Feasibility of Ultra-Low-Dose CT for Bronchoscopy of Peripheral Lung Lesions.
Jung Seop EomGeewon LeeJiyeon RohHyun Sung ChungYeon Joo JeongPublished in: Medicina (Kaunas, Lithuania) (2020)
Background and objectives: Thin-section computed tomography (CT) is essential for identifying small bronchi during bronchoscopy using radial endobronchial ultrasound. Some patients should receive an additional CT for a thin-section image. We performed a retrospective study with a prospectively collected database to identify the optimal radiation dose for thin-section CT during peripheral bronchoscopy. Materials and Methods: In total, 91 patients with peripheral lung lesions underwent thin-section CT (both standard CT as a reference and ultra-low-dose CT (ultra-LDCT)). The patients were randomly assigned to one of four groups according to the ultra-LDCT parameters: group 1 = 120 kVp, 25 mAs; group 2 = 100 kVp, 15 mAs; group 3 = 120 kVp, 5 mAs; and group 4 = 100 kVp, 5 mAs. Two radiologists and two physicians analyzed both the standard CT and ultra-LDCT. Results: The effective doses (EDs) of ultra-LDCT significantly differed among the four groups (median EDs were 0.88, 0.34, 0.19, and 0.12 mSv for groups 1-4, respectively; p < 0.001). Median differences in peripheral airway wall thickness were higher in group 4 than in other groups (differences in median wall thickness measured by two radiologists were 0.4-0.5 mm and 0.8-0.9 mm for groups 1-3 and group 4, respectively). Bronchus signs on ultra-LDCT in groups 1 and 2 were well correlated with those of the standard-dose CT (accuracies of two radiologists and two pulmonary physicians were 95-100%). Conclusions: Our results indicate that ultra-LDCT with ED of >0.34 mSv (ED of group 2) is feasible for peripheral bronchoscopy.
Keyphrases
- dual energy
- image quality
- computed tomography
- contrast enhanced
- low dose
- positron emission tomography
- high resolution
- emergency department
- magnetic resonance imaging
- end stage renal disease
- primary care
- ejection fraction
- high dose
- artificial intelligence
- pulmonary hypertension
- ultrasound guided
- chemotherapy induced
- chronic kidney disease
- machine learning
- optical coherence tomography
- deep learning
- electronic health record
- adverse drug