Deep learning image reconstruction algorithm for pancreatic protocol dual-energy computed tomography: image quality and quantification of iodine concentration
| Autor: | Hiroki Kato, Fumihiko Nakamura, Nobuyuki Kawai, Takayuki Mori, Shoma Nagata, Ryosuke Suzuki, Yoshifumi Noda, Fuminori Hyodo, Toshiharu Miyoshi, Masayuki Matsuo, Fumiya Kitahara |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Image quality Coefficient of variation chemistry.chemical_element Iterative reconstruction Iodine Radiation Dosage Standard deviation 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Deep Learning medicine Image Processing Computer-Assisted Humans Radiology Nuclear Medicine and imaging Prospective Studies Pancreas business.industry Ultrasound Dual-Energy Computed Tomography General Medicine medicine.anatomical_structure chemistry 030220 oncology & carcinogenesis Radiographic Image Interpretation Computer-Assisted Radiology business Tomography X-Ray Computed Algorithms |
| Zdroj: | European radiology. 32(1) |
| ISSN: | 1432-1084 |
| Popis: | To evaluate the image quality and iodine concentration (IC) measurements in pancreatic protocol dual-energy computed tomography (DECT) reconstructed using deep learning image reconstruction (DLIR) and compare them with those of images reconstructed using hybrid iterative reconstruction (IR).The local institutional review board approved this prospective study. Written informed consent was obtained from all participants. Thirty consecutive participants with pancreatic cancer (PC) underwent pancreatic protocol DECT for initial evaluation. DECT data were reconstructed at 70 keV using 40% adaptive statistical iterative reconstruction-Veo (hybrid-IR) and DLIR at medium and high levels (DLIR-M and DLIR-H, respectively). The diagnostic acceptability and conspicuity of PC were qualitatively assessed using a 5-point scale. IC values of the abdominal aorta, pancreas, PC, liver, and portal vein; standard deviation (SD); and coefficient of variation (CV) were calculated. Qualitative and quantitative parameters were compared between the hybrid-IR, DLIR-M, and DLIR-H groups.The diagnostic acceptability and conspicuity of PC were significantly better in the DLIR-M group compared with those in the other groups (p.001-.001). The IC values of the anatomical structures were almost comparable between the three groups (p = .001-.9). The SD of IC values was significantly lower in the DLIR-H group (p.001) and resulted in the lowest CV (p.001-.002) compared with those in the hybrid-IR and DLIR-M groups.DLIR could significantly improve image quality and reduce the variability of IC values than could hybrid-IR.Image quality and conspicuity of pancreatic cancer were the best in DLIR-M. DLIR significantly reduced background noise and improved SNR and CNR. The variability of iodine concentration was reduced in DLIR. |
| Databáze: | OpenAIRE |
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