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A phantom study on the applicability of a detectability index in ultrasound imaging
Summary
Phantom experiments evaluated whether detectability indices derived from Linear System Theory could assess image quality in medical ultrasound, measuring modular transfer function and noise power spectrum across four phantoms of varying composition.
The assessment of clinical image quality on ultrasound is currently often subjective . While image quality factors such as contrast response or depth of penetration can be evaluated semi-automatically, the evaluation of high contrast resolution requires test objects with specific inserts. The aim of this study was to evaluate the applicability of image quality metrics which were derived from Linear System Theory in the field of medical ultrasound imaging. Modular Transfer Function (MTF) and noise power spectrum (NPS) were determined on four phantoms. Image quality was assessed using a detectability index for different diameters. One phantom contained a cylinder filled with water, which appears as a circle in the US images. The other three phantoms were homogeneous and consisted of three different materials all based on PVA (polyvinyl alcohol). The basic phantom material was a 10% PVA hydrogel. The two other materials included microplastic spheres and starch to increase echogeneity. NPS and the MTF were determined using MATLAB routines. Two linear US transducers with bandwidths of 2.4–10 and 4–15 MHz were used to show the dependence of the index on the principal frequency of the US wave. The results show that for all phantom materials and object sizes (1–10 mm diameter), the detectability indices decreased with increasing penetration depth (from 6 to 10 cm). In addition, all indices of the higher frequency transducer were higher than those of the lower frequency transducer. When comparing the different phantom materials (PVA, PVA with starch and PVA with microspheres), different mean pixel value (MPV) were found, while the standard deviations for the materials were similar. This enabled us to evaluate the detectability index at different signal-to-noise ratios (SNR). Measures of image homogeneity (coefficient of the variance and variation) showed no significant difference to a commercial phantom ( p -values ranging from 0.16 to 1, average p -value 0.5). These results suggest that the concept of a detectability index can also be applied to US imaging.
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