Peiyuan Guo, Simon Spindler, Michal Rawlik, Jincheng Lu, Longchao Men, Mingzhi Hong, Marco Stampanoni, Hongxia Yin, Yan Xu, Zhenchang Wang, Li Zhang, Zhentian Wang
{"title":"x射线暗场CT人体尺度肺成像的优化","authors":"Peiyuan Guo, Simon Spindler, Michal Rawlik, Jincheng Lu, Longchao Men, Mingzhi Hong, Marco Stampanoni, Hongxia Yin, Yan Xu, Zhenchang Wang, Li Zhang, Zhentian Wang","doi":"10.1002/mp.17630","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Background</h3>\n \n <p>X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.</p>\n </section>\n \n <section>\n \n <h3> Purpose</h3>\n \n <p>This study aimed to develop a thorough optimization method for human-scale dark-field lung CT and guide the system design.</p>\n </section>\n \n <section>\n \n <h3> Methods</h3>\n \n <p>We introduced a task-based metric formulated as the contrast-to-noise ratio (CNR) between normal and lesioned alveoli for system parameter optimization and designed a digital human-thorax phantom to fit the task of lung disease detection. Furthermore, a computational framework was developed to model the signal propagation in DF-CT and established the link between system parameters and the CNR metric.</p>\n </section>\n \n <section>\n \n <h3> Results</h3>\n \n <p>We showed that for a DF-CT system, its CNR first increases and then decreases with the system auto-correlation length (ACL). The optimal ACL is mostly independent of system's visibility, and is only related to the phantom's properties, that is, its size and absorption. For our phantom, the optimal ACL is about 0.35 µm at the design energy of 60 keV. As for system geometry, increasing source-detector and isocenter-detector distance can extend the system's maximal ACL, making it easier for the system to meet the optimal ACL and relaxing the grating pitches. We proposed a set of parameters for a projective fringe system that can satisfy the simulated optimal ACL.</p>\n </section>\n \n <section>\n \n <h3> Conclusion</h3>\n \n <p>This study introduced a task-based metric and a process for DF-CT optimization. We demonstrated that for a given phantom, the detection performance of the system is optimized at a specific ACL. The optimization method and design principles are independent from the underlying dark-field imaging method and can be applied to DF-CT system design using different grating-based implementations such as Talbot-Lau interferometer (TLI) or projective fringe method.</p>\n </section>\n </div>","PeriodicalId":18384,"journal":{"name":"Medical physics","volume":"52 4","pages":"2155-2166"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimization of x-ray dark-field CT for human-scale lung imaging\",\"authors\":\"Peiyuan Guo, Simon Spindler, Michal Rawlik, Jincheng Lu, Longchao Men, Mingzhi Hong, Marco Stampanoni, Hongxia Yin, Yan Xu, Zhenchang Wang, Li Zhang, Zhentian Wang\",\"doi\":\"10.1002/mp.17630\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Background</h3>\\n \\n <p>X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Purpose</h3>\\n \\n <p>This study aimed to develop a thorough optimization method for human-scale dark-field lung CT and guide the system design.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Methods</h3>\\n \\n <p>We introduced a task-based metric formulated as the contrast-to-noise ratio (CNR) between normal and lesioned alveoli for system parameter optimization and designed a digital human-thorax phantom to fit the task of lung disease detection. Furthermore, a computational framework was developed to model the signal propagation in DF-CT and established the link between system parameters and the CNR metric.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Results</h3>\\n \\n <p>We showed that for a DF-CT system, its CNR first increases and then decreases with the system auto-correlation length (ACL). The optimal ACL is mostly independent of system's visibility, and is only related to the phantom's properties, that is, its size and absorption. For our phantom, the optimal ACL is about 0.35 µm at the design energy of 60 keV. As for system geometry, increasing source-detector and isocenter-detector distance can extend the system's maximal ACL, making it easier for the system to meet the optimal ACL and relaxing the grating pitches. 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Optimization of x-ray dark-field CT for human-scale lung imaging
Background
X-ray grating-based dark-field imaging can sense the small angle scattering caused by object's micro-structures. This technique is sensitive to the porous microstructure of lung alveoli and has the potential to detect lung diseases at an early stage. Up to now, a human-scale dark-field CT (DF-CT) prototype has been built for lung imaging.
Purpose
This study aimed to develop a thorough optimization method for human-scale dark-field lung CT and guide the system design.
Methods
We introduced a task-based metric formulated as the contrast-to-noise ratio (CNR) between normal and lesioned alveoli for system parameter optimization and designed a digital human-thorax phantom to fit the task of lung disease detection. Furthermore, a computational framework was developed to model the signal propagation in DF-CT and established the link between system parameters and the CNR metric.
Results
We showed that for a DF-CT system, its CNR first increases and then decreases with the system auto-correlation length (ACL). The optimal ACL is mostly independent of system's visibility, and is only related to the phantom's properties, that is, its size and absorption. For our phantom, the optimal ACL is about 0.35 µm at the design energy of 60 keV. As for system geometry, increasing source-detector and isocenter-detector distance can extend the system's maximal ACL, making it easier for the system to meet the optimal ACL and relaxing the grating pitches. We proposed a set of parameters for a projective fringe system that can satisfy the simulated optimal ACL.
Conclusion
This study introduced a task-based metric and a process for DF-CT optimization. We demonstrated that for a given phantom, the detection performance of the system is optimized at a specific ACL. The optimization method and design principles are independent from the underlying dark-field imaging method and can be applied to DF-CT system design using different grating-based implementations such as Talbot-Lau interferometer (TLI) or projective fringe method.
期刊介绍：
Medical Physics publishes original, high impact physics, imaging science, and engineering research that advances patient diagnosis and therapy through contributions in 1) Basic science developments with high potential for clinical translation 2) Clinical applications of cutting edge engineering and physics innovations 3) Broadly applicable and innovative clinical physics developments
Medical Physics is a journal of global scope and reach. By publishing in Medical Physics your research will reach an international, multidisciplinary audience including practicing medical physicists as well as physics- and engineering based translational scientists. We work closely with authors of promising articles to improve their quality.
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