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Accurate 3D Stopping-Power Ratio Estimation by Statistical Image Reconstruction From Dual Energy CT Sinogram Data Exported From a Commercial Multi-Slice CT Scanner

M Medrano1*, T Ge1, D Politte2, J Williamson2, T Zhao2, R Liu2, R Liao1, M Porras-Chaverri4, B Whiting3, J O'Sullivan 1 (1) Washington University in St. Louis, St. Louis, MO,(2) Washington University School of Medicine, St. Louis, MO, (3) University of Pittsburgh, Pittsburgh, PA, (4) Universidad de Costa Rica, San Jose, SJ

Presentations

(Sunday, 7/12/2020)   [Eastern Time (GMT-4)]

Room: AAPM ePoster Library

Purpose: studies have shown that our 2D Joint Statistical Image Reconstruction code using a basis-vector cross-section model (JSIR-BVM) exhibits better accuracy and noise suppression than competing dual-energy CT (DECT) methods for mapping proton stopping power ratio (SPR) on simulated and experimental axial sinograms. Towards making JSIR-BVM SPR mapping clinically feasible for proton-beam radiotherapy planning, we present our GPU-based 3D JSIR-BVM reconstruction and quantitatively assess its performance on simulated and experimentally acquired helical sinograms for phantom and patient scan subjects.


Methods: JSIR-BVM reconstructs 3D CT images of two basis-component weights from 90 kVp and 140 kVp helical transmission sinograms acquired sequentially on a Philips Big Bore scanner. These BVM weights were mapped to I-value and effective electron density, from which SPR maps were calculated via the Bethe-Bloch equation. Our synthetic and experimental phantoms contained fabricated samples of known atomic composition and density (hence known SPR) spanning the range of soft and bony tissue compositions.


Results: mean percentage SPR estimation errors averaged over the 12 inserts were 0.06% and 0.04% for 2D and 3D reconstructed SPR images, respectively. The RMS average errors were 0.08% for 2D and 0.07% for 3D reconstruction. The maximum percentage errors in SPR estimation were 0.16% for both 2D and 3D reconstructions. Our early experience with head and neck patient SPR reconstructions demonstrates reasonable (0-2%) errors with ICRU-46 tabulations. Concordance between 2D axial and 3D helical SPR maps is 0.02% and 0.006% in terms of mean and RMS average percentage error, respectively.


Conclusion: work demonstrates the feasibility of accurately reconstructing high-resolution 3D SPR maps from synthetic and experimentally acquired, spectral-hardening-uncompensated dual-energy helical sinograms exported from a commercial multislice CT scanner. Finally, for the first time, a principled dual-energy statistical image reconstruction, 3D JSIR-BVM, was able to reconstruct plausible 3D SPR volumes on clinically imaged human subjects.

Keywords

Helical CT, Reconstruction, Protons

Taxonomy

IM- CT: Quantitative imaging/analysis

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