Image Comparative Assessment Using Iterative Reconstructions

作者：Varut Vardhanabhuti, Richard Riordan, Grant Mitchell, Christopher Hyde, Carl Roobottom · 发表于：Investigative Radiology · 年份：2013 · DOI：10.1097/rli.0000000000000017 · 被引用次数：72 · 研究领域：Radiation Dose and Imaging、Advanced X-ray and CT Imaging、Digital Radiography and Breast Imaging

OBJECTIVES: The objective of this study was to compare image quality (objective and subjective parameters) and confidence in lesion detection between 3 image reconstruction algorithms in computed tomographic (CT) examinations of the abdomen/pelvis. MATERIALS AND METHODS: This prospective institutional review board-approved study included 65 patients (mean [SD] age, 71.3 ± 9 years; mean [SD] body mass index, 24.4 [4.8] kg) who underwent routine CT examinations of the abdomen/pelvis followed immediately by 2 low-dose scans. Raw data sets were reconstructed by using filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and a model-based iterative reconstruction (MBIR). Measurements of objective noise and CT numbers were compared using repeated-measures analysis of variance. Six subjective image quality parameters were scored. Diagnostic confidence and accuracy in detection of various elementary lesions were performed. RESULTS: Objectively, mean image noise for MBIR was significantly superior at all dose levels (P < 0.001). Subjectively, standard-dose ASIR and low-dose MBIR scans were better than standard-dose FBP scan in all parameters assessed (P < 0.05). Low-dose MBIR scans were comparable with standard-dose ASIR scans in all parameters except at noise index of 70 (approximately 85% dose reduction), where, in this case, the detection of liver lesions less than 5 mm were rated inferior (P < 0.05) with diagnostic accuracy reducing to 77.4%. CONCLU...