Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy

• Published in: European radiology 2024-01, Vol.34 (1), p.28-38
• Main Authors: Lyu, Peijie, Li, Zhen, Chen, Yan, Wang, Huixia, Liu, Nana, Liu, Jie, Zhan, Pengchao, Liu, Xing, Shang, Bo, Wang, Luotong, Gao, Jianbo
• Format: Article
• Language: English
• Subjects: Algorithms; Body mass; Body mass index; Body size; Computed Tomography; Conspicuity; Deep learning; Diagnostic Radiology; Energy; Image contrast; Image enhancement; Image processing; Image quality; Image reconstruction; Imaging; Internal Medicine; Interventional Radiology; Lesions; Liver; Medicine; Medicine & Public Health; Metastases; Metastasis; Neuroradiology; Noise; Portal vein; Quality assessment; Radiation; Radiation dosage; Radiology; Sex ratio; Signal to noise ratio; Texture; Transfer functions; Ultrasound
• ISSN: 1432-1084; 0938-7994; 1432-1084
• DOI: 10.1007/s00330-023-10033-3

Objectives To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). Methods In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. Results Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. Conclusion DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. Clinical relevance statement Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. Key Points • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinica