Work

Detection of intracranial hemorrhage using ultralow-dose brain computed tomography with deep learning reconstruction versus conventional-dose computed tomography

Year: 2025

Type: article

Abstract: BACKGROUND: This study aimed to evaluate the diagnostic performance, image quality, and radiation dose among ultralow-dose protocol with deep learning reconstruction (DLR), ultralow-dose computed tomography (CT) with iterative reconstruction (IR), and conventional-dose protocols for detecting intracranial hemorrhage. METHODS: This retrospective study enrolled 93 patients (median age: 67 years; interquartile range [IQR]: 59-76 years; 61 males). A conventional-dose CT was obtained using 120 kVp, 123-188 mA and IR. Follow-up ultralow-dose CT was obtained using 120 kVp, 50 mA with IR and DLR. Qualitative assessments and quantitative assessments were conducted. The diagnostic performance for detecting intracranial hemorrhage was assessed. RESULTS: An approximately 84.0% reduction in median volume CT dose index was found in the ultralow-dose CT protocol (5.6 mGy) compared with conventional-dose CT (35.02 mGy). Ultralow-dose CT with DLR significantly (p < 0.001) reduced image noise, improved signal-to-nosie ratio, and contrast-to-tnoise ratio compared with ultralow-dose CT with IR and conventional-dose CT. Ultralow-dose CT with DLR resulted in higher sensitivity (99.3% vs. 98.6%) and specificity (97.5% vs. 97.5%) for detecting intracranial hemorrhage than ultralow-dose CT with IR. CONCLUSION: Ultralow-dose CT with DLR is not inferior to conventional-dose CT in terms of image quality and diagnostic performance for the detection of intracranial hemorrhage, while achieving an approximate 87.7% reduction in radiation dose.

Source: BMC Medical Imaging

DOI: 10.1186/s12880-025-02082-5