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.Assuming MC as the algorithm of highest accuracy it is shown that based on selected dose parameters, RT slightly underestimates the dose in homogeneous regions and overestimates in heterogeneous regions. In addition, deviations occur due to tumor size rendering large differences for small tumors. We conclude that dose prescriptions for radiotherapy treatments should differentiate between RT and MC calculation algorithm. This is especially important for small tumors in heterogeneous body regions.
1 September 2019 in Current Directions in Biomedical Engineering
In this research computer tomography (CT) iterative reconstruction (IR) algorithms are investigated, specifically the impact of their statistical and model-based strength on image quality in low-dose lung screening CT protocols in comparison to filtered back projection (FBP). It has been probed whether statistical, model-based IR in conjunction with low-dose, and ultra-low-dose protocols are suitable for lungcancer screening. To this end, artificial lung nodules shaped as spheres and spicules made from material with calibrated Hounsfield units (HU) were attached on marked positions in the lung structure of an anthropomorphic phantom. Nodule positions were selected by distinguished radiologists. The phantom with nodules was scanned on a CT Scanner using standard high contrast (SHC), low-dose (LD) and ultra low-dose (ULD) protocol. For reconstruction FBP and the IR algorithm ADMIRE at three different strength levels were used. Volume CT dose index (CTDIvol) and dose-length product were recorded. Radiologists assessed subjective image quality using a six-point Likert scale by reading all image series in terms detectability of lung nodules. As a measurable objective image quality parameter signal-to-noise ratios (SNR) were investigated. The CTDIvol decreases by more than 70% for all protocols and nodules compared to diagnostic reference value for chest CT (p<0.00001). The evaluation of image quality parameters, i.e. SNR, indicates that LD and ULD protocols in conjunction with IR assert high quality lung-nodule detection. The results reveal that IR algorithm with moderate to high strength is an indispensable alternative to FBP in low-dose scanning, thus, potentially suitable for lung-tumour screening.
1 September 2016 in Current Directions in Biomedical Engineering
Metallic implants in magnetic resonance imaging (MRI) are a potential safety risk since the energy absorption may increase temperature of the surrounding tissue. The temperature rise is highly dependent on implant size. Numerical examinations can be used to calculate the energy absorption in terms of the specific absorption rate (SAR) induced by MRI on orthopaedic implants. This research presents the impact of titanium osteosynthesis spine implants, called spondylodesis, deduced by numerical examinations of energy absorption in simplified spondylodesis models placed in 1.5 T and 3.0 T MRI body coils. The implants are modelled along with a spine model consisting of vertebrae and disci intervertebrales thus extending previous investigations [1], [2]. Increased SAR values are observed at the ends of long implants, while at the center SAR is significantly lower. Sufficiently short implants show increased SAR along the complete length of the implant. A careful data analysis reveals that the particular anatomy, i.e. vertebrae and disci intervertebrales, has a significant effect on SAR. On top of SAR profile due to the implant length, considerable SAR variations at small scale are observed, e.g. SAR values at vertebra are higher than at disc positions.
The aim of this study is to examine the precision of semi-automatic, conventional and automatic volumetry tools for pulmonary nodules in chest CT with phantom N1 LUNGMAN. The phantom is a life-size anatomical chest model with pulmonary nodules representing solid and subsolid metastases. Gross tumor volumes (GTVis) were contoured using various approaches: manually (0); as a means of semi-automated, conventional contouring with (I) adaptive-brush function; (II) flood-fill function; and (III) image-thresholding function. Furthermore, a deep-learning algorithm for automatic contouring was applied (IV). An intermodality comparison of the above-mentioned strategies for contouring GTVis was performed. For the mean GTVref (standard deviation (SD)), the interquartile range (IQR)) was 0.68 mL (0.33; 0.34–1.1). GTV segmentation was distributed as follows: (I) 0.61 mL (0.27; 0.36–0.92); (II) 0.41 mL (0.28; 0.23–0.63); (III) 0.65 mL (0.35; 0.32–0.90); and (IV) 0.61 mL (0.29; 0.33–0.95). GTVref was found to be significantly correlated with GTVis (I) p < 0.001, r = 0.989 (III) p = 0.001, r = 0.916, and (IV) p < 0.001, r = 0.986, but not with (II) p = 0.091, r = 0.595. The Sørensen–Dice indices for the semi-automatic tools were 0.74 (I), 0.57 (II) and 0.71 (III). For the semi-automatic, conventional segmentation tools evaluated, the adaptive-brush function (I) performed closest to the reference standard (0). The automatic deep learning tool (IV) showed high performance for auto-segmentation and was close to the reference standard. For high precision radiation therapy, visual control, and, where necessary, manual correction, are mandatory for all evaluated tools.
1 September 2018 in Current Directions in Biomedical Engineering
We report on investigations that illustrate the interaction between the specific immune system and a young avascular tumor growing due to a diffusive nutrient supply. We formulate a hybrid cellular automata-partial differential equation (CA-PDE) model which includes cell cycle dynamics and allows for tracking the spatial and temporal evolution of this elaborate biological system. We present results of two dimensional numerical simulations that, specifically in this work, include special cases of the spherical and papillary tumor growth, the infiltration of immune system cells into the tumor and the escape of tumor cells from the regime of the immune cells.