡΠΎΠ±Ρ ΡΡΡΡΠ°Π½Π΅Π½ΠΈΡ ΠΈΠ»ΠΈ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ ΡΡΠ΄Π° Π°ΡΡΠ΅ΡΠ°ΠΊΡΠΎΠ². ΠΡΡΠ΅ΡΠ°ΠΊΡΡ βΠ³ΠΈΠΏΠ΅ΡΠΈΠ½ΡΠ΅Π½ΡΠΈΠ²Π½ΠΎΠ³ΠΎ ΡΠ½Π΄ΠΎΠΊΠ°ΡΠ΄Π°β ΠΈ βΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ ΠΎΠ±ΠΎΠ΄ΠΊΠ°β ΠΌΠΎΠΆΠ½ΠΎ Π΄ΠΈΡΡΠ΅ΡΠ΅Π½ΡΠΈΡΠΎΠ²Π°ΡΡ Ρ ΠΈΡΡΠΈΠ½Π½ΠΎΠΉ ΠΏΠ°ΡΠΎΠ»ΠΎΠ³ΠΈΠ΅ΠΉ
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