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Updated: May 22, 2025

Lung CT Segmentation to Identify Consolidations and Ground Glass Areas for Quantitative Assesment of SARS-CoV Pneumonia
Published on: December 19, 2020
Denoised Ultra-Low-Dose Chest CT to Assess Pneumonia in Individuals Who Are Immunocompromised
Maximiliano Klug1,2, Tamer Sobeh1,2, Michael Green1
1Division of Diagnostic Imaging, The Chaim Sheba Medical Center, Tel Hashomer, 2 Derech Sheba St, Ramat Gan 5265601, Israel.
Abstract:
Purpose To evaluate the accuracy of chest ultra-low-dose CT (ULDCT) as compared with normal-dose CT in the evaluation of pneumonia in individuals who are immunocompromised. Materials and Methods This prospective study included 54 adults who were immunocompromised (median age, 62 years [IQR, 47.75-69.25 years]; 34 [63%] male participants) referred for a chest CT scan between September 2020 and December 2022 to evaluate for pneumonia. Each participant underwent two scans: normal-dose CT (120 kVp and automatic current modulation) and ULDCT (100 kVp and constant current of 10 mA). ULDCT images underwent a postprocessing procedure using an artificial intelligence algorithm to reduce image noise. Two radiologists, blinded to all clinical information, examined the images obtained from the three methods (normal-dose CT, ULDCT, and denoised ULDCT) for the presence of pneumonia and associated findings. The normal-dose CT was used as the reference standard, and sensitivity, specificity, positive and negative predictive values, and accuracy were calculated. Results The median effective radiation dose of ULDCT scans (0.12 mSV) was 1.95% of that of the normal-dose CT (6.15 mSV). Ten of the 54 participants were correctly identified as having no pneumonia, with similar accuracy between denoised ULDCT and ULDCT (100% vs 96%-98%, respectively). Both methods allowed for detection of pneumonia and features associated with invasive fungal pneumonia, but accuracy was slightly better with denoised ULDCT (accuracy, 100% vs 91%-98%). Fine details were better visualized in denoised ULDCT images: tree-in-bud pattern (accuracy, 93% vs 78%-80%), interlobular septal thickening (accuracy, 78%-83% vs 61%-67%), and intralobular septal thickening (accuracy, 85%-87% vs 0%). Conclusion Denoised ULDCT imaging showed better accuracy than ULDCT in identifying lungs with or without pneumonia in individuals who were immunocompromised. Keywords: CT, Pulmonary, Lung, Infection, Technology Assessment Supplemental material is available for this article. © RSNA, 2025.
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