The Potential Role of Grid-Like Software in Bedside Chest Radiography in Improving Image Quality and Dose Reduction: An Observer Preference Study

Abstract

ObjectiveTo compare the observer preference of image quality and radiation dose between non-grid, grid-like, and grid images.Materials and MethodsEach of the 38 patients underwent bedside chest radiography with and without a grid. A grid-like image was generated from a non-grid image using SimGrid software (Samsung Electronics Co. Ltd.) employing deep-learning-based scatter correction technology. Two readers recorded the preference for 10 anatomic landmarks and the overall appearance on a five-point scale for a pair of non-grid and grid-like images, and a pair of grid-like and grid images, respectively, which were randomly presented. The dose area product (DAP) was also recorded. Wilcoxon's rank sum test was used to assess the significance of preference.ResultsBoth readers preferred grid-like images to non-grid images significantly (p < 0.001); with a significant difference in terms of the preference for grid images to grid-like images (p = 0.317, 0.034, respectively). In terms of anatomic landmarks, both readers preferred grid-like images to non-grid images (p < 0.05). No significant differences existed between grid-like and grid images except for the preference for grid images in proximal airways by two readers, and in retrocardiac lung and thoracic spine by one reader. The median DAP were 1.48 (range, 1.37–2.17) dGy*cm2 in grid images and 1.22 (range, 1.11–1.78) dGy*cm2 in grid-like images with a significant difference (p < 0.001).ConclusionThe SimGrid software significantly improved the image quality of non-grid images to a level comparable to that of grid images with a relatively lower level of radiation exposure.

Improvement of image quality applying iterative scatter correction for grid-less skeletal radiography in trauma room setting

“…Software-based scatter correction is increasingly under review, with current publications for plain chest imaging (5–7,24), mammography (25), cone beam CT (26), and veterinary medicine (27). Another recent study evaluated ISC for skeletal radiography (8), but only for pelvic and spinal imaging and solely under experimental conditions with body donors.…”

Clinical Implementation of Deep Learning in Thoracic Radiology: Potential Applications and Challenges

“…The DL may also contribute to the improvement of CXR image quality. In a study by Ahn et al (116), DLbased software could generate CXR images simulating those obtained with grids from those obtained without the utilization of grids. The subjective image quality and radiologists' preference improved in those generated gridlike images, without the need for an additional radiation dose because of the utilization of grids.…”

Contemporary research in digital radiography

“…Evaluation of this technology has shown that a combination of the image scatter correction algorithms, and an increase in SNR results in significant dose reductions (20-50%). 5 The increased SNR due to the removal of the grid results in a higher EI. Again, this method of optimisation will not work if the EI is constant before and after the optimisation process.…”