Calculation of effective atomic numbers using a rational polynomial approximation method with a dual-energy X-ray imaging system.

The study aims to develop a rational polynomial approximation method for improving the accuracy of the effective atomic number calculation with a dual-energy X-ray imaging system. This method is based on a multi-materials calibration model with iterative optimization, which can improve the calculation accuracy of the effective atomic number by adding a rational term without increasing the computation time. The performance of the proposed rational polynomial approximation method is demonstrated and validated by both simulated and experimental studies. The twelve reference materials are used to establish the effective atomic number calibration model, and the value of the effective atomic numbers are between 5.444 and 22. For the accuracy of the effective atomic number calculation, the relative differences between calculated and experimental values are less than 8.5%for all sample cases in this study. The average calculation accuracy of the method proposed in this study can be improved by about 40%compared with the conventional polynomial approximation method. Additionally, experimental quality assurance phantom imaging result indicates that the proposed method is compliant with the international baggage inspection standards for detecting the explosives. Moreover, the experimental imaging results reveal that the difference of color between explosives and the surrounding materials is in significant contrast for the dual-energy image with the proposed method.

Application of tomosynthesis for vertebral compression fracture diagnosis and bone healing assessment in fracture liaison services.

Early identification of vertebral compression fractures (VCFs) is crucial for successful secondary fracture prevention. Tomosynthesis, a low-dose tomographic imaging technique, may facilitate the evaluation and long-term follow-up of VCFs in patients with osteoporosis. Herein, we compared the performances of plain radiography and tomosynthesis for VCF diagnosis and healing assessment in patients enrolled in fracture liaison services in our hospital. Forty-nine patients with new VCFs at the T10-L5 levels were prospectively recruited between August 2018 and May 2020; all patients underwent thoracolumbar plain radiography and tomosynthesis. We evaluated the accuracy of the VCF diagnosis, image quality, and VCFs healing process. Tomosynthesis identified 90 levels of VCF in 49 patients, while plain radiography revealed only 87.8% (79/90) of them. There were 44.9% (22/49) patients with neglected chronic VCFs as seen on tomosynthesis. Tomosynthesis images had improved VCF diagnostic accuracy up to 12.2% and showed significantly more anatomic details than plain radiography. For diagnosis of VCFs, the performance of plain radiographs was poorer than that of tomosynthesis images (plain radiographs: sensitivity 84%, specificity 93.5%, false positive rate 6.5%, and false negative rate 16%; tomosynthesis: sensitivity 93.2%, specificity 100%, false positive rate 0%, and false negative 6.8%), using magnetic resonance imaging (MRI) as gold standard. The Kappa coefficient between Tomosynthesis and MRI is 0.956 while between radiography and MRI is 0.704. Tomosynthesis showed significantly more anatomic details than plain radiography and all the examiners revealed a clear preference for tomosynthesis. Tomosynthesis scored 3.3 times higher on the fracture healing assessment at the 3-month follow-up than plain radiographs. Tomosynthesis is a promising tool for VCF screening and diagnosis in patients with osteoporosis and for monitoring fracture healing status at a low radiation dose and cost.

A geometric calibration method for the digital chest tomosynthesis with dual-axis scanning geometry.

The aim of this study was to develop a geometric calibration method capable of eliminating the reconstruction artifacts of geometric misalignments in a tomosynthesis prototype with dual-axis scanning geometry. The potential scenarios of geometric misalignments were demonstrated, and their effects on reconstructed images were also evaluated. This method was a phantom-based approach with iterative optimization, and the calibration phantom was designed for specific tomosynthesis scanning geometry. The phantom was used to calculate a set of geometric parameters from each projection, and these parameters were then used to evaluate the geometric misalignments of the dual-axis scanning-geometry prototype. The simulated results revealed that the extracted geometric parameters were similar to the input values and that the artifacts of reconstructed images were minimized due to geometric calibration. Additionally, experimental chest phantom imaging results also indicated that the artifacts of the reconstructed images were suppressed and that object structures were preserved through calibration. And the quantitative analysis result also indicated that the MTF can be further improved with the geometric calibration. All the simulated and experimental results demonstrated that this method is effective for tomosynthesis with dual-axis scanning geometry. Furthermore, this geometric calibration method can also be applied to other tomography imaging systems to reduce geometric misalignments and be used for different geometric calibration phantom configurations.