Published in:
Open Access 01-08-2020 | Computed Tomography | Computed Tomography
3D printing of anatomically realistic phantoms with detection tasks to assess the diagnostic performance of CT images
Published in: European Radiology | Issue 8/2020
Login to get accessAbstract
Objectives
Detectability experiments performed to assess the diagnostic performance of computed tomography (CT) images should represent the clinical situation realistically. The purpose was to develop anatomically realistic phantoms with low-contrast lesions for detectability experiments.
Methods
Low-contrast lesions were digitally inserted into a neck CT image of a patient. The original and the manipulated CT images were used to create five phantoms: four phantoms with lesions of 10, 20, 30, and 40 HU contrast and one phantom without any lesion. Radiopaque 3D printing with potassium-iodide-doped ink (600 mg/mL) was used. The phantoms were scanned with different CT settings. Lesion contrast was analyzed using HU measurement. A 2-alternative forced choice experiment was performed with seven radiologists to study the impact of lesion contrast on detection accuracy and reader confidence (1 = lowest, 5 = highest).
Results
The phantoms reproduced patient size, shape, and anatomy. Mean ± SD contrast values of the low-contrast lesions were 9.7 ± 1.2, 18.2 ± 2, 30.2 ± 2.7, and 37.7 ± 3.1 HU for the 10, 20, 30, and 40 HU contrast lesions, respectively. Mean ± SD detection accuracy and confidence values were not significantly different for 10 and 20 HU lesion contrast (82.1 ± 6.3% vs. 83.9 ± 9.4%, p = 0.863 and 1.7 ± 0.4 vs. 1.8 ± 0.5, p = 0.159). They increased to 95 ± 5.7% and 2.6 ± 0.7 for 30 HU lesion contrast and 99.5 ± 0.9% and 3.8 ± 0.7 for 40 HU lesion contrast (p < 0.005).
Conclusions
A CT image was manipulated to produce anatomically realistic phantoms for low-contrast detectability experiments. The phantoms and our initial experiments provide a groundwork for the assessment of CT image quality in a clinical context.
Key Points
• Phantoms generated from manipulated CT images provide patient anatomy and can be used for detection tasks to evaluate the diagnostic performance of CT images.
• Radiologists are unconfident and unreliable in detecting hypodense lesions of 20 HU contrast and less in an anatomical neck background.
• Detectability experiments with anatomically realistic phantoms can assess CT image quality in a clinical context.