Evaluation of Eye Lens Dose Reduction Technics in Head CT

The purpose of this study is to find the best protocol to reduce the X-ray dose to the eye lens during head diagnostic computed tomography (CT) without decreasing image quality in the organs of interest according to the type of scanner. The lens of the eye is one of radiosensitive tissues in the body. Radiation induced cataract has been demonstrated among staff involved in interventional procedures using X-rays. This study compares the absorbed dose and image quality of several dose reduction technics to the eye lens during head CT exam namely bismuth shielding, organ-based dose modulation, tube current modulation, tube voltage modulation and the combination of a number of these techniques. Compared to the reference scan (Fixed tube current without bismuth shielding), the dose to the eye lens was reduced by 29.91% with bismuth shield, 14.55% with tube current modulation, 37.76% with tube current modulation and bismuth shield. The combination of organ-based dose modulation with tube voltage modulation reduced the dose by 44.93% that of tube current modulation with tube voltage modulation reduced by 19.03% and that of tube current modulation with tube voltage modulation and shield by 46.73%. The combination of organ-based dose with tube voltage modulation provided superior image quality than that of tube current modulation with tube voltage modulation and shield while similarly reducing dose to the eye lens.

Image quality assessment of deep learning image reconstruction in computed tomography using tube current modulation: a phantom study

The novel deep learning image reconstruction (DLIR) is known to change its image quality characteristics according to object contrast and image noise. In clinical practice, computed tomography (CT) image noise is usually controlled by tube current modulation (TCM) to accommodate changes in object size. This study aimed to evaluate the image quality characteristics of DLIR for different object sizes when in-plane noise is controlled by TCM. We used Mercury 4.0 phantoms with different object sizes. Phantom image acquisition was performed on a GE Revolution CT system to investigate the impact of the DLIR algorithm compared to standard reconstructions: filtered back projection (FBP) and hybrid iterative reconstruction (hybrid-IR). For image quality evaluation, the noise power spectrum (NPS), task-based transfer function (TTF), and detectability index (d') were determined. The NPS of DLIR was very similar to that of FBP, and the information in the high-frequency region was maintained. In terms of TTF, DLIR showed higher resolution than hybrid-IR at low- to medium-contrast (Δ50, Δ90HU), but not necessarily higher than FBP. At the simulated contrast and lesion size, DLIR showed higher detectability than hybrid-IR, regardless of the phantom size. In this study, we evaluated a novel DLIR algorithm by reproducing clinical behaviors. The findings indicate that DLIR produces higher image quality than hybrid-IR regardless of the phantom size, although it depends on the reconstruction strength.

A phantom study to optimise the automatic tube current modulation for chest CT in COVID-19

On March 11, 2020, the World Health Organization declared the coronavirus disease 2019 (COVID-19) pandemic. The expert organisations recommend more cautious use of thoracic computed tomography (CT), opting for low-dose protocols. We aimed at determining a threshold value of automatic tube current modulation noise index below which there is a chance to miss an onset of ground-glass opacities (GGO) in COVID-19. A team of radiologists and medical physicists performed 25 phantom CT studies using different automatic tube current modulation settings (SUREExposure3D technology). We then conducted a retrospective evaluation of the chest CT images from 22 patients with COVID-19 and calculated the density difference between the GGO and unaffected tissue. Finally, the results were matched to the phantom study results to determine the minimum noise index threshold value. The minimum density difference at the onset of COVID-19 was 252 HU (p < 0.001). This was found to correspond to the SUREExposure 3D noise index of 36. We established the noise index threshold of 36 for the Canon scanner without iterative reconstructions, allowing for a decrease in the dose-length product by 80%. The proposed protocol needs to be validated in a prospective study.