ESTRO 37 Abstract book

S1145

ESTRO 37

Results The omission of zinc in the base material doublet resulted in larger errors in both the linear attenuation coefficient (LAC) and the mass energy absorption coefficient (MEAC) for the calculi and the prostate tissue outside the calculi. For instance the error in MEAC in the calculi was increased from 3.9% to 6.6% at 30 keV when Zn was present. In the prostate tissue outside the calculi the increase in error was not so strong.

Conclusion We created the contrast medium extraction method and it is expected to extract only the region of the contrast medium from patient CT image using it. EP-2082 The effect of zinc in prostatic calculi on the accuracy of the MBIR algorithm DIRA A. Malusek 1 , M. Magnusson 2 , M. Sandborg 1 , G. Alm Carlsson 1 , A. Carlsson Tedgren 1 1 Linköping University, Radiological Sciences, Linköping, Sweden 2 Linköping University, Electrical Engineering, Linköping, Sweden Purpose or Objective Absorbed dose distributions in brachytherapy of prostate with low energy photons are affected by prostate calcifications. The calcifications shield the photon beams and may produce cold spots in spatial distributions of absorbed dose. Unlike breast calcifications, where the high atomic number elements are mainly represented by calcium, prostate calcifications may also contain several percent of zinc and smaller amount of strontium and iron. Some modern radiation treatment planning (RTP) systems can, in principle, take these inhomogeneities into account, nevertheless they need data from imagining systems like CT characterizing the elemental composition of these inhomogeneities. Model-based iterative reconstruction (MBIR) algorithms in dual-energy and spectral CT can improve the accuracy of the predicted elemental composition compared to the currently used single-energy CT. Of interest is, how much should these algorithms be fine-tuned to predict the elemental composition for the RTP of prostate. The purpose of this work is to estimate the effect of zinc in prostatic calculi on the accuracy of elemental composition determined by the MBIR algorithm DIRA (A model-based iterative reconstruction algorithm DIRA using patient-specific tissue classification via DECT for improved quantitative CT in dose planning, Med. Phys. The accuracy of elemental compositions and mass densities of tissues predicted by DIRA was compared using computer simulations for two configurations: (i) a breast calcification according to ICRU report 46 and (ii) a calcification containing 8% of Zn; this value was obtained by the micro-PIXE method. In both cases, the material of the prostate was decomposed using the two-material decomposition method inside the iterative loop of DIRA to tabulated prostate tissue and calcium. Such material doublet was well suited for breast calcifications used in earlier studies. The calcifications were inserted to a mathematical anthropomorphic phantom derived from the ICRP 110 voxel phantom, where the size of prostate, bladder and rectum were adjusted according to a clinical case. Noise in projection data was not simulated. 44, 2017, 2345–2357). Material and Methods

Conclusion Errors caused by the omission of zinc in the two-material decomposition of DIRA were present, nevertheless they did not break the algorithm. A more accurate material decomposition method of the prostate is desirable, nevertheless the tabulated prostate tissue and calcium doublet may be used in the meantime. EP-2083 The Study of effect induced by respiration on CT radiomic feature extraction Y. Lu 1,2 , G. Gong 1 , Y. Yin 1 1 Shandong Cancer Hospital Affiliated to Shandong University, Department of Radiation Oncology, Ji'nan, China 2 Shandong Normal University, School of Physics and Electronics, Ji'nan, China Purpose or Objective To assess the effects of respiration on CT radiomic feature extraction based on four-dimensional computed Thirty-four thoracic cancer patients undergoing 4D-CT were studied retrospectively. 4D-CT scans were sorted into 10 phases according to breath cycle, i.e., 0%, 10%......90%. The 0% (end of inspiration), 20% (middle of expiration), 50% (end of expiration), and 70% (middle of inspiration) phases were selected. The left lung and right lung were selected as regions of interest (ROIs) for feature extraction. Hierarchical cluster methods were used to screen features, compare the features of different inflation and respiration states of the lung tissue, and quantitatively analyze the influence of respiration on radiomic feature extraction. Results Eighty-seven features were extracted from 4 phases of the two lungs, and 10 non-redundant features were selected after hierarchical clustering. The number of features that differed significantly between the 0% and 50% phases was 7 and 4 for left and right lungs, respectively, there were 4 common features and 3 uncommon features. The number of features that tomography (4D-CT). Material and Methods