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Low-dose whole-body CT using deep learning image reconstruction: image quality and lesion detection
- Source :
- Br J Radiol
- Publication Year :
- 2021
- Publisher :
- British Institute of Radiology, 2021.
-
Abstract
- Objectives: To evaluate image quality and lesion detection capabilities of low-dose (LD) portal venous phase whole-body computed tomography (CT) using deep learning image reconstruction (DLIR). Methods: The study cohort of 59 consecutive patients (mean age, 67.2 years) who underwent whole-body LD CT and a prior standard-dose (SD) CT reconstructed with hybrid iterative reconstruction (SD-IR) within one year for surveillance of malignancy were assessed. The LD CT images were reconstructed with hybrid iterative reconstruction of 40% (LD-IR) and DLIR (LD-DLIR). The radiologists independently evaluated image quality (5-point scale) and lesion detection. Attenuation values in Hounsfield units (HU) of the liver, pancreas, spleen, abdominal aorta, and portal vein; the background noise and signal-to-noise ratio (SNR) of the liver, pancreas, and spleen were calculated. Qualitative and quantitative parameters were compared between the SD-IR, LD-IR, and LD-DLIR images. The CT dose-index volumes (CTDIvol) and dose-length product (DLP) were compared between SD and LD scans. Results: The image quality and lesion detection rate of the LD-DLIR was comparable to the SD-IR. The image quality was significantly better in SD-IR than in LD-IR (p < 0.017). The attenuation values of all anatomical structures were comparable between the SD-IR and LD-DLIR (p = 0.28–0.96). However, background noise was significantly lower in the LD-DLIR (p < 0.001) and resulted in improved SNRs (p < 0.001) compared to the SD-IR and LD-IR images. The mean CTDIvol and DLP were significantly lower in the LD (2.9 mGy and 216.2 mGy•cm) than in the SD (13.5 mGy and 1011.6 mGy•cm) (p < 0.0001). Conclusion: LD CT images reconstructed with DLIR enable radiation dose reduction of >75% while maintaining image quality and lesion detection rate and superior SNR in comparison to SD-IR. Advances in knowledge: Deep learning image reconstruction algorithm enables around 80% reduction in radiation dose while maintaining the image quality and lesion detection compared to standard-dose whole-body CT.
- Subjects :
- Adult
Male
Quality Control
Image quality
Contrast Media
Computed tomography
Whole body ct
Iterative reconstruction
Signal-To-Noise Ratio
Radiation Dosage
Portal venous phase
030218 nuclear medicine & medical imaging
03 medical and health sciences
Deep Learning
0302 clinical medicine
Neoplasms
Humans
Medicine
Whole Body Imaging
Radiology, Nuclear Medicine and imaging
Postoperative Period
Prospective Studies
Aged
Aged, 80 and over
Full Paper
medicine.diagnostic_test
Lesion detection
business.industry
Deep learning
Low dose
General Medicine
Middle Aged
030220 oncology & carcinogenesis
Radiographic Image Interpretation, Computer-Assisted
Female
Artificial intelligence
Tomography, X-Ray Computed
business
Nuclear medicine
Algorithms
Subjects
Details
- ISSN :
- 1748880X and 00071285
- Volume :
- 94
- Database :
- OpenAIRE
- Journal :
- The British Journal of Radiology
- Accession number :
- edsair.doi.dedup.....a64a3fb6296f40d359a6ea1d3e635fc1
- Full Text :
- https://doi.org/10.1259/bjr.20201329