Prof. Tiezhi Zhang Profile

Prof. Tiezhi Zhang

Professor at Washington Univ School of Medicine in St. Louis

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Publications (5)

Proceedings Article | 1 April 2024 Poster + Paper

Dynamic x-ray flux modulation of inverse-geometry CT

Liuxing Shen, Haydon Windsor, Shuang Zhou, Hao Jiang, Tiezhi Zhang

Proceedings Volume 12925, 1292540 (2024) https://doi.org/10.1117/12.3006916

KEYWORDS: X-rays, Modulation, X-ray sources, Power supplies, Computed tomography, X-ray imaging, X-ray computed tomography, Tungsten, Switching, Prototyping

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Proceedings Article | 7 April 2023 Poster + Paper

In vivo proton range validation using pseudo proton radiography

Chih-Wei Chang, Shuang Zhou, Yuan Gao, Liyong Lin, Tian Liu, Jeffrey Bradley, Tiezhi Zhang, Jun Zhou, Xiaofeng Yang

Proceedings Volume 12463, 124632K (2023) https://doi.org/10.1117/12.2653669

KEYWORDS: Proton radiography, Computed tomography, Physics, In vivo imaging, Machine learning, Proton therapy, Biology, Monte Carlo methods, Medicine, Material characterization

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The current clinical practice for Monte Carlo (MC) treatment planning reserves a 3.5% margin to compensate for proton range uncertainty. Additionally, patient positional uncertainty is typically 3-5 mm for proton craniospinal irradiation (CSI) treatment planning. These two uncertainties compromise the sparing of spine vertebrae in proton CSI patients. Computer tomography (CT) material characterization contributes approximately 2.5% proton range uncertainty. Multiple CT-tomaterial conversion methods have been investigated using dual-energy CT or magnetic resonance imaging to improve the range uncertainty. However, there is a lack of experimental data to validate the credibility of those material characterization models. We aim to develop an in vivo proton range method using pseudo proton radiography to validate imaging-based material characterization models consistently. Proton radiography techniques, such as proton water equivalent thickness (WET) and dose maps, were used to evaluate the in vivo proton range accuracy. Anteroposterior proton beams were penetrated through an anthropomorphic phantom. Then the exit doses were measured from proton radiography imaging. The validation experiment applied a newly designed multi-layer strip ionization chamber (MLSIC) for the first time to perform four-dimensional (4D) measurement for depth doses from 625 proton spots in two minutes. The depth doses of each spot were post-processed into WET imaging. A MatriXX PT was applied for 2D measurement from 19x19 cm2 proton fields. We compared the performance of the empirical DECT model and physics-informed machine learning (PIML) models for material conversion. The results indicated that the PIML-based material characteristic method generated more accurate WET and dose imaging using DECT compared to conventional machine learning and empirical material inference methods. The proposed in vivo proton range validation method can be used to quantify the credibility of DECT-based material conversion models for proton range enhancement. The method can potentially provide in-room patient anatomy changes to accomplish online adaption for modification. This technique will significantly benefit proton flash therapy, which demands high accuracy.

Proceedings Article | 15 February 2021 Presentation + Paper

Accurate characterization of metal implants and human materials using novel proton counting detector for Monte Carlo dose calculation in proton therapy

Serdar Charyyev, Chih-Wei Chang, Joseph Harms, Cristina Oancea, S. Tim Yoon, Xiaofeng Yang, Tiezhi Zhang, Jun Zhou, Shuai Leng, Liyong Lin

Proceedings Volume 11595, 115950B (2021) https://doi.org/10.1117/12.2581751

KEYWORDS: Metals, Sensors, Monte Carlo methods, Spine, Tissues, Spectral imaging cameras, Particles, Aluminum

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Owing to poor characterization of implant and adjacent human tissues, the presence of metal implants has been shown to be a risk factor for clinical results for proton therapy. In this project we have developed a way of characterizing implant and human materials in terms of water-equivalent thicknesses (WET) and relative stopping power (RSP) using a novel proton counting detector. We tracked each proton using a fast spectral imaging camera AdvaPIX-TPX3 which operated in energy mode measures collected energy per-voxel to derive the deposited energy along the particle track across the voxelated sensor. We considered three scenarios: sampling of WET of a CIRS M701 Adult Phantom (CMAP) at different locations; measurements of energy perturbations in the CMAP implanted with metal rods; sampling of WET of a more complex spine phantom. WET and RSP information were extracted from energy spectra at position along the central axis by using the shift in the most probable energy (MPE) from the reference energy (either initial incident energy or energy without a metal implant). Measurements were compared to TOPAS simulation results. Measured WET of the CMAP ranged from 18.63 to 25.23 cm depending on the location of the sampling which agreed with TOPAS simulation results within 1.6%. The RSPs of metals from CMAP perturbation measurements were determined as 1.97, 2.98, and 5.44 for Al, Ti and CoCr, respectively, which agreed with TOPAS within 2.3%. RSPs for material composition of a more complex spine phantom yielded 1.096, 1.309 and 1.001 for Acrylic, PEEK and PVC, respectively. In summary, this work has shown a method to accurately characterize RSPs of metal and human materials of CMAP implanted with metals and a complex spine phantom. Using the data obtained by the proposed method, it may be possible to validate RSP maps provided by conventional photon computed tomography techniques. Owing to poor characterization of implant and adjacent human tissues, the presence of metal implants has been shown to be a risk factor for clinical results for proton therapy. In this project we have developed a way of characterizing implant and human materials in terms of water-equivalent thicknesses (WET) and relative stopping power (RSP) using a novel proton counting detector. We tracked each proton using a fast spectral imaging camera AdvaPIX-TPX3 which operated in energy mode measures collected energy per-voxel to derive the deposited energy along the particle track across the voxelated sensor. We considered three scenarios: sampling of WET of a CIRS M701 Adult Phantom (CMAP) at different locations; measurements of energy perturbations in the CMAP implanted with metal rods; sampling of WET of a more complex spine phantom. WET and RSP information were extracted from energy spectra at position along the central axis by using the shift in the most probable energy (MPE) from the reference energy (either initial incident energy or energy without a metal implant). Measurements were compared to TOPAS simulation results. Measured WET of the CMAP ranged from 18.63 to 25.23 cm depending on the location of the sampling which agreed with TOPAS simulation results within 1.6%. The RSPs of metals from CMAP perturbation measurements were determined as 1.97, 2.98, and 5.44 for Al, Ti and CoCr, respectively, which agreed with TOPAS within 2.3%. RSPs for material composition of a more complex spine phantom yielded 1.096, 1.309 and 1.001 for Acrylic, PEEK and PVC, respectively. In summary, this work has shown a method to accurately characterize RSPs of metal and human materials of CMAP implanted with metals and a complex spine phantom. Using the data obtained by the proposed method, it may be possible to validate RSP maps provided by conventional photon computed tomography techniques.

Proceedings Article | 15 February 2021 Poster + Presentation

Radiographic imaging with a linear x-ray source and multi-row detector

Qinghao Chen, Shuang Zhou, Yuewen Tan, Tiezhi Zhang

Proceedings Volume 11595, 1159537 (2021) https://doi.org/10.1117/12.2582159

KEYWORDS: Sensors, X-ray sources, Photon counting, Head, Fluctuations and noise, 3D image reconstruction, X-rays, X-ray detectors, Stereoscopy, Radiography

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Proceedings Article | 15 February 2021 Poster + Presentation

Quasi-monochromatic x-ray source using reflective thin-film target – a simulation study

Yuewen Tan, Qinghao Chen, Shuang Zhou, Tiezhi Zhang

Proceedings Volume 11595, 115953A (2021) https://doi.org/10.1117/12.2580609

KEYWORDS: Thin films, Monte Carlo methods, X-ray sources, Reflectivity, Diamond, X-rays, Electrons, Ytterbium, X-ray imaging, Tungsten

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