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Siberian Journal of Clinical and Experimental Medicine

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Automated analysis of lung lesions in COVID-19: comparison of standard and low-dose CT

https://doi.org/10.29001/2073-8552-2022-37-4-114-123

Abstract

Introduction. Chest computed tomography (CT) plays a prominent role in determining the extent of pulmonary parenchymal lesions in COVID-19. At the same time, subjectivity of lung lesion volume assessment using 0-4 CT scale in COVID-19 and gradual introduction of low-dose CT (LDCT) requires an investigation of semi-automated lung segmentation accuracy in LDCT compared to CT.

Study Objective. To compare the accuracy of affected lung tissue volume calculation between CT and LDCT in COVID-19 using a semi-automatic segmentation program.

Material and Methods. The retrospective study was performed on data from the earlier prospective multicenter study registered at ClinicalTrials.gov, NCT04379531. CT and LDCT data were processed in 3D Slicer software with Lung CT Segmenter and Lung CT Analyzer extensions, and the volume of affected lung tissue and lung volume were determined by thresholding.

Results. The sample size was 84 patients with signs of COVID-19-associated pneumonia. Mean age was 50.6 ± 13.3 years, and the median body mass index (BMI) was 28.15 [24.85; 31.31] kg/m2. The effective doses were 10.1 ± 3.26 mSv for the standard CT protocol and 2.64 mSv [1.99; 3.67] for the developed LDCT protocol. The analysis of absolute lung lesion volume in cubic centimeters with Wilcoxon Signed Ranks Test revealed a statistically significant difference between CT and LDCT (p-value < 0.001). No statistically significant differences were found in the relative values of lung tissue lesion volume (lesion volume/lung volume) between CT and LDCT using Wilcoxon Signed Ranks Test (p-value = 0.95).

Conclusion. The reliability of developed LDCT protocol in COVID-19 for the semi-automated calculation of affected tissue percentage was comparable to the standard chest CT protocol when using 3D Slicer with Lung CT Segmenter and Lung CT Analyzer extensions.

About the Authors

I. A. Blokhin
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department
Russian Federation

Ivan A. Blokhin, Junior Research Scientist, Diagnostic Radiology Research Sector

24, p. 1, Petrovka str., Moscow, 127051



A. V. Solovev
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department
Russian Federation

Alexander V. Solovev, Junior Research Scientist

24, p. 1, Petrovka str., Moscow, 127051



A. V. Vladzymyrskyy
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department
Russian Federation

Anton V. Vladzymyrskyy, Dr. Sci. (Med.), Deputy Director for Research

24, p. 1, Petrovka str., Moscow, 127051



M. R. Kodenko
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department; Bauman Moscow State Technical University
Russian Federation

Maria R. Kodenko, Junior Research Scientist, Medical Research Department, Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department; Bauman Moscow State Technical University

24, p. 1, Petrovka str., Moscow, 127051; 
5, 2nd Baumanskaya str., bldg. 1, Moscow,105005



Yu. F. Shumskaya
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department; I.M. Sechenov First Moscow State Medical University (Sechenov University)
Russian Federation

Yuliya F. Shumskaya, Junior Research Scientist, Medical Research Department, Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department; Laboratory Technician, Department of Hospital Therapy No. 1, I.M. Sechenov First Moscow State Medical University (Sechenov University)

24, p. 1, Petrovka str., Moscow, 127051; 
8, Trubetskaya str., p. 2, Moscow, 119991



A. P. Gonchar
Clinical Research and Practical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Department
Russian Federation

Anna P. Gonchar, Junior Research Scientist, Medical Research Department

24, p. 1, Petrovka str., Moscow, 127051



V. A. Gombolevskiy
Artificial Intelligence Research Institute
Russian Federation

Victor A. Gombolevskiy, M.D., Ph.D., MPH, Head of Key Research Programs

5, 2nd Baumanskaya str., bldg. 1, Moscow,105005



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Blokhin I.A., Solovev A.V., Vladzymyrskyy A.V., Kodenko M.R., Shumskaya Yu.F., Gonchar A.P., Gombolevskiy V.A. Automated analysis of lung lesions in COVID-19: comparison of standard and low-dose CT. Siberian Journal of Clinical and Experimental Medicine. 2022;37(4):114-123. (In Russ.) https://doi.org/10.29001/2073-8552-2022-37-4-114-123

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ISSN 2713-2927 (Print)
ISSN 2713-265X (Online)