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Hierarchical Clustering Based Atomic Composition Extraction From Dual Energy CT for Proton Monte Carlo Simulation

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J Zou

W Zou*, L Yin , J Luna Castaneda , S O'Reilly , Y Xie , Y Xiao , E Diffenderfer , L Dong , B Teo , Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA


SU-K-605-3 (Sunday, July 30, 2017) 4:00 PM - 6:00 PM Room: 605

Purpose: Proton Monte Carlo (MC) simulation models the physics processes between protons and medium and yields more accurate dose calculation compared to proton stopping power based pencil beam convolution algorithm. MC simulation is also essential for prompt gamma and proton-induced isotope production for in-vivo proton range detection. It requires the tissue element composition to be determined from patient CT images. We propose a new hierarchical clustering based approach in extracting the atomic composition in human tissues from Dual Energy CT (DECT) scans.

Methods: 70 published human tissues samples were used for the theoretical study of this approach. The tissues were first clustered by their composition similarities using hierarchical clustering. For each tissue cluster, three base tissues were randomly selected. Other tissues in this cluster were the weighted sum of these base tissues, where the weights were derived by fitting the attenuation coefficients calculated from DECT X-ray spectrums. The derived tissue atomic compositions and effective atomic number were compared with the ground truth.

Results: The soft tissues and bones were clustered into 8 subcategories, with cophenetic correlation 0.895 and inconsistency coefficient (IC) > 1.15 (ICmax = 1.1547). The mean and standard deviations of the difference in the derived atomic compositions and the ground truth for H, C, N, O, Ca, P were 0.05% (±0.07%), 1.56%(±2.02%), 0.61%(±0.55%), 1.81%(±2.37%), 0.03% (±0.07%), 0.13% (±0.16%), respectively. The Zeff from derived elemental composition was within 0.04 from the true values.

Conclusion: We have investigated a new approach to extract the atomic composition from DECT scans. The accuracy of the extraction was demonstrated for published tissue samples. We plan to validate this approach with additional DECT scans of animal tissues and compare the Zeff derived from this method against measurements from proton beam irradiations.

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