АВТОМАТИЧЕСКИЙ АНАЛИЗ ПОРАЖЕНИЯ ЛЕГКИХ ПРИ COVID-19: СРАВНЕНИЕ СТАНДАРТНОЙ И НИЗКОДОЗНОЙ КОМПЬЮТЕРНОЙ ТОМОГРАФИИ

Аннотация

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.