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- Elektrotechnik und angewandte Naturwissenschaften (50) (entfernen)
Radiotherapy (RT) treatment planning is based on computed tomography (CT) images and traditionally uses the conventional Hounsfield unit (CHU) range. This HU range is suited for human tissue but inappropriate for metallic materials. To guarantee safety of patient carrying implants precise HU quantification is beneficial for accurate dose calculations in planning software. Some modern CT systems offer an extended HU range (EHU). This study focuses the suitability of these two HU ranges for the quantification of metallic components of active implantable medical devices (AIMD). CT acquisitions of various metallic and non-metallic materials aligned in a water phantom were investigated. From our acquisitions we calculated that materials with mass-density ρ > 3.0 g/cm3 cannot be represented in the CHU range. For these materials the EHU range could be used for accurate HU quantification. Since the EHU range does not effect the HU values for materials ρ < 3.0 g/cm3, it can be used as a standard for RT treatment planning for patient with and without implants.
Background: By reviewing image quality and diagnostic perception, the suitability of a statistical model-based iterative reconstruction algorithm in conjunction with low-dose computed tomography for lung cancer screening is investigated.
Methods: Artificial lung nodules shaped as spheres and spiculated spheres made from material with calibrated Hounsfield units were attached on marked positions in the lung structure of anthropomorphic phantoms. The phantoms were scanned using standard high contrast, and two low-dose computed tomography protocols: low-dose and ultra-low-dose. For the reconstruction, the filtered back projection and the iterative reconstruction algorithm ADMIRE at different strength levels (S1–S5) and the kernels Bl57, Br32, Br69 were used. Expert radiologists assessed image quality by performing 4-field-ranking tests and reading all image series to examine the aptitude for the detectability of lung nodules. Signal-to-noise ratio was investigated as objective image quality parameter.
Results: In ranking tests for lung foci detection expert radiologists prefer medium to high iterative reconstruction strength levels. For the standard clinical kernel Bl57 and varying phantom diameter, a noticeable preference for S4 was detected. Experienced radiologists graded filtered back projection reconstructed images with the highest perceptibility. Less experienced readers assessed filtered back projection and iterative reconstruction equally with the highest grades for the Bl57 kernel. Independently of the dose protocol, the signal-to-noise ratio increases with the iterative reconstruction strength level, specifically for Br69 and Bl57.
Conclusions: Subjective image perception does not significantly correlate with the experience of the radiologist, which presumably mirrors reader’s training and accustomed reading adjustments. Regarding signal-to-noise ratio, iterative reconstruction outperforms filtered back projection for spheres and spiculated spheres. Iterative reconstruction matters. It promises to be an alternative to filtered back projection allowing for lung-cancer screening at markedly decreased radiation exposure but comparable or even improved image quality.
This study investigates differences between treatment plans generated by Ray Tracing (RT) and Monte Carlo (MC) calculation algorithms in homogeneous and heterogeneous body regions. Particularly, we focus on the head and on the thorax, respectively, for robotic stereotactic radiotherapy and radiosurgery with Cyberknife. Radiation plans for tumors located in the head and in the thorax region have been calculated and compared to each other in 47 cases and several tumor types.
Stereotactic frame systems are widely used in neurosurgery. The accuracy of frame devices is considered as a gold standard to which the accuracy of new frameless stereotactic navigation systems is compared. The purpose of this study is to develop a general approach for the prediction of the application accuracy of stereotactic systems. The approach will be applied to the frame‐based biopsy performed with three frame devices: Leksell G, Cosman–Roberts–Wells (CRW), and Brown–Roberts–Wells (BRW). A work‐flow analysis will be carried out demonstrating that the accuracy relevant for a clinical application comprises several error sources including imaging, target and entry point selection, image to frame coordinates registration, and the setting of mechanical parameters of the frame. These error sources will be postulated to obey a Gaussian distribution probability density. The linear, i.e., Gaussian, error propagation, will be used to link all error contributions thus to calculate the cumulative accuracy of the frame used in the application. Although the Gaussian approach is an approximation, it allows for an analytical treatment of the accuracy. Both the accuracy at the target point and the accuracy of the probe needle guidance along the planned trajectory have been investigated. Of great significance is the relationship found between accuracy, pixel dimension, and image slice thickness, the latter being the dominant factor for slices of more than 1.5 mm thickness, yielding inaccuracies larger than 1.5 mm. For target points the predictions for the application accuracy have been compared to the results of measurements, showing good agreement with the experimental data.