Open AccessDevelopment of a method to create uniform phantoms for task‐based assessment of CT image quality
Author(s) -
Conzelmann Juliane,
Schwarz Felix Benjamin,
Hamm Bernd,
Scheel Michael,
Jahnke Paul
Publication year - 2020
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.12974
Subject(s) - imaging phantom , image quality , contrast (vision) , nuclear medicine , materials science , lesion , polymethyl methacrylate , biomedical engineering , confidence interval , medicine , optics , computer science , physics , artificial intelligence , image (mathematics) , surgery , composite material , polymer
Purpose To develop a customized method to produce uniform phantoms for task‐based assessment of CT image quality. Methods Contrasts between polymethyl methacrylate (PMMA) and fructose solutions of different concentrations (240, 250, 260, 280, 290, 300, 310, 320, 330, and 340 mg/mL) were calculated. A phantom was produced by laser cutting PMMA slabs to the shape of a patient’s neck. An opening of 10 mm diameter was cut into the left parapharyngeal space. An angioplasty balloon was inserted and filled with the fructose solutions to simulate low‐contrast lesions. The phantom was scanned with six tube currents. Images were reconstructed with filtered back projection (FBP) and adaptive iterative dose reduction 3D (AIDR 3D). Calculated and measured contrasts were compared. The phantom was evaluated in a detectability experiment using images with 4 and 20 HU lesion contrast. Results Low‐contrast lesions of 4, 9, 11, 13, 18, 20, 24, 30, 35, and 37 HU contrast were simulated. Calculated and measured contrasts correlated excellently (r = 0.998; 95% confidence interval: 0.991 to 1). The mean ± SD difference was 0.41 ± 2.32 HU ( P < 0.0001). Detection accuracy and reader confidence were 62.9 ± 18.2% and 1.58 ± 0.68 for 4 HU lesion contrast and 99.6 ± 1.3% and 4.27 ± 0.92 for 20 HU lesion contrast ( P < 0.0001), confirming that the method produced lesions at the threshold of detectability. Conclusion A cost‐effective and flexible approach was developed to create uniform phantoms with low‐contrast signals. The method should facilitate access to customized phantoms for task‐based image quality assessment.